Zahori

[Morgan]

Hi Morgan
As I know , mini zahori is broadband receiver without tuning section .I think energy filed is electrostatic and electrostatic field without radiating as frequency , I remember you said long buried metals produced electromagnetic field, so how much frequency emitted for example from gold? Silver ? copper?
Best regards.

the electromagnetic field emited by treasure can produce also electrostatic and ionic field,this are things we are trying to understand.

[Morgan]

As I side it is sensitive broadband detector without tuning , if add tuning section
Then rejected radio station , but maybe reject also target signals .
Best regards.

i dont think so,two people already found someting with this antenna ,and they not talk about radio waves,becouse they use pot 22k connect L1. So we just need some solution to avoid some RF in zahori full power.


Regards

[J_Player]

the electromagnetic field emited by treasure can produce also electrostatic and ionic field,this are things we are trying to understand.Hi Morgan,
A buried treasure does not emit an electromagnetic field of any strength.

The buried treasure corrodes in the ground, and ions from the metal surface enter into the soil. The chemical action between the soil and the metal causes a voltage and can increase the conductivity of the ground. The voltage is not high electrostatic. it is usually less than 1 volt, but is always less than 2 volts. The chemistry will not allow the ions to produce a higher voltage from natural corrosion. There is no high energy coming from the treasure.

The only source of high strength electromagnetic or electrostatic field is from the atmosphere and the telluric currents which are produced as a result. The way you find treasure is speculated to be caused by the change in ground conductivity in the area where a treasure is corroding. The flow of electrons from the earth to the sky is very small, but the electric field that pushes these electrons is very large. It is speculated that a small difference in ground conductivity caused by a buried treasure will cause large differences in the electric field in the air above it.

This does not mean there are treasure ions in the air above the treasure. We know this is not possible. But it is very possible that the electric field gradient will be less in this air above the more conductive ground. And this is the kind of anomaly you are looking for.

So you see you make a mistake if you think the treasure is emitting electromagnetic and ionic fields. These are false theories that people made up to try to explain why they find signals in the air. The only real electrostatic in the air comes from the atmospheric charge. And the only detectable anomaly near a treasure is an anomaly which could disturb the atmospheric charge gradient. Look for a place where the air is not 200 volts charge at the height that you hold your Zahori. You should see lower voltage where the treasure is buried.

Good luck with your Zahori :)
Best wishes,
J_P

[Morgan]

Hi Morgan,
A buried treasure does not emit an electromagnetic field of any strength.

The buried treasure corrodes in the ground, and ions from the metal surface enter into the soil. The chemical action between the soil and the metal causes a voltage and can increase the conductivity of the ground. The voltage is not high electrostatic. it is usually less than 1 volt, but is always less than 2 volts. The chemistry will not allow the ions to produce a higher voltage from natural corrosion. There is no high energy coming from the treasure.

The only source of high strength electromagnetic or electrostatic field is from the atmosphere and the telluric currents which are produced as a result. The way you find treasure is speculated to be caused by the change in ground conductivity in the area where a treasure is corroding. The flow of electrons from the earth to the sky is very small, but the electric field that pushes these electrons is very large. It is speculated that a small difference in ground conductivity caused by a buried treasure will cause large differences in the electric field in the air above it.

This does not mean there are treasure ions in the air above the treasure. We know this is not possible. But it is very possible that the electric field gradient will be less in this air above the more conductive ground. And this is the kind of anomaly you are looking for.

So you see you make a mistake if you think the treasure is emitting electromagnetic and ionic fields. These are false theories that people made up to try to explain why they find signals in the air. The only real electrostatic in the air comes from the atmospheric charge. And the only detectable anomaly near a treasure is an anomaly which could disturb the atmospheric charge gradient. Look for a place where the air is not 200 volts charge at the height that you hold your Zahori. You should see lower voltage where the treasure is buried.

Good luck with your Zahori :)
Best wishes,
J_P

Hi J_P

The mini Zahori is only experiments,of course i have the PD,but i want to see also some results with Zahori.

Thanks for the explanations,i imagine the air voltage is higer over buried treasures...

Regards

[aft_72005]

Hi Morgan,
A buried treasure does not emit an electromagnetic field of any strength.

The buried treasure corrodes in the ground, and ions from the metal surface enter into the soil. The chemical action between the soil and the metal causes a voltage and can increase the conductivity of the ground. The voltage is not high electrostatic. it is usually less than 1 volt, but is always less than 2 volts. The chemistry will not allow the ions to produce a higher voltage from natural corrosion. There is no high energy coming from the treasure.

The only source of high strength electromagnetic or electrostatic field is from the atmosphere and the telluric currents which are produced as a result. The way you find treasure is speculated to be caused by the change in ground conductivity in the area where a treasure is corroding. The flow of electrons from the earth to the sky is very small, but the electric field that pushes these electrons is very large. It is speculated that a small difference in ground conductivity caused by a buried treasure will cause large differences in the electric field in the air above it.

This does not mean there are treasure ions in the air above the treasure. We know this is not possible. But it is very possible that the electric field gradient will be less in this air above the more conductive ground. And this is the kind of anomaly you are looking for.

So you see you make a mistake if you think the treasure is emitting electromagnetic and ionic fields. These are false theories that people made up to try to explain why they find signals in the air. The only real electrostatic in the air comes from the atmospheric charge. And the only detectable anomaly near a treasure is an anomaly which could disturb the atmospheric charge gradient. Look for a place where the air is not 200 volts charge at the height that you hold your Zahori. You should see lower voltage where the treasure is buried.

Good luck with your Zahori :)
Best wishes,
J_P




Hi J_Player
Yes, for most metals this voltage under 2 volt . For example ,underground
gas pips protection system used this method.
Are you sure long range base on this subject ?
I remember minoro animation
Best regards.

[Rudy]

Hi Morgan,
A buried treasure does not emit an electromagnetic field of any strength.

The buried treasure corrodes in the ground, and ions from the metal surface enter into the soil. The chemical action between the soil and the metal causes a voltage and can increase the conductivity of the ground. The voltage is not high electrostatic. it is usually less than 1 volt, but is always less than 2 volts. The chemistry will not allow the ions to produce a higher voltage from natural corrosion. There is no high energy coming from the treasure.

The only source of high strength electromagnetic or electrostatic field is from the atmosphere and the telluric currents which are produced as a result. The way you find treasure is speculated to be caused by the change in ground conductivity in the area where a treasure is corroding. The flow of electrons from the earth to the sky is very small, but the electric field that pushes these electrons is very large. It is speculated that a small difference in ground conductivity caused by a buried treasure will cause large differences in the electric field in the air above it.

This does not mean there are treasure ions in the air above the treasure. We know this is not possible. But it is very possible that the electric field gradient will be less in this air above the more conductive ground. And this is the kind of anomaly you are looking for.

So you see you make a mistake if you think the treasure is emitting electromagnetic and ionic fields. These are false theories that people made up to try to explain why they find signals in the air. The only real electrostatic in the air comes from the atmospheric charge. And the only detectable anomaly near a treasure is an anomaly which could disturb the atmospheric charge gradient. Look for a place where the air is not 200 volts charge at the height that you hold your Zahori. You should see lower voltage where the treasure is buried.

Good luck with your Zahori :)
Best wishes,
J_P

Hi JP,

Interesting. I think one needs to look at this effect from two different points of view. A "passive" instrument, like a Zahori; and an "active" system that uses rods driven into the ground and pass an electric current into the ground.

In your explanation above, I personally can't see how a large electric field gradient is maintained over the buried treasure.

[J_Player]

Hi J_Player
Yes, for most metals this voltage under 2 volt . For example ,underground
gas pips protection system used this method.
Are you sure long range base on this subject ?
I remember minoro animation
Best regards. Hi Aft,
Yes I am sure.
As an engineer you know it is impossible for buried metal to build strong electrostatic field which can be measured. Any large electrical potential from buried metal is quickly shorted and dissipated in the ground. The most voltage a buried metal can develop is not a high static field. It is usually less than 2 volts, caused by the chemical reaction of corrosion. It is the same as if you buried a battery in the ground. This battery would show maybe 1.5 volts for awhile, but you could not measure this 1.5 volts as a strong electrostatic field from any distance.

The electrostatic field you can build in your body is quickly discharged and dissipated the moment you youch your body to the ground. It is the same for buried metal. Buried metal does not accumulate any large static charge. But if it did, then the ground in contact would dissipate it so it no longer exists.

The Mineoro propaganda has been shown to be false by scientists and technicians who measured the content of the air in different conditions. They found that gold ions do not exist in the air. Any ionized gold will quickly combine to make a gold particle. All of the gold floating in the air has been found to be solid gold particles, not ions. Chemists have seen that Mineoro propaganda is correct for gold ions moving up through the ground above treasure. But they saw that all these ions are neutralized in the last 10-30 cm before they reach the surface. This is where the gold ions combine to become tiny gold particles where they can attach to other gold particles and form micro gold dust. This dust can wash into the oceans or blow into the wind to become an extremely small concentration of gold particles. Gold recovery companies determined that it is much too expensive to build equipment to recover the gold from the oceans or from the air. They continue to look for larger concentrations that are found in deposits under the ground.

The entire Mineoro theory of gold ions floating in the air has been demonstrated to be wrong. You can also prove this is wrong for yourself by taking a drift tube ion detector near where you know there is buried gold. You will see the drift tube does not find any gold ions anywhere in the air near the buried gold or away from it.

The gold cannot cause any static electric field more than 1-2 volts depending on what other elements are near the corroding gold in the ground. This voltage is not easy to measure from the surface unless you are using probes like are used for ground resistivity. If you measure some voltage with this kind of probe, you may be measuring the gold chemical reacition voltage. But this is not likely because the gold ions are in very small concentration (around 3 parts per trillion), so any voltage is quickly lost in the when begin to collect some its current to measure it. But there are other metal ions in larger amounts which are easier to measure like copper, zinc, lead, iron, and others. These will be much more plentiful and are more likely to show some measureable voltage. And even then you cannot be sure you are measuring voltage caused by chemical corrosion. There are even stronger voltages caused by the telluric currents moving under the ground. These telluric currents can actually be used as a power source for low voltages. In the days before telephones, telluric currents sometimes powered the telegraph lines which used a single conductor, and a ground rod for the return path.

But back to LRL theories, ions could be involved because we know there are trace amounts of gold ions corroding into the soil and moving upward in a column. And electrostatics could be involved because we know there is a 100v/meter voltage gradient above in the air above the ground. We also know electrons are leaking from the ground into the air, driven by the force of this electric field gradient. Will this field gradient become changed above an area of more conductive, ionized soil where treasure is buried? You tell me... you are an EE. We have many choices for real physical phenomenon to develop a true explanation, but the buried gold emitting ions into the air and generating large electric fields from under the ground is not one of these possible explanations.

Don't take my word for it. Test the air above some buried gold and see for yourself if there are any gold ions floating around there. Also put some probes in the ground near the buried gold to see if you can measure any strong electrostatic fields under the ground.

Best wishes, :)
J_P

[J_Player]

Hi JP,

Interesting. I think one needs to look at this effect from two different points of view. A "passive" instrument, like a Zahori; and an "active" system that uses rods driven into the ground and pass an electric current into the ground.

In your explanation above, I personally can't see how a large electric field gradient is maintained over the buried treasure.Hi Rudy,

You are correct. An instrument which stimulates the target area will necessarily work diffrently than a passive instrument which measures only natural state signals. As an example, a conventional metal detector measures signals that don't exist naturally in any measureable amound from the buried metal. A passive detector in the case of buried metal is looking for a much smaller signal which is more likely to be buried in noise, and more difficult to find. This means you would need to make an exhaustive search to find the most likely kind of signal that will be strong enough to measure.

The most likely candidate for a passive signal seems to be the atmospheric air charge. Everything else is tiny in comparison. As far as a large electric field gradient, this is the standard gradient in the air, driven by solar wind at the ionosphere. It varies from day to night, and from season to season, and even has local variations. But it usually falls in the range of 100-200 volts per meter altitude in the vicinity of the earth surface. See here for my previous discussion of this: http://www.geotech1.com/forums/showthread.php?p=126688#post126688

The current leaking into the air is typically around 11.76 nA leaking from any 1 sq meter of earth surface on average. Of course we can't measure this current with any normal kind of milliammeter, but we can expect it will change to maybe double if the conductivity of the ground is caused to change to double the amount in found neighboring areas. The theory is that chemical reactions of corroding buried metals will change the conductivity of the ground to become higher than ground with no chemical activity involving metal corrosion. When this happens, we could expect the 100 v/meter gradient to be reduced in this local area of higher ground conductivity and higher current leaking into the air. This reduced voltage gradient should be easier to measure because it is in a range where we have instruments that can measure it.

The only problem I have with this theory is I haven't seen any field data to support it. It would be interesting to see some actual tests that show the field gradient over uniform ground that has places where a conductivity/resistivity anomaly is created in the soil. In a test condition, the conductive soil area can be made by simply pouring water into a small hole and giving it time to absorb into the soil. Or maybe by driving a long metal rod into the ground to conduct to the lower layers, then pouring a bucket of water on the top surface.

I am suspecting that if a zahori is very sensitive to electric field variations it will detect this variation in gradient. Of course, the same variation in gradient could be caused by a damp spot in the soil where an animal recently visited. This could result in finding a questionable treasure. :eek:

Best wishes,
J_P

[aft_72005]

Don't take my word for it. Test the air above some buried gold and see for yourself if there are any gold ions floating around there. Also put some probes in the ground near the buried gold to see if you can measure any strong electrostatic fields under the ground.

Thanks for good preamble :), and big problem is don’t have experimental gold
Target . I am not treasure hunter ,but interesting to philosophy of long buried
Metals .
Best regards.

[aft_72005]

J_Player
What is your opinion about moving conductive air over ground ?
I heard travel from south to north ,
Best regards.

[J_Player]

J_Player
....big problem is don’t have experimental gold
Target....

What is your opinion about moving conductive air over ground ?
I heard travel from south to north ,
Best regards.
Hi Aft,
A gold target is easy. You can use any piece of gold jewelry and bury it. Or you can bury an old circuit board or component that has gold plating on the conductors. This will be more than enough to make as many ions as a solid gold item for test purposes. If you want to make gold ions, you can put the gold plated item into a dish with some aqua regia, or some cyanide solution to dissolve it. Then you will have a dish of gold ions that you can dump into a bucket of soil. Then you can stand above this bucket of soil with gold ions and check to see if there are any gold ions floating in the air. You could also check the theory for other buried metals. It is easy to bury copper, silver, lead, iron, zinc and any other metal you can find (These can be dissolved with less dangerous chemicals like muriatic acid and suphuric acid). Then measure the air above the buried metal to see if you can find some metal ions floating above them. If you know where there is a buried pipe, then you already have a long time buried metal place to test.

My understanding is that the south to north detection is related to the magnetic field of the earth, not the conductivity of the air. For example, a compass will respond to a magnetic field. But the compass does not respond to the conductivity of the air. In the case of an electric charge detector that is being used to check the charge in the air, more conductive air is air which has higher humidity. I would expect that the current flow leaking from the earth to the atmosphere is more in areas of high humidity than dry areas. All this can change in weather systems where the local air charge can change to become more or less, or even reversed for short times. The only reason I would think south and north has some influence on air conductivity is if you are in an area where the wind currents travel from south to north to blow in air that has a different conductivity. I know of no magnetic component that can be measured when checking the electric charge of normal air, no matter what its conductivity is. Possibly in rare circumstances like during a storm, the air could be come much more conductive in certain paths and directions. This is generally what happens when lightning strikes. I doubt most treasure hunters would go hunting during these times, so I figure they are not seen much when treasure hunting.

Best wishes, :)
J_P

[Rudy]

Hi Rudy,

You are correct. An instrument which stimulates the target area will necessarily work diffrently than a passive instrument which measures only natural state signals. As an example, a conventional metal detector measures signals that don't exist naturally in any measureable amound from the buried metal. A passive detector in the case of buried metal is looking for a much smaller signal which is more likely to be buried in noise, and more difficult to find. This means you would need to make an exhaustive search to find the most likely kind of signal that will be strong enough to measure.

The most likely candidate for a passive signal seems to be the atmospheric air charge. Everything else is tiny in comparison. As far as a large electric field gradient, this is the standard gradient in the air, driven by solar wind at the ionosphere. It varies from day to night, and from season to season, and even has local variations. But it usually falls in the range of 100-200 volts per meter altitude in the vicinity of the earth surface. See here for my previous discussion of this: http://www.geotech1.com/forums/showthread.php?p=126688#post126688

The current leaking into the air is typically around 11.76 nA leaking from any 1 sq meter of earth surface on average. Of course we can't measure this current with any normal kind of milliammeter, but we can expect it will change to maybe double if the conductivity of the ground is caused to change to double the amount in found neighboring areas. The theory is that chemical reactions of corroding buried metals will change the conductivity of the ground to become higher than ground with no chemical activity involving metal corrosion. When this happens, we could expect the 100 v/meter gradient to be reduced in this local area of higher ground conductivity and higher current leaking into the air. This reduced voltage gradient should be easier to measure because it is in a range where we have instruments that can measure it.

The only problem I have with this theory is I haven't seen any field data to support it. It would be interesting to see some actual tests that show the field gradient over uniform ground that has places where a conductivity/resistivity anomaly is created in the soil. In a test condition, the conductive soil area can be made by simply pouring water into a small hole and giving it time to absorb into the soil. Or maybe by driving a long metal rod into the ground to conduct to the lower layers, then pouring a bucket of water on the top surface.

I am suspecting that if a zahori is very sensitive to electric field variations it will detect this variation in gradient. Of course, the same variation in gradient could be caused by a damp spot in the soil where an animal recently visited. This could result in finding a questionable treasure. :eek:

Best wishes,
J_P

Hmm, interesting. I would surmise that during normal weather (not a thunder storm), the source resistance for this 200V/m electric field must be very high since the air molecules are mostly not ionized and the air therefore acts as a dielectric medium.

The presence of the human hunter must then have a significant effect on the electric field in his immediate surrounding, given his relatively low resistance, specially on a hot humid day. One can model the human resistance roughly as an outer resistance and an internal body resistance, where the skin resistance is of the order of 2,000Ω or less if sweaty, and the internal body resistance on the order of 500Ω. The resistance to ground (forgetting shoes for the moment) is then:

Rbody = Rskin(in) + Rinternal + Rskin(out)

Since we get from the external skin to the lower resistance internal organs and back to the external skin.

So Rbody ~4.5 KΩ maybe less if sweaty.

Assuming a 2 meter height for the human, We would effectively have 400 V from head to feet and Ohm's law would say that we'd have almost 90 mA of current flowing through us, a lethal amount.

Of course, we won't die because the source impedance behind that electric field is so high that it can't provide that kind of current. But, wouldn't our mere presence be sufficient to collapse that electric field in our vicinity?

[J_Player]

Hmm, interesting. I would surmise that during normal weather (not a thunder storm), the source resistance for this 200V/m electric field must be very high since the air molecules are mostly not ionized and the air therefore acts as a dielectric medium.

The presence of the human hunter must then have a significant effect on the electric field in his immediate surrounding, given his relatively low resistance, specially on a hot humid day. One can model the human resistance roughly as an outer resistance and an internal body resistance, where the skin resistance is of the order of 2,000Ω or less if sweaty, and the internal body resistance on the order of 500Ω. The resistance to ground (forgetting shoes for the moment) is then:

Rbody = Rskin(in) + Rinternal + Rskin(out)

Since we get from the external skin to the lower resistance internal organs and back to the external skin.

So Rbody ~4.5 KΩ maybe less if sweaty.

Assuming a 2 meter height for the human, We would effectively have 400 V from head to feet and Ohm's law would say that we'd have almost 90 mA of current flowing through us, a lethal amount.

Of course, we won't die because the source impedance behind that electric field is so high that it can't provide that kind of current. But, wouldn't our mere presence be sufficient to collapse that electric field in our vicinity? Hi Rudy,
Yes the air is considered one of the best insulators and a dielectric which basically makes the earth a capacitor with an opposite pole at the ionosphere.
When we consider the resistance of a person internally and externally, and even the resistance of his shoes, this resistance becomes a moot point because of the tiny amount of current that is flowing through the resistance of the air. The amount of current which normally leaks through the air is only around in the area he occupies is around 1 nA, which would quicly move from the ground through a person;s body before it met any noticable resistance that could develop a potential in his body. At this current level, the person (including most ordinary shoes he would be wearing) basically acts like a conductor, which raises the ground potential to his level. This is especially true on humid days. If we are talking about a very dry day where a person walks across a carpet to generate a sizable charge, then he could build up thousands of volts. A lot more than 1 nA will be leaking from him into the atmosphere in this condition. But without generating a charge by this method, only a tiny trickle of 1 nA will charge a person, that would require better insulating value than the air to keep from seeing him as a conductor and preferred path to the ground. Also consider that simply by being there, the person may double or triple the leakage current to 2-3nA in the surface area he occupies. However, in this same area, he has caused the voltage gradient to make an enormous anomaly where it dropped from 200v to 0v! ... Why it is better to measure anomalies in the voltage gradient.

Another way of looking at it is a person standing on the ground (or plant, or any other partially conductive object) will raise the ground potential from the ground up to the level of their body. In essence, a person will distort the ground potential by simply being there. By standing on the ground, we have created the effect of a small hill shape on the ground to raise the ground potential to a higher altitude. Thus, we are not standing in a 100-200 volt/meter gradient because our body caused the gradient to drop much lower, nearly to ground potential along the full height of our body. This may be easier to understand when you consider a vertical cliff maybe 100 meters tall. We will se ground potential at its base and at the top, as well as all along the face of this cliff. We can expect the vertical voltage gradient of 100-200 volts/meter to be distorted to a horizontal gradient when measuring it at the face of the cliff. This distortion will be expected to gradually return to the normal vertical gradient as we move away from the cliff.
You can see an illustration of this from the Dr. Feynman's book of his physics lectures Vol 2 chapter 9 -- online copy of this page here: http://student.fizika.org/~jsisko/Knjige/Opca%20Fizika/Feynman%20Lectures%20on%20Physics/Vol%202%20Ch%2009%20-%20Electricity%20in%20the%20Atmosphere.pdf
Anything on the ground is basically a lightning rod/grounding rod unless it's resistance is somewhere close to the resistance of the air. And this is a fortunate state of affairs because it prevents people from inadvertently dying due to electric shock from accumulated atmospheric charge in non-storm conditions.

But as a final thought, When we consider the big influence of everything from trees, people, hills, wild animals, lakes and streams in influencing the atmospheric voltage gradient, it seems more likely that a more conductive area of ground could have a significant effect on the gradient.

Best wishes,
J_P

[Rudy]

Hi Rudy,
Yes the air is considered one of the best insulators and a dielectric which basically makes the earth a capacitor with an opposite pole at the ionosphere.
When we consider the resistance of a person internally and externally, and even the resistance of his shoes, this resistance becomes a moot point because of the tiny amount of current that is flowing through the resistance of the air. The amount of current which normally leaks through the air is only around in the area he occupies is around 1 nA, which would quicly move from the ground through a person;s body before it met any noticable resistance that could develop a potential in his body. At this current level, the person (including most ordinary shoes he would be wearing) basically acts like a conductor, which raises the ground potential to his level. This is especially true on humid days. If we are talking about a very dry day where a person walks across a carpet to generate a sizable charge, then he could build up thousands of volts. A lot more than 1 nA will be leaking from him into the atmosphere in this condition. But without generating a charge by this method, only a tiny trickle of 1 nA will charge a person, that would require better insulating value than the air to keep from seeing him as a conductor and preferred path to the ground. Also consider that simply by being there, the person may double or triple the leakage current to 2-3nA in the surface area he occupies. However, in this same area, he has caused the voltage gradient to make an enormous anomaly where it dropped from 200v to 0v! ... Why it is better to measure anomalies in the voltage gradient.

Another way of looking at it is a person standing on the ground (or plant, or any other partially conductive object) will raise the ground potential from the ground up to the level of their body. In essence, a person will distort the ground potential by simply being there. By standing on the ground, we have created the effect of a small hill shape on the ground to raise the ground potential to a higher altitude. Thus, we are not standing in a 100-200 volt/meter gradient because our body caused the gradient to drop much lower, nearly to ground potential along the full height of our body. This may be easier to understand when you consider a vertical cliff maybe 100 meters tall. We will se ground potential at its base and at the top, as well as all along the face of this cliff. We can expect the vertical voltage gradient of 100-200 volts/meter to be distorted to a horizontal gradient when measuring it at the face of the cliff. This distortion will be expected to gradually return to the normal vertical gradient as we move away from the cliff.
You can see an illustration of this from the Dr. Feynman's book of his physics lectures Vol 2 chapter 9 -- online copy of this page here: http://student.fizika.org/~jsisko/Knjige/Opca%20Fizika/Feynman%20Lectures%20on%20Physics/Vol%202%20Ch%2009%20-%20Electricity%20in%20the%20Atmosphere.pdf
Anything on the ground is basically a lightning rod/grounding rod unless it's resistance is somewhere close to the resistance of the air. And this is a fortunate state of affairs because it prevents people from inadvertently dying due to electric shock from accumulated atmospheric charge in non-storm conditions.

But as a final thought, When we consider the big influence of everything from trees, people, hills, wild animals, lakes and streams in influencing the atmospheric voltage gradient, it seems more likely that a more conductive area of ground could have a significant effect on the gradient.

Best wishes,
J_P

Hi JP,

Thanks, I think you said what I was trying to say much better. The implication is that a person standing in the field holding an electric field meter of some kind, is dramatically distorting the field the meter is reading and the distortion moves with the man/meter apparatus wherever they go. Hmm.

BTW: I had the pleasure of meeting Dr. Feynman back in the late sixties when he paid a visit to the company I was then working at. I was most impressed with his wit and demeanor.

[J_Player]

Hi JP,

Thanks, I think you said what I was trying to say much better. The implication is that a person standing in the field holding an electric field meter of some kind, is dramatically distorting the field the meter is reading and the distortion moves with the man/meter apparatus wherever they go. Hmm.

BTW: I had the pleasure of meeting Dr. Feynman back in the late sixties when he paid a visit to the company I was then working at. I was most impressed with his wit and demeanor.Ya he taught classes in Pasadena about real science, not a bunch of made up stuff that seemed like it might be true.

About the electric field meter... some LRL enthusiasts such as Esteban say it is important to wear cotton clothing when using an LRL that works by sensing faint electric fields. This is so as not to develop a charge which could be seen as noise to a sensitive meter. Also, the typical LRL is held out in front of you hopefully at the periphery of whatever you are doing to the field. The presumption is the meter is looking through a fairly constant window of a gradient (your body gradient) to the distant charge anomalies that they try to detect. As long as your body charge gradient is not varying, it should not skew the reading, but simply raise the noise floor a little. We know a zahori detects something because it picks up electric power transmission lines from a very large distance. In the best of conditions, maybe it can detect nearby anomalies in the space charge. What I keep thinking is the influence of variations in the ground water will have a larger influence on the charge anomalies than traces of treasure ionization in the soil. This is why I think it is more suited to finding water.

Best wishes,
J_P

[Rudy]

Ya he taught classes in Pasadena about real science, not a bunch of made up stuff that seemed like it might be true.

About the electric field meter... some LRL enthusiasts such as Esteban say it is important to wear cotton clothing when using an LRL that works by sensing faint electric fields. This is so as not to develop a charge which could be seen as noise to a sensitive meter. Also, the typical LRL is held out in front of you hopefully at the periphery of whatever you are doing to the field. The presumption is the meter is looking through a fairly constant window of a gradient (your body gradient) to the distant charge anomalies that they try to detect. As long as your body charge gradient is not varying, it should not skew the reading, but simply raise the noise floor a little. We know a zahori detects something because it picks up electric power transmission lines from a very large distance. In the best of conditions, maybe it can detect nearby anomalies in the space charge. What I keep thinking is the influence of variations in the ground water will have a larger influence on the charge anomalies than traces of treasure ionization in the soil. This is why I think it is more suited to finding water.

Best wishes,
J_P

The power line electric fields are time varying, not static. Maybe that is why it is picking them up, dE/dt.

[J_Player]

The power line electric fields are time varying, not static. Maybe that is why it is picking them up, dE/dt.Yes,

About that power line thing.... The original circuit for the zahori had a 4066 switch that was used as an input signal chopper set to 60 hz or to 50 Hz in Europe to filter out the power lines so you could concentrate on earth signals (es1, es2, es3 and 7555 below). It seemed a novel way to filter in a pseudo-digital manner, which also reset the input by unloading it, then sending a fresh ambient signal at each cycle. I suppose this kept the antenna from becoming overloaded with air charges. You could also tune this 50/60 hz for a beat frequency and concievably operate it as a BFO to see if any local anomalies will cause the internal clock to drift and make an audible sound. The original article published with the zahori circuit described it as an "electronic water witch". And it seems like it may actually work for that purpose, considering the known facts about local atmospheric field anomalies. Also note an early antenna mod changed to three extra long antennas which are extended to protrude nearly 3 meters beyond the person holding it when you consider his arm as part of the assembly. This was probably intended to move the sensor part away from the field distortions caused by the user.

But most zahori builders removed this line-power filter function from thier zahori when they bagan hacking it. Today's versions are simply FET charge detectors which may have various antenna schemes to replace the original, and small pieces of gold soldered into the antenna -- a strange arrangement. But hey, if someone finds treasure with it, why not? It's not like they paid 5000 eu for these experimental LRLs.

What most experimenter never noticed about the original design is it contains an interesting feature which could be exploited. Suppose you were to synchronize the chopper circuit with the local power line fields, using a feedback loop or a PLL to track the line frequency. You now have essentially a signal sync circuit similar to an oscilloscope trigger. You can examine a repeating wave for an anomaly when pointing the zahori in a particular direction. If you have instruments available to examine the input signal, you can also add some circuits to further filter known repeaitng noise, and leave you with a cleaner earth signal. From here, you can look to see if you can find any "treasure signal" that comes when you pointi to long-time buried gold, for example. Your additional filtering could easily take adjustable time duration slices of each repeating 50/60 Hz wave to examine a part where you found something interesting. This could be a worthwhile electronic adventure if the buried treasure is somehow stimulated by man-made noise to emit a signal that can be detected. If the theories of LRL enthusuasts are correct, then this would be a good way to isolate this elusive gold signal and build a magic zahori to find only gold at long range. If it didn't work, then maybe it would still be good to tell when you are close to ground water that is near the surface. :D

Best wishes,
J_P

http://www.geotech1.com/forums/attachment.php?attachmentid=720&stc=1&d=1148598254

[mehdi]

Hi
report of some field test for mini zahori!:
i use AL wire as antenna, not big difrence in performance;
i removed the brass sample, and L2, now it work better than before!
yesterday it can detect a hole at about 1meter underground at distance of about 2-3 meter but there was not treasure.

mehdi

[Morgan]

Hi
report of some field test for mini zahori!:
i use AL wire as antenna, not big difrence in performance;
i removed the brass sample, and L2, now it work better than before!
yesterday it can detect a hole at about 1meter underground at distance of about 2-3 meter but there was not treasure.

mehdi

So,now it work worse than before,becouse before you found one coin and now with modifications you found one empty hole...

[nelson]

Hi Mehdi and all friends.
Last weekend i made a short test with mini zahorie. The detector mades a tac tac tac on one direction, so i tryied to pinpoint the signal that was a small area of about 50 by 50 centimiters. Then i took my metal detector and yes, it detected a signal, that after i dig it was just a small aluminium foil.
Perhaps it wasn´t a treasure, but i must said that for me it worked in detecting that aluminium foil at a distance of 1 meter. I thing this is a good startting point at least for me.
I m waitting for this weekend to try it again.
Regards
Nelson


Hi
report of some field test for mini zahori!:
i use AL wire as antenna, not big difrence in performance;
i removed the brass sample, and L2, now it work better than before!
yesterday it can detect a hole at about 1meter underground at distance of about 2-3 meter but there was not treasure.

mehdi

[Qiaozhi]

Hi Mehdi and all friends.
Last weekend i made a short test with mini zahorie. The detector mades a tac tac tac on one direction, so i tryied to pinpoint the signal that was a small area of about 50 by 50 centimiters. Then i took my metal detector and yes, it detected a signal, that after i dig it was just a small aluminium foil.
Perhaps it wasn´t a treasure, but i must said that for me it worked in detecting that aluminium foil at a distance of 1 meter. I thing this is a good startting point at least for me.
I m waitting for this weekend to try it again.
Regards
Nelson
A suggestion for next time:
After digging the target found with the metal detector, recheck the area again with the Zahori to see if the signal is still there or if it has disappeared.
Also, check the rest of the site with the metal detector. The results of these tests will no doubt be most illuminating.

[aft_72005]

A suggestion for next time:
After digging the target found with the metal detector, recheck the area again with the Zahori to see if the signal is still there or if it has disappeared.
Also, check the rest of the site with the metal detector. The results of these tests will no doubt be most illuminating.

Hi to all
If for first time detection done with zahori ,then check aria with metal detector,
Using again zahori at seem area after metal detector will be without result,
Because metal detector transmitter section destroyed phenomenon energy!!!!!!
Best regards.

[aft_72005]

Hi
report of some field test for mini zahori!:
i use AL wire as antenna, not big difrence in performance;
i removed the brass sample, and L2, now it work better than before!
yesterday it can detect a hole at about 1meter underground at distance of about 2-3 meter but there was not treasure.

mehdi


Hi mehdi
Detected hole!!!!!!!!!!
Maybe Your zahori so sensitive now , in this condition you have noise from unwanted Subject

[J_Player]

Hi to all
If for first time detection done with zahori ,then check aria with metal detector,
Using again zahori at seem area after metal detector will be without result,
Because metal detector transmitter section destroyed phenomenon energy!!!!!!
Best regards. Hi Aft,

Nobody has ever established that a phenomenon has energy.
This is simply a legend experimenters began to believe when they hear stories of LRLs beeping in the direction of buried metal.
We also see the geologist VLF receivers make different strength readings when they move them to different places at the ground surface.
Some of these changes can also be caused by metal things buried for a long time.
But we know they are not measuring energy coming from the metal of a phenomenon.
They are measuring how much RF is absorbed into the ground, which tells them variations in the ground conductivity.

Geologists also can detect metal particles in the ground by using induced polarization and spectral induced polarization to find various different metals buried for a long time. They know for certain they are not measuring any energy emitted from buried metal when using these methods. They know for certain they are measuring properties of the metal and the ground it is buried in, not energy emitted from the metal or any energy-emitting phenomenon.

When we hear a signal coming from a static charge detector, we have no way to know if the charge variation we are measuring was caused by energy emitted, or a static charge accumulated, or a cloud of charged particles in the air near where the antenna is held. If we find buried metal, then this does not tell us the metal or the ground emitted energy. It only tells us we measured a change in the charge in the air above where the metal is buried. Until you make some experiments with instruments, you can't even know if the change in the air charge was positive or negative. You only know it is an anomaly in the air charge strong enough to measure, not if it is increased energy or decreased energy of a charge. From what I have heard reported so far, it seems to me to be very unlikely that any energy is emitted from buried metal or from the soil it is buried in. The probabilities alone point to anomalies in the earth's electrostatic charge that you are measuring, not to energy radiating from the soil or from buried metal. Any ionic activity in the soil could not be measured without putting probes in the soil. And we look at where the zahori antenna is put... in the air -- not in the soil. In fact, we are measuring variations of charges in the air. The whole idea that we are measuring energy emitted from a phenomenon, or from the ground is wrong.... it is only some theoretical idea people made up.

I do not think it is a good idea to continue the legend that buried metals emit energy unless you have some strong evidence to show there is actually some energy emissions that you measured, and show what kind of energy this is, to show you are not simply measuring an anomaly in the air charge.

Best wishes,
J_P

[J_Player]

Here is a test I think can give better information about the secrets of "the phenomenon"

1. When you find beeping on your zahori, Write down some information:
A. How far distance it is beeping.
B. How wet is the ground.
C. Any plants near? Rocks near, etc. ?
D. Near to power lines, buildings?

2. Dig for target and write down more information:
A. What did you find? how big? Empty hole?
B. How deep below surface?
C. Measure again with Zahori - how much distance it beeps when target is removed and hole is empty?

3. Put dirt back into hole, and compact it with your foot to make it hard same as before you start digging.
Then take another measurement with the zahori to see how far distance you find beeping when there is no target in the hole.

We will now have 8 items of data to help us learn real information about "phenomenon" instead of believe legends that always change from different theories.
We can use facts and data that people measure instead of theories.
And we can learn some real ideas about what "the phenomenon" is.

Best wishes,
J_P

[nelson]

Yes Qiaozhi, you are rigth.
Next time i will do that.
Regards
Nelson


A suggestion for next time:
After digging the target found with the metal detector, recheck the area again with the Zahori to see if the signal is still there or if it has disappeared.
Also, check the rest of the site with the metal detector. The results of these tests will no doubt be most illuminating.

[Qiaozhi]

Hi to all
If for first time detection done with zahori ,then check aria with metal detector,
Using again zahori at seem area after metal detector will be without result,
Because metal detector transmitter section destroyed phenomenon energy!!!!!!
Best regards.
According to the pseudo-scientific theory.
But in practice you might find something different. :rolleyes:

[Morgan]

Hi Mehdi and all friends.
Last weekend i made a short test with mini zahorie. The detector mades a tac tac tac on one direction, so i tryied to pinpoint the signal that was a small area of about 50 by 50 centimiters. Then i took my metal detector and yes, it detected a signal, that after i dig it was just a small aluminium foil.
Perhaps it wasn´t a treasure, but i must said that for me it worked in detecting that aluminium foil at a distance of 1 meter. I thing this is a good startting point at least for me.
I m waitting for this weekend to try it again.
Regards
Nelson

Hi Nelson

Nice to hear that you found some metal with your zahori.I supose you are using the LOOP with SILVER SAMPLE ?

People with ZAHORI already found : one treasure,another treasure,one coin,piece of silver paper,one empty hole. Better results than with 10,000 Euro MINEORO or other expensive LRL´s ;)

[J_Player]

Hi Nelson

Nice to hear that you found some metal with your zahori.I supose you are using the LOOP with SILVER SAMPLE ?

People with ZAHORI already found : one treasure,another treasure,one coin,piece of silver paper,one empty hole. Better results than with 10,000 Euro MINEORO or other expensive LRL´s ;)Hi Morgan,

You right..!! :)
Zahori is better results than with 10,000 Euro MINEORO.
Maybe Mineoro company should sell zahori for 10,000 Euro? :rotfl

I have a question...
When LRL experimenter solders gold sample or silver sample in coil for zahori, why does it find false beeping from silver paper? :???:
Silver paper is not gold, is not silver.... is aluminum...! :eek:

Better idea:
Connect aluminum sample into coil... less money to make zahori -- then you will find gold and silver from false aluminum beeps to locate gold and silver.... :good

Best wishes,
J_P

[nelson]

Hi Morgan and thanks for your message.
Yes, this motivated me to continue investigating mini zahorie. So after i have done a few more field test, i will coment it.
My antenna has a gold ring at the center, not silver.
Best regards
Nelson


Hi Nelson

Nice to hear that you found some metal with your zahori.I supose you are using the LOOP with SILVER SAMPLE ?

People with ZAHORI already found : one treasure,another treasure,one coin,piece of silver paper,one empty hole. Better results than with 10,000 Euro MINEORO or other expensive LRL´s ;)

[Morgan]

Hi Morgan,

You right..!! :)
Zahori is better results than with 10,000 Euro MINEORO.
Maybe Mineoro company should sell zahori for 10,000 Euro? :rotfl

I have a question...
When LRL experimenter solders gold sample or silver sample in coil for zahori, why does it find false beeping from silver paper? :???:
Silver paper is not gold, is not silver.... is aluminum...! :eek:

Better idea:
Connect aluminum sample into coil... less money to make zahori -- then you will find gold and silver from false aluminum beeps to locate gold and silver.... :good

Best wishes,
J_P

The sample made of gold or silver never solder to wire from the circuit,the sample must be in situation as a ferrite with coil around to produce the efect. This we can see in the Esteban Blue PD. If you solder the wire who goes to ANTENNA to a SAMPLE you will never have any efect of SAMPLE RESONATING,in this case the sample acts like one antenna.
Here is the best solution for the IVCONIC ZAHORI.
15375

[J_Player]

The sample made of gold or silver never solder to wire from the circuit,the sample must be in situation as a ferrite with coil around to produce the efect. This we can see in the Esteban Blue PD. If you solder the wire who goes to ANTENNA to a SAMPLE you will never have any efect of SAMPLE RESONATING,in this case the sample acts like one antenna.
Here is the best solution for the IVCONIC ZAHORI.
Hi Morgan,

Maybe I make a mistake to think the gold sample is soldered to the wire in the antenna.
I don't know where I get this wrong idea.
Maybe it is because I look at the picture that shows gold wire soldered.... :???:

[Geo]

Hi Morgan,

Maybe I make a mistake to think the gold sample is soldered to the wire in the antenna.
I don't know where I get this wrong idea.
Maybe it is because I look at the picture that shows gold wire soldered.... :???:

Hi J_P.
Gold sample is the ring, not the wire. So i can't see any solder to it.
Bu maybe to make mistake!!!! Maybe bad photo..... or maybe you have right

Regards:)

[J_Player]

Hi J_P.
Gold sample is the ring, not the wire. So i can't see any solder to it.
Bu maybe to make mistake!!!! Maybe bad photo..... or maybe you have right

Regards:)Hi Geo,

I don't know the answer.
When I see the ring, it looks not like gold...
The ring looks like brass, but the wire looks to be gold color.
Maybe this is a trick to fool people so they will not discover the secret of putting gold in the coil... :rolleyes:

Best wishes,
J_P

[Morgan]

Hi Morgan,

Maybe I make a mistake to think the gold sample is soldered to the wire in the antenna.
I don't know where I get this wrong idea.
Maybe it is because I look at the picture that shows gold wire soldered.... :???:

No gold wire,this is photograph efect on shining brigth copper wire...
Some stupid people connect the gold direct to RX wire,they will get O results,in this case the zahori will detect tin?copper?lead?iron? becouse all this metals are present in RX circuit.
The Gold must be in touch with a coil NOT CONNECTED,and the coil must be tigth.

[Morgan]

Hi Geo,

I don't know the answer.
When I see the ring, it looks not like gold...
The ring looks like brass, but the wire looks to be gold color.
Maybe this is a trick to fool people so they will not discover the secret of putting gold in the coil... :rolleyes:

Best wishes,
J_P

the ring is SILVER

[Morgan]

Hi Geo,

I don't know the answer.
When I see the ring, it looks not like gold...
The ring looks like brass, but the wire looks to be gold color.
Maybe this is a trick to fool people so they will not discover the secret of putting gold in the coil... :rolleyes:

Best wishes,
J_P

hi Joker_Player,you must pay more atention to my threads,i give a few times information about the antenna and sample.
Made of Brass? No,you make confusion with Mhedi.

Regards

[Morgan]

hi Joker_Player,you must pay more atention to my threads,i give a few times information about the antenna and sample.
Made of Brass? No,you make confusion with Mhedi.

Regards

sample SILVER not BRASS
15397

[J_Player]

sample SILVER not BRASS

http://www.geotech1.com/forums/attachment.php?attachmentid=15397&d=1306068334Hi Morgan,

If this is the standard method to put a sample of material in the coil circuit, then there are two known electrical effects that can come from changing to different materials. The sample is placed inside a magnetic field from the wire that is wound around the ring. This means the small coil will feel some impedance from the silver ring in the center which is caused by eddy currents. There will also be a phase change to the small copper coil due to the time constant for the silver material.

This effect will also be present for any other coils that are in the area where they can be influenced by a magnetic field, (like the larger coils), which may even see more impedance from the ring in the center, depending on how much current passes in these coils. And the larger coils can be expected to actually induce a current traveling in the circle direction of the ring, which we can expect to be stronger current than if it was simply a small ball of silver. For this reason, we can expect the larger coils which follow the same direction of the ring will also see the effect of the solder joint resistance.

A third thing to consider is this is probably not pure silver. Unless you are using commercially pure silver, it is an alloy which contains copper and maybe some other metals, same as most gold contains copper, silver and maybe other metals in the alloy. This means the resistance of the metal will be different than pure silver or pure gold, depending on what alloy, and the eddy currents will change along with the impedance and phase shift to the zahori coils. Then there is also the solder junction where the ends of the wire were soldered together with higher resistance than silver.

To get an idea how this can influence the circuit, look at the VLF metal detectors that have a dial which shows the different coins and metals it detects. The change in eddy current strength can be determined by measuring electronic changes in the RX coil when different metals are placed in the magnetic field of these coils. We know silver is the most conductive common metal which we find at one end of the scale, with copper near to it. Then we see less conductive metals like gold and aluminum farther down on the dial, then weak conductors are near the bottom where we finally get a reverse effect from iron materials and hot rocks.

Still, this says nothing to help show how putting a metal sample into the coil field will help find a buried sample of similar material. For a normal VLF metal detector, any metal sample you put at the coil will only make the coil less sensitive to buried metal you are hunting for, because the coil must now find a second piece of metal in addition to the piece that is put in the center of the coil. This is the reason why most metal detectors use non-metallic shafts and plastic hardware near the coil, to avoid having metal there which will make the coil less sensitive.

In the case of the zahori, we are not searching for buried metal eddy currents. We are searching for changes in the charge that the circuit can measure in the air. So we do not need to be concerned that we have added some metal to create impedance to those coils or a phase shift. More important, in the zahori circuits, there is no VLF tuned circuits I can see. These are simple coils connected to a high impedance amplifier. This means any eddy current effect will be working on changes in charge sensed which happen rapidly. I would expect any pulses that you might detect could be from a static discharge or even VLF impulses or natural frequencies from a few KHz up to the GHz region (or up to the limits of your transistors). The impulse signals you might measure from charge pulses with time durations in these ranges could possibly be influenced by the effect of the sample metal in the coil fields. Considering the single loop coils, and the 10 turn coil, I might expect it could be more sensitive to frequencies and pulses in the VHF range if it is sensitive to frequencies at all. This would depend on the circuit capacitance at these coils. The sample material may even be helping to tune the coils, or acting as a filter, considering the different metals have different time constants.

It might be interesting if someone connected an oscilloscope to see how the signal looks at the first transistor input with the sample in place and with the sample removed. Especially interesting what the signal looks like when you make a battery sparks nearby with the sample in place and with the sample removed.

Best wishes,
J_P

[Morgan]

Hi Morgan,

If this is the standard method to put a sample of material in the coil circuit, then there are two known electrical effects that can come from changing to different materials. The sample is placed inside a magnetic field from the wire that is wound around the ring. This means the small coil will feel some impedance from the silver ring in the center which is caused by eddy currents. There will also be a phase change to the small copper coil due to the time constant for the silver material.

This effect will also be present for any other coils that are in the area where they can be influenced by a magnetic field, (like the larger coils), which may even see more impedance from the ring in the center, depending on how much current passes in these coils. And the larger coils can be expected to actually induce a current traveling in the circle direction of the ring, which we can expect to be stronger current than if it was simply a small ball of silver. For this reason, we can expect the larger coils which follow the same direction of the ring will also see the effect of the solder joint resistance.

A third thing to consider is this is probably not pure silver. Unless you are using commercially pure silver, it is an alloy which contains copper and maybe some other metals, same as most gold contains copper, silver and maybe other metals in the alloy. This means the resistance of the metal will be different than pure silver or pure gold, depending on what alloy, and the eddy currents will change along with the impedance and phase shift to the zahori coils. Then there is also the solder junction where the ends of the wire were soldered together with higher resistance than silver.

To get an idea how this can influence the circuit, look at the VLF metal detectors that have a dial which shows the different coins and metals it detects. The change in eddy current strength can be determined by measuring electronic changes in the RX coil when different metals are placed in the magnetic field of these coils. We know silver is the most conductive common metal which we find at one end of the scale, with copper near to it. Then we see less conductive metals like gold and aluminum farther down on the dial, then weak conductors are near the bottom where we finally get a reverse effect from iron materials and hot rocks.

Still, this says nothing to help show how putting a metal sample into the coil field will help find a buried sample of similar material. For a normal VLF metal detector, any metal sample you put at the coil will only make the coil less sensitive to buried metal you are hunting for, because the coil must now find a second piece of metal in addition to the piece that is put in the center of the coil. This is the reason why most metal detectors use non-metallic shafts and plastic hardware near the coil, to avoid having metal there which will make the coil less sensitive.

In the case of the zahori, we are not searching for buried metal eddy currents. We are searching for changes in the charge that the circuit can measure in the air. So we do not need to be concerned that we have added some metal to create impedance to those coils or a phase shift. More important, in the zahori circuits, there is no VLF tuned circuits I can see. These are simple coils connected to a high impedance amplifier. This means any eddy current effect will be working on changes in charge sensed which happen rapidly. I would expect any pulses that you might detect could be from a static discharge or even VLF impulses or natural frequencies from a few KHz up to the GHz region (or up to the limits of your transistors). The impulse signals you might measure from charge pulses with time durations in these ranges could possibly be influenced by the effect of the sample metal in the coil fields. Considering the single loop coils, and the 10 turn coil, I might expect it could be more sensitive to frequencies and pulses in the VHF range if it is sensitive to frequencies at all. This would depend on the circuit capacitance at these coils. The sample material may even be helping to tune the coils, or acting as a filter, considering the different metals have different time constants.

It might be interesting if someone connected an oscilloscope to see how the signal looks at the first transistor input with the sample in place and with the sample removed. Especially interesting what the signal looks like when you make a battery sparks nearby with the sample in place and with the sample removed.

Best wishes,
J_P

I test the Zahori with 1,5V sparks and not detect,with sample or without.

What i can say is the sample must be there for some LRL results,remember that the old zahori not have the SAMPLE and nobody found nothing,

Regards

[mehdi]

some good news with mini zahori:cool::cool:;)
.....
mehdi

[aft_72005]

some good news with mini zahori:cool::cool:;)
.....
mehdi

Hi mehdi
Nice work http://www.iranmicro.ir/forum/images/smilies/good.gif, please test it in real historical places , I am interest know , what will be result !!!???? http://www.iranmicro.ir/forum/images/smilies/connie_slingshot.gif

[mehdi]

... .
http://www.iranmicro.ir/forum/images/smilies/connie_slingshot.gifhttp://www.iranmicro.ir/forum/images/smilies/connie_slingshot.gifhttp://www.iranmicro.ir/forum/images/smilies/connie_slingshot.gifhttp://www.iranmicro.ir/forum/images/smilies/connie_slingshot.gif :shocked:

[Morgan]

... .
http://www.iranmicro.ir/forum/images/smilies/connie_slingshot.gifhttp://www.iranmicro.ir/forum/images/smilies/connie_slingshot.gifhttp://www.iranmicro.ir/forum/images/smilies/connie_slingshot.gifhttp://www.iranmicro.ir/forum/images/smilies/connie_slingshot.gif :shocked:

Yes,test the zahori in real historical places,but say to the police that you are using a PETROL locator ;)
I know very well what they do to TH´s in arab territory,its a shame.Be careful

[aft_72005]

Yes,test the zahori in real historical places,but say to the police that you are using a PETROL locator ;)
I know very well what they do to TH´s in arab territory,its a shame.Be careful


Yes, mehdi very important, you must be careful from intelligent police . Any digging in historical places is forbidden in your aria, I hope successfully for you. As Morgan said in This forum, he had more success with his zahori( yes ,I called this circuit Morgan zahori) .
if your circuit without problem and if work correct , you must be found something . Morgan see mehdis avatar . my opinion he isn’t Arab . :rolleyes::cool:

[mehdi]

Yes, mehdi very important, you must be careful from intelligent police . Any digging in historical places is forbidden in your aria, I hope successfully for you. As Morgan said in This forum, he had more success with his zahori( yes ,I called this circuit Morgan zahori) .
if your circuit without problem and if work correct , you must be found something . Morgan see mehdis avatar . my opinion he isn’t Arab . :rolleyes::cool:

Hi Morgan and aft
yes , any digging in historical places is forbidden in my country :angry::angry::angry: and we cant dig it at all. and surely i never dig any historical place:) but i love very much MDs and special LRLs only for fun and education. be sure.

mehdi

[vali]

HELLO
I agree with MEHDI .
best wishes.

[mehdi]

HELLO
I agree with MEHDI .
best wishes.


Hi vali
thanks a lot
all the best

[raff33]

Hi Michael

One of ZB user found one silver box with jewelry buried in old house yard (garden ? ) he said ZB start the sounds at 50 meters,he folow direction and use the ZB pointed to ground to understand where it comes the signal,and of course with metal detector he found the box only 40 cm deep,material was from the 18 century. The other one found one gold cache,more than 1 Kg of coins in a remote place like a forest,distance was 80 meters,i not remember the deep,he told only with Pulse Induction large coil he get the pinpoint of the cache. Both of them said after remove the treasures ZB not give more signals. Should i believe in this stories ???Well i need to rebuild my ZB and go to the fields ;)

Regards

Hi morgan,
are they found big treasure with ZB+BFO or only ZB ?
Regards

[detectoman]

mehdi my congratulations for you tipe rustic lrl z. morgan design, semms same quality how andreas last lrl prototipe, may be you can put ready knockout at any bad cop whit these

[miguelsaen]

hello
Pardon my English is not very good
I do not understand electronics and I like to do the dowsing
if someone can pass a list of component
since they did not know and do not know what to buy are latro
thanks for everything

[LRLMAN]

Hi, I have a question to all members of this forum, someone knows why they took away the image of Stephen? that instead put a picture of a four-leaf trebon?

Well, I commented that since the end of the second prototype of the Mini Zahori and I'am to share some field tests that I have done as well as images of the two Aparatus or Equipments recently completed.

I send many greetings and a hug

lrlman.

[Morgan]

Hi, I have a question to all members of this forum, someone knows why they took away the image of Stephen? that instead put a picture of a four-leaf trebon?

Well, I commented that since the end of the second prototype of the Mini Zahori and I'am to share some field tests that I have done as well as images of the two Aparatus or Equipments recently completed.

I send many greetings and a hug

lrlman.

The Zahori is simple LRL project,i think is available for everybody in this forum.

Hope you will make some nice finds with your mini Zahori.

[miguelsaen]

anyone has tried the dowsing
that this is for metals like gold

[LRLMAN]

Hello friend Mogan here are pictures of my Little-Zahori which works well but i could not find some buried metal objects because I have not been much to the field

lrlman

[LRLMAN]

Let me tell you that the second prototype is malfunctioning because I did not do a Faraday screen at the fiberglass PCB

and here the pictures

[Morgan]

Let me tell you that the second prototype is malfunctioning because I did not do a Faraday screen at the fiberglass PCB

and here the pictures

Well done.

Now you need to go for field test and post the results.

I think we dont need the big loop,you must try near your TV and see if with only small loop the distance is bigger or not,try both.

Good luck.

[LRLMAN]

Well done.

Now you need to go for field test and post the results.

I think we dont need the big loop,you must try near your TV and see if with only small loop the distance is bigger or not,try both.

Good luck.

Hi Master Morgan and all friend.

I did tests with TV and this is detected by a 5 meters away a power transformer from a pole in the street it detects up to 20 meters

This ZB can detect the pulse energy eliminator on my cell phone is a green LED that lights up when i connecting to the cell wall charger and can detect up to two meters away like a human heart beat of a boom boom boom

and one very important thing that I'm watching, and this is for all partners of this forum, this small zahori providing me data or information on where to work with some other long-distance and equipment becouse I can know with a headset when a field Elecro -magnetic interferes to work with a LRL of alonso or other one like this, because these others only have a buzzer system with a beep and see the Mini-Zahori could better detect interference or areas where they could work with alonso equipment or other similar

This evening i test de ZB whit only one loop with or without sample and late conment to you de result test.

Regards.

LRLMAN (believe me I am excited about all this)

[LRLMAN]

Hi Master Morgan and all friend.

I did tests with TV and this is detected by a 5 meters away a power transformer from a pole in the street it detects up to 20 meters

This ZB can detect the pulse energy eliminator on my cell phone is a green LED that lights up when i connecting to the cell wall charger and can detect up to two meters away like a human heart beat of a boom boom boom

and one very important thing that I'm watching, and this is for all partners of this forum, this small zahori providing me data or information on where to work with some other long-distance and equipment becouse I can know with a headset when a field Elecro -magnetic interferes to work with a LRL of alonso or other one like this, because these others only have a buzzer system with a beep and see the Mini-Zahori could better detect interference or areas where they could work with alonso equipment or other similar

This evening i test de ZB whit only one loop with or without sample and late conment to you de result test.

Regards.

LRLMAN (believe me I am excited about all this)


Excuse me

the Mini-Zahori could better detect interference or areas where they could NOT work well with alonso equipment or other similar

[GOLDENSKULL]

Hi LRLMAN,
good work,

please tell us more about your zahori antenna ?
what is antenna size and other specification ? i want build your antenna...

i build mini Zahori and if you use BC237 instead BC548 you can
get better results...

Thanks...

[LRLMAN]

Hi LRLMAN,
good work,

please tell us more about your zahori antenna ?
what is antenna size and other specification ? i want build your antenna...

i build mini Zahori and if you use BC237 instead BC548 you can
get better results...

Thanks...


Hi Mr. Golden, Thanks for information about BC237 I have BC239 And i believe the BC549C is for two 9V batteries and i will put this at other PCB Little-zahori and the information about antennas is next:

L1= 8 CMS Diameter enameled magnet wire of 1 mm thick.
L2= 12 CMS Diameter enameled magnet wire of 1 mm thick.

the two antenas was the two antennas were made ​​from strips rounds of mahogany (CAOBA) wood.

The wire has a silver ring is 0.5 mm in diameter, the ring is 2 cm. diameter, with 17 turns in the direction of clockwise.

The L2 Antena have the ends of the wires inserted into the wood to the back of the tablet.

The magnet wire the two antennas is placed within a narrow channel made ​​in the wood.

And glued the wires with tape magic.

All this is the first prototype.

For the second prototype is the same think only just change the red wires that are in the photos are of the RCA for sound systems of cars and into the wooden box is a female connector to connect the RCA male ends; except that attached to the ends of each antenna wire and magnet wire with a little hot glue silicone so they do not move much.
as shown in followings pictures:

[GOLDENSKULL]

hi,
Thanks LRLMAN,

please tell us about your mini zahori, that what thing you can detect by this device ?

i tell again:
if you use BC237 instead BC548 you can
get better results...

[goldfinder]

I am amazed this thread keeps going on and on and on for a simple topic that just detects electrostatics.:lol: At least it does that... I did extensive tests in the field and there are so many source of static charge. Even walking across sand sets off my stab at this one. Along with clothes rubbing together, different fabriks, bushes, trees. I can detect a tree 100 yards away. I was even ready to dig a hole in the sand charge until I saw what was triggering my detector. I seemed every step rubbed some sand particles and created ions.

The LRLers are really desperate!
Goldfinder

[Geo]

Zahori or miniZahori are not good projects for treasure hunting.
May be able to detecting a buried object, but the chances are very few:frown:.
LRLers must looking for something better.

[GOLDENSKULL]

Zahori or miniZahori are not good projects for treasure hunting.
May be able to detecting a buried object, but the chances are very few:frown:.
LRLers must looking for something better.


Hi Geo,

you say by zahori we can not detect buried treasure ?
Thus which device we can treasure from distance?

if you remember i build a L-Rod that can detect any thing from at least 1km...
but i must learn many things about this... !!! :cool:

[Morgan]

I am amazed this thread keeps going on and on and on for a simple topic that just detects electrostatics.:lol: At least it does that... I did extensive tests in the field and there are so many source of static charge. Even walking across sand sets off my stab at this one. Along with clothes rubbing together, different fabriks, bushes, trees. I can detect a tree 100 yards away. I was even ready to dig a hole in the sand charge until I saw what was triggering my detector. I seemed every step rubbed some sand particles and created ions.

The LRLers are really desperate!
Goldfinder

This one is not the MINI ZAHORI. Or you are using some EXTRA SENSITIVE antenna,with this device you cant locate tree or a rock,nylon clots is possible.
I agree with Geo,but this is something simple for the LRL beginers to build.
Well,i know people who found buried metals with this device,and start to become popular.

[Geo]

Hi Geo,

you say by zahori we can not detect buried treasure ?
Thus which device we can treasure from distance?

if you remember i build a L-Rod that can detect any thing from at least 1km...
but i must learn many things about this... !!! :cool:

Hi.
You can make a LRL with a lot of techniques.
Electrostatic fields, magnetic fields, absorbance reflection etc.Most people don't understand anything about lrls and their problems. Best lrl is this that can go more near to object and not:nono: this that can locate the object from more far.

[Geo]

This one is not the MINI ZAHORI. Or you are using some EXTRA SENSITIVE antenna,with this device you cant locate tree or a rock,nylon clots is possible.
I agree with Geo,but this is something simple for the LRL beginers to build.
Well,i know people who found buried metals with this device,and start to become popular.

Maybe it is time for a more fresh schematic for the beginers.
What you say for something close to PDK or to lrl that i had with me at Portugal???

[Morgan]

Maybe it is time for a more fresh schematic for the beginers.
What you say for something close to PDK or to lrl that i had with me at Portugal???

Hello Geo

I prefere to give them the golden eggs first,but i keep the chicken for me ;)

You can give them,but are you sure someone will say thanks to you???:nono:

Regards

[Morgan]

Maybe it is time for a more fresh schematic for the beginers.
What you say for something close to PDK or to lrl that i had with me at Portugal???

Some years ago i put here the PD project,this is the Alonso´s and Heatkit invention,so this is for everybody,but about my work and changes in the Passive Receiver i keep for me.


regards

[folharin]

My Zahori found a can of old paint to 50cm deep water 3 meters distance

[folharin]

http://www.geotech1.com/forums/data:image/jpeg;base64,/9j/4VqbRXhpZgAASUkqAAgAAAAMAA4BAgAZAAAAngAAAA8BAgAIAA AAuAAAABABAgA4AAAAwAAAABIBAwABAAAAAQAAABoBBQABAAAA +AAAABsBBQABAAAAAAEAACgBAwABAAAAAgAAADEBAgAHAAAACA EAADIBAgAUAAAAEAEAABMCAwABAAAAAgAAAJiCAgAQAAAAJAEA AGmHBAABAAAANAEAALJKAAA8U0FNU1VORyBESUdJVEFMIENBTU VSQT4AAFNBTVNVTkcAU0FNU1VORyBFUzYwIC8gVkxVVSBFUzYw IC8gU0FNU1VORyBTTDEwNSAvIFNBTVNVTkcgRVM2MwAgAQAAAw AAACABAAADAAAAOTA5MjgxAAAyMDExOjA5OjE0IDEyOjU0OjMz AENPUFlSSUdIVCwgMjAwOQAkAJqCBQABAAAA6gIAAJ2CBQABAA AA8gIAACKIAwABAAAABwAAACeIAwABAAAAyAAAAACQBwAEAAAA MDIyMAOQAgAUAAAA+gIAAASQAgAUAAAADgMAAAGRBwAEAAAAAQ IDAAKRBQABAAAAIgMAAAGSCgABAAAAKgMAAAKSBQABAAAAMgMA AASSCgABAAAAOgMAAAWSBQABAAAAQgMAAAeSAwABAAAABQAAAA iSAwABAAAAAAAAAAmSAwABAAAAEAAAAAqSBQABAAAASgMAAHyS BwAkRwAAUgMAAACgBwAEAAAAMDEwMAGgAwABAAAAAQAAAAKgBA ABAAAAAAQAAAOgBAABAAAAAAMAAASgAgANAAAAdkoAAAWgBAAB AAAAlEoAABWiBQABAAAAhEoAABeiAwABAAAAAgAAAACjBwABAA AAAwAAAAGjBwABAAAAAQAAAAKkAwABAAAAAAAAAAOkAwABAAAA AAAAAASkBQABAAAAjEoAAAWkAwABAAAAIwAAAAakAwABAAAAAg AAAAikAwABAAAAAAAAAAmkAwABAAAAAAAAAAqkAwABAAAAAAAA AAAAAAAHAAAACgAAACAAAAAKAAAAMjAxMTowOToxNCAxMjo1ND ozMwAyMDExOjA5OjE0IDEyOjU0OjMzAFgxEAAAAAwAMgAAAGQA AABPAQAAZAAAAAAAAAAKAAAATwEAAGQAAAA/AAAACgAAAFNUTU4xMDAAFWMCAD8pAQCAAuABAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAABQAAAAEABwCgDwAAAAAAAAIABwBYGwAA oA8AAAMABwCIEwAA+CoAAAQABwDQBwAAgD4AAAYABwBkAAAAUE YAAAAAAABNTl9QUlbRAAAAUjA0MDFCMDQ1MgAAmwEAAAAAAAAA AAAAAAAAAAAAAADYAQAANAMAAEkBAACJAQAAgwEAAIkBAAB4AQ AAU+IAAKoAAAA7AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADqBMgHegStBfMIGw XwBVgJSAWjA6YFJwOqAisEYAISA9UEwQK0AjQEYQI9AxEF5AK2 A8oFQAP5AyUGcgOAA2UFAwMGBDkGegM5BIEGoQM4BIIGnwOcBD IHDARSBLsG3gN6A2kFGgOOBjkKwAVlBu8JhQUrBn8JOAWHAR8C IgFxAd8B+QAMAXUBzADxAEYBsAABAWsBygDiAEABsQDqAEwBtw DiAEUBtADSACwBpQC3AAMBjwCqAO4AgQBFAe4BEQEtBQkIfASA BOsG4QMhBn8JTQU5B0QLQAZkBuUJYQVpAcwB6AD8AJIB8ADoAH QB3ADVAFQBxwDhAGgB0QDIAD0BtwDJADsBtQDEADABsQCqAAUB lgCKANIAeQCSANkAegDSAA0BiADwBKcHRgQjBecHaQRcB3sLbA bvB2QM0QaWBZoIqgQdAWYBrgDQAEcBvADWAE8BwwDSAEUBuwBF AbsB5wDaAB4BkgAJAWIBrgCqAPgAhQCaAOsAgwCAAMUAbgB+AM AAbQClANAAaQDPBHYHHwRuBVQIpQR/B7QLiAYHCJEM7AbEBFgH/QMOAUgBnQC+ACoBrgDBAC4BrACPAQACAAHUAC4BoACpAAEBjgD pAB0BiQCQANsAegCTAMcAZwCCAMEAbAB5ALgAaADGAOkAbgB1A 0wF6gLHBFAHCATJByIMuwZcCAwNKwcQBD4GYQPKAAMBggCsAAs BmgC1AA4BlABfAbQB1wCjAPsAjQCoAPoAhwDNAAIBfQCbAOkAf wCJAMgAbQCQAMwAbQB4ALUAZwCgAMcAYABrA0UF5wKvBCkH+gM OCIAM7gZRCPwMJAcwA9oEngKuAOEAcwCSAN0AfgDPAC4BogC2A PEAfADYAEQBswCiAPEAhAAeAaIB2ACGAMcAbACHAMcAbACtAOk AeAB6ALYAZACQALQAWgAPA78EmwLkBIAHJQTtB1YM2gavB/YLlQY4Ak8DwgGNAL8AZwCIAM0AcwCGAMcAcACuAOMAcQCLAMoA bQCHAMcAbACCAMEAZwCGAMgAbQD3AG0BxgCkANYAbABtAKgAXA CMAK4AVgCgAhYEQgLIBE8HDwQ6BfYHYgTyBsgK7wVoAfsBAgFx AKgAXwB5ALcAZQB2ALMAZQCNAL4AYQCiANAAagB2ALAAYAB7AL UAYQCYANoAcQBTAaEBzACGAMMAZgBqAJ8AWAB0AJkATQAoAlwD 2wGtBDQH/gOUBaQI0ARmBMIGrAPWAB8BkgBpAJ8AWwBvAKcAXABoAKAAWQB rAKAAVwBnAI4ASwCUALQAVwCZALsAWgCuAOcAcwBuAKUAWABkA JYAUQBbAIwATABmAIcARgCfAYUCaAFLBJMGrQMgBoIJSgXlBSU J+wSCAKwAXABeAI4AUABiAJUAUgBZAIgATABdAIoATQBfAJEAT QBcAIsATABUAHsAQwBlAJcAUABjAJUAUABZAIYASgBZAIQASgB WAHgAQQBfARQCKgHwAxQGZgOzBdgI7gRcBVQIjARzAJQAUABgA JEAUgBbAIgATgBbAIkATQBVAIAASABOAHYARABaAIMASABXAH8 ARgBUAHwARQBYAIQASQBzAJ8AUwB8AKAAUwB8AJMARgA0AdEBA AGKA3QFDAMxBRIIjQRlBXAIpwQ9Ae8BFgEMASYBgwCMAKwAVQB 1AKwAXQBhAI8ATwBYAIMARwBVAH0ARQBSAHUAQQBVAH0ARABrA KEAWABeAH4ARQBlAJ0AWwBqAKcAZADuAQgDuwHYAmYEegIAAJE BAADEAQAAhAEAAM8BAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAkQEAAAABAADEAQAAA AAAAAAAAAAAAAAAlgEAAAABAAC/AQAAhAEAAAAAAADPAQAAhAEAAAAAAADPAQAAAAAAAAAAAAAAAA AAXgQAADE1OjI5OjU3IEF1ZyAyMSAyMDA5AAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAE1OX0NBUN EAAABSMDM3N0IwNDczAACiAQAAAAAAAGAAAAAAAAAACAAAAAAA AAAAAAAAtf///wAAAAA7AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAABsFvwdWBN0GjQrRBRcIRgzVBq0I/wwjB2IIbgziBpcIuww9B24HNQsyBiQJmA1yBwAJcA2GBw4JiQ2 PBwgJUA1xB8sFXgiHBNkHRwtOBj8H0AoVBrQG/QmsBTkGNAlCBVsF6geVBEUHDQsjBpUIEQ33BtEIXw01B9EEMAe gA24BSAJQAUoBGgIrAUEB+gEtAWYBSgJgAT4B4QEVAU0B/AEdAWoBMwJDAYABOQI3AWsBKgI2AVcCfQPJAcAFlwinBPwGagq rBb0FzAi+BEAIfAzTBuIHKgxpBqEJpw7DB2sBMAIrARQBpAHyA DgB9wEjAR0BrQEEAXMBSwJNAQIBewHmAA8BjgHfAA8BnAHoAPw AjAHjALYAGwGgAHkAsQBkAPoAcgHVALYGNgppBa4GAApvBVIF7 AdpBKcJ3g7vBzcKow9rCBMBkwHkACUBywEAAUgB9wEZAf0AjwH aAC4BxgEMAfsAgAHNAO0AagHQAAsBoQHdANEAOwGmALAACwGLA KMA+ACFAKQA3QByAO4H6gtfBhsHogq7BX8IIg0tB/cJNg8eCGUKoQ9qCBwBpQHeAPgAcgHJAAsBmQH0AAUBjQHXAFQE 4AUIA4cAxQBvAMIDwANzAYcA0gB1AM4AJgGbAKkA/wCRAI8A2gB7AHsBdAGZAC4GMAngBPIGggqrBbcJzA4CCNMJDw/nB+UK3A/cCM4BEALiANIAUwG3APgAgQHWAJMDEATJAesAWQG0AO0AYAHCA I0BpQGnANkAPwGjALEABgGPAKMA/wCCAJ8A7QB/ABMBIwFyAKcDdAW5Am0GeAkhBdsJHw8YCMEJDg/eBx8L4Q/0CFIBUAF5AM0ALAGvAMAAKgGgAP0AGwF/AMQAJAGgAL0AIQGdAOIAIQGIAMUAKQGfAL0ADwGMAEIBYwGeAL MAGAGWAI0AzABnAKEBZgIwAWgGrQlABfsJPw8wCC4KiA8tCM8K 3g+yCMcBtgGQALsAGgGfALYAEQGLALABzQG4AK8ACAGJALsAGg GDAK0A/ACFALEAAQGGAJkA5wB2AAgCVwIKAasA7wCBAIwA0ABzALEA+AC DAD4GaQnhBCkH4QrpBZcJmA60B0AHLAvpBakAvABTAKkA8wCGA JQA6ABzAKIA6QB+ALkA/wCGAJwA4gB6AKQA7gB4AIwA3AB9AMgAIwGMAOcAOwGlAJsA4AB 0AIQAvgBiAIoAzQB1ADIGdAkRBeYHOwy0BugBwgJYAcoD4QUhA 4EAuwBtAJcA2wBzAIcAygBuAJYA3AB6AIMArwBfADABYgGiAJ0 A2ABxANgBMQIEAYEAtgBZAIsAxgBvAHsAtQBjAHwAsABlAH0Ar QBqAHgFEwhQBAkIaAy1BmcHUgsOBrMACgGHAH4AsQBbAI4AzgB pAHMArgBeAHgAsABkAIUAxwBpAIAAwwBbADsAUQAoAIAAvgBpA JIAzQBrAHYAqwBZAHYArwBWAG0AqABdAGoAqQBaAEIFEwhmBEc HHwsSBrAH1ws3Bn0AvgBtAH4AwQBtAGIApABQAHUAqABZAGwAp wBVAGMAngBJAHoAsQBcAG0AlgBXAHcAoQBaAHYArwBbAHEAqAB VAHIAoQBaAG4AnQBUAGAAkwBGAAEFgQcaBEUGpglaBfUGnQq1B ZIA0wB3AI8CAQKbACACXAIAAXkAqwBjAKMA9wB5AHoAowBZAG4 AmwBQAGQAkwBZAGoAogBUAHMArQBgAHIAgAA2AJcA1ABxADEAS QAlAFkAfABEAGUEswanAwAAeQEAANkBAACJAQAAgwEAAHkBAAD ZAQAAiQEAAIMBAAB5AQAA2QEAAAAAAACRAQAA0QEAAAAAAAAAA AAARz4CANTKAQDrTwMAkQEAAMQBAAC6AQAAsgEAAHkBAADZAQA AAAAAANoBAAC6AQAAsgEAAHkBAADZAQAAAAAAAMD///8hPAIA608DAFjKAQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAeQEAAAABAADZAQAAeQEAAAAAAADZAQAAeQEAAAABAADZAQ AA4wEAAAABAABNAQAAeQEAAAABAADZAQAAeQEAAAABAADZAQAA eQEAAAABAADZAQAAfQEAAAAAAACyAQAAkQEAAAABAADEAQAAAA AAAAAAAAAAAAAAXgQAADE1OjI5OjU3IEF1ZyAyMSAyMDA5AAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA S2ltIE1pYWU/ADcAhQABAAAAAAAAAAAAUAA3AIUAAQAAAAAAAAAAAFAANwCFAA EAAAAAAAAAAABYADcAYgBlgAAAAAATAOoBCAA3AGAAAAAAAAgA GC8AgMoH8whTCaMFLATVBDUEEwXIBSYGZQU4BoEGgAYwB8MGbw U3CugJdwkoAu0BfQFOAXMBRgFSAUoBMAEIAfIA7gEFCO4GfAk4 C9IJ2QGVAXUBVQFoAT0BOwEyAQcB1ADbABQBpQfoB3QLTwyLCG 8BRwFRAUcBwgEkAWUB+QDrAMUAwQDWAG4HVwirC3sMTAdSASwB LgENAjABAQElAdsAygDCALkA8gBJBU4HFQz1DDQGCQEMAQ8Bwg H7APoACAHpAMkAzgC2AMwAQAUrB3YM5gzUBOcA3wAvAfYARQHy AKABxwDHAOwAtgC5ALgEfgdLDOULTAPDAM4AyQDnAMsAxwDAAM gAbgHaAKcAswARBFEH9ge6CvwBqgC3ALQAwADWALAAtQDaAK8B wgCfAJsAVwMxB6AIuAYjAaAApwCfAKAAkAC6AMAA6gCkAJUAiw CKAIMClwZ8CRQJsQCPAJQAiACLAI8AiwB7AJYAlACGAIUAegAW AhQG1AhFCJoAkgCJAIkAgQB3AIQAgAB9AIQAoQClAJgA0gF1BR MIYgjuATUBsgCsAJAAgwB+AHcAfQChAIIAngCpAAgDZwTqBK0F 8AWjA6oCEgO0Aj0DtgP5A4ADBgQ5BDgEnARSBHoDjgZlBisGhw FxAQwB8QABAeIA6gDiANIAtwCqAEUBLQWABCEGOQdkBmkB/ADoANUA4QDIAMkAxACqAIoAkgDSAPAEIwVcB+8HlgUdAdAA1gD SAEUB2gAJAaoAmgCAAH4ApQDPBG4FfwcHCMQEDgG+AMEAjwHUA KkA6QCQAJMAggB5AMYAdQPHBMkHXAgQBMoArAC1AF8BowCoAM0 AmwCJAJAAeACgAGsDrwQOCFEIMAOuAJIAzwC2ANgAogAeAYYAh wCtAHoAkAAPA+QE7QevBzgCjQCIAIYArgCLAIcAggCGAPcApAB tAIwAoALIBDoF8gZoAXEAeQB2AI0AogB2AHsAmABTAYYAagB0A CgCrQSUBWYE1gBpAG8AaABrAGcAlACZAK4AbgBkAFsAZgCfAUs EIAblBYIAXgBiAFkAXQBfAFwAVABlAGMAWQBZAFYAXwHwA7MFX AVzAGAAWwBbAFUATgBaAFcAVABYAHMAfAB8ADQBigMxBWUFPQE MAYwAdQBhAFgAVQBSAFUAawBeAGUAagDuAdgCyAfzCFgJpgUrB NUENAQRBcoFJQZlBTkGgQaCBjIHuwZpBTkK7wl/CR8C3wF1AUYBawFAAUwBRQEsAQMB7gDuAQkI6wZ/CUQL5QnMAZIBdAFUAWgBPQE7ATABBQHSANkADQGnB+cHewtkDJ oIZgFHAU8BRQG7AR4BYgH4AOsAxQDAANAAdgdUCLQLkQxYB0gB KgEuAQACLgEBAR0B2wDHAMEAuADpAEwFUAciDAwNPgYDAQsBDg G0AfsA+gACAekAyADMALUAxwBFBSkHgAz8DNoE4QDdAC4B8QBE AfEAogHHAMcA6QC2ALQAvwSAB1YM9gtPA78AzQDHAOMAygDHAM EAyABtAdYAqACuABYETwf2B8gK+wGoALcAswC+ANAAsAC1ANoA oQHDAJ8AmQBcAzQHpAjCBh8BnwCnAKAAoACOALQAuwDnAKUAlg CMAIcAhQKTBoIJJQmsAI4AlQCIAIoAkQCLAHsAlwCVAIYAhAB4 ABQCFAbYCFQIlACRAIgAiQCAAHYAgwB/AHwAhACfAKAAkwDRAXQFEghwCO8BJgGsAKwAjwCDAH0AdQB9AK EAfgCdAKcACANmBHoEGwVIBScDYALBAmEC5AJAA3IDAwN6A6ED nwMMBN4DGgPABYUFOAUiAfkAzACwAMoAsQC3ALQApQCPAIEAEQ F8BOEDTQVABmEF6ADwANwAxwDRALcAtQCxAJYAeQB6AIgARgRp BGwG0QaqBK4AvADDALsA5wCSAK4AhQCDAG4AbQBpAB8EpQSIBu wG/QOdAK4ArAAAAaAAjgCJAHoAZwBsAGgAbgDqAggEuwYrB2EDggC aAJQA1wCNAIcAfQB/AG0AbQBnAGAA5wL6A+4GJAeeAnMAfgCiAHwAswCEANgAbABsAH gAZABaAJsCJQTaBpUGwgFnAHMAcABxAG0AbABnAG0AxgBsAFwA VgBCAg8EYgTvBQIBXwBlAGUAYQBqAGAAYQBxAMwAZgBYAE0A2w H+A9AErAOSAFsAXABZAFcASwBXAFoAcwBYAFEATABGAGgBrQNK BfsEXABQAFIATABNAE0ATABDAFAAUABKAEoAQQAqAWYD7gSMBF AAUgBOAE0ASABEAEgARgBFAEkAUwBTAEYAAAEMA40EpwQWAYMA VQBdAE8ARwBFAEEARABYAEUAWwBkALsBegIAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAkQHEAS8AQQDu/xYDLwAPAJEBxAEAAKgCtAKkAp8CmwIOACMAAAAAAFsCegJ/AmQDAAAUACgABgACAAAAAAAAAAAAAAAAAJcAAAAAAAAAAAAAAA AA5/7n/k4KAAAEDAAA+wwAAHIKAAAnCAAAZAkAABAJAADxCQAAPwsAAK0 LAAAwCgAABwsAAEILAACkCgAAPgoAAEsJAACFBwAAvQwAANEMA AAIDAAAuAIAAHACAADyAQAAtQEAANgBAACyAQAAzQEAALwBAAC nAQAAjQEAALoBAACuBQAALAoAAKAIAADgCwAAfA0AABYNAAB+A gAACwIAANQBAACvAQAAyQEAAJcBAACRAQAAggEAAEkBAAAOAQA AaQEAAA8CAABQCgAAyQkAAA0OAABGDwAAUwsAANIBAAChAQAAq QEAAKABAAAEAgAAiwEAALYBAABTAQAAKAEAAPEAAAARAQAAUwE AACYLAABVCgAAbA4AAHAPAAB9CQAAtQEAAHoBAAB8AQAAjwIAA HsBAAA2AQAAbwEAAP8AAAAKAQAA8gAAAOcAAABEAQAAdAgAAHA JAAAEDwAA1w8AANMHAABOAQAAWAEAAHwBAADrAQAAPgEAADsBA ABSAQAAHQEAAAMBAAD4AAAA5QAAAA8BAADpCAAAmAgAAGoPAAD GDwAA6gUAABgBAAAcAQAAgQEAAAcBAACkAQAAfAEAAJIBAAD4A AAA+gAAACEBAADmAAAA8wAAAEYIAAAwCQAAQQ8AAK8OAADcAwA A8gAAAAMBAAD/AAAAIAEAAAIBAAD9AAAA9QAAABgBAAC/AQAA1QAAANMAAADmAAAAXAcAAOsIAACzCQAARQ0AACoCAADTAA AA4wAAAOQAAAD4AAAACQEAAOEAAADlAAAAPQEAAAgCAADcAAAA yAAAAMoAAABYBgAA2AgAAMgKAAAvCAAAdwEAAMEAAADPAAAAxw AAAMcAAACyAAAA6gAAAPkAAAAFAQAAygAAALsAAACxAAAAswAA AA4FAAAcCAAAuQsAADYLAADCAAAArQAAALYAAACnAAAArgAAAL QAAACnAAAApgAAALkAAAC2AAAArAAAAKkAAACkAAAAgAQAAGQH AADZCgAAZQoAAMsAAADnAAAAsAAAAKwAAACiAAAAmQAAAKQAAA ChAAAAnAAAAL0AAADZAAAA2gAAAMYAAAANBAAAkQYAAMIJAABZ CgAAoAMAACACAABXAQAAMwEAAL4AAACfAAAAmwAAAJcAAAC4AA AA2wAAAC4BAABgAQAAwwEAAEwFAABDBQAAvgEcBmcEVAHTBAAA AQBdAgILUgSeBOMBuwKBBrsCuwK7AqIH4QaiB4EGAAAAAAAAAA AAAAAAAAAAAAAAAAAAAFwAWQCMAJoA0QAKARsBAwGAAo0BSQHo APAAQAE4AT4B3ADyAPAA8gC5ACcBLgEiARUBMwEoAQwB7gDNAL UAkwCRALAANgGAAfMBhQEtAjMEtQG7Ac8BLwHmAOMA/gDoACcBgAFQARoBeAGmAYkBaAGJAY8BYgEeARMB0gBEAZsB7wD TAT0CDwJsAewDXgRJAfEB7wG4AakBOgFYATsBfwFjAToBLQFSA Z0BpgGSAZUBkgFWAR0BIQEAAd0ALQE9AWkBlwGSARkCkAT+Al4 BOgKFAdsB2QFTAXcBqQGCAcEBUQFnAWMBugG0AZIBkAGqAS4Bc gFUATkBEQE0AVcBXgGOAdYBmQLvA6YB5wEZAm4BmQEnApcB7AG AAW4BnwGSAbUBbgGyAcMBtAGyAVkBaAFIAV0BRwF6ASABIQE6A ecBzgE2BF4C1wBVAgIC4wEHAlECaQHHAesBvgHEARECygGfAbM BxAGPAdIBbgFZAVMBcwFWAYQDpgBPAWsBvgGyASgCiQHRAWACz wEdAgQCOAKNAb8BHAKrAfABmwG5AcwB2wHRATsBiQGIAVoBgAG XAZABzgCuAEsBcQGIAbEBigGtAQACLgIYAtoBagHNAdgBCwIqA iQCywFsASMCGgL0AdsBjQGGAYABNAEzAYsBZwGJABABQQFZAW8 BkgGgAQcCAAItAg4CaAHHAR4CFgLwAfsB/wGBAaABRQKmAlUDvAHAAYUBawF3AVkBhgEyAe8ADQEmATYBQgE 6AbUBrwHRAfMBrwFuAe4BPgIQAvwBDwIMAkkBdQG6AdEBDgKrA ZwBiwFqAWIBSAH3AMsA2gDoABkBFwFEAS0BXQH/AFgB3wGOAXIBYQHlAdcB0AHAAWgBOwGfAY8BlgGkAaMBegE8AR gBSgEPAewAAwHKAL0ACQH4AO4AWwFDATUBfQGBAZgBdwFAAZcB 4AF8AjECjwFxAj4ClwFiAXQBbAFbAUUBUQEAATABCgEdAbUAsQ DlANMA7wA8AUkBTgFXAWMBdQF3AZYBegHdAWgCZwGwAaIBGQKm ATkBGAEsARkBJgH4AAsBEgHcAL8ApQDWAOcA8wDjAAwBJQEwAU 8BNwE3AUYBpgGJAdIBfQHSAcMBLgK9Am4BUAEpAUgBRQFSASAB FwELAfIAzgCiAM0A5wDaAPEA9AAZASUBPAEuAQQBxgBZAUYBew GMAbIBFQKXAoECdgFZAUcBQgEPAfAA3gDpAPUA8wDDAKYAugDN ANcA6ADxAAcBCQH1AAkB9wD0AC0BMAFwAZYBIgE7AlsCVgIdAQ UBAQH4AOkA7gDwANoA3QDPAK8AlwC7AMQA3wDuAO4A7QDwAPIA 8ADoAPwAKgE+AZMBVwHyAKIAcAG1AfIABAEWAeoA9QDvAOIA3A DQAMYAnwCQAKsAHAHGAN8A4gDIAMQA4gDBANQA7AD6AAUBvQCX APQAsQCzAN0ACwEAAewA7QD3APYA6gDPAM4ArgCyAI8AowCzAL EAxQDNANEAwQDIAMwAugDmAPIA+ADSANUA/QAIAQ0BAAHqAOsA5QDVANIA1wDbANYArwCXAKEAiwCVAKMArQC 2AK4AtAC/AMQA0QC6AMYAywDxAL4AuAD1APAAIQH6AOgAygDmANMA1AC8AN IA1AC5AKIAlgCGAJoAlwClAKgApgCiAJgAugCyAKAAqwC2AMsA rgDAAOkA6gDlAN0A0wCzAM4AywDAALoA0ADLALgAmgB7AG0Aiw CRAIwAjgCpAKIApACtAJEAkgDBANIAzQCtALIA0ADHALsAzwDC AMMArgC1AL4AvQDjAM0AvACXAHcAMAA4ADoAQAA9AFMAZABtAG wAcAB2AI4AnQCrAKUAngCsAK4AwAC0ALwAtwCsAKMACQHWANcA vQCcAIAAewAuADQAOAA6ADsAOAAyAC4AIgAlACcAJQAiAB0AJg AqADsARQBPAFEAUABNAEUAQABwAFwAdgB5AHAAZgBRACsALwA1 ADoAOwA6AD8AQwA2ADoAOQAtAA4ACwALAAsACgAKAB4AGwAVAA 0ACwAIAAcACQAPAC0AxQCCAuEApwEJAqED8AL6Ap0CnAJdAoAF rQMqA4UCJQMOBAIFxAQvA5cDCAN8AmIC0ALvAsICpQLbAsoCgw I/At8BkwEZAjICvAKeBIoE6ASUA/4EWwu5BVUEXgSAA5ED2wOgBFkDOgQ3BPQD8gLkAyUE0gOCA7oD vQNdA+QCkwIIAiIDcQPaArUEjwWaBZoDyQkADGwE0QTsBKYEUg S1A0wEQASfBKcDhgOmA3QDUgRMBAQE6APSA18DpgK0AmAC2wIj AwIDygNSBNEDDgWuDNMJfgRpBXsE4AQTBTsEpQQNBTMFfgXqA0 AE0wO1BIkEOQQMBBMEGwMuAwED6QK3AvsCLgNeA8MDRQQLB9MM YwbXBAIFEwS8BJMF5QSZBfcE3wS6Be0EKwXcA9cE3ASfBFME0Q N8Ax4DLwP8Am0E/gL2AjcDQQQ5BIQKYQiAA5cFnATKBJsFIwbmBKAFzwVoBY8FXQZ bBX8E0gTgBH4EjATTA14DUQN4AyQD9gSXAm0DjwMaBBoEHwhzB aIEuAWTBAAFwwUSBqkEcQVjBl8FLAY7BfMEiAVFBQYFxwMnBLM DwgOJA58DdAOuAtACmgOvA+wDdQTZBHcEFwXFBQIFxQTgBMEF4 QWMBusG0QbaBUMEgAVaBdAEdgT/A0kEtgOLA1cDiwMhA5ECRQNwA6YD5gM+BX4EFQUVBZwFEwXFAx 4FxAa6BooGuwYABxYFaAXnBkEHsAb7BJkEsgOMA7IDZgNkA88C xgIDAzMDYwO1A8sEwwQHBXIFmgXBBE4ElwauB38HagfBB8gHGA W/BbkGeAbsBvYE1QRbBOMDqwM2A3QCUwJrAsUCOAM/A10EOwRDBLoDfQS7BfcEygTgBY4HdAeKB7AHzQXyBbIGGQawBZ YFPAWGBM8DbwObAxADlwKbAl0CcAIlAyEDLARDBNMD9wMKBVAF twWABQMFHQdhCP0IsggHB/IIvwgdBmEFLQXpBGME7APRAysDKwPMAskCPAJIAt8CzQIDBCsE XQStBA4FXwVnBe0FwgUYB14I6QjoBzEIIwiaCKkGywR0BEUEAA TtA0QDKQMcA6ICTAIaArsCBQPnAzoDxANMBI0EIAUIBfAEhwXs B/YHUwj+B1MIRAivCD4JmwaMBYAEpARoBEMErgNsAwEDmQIiAicC ywIVA9IDUQOYA1EEnwT0BAoFgQS0A9oHUgf8Bw0IMwiWCBgJAg nbBrMGrAXzBBkEkwM1Az8DEAPXAkMCOwKYAhUDmgNYA6gDLwRS BIMELwXqBE0FUwcgB/EHFwijB7wI3AjXCMEF/gTGBA0EngOLA0ED2gLQAn8CJAItAq8CVwN0A6UDyQPkAzkEbQT PBG4FAAZdB78HFAjYB3MHzQTxBzYIDAVaBQkF4QPXA30DYQMZA 9UCggIqAg4CogKEBCYDogPIA3ADiQOABDsEpQQ1BScGMQa7BLk FNAfXBsUGFwbEBWgFsARZBBoE1gNmAwAD6QKHAnYCLQKbAhcD2 gJbA34DwQOzAwoEjgQQBPUFBgZyBWgEfgT1BfQF/gXyBeQEtASLBAgE1wPCA4IDNwO3AlgCaAIpAlACpwLkAh0DEAN TA7oDCgSaBGAEKAXjBMsF1gObA8EFWQUcBoUFuAQXBIAECASvA 2UDmQNUA9UCbQJLAi4CdAJ0AtEC8wLgAvsC8gK0A+QDgQP5A8s DOQRFA8ID/QQjBUMF4gQ1BHUDAATLA3UDLgNwAzkDzwJfAgsCwAFJAnMCZAK XAgUDygIDA0MDkAIDA4cE7ARCBEUDgAMhBJkEowNCBN4DvgNDA 0gDbgNRA7gDMwMSAzwC2QGZAMwA5AAFARQBogEEAkkCNwJMAnA CMQNrA60DHwMSA2ADpwPMA3wDugODA1MD/AJrBH4DYgMHA24C9wHUAVAAUQBRAFEAUQBOAEkARAA7AE0AbAC KAKoA7AAiAToBjQGlAc8B1QHVAbcBiwF6AVQC+gEpAhUCyAGVA U4B5QABAR8BKAEeARYBHAERAc8A0QDDAIsAjQCAAIYAawBKAC8 AQQA+ADYAKwAjAB0AGQAbACQAUADTAEYCyAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAExlZSB CSwAAAGQAAAD9AAABHgAAAP0AAAEeAAAADAAAAAUAAAEOAAABD gAAAAAAAAD9AAABAgAAAQcAAAEMAAABEQAAARYAAAEbAAABIAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAACKNtAAj5xQAJnGgACo51AAu uXgAMpDgADXBmAA5FQQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEe2 7ABMj3AAUjA0AFbBEABZpmAAWausAFimpABZQkQAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAABigfAAaUawAHEeQAB7cdAAi8QwAJxSgAC nyWAAr/xwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAB4UbAAg/WwAI8xgACaz0AAq54gALwDAADHrmAA0TmQAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAACSNnAAnpZAAKxe0AC8FWAA0CjgAODEkADtLpAA +eGwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA7zBAAQCygAETiAABT 0TAAbOcQAIQFEACX2uAAqw4wAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAX0DAAGogQAB2yAAAhbKAAJmdQACvFwAAw9/AANZ0wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAaLFAAHHZQACAkQA AkpYAAKp3gADIdkAA67sAARQsAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAABB+lAARwOAAE6zIABYtlAAZrXQAHTqYAB/fKAAhu3QAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAASAAAAEUAAABIAAAAS AAAAEgAAABIAAAASAAAAEgAAABIAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAEAAAAHAAAAAQAAAAEAAAAB AAAAAQAAAAEAAAABAAAAAQAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAEAAAABAAAAAQAAAAEAAAABAAAAAQ AAAAEAAAABAAAAAQAAAAAAAAABAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAaQAAAAAAAAAAAAAAD0AAAA9AAAAPQAAAD0A AAA9AAAAPQAAAD0AAAA9AAAAPQAAAAAAAAABAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAORUEAFmrrAAr/xwANE5kAD54bAAqw4wADWdMABFCwAAhu3QAIo20AEe27AAYoHw AHhRsACSNnAAO8wQABfQMAAaLFAAQfpQAORUEAFlCRAAr/xwANE5kAD54bAAqw4wADWdMABFCwAAhu3QAAAGQAAABhAAAAZA AAAGQAAABkAAAAZAAAAGQAAABkAAAAZAAAADwAAABPAAAANwAA ADkAAAA6AAAAIgAAACwAAAAlAAAAMAAAACkAAAABAACCNQAAAG kAAABQAAAAAAAAAQoAAABOAAAAqgAAAQYAAAFiAAABvQAAAhkA AAJ7AAAC3gAAAQoAAADWAAAAqwAAAIsAAAB6AAAAeQAAAI8AAA CnAAAAAAAAAAAAAAAAAAAAAAAAAQ4AAABFAAAAhQAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAASVBDRAYAAACQAQAAoA+4CwEEEEAADBAE8BEAAAER28 B5BFNlcCAyOCAyMDA5LCAxNzowMDo0NQBNYXkgMjkgMjAwOSwg MTQ6NDk6NTUATUQxMDNMAAAAAAAAAAAAAAAAwBvgEtAi4BIAAA AAAAAAAAEAAAACAAAAAgAAAAIAAABgAAgANwAvAOgDAAAAAP//AQAAAAAAAAAAAAAA////////////////AAAARCQAAAD1AmQEXQIAAAXxCgBMIBkA+XUHADEASQAlAB8L4Q/0CAAAAAAAAAAAC////0kAAACRSwAAhgkAABEAAAAIAAAA+////84jAABpCwAA3QAAAP//AAL///8B////AP///wgDAQIC////A////////wEC////AwsIBAH//////////wAAAgAFAC0AIQASABUADQALAAEAAQACAAMAGAAAACoAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgADAAwAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAUmVsY XRlZFNvdW5kAAABAAAAAQAAAAAAAAAKAAAAAgABAAIABAAAAFI 5OAACAAcABAAAADAxMDAAAAAABwADAQMAAQAAAAYAAAASAQMAA QAAAAEAAAAaAQUAAQAAAAxLAAAbAQUAAQAAABRLAAAoAQMAAQA AAAIAAAABAgQAAQAAABxLAAACAgQAAQAAAHcPAAAAAAAAAQAAA AEAAAABAAAAAQAAAP/Y/9sAhAAIBQYHBgUIBwYHCQkICgwVDQwLCwwaEhMPFR8bICAeGx0 dIiYxKSIkLiQdHSo6Ky4yNDc3NyEpPEA7NUAxNjc0AQkJCQwLD BkNDRk0Ix0jNDQ0NDQ0NDQ0NDQ0NDQ0NDQ0NDQ0NDQ0NDQ0NDQ 0NDQ0NDQ0NDQ0NDQ0NDQ0NDQ0NDT/xAGiAAABBQEBAQEBAQAAAAAAAAAAAQIDBAUGBwgJCgsBAAMBAQ EBAQEBAQEAAAAAAAABAgMEBQYHCAkKCxAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2 JyggkKFhcYGRolJicoKSo0NTY3ODk6Q0RFRkdISUpTVFVWV1hZ WmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpK Wmp6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl 5ufo6erx8vP09fb3+Pn6EQACAQIEBAMEBwUEBAABAncAAQIDEQ QFITEGEkFRB2FxEyIygQgUQpGhscEJIzNS8BVictEKFiQ04SXx FxgZGiYnKCkqNTY3ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaG lqc3R1dnd4eXqCg4SFhoeIiYqSk5SVlpeYmZqio6Slpqeoqaqy s7S1tre4ubrCw8TFxsfIycrS09TV1tfY2dri4+Tl5ufo6ery8/T19vf4+fr/wAARCAB4AKADASEAAhEBAxEB/9oADAMBAAIRAxEAPwD3SKHAqYJigQ8DAoZggyxwKAMa68S6bFK YjdRLjqxbgf402LxLogORfwlvUtSAkPiHRHIJv7cN6+YAaX/hIdMUZj1G1kHp5yg/zx/KmFx8HiHS5shb2EEdQzgGrSanYuPlu4T9HFICVbu3b7syH6NSv cRIpZpFAAyTmncZCJBc4YnEfYetTArjAIpCDI9aacUxjSKYy0A V5Rz7VUnjBBpiNxRTqQDGkAO1eT7VyXxG1B7PTo4FkIknJGFOO O/+fekBwmnabPeK75OB8uTzUV3BHZNiWaMH/exUzrwg+VmkKEpq6IbloGRWiuouPRhVUbGfi4jx3+YVLxMLlrC zJ57i33YW5jzj++KZ9ojXpKvPoav28WQ8PJEdvdyNKd7BVHQ7q sNfBc5uF/77FJVUwdGSHrq04/1V44/3ZKU69qcfKX1z+Eho54i9lIafFetR/d1Gb8Wz/Oj/AITnXk+5fk/VVP8ASqunsS4tbm54Z+Jkgu0ttcC+W5wJ1GNp9x6V6irB0DKQQ RkEUCI5FyKrSJweKYGoWCjJNN+eT/ZWgCRVCjgV5n8TLnzPEVpa5HCADPYkn/AUAzE8SXBhuY9HjfECxB5AOC5zjBPp3P1HpWHLYWe/H2dMH2qaS0b7sqrLVLsivNZWgBxbp/3zUf2O0E6qYEHHPFaGdyzNaWqrnyU6elVI4IfNP7pfXpTYIc0U K4BjX8qc0ULLxGv1xSGV/s0GCSn61Unt4hyu78GpMaZA6lR8k8qn2c1JYlzdxR3NxmFnAYs uSB9RUOEXsaKrLrqWPFEFtY3yQ2c4mBJDEZBUjsRXuvgK4a58H 6ZKzFm8hVJPtxRFqUU0TNcsmmbvUVBKMCqJLqRYOXO5v0FSUDC vHfGkwuPG1wrcqrog/AD/AOvSYHPTSrLqd1cNy3mFBk9MAD+lIkxZ+e3SlR/hxKr61JepHJIOueQKZvDglh16VpcyHI2EEeScDGT1piRuGLBSf woew0hwguJgdsLEDvjpTCu3Kk9RipuOxWmfGVzVKUkqeenFAFZ sh8Z4NKBgEkcigC1rreZftJjiRVf8wK9u+Esom8EWYPVGdf8Ax 41nS+BI1rfxGzqyMcimOARWhmW6KAEJwCa8RuG+2eLLxs5zPIR +BOP6VFR2i2VTV5pHN28gkiMo6uzMfxOasRcNnPanSVoRXkFb4 5erEJBcn8Ks6TZSaheJBChODlzjgCrk7K5CV3YueJrvStFEaad bveXLZyQfkX8efyH51zUmsa7OSUW2gUnG0IGx+ea51Fz1b0Ojm VPRLU07PUNUg8L3cn2lhMZlUOFG3HpXPN/asTGUTrPk5Kv/AI0U46tBUekZdya1vo7pihUxTjrG3X8PWkLdc960T6MykluipI CGyaASVKk81ZBcnV5LO2mk6bdmfpXrnwWvUfw3LbFxvinJ255w cGs4bNebNKu6fkj0DIpj9Ca0My3RQMjuXEdtK56KpP6V8/C6khW8vF+8qMc+5rKt/DfoaUf4kfUzLdsW8Y6EKKlhdtp3EZ9q1Whi9XcRiW4QEsx4x3r f8R3H9h2Fvolk2y/nTzbqVTyinjH1PT2A96znr7vc1pq15djn1cJAsC4KAcE9ajYjH FUklsRdvcdLOU8P3kKglvMV8jH61Wh3m2XNZw+KRrP4IlS8txO ox8siNlXHUGpInM8Ds4xNHxIo7+4q5aakR1TiV5DnkDvSZweeu Ksg0DIW8MIrfejujz7EV6P8FFiuNNv4pFBKyhgehGR2P4VlTVn L1/RG1V6R9P1Z6HsuIP8AVN5yf3W4b8+/4/nSx3iOSjAo/wDcYYNaGJq0UxmZ4pn+z+HNRlzgrbuQfwr57vLhhp0qKf8AWMq n86zqq8WjSk7TTIUlIIB6CniUHrgVoYmh4XKza7a+Zgxo4Yj1x zVHVdQbU/EOoagSSskxVM9kXhR+QFZ7zNlpTZAJBnmlD9KtmRMzQ/2ZeLMzCRkGwYyCc/Tiq8Mg+zr7AVnH4maSa5IorltxbFJE3l3Mcnr8j+4NW1dWIi7O 4ydSszJ6GonBHbmmnoOSs2iaKUnTZ4Tzh1b+lekfAtyLjUoif4 EP86iO8v66Iqp8Mf66s9Wb2qGaJJk2yKGHvVmZp0UxnM/EycweC78g8sFT82Arwi5UiyjY9GlA/wA/lWdR6fd+ZpTXvfJ/kV9459hUto0CzK91C0se0qVVtpGe4PPNaGRe027jjubGOOFY3i BVpFP+sz0yOxrJjPlK6HqHYH86y/5efI0/5d/MtaVHbXGoQx305gt2OHkAztFSajFBZ6jNDazpPCjnZIh4YVozM 2pde0n/AIRJrL7Af7QIK+aDwR61yUZKx7Sc1KVmO+gYxkkEZqSHDyxxjq zAfrVCH3ht47zUI5fMEy/LEVwRu96qMdrn59w2jkjGD6VMPhRc/iY+y2mK6RuGMYYfga734Gz/APE9vY/78IP5GlH438ip29nH5nspNRuePQVZkaFFMZwvxnuvI8KLHnHmz qv5ZP8ASvErmZ/JgTnZvLfoayqdPVGlLd+jIS2MkVIrfID7c1oZAspWVZE6qQamv 1DS/aYv9XONwx2PcVEtJJmkdYtEIccA8U0uOoPeqMxrupOKDtAHNAF 2xh+2wSozDcgyuTitLT9Altt2o3I22tuhkLepHalN2RUFeVjlT I88sk8n35GLkfU06UEAetOKskgk7ybJtPAe9WMnAdStdf8ABeb yfF3lkf6yFh/KpXxv0/zLf8Ner/Q90NRMAQc1ZkNt9TaCYWuqARSk4R/4X/wNaYIIyKExnmHx4udthp1vn70jP+Qx/WvIbibAt4/QE1nNXt6mlJ25n5EauS1K0vIHtWpkDH7u3pUtnerBvhuwTbOc5 HVD61E1dWRdOVpaj762aErIuJImGUkXkEVVRso1EJcyuE48rsO yCODzS43OATgY60yTU0bTbi9uB9nOIurS9ABW74g8XWTQRaFp4 aaxhj2z3DncZH9vYf56Vm5cz5UaxjZOTOLnZGuGaMYQnionYsx xWqMgglMd5E465rqfhdL5Xjaz/wBosP0qft/I0f8AD+Z9Ak1FKeOKoyEuLNNXUfbI/wBwOUUjk+9UFlvtBfbPuubDPDjl4x/UUnpqM84+NuoQ319pgtpFkQRM2VPqR/hXm+pgR3YA7Riok/ej/XQ0gvcl/XUiVgo60j9ck1qZgp55oZsg5oAjtry7sCxtHDRk/NBIMo3+FW49X0qbi9tp7KQ9WQb0/wAf51jKDT5oG0ZprlmSo2iMNya1D9CrA/yq5Z3/AIYtstc3M1zIBlRHGcE1PPN6WG6cFrcrXet3WpRvDua1s8YSGM dR/tGs4YRMAYFaRjbUycm0kIX4z3qMSYOTVkiFyHVx2NdD4GlePxj YMuBmbH86l/EX9h/13PooE0O3FWZmlnimlQ6kMMg9QaQHg3xQEOk+PFkto1ZRGrtE/wB05zkfpXF6zqK6lemQW6QbcD5TnP6VOzSLS91sqI4IzmiSTjA HSrJI/MJwelSKwIwetAASByajcKVxikBmxxxf2oUYfLtzjbxWqkUS42K B+FAEgbaRUczelADQ3IB6UjHA6UwI3f5elbHhuQReKLFiTjzVP HWofxItfA/kfSwb5AR3FRyPgc1ZmauaXNID55+Ls3m+O7of3URP0z/WuJdNskinrn+lT1RcfgY0/Jg0u8nmrJEZQRxTJiURTnmgByylhyfxqTIxwQRSAjPLZwPrTyc DIoARZMtgUO2SKAG/jRnA5oAjkPynFX9JYprlixBH7xP51EviRpH4JH07E2YIz/siobh+DitDE2VOadnigZ88/GO1e38b3EjAgTIjqfwx/SsWxtNI1GIvPqsdlcAYKTKcN7g9KxquUY80VextQ5ZXhJ2uSXn h2FbdJ7TWtNuAeGRbhAw/DOf0rNl0y7TCJAz5OBsG7P0xShW5tGrFVKDjqndFdreVZ/JdSrjgg8YNR3kDjMbjawrYwIViATa/ORSoAFCIcAdKBCM2BjvQGJzzQMVFw3WtCxg097Wa4vr9InjICw 4O5/cUnsCI7i70jf8A6PFcyD2wKlu20mCxhfypzM5yUDDIFZJ1Wb2o q2tygmoWccweG0mbacgSEY/GtXw+Z9d8XWpaNQzSKSsYwFAojCfNzTewTqQUHGC3Po/cEjVR2GKp3MvHBrc5jeifIqTdQBz3jDwhp/im3VbsFJ0+5MvUV51d/Be53HyNRiZewZaAMy4+DWrdFmtz+lRQfCjxVZPmxvFhI5G2TFJ pPRjUmtUV774Z+Nbud57u5jmkblmeTJNc/qmh6npc4gvYFSTp14JoegIzriGeHiSMiqAvoAxBYA0XGXIopbh Q8KBlPQ5q/aaHqFzzHAP++qTdgLyeEtXYYWBf++xViL4f6xcOAVhUE9S9LmQ WNVPhJrGATc2wH1qR/hFq87bpdQhZgMAkk4FWK46H4M3xf97qUKr3wCa7jwj4I07wuDJ Dme5I5lfr+FAG/JITVK4lwDzTEf/Z/9sAhAACAQECAQECAgICAgICAwMGBAMDAwMHBQUEBgkICQkJCAg ICgsODAoKDQoICAwRDA0PDxAQEAkMEhMRDxMOEBAPAQICAgMDA wcEBAcPCggKDw8PDw8PDw8PDw8PDw8PDw8PDw8PDw8PDw8PDw8 PDw8PDw8PDw8PDw8PDw8PDw8PDw//xAGiAAABBQEBAQEBAQAAAAAAAAAAAQIDBAUGBwgJCgsBAAMBAQ EBAQEBAQEAAAAAAAABAgMEBQYHCAkKCxAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2 JyggkKFhcYGRolJicoKSo0NTY3ODk6Q0RFRkdISUpTVFVWV1hZ WmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpK Wmp6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl 5ufo6erx8vP09fb3+Pn6EQACAQIEBAMEBwUEBAABAncAAQIDEQ QFITEGEkFRB2FxEyIygQgUQpGhscEJIzNS8BVictEKFiQ04SXx FxgZGiYnKCkqNTY3ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaG lqc3R1dnd4eXqCg4SFhoeIiYqSk5SVlpeYmZqio6Slpqeoqaqy s7S1tre4ubrCw8TFxsfIycrS09TV1tfY2dri4+Tl5ufo6ery8/T19vf4+fr/wAARCAMABAADASEAAhEBAxEB/9oADAMBAAIRAxEAPwD9ooLc5BGauQ2+cc8VqzNlyCLC/XtVhYehzSAmROKkjix3NAE8anAFTxpmgLkyp2pwXNQy0x2zNKF 5oFzC7Mn0p4XmmkHMSImPap1XipHcdtNKBjvQFwxxS45oGB4ox QFxSKAue9AChMd6XbQABeKTy80ABXApjnFAFW4uAikA1QuLgk0 AVnyeT0zVTUdWhsIyXcD09aVxXMKe/u9el8qJWjjPHHU1veHvAa24V5vrirWmoX1Omt7RLdAqAKB6VMF 49KTAVfensgccjNIZR1Dw5bakhEiA1yWufB+ORzJZu0TU0wMdG 17wVJ/HPCOx6VvaD8V7a8IjulaB/fpSA6eC5t9Tj3RSI6npg0PYEcqaAGq0lv64qeG+BwDQBYSVXHB FOoAKKACgmgAzijNACFtpppbHWgBQ9OoAKKACigAooAKKACigA ooAKKACigApMUANbrUUjhAeaAMzUdSCA1gajqZQFi3FAGBdX8u rTeXHuAPHFb3hnwgsAWSUZb3qou2on2OnhtVjUAU8JjjNSMXZx 1pPLzQAhXB60jD60AJjI5oxzQABPlo20ANMeR1pClO4DSlNZKQ DSMD1NIB+VADSuRTGTHencBCue9NKe/NFwEKmkKYXg0XARV+tBTjFFwGNDmmFOBT5gApgc0wx5ouK7I3i NNSLFHMAySHBzUTRccmmpC2RG6jdwaa4LDiqUgbKkqnJBqMqT3 NNMVyvcQ4BOapzqVyKUpAiq8bEnrnPHtULwkg881UZaWHzaWKs 8BC9c81UlTJ71fPoCZVuLcEVm30JTH14pKY0z1y3jx0q5FFn0r G5my1FDtFTJHuxQJKxKIvxqREI4xRconSM1JGm3ipuBMowKeq5 FS2ABSBTlAIz0pgLt9OlPiUGgCRFAqVBQA/tTeaAA0bsGgBetKaTY+gA8Y4pemaNQuKOlHUUyugvekyKAuRyT hB71TuboscDpUNktlOWUuarzTLEpZiBQIwtV8QSTt5doN7dC3Y UzSfBtzqkoluC2euTVRiOx2Gk6BFpiAKo3dzWgqY6VTYWHbaMY pA0IaepyKBpi0UFEc9tHcIVdFYH1Fc/rfw2sdVDFU8tj6UAcxdeC9W8MTGSzmdkHbNW9L+J1xYSCLUYGU jqwFQ9CNjqtM8TWesxgxyofbNW2tVcZU80RlcaZGY3i6Zp8d6V +9Q2STx3ayd6kDgjrVXL5hc8U0nPai4PYTdkUE4pX1JuN3fSjz OPWqGxVOcU9enrQULRQAUUAFFABRQAUUAFFABRQAUUAFIzYNAE M0wT2rL1DUsZA/nU3JuYOqaoIlJdsVhBZtcn2oCEzRuwudP4f8MLZIGZQW+lb0UQ RcAYp36CT1H7dooxRcdxMZNKy5pjQ0jjvQFwKBiFeKAmR0oAQr gUmNw7UhMOlJwTTBbCMuBTGFJMExjd6bjPamDQ1hz3pp5FAXG7 eeaCmPegGIRik20AIFxSEAigBMU0igLjCuaQjA5oE2MKnHNNMe PrTuFhCtQyp7UICrKhRh1qJpNvWn0ArTyBzTQ3A4ouSRzKWHFV ZYuCaGOJWkTBPFMePJwc00DK1zab+e3sKpT2xQ9+tMSKkkZOeB 71SvbXfnkilexSPV4Yxx8pBq3HDkDFIz3LMMfbrUyx9OKdxkiR 1Ki0DJUWpFXPT+VSwJFiJNOKHb71IAuQPmzSxLuHB5oAesZoCk GmMlTJ6ipE6UCHZpCfakMD7UA5oBC5o60NDsL0NKG5piF3ZpCc UmDY1pgo5NQTXY7GouK5TmueetVpboK2SRTVhqxmar4ngsAVLb pP7o61lW0d34nuMHKxH+EUR94GdVovhSHT1BcBm/lWwqrEoAAqxpgHB5pwkBpXBbB5mKQyCgLgGDGnqfrmi4rjgc0U ywooAQqGGCMis/VfC9nq6ESxISe+KAOT1j4XSWjmWwlZCOwNZ0Xi7WfCkgS6iaaM cZNQ49SWjo9B+JtjrChXYQyHs3FbqNFeJuRlYe1SmSRyQNEcrk 0iXjRHDVdtCraE8WoBu+DUonBHFCBCh+fWkLUdQ0EpwXNNAh6r jtxT6EMKKYwooAKKACigAooAKKACigAooAaWqCe5EYznmk2Jsy dR1QjIBrA1fWhbqSTk+lRJkvUzLOwn1+cFs7c8Cuw0Xw9Hp0Q+ UE464qlogZpeWFFOAxQtRoCaByaLBYD0zSEUxjQCeKUChAhccU YpjEIpoHHNKwrAwpuMe1MLCEUx+KAIzjNJigENII6Un8NJgxuM 8CgnmgLCAAikVd2aYxNo60hXFAmMPSgDNIQhAprJgUxjTjNDKK YJkbrnFQSKRQBBMuT15qjKhyaLkpFZkGeKFG31ppiAnOe1QulU CIZI8545qB05IP4VN7FWuQSHnmoZUD47D6U1cTKVxbhc4H6VSu Ih0zSaGj1yG255AqxFbgDFF9SLE6QjHaplgxxSbGKsOMVIsAoT AekIXtUiJg0gJQvFKAMUDFSMSUgZYHIbC+lTcRKBupNgzVIBVX FSIPwoGOccU3FKwMMUm3BpgLSgZoGwIpO1JiYbsD0qvPfKgODz UtiKNzqIB5NULzXo7dSSwA+tDYzm/EXxNtdGgeSSRUUd2OK4W7+M134qmMWmKVT++RyfpWd+Z2DlOk8 JeHLy7VJ71iCeSCea72wuEs4wqKFFapW0QMujWCDTX1vH1pCGJ rxNP/trg9KQDTruDTxrII4poBP7bCNmpYtcR6QE8esLUg1VCKrmGmMG rKxIqRdSXFK7DmY4aimOtKNQjPenzD5gF/Ge9V722tr+MrIisD6ihsGzjfE3wvtbzdJbN5MnXiuPvtU174fS l13zQDr3pNXQdC7oX7UGmvOsOoYtnzgk13ukeMNN8RQCS2uoZV P91qhSFZlplXGUcYpI7xoeM8VYMtW+oK+M8GrPnqVzkH6UhDfP B7jNPWfI68UwJFn96d52e9Fx3FEopd9Vcq4u4UZFFwuLmjOaYw pAQaADIpc0AAOaKAEJxSbwKlslsRpcU1psDrxRcLlS71ERA1ia lrZTPPFSyTA1PxIoG1DlvSo9H0SbWLgPJk80RV9RnaaXpEdjCA oGfWroG2qbADS44pahqJ2pQD9KYwooATAzQeTTGJ0PelHFACHr TSOc0ncTuBOaTHtTBjW69aYeDigYwgECmlKECE2kUhGaSWhPQN ozTStMoTbx6Um0g+tMLiEelNNAmNzkCgLQOwFcnNJs+XtigVmx joAc03HFAxjRVFJHmmJMryx4qhdKSD1osHmUzHzkninEDrT2E9 RpQ4xTGXJGaGxojlTgc1A659aEDIJlAznFQMwY46+lFwsQSKM5 xn61SvIscii4onr6Q4JPSpki4pMVtSVI8VKicUAPEYz0p4iwKQ D0SnBeaTAeq04gGmMq3UM8RBhKnPXNWEhM0I8wDd7VLWgh8MHk rgEn607bzVDFC54pwXFA+UU8ikIFAPcQjIpMUkKwoXNGMimDQp 6ZNRyzBBzUsRnX+p+WOvFY15q5bPJqQMTWPFsdhGdzDI689K8f +Kn7Ten+G2khglS5uugVW4WsZyu7IaPPdC1fU/ipfie9nMVtnO5zgAewr1jwprPh7wFZ5a5hZwOWYitVaCCTsbaf tEaAtupN9bj0+cVDe/tN6Dp1sGe/gZicDDUOelyS4f2jdBjt0dr+3BI/vim/8NDaDcSbV1C2z/vilzoTuWU+OOjDGb6Af8DFPX426NK4C3sBJ/26PaJME9Sf/hbulNgi7gP/AAIUsXxl0jeF+2w7v98Uc6Q1csSfFHSnGBdwj/gYpE+JunBgPtUR/wCBCr5wZbi+J2mqB/pUQP8AvVctviJYS9LqI/8AAqXMiUxsnxCsYJR/pEZB75qXTfiTp+pM6pcxEqcH5qLobZe/4TCzOP38f/fVKvi21/57xn8aLoEx48V2zdJozx608eJID0lQ/jRe40x39vwMP9Yp/GoLu6s76Mq5jYH1pjucD8QfgfoXjOB22pDL2ZOCK8W1z4U+Lfh ZfGfQ9UllgU5EZbrUSgpFRkSeHP20tX8GX4tPElhKFU48wD9a9 o+H/wC0h4c+IUCm21CJZccozYOahNxeonodxb6vFKoZJFYHuDVpdTA H3v1ra6sS2J/aoJ+9zT49WIB+aiw7ksesknrUo1nPcUguOXV89+lOXVuOvFADl 1UnoaeNVI6mmFxw1X3pf7U6c0rhcX+1uaX+1RkUAKNTUd6F1NT Tux3ZIuoKB1pf7QXHU0JgmNa+BBwaZ9vUnk/rQAjX6gdaqXerhAcHikIxNU11I0JZgK4zX/GqzTmGB1Z89j0qJdgLnhPQZL+YSSEnnkmu90+3SyiCqAK10SBF 1bjjrQbjPfii5VxRNu+tHn4oTBMUT5FKJxQkCQpmB+lJ5wPWls LYGkFJ5w5ppjTFEooEgBFAAZRmk3A96OgdALDpSF6E9AT0Gk88 0hosFtBCBim/rTBCZyKQjNCBIRkyKaV45oGN6deaD170wsMfg+1IRkZzQAgHPa jGelAXAqcUmKAuMkFMU0AI/emNxTTEyCYZFU54QTkU0wa0KUsJyMcVGFKkDrTsQhjKxI6daRx nnBqbDu7EMnHSoZMqTxTKW5DJh+tQvCOSOaVw2K1wmR61Tvdx4 H4UWBPWx7GifN7VKq+g4pMkliTBqVY807APWPApwTmkA4Kcc0/bkUmAvpilIyppodgUU4ClYQYopjuOUk0ooBMWkIzQWNbINJQQx QcDFNaQKOTxUgyGW9ABArL1LVhEDyM1LEc3q/iMQbmZvoK8x+Kn7QGl+ArOR7u6RXx8sSHLN+FZ1J2WgmfMfxd/aq1LxjI1vaTm0tj/AAxnlh7mvMJ/FE6xvdAbmBzvc5rSlS0uDnymRqvxn8RRIYYrt0XttboKxL74m6 1fsUe+mIPXL1r9XvqTKavoZE3inVZnI+1z7R/tVWPibVSrb7yc45XLHirVGwOrYq33j3V43ULe3G7/AHzxWe3jzWoZzIt7cjH+3UuimEZGhY/EnXmgz/aFwfT5jU9j8UddtZVJ1C5Bz/eNU8MilNM03+MfiKSRRHqNx9N1Vn+KHiNbsONQuC2eu41Kw5PP Ysj41eKRKSdTuCOmNxq7bfG7xU7Kp1GcccYY1pDC8wpVUtx1x8 cPFwlXbqVwBnjk1Nd/tFeM9NjZv7QmG0dMmplhHFBGrFjbD9qfxfc4El/KCBzljVnRv2jvF2lTu0V/MQ5yfnNKOFbE6sUrlq4/bE8cW67Ptch445NQL+2z45SJFN25Pf5qX1Vpj9rFGi37cXjWKA OLlyB1+arOnft9+MwozKfUnPFZug07DjJNaGtb/wDBQDxaAG3kjvU8v/BRXxMNoUNx156050ZFOSuXB/wUe8REKm0571sW3/BQbV72BRNb+Z68URoyDmiY3iv9qaHxhHIl3YrlgcEgZrzZviK9 ldvcadNPbOGyMEjH5U/ZPqJ1InoHgn9uLxd4PdIjdm8t14xIc/ka9N0P/go/dPGgurZkfHPek6LRMZpl6X/go3HA/wA0bAk1dtv+Ci1pIOQQcetRyyuUlqXoP+CjGnoo8zK4681o6f8 A8FEtJuMEsBn3pWaDQ17P9v8A0SZBmYLntmtCP9u7QmIBnX86L MEtDStv23fD7x5Nyo/GrkH7anh6UqPtUfPvSbYbmlD+114emH/H5EPxq3b/ALVnh+fpeRY9c0XaKZbP7S+gtt/0yLn/AGqmg/aI0SfGLyHB6fPRzCLUPx50Vj/x+w/99VdtvjRo864W8iJ/3qdxl2L4qaY5AF1F/wB9VYT4jae3H2qPP+9S5xJj/wDhP7I/8vEf50Dxlay4K3EZB/2qOcdx7eKrdhxKhH1rE8S+PLXT7Z2MqKB1OaUpBc8V8b/Hk63qDWmnyggnBfNdL8MdDe+CzzOcepPJpxj3FKWtj1jT76Oxg RU2hfrV6LXFI+8KoNiZdYB6NSNrOG60xksWrZA5FOOq+4ouO4i 6r6mn/wBpgHrRcV+gf2qM8VINR564pAL/AGkPWj+0F9apPQpPQf8Abh60hvxnrSQkH2wHvTheADrQDAXQ9a PtQJ60XC4hucDrQLoZp2HYR7oEYzSJcY680IFuL54zxQJuetML 2ENxQ02OmKBMPMBHqKAwIoZVxHXIpgzj1NMVxV60/aBQJhjFMYYPFBT7DSA2f8aaYaaFeyGOu0Uwpk8HFIRFLHkGqzx U9gbuV5oeDVWSPDYqkxMikGBmoncY60noBG2D7c1FJ8w45pXGk QsnOM0xkoY0iGWEEHNZ97FgE4ANNIdz2ONexzUqR8VJBKicelS IPwqkwJAtLtpMBQMGnBce9S0PoOxnFGMGmDFAo70CEpO9ADl60 4UDQoooLGlsdaHIAzQSQy3ATPeqstxuPWpbugbuihqF8LeNua4 fxj47ttIgkkkmRFXlmY9KynOxJ8y/Hb9sqDSo5rXRW8+fBBn/AIR9K+RvE/xG1Txl4gkuLu6lmkc/xHNKlHm1YPYSPXodNmdrhgxC5ANZ3ivx7nTEjh43N09RXYuxhN 6GBJ4lkuYpWLYbHGaTwzdS3dvLK7bgrc8V1UlbQhytEvX10XQF cAY5wKzjqLR3DL1B44qmtbBG7WpXj/0iZvb2qve4hgI9qzcbMqT0uLpBPkYPHPArbgtVkhz0+XJraV2t DGMrbjdMiSGAscg9iamhjQhSMccis5KzKjK6G2unnyZJm43PwK v2flqxbbyF9K1pOxNVczGTXgtV5AbHP0qneamGUSSAFTxiirIU Ys57XdUSNJJUBAB7f0/KtfRdUH2aAyLn5eTWdJtsU46WFvtYj8045bGKwJr1o5tpABrSd 2wjZaj73UltoAjc9yDUMmpqqBduBnP4VnNFUmzRtb5DaL0IxUU 94sQViOPeptrqVNNaEFtdG8vdwxiux0TDbIyMcDmtI7kQbav2L ut2ItCpDAkjtWJ57xxsu3knrWzimrEOdyBJ2jj3Ejdn1q7b6gN 3zkZ/lWaika3dm0R3moC6kCD1qGGQi+GGJxxWfLrYpTtqQ6jeNIZFB5 FQW9+0EeMnA71mopg5djU0e5eYbt3A569K1VuSIUfdg1UaaaJd R2IBq74I3EY689KR9algUESScnruqZQRUW9mWrbxNMiKWmkHf7 1WB4ruojtFzLk8/frCUUdMW73HT+OLwMmLqZBnj5jSp8Q9SinAS8mxnA+Y0lBPQzc maFr8SdUckfbpx6ncauWPxZ1e3Y4vpyM8fN1qvZA6jNm3+NWux xIwvpDkZ5NSxftC6/abj9uk/E9KmpQCNTTUlh/aW8RtCzJeN+JqxF+1b4js1QC5ZvbNRKiac0bGlbftf+IPM2+c2 cdN5rP8S/tI674hj2S3LrGTjAal7AlVFa5jeHfjDJpOoeZIWYg5616hon7Z 95YWiAK2AOAKUoNMFJXNe0/bvuIziQEZ681oxft6+UiEj/69RyMu5rQft7W4QFnwe9Xbb9vKxlVSXAHuaTi0gvoaVj+3Lp8z qDIoGPWti1/bW0hwMzp+dLVDNCD9sfRZVyblB/wKpoP2v9EeTabmP/vqiMriT1NO2/ak0Oc5F1H09a0rL9pDRLjj7VH/AN9UcwzQi+OujzqWW7j/AO+qsRfGnSnYD7XEM/7VNSuBcg+K+mynAuo/zq0vxD0+U8XMf/fXWquFyzD45s5EyLiP/vqpR4ttyARMmD70X6AOHiqBiB5q59jSHxNED/rB+dFwHnxJESAHqRdfjOfnGadx3Gpra8ksAPrT49aWbkMMU2wb JF1YdM046sAuSaQhV1MMOop/28Gge5Il2GHXin/aMkGmx9CSK43DmpVORmqGLjml6CgL6iD3oNAm9RNnekYYoBoRl yKhf5TxQGyI3XIqCSPB4zTBKxE8YPWq00IPbNOINFS4hxyOeaq OPm6daV2DQ1lwuaQ46YpBYikTBNROuc0DInXjB6VSu4gO7CqQm evxrk1Mg9hSJJUXBp4TNDQDwtOCjFIfQUKFpQMUAKB9aXbxQVu G3AowMe1BLE6daOCeaAFAxSigasLRQUMmkCDmqs8+7vgVLZLZW lmweuTVeaXYC36VJJ5f8afjHbeCtMk5824IO2NT/Ovkzx54k8VfGW8mUNJbaehJduVQD6965o+/Majpdng3xN1e2tL19PtXEwQlWk7sa43V3TQbfeMGQ8gV1UmuW6 Iq6M4+/wDEEt/fM0jE544q1eTmW4t4zkgrnPpXZFaIykLNaeTZsyk5zke9X/Drm00sqQSWOa7IpKVzF+8jZmQTWyAL056VhshEkr7gAD9KGnzC UvcsRwzL9sdyOMVFe2xur1VX5gf0rBX5tSnrHUuW+keVJ6jHNa luUgtTnk45roemxEUmhBCJrbj5eKrLDLbSqG5G3PNQ4ahGT1sa +nKslhknk9MnpVi304R2xY5bnFVBakz3KOpQAuQvTHTFYeqtsV Mjnr1qa8bKxpTUm7mLqsI2bSAA3FOa9a3sY1HQDpXJTk+htLa7 IrfUUkmLcZz0p+wS3e7PHeu9vRHM0RalAWnLnpgADvWRqN8YmA zgA4NctRNGystjRhuCEUDODyBnpTbrVftUxiJ5pcw0tRLBnttT +UfKDgV32gTGRlIBxj0renG+pm9E0XdXSTcrE5HYVlIxe6Y447 YrddjBakOoRCO03DJbd1qlPIYwvbjjIrJxtqdFOXMiOeZrWMu3 IC0/R737Q6tn5i1ZvSVzNX2JryF0mnOOPUfSsY3EhjOMj8OtDir3Rp Fu1madhqDQ2oVc5PGKvx6q0mxCTtWhPS41SVrliFgsEjnA3dKr XMhxnIAx6VjN6XEk7kL6idinOBTpdVzj5s4rF+RtF2RDf6osaJ zjmkh1MmZWznnoOtNO2pN7tov2+omRto4BPep4LvzGC+mcehrW OuhMkaEeq7Ih83A45qpdakQhGRjvRJNKwKVxY75o7PGcA+tVpt QaQKeSAeKyvqU10J01Jo8nOT9Kmi1fMQBGe5qkxSdnZEDXwXcc 8etXdI1AyWZJPGfWktWONmVr7UGW4JGcY4pi6kwizuOOlVy9Cm myD+2GDkFvwqe51rZbKFJDHrWbQ09bEg16SCBSG/Ont4lYW5KucE1LSYXuivL4qmhhGJZAc9mqEeMpg6nzXHqQTSjB DvZJk0XxAu4pPkuJB7hjU8PxO1GFxi7mzj+/Q6aY5VC1F8YtYtgCL6YAD+9VkfHrW7dlP26Ukf7VL2aHzokj/aS160+5ey7u/wAxq9aftbeIIgf9MfA6gmp9loJT6Fkfto+IbSIN9pOOn3q2R+3 Xra2yZkbOP71T7FopNMtx/t9axaYZ3Oe3zVp2P/BQ3UEC+YXx2O6odFjbV7Gvaf8ABQ2dUG523/zrT0T/AIKJPGHMzEknv6UrSuNovt/wUWhLKpkPXk1uWX/BRPTo4gDKC3uajmklqKzNbT/+ChujyhfMmjVj6tWuv7fGgzKAtxGT/vU+Z7hY09L/AG5fD19dLGLmPPf5q7Hw/wDtSaBq0iqt7GC3q9P2ltwtY73QPH9prMatDcI4Poa3bfU1kUc g1qmmFy1DdZPtVyC4zjmrKRZRwRTs47UDG5xS59qADdyKaeTQJ jScCopGFAbjGzULnJ6UDYwrj6VBNGQabRLbZVniz2zVaWEd+Kp IOhC1vx1HHSkMWCemamyuBFIuT6VAykNSKTGOpK+9U7tCEx1oQ JnrqipUXPtQQSoPyp4FO4D0GaUDgmkApH60uKBpCrS0FITqDTf WglsOvAoVSDQAA804HNCBCk4HNRS3AUccUmymyldzkoecVn/2qWuBEVIJ70txLULu9jtIyzsAP51z+uavc30DR26sgPGe5qNyT y7xP8J11i9abUWJTrs9frXh/wC1b8RLX4eeHV0bTljiklUhgowQKiStGy6lN3Vj43vLkPNc3Mj/ADZJUHqa5K+1ebUbs5bK84H+fxrrjT2RhOVyu1j57MGG0gcGrN qCl8gySoXuOlb2ehDdomu9uL21wvH4Vp6RpBFqp2g5rvjFbnPN uzL2pSi1tmUD5tvQCufMW6BhjknnNZSk+ctW5Rttph8tueppYI AmpKR0HXii6TuLdWRemVLm6whyo681JJD5ZKgEDoKtyVyYpqRL fWrImY+CFzkGqy3vmyhCCW6UJXbJhLqaM+mS/YkCAgkda1rG3khs40dSw75qowsxSaauitrdkisgUYJrkNZuPNv JAQQFBrnxMtTppaJMwPE8hM9qqE5PJwOtUrm4Jcq23d6VwQdmd EleJJFbE7QuAfYVat3JkBfJ56Cu9y91HPGDvqGqXHmXnAHHQZr mNSnYXLgksM5HFZ1J3Q3TaehfS9KaWjMG3nj8KhS9MsquBwBk/wAqyijbldzY0V/tNwrMowTxXf8Ahq3/ANI+UfMenFdWH7M5akLamrrtkxtjIDlhwBXNpMYrogqdoOCTXR VdtUY0o30LFxOstqxCjdnv2rH1JCDkhh3rObVrFU1roVb68RY/LYZBAzmmadKkeHULu61k5J6FuDjqaq3KtCd2Mt71RmgCsRjd/M1TaSBXauFnEFfoFHUgdqs71QkjBBrFO5oxYb8lwjcilv51mhH bHas5bDg9bmJq2oeUuFOAO5qpPrOxyC2D65rG+tikQX+toyAZA 5/Kp7TVlfaQ5yR19qcTVxN/Spy5JyduK0bWZcnPAHatUzKSJGkIHUkAZ6VR1CcBiVOAD0NOUr ijqKlyZrbrkj+dOWXC8MNueRWTZbT6E0jZhyD9aikmEMJPGD19 qfMTKGoxrstHwACeoq1pUmLUqQMU76kyg7jbq7yxzj2quJx5Z5 Bq9LFRvfUg8zkEc804y5jwcA9M+tZ3LSHXNxiFSKglnO0c8dsV NxKzuNupwtlgkE96y/tBE6qT+tOwJXSTJDcmKY/MB3JqE6oVc5PamwlHUG1QyRBkY56EVDcawQ6gtwPzpq25PNZ6k T6weSxyfY1Xn1PavykEdM5qoLUUX1ZUutWdo1BJDelLcayV2Dn 3461o4q5pd9Clfa273QIZsDpmmrrzrIMnA7VFlqwszQi1psrzu 9MHpU8fiExx5LfTNY2RpGTsU9R8V5A2HPfrVM+L3V8biBQopsX NfUhk8VzHB3tx0+akufGU6IoWZgTxnNTKmmilLTUksPH11Z3GR NIGA6hu9dTovxdv49pivZlYdPnPWsp0k1Ypztueo/Dj9uLX/AN0iyXTz26kfePSvrr9nv8A4KD6P468m2u7hIZzjhjXL70HrsK UL7H1B4S8a22v2qSQSI6sByDXSJdkrkZ4rrjqhRfRli2vS2atx Tbl607AiQN+VKCDTH0AnvSdicUB0GOTUTn8adgvoMJySOajJGe aQIa0gBqOY5XjiqsJMrSrhqglTcppXFcrlNvXJ5pp6UMLkTDHa mSjcOBRYa7laQYGDVW7yFpFX0PXEHWpEFBBKq4p6+lA2OxilAo C44c0EYoHfQUUUDQ1uKAMntQJoUY9qTPOKAsNJ5prTBARUt2JI ZLrd9KgkuewoQ0V5ZQMkkVl32sKrbYl8yT17CpTBBp3h6fV5RJ OSR7/ANK1LvTIdLtTtUbsdadrILHl3xC1tbCC4mZgqIpOa/NX9oX4nTeOfibfSeYXgjkKpzxis95pEJs8s1y/aZ2jUgDODzWdp9u8c5wMkfjXoQVzCejJ5kMbs7U+wzcauqBeNu MVa3sObSidvpfhbOmrIwYcckitWLQ1treNT36AdxXpcqSOGUm2 W/8AhEjqzsNh2YwDisrVfhtLZMrLyCecV52IxUIQZ24bBTm0ia0+ HDtbZO45Pp3qmngVo5JGYSD0JFcEsdG+568Mrnq7DLPwY0cpYB ivU1JPaDcPlwQcVaxiezIlgJroU54WKnJbr0FGnaVE12zkE4HH tW0MVc5nhHHobdrYbyFY5HTFXbi1ZkUIACK3WItqYrD9LDn0T7 ZFnYRtHHFcnqngs3UjseC1cuJrJnRTwrehy9/4aH9ubfmKxjnBqvqHh+OWbd0IP4150MUrnY8FLQSHTBvYg4x7U yC0EU5z82TwcdK6ni49zGWFktWhbuxSbbtVSc8n0rEvtEUXHAI LHJ5pPEq241hZPoWV0Lfp65XI5PFFvoaW0A3rksfSoWLXc0WEk bWkaOny7QT0OMV3ngzTgkxd13bR6V10cSjCeDaWprXqxzOY8dT z7Vzep2X7ssseFDY6VbxFzGOFaWxVkto2VAc7c8jHFVNRQKkjb eOgwKh1rhGg7mXe2iXcX3cY9qrxad9nUAkkEZp+1CVHoy4lkFh HHsKdNZBgC3BbpR7S5HsdSI2fkMwJ744p08axohzznPNCqWZTp hZRIbol84AziluxHsPPQdaHV0JjSXNc4jxTeBHO08k8fSud1Px JiTjggc1yurY6lRZnT6+87g5I5zWpouuPcSoOeKpVSvYs9E8PX IkhAJya1QAkyt1+hrWMjDkJ0fdn26ZqreIWRie59aTkKNNDIUP lYCk9+lJLG8ci4HFS5IpQ0J4Ln5lz90dfekuJ/PLADgGiMxchDGwBwcjjgVZsrgtbsBwR1zVJicStqF0olAUZ44q KK8HksrHHPNNSZHJoRCUPLhSSBz9ak+0eXF0GTx7UpSG49R9y6 radSOeKpyOBBnOPrRGVtB+z0uVZ5jNEE3HnuKr48qUZI61akiO RliQGV8j8azruIl2AGB3zT5x8rK6M0cYAJzjoarXMxEwB6jrgU KSIlTctyKSRpOV4xxTPOMUZ+bntVOXQPZ2K9zcCaHrkn3/So7htig54A5xTuVG9ynLIBJ8rbj3x0omOVGOfrUX0Jb00CG4dZ ApPJH0qa5mKQnnOD1JqSktDL1G6LYCfdB/GqjyFpOvAPc9aqMu4PXUDclpHB5+tV5LhmOeR6cc0lKwm7EEWp FnznOOtSprLwy8EjnOM0pasG7k7+JJDb5Y8ZxVvSvGVzo18k9r cNC68gq2KzlBNWKi2nc+sv2O/+Cjlz4S1K30vXZ2e3yFEhbpX6UfCX4z6X8SNDhurO5imR1ByrV yU5uMuSQ5xtqd9byqyZGDV23C5HOK6uYVy2INwGDSiIiqRXQUR +lHl/TFMTGtGcVC8fekNEMqHPFR9BQJojkpjHmqQ+hHLHuNQSqRnj86 Lk2sV5AVbv09ajfBxii4WGFeopsqcHvSGVZRkVUuMBT1pFnrkU ePoalRfeghkiLg04DigQoXApSCTQMUUtBYUUAI33aFHAoJ3Fpk jhfSk2NuxWmuMVWkuR3Oai5BC824cnFVL7VEtFyxyewB5NF7AZ 8Yutbm2gMsfoK6DSPDEVmoMgBb0qoopJmqiCNcAYFc94yvxBav ntRJhI+UP20vigPAnwzvHR/30qlEwfWvzoOtzX8zSsDuYkk1FLWpczbsVljaWYs2SKtW8PlzM QMnFeklsYySbsTJaKwBYZOf6VNo0cMeuCUcbR6VUEkzNx0bPQY JZLy0gjhTLEjccV6V4P+DGo+KRBKLfbGF6sKjGYpU4s6sBgXVl c763+Ddto9kWvJ4oVAyeRWFrVj4W01olkdZXzxjmvhsxx1Sex+ gZZl8IatFG88VeHtJhby7Ysp9q53XfiDo5sS62wVs8DFeVCrVl LVnqzp07aI464+I1ofMCwKo9AOlYOpeM4SNwi6nNerRc+W7Z5t eMbuyMtvF0bq7NEQFzioNC8eRP5pKABj1r0Kcno7nmVIKXQ7HS dftpJo8Lu4H51q2usWwuWRoscZ5rvblbRnHGlBboe/jKzs7NxsB7D3rGm8RWjKMRZbqcVwV5Sa3O2lTjbY5WfxBZm/nbZyT+VZt/4osmcjyu+OleVGUrtXPR5YdiC38RWVxG+I8FfXvUc+u2dnAhaI nJrpcpNXuZ8lNq1inbeK7CSNnCcZPampr1nPcn5AKy9rLl3B4d c2xo6Rr2nTQ7WQg1Nqmt6YhiAiGAc9Kmdab1NFQjfYu6V4q02C EERDjnpzW/onjm3CpiIAE4/CvQoVHfc58RRjbREuqeJo2mmKIq8cVykvxGSR5ISuVHX611Ooo tK558oPZIH8TRTQFwmBnC4+tQXXimIyIAh2981UqiT3M40JPda jf+EgtHiLMgz2FNOr2oXLAEL1q/b3dyFh9HdFkajbNa/KwwwyMVSuNZhLgjkKAK09rpoc/sG2Jc6pC8aepHWqN1rUb5P3QO1ONR9QnQTjoiL+2kQoSCC/AxTL29MkbYJGRyaU6mjKhh1yp2OK8X6tFArBhlhkVyMlzHKucE n2H864ZVJdz06eFja7JLfySSdvP0rc8OzQib37Go9rLct0Eo7H eeGbiFTu6/WugW9hJB25Heu2FaTR5Tw3vAuoxiYjgg9O9Rz3agkhTVOo3qTH C9RkV9sBypC9CabLqJlXO3B9Kj2qS3N/q91oiOa/JdVAOPWopLmSJGOD06VUK8bXMZYWXYh+2yFEbDYz0qzpetKBJu 4atoVVfcwnhn2G3F5FM5Y4696pSOh3sCCM+vWtVIzlRVhsNyHU FWqRpsDaAAPr1pTqK1gjQuriySboCCeP0pt0f9GHzL9KhVNLil TaRTuYcINr47cd6oSxPFJncenXNbKZmqd0WYbwGTkkHHJqG7n2 uSpBXpkU3IHSaM+4uxCTyDz6VSkvRM2csR3pcxPIyaORXOASAo 7VDOys4GTt7Yp8wvZu5FMFeJueAOvf8AzzVW4kHyKPxrRy1FKN mQSR/ITn5vU9hUQnJQqPlI6GlJkOnoPK/vFJwQBzzT2cSRsrkAAZHempojkaZk3s4ncYPBPGDVaVm+ZR1Bx z6U9AltoRNIbeUAgcCo3lLS9VpbiS7kE8Hlj5SvPbFNLAqGBJY +op3uFktCleTyxznH3c4NPGoq5AB5IA9qVgT0Kkl/9mkyku1t2QQa+k/2MP24dT+Cut21ne3Eklk7AMrtxj2rjxdNyhdbo0Vpe6frh8A/jnpnxW8LW13aXCTK6jo3SvUrbggg59K1ozU4JmcezNO2cso5qX aTVoYoGBSMRiqKGg5pjrQJoheHNRNDtp7g9iGRcfSos7qYhrjg 9KhmTI70kNlWQ885qErluKoliAEcYxStHvHpS2EirPbdelU7iH aPek0aI9cjWpEWkS9x4WnAZoCzFxS9aCkFFAwooAKYGwemKCWM luQo4qrPcZ74qXsSVHuTjj86rzXi26lmIUepqQM241p7w7LVf+ Bmr+keFHuG82djzzzVJDsdBa2Udmm1FAqaqLEc7UJrg/iLfbICueTUTIkfnh/wUX8fm+8T2ujq+9EG5gPWvmC5lSGAgD5vSlhtbsyk7JIks3E1r kEdeavWi+VGSec9MmvSWxjLdE0EJmkhTGGJ4FTaJoL3eq3AjBZ iQqhamc9PQKabfKj6n+AX7Pyrp9tcakgZtobDV6h4o8TW3hm2N nYeWhUdq+NzDHOrUcU9D9By7AKjR13PJPFtlq+v38czNNLCT90 VZsvgbeeIRHmKRHI+UsMV87mWK9jCx9FgaCmtWb1v+zUttEBdy RKe/NUNe/Zp0aSJi97Cox03Cvj6+fVIuyPZhhKT2VzhdW+CGg6QHLXkJ9Du rh/Efg3QbRiPtsQA7bhXRS4grONjo/suhJ6o5TV7TQoIXX7ZFg/7Vc1Muh20exbyLGc8HvXZHP6zsiHklC1zQ0PxjpOmyqReQsPdh XQ2vjXSbwu32yIMwwTv6Cu58SYiMUrHL/q9RlO5a/4lNyg/02Eg/wC1Vy10/SEhbF3DuPfI4rhfEta92by4eoqKsYr+E9JSeZmu4iWP94VRuvC OizH5bqHrzhhXH/b1Vo3eRUrlIeEdJgLD7XFg9fmp9z4f0a5RA13D8v8AtCt/7eqxjfoZyyKitUUV8G6Iqqou4cA8/NTE8I6KjZ+1RY6/eqVnNZrQuOVUjT07wjovl7ftMefXcKup4F0e5ILXcJA/2hWrzqrsEMop7k3/AAgmigYF3Dx/tCpY9K0PTGVjeQlR/tDmtKed10yJ5NSS13IL7X9At4yDexY9261x97rPhi3LEXMXXpm tnmmJqSVjnllmHjr1Kv8Awnnh63AUXETLnjmnt408P3Y/10ec9d1dSxeLkYPBUE0xH1/QZn+SeIKOOGqZ7jRpxkXEbevzVUcwxK1M3llGWqG401h8twnH+ 1VeOOz2c3Csuc9etdFHOKrZxTyene6EZrJiC8yAA8HdVSb7Cik i4Qj69K6lmtVSt3Of+yYXKi3Nn5it5yEAdAelX7e9spQA0q88c muiWPn0JjltPYzda8NaZqp5ljB+tUB8PNNYZMqD3BrH65UaOyn gKdrFiHwDphf/AFilh6GtG08BaYpBEsYb1rGeOqE/U4M3tN8P6fp8B/fIGz69asR2thDkecn13V0QzCZg8tpNtjfs+mo5YzovY5PSi4vN NjhIMye/NN46q9DP6jSiys/iTSbeEp5sRP1/pVZ/HOkW+AXT86n2ldmio0YlSb4k6XG5O9WPXAqG4+JulSghSvbvVR jiEglCgMj8f6VMv3l69zSp4q0t5OHTJ7ZqlVrx1M/q1GehNJqWnXYJWRRx2prCza3dUlXJ71tDMaq3Mp5bTkrESQW8O 0LKDkZ61cj02GSNf3yitpZi+RtnPHK4tWEu9MVodqyKf6VEdKY RgCQH+lOlmmljGeUXWhXvtFmbChhjvzVe70eZGB7nJru/tGMkrHH/AGS2U7jTpmYHDZx0qrNa3PnHKkge9JZhEc8rlEo3tvL5hyh6cV nXMc0EqjacfnWsMXGXUwll8kye1dlUkqQT60lxc4Cheueprr+s xOaWFknqiBrwKvoT2B61VkvAknt9eRWinfU5pUQeYSNwwHYknr VOS5Vn4xx3pyq3M3R6FebVJHk2hs4GaaNYJQjkMamMrozlGwxr 4CNQMEnoakkCbATk+pxXRF6XOdK5TkdGm3DJHuelRMWVXI65xV J2IcdCCUsxOM/XPWoUvMMxcYI7Z61d7kyiRaheRtA7nHPrWWk+yI8Ak9vSkhrsN KmZ885B79qmYmdlkQksnbpRLYlPX0Pqv/gnX+2jefC7xxb6TqFy5spGCgMelfsX8MPHUHjHQoLiGRZEdAwO a4qK5JOI5b3OztJ+nNXAQTmulDQE8dqQ8iqGxtHboaAsyNmGKa 4BFA27FeVccVEU796AsROMetQyc1SRJBLECelRNAVbIpoGCIGF I0ZwaTJuQzQYzVK6jOeaGVHc9XQc9qeB3pMBy9adjOKQ1sHWlo GtwFFAwooAZJKFFVJ7rJxUNkNkElz+dV5pS55P4UhGZqWtLaHY v7yU9FFV7PSLvX5QZfu/3ewpqNxpHTaT4bh01AcBnrSAxVlIKKBkN7IY7diK8r+JupGNpG J4VTUSImz8sv2q/FTeK/jHqUmcqkhRTn0rzZ4Ga7UPna3HNbYSC5LswqKzQ+305o8hCetb lrA0lqMg5HGK9BLQwlLTQ1/D2mtLq8bsN20dMZr279nj4O295PLqV5FkmTMakV42aYhUcO2e1 k2F9tiEux7b4q8Zx+DbBbG0G+/kGMDogrkPCfhm/wDF+uhbZWuJCcvIfupX5nLG2bbP1ehg7wu9v0O48T/FrwJ+zjpck/iK9t7i/VeIsg4P0r44+Pv/AAVvkm8QO3hu1SG3ThTjjFaQw1TMo+yh82cU6kMJU9rP4ex4Z4 u/4Kd+OdZuWPnNGvqueK4jUv2/vHF3KVfUJ0VyeN3euyjwDT5uabPPq8YxhpBHNat+1l4y1wsHv5 8EHoxrmL/41+KdQ3Z1C4b/AIEea9ajwdhKbOGpxjVeqRh3nxR8RXFv897OSeAMmqT+PNa3b2 u5VVuBlutdseGsLGOiOP8A1rxLvciXxzrALgXU+c9d3Wr9p8Qd ds1J+2zAY/vVT4cwrjaw48V4mOtyw/xk8SQDC30+f94mny/H7xNbqgF9OT0wWNYy4XwzWiOiHGFdLUSX9oTxQxw15MQD139ar f8AC8PEowft05z71nT4Swt22jX/AFxr9CJ/jj4lUhDezknpk0Q/F/xIeft05zyBmtIcLYW97Eri2ta4s/xf8RCIk3s+cetUh8bfEbXiEXs2MdM9apcM4VbIj/W2uWm+PXiO2B231wCPf/PvV/Tvj/4nEAzeS89csaj/AFXwzlew48XYhxXMTR/HHxNeSEC+mGBzhqsp8R/EV5bO0l7cdeDurWHDWHi72JrcX4h7Fa98UazcwKVvLgsT3Y+lV ZbzVDN+8uJunQk13wyWhF35Tya/EmJn1KzXWoPKWaWQAnPDdeKmXUtQidStxKuOCMmt/wCzaXK0kZLO69tyVPEOppKf9Jk4H941oWfjLVpSqLcyY9Saxll VBtaGyz/EWtctf8LB1S0R83EhZeOtRxfFLVDKp85ypGTg1jLKKHRFriGul Y1B8ULyWzKeYfMPQ56VTPj6/Z9vnSEjtnrQsopXQv7eq3JrbxvfefgvIc9avP40vQoIkfp64rb +zKS1sSs9qtij4hXmMea+ccc1ZtPiDeOozK4Uc9azlldPoWs/rItnxzeIocTORj3pG8falvB82QAc4rL+yKdwjn1WxDL8S9R3DE zY9zwKjHxJ1Iuw85gAODWscppIP7fq2Gjx7qMrndPKO4560k3j a+kVczSH0z0q4ZbTSOepndaTGNr9/K5PmMAOCc1Wn1e6uDy7EAcjdXTHB04rY5qmZVpO9yr9ouPLyZH JH+1UFxfzkYVirHuM1o6EU9jBY6pe9ySLUp4lyJGPpz1qCfxTd q64eTPUVjLCU5dDenmNaL3Jk8cXsfSeQcdialtfihfxhcSuRn1 rGWXUmtjqp5zWT1Zc/wCFp3YbPmN0z1zip7f40X6dJCvHSueWVRaOqnn009i1H8bb2If PISB39asQ/He6iYfMS31rmlky6HXHiFJ7Flf2hJgCzAkg561bi/aFEmC2AR+tc0spmnZG6zmk0mOX4+W7ONzBeOppV+O1pNLjKnvX NLLatj0I5rQkiaP4x2E8mWK4PSp1+J2mXK5yjGuSWFrxZ3UcRh 5u5ZtfGelzMoDrgjnmpW1rS70KRJGpHvUurWg9TaphaE2RyW9h cKf3iA9uaqTaPbSsGEinn1roo5lUvZnFXymEndbEEnhY4yJcj6 1XPhSTLYYc9Ca3jm6vqclTJE9UZ994VuIlYr8x7Y9KyLmzuLWF mdGORx7V6+Hx1OojxcXk9Sm7ohtrgxptZTu9+1aMh8/aCePXtXpQnoeJUoOLuyjISZTk4x7d6dK3looJPI496u4mlyg0x 8jai5NU3iKSsrHnqOa1jI46l1sUNQAFuwyWU8cfzrN3hXUMeh5 GKa2JTJbkrHESuQMd6q2upeXgdSRgUPUpE1rqMuj63FexSFGjI bKnHNfrf/wSy/anPj7wNbWFzcZuIQFwTkmuWrHlmmRPWKPvvSb0XUKODkEVrxt8 gNaoqIbifelz2qlcaFFIeKYXI5EBNNAx60DI3QGomjoAY0XGDU LwHJIpiIzAVWmeT9KdySJoQrd6ay4ouOxDMAVwapXQwaVikz1J BmngUiB4o6igtB3oBoBMWjOKBiFwO9Qz3IUcVLZLZWmuvU4qpc z7+mAKlksqS36W8ZZ2AHvWdJqU2pPsgUqnqepotcFqamjeEAuH mHPoa6CC3S3QKigCtFpoWkPooGFFAFXVm2WhrwT48eJF0Xw7qt 27AIkTdfpUSM5M/Kvxhqx13xZfXROTJMWHPvVKf55AD1WtqCtBGdRJv0LtlGvmRjI OTyK27cq7uMAc+tdsr2scsFc774S+EJde1qP90NuBzivpLwrDD 4RsreLC7zwoxXxPE2Jty0z73hXDNpyYL4Y/4WX48TS9PYG4Yg3M45Ea1jftjftK6B+x/wCFv+Ef0KWOTWGi+dwclTXxOJwzrStT3bsv1Z9rHEcsYwntu/RbfefmJ8U/izq/xg1iW5vLmWdnkJ5Y8Vz1t8PZ9SbhSSfbNfquR5ZHDUFBI/L88zeWJqt30J9Q+DUzQM5iYEdsHmq8XwUMsau0eGxwfWvXcOV2 PD9o2rko+Ck1qqO0ZVSevc03/hTsoun2wHbjoBUSotXRXPdXK158FZXmWIRfOemO1VNQ+EXlXMa GPkdeM1E6UkhQqJ7E/wDwpfzLVZFiyHIHTmr918F/MhQFAjY7L1pRpsty0Kh+BzLA5aPODyfUVSu/gpjjy8gDqB3qnTeiCDvqyKP4LK1oSUGc+nNQz/BllC4TJ5OelJwswqTdtCs3wXkuGDqoCDvitKz+EPk267ogHNLk aZopXiR6r8Ftlsx2YGOOOlZw+EMYg37Dnb92iUdbESbZVl+Ehn JAAJJ5HpV21+EgkuFjAAIXnAyKFCyG6mlzS0n4MEljszk9+M10 tl8GybUDYSM8H3reFO5zyrNMa/wUmcYWLK5602++ErLbq3l8r27HirlSa1RCqXaRVT4RsuN0ZGeR xUs/wULIrsCMnNZxhZGznYpD4StDwVIycdOlWrT4SvZTh9q7ACah0n uN1b6GN4j+HUrOxCkA9RWfb+APImIkVQQMYrNxSNFMvQfDp4rj AGF65qS3+HzKeVLHPpU2uCkaGneBPMyrKd3Wr4+GzPAGK8joRW sad1dmftLFL/hXhW4beAR1ANTQ+Bh5eAueOKmcLDvoW/8AhBnMClVBbvTZvAZaBS2Fz2rFGkdUVpfh7IHUH58nOKgPgh5J 3UDC9xWqjdIXNrYsQ+BSIyAoB7VKPh/IFBIGPTGDVKnoS9yVvAUweNdjHPJAph+H8lvG0hQjJ9Km1yiC8 8Fv5RAXBxnNZsHhGVzl1HXJz7VFRW1EmhLjwtK6ttXBHFY9x4Y likA2MMtzQkrFX1KcuiTKSAucDGcYzUUGgSrCzDI6cdRT5UHNZ XCfRpXA4fH0qI6PLHLypyR1NJJCUnuxDpro4O07AOMjiq9xaSL uwpzjGamxXM72K0ls5gY4565NVbgNGVGTv781PKWnoU5kkRSMt uxxVWZ5wg+ds5xRZFKchjahcRDGWJzgZ4ph1i7ByjvnuBS9hFm tPFSj1D/hKb63k/1snJ6DpTv+E81C3kyJTjvz+NYTwVNvY9Khm9WMr3LUfxb1C3fl 39TzV61+M98rBy5AH44rgnk0GrnoQz6ryWNGP9oS5TJYtn2NWo/2kXiiHz4/HJrza2Q9UexhM/h9o1NK/aUglcJKAR3BNdRp3xd0jXY/mdAehBry6uBrYd3R6yx1Cvu9y6raTrDgRyR5JzgVbj8NQ3GPKk X860w+ZTpaTOetlNOuvdM2+8H3Ns7MuXGeg71h3dvc20h8xWVR zggjFfQYTMIVWfLY7KqlG7toSaMpmJyGA9ade6UXuGxlTivVg9 T5+rGyMi7014IQCGBzn6VkXG+F8lc57+ta9DnaK90+62kLEH2J 6Vm/bTCFXGeeo6CjyHcsS3plgJ25JFfTP/BMj4rz+EPirDaGXCO+CM1hX1gRNXjY/bn4T+JBrGiQsDnKg13sMu6JTVx2HBjg2eacDz1zT6lPccrZPpS nrTC40jimEYNALYYx461C5waA2QzfTScimKwmMiopEyOOTQBC8 RJ6cVG6gCkUyvKMZqncdKp6O5MT1BDg08GpDqOBx9KUHJoGxAM GlAoCwhamPOAPek2SVZZ8nINV5rrHTk1AFeWXJyTms6+1kISkQ 8xz3HQUAR6d4cuNXnEkxyPfoK6fTdEh01BtUFvXFaJWQ0i7RQW FFABRQBneI5fLsmPtXyN+3F4q/sP4Tam24I0ilRzyc1lMh7n52JZCWFZGOGzn1qqMxXLbucmumOi SMXuzTs40E6tlVA5GK39Dt/7RuVULks2OldMpe7YxinzWR9N/Aj4fHTNKM7p823JJ9Kf4v8VeXq5Ckkp8sYHc1+XZvilUxtnsv0 P13h/B+zwq7/5lHxZ8drb9lX4cXmoCVW1u8Ulcn5smvzl+JfxQ1f4zeN7zUdQn knllckktwM0cF4aWJxMq0tk9PmRxfWWHw/KvidvuRu/D34ZC9dS0YGf4sV6Rofge3sYwQFeTPYV+wUqaUT8frSbWpc13Q YYogmwZIFYGvaUlkVCrg44HrUVNrmdOfQWSAXsUYYKpFVzEEny EUgnFZSfM/M3hdryJLaKNtTLEZUCsy60lbiaRgo5PpSnK+hnBNIYNNCtHHkB RU81iCdw4CnGO1Zxlc6YPuLOkaWZDDdz0qpBaRTQyvimtdTNTa divbaOBbk7c7jnGOtU7/T0jWQDqBjilFdzeUktTMtJGt32n7hPPFbi6bHeGNwFAPXFLWwR k0iXU9FQ2pD8buMYrl9Q03CTAEKo4z2ok0EJ9ws9D+RDlcnnNP 0bSPN1GRmG3Bx0pRBrQ6fTdJD3USnCjGenFdBpGmAo7nG1e1b0 U27nPN2jY0Y7GJLORjg8HArKv7RGjX92u4nGAK2nO2hnGF7tFP UrRUeMnrgYpk9kxTgErng1zO7NYySiilq9l5UMeUHJ6VBeOXCj aCnoBmlCVtwk9U0V9dtEt4QzoACM4rjdUmja7VsAANisqmrOmK 6mxb2oaIdDkcVELcx6kIsZJHYdKaSG1Y1NOtwhJB+btzWiQnkB OAF5JpOdloQ4so3KKgDDIc9PeoLKPexGMLnt2qlG4SfIkaTQD7 MORtPtWfdzrEACFABwOMVhKNmXCaew9rozSRgLuXpmk8hZpS6h A3UCtVKyIuloPSIBwrL0PIHSrZYLGSUG3qKOZjv71ixaskQHGS TgGprhFORt6CoeiG46FS4sFW1ZiOSfTpWBqUUUhCqqr2znrRKQ RstSSW2QRcqM45rGuraOSXYAAS/0NSnoV0Em0KK4lYEDAXpiqkOgpNEwAGfp0p76Gava5bPhdFgiZ kXDVGPDEJkG5Bgke9XOHYSfUiuvBsTO6heM8e9Zt/wCC48MqgA/WlyqxtbUzn8HL5LZGAO5HX8Kgn8AKQTwCOTmpWgXu7GVeeDVJA U7VHJqm/hNXjAKKD9altOQJuwlx4LTjaBzznFVX8IpDMflG0n9Pen1Ju0R 3PgpJnG0cepNVbr4fCWQqqhh7VL2KvqZr+BJFONp655HSobnwK zR4TeRn86pK5fPYy9R8Ey2wAUYIOc4rKu/CdxDkAEjoCac7bIcqrWxQm0K7tcFc44x3pkN3f6bCCrSLn3rGp RjPU6aVeS1TNbTPiTfaa5bzXx03Z4rqtD/aIvNOVS8jOg455rw8bk8Kq0Pfy/P50Ze9sd54T/aOiu3VJ+55zXpeiahYfEKxJgwWbg47V8riaFXB1FbY+2o4vD42 lpuWLf4cyWNxgL8p5GOlOuPB+y9Hy5z6ivtcvre0ppn51m+H9j VcTN1bwO/ks2wkgk5FcV4g8Pi3ibAAx3r0Ltnj2ucRrr/YGZVB3EYPFZxm8+FWYnJHNNktFm3lxGAQSCODXpn7JutnQvi7p 0qtgGYA4HvUyV4sLXP3f/Ze1pdQ8L2Z/vRg/pXtkJzGBxipjsZQ2HEDbik3Y46VaNA83HNOW4BNA0hRJkUuMjN A7iGPmo3ixyBQFiJkAppTFAIjkG1TUCXCk8kUNiHNzUTjPFAXK s8X5VTuVx04p3GrHpanmpF5FIkcOKXbg8UAITzSF8c0DbIZ7jK 9cVTmuguSTWbJKst0WGDwKqXuoR2aZdgPbuaGxszhLda7MUQNH EegHU1v6J4TS2AaUZPpVxjYaRtxxrEuFAAp1MoKKACigAooAxv GMvladIf9mvhH/gpXrq23gm2tN2GllHFY1GZ7yPh+S7e0QgksB0qFNSjD7WK7ic4 I6V031RnKOjZft7vzrtEXOTwMV618DPAcniHxTZqUwhcE56Uqk n7NmmFivaK59eR6ZH4Q0K6QlAoh4P4V5R4ZsU1C8vNXvABaW2X 3NwDX49mtX2blLrZr8T9oyrWGnkfCf7Yvx3m+KvxCuY45GNnC+ yNQeAAa4rwD4Y827jk2/LjnNfonBmE9jg4vq9T4HjfF+1xTgumh7F4du47BVjQbePpW/os6ebI+SB6elfauVpHws72ZBqLNPOzFmwD+dc7rNyJ7nk44xWN RtIinBOQ1YRDbGXrgdjVfz9yjIzjqRxUR0ZrNNXsLFFvt3kAxn pipbaJImG89eeKifcqOkbFdrTzbqRlPA6YFJbT7ZXVgQBxQo6X Cbvp1DU7WMxxj+JjWVLAbK3kZWIU84NDloPl91J7i2lw11HnPS qU9yI0laReTxTuVF3MlJVu0G0ZA6EVvaDchEXgMDxzVpaaDlNI m8QSs6IDj2z3rnNclLQbVI25GD3rGtpqCV4pCWN4sFtsLAnbxx V/w5DhXkI5IyaFI0lY37BP3u7npwDWpaO/2Z0Tg10Qk7WRhUje4NNKLdgSQCOT6UquI4yzgHaOM1bZik76GZ fEX16F4OBkZq5M2y2hThvU1hKVnZB7PRMzvE4WdFYt8o7dKx5b pbUKAcDPeplPoaKLsmZPjbUZbqQuowm3piuTuwSY2Hr3pSVnqd MNY6GrZ3bI8ZPIx61dtZ2k1QMS24jGalXtoEo3RpWJZ9SKrwM9 quahGY0xnJPcdqdhTlqZzzhZslehx9Kka45Vkxg+9Vs0ybKSaL hcfZlwOo6CqV9bCOLJByTnFTU6lU3pYhtciLO8ZPT2qWxbdc8q Gx+lZ3vqU4ps0I7cY8wgjPvUeoTFYwBjaBWltCbahHcmCGMsM5 ORxV57kSxEj7x6mnNXjcJXsQXzBbfaM4xnArEmRZNzDOeoOOlY vYUdxiLI0TsTuXGMVkvKPtTAjo1Zt2NFLuWmuN8mTnlcU6xUFW xjHuK2S1uRUdlZF+4Tz4FBwOOtV0cQXAUfMBxzWjld2ITs7E4K eWQOT1x6VmXSlpc5yO4zWU99DWBBKiGMgsMAjvVcxfaYDhjhjy TSlcLWdynfWYghJwCCOMdqxbqHaA2SW/h5NZp2KtcSIJGASx/GoL+zE0ZKgZPNUpXZLTuVUsxE6gseeMZqx9hJl54Lc+lLmuLls wa0VUORuzximLbRrG+UUDHcVonYb10MzUbeFWbIVgfbisi9sEu mLKoUD3rPqKKfUqR6QkkJV4xj+Gqmo+FYpI1KqMkdlpjUmmZcn w+WSEnq3cYxis+8+GkwAKjOTznrTSWpopMyLrw5eaa52hs59P0 r6F/ZAsLt9SjWcyshYDDDrXnY7CRq03dHs5RjpUau+h9raL8EZNc00 OkY+7npzWH4h+A15bWbS+WflPFedgqcqPunrZxONdqR5x4i8LX ukpLugYrz1WvI/G+qQWTuJU28c7u1e1do+VvZ6Hk+u6hb3Ekrg7iWzkVQijR25bn HA/wDrVerJTJpl2uiqAG2425611/wW1L+yPGunuDhhOKq3uku5+6n7FutfbfBmmucAtEv8q+mLY74Q etZIxpkg+maawpmomM9OtKBgc0Id7AWp8bjPvTGmSYzTGGaARE 65FRFNv40CvYjl+bg9KpvpimXcCR7Umrh0JiMD9Kidt1NC6EEp 44qpcxBgcUFI9GQ809eO1Nkj88UpO0UguRvOB0wagluODzUtiK dxe8Hb19apyy7ssT9SelJjZmXusl2MdqN7dNx6CrGkeFJdQl8y Zic9SacF1YI6jT9Kh05MIoz61Zq2ykgopDCigAooAKKAOa+IFx 5dg465r85P+ClWvtf+LdOsFbhFLkVhUM3ufJ19P9nU5ICiuPvv Ev2nVDtcgrxWk5vmQnc9S+DvhF/E9xAxYkAjJNfVfwp8LR+GJLeYgLtI5HHFXVdqbRvhkvaI9V8d2 La14bEkDM6yAKuPyrx79vHW0/Z1/ZrWBWEN5fLt9CeOa/Hc9w8nW5eja/M/YMorQVBd/wDJXPy08MasfEPiGV2OS78V7z4V0KOw0yFRlnxk8V+yZZT9nQU etj8gzXEOripyfVs1okKSmXcAfStjR3MOZM844ya9KDd7M8mq3 Yn8z7ZJjbjP86xdZsNkxZDkCnLVEw0KjvKtoytkZ6YqpauYbZj JwB0GKyTsy5aq6Lds4miQqe9Wrlf3YBGD60NaNlJ7Mhts21pM5 5z+tZ0F6JDKT1H9ajyEnfVAzO20hs8d6q6uS1uoycDqB3qJqxp HVXK0Ugjgz2A4rM1TUvMtWDISfWqWqCK5mVtGtPOsC4bknjviu j0vEMK7hyByMVcU1oiW9dRNWcAGTIJxwCa4nxJNIHRFO0Fu3FF W3LqVFtMW1gkwMlsAYOT3rpPD+fs5J+v1qIaSHJu2pt6Xua5+b JUcc963LYiKXAABPX2ropPUyk+wssgaF1Ugk9O1Vr6Fp4CFyDj Bq5K5jdp3M2S3a3ugS3UVK4d5l6kY4yax5dS1KyM/xFcH7IACSf0rlNVvHwnTO6sZK9zqjJbFy+VbyxVWwcDnNcxrAW O4UD7oH51NS7KpaImgYfIMHORg+lW7K6/04gDBA4OKhOxTaRqaRMV1vLEeXj1rZuJEmYqCSTn8K3jtc5+rR lalahWKgYyc9ajhKAEHlhxn0qrXLjdWL91MttCnPOPTpWXcXzX QGDgAcYrG/vGsLXETEW0Ict1pttMzCQcBu5JqGtQi9TVtpyY1TIx1zmm6qxg hyR261dOWljFp8xVa7326E9B6CrryDyIiD1NUpO1h815WHyfvr cjDN79ayJo9rO23gLipqW6GiSuOs3KWzggDC+uaxZ49k5JAOTm sQs2rDy3CZODjgetSxyeQmBnOec1vYLX0NeF1XTgWAJPGO4rOn ky68ketZpMzStISGXJdmzg9Paq904k3KuMA9quTV9C4PUryWZQ njnFRi4CxKMgkVDlctvQz9ScyRqWySe3Ws68hJTGQuDkEVnZIS ukilIu4s2dvoDVc3ytIUB79D3pFbkhg8y4BUjPUmrYxG4JI6df WmtyHJ3Kcl6qXbYGFX8qY063CHaQB3zTRV7K5m3EQcMBj296pG 3ZEbDdD0o1ITZOkSfZ23LyfbiozCHXdwAPWrGtxkgAhHynk9jU okTaoYfNRexVhJtMt7s/c+YnvXvf7L3hm2065hdgM5GRioqO0NR0n76sffnwps4r/AE6EBUVNvOeldpqXgK11LSJVVI3FfOSxK5z6arTfJqeN/Ez4KwXMM37gD8K+Ff2v/hhJ4bjuGtgw4PrmvdpVYzVz59xtJnxdN4xubPXmglDAbsEkV3v hrUF1WNG3ndjnHFbImSszWnUG44OGPc+tafgaV7HxRZsc5Eq9P rTtoQz9w/2AdaXUPAmlsD/yzUnP0r7CsQGiB7VjExp6Nk3QVG3piqNnsNYY6daA/Y0DDbmnJ8tA0iYHKigjNK4DHU1Cy89OKZLQyRM/lURGB6ZoAjlHGc1Wfj60DK8ku081BP8AMlA0ekiPFSBRignqNd wneoZJ89DSbBlaa4WPvk+lVJ7rcf6VDYihqGqR2Y+c5b+6OtUY re616UAghOyj+tOKuNHR6N4UjslDSAMw7VsKoRcAACtGNIWikU FFABRQAUUAFFAHE/Eu7CwkfjX5Xft2+LW1X42XilwUgTaBnpWMleSMnufPPiPUGkhA U5DdSOK4m0VRq0nmudpPWrloxx0R9M/s56nBpsMZTDYAr6q+G6f8JRbKFT5OhOKwxU+WJ14WHPU0PSodK/4R426k+ZBHhth74r4y/wCCtnjKb45aHCltuhgsoygQdznrXi1MHCtKN+/5H1VDGSo69r/kfnV8MdXHh/xMkN42yUNjBr6b8Jzm7tAysG3LX1NJ20Phq6vdlq/SWHOc4FatlMxtQdpHFd9Pqc8tky9A/lTZI7ZFZ2p3JnlCqvBODUyu0ZqylYqaqvkxqOhrDv7poY9nUMa zfmW2krIu6TdAvtBO3Ga1by4VLTcBz2oUXa7BPoU2uv8AiXgnG D2rIiYCaUHufSk171xQskXbaVWgfHJHBNZupzlDGrhs+3Y1Mk2 aRVlYplCbVgS2exNZV7AWtZVGcY6mqaIpPS4uhxP9m4O35q6O0 m2BjgeYF6ela8ulwnJszPEF4bJUQEF2561xmplri5Jzls8Cuec ro3jG7uWIL0xoEYEHHpW7ot+WgUA/KB69KcNHZjmdNolyqszk/NjitaObceowcZNdKmrnNy2uOlKptAOATTvtig7ACQcc4rRp3bM 5aoq6hOk1wAPur+tVrjURFOAuDgYGK55SbdkaRskYniC6Lvg9e/Fcve3BeRVJIJ71jU3NqS1L4mK2uefu4AzWXqll5ce5hyTnFOb0 LfSxWMqwSKEwT26cVoaKVuJ+Su7PQViwk2tTRsUEV/nls+tXJWYzh8AL04rqhLRGTWrGFw85Lk4x8tMls8RArnOctmm5 aaGkdWR6jM8NuAxLelUDOI2zuyT6jpWCSQNOwsQfzC2enpVe1v nN1IAoJA5qZI0tdF2y1Dy1Vi3I7+tXbrUTPBlgQCOlKN7i5bMz bu++z2yAHHI6960HuzLaxnOAB2rRRJikie3LFAp4zn/9dVvK+03LKTxtznHWiQKS1GRuB5qghieAKybxSszAZ4PHvWCKT vdCRHN0u4HHoRU3lK7k8Y9fT3rRPYqXdGiu37OoJyF6mql5AGd TzgH86q+pi7qzZTuH8sgKxJHvVBLnyiSTgA1MkjQuR3HmpksPu 8VnCMKjuT8uen41EiY6PUq3VyjwMQQecAjtWexMm0ZJFRc2I9R jEj4Vtu31rONsGnI4BHSmg5tLksJcSLg8Z60y71Flmz098UJ2Z HkU7q6WbIHUmq8DNHESc4zVvQHoMjd5pO3sKkV9jEYJbPapvfY SVtSWKEGMnq1QMd2VAOTxxTuUo3dwnsvs1uueOBxjrVWcmCVCR njt2pXuK2hG146MxbAYHjv2rvfhL8Y20XVYEkbyxuB56GsqzvF mtNan3v8ACz4wRaj8P4JLKXMgUZINO8Y/tY3XwysIzcsSrjnJr8nq5u4Ytwfc/WqeRyrYJSS1sc1on/BQbQPFJkguJo1fpgnFeTftN/EDw94s8O3EomhyVJ6193g6ril5n5piaLpzcWfm/wCPNLiufFV1Jb4aIsQD29v6VueALltMCknf/OvoI7HBJXOytiZxuDYJ5q7p0xt9Wt2JwVkDDB61oneNiJ6H7Lf 8E09fN98OtMbIPyrX3po0u+1X6VhFGNPdlsrTSmR0FUbojK4NM c80AthyDFOGCetS1qNkikAdacDk0xiEYHao2Tn3pgkNMXy8ioZ ocd6BIpzhgars3ODmkwuQXEBxniqzfID3pjR6duAHJ5pklwAOK XUnqV5bjA64FU577jjgetS2IqXF4IlLMwVfU1k3GtS3rmO0Bwe sh/pSs3sBf0Pwg05EkucnqT1NdRZ2EdkgCKB71paxa2JqKBhRQAUU AFFABRQAUjnCn6UAeZ/Fm+8uOY5ACxk1+RP7TerPrfxY16bdx9oKgg+nFY395EI8s1u2a fT9wyQvTivP/F/nR3tvsG0A5JHeqfvMFoe3/AHxHmOCPedxIGM1+iPwM023s/BUEmVDFASa8zNavJTuerlMOabRlfEr4rLYajNZwyKWCckV8ifH/UYNd0+5iEquSSW56V5+W4pVJJLoevmdGVGldrc+BfjFpYs/E6zW/wC7dZOSBXs3wF8dyW9jCk/zDAAOelfUw1eh8lVV1Y9XnvI9RUFQckUQXn2cLGxGa7Yye5xuP u2NCC7Rzvzk4x1qOKNEuV3kYznPY102SOfmtqUPEUq3d6FQEYH TFc9qlv5UkSN82etcjl71zZK9g0yUpNMQOV9RWsxaa0QsecdK1 avHQqOkhl/ttrRWByD0FZVyglg+Tgk8etZtkrVDRDPYFs52kDgUmoXKXcwBB AC80n2NKfdlXg2wZdw5OM96q6hG8duxIAQjk9qFFkrVXJvC1h9 oiyW2g1pTWDxMSvJBrXl0M+dp3MXWXWaVRJy56Y7Vy2sWrwasg YdTjHtWE1ZHRRqXLklssybiOg4OKt2Fs8DhVAAI71KjZlTepr6 ffuF2jls8mtIa/HAi/OevQ10bmPLujZtbpbqBDgDvRcdA54rVOTWpnOCvoZV3E4mbaxG TxVdFYXDM3asNEyrXZm63OWLBVOawSB9o5z07ms5JXOiLu9C20 LSFQvpkis3WInuIVydueBzUyY0k2UbizaFFLfgelaOhW/78hSC/1rNl2e5sW1sIroHaTg84PSrZj+0MgyQx61pBPdESatdkN1atCh Ofb6061kaUbH7jmrV9SeayE1+1fyo8HOFNc95L+dhhgHnrWbWo 1K5cgkydg5HNZ1vKY9RnTA689eKgaLPmebGgUArnpVi6ujGnIG MYGKFoipO6Fu7dZolHp19qssyi3RQO/GauL6Exi0aNqgW2O4bjjFZ8zGB9wUNkelJp3GoIgsZfMnkLdec 1RuXxO27AOetZt2KfxCIxChh8x/lTovlR9xyM9auJm00y3bMrWQ2g/N1qjcXDxOVzgZ7VctdCnrYpT3OxXY8NnABNZlxKcgZ9xg1lJ3L SvqWPtjKijnHeqs97stdrZC9ciictCdLFP7aJIgCSSeRn3qf5b e1GSM9yKnQexmXco2tIGww6e9ZkVy5kZmyT6+lO+gPVEq3jIXJ AyB1zVW4udzDOOvA9aGC7kNsyzT4cnBHBNWrGMMpViG7DBonqK T6EEkQWVlU5PTOarrd/ZnZzgnuM0loVfoS/axIm7IXIxVX7f+/ftxwDSsNlkXLXQDMSQD1qlLcYnjwdwzgU7ALd8OQAcEdDWdKvX b8rDpg0pJDpt81z7C/Yh8SG88DCJ3y69c11f7UOjHVfCMchHC1+GZrS9nmdvM/obJq3Pl6t2/Q+CPFsNzpfiWby5JY/nPQ9abcTaxqNh5cl3NJFjOC3av2DLaalh4tn4lnLaxk15nLX3h J413feLe1S2Wg/2W6yuOp4yeK9WKPHk9TotFlYuwPzY5wRWhC6tdrJ0IOevvTvyi i0z9bf+CWmped8PLHnOABX6NeGmLWMR5Pyiso7GMUuY0yPagcD tTNiN4+O1QlSDQCAAkYpNh3ZpWHYep2jqakj5osOw9VxQV47Ux dRpXHpUUi8UB0Kc0fOKqyxjPPBoBakMnzgiqrxcH0oKO+e53Hq aglvAnfn2qGzMqS3PmHGcn0rN1DWo7Nio/eSdlFPyK8ipaaRda9PulJ254UdBXU6N4Xi09QWUFhVxXKBqqoU YAwKWkUFFABRQAUUAFFABRQAUyc7YWPtQB4r+0FrH9n+HNUm3Y 2QNjmvx6+JWtnVfFV7NklpJ2Y/nWa+JGUnoZE12n2UIw4br71T1bwZHqUAbYCQOCO1Uou5Kd9Q8C aRdeGLoTwsSfMBwfrX2h8P/jLfjwhb2wJRvLGTXyvFtWVPD+6fZcJ4aNbEamP/AMJF9q07XtSuZMsiNgnnoK+GJPj7PP481C1uZWeF5GHPYZ618d wTXqVcdJN6W/U+043o04YHRa6GP4o8DReOr9pbZwFHzGpfhx4Yns7xYsEhWxnt X7BRaTPxq7a1PatMtGWyRweQMVIYUkvAG4G2u+yOPlaHbfIRtu SF7etFpcPKylhgY6ZqubUyT7jZZcXjDqB3rI1qL7ReRnkEVkpK zNbOTG6euI5CRtyecVtti3hTKhsjgVtTstBNNWZla6xljjXBA7 1HLa+SkeD7msZw925a+K6Eur/zEO4gqOelZV9NtkZtwJ28A1HUtxs7EU18r2qKVx6cVLck3WnbS Rn9a1jvqKorQsjQ0y1FnaR7QA+ME+lTDUWgE+4EnGc05S6mUY6 WObkK3upluOTz2qDU9OSe9Rz97nAFc7eljVwtawXOjGGFiDkVV jnmiulBBOPUc00knYp2av1EbVltLpz0yO9ZL+Lh9s8tuTng+lU p2RVtdD0Xw/qy3NtHggk1rXmJ4BgcjrWsZXdznm1FWKNyFRk+bnGTzVF7vc7f xAjHSs3vYhvl1KWq2okA2jDHnHpWR/Z6rLzk44PvUS00OyF7CzubRzjkg+3NZmq3BIUqMDtntWbuXGzM 68uJJ2UbSFzg+lbHhmMm5cnaW6DB/pWMn0HKdkb0YKXBycn0PrUojQyFsjAGAO9dFOdtDFLuNupOFIG V6dcVGjxxgsWPP8q0S3ZCfOriX9wDB6k8VmXEQEykDCkDPNYt6 m7kkJFAscgKYA5NZ0KKl1O7ZySe3+fWobBaoLY+Su4AbQe1acx SbTy7cEetVfQL2WpXnU+RuHK9qdHMy20YdcN14NONriTbNzTrl LlAWAzWZfbxeEAjaBzUyd2ODuZ9nKJJ3VcZPXHFMu41IIG5Tnr Wd7lt6jZI1RAFOPpTTP5UZyo4rREy1JLWfdEWByvYDtVbzQ8jb xnuMCrT1JUbMztUOLd2Ukc8YNYaSMLnDEsCPXNQlqVY1XZjbhm xtIqle5uI5ADjK9+v40PYSiijHb7YCwUgDofWnBGmQHqwH+eKi 2o5PXQy76UxDbnPPSorYm4VjjHHPPFG5ctrorvcsZirBl7Z9ap SzCViOSSeuafmJpbk1pGUuP3nQ1OGeIlugJximyGyvpt6Y9+5T nsSahH+kzHnCnoTWaNB72hh+6TtHX6VmXbFbwkcntjv7U07sm6 LdnfkQhdxAovZlWQDj+fNDKSJiwuCA204HPPSo5LWMQuwY7W4P rQhJ7H0F+xBq6xNJbFxtHFe9/FK0/tnwbcR4LbBkCvxnia0MzbP3fhSfNl6sfDHxP0kW/iCQouMHk4rNtwogAQAgjmv1XKp3wsWux+ScQq2On6lC+kijYIy gDOTVHXI01ApsAwBxjnFelG9zxHEbYII3KrlQf4h2rVihyyEEB d3fvTeqGtz9Q/+CSHiD7Z4RSI8BH4FfqB4SxLpcJH92so6HPCLU2a7RYHSo3THa qOhjSuajkXg0CsRgYpGbHvSKYqL3/OpFJBoESgcUjUx3GMaY55oQrkMseRVaW34zQCK5s8nI4qteIYz 3oKOjnvsnHQVVur5LaMtI4RffqaiRDMubULjU22WwKRnvjk1ra H4MPDy9epz1NVGPVgdLa2aWkYVVAxU1U2UkFFIYUUAFFABRQAU UAFFABUN+221c+1JiZ8zftj+Iv7G+F+uzk4PksB+Vfkhqk5ur+ YHBYuT+tZwl79jOWwy4ljiuIY2xwc8+tbMFxi3kOOgrZWvcV1s XfDFv9sngUjqwr6J8P2og0nOANsXPtxXxPGUv3SR9/wVT95s4L4heJW0H4P65cByu8MBXwSmiy6x4illjPzMc4HrXg+H 9K9apLyR9F4gT/2WPqdnoOk6roiplmEL9fT8a9N+G2nRvCZJB8wHcV+s0o63Pxyt NctjqbechCBwM/LmiQGKXe2RxXZHWLbOSbkmkiteaiERSccnirGm3iNvZjwKyhPX UudO6bRV+0MbhyACM9fWqc135+oM+QABRpuSoSvcmaVUKAgDcQ enWtK8uQfL4J24Bqk3e5q4xM3U7gNMoGCcVn6hqBUIuCTnFVN6 GCVnceTttgp69Kypz59w+AeOlc61N1a1xpRUuEPC8HAHep/PEcRG7nOQa2g+4Tjr5F+w1BpZEQ5ZRwKfrFwIIJQdpLDp61Umu XUygmjl7OdUvHO4r221pRWnn3sO3aRjJx2rBbHSmbNzZpLaBcD 0PFYV5pxF4PLByBycVaWpMHpZmJfaK9xeFslc9q898YGbSdZXs meKzqLsbRZ6J8PNWe4MCtv4b0r0S4v1lQY6HgnpW0YtI4p2jIz 75PNnz/s4FU93lfKSD2+lKTVxRXM7MgvNwYHHPb3rGnmlDuCvfGahxbZ1 NEdzcLNcbX4KjnFUNVmC7AgLDucVM1oCeqKzqZNnpir3h/dBcscE856dK5nuay0sbtkWZ2Ldc9+1OjnIndl6AcVtHfQzejC4 kSdMjIftWe1yy3IBGcc8Vo5WQoJWuixdzNMQw6D0qujrI2COc9 SayWo3orhNJ5cZfIx71lvI7TSbW+lLqODvHQmgjJsQ2B97J6HN TamhFsu1ssV9ahysy7rcasm+zUYww7DvUyACyGfv/StE7kNmtoUavaHnGeTVTUv3YwF68Z9am+tgg9DA06QrqDjJGPe n3khY7jkj061mtDSwEuYg5xg1HJc7rdxtK5FX0J0sR29wFthG/Ax1xUE05R9owuR0q9iW3YqXhPlYIJOfwrGvJCbgL0APpUzegrs 0JLxI7ZFYj8qpapc7IRjHPWp12BXuQG9BtGXgDHFVry8a0s0PV scn8aGWrmS98Lkn5SpNNtrkwzdc47UcotUxbq6Wa1POG6kYrCm uNl4NwIGM+1NblyLsd0882QxwOeTirMV4znHRcetVJJ6EctyrL KEyytjI9eKrrc/vTg4A6D0qFoVYvi7DW6hSST06VQlhYtnkAGjlsyYlxLMb14H8/wAqfcWSrEX5IzngYzRcq5HZobnDAcEd+9FxBstixBAHrQPY9g/Y81IW/iYxHAB96+pNXQ3Xh28jAyShwetfkHGVNLHJn7XwU3LAHxH8ZbR hrsvUfOe9cgk/lqAoYnGOBmv0fIHzYOJ+ccUQUcfJFHUx9rlAOQAOhFFvAqoQMA 9vavZjufOsc+nncGyQpbrVmymYzBF+8vH0qrXMZPU/R3/gkTq+bR4CSSrDFfrL4BJk0aE57VkmJSvM6EpTWiB60zdDDCGpr WwzQKxDJb4BqtIhBIzQPcdCmKmC0C3Y4cmkIwaBtjSKjlwvOOK BWuMEgf1qOVc0BYhZMVDcRB1PAoKILzXViYpCPOlPcdBS6X4eu dYnDzbmz2PQUoxu7si512k+HotPQEqC/rWiBiqbKSCikMKKACigAooAKKACigAooAKp63L5Vg59qT2E9j4 w/wCCjXij+yPg1qGWC+Z8tfl7LcmK5LnOM+uT1rCF/aGVm2LFcm61mMtyP510HmrErZ6YrojsWkdR8KrJLvxFbxnnnOK 98lmWx0a7OcAR4BH0r4HjGWyP0jgqF4NnjH7TF0ui/AGUseZuT7ivjv4aSF9UdiGbLdqx4Aguao/Q6vER/uoLzPbnt4rrQ7dQi7gMnmk0q2fTQWXcFPav0yMbs/InLVpnSaVcq1tuOAaT7WZJJC/T+GuvpYXLfUydYnExQIQcZzzVOy1RoopMgk5x161x/aZcXZEyak0csYHJY85pIP314/zfL0reK1QN63NAoDdQqvy7ffGavSgljwCR60SuZxZj6g+bg5HI J/Cq966ARZXcc8YHSlFpIORSLZtt8YkPyqo6VnXARIVZepPXvSW2 pqrNalSWTfeKdu0KOB1ovJAdpPHPFXq0iVAm0u/SLDAj3p2oaol1KsYwzd8VMjSMLamBqjeVrC7DyTitXS7t4bgAc 475rKDKexuxzNc25AIB4wAKzDM7koxDc4Jx3rVX2MYuxDA8ct+ VIDEcc1heJfBa63dBwgYA5zjpUt3RTk4xTNTwV4cXTJslcKB+t dBcziQld20Hjit76GUld3Io5jsyG5zjFQwZMh3Dnr71FuiFCCU rsdHbLJNjOR7Vm6hsSd9wAUUlozdJW1Ma9IaR8bck49KpXKtI6 46DvWE7sqLVyzaW/mbATnH86s2MJjvWx9zGOlYWuat+6aFm4a6YA9e1OeTy75l5x6Z pxdjKUXe40SB5mx90DgetQ30G3Dnhs8Vs9hU2tio96Y/lIJx34qW0ljfBPBIyOajZ6D6WHNIrsVGWA7H+lZ0jrHcSHB6VL ZcVZaDLK6M1semAenQGtk7HsAxwcDiokK6tYrWtobix3cLzwKr XbOts+APl9eK0S90UnpY0PDF46WyoWJJ/SrlyVKl8AN/DjpUzHZLQwoNPDXLMByD1zUN3EyuRzj64qUaRemokso8pYy2RU NwAtu+w545pt3ItdFO1k32+7j8KiurvZIoYZPtVcyuTqRSyLLI Q2T3BNZd/EpuSNwyvPoDQ3qPYinfaqbmIHemXUqTAOc/L04ovcFuipOhXe3JP5VQvHeZSMkAdutQ0N6lQIyMeeO5I71GHa O5JA6cGqWwnpqSLm5BwAWHJ4rI1lds6hSc9/SiNuYIJ31Ikn8iMEkAY6HtVmG9Gw8gtjHFNuw0x0KGRXcjjkYz TpbYFg+Ccj6UPa4LUhEgjuyQTgdRiltrgyMwYAc9x0pwu3qKO2 hpswRV2ElD6CkmiD2OwMeDk8mpaKSJI8xWcZIODxxxipb9Qlgr ZGapLQb10Op/Zt1oaZ48RwwCk4619jw3ou9HlHdk/OvyHji8cWpH7LwJK+EaPjf8AaCUWviGVcDlj0+tcE5RLaMk5J6 V93w1V58FFo+J4xilmErdSiI/MmLZyd3Bp9sMEbgDz0Jr6Gx8dfXUtM3mW+w4OBx7UzTX+znoOO h61afQbij70/wCCROqyQazMjOACQQK/Yj4ZT+doUXIrBbmW0zrBgikIzVnQmJtpGWkxMhmX5apzJzxQgW w2ME9RUyrt60xIUMQKCPwoDyG4xSMOOxoKGbFHYUx0FAkiCRKg mGM0DRc8O+CVhw0gx7V01vbJbIFRQBVNkpdSSipLCigAooAKKA CigApAcigBaKACigArK8Vy+Vprnp8tKWwnsfn3/wAFUNf8jwJbWuQDJL69a/Pi8tvLtlIJOTWVNrmZlNqMbjdPfdqIHzfKOneta/ug9oq8Lk4zW19Coyukz0H4M2bTeIYpVBwFr2PxTcMvhwgEhpGC 1+a8Zz/eH6pwTSvTPCP+ChGpjQPhdptirYdxyK+Zvg9biaUM3Abpmu7w9 h+4qSfc4PESs3UhH1Pc7LTS1umcDjke1NuMxQ4I6DoRX6Oo6XP yzm1JIZmihjUYyTUtpIXMueR0rZK6NLrYw9akMNxtXHrzWfYap gqGwdzc+tcjNdNi1OC0+5Tz1ANPW9ZVJ5HNbxm76Eq0m0aFnct NeoMkAVoXOoPbggc5rWa1MYlSa5ikuNz8D0qrdXUf2yMYwp6fW ueVmy4x94v386x6cV9s9etYk2+aJSASvU/Wm3qEXqCKjRM2VyOtMvxG9qA5wOxq4suN2jNaVIQojxgdPenwD Fu8g+90JI6VhJ+8U7tWKEL/AGrVCCQce9a1pEqXQ569KIO2oSvY2LadbdmcnkDoTUemXMdxFO Cp3k5zWjnqZQXMmZKk298QeWwRxV6wvTHA/Qkmly6Gri2rFq1kVoCQdvrWXf3pUlNu0CtVLUlLWxY0S8N1nce hq08wluGxgY7Vc0kRNtaAw8hSRkPyTUVqIb2QeeARz+NQnaWoS j7py+rJm8kZcJHvOOO1DOI4lHPTnjgmsKj0OnlLtrbFipAIJPF WJGCTsqYGAOc1gnqGuxBYXTpIxOGB7013Zr98n+Hg0Lct7FaO+ KXagO3qasXd81zKAPlXGBWjldGfLZFDUWMScnpTLKdTIoDZ4wK hsqOxYS5MUu3OB6U6WRGMi4GSMZqLlXGw2vlabkdOpPvWpaIJL QEDdnlhnilJ6kySvcm0yIfZG3MB2GOlV7xEFqe+evHFXF9hu24 zQZg/mA4GOBgVfZYjIqMTwM0TepKXvNmeF8q4YY4J5FUtVTzZSBgEdh UrY0KU1sR9feonBNu4554NJbkxdnYowXf2ayYMp2g0y+mjkaJs 7SR36ChoT1KpyZ9nI4496p3+VmOOcnrVAtStfArBGV5weaitkE 8kaliBjtRF3FsWl08yE46D1NQSaaJmdW+U54wKV9QTszOubDy5 GGRx681nM6x3JDZY5xiqHLcmggdpm2ggnt6VR1NBHKMrk5wcCk S9EUbq1LNu4Jzxg1TQqJQPu496pasS0NOyuw0YXA/CtEbLhUAbGDxxQtimilf2Kx3ISNwUA6560y3hLuwAx60XJakti 7DAVODnA6ijycKxIJH54qb3LjsW4CXhVW61DqqG4i2jPHU1XN0 C1yb4STtp/je2OcZcAYNfZ+i6i01lGB3jHP4V+Wcex/eQZ+tcAVP3El5nzJ+0ppDf8JJMx4Ibr6V5exVVXJDEdO1fW8Ky TwMbHznGq/26/kIXEwPamPIqRsyjcx4FfS3sfEWVxIrkcpyM8HjtT4SBG3O7HpW nQN2faX/BKjWxB41MQIycA81+z/wimMmgxYPYVglqZNWmdwmdoz1p3U00brYMZ9KQrTHcjcZqI2+T S2DZDTBg5HSmlOlCJQxwVIpN2aY2hDyRigtkUDW4w8Zprc+tAE bjP19qq3KHBxQM7RF2iloAKKACigAooAKKACigAooAKKACigAr nvHlz5WnOPaplsKR+aH/AAVS14XGr6bZ7uBuYgH8K+MVlM8W0HO3isacVzNmTSKtp5kV2z cYx0FWHvnuwqnoT09a2toNrRI9m+AkAS3lc/ervvE2pNEtjC2Su/dj1r8n4vrN4lxP2ThGm44eNj5R/wCCh3jp/EniOyshnZAACK4D4SwCO2iYEZJ7jrX2HA9PlwKv1Z8jx5Pnxij 2R69DqDRRRKevQ80/ULrzUIxg19xHbU/PZfFZFSPVZEUbgBg4z7Va0e/Bidic7j0ouoq5qkrmbrL/AGieQgDCrWHaQtuVunzcVytmrjpcu3F9ttsng561asrUvEvUsx zWsXaREtFc2LRBDL24X8qUSj7Rs755Jrqk7o5oNmfqFu5uywYY 7jGKqXNz5c8Qb5Wz+Vc6a3OhPqX7y4EkHX61RvdTa2tcYOMdac lcHvoZ+lXhazlZ2BGfTNPv5TPZZx8vSpTG209DMjn8lyG+5z1q 9p82/TmHBJPGe1ZSd3Y2toVNKsGTU5nOV64ArTtX8+YA5yDxRBdCJ7W QXRkg1PYWOzHOTVOLWJbbVWRckNjvVbszjFpI0re1Ju2Zlz6VA lz5Fy/Rj2q7MabuWdPffbs6kYbtVXUleSDIwCTWnRAn71xulCS1XBIPr 71ctIcEvk53dKerWpM03qTNdlpCrZJPA5pmxFn6gnGfpTv1KSM y4sorvkAjnoe9V2sA8+CxwDiuZq+5pF31NG6RIvKCdV6mqxjY3 AJUgMc5rmtZjXu7iWpUysh25z19aZO628rhQSzDjmquWZYgeS/ZhnI6c8Van3W5ZipJP6U4ysZtalOWCW8jJwSCe1LougzTXqgg8 npSbNVsaN14euLW/G5WGQPpinTaDO8ruFJRevHWpYpabF+18Puumj5W5bBqwliIbDq DzjGKG9BPVBYKFtGQ9Sc4zUE1iUgJLClGVmFuhS0oiOZ1HJ7kV oxQF5SA2RjvWkrWJasVUtT9ukGeRWfqeLecnGDUJlWbKf2ncCN xOOvHSq004MEjZPHQ+9D0BLVGHNe+VYsScnOeajlYXHlEbgv06 0xNE8xVrobeOAKhukLqBj6E0kSrrUz9WjKxAEnJ9B0qtbkwLGW yW9KuKFIntL14tzMMFhkZ7elTW1z5gy2M/Sk1YvQztSm8u4ZeWz39KybUL9ubdwQc59aQaGrDbxo4YYyO2ar 3trCHznqOM1S1FujHvY1jkZVJIxWTN8jMV4UHsOetFwi7mjoSC WT94cdhz1q1eRGKUNG2Ao4x/n2pDSILfzC7BwSDnnFTpmGINuAzwP8AGga8x8NyCRubGDzVnEf 2c9m54HemJaaDCzW9qCTjOTTJL4JbnGOe/wDn602tR27FDwvqTWnim3kfAAkwK+yPAGuC90y1diT8g/HivzjjelflZ+m8BTvzI8m/aSsvMv5ZAR83Oc14LcsyfLzvXjNexwhJvCWODjqFsSmS2Rdo1O Gxjr6UtwwAxjjPNfXNWPg7FeQlPlxgDnOMU63Ktjy+aroZN8ru fT//AATT1d9O+LEEPmbNzj8a/cX4FX5uNBiB/uCsepLXvXPSUbK9aUGnqzbVjs5FITxTAaRg4pCMUBfUM5FRyCk gIJVxxULqQaoGg34pQ26gY09KQnNAEb1BMuR70DOyooAKKACig AooAKKACigAooAKKACigArjfiXe+VaECpnsTLY/Kb/gpR4k/tL4wCANgRxcgj1NfM1sTZu+3LE5rKh1ZKVlcitJzLOyEcfWnzy rb3sHXr1PatVKyY4tN2PcfgtIqaVu6FiK76TybvxRawsVKxpux 17V+NcUVb1pSP3DhWNsMkfDH7aeux6h8cbqGMDy1OBxxxTfhXa FbVWzgYzX6NwdG2XQZ+d8byTzBpdj0q0u0AXc5Pp7U64vt0gwv HTivrU3fQ+IlH3tCo9yCzhjnIqfS5UhgdcDI55oumVa25RupSv nEcAjFVEjWKSJc578c1zs2jawl+6yWwUHb82TntWhZXBtY0Kn5 eOlXF6mVS9i7a3RNwdwwD+tT7gboEnHHc9K7IWtdmDWmhWvtR8 i8zxg/jWTqkjXV4jBRwc5rlSOjyHXN4LZQNxyfXrUWo3YntAOhPFXKVt Aitbla1QQWUhzxnFWmlzpfIHTPNZJtCepzV9dl0bjHbjvWx4bu gmnrk5XPpWb1Z0JqxKl4PtbFF5ParmmzpBcNvxgcVS3MJavQXV JMzNJu6j61mwW3naumSM4yOaJPY0Ubo2pZwt0ioww3XFNu9OUF zx0q6ctdSLW0K8D+TwG6dj071C1w7b2cEBfQVrKWhM7pXGaXfb g+/nPIzWnYXKFMKw65xVKfuhzXVx+UDKRwx602TE0jbMFjjionIIu +xFJpzpLtVTntVeTRpt4OMHP51zuVzqUeiLlto7yzBWJwOtXLz Rv3qADgDjIrmqTSNY0HJiQ+GwlyT5Zxjt/Ko28Ms1+P3Zx9K5ZYlaHY8G0gXwq325/Lj425qKXw+9wG3Lx9Kr26sRLCS0L+g+A5ZpFX+En06V1mmfBic alBIqMQzDnHSqhPS5y1I2djQ8Z/DuaxvECwsTsweO9TeGfADtpTNPEAW4yadOrzNsiULJGN4s0mDS LN143Kegri3miSzAUAEnNJVG2JR0K+noUgdlYBc0y4u+GQ8kel btpSKUTNspF+1uVB4XrV7T7sR3KjOfx61p0Ja1CWbbcyFfzrD1 WVpLkA5zUp2QSfYz5bn7Nk5wSM1Ukn+0RSADBySSKEgWxk6ggk sXKE7M06W5BsIShDGgl6IlmJjCuw2gL2FNSfzSpODzkZ4pSbIV 92UNdlYQbiOM1Vsbn7SwXAOR1/GrixyVy24Ek0i4wE6+5qjbyfZZXIAPbgGm2VZJFe6YXF5tPHtU VzZBLkFOoqUxKwxJ2tpArrk9eag1S8D3hAJOPU9PeqT6gtitFm aNmcg8YGKz9yrIxZWP0pJk7EtiCWUxj5vyrSF1GqDfgj2NCHHR Fi32SoV4z0JxwM1IbZW+U4OF4PajUFe5UltDC+B83tU9hZmRyx +71x6U09RyWmhJNaC4QsWO3OMCqMtqZFwBgZzVOQQdtGZ1uAms Q9AquM5r6++G9i914Ss5In3fKN2D0r4bjSClQR+hcCTtVcTjf2 hNFe3JVwRuTINfODR7b+VGHAbFacHytRaZvx3G84SZZQeUhBJ9 gBVS6vR5y5G337V9mz83kNdDLCxGc4O0gU+2tjbJuLAOB6VUlo Te6Pd/2CNWax+M9mc4BkGOetfun+znffaNDgPUlB/Ksepk2+ZHr8bZQZNP3Yp3sb30DdxSM2fSmUkJv5pc8deKAuhrN z60xjjrRYViN+fWo+GFNDuQTIVPFIjnuTQIXPWmlsDNAkIzZqK X9KCkzsKKBhRQAUUAFFABRQAUUAFFABRQAUUAITgE1558VroRw t7A1EyZH4+ftweIBq3x01Rt5ZUYLXjkNyUVmOOnSsKV3FkWvYm 0O3+0SM+Mn1qWSzDaih6qK1m+WNzWmtbnuPwytVstBhPAJOa2Y tUMOq31xx+7i6n6V+KcSS56rR+68ORaw6R+fHxp1iTxH8ZNRn+ Zv3hzk+9d78NZ/s1jEMDJxnIxX6xw5TUMvppdj8n4tnz5hNo7MymR+MBQeoPSn29 4zysGwcV9ApWZ8om7ktxNHHlyCWPYVAlwbYO2CVI71Un1NIK6u yo8rmLccbW6YoFxm7VTgcd6wluVTi7D9QdJ0hAwuP1qWKUxSIr Y25HHpVwMpKWxtWypOPM6t9Ksi3VGUkk84rdNqISaTIb7Sg8ob GQKyL+3Z9QAA6Dn2qHe44uxV1W02KC27NZQld7ra5O1R+NTU+I 1jsatsv/EnU43BmrR1C2ji0zgDJHHrRHYykryOabTVFm3ygj+L3NWPC8SG 1csCcZ+XOMVEjVPQZYu3mu4wTn0rUjZWBJJ3YBNCQJLchuQVuP U/WqVuZF1Mnpxj2pTauX00Nd5FghHy5ccn8qsJuvLIFepHXHSlz2 JnEqYawLh8EgZ/Cs26uSYvLK7sk5ycZ/Gt0+bUSi+otqqtbELndntVrw/bzLOTh8EkGs3LUmULx0Oi0rwnJeXA4IHXPrXQaf4KJBKxMW7cV jVrLdnThsK3sX7HwHKU3Ou0Y79ae3hCJpgHbHrivMljbbHsUcv 01Jk8KWlm+4tmli0i1WXJQsRXDXxbbPTpYRRiPureCF/lh3fQVmX5c3JKQHgcjHWuV4hWOpYa60KkNtdSzlhGRk46Gp38P 3ErLsRh06CoeJJeEdjq9A8BXe+EhDgkfhX074Q/Zvl1jw9Z3O5Iyq5OR14rvp4lSpOK3Pn6mGtO7MjxX+z9qCSyOq KwbhTjqcV5rq3gXxBpiTQSWc21TwQhrTDSklZmWIUZPQ5bUvh+ k+jvNeqVlLcg9q8t8b+HtOtJJvJuI9qcAg8VvKqonPGDm7HAza m1s5WGRmTPaq638gjLMG54Gf8AGtFXi9y3RlfQbZ3DJclRkCrF tfg3TbThq6oyujOULWLFvKbiaQk59hWbqk2yffjGPSiLuzBq7u Y12/nXJOazZ7jCSKDhjwCDWm6CxWZWFi5O36Y6VPDZLJYIygFSaLie rLk4Vbdcndn8hUd1bJLMmDhgBnFS2FtTJ8RXDiEJjgDJIrIE32 YxDKhuo9/arSsD2NWC4H2bPGT97mmCAzH+8rEbcHpQ9xN3ItQtvschcMSw6 cUy2nBk3N1PQ+tJO4Joo6lcme/+TACjpjrWPeybLkswyewFNaC+FC28u6L1GOelVL2REbPBHaqWj EldXJtOv1iiYZzj3pWnRcyE9TwCaW5V76FvTtUEkWNw644q9Le CN8ZJzgZAprQErLUb9pMTjeMt6n/CrETl8BSdpqVuJXDLRR4wMc5PY1Qv9S8tSgJyeBTuNau5jXczq rNuG4n3Br6o/ZZ8WvN4USKUFiBivkOMqd8HzdmfccEVP9rcTU/aBgW90D7RgEjOf/118qSxqupSE/3ia4+DJp0me5x5FOECzsV7N242+pFYtyT5h788cdq+8Py1xsXI V2cDeOO4p01sjR5Gck9qpuzEldWPS/2Q9S+xfF/TQCAfMGa/dr9lvUfO0S165MY/lWT3MajtJHu9u/7sVIT3ps2S0GmTApDJ9aY+oduKUHNLcSQUhPQc0FEb4xUZzmmJ IbJyKgdcN7UDeogbigglaBLQY3fNRSNQNHZDpS0AgooGFFABRQ AUUAFFABRQAUUAFFADZTtjY+1eS/G3URb6bdvkfLEaiZEmfjL+0NqP9ufFPW5iSd9y2D7Zrip7NorT OCQfas8O7wRV0T6RdrZwKh5z14rY021/tTUERQPvZNFd+4y6C5qqPbvCemta6dbh+gHpWf4j1BdL8M63dh wMI3XtxX4rnfvV3Y/e8ljyYa77H5/3wF944vpuXLynJz1r1TwlbLHaw8EgDoOK/Zcnhy4OC8kfivEFRPH1PU3RdM6lVOTmpNHlJkdicjJ7dfrXovc 8KMUid5TNPnO4j8sVJcFWx8xYAcj3ondpI0UlexBqDlbZMLjnN V4pzLeEkAMB94Vk3YOblVhNUZoLmLaSc8HmtC0nWVlDkb8cHNa UvMTv1NmxgYRA7cgnOKSaSQvtAOQeorsU0zkavItCdoLNhgZ9a zZ0QzrJnLe56UJXdzWKS0Kuoyl0XP6Vz91D5MkjHgkda5qt0bw Nm2CxWFrETgnnA71osjNbBnIyO3NVSi2c83y6mVqNoGR0Uj8Kh 0OAxWcwAwBn8amSNYSIoYmMgUZHrVy3sjFCzuT7e1VFaC1bEuV A2srAgj5qq2b7phhQT9awmrM0g9LHT+GtG/teVt6ngc1o63bxaLaMsMRZgMdK5p1knY6FBt2Ofi06W6jZ5Acn vjGKS18A3uqOzRROU28MBmto1LRuTyOUrI6fwf8ABa7a2JeF8k 88V2mifCT7HGWkVU5rhr4xLY9LD4Bt6mvZeHNP0ZDkh2NWLO8R nMcEY46HFeTWxcnofQUcEobIZf6RfXcO2ND9AKqWvgC+kbdIrq M9DXBLEqx30sI3qbOn+AIjt+0SouevNbkPgfRbRFLzxnjkEivP rYxs76WDI5bLw5axtunhwPeuf1rxN4U0wFhNAzfUVxSxUm7I6v q1lZHMat8Y/DtkGEbwnHTGK5m9/aO0e2HyNGT060e2m9DF0o9TvPhN+0Bp+tXkKEoFBH3q+loPjld 3Gj2cOlkFMYZV7iux15U9TzZ4KNR26F/4nfHqfwp4Rt9Qvo1gjiXPzcZOK8n0L/go94Vv0uIr5IhOMgHGK9bA5iq1Vp7HhZhlLpUeaO586ftKftbQ Xum3cunuqxuxIC9vevlzUvjg8tncSTXZUucgbua9WjS5rtnl05 cqsM8OfG2OKZGeYFAOSWzXU2nxcs9djUBlQ4xjGBXNiqU1O6O7 B2e5raXrkV0qsr7mrUt1Kyb1+7zzW+FxckrSJxOB1uiWy1D7PM 3Yjp9arahKbqU8ZHavVjNNKx5U6Ti7MxSxMzfwkdQelVXshIJM Ag5qlJX0MWhJ7PMOxSOnNXYLQR6Um7I9M9+KuT0IY6+iUWaAFs 5ycCsq+lMNwu1uT1/+tWcLXEkitdXiy7g2S3QGsvUNOab51zsB6g9a1TBss2TBETcTg Dr61ZhhEjAqWIPBHpSerIsLrdmWctk478Vg3l20E4QYx0GBSir sq3RC3FwsUakrz2OaxNSjE865OcdMc1pcVhkbGOML1445rOv5H W55LH8elVsEWGnz+fPsxz1wauSR+ZAysOB0INJMLO4y3HloDnp 3zWna3+8KeCc8A8VLKYPITIQdzLn1q5Z3ISMhSD2wRxTaJk9CX zf3Jz0J796xtZkELjGWPf2qR9DNMqtIWPJHSvd/2WPFS28ckZx6cjpXz3FEebBSufT8I1OTHK/U9X+Jnl6r4IuySCQpI9q+TtUi2zSbcj5jnmvnOC3ZyifacbRXs E2MjnaW32/mKpPamORfuk5ya/RkfkzZYM+MqVIWpjiWN8ECmkZqWtjrP2erxtH+JunzfxecvU+9 fur+x7rIvfC+nvu+9GKh7mdSKufSdpJuiqYtlaW5stiJ1OeDTU 3c5qgZLg7eagdJUkGDuX9aQ0tCYEsOetGfemFhpak60DGS9OKg ZSTzzQJbjCOTRu3DNAmNZ+cVDK3Hago7NelLQNBRQAUUAFFABR QAUUAFFABRQAUUARXbbYGrwP8Aaa1b+zvCGrzbgu2FjnPtUSM5 n4x/EHU5bvxZeSglg8zH9aq3lxm0QMc+orOj8CSKk7vQltLdbqHIDe 1dB8PLOT/hIYVPKlufaoxkuWk2dWCV60V5n0PbWKjTSQBwnGa8t+MjnR/hDq9wWOXDfrX4fjqnPifmfvmBp2wtvI+IvDarf6vO23BaXPy9a 9s8N6MwtIyQAoXBr9zwOlCPoj8Dzl82Lm/Nlg2KxuSSRx+FN0lSY3zhjntXalc869tCNZ9juuM498VKkxlUd DzUtgndhfymYICSqjtmprO3jliMgwCODgVm+5qmnqzO1SM/2lEc/Lnjirka+Zfq3zHHIFaUyZnRaa42lckED16U2O+FrIMjePfvXTH TUwfLbUfPqAuECBSSTzVK+bEvAOSMdKuUdRwi29TOmYW+3cGIP aqF2TcyEbeM+lcs07m0FYvWEZvNaUHGxBxWzfu0ds2Oc+tXF6H PUV2YkjGFSxxu/KpdJug8ByuQeCfSibvoaRj7olpbia5z0UHqRWkNksOwDgH0rRX 2JbtLQqX+iOLdnT5U9u9Z+gW5vdQCEfL61y1ItaHRSV9jvPD8v 2QNHDGSzcZr1TwB8Ek8a2vmXKbQRzmvn51Hz3PQpw0OgvP2W/7QXyLCIyH2Ga9R+G37LEHhfwg02ppHG4HOccUVcbenZHo5fhLz uzmvFtxp+iebDYxK5XjIFcA9nqGu3J2owXtgV50q2up9HHD2lY 0bD4ZSuwa5bYD6mrkunaH4RhMlxcxAgcgsMmvPq1+h6NOiranH a3+1F4Z8LTSjfC20djXkfxG/b9sY1dLQIq88jvXAlUn8J2vlhE8e8S/t36i5bypuD79K43Vv25daYkfa2znrurto5VOdmzz6uZwhHcx9X/bO1K6sSFuZN+OcPXK3H7SGqXrMJLqRs+9d0cj9/U4qmexjqii3xtvXkbdPJ9d2ak0v4g3uq3YJlJBOOtdkcpjHVnC s45nyn1F+yrpcurTRs7PkHI5r7D8HeN5PAelmWa1kIjHGR1r4/MsRZtLY+xwGH9rFM+aP2zv2wtZ8dFtPVJbWzQlQu3ivltfiLNG svUsQck9RX0PD9FOm5M+W4mk4WgjA8WfERr/TCjSl68z1TUbm9uMh32569q+so0uXc+MnKxXi8SXUAKiRsd/WtTTPHFzaOCshz6iorUuYulX5bHa+E/jNPaFA8rbRjPNeoeDvjlDdusUsgXPHXiuGdFRdz3qFeNSLueg6 Rr9prMaski7yPxq7cRHaSuWz0FKnV5dDOvh1UjdGJMxjuTvBOf arlvAkySAgAeh9a7KclyKx4k6bi2mUdStioJUZ5p6OZNNUEglT gCt3sc04jb6QwWy7uVPHJrG1S6AlQDaTmhGcdCpLCZ2d14zg8c UwXPllImweRyR0rZbDa0LctiskRY9MdM9ajhnMBXa2cHAo8iH2 LUpaZVLZ246VzmuIUuQQuV6iiLL5tDMu7khgCQMD/CqNxKsdwnv3zzVIa0FcGV8k5A96qRne+GPy/mDTuSrC2kQW4LAc9DzVmMMJHPGMHihIaehSgn+/2bOMVNHMzbGBK4PJoC5rWoEyZIJfHHtSPE8SLzhc5obJsrBHM8 8bAZ2g96gvMeVkdO+TmhFGPcK0lwGUDaeoPNdp8HfFH9ha0yna oZugPTNeZm9Lnwk4+R6+RVOTGQke733iAap4ZljzkMnc14Z4t0 s23nMCp55GK+L4YfJWaZ+k8X2nhUzK064VbRY0zvJxmrP2RZ5V 3AevuK/Rloz8e62I7hYosElcngg1QWX7Oz7OmKSuTGOtzo/hRP8AZPFtlJgBt4/Dmv24/YZ1j7X4O0xif+Wa5pN6mVRe8fXenyZgBHpVkNxikbIUHIoA49K q4wPHtSbsGgoAQaOtCYriFfamEGmLca/0NMZc0FJkboc96j2letBPQjlGDUEjYFNlI7dOlLSGFFABRQAUU AFFABRQAUUAFFABRQBX1M7bRj7V8o/t0a//AGT8I9ccNtJiYA59qyqysmyJH5I3apNqLFiPvHPHU/5NQXVwk96EUZC1NLWKCafPoaOnyFEwPvYzXXfCG1N14nUcN61y Zm+Wg2ejlUObFRR9BTWotvDcxGM7MCvF/wBsK5Xw/wDAcJjDS9cd+9fhtZ82NjHu1+Z/QOH93DNHxP8ADZjPesSu7c+ea978OTNDZIvAOBgV+/YaPLSivI/nXMZc2Im/Ni3LPP5gUDb0JFMgj+wxLzyRya64vQ4WimIz5rMQB2p8V0Fmwe w6VMlfQa31FuZEmhyM4zxVrToCLduuetSloW7IIrL7RdkOAdq9 cUWsJS7OMH6VcNGTLsa1rbN5xK8nHQGoZkka6jQ5BzkcV26WRy yV/uJJIvJkLsBiq73gDMzAfWm1oNzaRWvFjukUbhu7mqjRpHOihRj cc4rkqPU6Kd7Gta2iFXZSM+wp11LvkCN0HvVJGLbTM69uI2VyC M/pRpHli1cjDHtVuSvc0voS2snlSkEcHnH/ANarFhEfPYjGzPQ03cHBJ3F1O9+SSMn5R0qn4QKpdqSc7j1xXP Uk2jWndSPXfhb4XTWdUhjCljnJwM19afD34cLBoSlUK4HYV8xX +Jnu4eGlz0f4W+D5rUy5iVT1UkVD8QvBGveIYzZwByrH7qDrXn VYNHu4Bw2Zxc37NZ8OWj3msyJBGoyQxxXkPxZ/aH8G/Ce0njhkhlmUYrlqOyPaoq8m0fI/xl/4KFy3c8iWEnlxjI+Wvnjx5+1/rOsTMXvZGBPQGnQwUqzVy8Ri6dGPvbnlfib4xajqILec5Le5rm LrxXd3spDSORnmvocLl0IRVz5XF5zOV7DWuLq4TYd4z+NNl0qW SIkknPQHnNenGko7HgzxMpbkdtocsgICHjnI9a0tH8LPdbgy7u c8jtVW6sxqVWydPCskU+wbunTHUVp+HNFa21ND820Y7VNRe6zf D3dRWPuX9iW0iikikYhtoHBr7S0S70rUrBheW4Rdv93rX5Rmvu Vn2Z+x5XBuhZHyD+2LFod9qlytlYLGi5+baBXxH421FtPuJooI wGJOPWvd4YnKc2kz5/ivCpUry3MHRvDkuqf6wcntjir0/wAPWEXC9R6V+grsfmTndmRd/D+VHwUYjPy8d6zdR8Hvb7SUbd7807BHQzLvT5LSQH5sdM1Ha+I rnT3+8w9MVlUpKSNadVxdzs/CHxnutJuE/fHavua9t+Hnx/ttRKRXJAbHc15mIocruj3sDik9Gel289j4itRJGUOeVxVW70qS 0kO0ZU9eOtc1Gvyux2YvCKcG0tSjf3BKhMZwM5xVKOXbiMbV5z nPWvVhNSu0fLSg1oya923kIUHGOnvWBrlqYypQ5YnkVtCWphfU SyY+Xg4yfai7tll5xg5rTqStyGC+PzLk8joaUFnYkcYOaT7kMs yTsxCsTkr0IrK1aBlGTyM0ooaRiauNwIA4PGelUZLErJGwK49/SrvYJOxbudqxlQOT2ArIVhHekcE549qdirF2xgVpXI6+vPNPmQ W4OCNx6mgSM0wrCruW5Byans/mjwfu4FPqCWmpftW+bjjjvVwylzgbT7etK1gih8KqzN8oB6ZPe qGtRlIsc46cHpTsNKxlMDHHubOM8jrTvDd2YPEK5ycn5STzWGJ jejJHblrUa8bn0B4dR5tJjHZlyK5L4oWBtI2O0DI7V8LlcVTr6 n6nnH7zBfI4TT2wAucMG5zWszmLAQEYHJr9AWx+RS0ZVmgwNzY yRxWe0RDEHBLHvSZi2zd8EL5Ot28mSAHBFfsj/wAE/Nc+1+BtLO4fcXPNE1qZz1PuHRrjfaRnpwKu781BpHYcppwcYxV dCr6CbgR2oIzQnqNMbuxSCXHFCFbQcHoZsmmhxGE4PNMfk470w sRk4NAIcDtQSRTR54qrIAOtBodqlOoEgooGFFABRQAUUAFFABR QAUUAFFAFDX5fKsWPtXw9/wAFNfEX9n/B67jBwZWwefesK7tFmc1dn5ez3hF25z8vbPanaVFvkZ2B5PbtV QVood7l83aISFwWPHWvWf2dtJS71PzGHI5rzM5k1hpM9nIoOWN ie3a/bCPw4VX7xcACvmn/AIKU6s2hfDSytsldwJx+FfilB82YQ9V+Z+8t8uEbPkT4S3J3x5 5OcnFe8eHWM4BH8IxX9AwSUUj+dMQ+arJ+ZO0e0kEBf51FqUUk wBTjA5561vFK5xx0M6YbUVSNvNSw25kbvx265qZNt3Kkroke3E MiqSBmrls/2XjIyOpPemloZp3kRw3ZhuGIJOamtlJugzZCVUIlt3TNaxuNkp Jxg1HdSYv4ecH1z0roje5i4kupcbB1PUVhaxL5EoKjC98UnJ2Z K21Klu7z3IUA8c4qxdOrqWPDAYHua46h1I0wotrFOck8nmqkpM 0rlsjjiuilqrmMoqJWutPxAIs8nkiltrfyY9oPTHWnYE09CNbp jeJziMccVpzawkEOxCAx9qmUrobi3sZF1eMZME/N3NafhDSLjUdQgS3QuMjpyK5qk7Ruzow8HKVj7h/ZN+B0Npoy31/F+829xXvnhrX9Lhje1j2Kytzmvl3V5qp9V9XcKR0w1WDTLUTow XA6DjNc/P8Ath+HfhpJcXGsbF8tTsB71WKtZWM8FdyaPz4/bv8A+CqV78QdSvLTR5DaWAJC7Tg1+evxF+Omo+KL6VpLiSUk5G TXnYLDSr1W3sfTYrFQwtPTc851DVr7VLlixcj270kfh+a7HzZ2 45xX1lHDRgtD4nEY+VRtlmHwc8r5ZWOWx7Vp6f4J3kbo8MSOAO tdHL2PNlOTZ0Fh8PjIuAgUY6belSXHgNli2pETnrxVtEsXRfh/MS4MbE+uK6DSPhzslZwnzEcrik0iroU+BgupOrAnK+lSjwF9jZ HVSOlRUj7rLoz5Zpns37Pfie78K6vaiFGK7gCOtfoV8GvEmjan 4ZFxqCKHEeWDDn9a/Mc5SVWzP2LJqspYZSW7Pmr9r7XtC1S5vGsreKNATyAOa+HfFHh iHVdXmaJQ3zE56Zr0OE9KjsePxamsNqT6B4Ra0idvL9gcV0mie FVlCl1yBxjFfoiR+XE2peCLeaVcJjnjgVnan8LIZyDtXp6URaM k3Y5TxF8Ht0REYyCeuOled+KPhdLZu22I4HB4oNU1c5PUPDFxp 0v3HXHHHeoYdcudHlUxs3ueefrWVSCe5rTqOL0PUfhh8fptHlj jndivTk8ivoLwR8VbHxTDGPMUM3HJ7189i6Dpyutj7HAYr2tO3 U2NR0BLqMzQ87h09axGtjbyBGzuBxg9a3wda+jOHMsHb3okV1b SIOCfbBrC1dmhnQnGAD+Jr1Kc02fO1FqVLW+ZcZyQTzirgu/tDbua6Ohje6KjFUnDnIXpzVixIlkKk8emetCuQl3LNzKFdShXA 96o3VyZUwOfTNKKHEyNTtmWMNg49KguN3kqwAPQfSqsPcbdAOQ wBAxtwTjFZb2Ob5jjacdxyabY+lxLWcpcFOcfWppIt1zn5jjk0 0NkT2X2xW+YAd/SkjKQTED7v60+onG7LcMvlRtnqenGTUyTeXKoHJ7knNLcZp2sY VQTycetUb795jIJPvRfQl6K5m3dtuGMhiDwPSqtihg1mIjIIfp UTXus1w7tUTPo/wCH9r52i2+3k7RVX4iaF9qC5Cn5egr8+51DEux+u1LVcGvQ8jv dNMOquo4AbJ4qyk6RAj77HtX31CTdNM/JcXTcKskirq0m/IHIzgj0rMlyHAzkdMdhWsV3OV+ZraDdmG8hJ+5uFfrP/wAE4PECv4F01Q38IHWlMiS90/QPw7fBtOhOedtaaXO4ZBpX0NYvQsRSMxOelSE5NJCDdR5nFCY0 xGwfrTSvHeqGN3YPfFKG3imOwd6Qrkde1ArjWjyOtIBtoC5HKc ZNVJm4NOw7naIMU4UhIKKCgooAKKACigAooAKKACigAooAxvGN 0INNkznpX55/8FVdUEngy0t9/wB+XoDXNX1izN6tH52yRhrx0b5QPQVaguUhsMgY9wOa2SCOhGM GVD2PJ55/KvoH9mmy2wu4PGOvpXg8Qu2Dkz6HhmHNjEz2LWIBOllADjdIM8 V8cf8ABWLVjFfafYK2CEGRnr+Ffj2VR58ygn3P2zGvlwEn5P8A Q+aPg/YFJozyBnIb/P417b4VnDxyqzY47d6/oKK0sfzpOT5i1e3myMD5Q2ehNImovbqcjJPOTVwWhztspXNwLx 128EGpbRnWUpnOO+Kd9NRpstGcPcjIP171bjhEduHBHPfvVxeg PuZ0d2BKQDjLd+tacT+dKgAJXHNOGpMleNy29uzgbCRjtVKS5k GpxMcMAa2p3REZ3di/qFwGdS+A1YmpylZBj6kmqq7Ao6EcEojnAAIY9MUt5EVGe+frg1 wSXvHRtoW1iMNtHuJYds1ZnnihtRIxXOelax2MW+ZXMua5M0+T wD+tTwQszFV5HcnitLOLsVtK5l6tdeXJFAg+Yn1pl1c+XPGikA 55rCTNKS7mn4f8P3HiPUxHEjPzjjoK+3P2T/2W7LTfDialqEIaXbnkV5mZYjkhY9zKMLzz5j0bxF8S4/Brpp9lD+7JwxUcAV1fwl8NWHifVDe3UpgjRdx3HFfKRqt1Ln2d aglSZxfxW+OVnpfim8sbG4WSFDhSpyK+V/2lfHH9s6bcHzS8hBHriu2MlJXZ89UXsp2R+enxftbu58Qyjc5U sTwDXMQ+ByV3OHP19a9rAwSV0jycdiJTdmy7Y+D/AN8A0eE+ldJpfw/8wZKMfTPpXqHnXSNSLwHtI2rj+la+i+AY45l3YJzgYFS9BHVRe ErW3i4AB288VHeeH4Y1yUXPsKFJ3JjfqUdLsI47lsoueucVo6R pzTXspKBcrxU31HbS5De2McFyzZAPT3qGG3Go3CRgHb6496mTd mXBe8e9/s6/C06uFkiiQv2Jr2K4+GviSy0+aGEMVIOFjFfl+cSvXd2fr+SS5M OrHzn+0D4P123gnhmjeNhn7wrwvStDbR7p/PJD84Br6HhmnBSvE8Pi6q5UkjrtBthfoqbVJHJ47VZe2FveBUX Ixzmvtbn5rPcj8ki8XIP5VauVEgBKkD6UrD5CtewRquTt+nrXP 6polreowKKSx601oiY6O5yPi34Wpc2uVQHvmvKPHHw1ksNpC/d9BjNKS6mlupxt3o89leYUkewra8JfEG98MXKYkcDOBXPWoxqR szvwWJcJJn0L8KP2gE1CKOG4lG33r08xwa4BLCVcEZHvXy04yo 1UfXUpRr09DLvrWSK6AI+XFcv4hgZrshMe/Fe7hq0ZNM+XxNDkk0UYz0VlGc8nFWLAEzc4OFPB7V6V76nlOLT GXNtnLHGM+vSqyXL2sqleVPT2puQO1y5MBNgA4GM4rLaKVLpif 9Xnj2o6BcsSSie1VSeQeai1GJYLROMANz8tJpgjP1Kc+Wgx8oO Qcfzqm0oafk/Nx+FGrJs9EQeaiS5zyDiluH3LGoPJPPvVF3uXbeHyIDhckjB7c VGtukgPzADHIx1p9AZWhlWTd04p1tdjzMMctngmmiL2NWO4Bwr MOlRTsTM3AAPBPrQynqMf57Y8YI6CqaR+XfK7HAUgg5qXsVT0a Pon4GK2qaOhzuCit/xPobXsvypwB27V+X5lL2eLaR+yZVTdTAp+R4n4xt10/X5o8EHPQissWyznGSSfbFfouXT5sPFs/LM4hyYuSIL1FtJQuCffrVEojysxIBPvXc3ZnlNDYXW3dXbhc5H av0N/4JofFiNdMt7RpgdrdAelRVn1Ia0sfqX8P9XXUtFgdSCCldLDOU PFRcpbFiO9IxVmO63dTTZTJFlDDrTt/FC7gkBak3E8YGKYxjkEmkSQde1O4h+7PNG/NMa1QhbNNPoaBEU3eqUv0oKR26DinUAgooGFFABRQAUUAFFABR QAUUAFFAHLfEOUpp7jGc1+Z3/BUjxKbrX7HT15Iy2K5q8bqxn9o+KZLeQW7E4HJFSTWZOnx46Y6 ZrfclaoqTQPDcIM5Y9jX0j+zinkaDuI+Y9a+b4ply4Nn1/CMObFJnq6TfafElkn9z5jXwT/AMFNdfOsfGFoSdwiGMA9K/KeH6ftM2p27/ofrWdaZbP/AAs8x+G2kmG2DAAE+gr0fREe3tnJLL71+99D+ep6k9u4luVDZO KkmbzXZR1PvWkVZGTXUrWspRyCvIPXrVm3d5ZSVJJ6cdqb6CSv qPljZZefXn1NWHume3Cg7QOM1pFWFo2V7eIAlieCT1PNaOkyMw Yk4H5U4xIc0omgboY2j+dUYWzeFmOfatFdEU9bsLq5Mkhb8h71 kXV25jdmLHJqZu6NYfCkQ6ZetLfADOByDV/VCzW6MGALNk1yTZs7D7/UGWFASp4wDmq/29LjaGOD35rWLdjDlaVkWbjyyqBM+5PekW7aNiq4C5qnK4JX3M 7VUAvUIwepNGlaVda7rkEUSsxZsEAVzzlZHVTjd2Psf9mX9mmL TdMj1G9hxIfm+YV7vb+PY9D26RCgVWwuVHSvlM3r80tD7nJsLa FjvvAXwo0bWreTU9XMUdrAu/MnHT1r4y/bW/botPDfjK70rwrcCK1jHl74jgt6mvEnJ8nu7nvRi5Sd9kfO3hb4 8XWsX7PNM8jSH5stWl4qvp/EMZRdxBGTz1r0aTtBX3Pl8W1Kpc868XfCGLUrR5ygLg9+tcQfh 35e5Cig46Cvfy2rzR5TwMZGzuEHgUWtwrOvTJ4rf07S4o4gFCq SvrXrnmsaumnzmYgYHHtUlnaMZV2gEd+KTeopN7mrFa+bcfMMc YFR6paqVbke2KzTs7DUncybC1+zzcYLe3ar2nyeQ7sRwR2+lOS VyvIwtVmaW9fIY81XsNS+wXRYnPTg1nV+A1ofGrn07+y98T7ax S2hkkRJTgZ3f0r7L+HN095prSGFbhdvylhX5ZnF/b6H65k8V9WTPkT9sbWdRHie9EkKR/MSAFr47166nuNZkZjjnkV9BwpB82p4vF8oRpqMTb8LeJhawOGI BHAOeTWpY3BuHzv5PXNfcwbvqfmjbuTAgXwAA5Har10phhXgYH SmndDu3sUr+Hz1VuMYzyaqXlqkmwkBu/Wmm0Ty2dylqBQqDxyRjmsDxZocF7AodEJPAFKXY0RxXin4XRTl GjRQ205GBzXmnir4ez6dLI44A5P0qJaalRetzAs9TuPDs6SKzr t5zXuXwQ+PQCw29zIuP9o9a8nMsNzxuj38rxih7rPerW7t/EenCSJgWI7HOOK5XXLBrC5JYbienFeZl9dRnyyO7MsPzU+ZGOt mJX3HoelUlBkvjt3KB6Cvp4yPl6kS8sOwHfkggiq95blVXjPpi mkcyjrdjIpB8o5xwOe9DWySTttLH61oipEPk+VvzkBecmklnDW T7zlS3AyOPapeor6la9ZPsAIUnnHB5FY1xbMm0/KobkimLbcj8lXkXp159aV7NY2Vg2TngVS2Ki9DWRDKhDHKgZ+v 4VXlgEKuinJHpQ2NvuZwg8oHd1PJ56c0wIwZlzkDpQmibou2at lSSxA7VoWUfn3ALnAHr3plJ6XHzwCVnKnC5+ueO1ZF9bkxliQM e9S9Ae59Ffsc3Q1PTZIDhh0BNe5zeB430y5cIDJjgV+PcSVXTx zR+5cML2mXx9D5U+OGlNpmvSuqguW4HcVw9pfhHHJ3Ac81+l5L PnwkWj8s4nhyY+aEmfzpNxxn3HWqjuqEcZPotewfO20K88ocA/Lg19K/sgadqEOnR6hp0s0MiHhh0NRJXVhSStc/R/8AZl/aq1DTLa2sdcjOxRgSqP519VeFPiZp/iW3V4biN8j1rFXiXy6nQx3YdQVIPpUkd0QB2rVMSJor0k81biv AwHINAEyyA96du+lPcNxrYbmm42gAcUkIN+etLuz0qhiE88UNj P8A9amguRSpu+tVLhMCncaO4opFBRQAUUAFFABRQAUUAFFABRQ AUUAcZ8TLry7Mivyl/wCCi+sC/wDjCyFhtjiIPPv/APWrCo9V6kJe8fMeo3B+yvg7snqKd5wMMW4A59uRWyWhlyu4iR Je6pGgPfpX0R8IrRtO0eBD6DNfIcWyaw9mfe8GRX1i53nh6/MviaeRiSscWAa/PD9snVz4g+ON8/mDmYgd6/POENc1jfzP0fieThlc35Dfh1ajy0XGBjmu2mxFaFQCB3x9K/cmfz7N3K6WuLhQnA7kf1qJBtvBhgy4wK2grEzld2LtkqtuyB70 tsgiuj9KcmTK+w2S633RJAPPSlvZUWIhQp4zgGqhawpR0GaZcf Id5XIHWtvS7cGFj2I/OlG7ZNS1rInkQIOc4B4NUQPLnGcEgfnWrva4qU+g+2dLuNs53d wM4rA1RyrnByeg5rGUuhpqnoJ4blMmoMGPbj1q/fXCTyKhJ4asJG1vdK+oHd8uDkdOaz7eUPIVBNawdiJJ7l/TwfKJY4BPXOc1qwskUSnbnJ7VcbXITVyGy01tZ1xYVVmyeMDvX 1p+yb+ySuoLHqN7AVXIZQwrz8VVUYM9bLqPNPXZHvPjfxBZ+Eb WLTLQr5o447Vo/Dvwrp11E2sao6R20K7iznrXyFSXPJ3Pt6CdOF0fH37eP/BRGexvr/QfDd55GnAGMsh+9X57XXxDufFHiRpppHl3E/MD60stwntqrfQrMseqFFJbs9X+FOlEajFIc/MK9w0nyYLXlQTjv1rbEx5Z2Pl/ac8bnLeKVvrp3iijbYQf4awUsHt7eXzEw49RXoZZFw1ZhieV0z A1GcpcgBcknmls7YMM8g9c19FY8V/EVYXkHmH5vX1q3okwMrjBDfSoautCb3Rfuw0ZU4OO9VZk82VRu GD14pQ21NFsVUszCcqRgc+1JYSMZ3I5GOnrVOz1KRXuI1luGJU EnvWHqGmNPcFVK4zwD3rKprFmlJ++j2T9n/QlDRTEkuvOOtfUPgz9oXXPCdhJaQadO/y4DY5r8zzaH7263P1nJnF4flbPm79oLx5q/iDVLua7ilV2Ykls1826hfTXN3K0oZV56da9vhSk1eT3PF4wcVB JdyrYXxS6Vd5Zc9M+1dlod2JAOcg19tdn5y31NiGMJdx7SSD61 c1K4bYPlJHr6U46oT1K91MsdoMkrxg1n6gxa3DLjAHHGMUJu47 6alG8y1srd1XnBrL1id2jj+XO3g1ctWNbDkhEskLfdB7VU8U+F oNXsHQxqGPVjWLetiIybdjxr4m/C6WyJZVIxk+2K8zW/udEvoym4FWPzCi3Nozpo1HF3R9BfAX42PZeTbTybumMtXvTxw+ K9PWVCMkdc818hmFP2VW6PtcLNVqKucvqejPYzkAZFZMqNa3JY D2GK+iwVRThc+bx+HcJNER3y3JB5Hfmo7ucuwTOB065xXaeVYY JA9soySc8Y61Nbhlc5JyF4qriZVmDYycc+9ZkjPLCQw4B4IFD2 uiE9SJLlobJg4JG/wDpVeX5rVTzu9Ohpx11KSvqNtYP3qggDn86HhzLnOfYmqHpY0L CfeDuxgjnvjikOJ3cJg8dxwaTRnJ3Rm3ZMWSM7iMU2BWc5bqeo oWiKWxcgjLR4XcD6elW4o2TDkMGC4NMLW0CS4LzOFK7scAcVk3 zyJARnGTzxUt6je575+w3ega79n4BPSvsbTtEE1pOuMsUOc9q/GeL4OGPufu3BVv7PR8Y/tS2y2PiyRSvVj26V4yVMLseSpP4mv0Xhepz4CMj824ygo5ixov f3ufTt61aVY5QSBjjjFfRnyLKF9aHJCjPfrjFfcn/AATAS21vTmtZ41kUEAhu9S2Zzl7p+kfhT9mPR9Y0RJbeJYpMZ6 VjeIPg7rvgG8a40+SUAHjB4NKUVJGsGmXfC37RGo+G5Vt9Yt3K D/loBj9K9Y8JfFbS/FMCtBcxsT1XdyKwTaY5R10OmgvEkAKsMVPBOVArdMm5ahusHmr Ed1nvTQIlWYEdaVvWmUxhOKAwB4oQhQ1ISQPamJbibsCoZQCOa EOJ2VFBQUUAFFABRQAUUAFFABRQAUUAFB4FAHnvxZnxbP7KTX4 6/t1+IH1n4z6sityjBeDXNUvzIyT9655I0SrpkKtw4OTnvTbtl8z dxgDkA10ryE32IPCO688SGbnG7GfSvonwdrC6fYxAkcL0zXxfG E0qSR+hcFQXO2a1j4n+w6Lq14SOEIBz7V+dPxY1/wDt74s3MhIceYSM+ua+L4KjfMrn2fGlZxyxrueh/Du1SaAMeMCuvnjVIEDAFs/nX7NI/Cai00KUeZbp1JK/TtVaSFhdYzkda2iTJJajzfrbTRrIcEnpT7i9Vbwk4A7DNEthW0 KcN/8A6WwyD7VPeXq4I79BgVSkimnsyJLwQhVUZJauk06YvCDjBxxT IcFuOurnZb4BAXP51lCVmvj82eOlW3oRGmmx8M2wbf7x5qpLbe ZOxcAnPU1g3bU3jHqQ6CANQbBwwH0NaLWhF4GAySelYvRmnmVd XultbgJxuJ5GOlYE959jnlKsOccelbRYS2uaujXm9FBPOK2jDI tmjA7s5wAafQy9mme1fsefBGbxv43gnuIC0AYc4r9CY9NtvAmh pbW8YV9nAHFfM5pXadj63KsPaCZxmh/AKbxrrk+q3jFLSPLOx6GvkD9vT9s5fBVpfeGNBuwsKO0bNG33s cflXjzi1BW6n0NCpzNroj84PFXim78V6o7ySO+9s5J61q+EfCT swlC5Ofzr6rLsMqVKx8bmmKdWs2ewfDueTSyguE+6Pyr2DQtZ0 +4jjLugbHOT3rnxmEvLmRxUqr5Wjro9V0S2sjJI8bMV7V5T4w1 WHWL+T7MqiHPBqcHTdxVHJrU5DVIljmLMnB457UQxi4jKhsHHQ HrXsJ9DlvYhjsTCrKQcdCMUabhLtg4AxyO9TK9xJal68lyFAUZ xms+8TMhI4/DrSS0LS0Gu52HPQjvVMXJimIUY4znOKb0KehUa/DO2OntWbdXTwu8wUhTwB2zWcouxVJe9qe2fs0XYmuLcuQAeSK+ y/h/8QPDem2bLd2qlwOpXrX5xnPu1ro/VMjg50bLc+WP2x/iRpt7r139iszHEScAL1r4/1LxB9t1V8EoucY6V6fC0nzO55/FULUVfoQQTASsd2Sen0rpvCmoGe5C7/pX3R+cNaHUQXmy8QYyQcc+taFzd/u8EcnOQPSpWiFtoZ2szGbTX2c4GOtQfagmmISDxRHdkpX3IDI1 zCfl+XsPSq1wV8hhgHnirk1cSlYfHbpJboQ4GBnip51WaIFcLj qMdazk72YdTnPHNgl3YNuQEFTkYrw74k+ABbHzY1K7icY7U47W NLnG6bcT+HL9H+YFT0yeK+kvgD8YftcCW00mQOOW5rx83w/NTuj6TJsTaXKz1/ULSPWbRZYjkkZOK5HVbRo9QxjLEdOledlNdxfKz0s3oKUeZGVc xPbXgOQARk49KqrbNNIxYkMWyeOlfUReh8dUWoqXI2MG25B7U6 O6IdTg7T+FOKMrC3l2suFHGScntVPcTH5eAB2HrTihDZdJVLDr g56CqF1GY7ePO0gEUoslSI3JIQqOe1RkMkuTnOKtFxJYpyI2AU cd8UyJzHkqxBOfmpiaQkhJCkgUAoc4b5gOKAe5ato/3cjk7QeOuKtRXOLXbja2Oo70mDVynqcsVsrOW2n0NY97q8IgJZ uSevbrSY0e0fsQa0kPj2MZyDjHPav0E8OwJKz5H3k9K/HeN4f7apH7dwPK+CPiP9t23Gn+NJ2GAQTtxXzlJdu08gPDE8V9 1wf8A8i+J8Nx1C2Y37okWTbICvJIwcCtG2i3RKck4PAzX1R8VY ffJ5asBx646V9f/APBLvVhZ688WTwf8KmW9zKrZQP2H+C175+gx59BXdXdhHdwlZF DqfUUIKexw/jT4Jab4mjciJUc98V474u+A+q+Ebz7RpzyrjnKHFKUUzdMTw18 c9Z8HXAt9WhkmjXguBzXrXgn4z6X4phHlXCb+6k4IrFJx0JnHq dlbXkdwu5HBB9DVhZSuefxrVNMgel1jBHSpo735fWmMf54anK1 U2Njw3GOtG/8AGmJINwI4NQTkjpQWjs6KACigAooAKKACigAooAKKACigApG+ 6aAPL/jTeC30y6fOAsRz+Vfi1+0Rqf8Aafxb1ucEM0lywBrml8SMl1OG vrgyzRwjHy9TUrnZllOQR2rqvYm3MiXwnC66mCqjbuwRXrmnXw gg+b+EV8Bxi9Ej9J4MVkVviJ4mXQvhJfS7gGdDgfWvgaS6/tfxpc3DN/y0OD6814XAdP8A2ucme5x5VawSXdnsvgUm10tG/vDmummk+0KgDc9RzxX61JWPxy3QZZxk3DljuOaVgwbO0/U10USJ+82ire2W64RwGJXkmsHxLrB02Jpmzsx6dKzne40tTM0j xMl0Vl3YyfwraW5N7MGQsV68CpT1KnsXYJUVQ7A4XofWtrSbsv p+Vbr7/wCfStuYxlG6sW5GEsAIHOO/es2EeXcSsSen40oqz1Ii7XRYggZxEeMHmotSBR+SMe1Q1c6Iu6 uippCAagZDkA8dDWiuoCXVYwCNo7ViXYpatCLu8L44UcE1zGqS KjSEZALcGriTdbGhYLstI2DnOOmK9K+DXgq5+IWt2ltEruu4dv eoqVLRuXRpudTQ/Rz9nr4PW/wy8LxTNEqSKmSfwrqdI1b/AITvxCIcHBfBPZQK+NzCo3M+9wdPlicD/wAFKP2wtN/Zw+E//CPaJcRx6ncQlXZDzGCK/Ev4l+Pr3x74iuJpJnk3sWJJrTA0nXxOnwxJxVX6vhXLrIk8G+E Ptsil1HPr2r1Twf4RFqgJAK7fSvsUrHw1aW7Ormt4YLVUUDOMk 46Vk3dzKrFVkKAHP41M43Mqcr6jINUmdsSSswxjrWpol1vjb7p x0FTCKijRzvqRa/CssLDrznjtVOyjCjcCCBV2siW9BbaXfI53Z/WobVdt07HGfY0pbgia4uAyAADpioLuI+Xk5H0NQxspmXfIFPtx mmGLF2cEYx+NMvoY+pWL28jH5tlRzSmWy8s5HvUt6DhfmR638A LFhq9uysAoxmvsPwLrHhu1iX+0Vj3hQSWHWvzvPfdqH6hkTnOj ZbnzJ+2/8UPDR1OdNOttygHDY6mvhzWfEpn1wmIBMnp2FdXDim6jk9jDiS PLh7S3ZPoGpy3F2QygKeea7XwMpkviDhT1x6V97Fq1j82aszrr cB7xcZJDYNaWoQYCkcH0NLZkMpzndZlTt4FZ5YCxHXKjA9KcWZ q9gt3lMXy9M881H5O9Jc859aptNj0bsRify7UBTntj3qxZybd2 WB+WpexSRS1jF0oXAJxnp1rjNd05dSfayAg5/h6Ux+ZwPjf4eBoWaIBioycd65bwlrFx4X1ZcFlCntxisa8eaDO vCVeSaZ9OfB74mJrlgsUkgz0zmuw1jSFuWMoAA69Oc18ryulUu j7lWrUHFHPXOn+ZdKcH8qz7oCByhwMkkivpqFbmgmfEYqk4TcW UhbqJGO4YxzTI4g9tt+XJ7+ldKONoW9tlCLkgt7VDK5jGMAenN N6Im5XuLn7NIFGcH3qtezI8JUnnpSsriSW5UZxaYz3HQ0jXYlb Ix9M1SLRHKWhJwwOTkCpLVd7D5cAnPWmlqHKTXA3gBQSo/SkMAaRWHCgUmRe2pYMytBsAbcT0z0pJQsVhgbsjvQUtDndauWV CSy7RjrWFdmS6T7rbQevY0mF9D1v9jvWG034kWwyQCR7V+lPgr VlmZDngoOtfkXHMX9aTP2fgKd8HY+P/ANvu2H/CXyvjPfivl+SZbe4XqdvPFfXcGSbwKPluPYf7YvQms5BJJ5mTn suKv2lwD1XaODkGvsT4HcmvJhJHgcHpyK+mP+CcerJp/wAQVRmK5br61MloZ1Y+6fs/8A7tZ9FiwcgqMV6jyVHWkmKnoNEftUc9nHcqVdVYHsaLl3OQ8Y fBjS/EsLgxIjn0FeN+OP2dtQ8PXRudOeRMfdZDVblpmfoXxh8RfD+dY dQie4iXqejCvVfA/wAetM8UxhRMI5SPuPwc/Sude69RSWp21pqcd0m5HDZ9DVgy4OckGt732E/Iel2VHUVLDegkYPakIsx3AIHNPDE9xTuMXdjvUc0gAOaoo7Sig AooAKKACigAooAKKACigAooAKbKcRsfagDwv9pnWP7N8HarNuw Fhavxf8fXzaj4rvJj/FOzZP1rnSvUTMuZq5ztwd+oZTHyjnHWpBMwLYOMdq6EwXkdL4A hE86OFBwfmPpXa6re+RZtjr0Ffm/FVW7a7H6dwgrQPNv2mPGJsfhp5KNyRzXyH4FumudbkcncM5Jp8 B0F78zTj+bUKcOh7p4McrpA3EZzj61stO/nrg98cc1+jS8z8uUVuWbS6aO5JbIbFOeYOc5AHatKUrMyqR1Fg udysBjPc96xvFekLrVk8e07T6Vb1RMG1I5Wbw6NPsxEn8J7Vv8 AhmfZYFsYI64FZxN2zYe1+3wDgjPetGyIsrBI+GA6cVUdWYSZb imWTIOOnrVE4QSHpWsld6DS0HW1/wD6QqjkAdDTtRK3KjCkHP51hK63Naej0FtIViBy2NwwDmqDp5D yT565GB1rN9ynfQSTUlW2A5yRxWPqUPnKWOCxPNCI5U2WNHUzt twTxgCvun/gnn8Gkt7eO/uIQSwDcj8q5MVUtTPWyqnzVLn1342VodMSzt1OZBtAUVzXxa12 z/Zl+Ds2rXjomoSIfL3HBJr5KtJczb6H2dJaKPc/GL9sX9o7UfjH8QryWe4kky5GSxOOe1ebeEvD320l3UnnnFe7kN DlpOfc8HiLEfvfZLZHqPhnw6tvEh8sgcc4rrtJkMSjPOOmK95L ofLTV0WLlvP+bGcdeKzNT2qwwMc9RUsIxskZCkLKQxC8etXNFv GjmGT39aE9B3Rr3U4ktnAxvIwKzQCsJLHgdaqT0IeiHaYNkXDH cRwabaAG4deoB4rKT1L2GSnAHTNVNTlZgFy20VSQ9yJYyQMEZF VhcyRXWWJ64qGNssXrLchdo4PX61malF5ERKrnnOSajl6jg7M1/BHxCufC7wyAkrnpzivrP4DeMtE+IdpF/aciBuM5PA9q+Ez2lyVeZ7M/S8hqOdD3dzgv2138F6eRFYpHIyx/M3GM18E+M5bWXXG+yIoBY9B0FHD1SUqz7C4hpSeGUpvUj8P3LL e4HzAdPSvQ/B+UuS5JbjpjOK+9hFJH5zUep02mTgXxzz83pW3csJpUXr6H1pL RXMqhWuYBEkgYkcelUIbAvZ5PX061cSYrQbbWkqxnDN71E0rIs qgD/CnZPYVk0VVlVbfp3P4VXMj7XZT8u3rmpuDYtveC4jcbSfl44rD vA8m7C455NNaFLTcgmtBcQMhVmOeeOlef+Mvh6TNNNCnOPSixU XZmZ4J8VT+EdZQFiBnkZ5FfU/wz8WQeL9MTEgJ2jjNeHjqWp9bleL5lY0dW8Om3dnIO3B6dq5fV PD4vN8h656UZfWtozmzeg1LmOanja1laNsnsMdKjSb94SvBHSv cR81Pawt9cExAs2Wz3qtc3AlI559BTkZuPUguAssincOfes7UY mSYYYnn0p7FtDCjyA5OfSmIfLAI6gUxMk2GXAAOPfvUkBbcMHH PQ9aotssz5RF/ve1VRcMZfm5X+VKxm9i6pUxqF2le5PrTLpitoRnC44zQ0VF3Rz 2qwb488456jrVS2tlA6En+lKwJWO9+AzDS/Hlo4ITLDv2r9Cfh7r26C1ZmIOwV+W8dx/eJn6/wFJewaR89/t02/n6m82QMjP4V8nzr59yWG3HtXt8Dzf1VxPD8QP96j6FqzsXVywB HYZH61e0xd0uSCMHvX3KPzpmill9oO4DK9hmvf/wBg+Zbf4mwK4wC3NZTbtoFR6H7Mfs4yKNNhAPG0cZr2iP8A1YN PqZ0xSOaRjQjVCMOKikgWZcMoIPHIqijlvFvwp07xNE2+FVYjB OK8d8dfs2XOmymfT9ykcjbxQ0mNM57SfiN4k+G1wsV4ktzAD1b qPxr1DwP8e9N8ToEaVY5u6PwRWDTgSzuLTVIrxN0citn0NWUc5 68Vpe5LZMlyU6dKsQahkelNbDvZFuO5Vhzio7hgV45qkUjuqKY wooAKKACigAooAKKACigAooAKivW22zH2oA+X/wBt7xANH+FOtyk/8smHX2r8gtbm+2ahI5Hc98VhF/vDPoZMEQFwzE4OfrUjoVXA6HuK6ErIiGktTvPhppDfZdxCj045 rZ8a/wCjaWg+6WNfl/FFROqz9d4Wp2pJnzv+1x4hkt9EjgLYOOQK8O+H8TQRl3wSX6dM 17HA8FHDyfmeLx7N+3hHyPadElW2tIEGeRW8kuLkbRzjnvivuJ n55qPjuhcO5AHBweOlVbxy0wYE7PanCLuKUmySwuhGhyATn1zS FtrLkgg549a2fmZR3KNyi3Lqu0AY5FWLfS1t7MA/Jk8msbdjVOxoxyJaQqFCk46g8VJbyecB0Jx271pGyYtb6k/lhc5HBB9M/SmRNvRlORzzz1pOTuTFMhtZkg1LB6Y6U65vlN0dpBAPaold6ms VyuwwXjspzwPXFVY4ZJIJDksOwqNDVlWVcRFs/Mozj3qiboHTnbnOeFNS11JUdbnd/ALwBL418RQxKhZdwzgcV+p37PHw7j8FeAbcLHsKoN3HQ4rxcyq +9Y+nyal7rkdx4GlTXPE73U4H2W1556Zr84v+Cxv7aC+MfF02j aXcgWNoDEgVvvHPJr5+p70Uu7Pp6UeWrzPaKufm5pNzNr2v+ZI wOTk5PX9K9l+Hnh6IWyEqcg8mvt8LSVOmoo/Pcwr+2rSmd7FbBIuMDHcCq63JUbeCevFdF/eOFakn24oxBzwOeagul85CxweSSB3qX3G3dXMucRoSB9407TJx FhT6ihbkM1Vk+1RnjaR61U1CQx27DAPGeO9UyobWEsZ1W1UE/wAOKXT5zJKy4HOScdqwZS2sMunLXHHY88cVn3UxWEkcMW4Oa0R USSzkPmAkYbHPvRJDGclskntion3DqVfOEEbEkHB+XvilmZb2J Rg/jTtoNFjSfDiajexxHAT+deiQaXL4QsF8hpD8ufkr4rN5xnU5Wf oWQ80KN0eIfG7xHrWsXbp9muNp6Mc4NeMXGmXFvfbpUYMc53d6 6cqw8KbVjDiHFVKkbLY3PDlozXY3ZGMZOK7/AMDWrPeydj64r6mCsz4eSOrs7JYroHcOD+Fa8lsu9SecDvRe6M ZN3sM1CzV7dTnBOcCs4RmF8LzVKRSY4gxRksACeR7VnuFYS5wQ RzinEhamUFR4GIIz71Zs4YxaHd09/T2pS1HKNxs6R2UG5O+eeahsokuY2ZowoK9OKb1QpMpSQIkxwFx 6+tUr/SVuztAHJ6etTsNKx5t8QvBjWdy8iKFXPOOtanwN+JL+F9TWKVj syAQTjiuTFRuerl9dRmj6w8OX8HivRUdCGyua53xRoz2JcqGC9 q+fg3TrWPqcTS9rR1POddQpOxIIXnmsuCcncQx29xmvqaOsUfD 1Y2bK9/chQFxn61UvZ2jjyo+Y8ZB61sjLZFq03ywqzDA9+9NuVEhGOWzk mmCIvIjiBJbFMmssHKpkHnNLyE9B6Zh2hhtOOeKs24EbglVDEd qpMuLQl8VSM4wapJIsL5YLj0pX1Ie48TgMMHaScdKtSqbi3A2s CwyR6UyktDJ1bSzKh4O0Z4PPFU0sGgj3Kn9aBG78MtQa08VW0j EffHAHvX3d8NNdWXS7MggnaK/NOOqd7M/U+AZe60eb/tnWZu9PEg/u5JxXyXInlyuu1Seg9QK9Dgdr6u/Uw8QoLng0WIrnyzgDgDJ56inqyyK2OcdcV90fmt1Y0dOkfHIAG RivZ/2PtTNj8WbUHHMgB46VO5Mtj9oP2Yr7z9Ltznqo4r3uAfuhUswp O6uPFGAaZsMc4NMz70JghNtNeESJhgCDTTEc54n+HGneIo282F Ax7gV4/wCPP2Zntne40/KkcjZQ9dC0zkrDxb4m+GVyI7lJbm3U8lutejeBv2hdN1/bFK4gn6FW4OawalF+QOPY9BsdZg1KMNG6sD6GrkbgL2rVST2Jf YlW4KrhTQ2oFByatFI9MopjCigAooAKKACigAooAKKACigAqrq 77LF/pSYmfFf/AAUi13+zfhDfqXIMmRX5dakFaVyp5HfrWMH7zMmny3RkM25Dnr nJyau2qrdMgBXPt3raTvEHrI9e8B6Xs0hfQ8c0/wAZaYbvULeJfmwMmvyTiWa9o7n7bwzBRoI+QP209QEnihLQE4U 9B61xPgGyULEGALcZ46/Wvr+DKdsvT7nxPG9S+NUeyPW7KxVDCNuSB25B+lTyTO08rEsOO tfXyXU+Ijrox+hMxtHYnIJouJ44iw6Y9KqD0JktWxLFjLGOMHd 2qZi0Z+bPy9q0aujJS1sRR2++R5QDt7Gn6let9lRQQVPSs2avU jMjpEuc/nwa0LGRAyhjz0HtVJCqXcdC01wVU7jk9hSPH5FsrMOtZu97F8v umdJcZvFyDu6H2p6t5k5k9fTvSk7jirk04WJkABLH0pougto6K rHmsnfVFxK81sJrJx93ArmjeMjSIFLjfj6UTbKSu7I+7/8Agm58El1DSzqdxCcnkFq+39cLeF/B4ijX53+UACvk8fUvJs+8yyioU1E84/aR+KEX7Pf7N2qXbyeVqFxEVjzwdzV+Fnx9+IM3jvxncO0hlYyH 7xNcuDpupiYR6I6swrezws5LqU/AeivJfISQR34717X4Ot1tIljC9uSK+7SPzd6vU6C5Pkwnbj8Kx YLl1dmIJ+b6VKepFtCSO+Mjk55AA+lSLeeZHt3Eg9OKqUdR8qK ckGG3FgPrTYpAHIzyDzjnNRfW5nNXehoRXW22faW3E46ZxVWa4 EmQ3Jxn/Iq5XLjfoQSPlWI4OOxp9giCIFWxk9ax2NEiaUqJODkH0qvexqk K8Y55yaV2wTJrW1RrdXPI649KgaUm4PAAxWi7BcivrcsmRkbuR 7VXkcWcKqcg9c1EnpZCXZE2ja8LG+iKjJB45r6A+DvirS/EhhgvghHAORxXxmd0VfnP0Hh6d48jNv8AaUPgjw74UjEcUElwy +g44r4U+Jer2Gpa0wtAgXdjAPArhymrUlX8jszenCnQ5mZfhmM xX33dyE969I8FRhpWIHPWvv47an5xU1Ogs7QfbJAWGRWrcQBVU YxgD8aXNYx6jNSUmyRl5BBJrGWbywWbC5P5U0m2KzHTfv7b5ck nHpVJ1CpIFLZ296u/QptLYy2twbQkHLg8ChFaGEAc/wCNFugIu21qJbTn5sjPJrPEDIJGQHb0wtSmuYLDbLTzM+TwMc4 pE08reMMgjdwKJS6CbMvxV4bXUbaQFQPQ4rxvUvDsvhvVHlLcb jtb0rOUeZGtKXK9D3D9nP4qbttvNJ3wte66tBHreml0AI29a+d xlNxlc+3wlX2sDyvxZohjlkJABz6Vx62bwXJ4yufXrXuYCrzQR 8xmND2dRlPUbX5ixyCOdppqWokjVj93Ndy7Hkt9C69uGsQF6Z4 461SZPLfkgcdcUxtDb+2LSAZIX0FRRXBwqEHGQD7imhxZektQE BCg56EnrSSw5kXIxt6ilcV9StqMbxI3ZumMVlK7zTDIA+lESep aVS06hQeOCM1aa4eNgAGUg9jVWKQTSec4xnHv2qxb2azQEbu2T SGncq2FibLWopASCHz6V9jfCPVmk8P2jbhwBXwHHEF7OMj9F4D mo1JIp/tMWp1HwwJTydnU/Svj3VbX7LfOynIBJ69aXA8lySRt4gRfNBlaa5aZAA2XPZe3+c1 LaXbIcYLZ4JIr9BsfmbRs6RPnqpzn6V6d+zfeNp/xJsX3HIlGeKzatqKSsz9of2TNT87SLPB/gFfTNn88IpIwoKyJStNP0p21N7akUgxUXmHd1/GgB4+cUoUigAKjbx0qJ4Q3Wn0G9jD8R+AdP8QwsJoVLHvivIfi F+zAkrvNYHY45BXg090CZw8Wq+KvhbcBXV7q2Q/xZyK9B8CftFWOsMkN0xtp+hWTiudxcHdF2Vj0jT9ct9UjDJKpz zxViUF8kHNbQlzELc9XoqygooAKKACigAooAKKACigAooAKzvE knl6e59qT2E9j8+/+CqmviHwHFbA8ySgYzivzomyWc5HJrGm1zMhWsULt9xSMgElqs wTldQhXOBWr+FkU1zTse1+D7oDSIsnt+dW3dZ9TmmbkInWvxfi Sf7xn7tw7D9ymfCH7UOojW/ifcN1VZD3461J8O9MLsjYOPev0vhWHLl8EfmHF075hI9C0qbF2 5OAMYHNXYpkIZSM/Q19DM+Y8iRmSC2VU5JOCMVm6kczYU7faqjqJpJ2JtJcwqXbPoR mtRIVaHd7elavVmJVlkaKM8AdsVJ5CyIgyCcdx0qXHsaakN2VV SoXj1plvukuE4wMdKg0XYvxy+S2HIbPXNPvdQ3KqKq+9Z9RJMo 3IV7gEenPPWktm8gj5uvtSRVO5Zt182R2P8IwCabEI3tc5+die nTFJ3NSSaQJalfUfjWb4R8JyeJ9bjghBLNIOMZzUVNItl4Ze+j 9YP2HPACeEfh/ZwOu1mUE/lXvf/CPw+IvEtvbkhooBvevj66u/mfoFF8tmuh+bP/Bb79oWNPE58NWMy+TZoVkAb+LFflbZbtU1TzWDY39cHiurI6f7 +cmcXEFXlwsIHqngHTFtkVjtzmvSNJkMZUDp1ya+rWp8M0XrqQ yRsuRnHNZxH7srj5SfepSDYiDEAkgZ6EiljuDHEVUEcfhVrUz5 m9CCXcWGGIPUZHSpEQLbhjt5OaS1ZTWhNCwjsyenrxVe4l+U84 45xTkVBaDIRugxk7Sc4qewUINjtkfWsXuNNk1xGrk4ztHXtUd7/wAex2N9aVx31Es2dbcAAZI69acYlmQ7j2x0qr9gktAltt8HGOB +FUbjTGuRxjqOfSpluSn1IrLTY49VhJb+Loa9w8PeDvs2gLcWQ 8yXbnCV8jncnflZ99w7Dnhc8h+Ofgfxl4nLNFaTfZkJ52/1rwXVPCOoeH73N2rZ/iB7UZROjHRbk57CrKFlsXvCZNxdNuU4zz/n869F8KAjPQD6d6+rpPWx8XNnTWUpmueoXBq/qQaOHI5yPSi6bsYu1yOeXdpijqAvA71kTr5tsBkHLdc1S2YdCb yBbWJY43nrzVOWWMqy8fhQrvUOVJGQyna+CAAe9QG6L2wXG33q 7kq4qX7RWi4OR04p29pLVlGdvWp8xvWxBbaoYW2rg/hU0V8ftKhuR7CjUTb2JdWIlhIVfm5zivPvGXhs3kczKB+A6VUd AijjPC2oSeGNeUhmVg2Tz1r6s+FHjRdc0eNTIvQZ55rxcyh7x9 XklZcriyx420dJAXHfsK4HULAQSFuAcenSoyqo0uUzzmnqYt7Z rIAxHfj61nySNAdjbwPTFfQHzco2epoNdIbH+Et2FZWoTeYFPH HtUpmcZO42YsGjTAx16U6dFhcE8/QdaopFlrguEX5jjg5qOclZcMeAeKLAvIg1C4Lnq2B0zxmqF0Ak ytu/+vQJokSMREMwJwOwqczhlBbGF569aaYxiSZLHJ2gdKuWd1GADk mh3YLQhmvT9vTcSRkYA7V9SfBLUTP4Wgwx4Ar4rjOKeHV9j73g eaWIZ0XxsAu/ATuQCwWvkLX4lWSRgy5ya83gWb96J6nHcXKlFnNXiOilgoAz2q 9ZOtwn8Qz7V+jn5hF6lq1dreUOpJFd/wDBXWvs3jqw3HAMg6n3pyWgmftF+xxqIn0GwbPVBX1npzbrZce lZHPTJ9wxUbvzVXN7jN3ao365xxTGCyYI44p+/IpCAnNIw5qhkbjPPWo5IwwOcdKlqwnoY+ueEbPXIGWaFGyOuOa 8r8e/s0QX5ea0G1+20YIp6MOY4AReKvhXdfI0tzAv8DjoK63wb+07ZX Uq2+oZtJ8ciTgfnWDpuDujVWkfXFFdBAUUAFFABRQAUUAFFABR QAUUAFYnjaYxaW+PSk9hPY/Mn/grB4mAuNPtCfm35618MR3huU3fcGRWNNXlIxeqViC5bZcZzyKt 2P77UIi3IBGeeK0qO0GbUVepFHq+iamIrOMA7cLzjtU2o+IUs/DuoShhwpwa/F+INarZ+55ArUEfB3xFvjqfxBuJCd48zJwfeu38BRhbbcckYr9 WyGFsDT9D8j4lbePqPzOm00rM7DoxNTrJ++Ybt2K9iaPB5WpFp YxKFB3YHUetQzRgbmI+Y9O9VGy1CStsEcIS0UY69a1LPKwKOT8 vNBnJ6DHVXjw4ySfSo5pGUqAcE8dKpXC9nZjHg81wCxzjOMVHH Oft+0BiQKGyr23LDJuBYHGeaiX5n5boeBWG2rNE+xEbgPcHpTp QqgMRj60S8hq9yZrkWlk2SMt3JqlJft9nUrwM8Z4zU3NETm8ea 22nvyM16j+x94HPiv4oW6eX+7VweBXNinaNzsy+N6yR+r3wz8O x6JoyIvy7Ix2q4muy+CfBeu+I7lwsUcbsrMegAr5WuveufbUXo z8Ev28PjFc/Ev4s6veNIztJcMWPU9a8m8HaYTCp6nPOTmvWyCny0eZ7s8biea dVRXQ9Q8Ix+VCAQPf612OkuBEH9uK98+UbsT3d6ETacA1StLpp HJJyM8YpJWE1YVyZZWXHHTkUgcxgnAB/lVJia94bLL5WCR2696nthvtSTuwT0pFtDpYw9sR0LHpmqExym0 gk9uKlsEuxIoPkoq52+tTxQMynGQOwNZvcLiTK8JA56etJcTGP T35yx709CrhYzF7PHFMjvsFgcYPHBqoibsSLdD7O2chsUiSn7P tIAzU2dyYsybuZ1v1BySDn616v8HPi5JpV1FBdHzYRjjsK+Yzy kpRbPtOH6rhoe8eOfjT4dtfhrII7aGS6ZMA44X1r4F+NPir/AISHXZhEqquSQMf5/wAivEyalOVdPoj3synCNCTe5y3hHdHcHd1PJzXpfgxQUOcHvkH pX6BFWPzeprNs3LJlWc43DBrSupReIh5LDpzSskzndrhNbGPTA 55JOBWYFDfMcjA4zST3DyKxufOQ72OM8DNVLhVDsUJB6mtFogZ jSzuzujE4PvzUrxgx4HynpRLQhvUjWwdLIkkgdsnipbaQRQNuw CFNK+hSehW+yiVuGPXk4qvcuLe9U5JUHr70nLUhu7L82ZkL+1Z F5beaZFbGMelWUtjz7xP4fFvcPOEGOuc9a7H4FeNf7PvUgMgAJ 4zXHjaScbnq5VV5Z2Z9AsBq2mgD5hiuF8UaebeU7124zXkYOfL USPosxhz0rnJ3A3zgLz7GsvVfnlYlVAxX00VdHxU49xLeT9wVL fP71XunIUYHQdelSTcjkuJBHH3Oc8dKfP8AvlDN8vHpVIIvTUl cnYGJLY6U17rzxyOtJvWwr2ehBdqZAp59qiNt5kgwAR/dz1poE7EjAqhyoA/lUExcoGAPocU0iriLKzrsBCn2GKetwqqApzQNMjuixuI9zcZ5r 6W+Al6T4ZTBOMCvj+MY3wh9xwTJfWmmd18TbkXPw8mbqQvp3r4 81q6zqMiFTncc5rxeB/4kz6PjxWw8bdylModSTkfUcmnQsIYTlgPQ1+lH5FbUsW7iYAhj uHbsa6P4cThfGtg27hXGeabG9T9nP2INS+0eGNOYEkbF/lX2fpMmbGP0K1nuYUncs9T1oEYBNBt0EZMD2qNo/l/WmmNMiYbfWlR9o9qLaCY7zgDjvTGl49KECEEuaXfvpsBkiZBqJ x2IBpPcDO1nw5aazAyTwo4I7rXlXxE/ZmsNdVngRUaqXmVF2PqWigYUUAFFABRQAUUAFFABRQAUUAFc18 Q7jy9NYZxUy2Jlsfkn/wAFYde+2fEy0t05ZUJNfJ8N2LZEA4/rWdHqSo6IrGc3FwHII/CtPQHxfrnNVX0g2Xhlesjuo7/ZCQMYArn/AB14iaw8E3xLN9w81+O53FOukfumRr9wkfHL3X9oeK5WB6v0x1 r1HwMhh08yN6d6/XsuXLh4LyR+MZ5Vc8ZUfds29OuBCHfnBPB9akjvwF445/Out6s85yLsWoZcZzk45omuzMRt9PpQr2M5S6k2QIkJPHrirsl0 Y7QMp5xwB3q7Eztcijv8lQQd3qaGuQJyTz7A0LsVyq+oT3mUGA Q3c4qLTHD3ZYZPbNS2OMb7lia83AR9T2Hao1GQf73oazbKWiKg OLhjzgfrTbu782eNSehpbmidxuu3mxSFAIXHGaqSXLpFCoIwTz xxUsaZda6JQKBzxX1//wAE4PBqLqRv5Bls5rz8fJqB6eUK9Y/QbTrxV0PahxI/yrzXkn/BUb4pj4M/stjT4pdlxe/uyM4O0DJr5utUSpyl5fmfY0Ic1SMfP8j8D/iVrR8ReK7h2O4ly3rW94OsNqqD9/GcV9LlVPkw8UfJZ3UUsVI7zQp1jt8Dk7sVt6Reys4TBx+tekeN N6FyaZSGzzxVaGVmDbTkZ45pXIlOxLaXYVn3kA5x/n86SafM5A4wOhNCCM7u40JuJ7DGPXNWWm2wDHTOAMU2i79hEvM IF+bOMHFR3MfQg5zjtStrcFuOSZTFhjweBgVb+1bIhgD8ahpbF dRJrlJmIyCAAPrUF7ErWCkE85+XFSkEbXDT41+z4LAcdKVLUPu LevU1aegSWhDMEklwM7cdjUxfy4VUgEA8Uo3BbDTpJ1B12kFie or1T4U/BBtWgEzg181nk7RPsuG3GSsL8aPhhqOnaGbexQy5XoB0FfJnjn w9qej67JDcW7IQecivMybExUmelnmGmqRW0fi+AXg555r0rwOQ lo7AJg8nNfY05OSPg5qzszatVEplYjHb6VfiYRQrjqB0xnNXY5 7K5Ib/AM7T0zjnuazZmWLcgxmiMdxakETxy2jZABqn5Y3nv3xinCV7jW pl3UoEshGOPTg1XeTdhSc5HOKq2hM12LLzmSyAA49fWo/srS2vyk5I7+lQtrsm73KZuWs1aPO7HAzVPUHLKjODnNO3Ufc0b W+LWaqBuJ7ntQ9iZIWducZ9gfpVFPsc14r01buHbwuBjGa5HSX fQtcVgGU7uOOKmtC9M6cLLlmj6W+F/iH+09HiIYH5fxqXxpYC4UttBz6V84klU5j7hqM6DPN9UhNrckL wR0I9qxr5XwwYA8ccV9NQl7iZ8LiFaTRVVvM5Lc5656UlwF2cc kdM1ZghshJTOACKnnQvCpPUdu1NAgWXy4gSQwFNDB4gowue4pN CYx13pgcdvc06FOmQAAOmaY3sFyPMA68c5FVXB8tuuAadib2KN zKwbgjdnrTllJAf+Ie2alFLaxFf3brMgHXjP1r6A/Z/1dR4eWMsN2OeetfMcVQbwbPseEJcuLPUfF0yXHga4XdxsNfJOt 2vl65MckAPweuK+c4J92tNH1/HVvqafmUyhIZj8ozkZqk+9TyQDniv0uK1Px5Se5c0klyW9eldH 4N/c+JrVl6iQZoqPSw1qfsF+wPqvneEtN68IM5r7s0AmfS4/XbWaRzUl71ht1HdxSjbjbVy2MkgG8Y4pK50MlJxTCM9sUxEbrg 1C64Hv9KobG7sdaac+vFFgGsxA64pQ+MCj0EOEnbPNDkFe1HUC CXOce1V5hvBzgmmionpZOKKZQUUAFFABRQAUUAFFABRQAUUAFc d8TZwLNgSKmRE3ofjl/wUa8SpqHx3vIgAwjTHrjmvm77YJ3HAOOPrUYfZg37oOv71iuOv rxWh4ZnP9oDcVBB9arEO9JmmD/jI6u61MJG20jpXDfFfWP8AiipwGwWGB2r8czaN8XFeZ+25VLlw x826LCW1h3B7nJ9a9R0SQxaMFKjkAdeK/YMKv3MfQ/F8friJX7lqziMsAABFTRqxjf5ckH8xXT5HDe7JPtW3YCMMeODT xcj7QMHJ74qrCkraGsrBoF3H5s1JM2FXJB447VUTObuynJdDzQ ccZyDUYu2WQ8d+ntSkuobkiT7+pOOuasaOyxxOSv4k1lJnRF23 Jpf3eCuARzTLe+WSByww3Tis3cdtSmJiJ3GA2TUE9wrXQzww/HFV00DlsZt9dsWKkjOcip7YmSSFHx68HpWcroqKZ0OlQreXHr2 +lfcP7FdkfDmhRNjAfGTmvNzOVoWPcyOn+8bPsfwVdR31/ZqHG1PmPNfAH/BcX46nVPE1vosUwaK1h+6G6E18vUkuSz6tI+yw8Uqqb6Jn5aWk DatrLSksQTz6dfWvRfDFoBbAkkAdsda+4w8UqaPzzHT560n5nQ aVE8MAYrlBxuPFdHpMcbDdg89K2bOO2ot8pjRjjjv/APrqK0JVGJGM9MHinZCcUA3MQGXbzyDwaUzBLhj6+lN7k8tth3 2oE4wKsA5UDgDr1qXe5TdtBsaiIgYz7GmXLMnc8t0BpscX0G3p FrEjOQCfQ1JPOI7ZDuz06jg1kmVsRSszgBTu9fanXV6y2IVcA+ lHQl7iW0m614YbifWrCXHk23VgxHOabDTqQwuME8DtV0p59uNu OvX2qZPWwc3QtaDdNFeRIiEtu/Cvp34JKt5YwxXB2DAxxgV8znVran2nDq9mk0eyXPg7RLTw5JdX dxbeWkZJZyMD8DX57ftW+LdEuPEd2LJo5WaQr8oAHX/61fJ4GnP28VE+uxlSEqMnJdDxTw4PMnLnDf0r0Hwpcn7MQPxr9 Npo/J6795m7o8vySEqSD2zWhbOJYQMALjkDkCq3Oa99AvFFvAqqQOc msu6k3owyR/OmnoCbuUZrgwQkAryeKYblnUFjt46jtVRir3RbZlahdhXbggjo DVSSdYACNxJGTkVp0ILEs7z2QZTlevBp1tO/2XIPHucn8qySuyL3IMNIXOPzqjrEitCOG357Va2NEXdMCR2iHP OOT6VaebzYgT0PUA0NdSUru5kajbgoxPAJzjOa43xNp/lv5gKqe5NE37pUXaSZ6F8D/EZjIQupHQDdXr+pWwvtNPPOPSvm8XG0tD7nAzUqFjyrxpbtY3B AB4Oc1hPcZV2zmvZwE3KjdnymZUuSqyvbQF2LEgkZOagaAyseT 69a7upw2VyNo2KY5ODx61dhRTBk8EZ5psG7Fe7jkCjgDPTAxUM ZZYiTycYz0pPYSLMEpMWJPXOaa0y4KqFUk5wD1p9BsWRRGhO4q OlUnus/KGOR3oE9itMocEA7gRxii1QDPJI9C1G+okveK+pRGNs4Kn9K9Z +AeolLLaSd2OK8LiO0sIz6nhiX+1qx61d6p9t8MzRgZG3BGe1f OXjB1GtzKVOA2RXyPCStimj7bjN82D1MmcmaPgkjPGBVFpMSnd gEd6/TI7n5A9zQ08gxjqO45rd8MhodYhOdpLAg5qZLuVF3P1m/4J46iJvCdiWYk7Rk1+hPg5/N0eI/7NZo5oq0jXzke1DCrOga3zUxxihasFqMYZ6VFLx0pCImYE9Kax 7d6pDSI2JyKVXwcUriuPIzmkI9etUCI3Udv51XnXJPHNBVz0qi gYUUAFFABRQAUUAFFABRQAUUABOBXnXxivhb6fOxOFCEmomyJH 4n/tkasuvfGbXJlfJEu0V4r5JEi4GPfrU0HdXE7WLFpcFXw2OnBrS 0FN96COOOcGnitIOxvgHesrmnqd4Y4JBu5xivOfi/qBh8LH5ic/4V+TY631yN+5+04GXLhJeh5N4QjWefIAwTx3zXqFrZeVpMePl4 6Ac1+t0NKSR+LYt3qt+YttKYo5RjJ7e9VrO/cBgxHzH1rSxzS8hd7TNuIyQOMVDFcM16eT06npWrjYnqbdrcFd qN3696mut0zZBINPoQU498bk5bOcZpXvB1x7DND1Q4RJDcR+UW xg4x71o6LOklpkrzz1rnlqXFdy+zqCQORjv1FVPtMTEArjPPHS sVK5qndlH7WkeoEZ4HvVK4Xz9YJU8AcjrTiy29Crf2pL9AxxnN NsY2N7jnavTtVvUhM7bwLbGa6jABIJ+7X3P+zwi2fhq1Xo20ZN eBmjsfUcPJa3Pc9B8RT6VZXNyrY2Rkj8q/Iz/goz8SpvGfxU1OWWQyN5pUZ9q+fopzqRXmfVYl+zhKS7Hz94Qg8 +6QgEg+/SvSNK0wiAY5GOwz/nvX3tNWifmM3dmnHEbOFFcjJHStXS7kRwkZzng0Svcz6kl/cB4tvy4PFQF/LAQA5xVokat6d3AHI781G9yySNg5cn8KbQJ7Cx3GYwCRg9frVq G7xGc4OOh61LYnLUmt5VkXdwe5pLybYwxtJ6mlzFpIg1NvtMaE 8qOahvYme0jdGG3t14pSeth3Q9b1lt1yvJ7560l1KvlDAz9RSd 7iemwlnKZIsKCR6VbUFrcEnPrkdKd11J9SuCyBs9M8YrUs5fJt QxB/OnJFPbQu+HdQjh1ITOflB4zXvfw/8SxeI7GK3tZgkuAMKcfrXyWd3bs9j7Xh+aSXkdB8QPhDruq+CL h5NYnW3KZID8Y+tfFPxX+H0Gj3k+648yQEjcWyc14uXWpV0ke/mU/a0WjgNALxTtgYUZH+fWu98JymJXx+or9BgtLn5pXS5rI27K8Mo facFelaOlXW+2+cnPf3puyOWWktR+pTCSNSCPxrGv7rarANn1O MCnFAnZldh5tspP3c+vNQTThHWMYGf0q1JhzNGXqMyGfcpBfPS op4/tg4AznHvT6FMv2tjusMDkjrinvbmO3GBgZ6Uo9yYpXGMq29uQo we4zWfqdq/k7xgADPWnbqNxe5Hpyl7YZJGa0shIuPzJ6UnuTf3ijqEJDLjrz WN4gsBPbkHgYyadtLF2G/D29/s7UYxvxg5+le/eG5jdWCjJf5ecV8/mCtM+symd4cpyfxC0cM53BF/DpXBXFj87D5to9B19K9HLZLkaPMziDVTUhjKxxEgE+4qqCwJYE CvQ6niS01I5EaRVRsk7jnpV23Hlw53Hb9c02K1yxI4njwBk98C qqwCGPOTz1wM4+lDL2IZFOwLtzn9KWAKYuVwRweaT2FJ6DZ0fG OTn1HWs+W3y2OD6kU7ai6ElvZMCARx2xzUwtjEmQBnHfAAxRex SM29QyIxzuwe3Q12nwZv9lyyZfGM4FeRnkL4SSR7eQSaxsWj1+ 11L7Rp0ydPlJ/SvCviFObbW5dwySfyr4nhd2xdj9C4ts8AZsUiT265Hy4pJbXZJ nB5469a/Tb6n5F1L1pYADBxz04rU0UlLpXckkN0xRfQqOiP1I/4JzamJPC1jjnj0r9HvAUu7RIcntUs5l8RvChunekaDSuKaR8tN jYxxioXjzTiOJC0WRTT096aQbCABu1KExQtibC4/KkwST0AoHcRlOKikXA96Y0eh0UFBRQAUUAFFABRQAUUAFFABRQ Akhwh+leOftCap9j8OahJnG2JqzmRM/Dz47a2dX+IutMuPnumB/M1xEsJWTKnjuaih8KsRVV9EQLM4lYbs/5/wD1Vs+GQRLycD6UYt/umdeB1rRRf1+PFu7Z7cV5Z8aJz/YSK24g9favyyrD2mMjfufstD3cE2+x594FiPnoxGV9Aa9Vgl3R x5JbA4PWv1qGkUfilXWbZDFcbLeY9x0p1hFGyoWUZHJ4P5UczU jnu1Kw15AblgowufyqOGFhcNxknjJrW99QbsTxXISZeNpHHI9//rVPJqBjlOBx1xRfUpRIor8FeQCx/WrAiDkNwD3pMyhdSK+qDKgBs+nNXdOkEemkAncBzWM30Nk76lq C9LWrKcg+uetUnuAmSgViF7dqxv7xorWsZtxelJpXYEbenPSmW GqpLbmUkFiexrVL3R20sWFlM6hsjcaesZjuQqBfwqHKwJ9Wdx8 N1P8AakKkcZ5xX2X8Ir42llbgfLwK8LONEfWZBBWuek+NvHSeH PhxqU2cP5Jx+Vfjl+1LrZ1nxvdOGz+8J/M14WXO+Iiz6HNG4YeUvI534e2Z+Uk/mK9O0clLdflAB/SvvnsfmTepcvbQSyxFeQB61btIhFbseDz1qd0TuQS/vCMtj+tO2iN/vAjvk1omgkrkZZQpOQGPeozHg5I3D3NJi2KslyynbtHXrVhLn5 cEkZz25oTuO9yxaXnlR/jwO4qSW6EsgVT+NRLe4WuyDUjItsFBBUnnNSXBZrJcgYHOcVPU cSWOJJLUAAfXNJdWzC1DDBz2zVJjsV7R2tlK84P51o20hmAVV6 ChrUTjqSmzVs8/Ud6fdRbLZVVQoxj1pOVlYdyFx9mtN2V4HNN8KfFG/wDDmoh7MOMHjjFeLjqKqx5UfQ5dXdJX6HR+PP2q/FWt6D9gL+VFjoCefrXiWu65eavK7Tys+WyQe1cWGyxUql+x14v N+eHJEi0a8CyMu0Z9NuK6XwrKHdgdzA859K+khK6PmJbmwkjQh thIU9cc81o6PIkkbh8D2ola1jGaVtSa8nEsJOAP8azp0UWzcZX NEUCtozPu5Ge1O3p1FZ6ERoXcjkYzVtkyZlXH7qTfuBX3pIbmR dpUDHpt61W+5SR0FjfPHZcqOemKsQXCrp7Mc5+nWoZN1e5TfBj GTk9/aquqoTp5UA5od2h3bRn6ZhlVNxPHIrUX94MlsYGBitEuolHUCg mjO4Lgt1rN8SQmSM7CGO3GPShaDb1MHRIza6oGY4+bJ969x+Hd +slnGueQOOeteJmkVa59Rkc7Nom+IFv5loX5xjn3rynUbjyJGV PlPGWyTipyubcnEjO42sykJwjHpgnuOtV2UxkhSwHsOBXvHzjV 9yVUeKPc4zn171PbReeduSPbFMDRFipTjJHaoVtSQTjJxxgVNg sQXUSwR/NhsD9ayIr1muiAp2g/nSSIvpdl4XDS5C8baz1LSy8LgA9RWiQ3e2hcgCCI7htPP51BdO Rnpt+nWkWn1M67nDxfKSGNb/w0uGt9TAUEsTgnHGK4cySeHZ6uS/73E9a0C/8AMlcE9RzivKPidZMdekP3ScnGe1fA8OJQxmp+l8S2eWyv5GBp m5kPHygYHOa1Y/3seQAfoK/S2fj61LCzmK3KuPyHNTaPfkyqqnIDc5GKUtgvZH6cf8E39QW48 M2YU8gDiv0t+HEm7RIvpU9Dljuzpic0gOBTtob20GM2PejPFFg sIwzUbjI70ARSDFRP9aNQsxD8xoBxzVWAUMPanhdxpJiGFMdqh m5HaqKR6DRQUFFABRQAUUAFFABRQAUUAFFAEd022Bq+df2u/EA0f4ca1KzYVYG5/Cs5kTPw78Yaub7xBeStjDTMxb8ay57sosYBGPbrSw/wJ+RMk+ZlcMW+b2zW14XnJbBDH14qcdb2TOvLY3xCRf8AEE+yw Jxx615d8aSDoqFhuJ71+W03fHpeZ+wWtgGmcf4CQGVduS2eh7m vQ0mH2UsMZHSv1lbH4vV+IjuX+zWBfIOf1oW7VLdMkKTzjtTau Q17w62lWNd5IPGRmnQ33mgMQFXt6U76WItuxZGGcEfhjio5mwd 247Qad9LjnKwtqyyShtoIA4q7NJ8qgA/hTi/dM09bGZq12beDeQeO4NV4/FaWun5ZgrMeprGSubxirE+n+LYHYpvHIx0pLDVlEzmVwcDA7Zr OxfJ1M3U9ShNrMS3Jz1rmoPEht5Ut9xOWwBmlFvYp2R3el2lws MUjqxBx261Zlv1g1KNGz65ppEuF9T0L4c3KvqsXPGeCRnFfV3w zvgtvBhvmwK+azmW59fw9tYvftEeITY/C68wxBMZ571+UXxfvxe+MJ25ZtxyO9eXkq5sSke3ncl9TkX/ANkywKzZ3Y5AHvXoOnIVlQZIx71981ofm+hpMA8ny8cc0912Rk KSR71F9CFoiiyFZxvbBA4HaiWbLgD72KtbEp6kU0xWMccdsmmm 9Y7jgBT6im0mSyCNhM7NjJ9TQjMZcJxx/nFJFLcnYll+XCgfjUMV0UUiTGScYqZLQcloWZNTDWijB3E9e9W 5L4GyUZyccVFrIbSSEUO9r8hzx27VL5sgtVXGSO9OwLQZEPOJ/u1s6ZZ7lB/EDPWmpA5alj7CGuR0Axkkmrr+Hjc2gIG49en+fWuatV5U2jSEd Stb+B73VoNiRsVz2BxUll8L5tOvkhdMux5FeL7SSnzM9+EI8ji afiH4JXNtaGcxM0ZAOSOK8j8V+CpbXzG27VGe/862hif3hwSprlujj9Mtp4dQcsATngZrqvDcwtmPf2z0r16OxwP c1Ir0i5csM1a0qcSAhRgk1pJWZk3qW7kMI89u2DxVO91DFoOMZ Hr0pR1IsyhLeKtrjt3rKnuDcMVUlc9Md6tltIzbtTFIxywAOM0 +1uB5QHBfPGecU76ahc27SVfsR7kjHXFSyXRS165A/WptdCUFYjMv2iBSMDNJLHmFgxGBwT60kyktbGdbuEc7fwxjrWn asrxOpJ4PWrEElm5gAQHJ/SqOrR+VZsGPPYj9aibfQmbfQ5mEkXxYEnHfvXr/w1uNlrEpOTjkGvLzKzge7k1S1Q6jxjAZdFbgcDn6V4f4iuvL1C RCRwc+ua5stb9q7bHp5zC9NyKkN5iNt+1mOOOlX9Mt0lc9F449 q+iaPkr6lmQoifdG3sPSnWsYJODtbsQaTelxtWL9hbiVGGSSp7 02aRYbb5QD9DU811dC3Mxx5yMWB68VlxKI71vlOCR+FNLQm2mp btYcyMAQD3BNTJbpGpIGWJ7f59qexS2KN3mO1Ygbc881i3N69x IQSQufWmkIrXV28ZwAGBPQjrW38PdYSPWUBVhzg4rlx0L4eR6m UytiY+p7L4WYNNu3HJGcZrhPjLZCHUGcLgmvz3Jklj0fqXEEG8 vl6HHae2yM5I69a1tOChGP3jmv0xH4ymLqFyrKTwCCMcVX0m42 ygEknOaT7FNo/R/8A4Jl37xaNAQ+7BA61+pfwovDdaNH6YFRE5Yr3rnYZ570MeTgi tLHTYaOetJzmpJAemKCNwPrTGRSpjtUUgGOlF7he5ERjPpSAkN im2JqwoUk9vpUi5C80WCw1+lVrh/cYpjieh0UFBRQAUUAFFABRQAUUAFFABRQBBqLbLNz7V8if8FCd bGn/AAW11y23902KwrbESV9D8VtZkLXchyQGc85461XhYSXCHnaBn/69bUl7qCW7JJ3Czn/ZHFbnhI4VzgZ+lc2YO1BnfkyviYsn8SsWslVR35968u+M1yUto oiQBt5r8yw0VLMIvzP16rJLASfkc98PYR9tJwv5dRXaXKbLRmG QD3zX6umfidR+8JdxPc2cMRPudtNuLVmhAGRtHYVSasZSdtWQ3 P8Aqwg7YPNT6UjNEADgd/epH8SJGLG96ZXAxg1HfzAoVc4A6GneysLlsRabuQhg525OOa0/tG1Ceh9qH2C12ZPiebGnsMct09q4PWpjcxxxbm+9wO4NQ9C4pR Rd8HWV0/iO2ieKTDHBJ54r074hfDWfw7o39oBGVSB2ot1LUraHlU+rPLPt A+U12/hT9ni+8VLb30XyoSDkDIqIRu2KckkfRcvwft9K8AxNLt3xxjJH tXz/AOIZIj4sCIRsjOOOh/yKGvesRBts7XwPqHkarAiv1Iwa+nvh1q+6O3OT90fhXy+d7n2H DzaQn7Tmu4+HU6bsDZzjvX5kePGW58Uzsp2/vD/OvNyDXEHtZ9rhmdf4CiIQE9McEdxXZW8LibcQWx0r79H53YuyS rGx4ycDGKlivg7/ADDA2/rWaWpklqzKuLjzb5iCcD04p0S4O77pzzzzWlxvXUS5IKNz+fao ZFDxZPzEihiIlmCxAhiKnsx5mcgHvSY5PQsqFiZiRjJxz61Sm2 TThFYfMckVEn0BvsNubcwSBd2R6j/PvU+0tCF/2uPejdBbuWoJXijAAIAHOaDqLSRFdo24waURR7EumvsAznBPWu q8POs0QUgMcUmmhpF2505zMqgD7wx716B8OfhVf+KJEWOJtjEd s1x1Icy0NotLVn0h4P8A2arbRtBja4gG8jPIrmfib8CP7Juku4 4CI85GF4rixMNGejhK92rlu58Jxar4KZPJ/eBOuMV8t/GPwMLJLkKFDLnIryJzaqJm8IfEj5vuZjYa46OQFyfwrQ0K7M16 2cHHTntX1FNtxTPIno2jalmAchWX8+an0iYtISOSPeut7GEloa Mt35zDknArL1VyikZ5PX6VMdxqVygG85OeMdAKf9n8rkkDA446 U2hsy7qHMnAYnuCahW38pS2SQOx600xLU0LKVmgUbvl9RVq43i 1OG+tEimVdPnbIwDtHocVM1750LISSc+lStRLQgsgolGSMZ7mt G0kKyuSCR7VbJ30NC3ZXtDyCegqrq9jvsnJwB2A5qOpSORayK3 LELkA8V6b8NA3kRsc46fWvNzGmnG56+T/xTufENuZ9EbHUrXz/AONIDHqe3JHPXHWuHLp/vUke1nFN+xZTVD5G7JHHcVb0vUEBKqSWHY19Kz46+h0FjpUuo2 TsBkKOp71lpc/YrzDMBg5qW7BqbOk6tH5h3MMkdR2qC+mSRwq4BPSoirFNaGTdT jey5wPc1WQq0m/JbOepqosi+hZto387nPPSrwh2pgNz2wKcgsZWtZihK9j156Vgp OPOxgbs/lTg2LVjpVVyeBn0/CpfBGyHxEiZKjPOBWGL1oS9D0MsfLiIN9z3Xw7bFpoyAduO9cv 8dbN7dQSGx696/Ncumo49LzP2LN055fJeR5baXhBwckE9BWxYXDGMkjj+dfqTR+H 2sxbpvtEf3vnJwTUNnbNC+4GhIdtT9EP+CZmoE6XAm7PzDpX6s/BybfokffgVjFWRzKNpndduKb3qzYX3pDzSQkIc5ppBByKaGhM8 c1GyjNO1mO1mMCgmk8rnvQhCBcZpScGhMRDNLgVUml+gFUVE9J ooKCigAooAKKACigAooAKKACigCprbbbB/pXwV/wAFVdffTfgrfopPz8cHrzWFb4WR9pH5HXlyDdPx0OeeahhnAvA wAA7VrFik27jpp99yxI6c4rpfCyZtQ4B561w5rUtQZ6mQvmxKL +uwgRxgkHmvHfjvJt1OJF4OOlfnOXLmzJH6nmEbZdJrsU/hzGu8uw+XHFdNqirKsY5Cluor9VR+N7sbqUbxSpGCDxzj6U2KS RTtfOO3FMiSTQ2SA+YzE/u/X1q7YIBbAEEA/rSb7ExfREstuDICOBj8axdXdhKwGRt9ehoQ1sMsbkuAOgAyO2a 1rf8AeA/dIHWqasxaMyfEpZgApJ5wcjmuc/spofE2niZG8qSZQD+NZvUaR9s6D+zLptx4GsdUtYY3mWMMfl5N cB+0pcTP8O3tbeyk3oNp2rzSqy0JpyTdmfJbwtBeRxyKyOG5B+ 8K/QL9iDTfD/jDwFFYXbRx3O3GTVR2LqxbWh6x4z/ZJ1XxfoF1Dpk5aHGUxzn2r4t+LX7NWpfCXULqfVgUYElN3Vqiy i+YmMrHP+ELjy9YhYYPPJ9K+mPAWpj7LDggcDPNfN54kz7Lh9X 0Kn7S13JL4AmO7GEr87vFSBvEcxBOdxBz3rzsgS9uerxA7YdeZ 3fw6G2Ncjgmu1gO9MArkHPWvuGz8/ejGyW5d9+Rj/eoADgA8nqeKGZy8ijOF84444pd/IA+b8e1WthKXQidXRRuPH1pk04kh2ZGPapYW0GwqsnI+bB/M1a02VLcMzYPHGalSBdht5dmZlKKT9K1NA+G99qLC4CuOMDiho b0RX1fwxdaPdbpx+JGCKR0SJlLEEcDFC0KWpMxjdcL3FRC3CTD ABHXp1rPmsyW/eJoATOm3AGcda6PQz9miDBsN6Z7Vb2K3Oh8NXAutaiyV+8Otff f7IXwutNV0a2laNd2Aelc8Y6k1Ez63h/Z5tfEukR4QLtHGKo+OP2c9Ov/AAqbaWFDIq4zinOmmnfqVTqNNHiHjn4GxeF/CF1LAgJRSelfnJ8frm5h1PUnddgDkbfSvmsXRcKiPcws+aEu58 lamd+uytIfpmrujXqQ6iArAe5r6XD25VY8qtZyZ0JlyVK5x6gd atWMhz1Jyck4rom9DBvQupMoJ2tlu/0qjqwY2+c4696mJHWxVtomEIAO7PNOlLKyglsU5Oz0HezM+45n ZQBzxxVW4hJkCY4xyM0LRXHbqaunyLGQvOP51cu7YC1MnO3rTu UULCRYFbKnJ9+lWrBkVfnxnqDUy20JexE1sn2sAN/EDVu5Uwy7AuVxzTjtqOJZtJDCOmR6VPNKtxBtbrnt0qd0TF3Rh 3VqqO5zkk8Cu++H1qfIXAwMCuHMP4dz2Mof71Hfalb/APFNyM33tpz7V83+N5c6y55I3cZFeRl/8ZH0OcpewZBEBcKqgHI6Vag+HOp3GLmJSEJByBX1S2Phk0kep+ E9Lt9O8HSLcsFl2n25rw7xN4pjs/Ek6GQYVsAd6Jb2HTu0WrLXYtRfMEig5AxnirMGtiLXI4Sxweo7 ihW2NEP8UyrDd4jO1SOM1WtZA0wJJz6ZpJmetzZtZCdpI2n07G rEkoEO4gA98dqGNsxtQuhcuc7do6n9aylt2M+9NpANEVYCG7Bg 3Bh8/cg0eBwJPEsTHB3HjmssT/Bl6HXgHavFvufS/hmwWQwMADkCuf8A2htDzpysQQccV+TYOrbGxfmft+Jg5YBtdjx Gzt15QD5M9q0jEY7UH5cHtmv19SvE/B5fEylPcrb8kgbvfpVqwvUlkwWU96aZPU+7v+CaupFJwnO3cOK/Wv4HXe7R4x0+WotoYSfvno45ApCcmnc2uAHXj60p6etK2graCH kHnmmkGjqHUayjHvUMi88c0kIRRSjjFNILAx4Oahkk2e1UPYqz uWHWoGUnHXNMaR6bRQUFFABRQAUUAFFABRQAUUAFFAGX4ql8rT Xx6V+a3/BXzxTJB4It7MNkSyjI9q567STIfxI/Mi7TZMQAeTj6VDAxE56gAdT2ra10JhLExfGcA/rXb+F7M/YE659TXkZ5K2GZ7nDlJ/WbE3iK3JliwDkcj3rw341XudfVQxLV8Dkj58wS8z9NzuXJlUiX wHIq2DsA2zgD5e9dHOcSQBvmUnNfqzR+MNXZJcbX1HJxge/BpGaPzRypx3AqVdGeqGXt0uxTnnp607TEDIMggZ5zVj0WpPcXa xnafnOPSsXW2ypYgEk4pIFqQwSkzKNqgdcdq2rBlVSWLZ9zzVt iRm61HyGUZBbvV/xDoh1/RrSWy2rdwncO34Vg01cfLrc+pP2O/ju934fOna0ojWEbTkcV9n/D74GeCPiH4EnvLhLaTehbnHHFHN3IqKzuj8t/22/hvpnh744XdtoojMCMchPXNZ37Pvxub4b+II7a5YwxZwGzUxbsd C+HU/TH9k79pvSNR8Oy3F7fwLEqcKzDJr5O/wCCjnxj0v4g6xMunTpIPMA2pyPf+VTUTkkYxjeWp80+GZWOoRn LcEA+9fRfw+1Ix20PbjHFeBn0fcPsOHtC98dZPt3gCYHH3Pyr4 C8W2gTxLIDwd3X05ryshf79tHr8QpfVjtvAyeXajPy4XJIFdTY FjL0wPfrX3cdrn580Nv73ddBRnbnj0pn2zYuSMGkkRaxVgb7QX YkqQfShXaNsA5PoOnStWlYzmtbheMJAV/LtUNxbERsCWI7nNRc1Ww2xj2QAtyOc+tamlaTJqzrHCu5yfSpe iJnpse8/Av8AY5ufGIgmnik2HB6V9AXn7Ltr4V0gx+TyBzx0qm+VEyk27H zz+0v4QtfDWiu+EDL0PSvA9KkW9VQxIOcDms47s1itLmmbYQyB S2R2NRTyCN1xhi3Q9ealx1I5dR0U+2fnPA6AdK1orgiFVXkYxw KvyHy6lzQtb+zagkgyACCa/Qv9gP432VzZW9nPKqPkAAmsZaO4Su1Y/Rz4da1Be6GpRlOVrG8fal9kSXgFcU6r924obnjOreLdO1S1vbK aRM4IIJ7V+XP7d2pad4W8f39vG6iPljg9K8fEPnpp+Z6NLmhJ2 7HxNrd3HqGuzPF93JxnnNO0iyZbreSuR+tevRVkjmkkkb5uSFX kN3AJ61ctpgPmViSTzW7RnYti8O3AGeKivbsLEqMSRgZ7moaJc eoQzx+SOAnv1xSyKGXaM4PvRPV2FuZN2fLvOo2jqamjG9d23B6 c9aoL2Rd+yBI074P40t3OQoQ9AO9RNNCbZQV/MlIx838qs2x2yYJwPQd6saQ7ymiu9xAC5GARmtDfGGy43CiT0G nYsbo5IlC4YEdRx+lVbuPbbttOc8AUo23CKMlTJ9pAY4Fer/De38ywUkHt2xXnZmv3Z6uVfxUegatpu3wnM5UfcPJFfK3j6dLb XHUHPzHAryMrn+9R9Hmsb0Hcl8J3Ecuo2qtwu4Bv8a+5/hF8CNM8YeAIXjjjfKDoM19erWZ8DWvFox/ih+x8NF8G3uoI0ixgMVUHp7V+bnxW0h9N+Il9bRSsw8zCkn+fp WLbUjqw7vFs6/4FfDm48RXT+W/zgZ24+8aveIPDmsaV4jNv/Z0plDEAgZqlqtDFSu2jlvGXi250+7S2uFb7Qj/MCOR26V0PhLVPt6I7dW56U7GnQ68W5AXHQ9xVe/zFAQWzkfWkxSWhhThmcsRx9ajF/sYKSPfOKpMFJEF7KZELDGOxz0qPw4722v27Ekgt61liI3pNHRh narF+Z9TeCG8/TrU8fdH4VT+P9n5nh5WQnG3HH+fevxmDUcbZ9z96pwUsHbyPnd 0Nu5UffzwMUXNyJIsA4IHY1+zUXeCZ+C4hKNWS8zPuczHKsTg9 zU1nFvcHcQM8YFbx7nMfcX/BNTWl/tAROfm38V+vfwEuFfSIsd1/Ks2ZTdpHqQI2ilY8+lCNUA4oY8UJAkNLY/lQPwpISENRuM9+aAZH0pC1UDYwzfh71DM5PNAiEZLUpiyBTGme jUUFhRQAUUAFFABRQAUUAFFABRQBheOphFpb9jivyr/4LF60v2jTrZWJbeTjPtXPWWmhm/iPz3ubkGUnlgOmKY90jOCAAffqK3XYautCWNzcSr0Hzcn1r07w zZhtOh4J6dK8LP2vYWPpeF48+IZLrmnl7roDha+ZPi7d/aPG0wz90nBxXwvC8b5lr0P0PiVcuWSNjwLug0sl1LE9eM1uX8o mvolzt5r9W5tT8XuR3VyFmcknk4yaijJ8wnnJPAptXE9UEjGZw OlXI5PIQDaC2OOaqLsTOPMrELzMXYqCAvWqV/MrIvQc9CadkhJ22EstjXiYwSB94GtQTCCJmB5AxmlIafUhudlx sBwckdTUF3Jc6bdiS2c8DkZ46VmzRaI6Lw78aptE8KXlqINt5J yHA6H1rf8Ahv8Ato+M/COjNpsF5MIGGCxY1lbmegRtsYmt6y/iTVJLy6kaS5kO52Y5JrmfEnhYXMqSRgIc544zSimlYG7ysT6Zr ut+HdNZLa9uIIv7ociqMNxPeHzZ5XncnJLMetVZblyl0RoaJeN DqS7uxHTvXv3w21JJbKJWOD614OfRvBM+k4f1kzp/iUi3fhCdSP4K+D/iPp4tvFkiheC+c14eQu2IPdz6N8I32Or8C5ktyWxwMc10kBMcT egHWvu0nyn53ra5XBWS5AyTkcelR6tIqHAwFA/KtU7g/MzWmK9Dk/nmpbaRzKC4APXkVREr9Bt3qLxSDA59hin3ly0iKCQGzipZUbjN 2y2G08jqO9eifs6x2174wtxdABA2M5601bqJtWP1O/ZX8N6ddabAkccbHaMfLX0Xc/s46X4t0RzNEoLL1xzSk0zninufCX7f3/BP281PS7iXTZXCJluBX5y3Xhi68K6/PYXW1Z4mIf3rKOkjspu6sTajIVdSSPzqpAXa6DDkenpTTuiZ+Q PM8bgjHP51qwX6x2G4oM459ah36BILG585zySO9d78Lfi/e/DjWYp7eVkCtzilVjaNgT5dz9Av2Y/+Ck9vDplva6lKFcAD71e4eJf2yfD2saMzi7jLFcnkVwPE2VpFu Dbuj4j+Ov7Us2k+Mb+7srtlgIwMGvhT4/fE6f4m+K7m5luGk3HGWNcmHg6tTyuejKfLDzsed22jLJOCc7c4 xk81p2doBc7VwRkde9e7FW3PONiWz2xhs4AGcihFCgEnBPU9eK 1eom7j5YjknO4fSoLyIJEWYkMT6cVNiWrkMEhMfzAEDvUxuCip tJb15qbA7IimjFzKxzxn0p7qxZQuRgfNT1B73LMVzuAGeeM5FW XMbWjFhlscfWpSJM6NBHIx+Xp6Yp1jETOpOMj8atDdy1LcqSik gMTz1qW7kyiEELj0OM1K8xoSC6E0Yyy+5A6VHqF20ZUZJT/dqmk9B2I7W4W4ugAqnJ64r3D4ZaOr6dG+0kkdSOteXmnw2PYyh L2lj0HxTpgtfA0zHgbP6V8OfEm5ePxJMQWxvwTivFy1/vlY+nzJXwkhum3phQbCNw5xX09+yL+2Y/w5WHT9Ty9vnbn0/OvsOh+e1IcysfXnin9o7wr44+GkmLiEBkOVyK/K74zaBpuofEnVbyzcMslwSmDUbyLpLli0bHwauZPB3iOCbJjiJ 5+lfT0DaPrfk3qxxzTeVkHHeq2Jcdbnyd+038ObjSfiEb+Vlxc sdoUZ24xj61neErUW0yKgIA65FEC3ZnYW1wQCSx9gfWq+oyFoh 1PuKTWodLGJK/nE5OAP1qjLGUcdOehHaqS6EKCIZXaMEE5Gc03T70Q6nHIyKmGH HalNXizopaVEz6d+GWoi+0C1wea2fi7Ym68Iq/LMB6e1fjGIVsf8z97wLTwV32/Q+ZdbhFpdlTjIc+1QXm2SIqBjPGetfsVF+4rH4PjbqtP1Mwpt3 lgzH6fyq1pWVxknB7V1KW5y3PrD/gnhrT2vjNY1wYiRnB5/ziv2V/Zv1QT6XBzkFR0rF9zGp8R7WDmMYPOKaJG3AEfWkaEgNBbmncdx Dz7UE8ULYFsJ7Ux+vehXAhY8mmOM0dBED5znmmlhnGOaYmKqE4 7VIfu00yonf0UywooAKKACigAooAKKACigAooA5X4lTbNNYdK/H/8A4K068t58Uba3DbvLjJx6Vz1f1IXxXPi1o2fOMgCoXhO0BeMn 8/augHrqXdIiLSquCQG/KvXvCtpttIl4BAAGa+Y4mlakj63hKKddljWLU5mODkKcV8ifFP LeOLhhkMGP418ZwprmVz7zi92y06fwgdmlRqQMHrlua1pF83Ug +37ozj1r9Y8z8Whvcq3d4FdhwG3duhpn2kSEjAJHfFPUlsiP7i 3dlI3Me/ap7O6ZAFkIJ9+tJbgkSRTku4A255OfSsq+TaFx94n5uafUSW6Q 7TJzG5yAB6VqW9yl3Aw+9njmnLQojmf98ihQNvpVuwbz1mUben HvUNaleQCxjt7Z3IBY8jI6e1U9MsF+0GV0wGb8qmEbO4aI247f fKrsTgDillu0ZuRwvHtSd2wW5Q1u73WRBPIHArItZ9ksa4DD60 knYGncs2F6r6jlRjB4ya9w+FWoiSBMjhQBxXi5xH92fQZA2qrO/wDE3+meHJUUgnZxivi742aadP8AEkz7Ryxxnmvmcony4lI+tzi PNhWO8E3hNkDknI/MV0sF15wILAKeSK/RE9D81v0KNzdOl4ATgZ45pJZjuDYO3nmmiJLQgW5Mb5wPb2qaG 8SYbSQoHqat7EJDnVZGUjB9M0X9uwVOzZ4ArLmshp6Ej/uLRdy54q14Q1y40K7F1EcOG6juabQNH2r+xX+3fB4U1S0s9WYI pYAsx96/THwJ+1d4a8WaRbiz1G3fK54cVHNbQJx1ujzT9sT9orQvBXw61C 5nngkJjIVe5OOlfjd461keI/F19qzoI3nkZkUdhWe8jSmlZsxLvE0J3Ad+c1VtCskhOQB3Nat2 0IndbDZGUtk9B2zU5kV1+boM7fWkriuGn3yNIyKctnjirwXDhs 5AwQRVS10C19DR0TxhNpswVXYADsa2NR+KWr3aIFuZUjxyN+DX HWwkJPU1jVscn4s8U3OowOslw0hI55rzu+0wzTOyk4ArajRjBW RTqNkVvZvFIFx24xWjpFm8cwY4GBjNaJamaloXZpHwS5UH0qG2 ZZ5QQcnd35zWl7CWw43jAMuCOeQKbPtnhXOQRk0nIHIqyQu0W0 HoOD3Bp62jRWyZY4649KGh2JDButiykFsgDHrSyQM02B8zdc+l DZOiY77OVhyScnp2OarC82RAdR60kirEsTB49p5GamhnCyYU9O vPSh7iv0Fk2yg4I3HjNVryQrbBgMgdcUNhJ6EcV6IoGIyD9afN fAryQ/uabbsF+hPoK/adVh45JHGc19P/AAv0ndpMHAycE8V5Oav3LHt5MvfOt+LFkdO+HlwxGPkPX6V+fP xA1XzfEU4K5+cmvGytfvrH0OcyawTaH2IAslkyoKj9Kv2s0cKr 2JHIr7Fux8IpW3Na38S3sWntFHdTCNgeA54FYS6YTcl3lJz3J5 oS1G3fY3o8W9ooAyueM1s6J8SL/wAMRo0MhMQHK54pNIEtLGD8T/E958Q9QhlmHyIuFB/nVPQ7L7HGepcUJW2Je2hrtcLFGMZyegqK6mSb7owCOtKV7luxl Xdvg+XkZ+vNRSqDIFyWPNUTciuocxbvlOPQ1lXFziQHbtIPenI u9me9fAvXfM0aNWc8V6f4ym/tHwo6qQzBeMCvybMsL/tza2uft2VYhVMKu1j5i8exSWV6xZQDux0rnzqaxlQwyR3r9Rwe tJH49miSxUvUl+WUE8A9zT7QGNNythckYJ611rY87l1ufUn/AAT5vRF4yVSAct6V+yH7M7qbCArwNorJmE4tM95gkzGDUgPFJG 0dhc8dqaxwPWm0NoaHwRTyRtovoK+g3dikc56daSBbkLdajOSK oTI2GfSmlMn0pLUVxc4HakkcY6800Uj0KimWFFABRQAUUAFFAB RQAUUAFFAHE/FS4CWDc44r8V/+Cl+t/wBs/Hi8GQRCmK5qnxL1IjrI+bDILaEMcc9qrSKryBsgZ966b2CW1jW 8PGNrxE4K9q9j8NWgS0iJbgivk+KX+7R9hwlFqbaDWY0+z3kgw QEPfpxXxt4/nS48dzgcHcenbBr5HgyP+3yZ9vxk0stt6HVeHbby4YcHK4zitX 7cFLsxJ4IGK/WT8YSdzCkTzrpircHoKZ5zxK2Ms2etBNrAbuTYoGCc9q1bF42c A8DbTuF9SW9KoxI+Xp3rGvZ99yPTp1pAnZFsGEyjAz681ZjbyF OFGOlJvuJXBWMk6YwKv2jhQy9GIqZbDs9yRVN1HtIPPXjvVN5h Z3BRT9RilHQaRoWmpAoS3IA5qrJcCSIYIyW6g1MlqNoq3kKBM+ YTwaoBVt5DsI6c+1UpXBO7Klg7x3jOCc54Fey/BzVi4ReGGfWvMzaF6dz3ckny1T2EwfatMYHGStfJ/wC0zoDWWrs2zK55NfFZc1HFJn3eNipYeS6WOL8BXxZACcYGPwr roZCYxjJOfx+lfpUbWPyuSs7FSVC0zMAd+cAUSsxTHJwOfaqTu QtUQEKY2POcdO9LBEWiznCkYzVXEn1LNnABMuWwMir94Fj3bTk +uM5NZTtYS2uR3RzZA9zRZrm2bcB9Ka2Kv1LMTEEPGwVx6HGK7 LwV8cPEngN/Nsb+cIv8Bc4rCor2HfSxJ46/aL8QfFaRI9VvXkhUcRliRXMXdyLqRQRx61cFbccXcpay7QHKnI Jxj0qpprhLjJxz2qlbmFe7Ldx+7ZMtlelLcxlYGZecCknd2FEo 6cxikZ2Gf61etdT3DAOFPBz2q7CWrJS6pbsVPzfzrNu9WliGFO 0DpzUpXZMYaGdJdSTudxPJz17U1j5QD5zxgcdatWLS0IpFElwO Npxjp1qSJipBBzg/gKlOwoksj+Yh4JPX61St5CrP/vYGDTsUhYZxI53HnPbvU/llBgAgEUpK4NXGwqZgTwTnHB6VcWyd4SdpKjv6UJ3C5NpmivLC W2tgEZ4qRrb7OHdl4PA9qbJe9ylPEJo88j1FUbmMeVt/hI4otYIkVuxCMEBxnv3pLWbzQWZsNk0rkybFtJSsjgsQMdKbf3 PnW+0AdO9DNEVUUmHG7oOCB1prja2ctnIzWhMV3N/wBAbzXYE6nIr67+GenbLG2U8nArw81l7p9JkcfeZa/aW1BdN+HE6ggHZivzm8TzGfxFIMHlzzXnZNZ4hnsZ67YO3maUI KQYG1Ttq3b5ePqSMdOlfWs+FRagujvVQSR15qWF1llRgR9cVI7 di+3EXXt8wqDUpPLshgjr0NC1BlNbtzHz09c1YhlKvwODTQkwv boqQBzx2PFRRzMAFAIz1HpSbBMYhMkgbJ6cj0onQLMOGDY/yaEHUSdNwAJGD2BrFv12hj0XPY1Vyl3O6+DfiZ7VDHk8da9v0z xKt5oro3PHTNfBZpSUcRfzP1nIqvNgkjwX4sTA6wxxx2GK4dwW bGCPcHtX2WWS5qKPzrPoezxTSLsL7Y+oGR+dW7RSwHBUV3W6nk N2PoX9hjWxpfjuEOQAWHPrX7N/ss6h5+k2xLfwismZVHrY+jLUEwg1JuI9qSLjsKXxTd/wA3PNAxpbv704HqKGDBjg1GzEHrmkIaeSaQjINVcdyNmHIpjsu OcUkIrTXflMOeKrT3xxgc1SRZ6nRTGFFABRQAUUAFFABRQAUUA FB6UAeb/GO6EOnzNngIT+lfhz+3Lro1L4662Qd2JNp9RXNUb5l6kwlqzxG/YPbYB+aqxnbzVB5IHBPWujqQ99S/4cuWbVIwCCM9a9j0bUyIU+Y4H5Gvj+KvhVj7vhBasm1W7B8Nah LuOdh5Ar4t8SXD3XjO6O4jMx5Br5zgiP8Atc2fUcbu2XpeaPQP DkxNqm7IwPWrk7Kd5cAge/av1Ns/Hk9NDLJbcWQ59BVZZyJCsg4Y8/Wo1epLV9SZ5FtVAG3GMj3NWrS8X7SHwTgYwa1SuEnoXpY1eAs2 eeuKyNStPLmST5gR3NILhDuM+cg5xwa0TygUHnGSKlq42rk0BC zY64/KnfaXidsZyfWnpsXtoTLdq3IyCOnpVVmYXDvkBTzyalrUNA3FS OvI45p2zzyuDxnPFZvdka3K96jwFhuABHPvVJRvmRd2SR69qcL BEr3jrBKo3YGc49DXf/CDXza3kZOMA9RXLmKvRZ6eVz5a6ufRXh3WY9QsVwBnFeLftQ+G WubB5FQgdelfntJNYhPzP0ep72GaPnfw6Ta3rKOvTHvXU22oun LDGa/TKGtNH5ZVVptFi0usuGYAD171YR1ZTvC/StJaIyl2Kk/+vKjoKksnSWMg8D0Apol6E8FuVueAcZyBnpUlzHuXbu+XuDUS2 uUlcLjbHaL94/JjrT9OKzQYLfL0qL6BtoHmNDIQAAD+lWUuybNwTyKOXQcbGc90 kTrngkdfSrUV4I2DFj6Zok7Ml6MWZ/tTkqcKSN2OlQPKouyBnI7U73Dm1H3Fw6qinjHqKS4vmETMOTiq SVxkMMolhBJwehFKh2Etz/wE0JgtxXunMjqXxzVS+uVMQCklj37ULYaKhBbaelJJKxA3dAMD mnbQErIqXRb7QMck9afBcMtxzjGOMVOtgTNBrjanIzkdKrwbZW bkbsflTu7DG2ke+dgpY47tV5QXfkdOKTWoktSqs/2a+X07iuh0TUopY0RwBk8ZqEmjGo2jrdP0Nbi0byMEj3qG/wDh3MULHBXGTXTy3Vx+02OO1jSZLENHglR1z1rEluCqENkqe+O hrHqa+ZVhnCscA4HSmRz+be/j68U1qSldCyM32sgEnPTFMu5PskbFsHIx175pvYqwy2nMiDhue gxTJpQrMjE5A5IPejqG7sdz8EtLF1rEL7crnOa+vPh7agKhIIA FeBm1RX0Pq8khZXPPf21PE4svCRtwwTcOTnmvg27mL625BXJbJ yea4snV67kdXEMv9nijoBeA24BKjjpTbeYuBsAC9BnmvrmfFvY 0YZF8on7x/SiLcj5yAOv0otoF7F+K785ArNkAd6lu4Q2n8HPfpQlYVimYcA4 yPm/SpbOUsjNjgDHNAo3KmoSKW7Mfp0NRSXPKhGxgc+v0o3LSFUMMs DwPSkN4zzKMZPYg8UWsIfMwYqQMED0qpqsXmwMVwwANUlcF2ND 4Ysy6n5Y6k+leyaCXlV4+AdvFfCcQRtXTP1HhaSeEPMvizbvBq B3AsAeK4qM5IyMj+dfR5FK+Guz47iiHJjGS25ZlwVGM9v6Vets DIb7pr2b6Hzz7ntv7INuJ/iHa4IJDCv2U/ZPkki022UE9BWTRz1NJo+qdO4tEz1xUx7dKDVbDCM0wkfSn1K6 iqcrinZxSsKwhbmomYZpCGlwPrSM5C5AB/GmBC7PjoB+NQyIx5ZgKrRgtSGaaJI89T71i6xfuy4hXzG/2elBfU9popjCigAooAKKACigAooAKKACmzNtjJoA8b/aD1c2fh2/kzgLCx5+lfhT+0Vq41z4s63Ox5N4388VyyV6kfmZQ1bPPLlsvw SB16VnzXHzsoNde4S1Rb8MuRfq4YAe9eiWOvC2jwzYGPyr5Dih pwsfZ8J3UyxrPiyNPAt4c4Yo3evk/7W114mlY9TIecc14fBNK1eb8j6jjipfBwXmd/oalbYA5OB0J61aZ8xPuzyfyFfpMj8lXcz1meFDgjrRbsrXWJBx nPSpWoRlqLqqeSpKkH+lM027/AHvZseverTsyHHU11vlaI4xgjiqbxmZtzEn3PajoW7bjISJrzY DxnPStGVzsJzkZxx61MthN6Kw6D5UY4Xpx71IHDlQp3DHr7Uno hyfKiQgH+EkDkMO1UpbnzJ3YcDJ6ikkOKJIrhbiEDbkjv0qzbK IAT2HbHWpekim9SrqtxlQTgAnFZiP9nuchjj3pQiJLqQyxedMc nc2fw/Gtnwnfto9+mcsN3rWeIXPBo3wk17VNn0V8NvEUVxYxgd/Wl+L2kLrWgyYTIKn3r87rJxxJ+n0XenofIviHS/7F8SOm0gZPGKu2s32hec8fe7Y96/QsBNyopn5vmFPkxEkXYpRnBbpxwasFtkg54A9a6mtTiaKl3IUl znZk8gCrWjxqzjJ+QVTIaVzUt0V5MhixHB4pNRTEPByVH9axlt YopXkQmgDrgY45osVMSDJzx1xVJWQJWLEshkkHAzjBFWbiAG24 OKmQJX2Ma5tCk3ABGevrSgOkQALZB7DpVPXQNyWC5IOGYZ64p8 XN+SWHsDWS91q4OPUmvJgIyOMk9fSgW7+VlMHjucVrzaDuV7eP y1+YdTg5FSJC9udvYUrkp30RDMvL8MTjjIrPkQqSOAd3pT6C2Q KC3rjpxSykhSCMcc1W40VI2JYZByameDzJF28kHqe9KRVixO5W PAx0qK0hyr7iAec4FJOxKIvNEd1xyPbitO0uAwBUjH61D1Y+Zb IypyTqeSCfoKu/aMDIwp7Vb2uKSV7s6Hwp4qmsEJLHA5zmussviDJqFuYTjD8E+t aRlbYhwtqyDULa2ns5CUBkft1rk9e8NpCCyHd6+3FJmid0rnJy 2jabflCMfrUlvp7PfbhkE+vOKHoFyWSyaO8AOMjpVPWrVyvzDj rUqSsNMitYyyL8oGOMUiWZluSuM5IwMUS2Cx7d8BPCxzG+0Adg BX0r4cgOnacrkjOK+TzOd6jPtcoi1SR8q/tv/EFbjUXgVhheBXzBaSi5uw4LEn05rfh+m2pSZy8S1HaMDbEAdCS pI4/CrNrB5cSqCc988/pX1J8irtItwKpOG3HB+XIqy3zxAEZXOOaUrmhPJELdcrjOMGmi VhCFXgDoT2pJtiuTrAxUnAA96hv08qBgpIFMZjS3x80b+3X2pE nW65AA7CqiCZfscMxV2OB/WrYtVSRinPHTFS2KKZBIhLkLjPriql9mKLsPrQmxq4vga5WPXV 56kdOle3+FpgWUlgDgdBXxHFDtJM/TuD5J0Gcp8ZNP3t5hBGT6V5eAsechjk/lXrcMS/2VXPm+MIf7Umuw2Zsk+WuB3z2qexl8uX5iC386+laPlLaHsn7K d89n8QrTBBywxX7PfsjaiJNKtCeTgVlJamNWL5kz6x01/NtEPtUzDBpFLYQr7cU0oO9FyrgflHekIxTGNpjL9KGwbWxFMpV flGapXGq+Q+PLYmkSV5dXkJ+WNiD7UwC5u3wfkHvQBYi0VT80m 5zRLaJEMKgFUmOLPTqKZYUUAFFABRQAUUAFFABRQAVBfzCGAk0 nsJ7Hz1+1lrgsfAmryA4xC3fHavwn+Jupm+8W6jMeRJcuePqaw j/FT9f0M4rVs5iQnLEEEHpVa5gYKZCr5I+ldNh9CxpMxS8GcD1wa 6OfUHNuWyT64r5DiZXSPtOGNzB8V689p4UnAJ5BHJ614toTG41 pm3Bvmya4+D6aTlI9fjidqUInpGknFuqEDHp2q2QBGwbn6nmvt 5M/NW7mTcDfIAoB/CnWAInA5x04px1VwTRPqFmZdpJPtmq4QRNjG0dDVJicgFzhWHb PX1+tOjmwBtba2OM0MnW5Jp7lZA3AOOwrTjfz2UYGwdc1ncWoy 7jwWRCAB0xTNPlMDkszE98VSd0UnzLU1Hu447c43fN17VTvYQE ODnPHFJop7lTToyHIJJPvV6OULlPUdcZxUT3C1yjqZYOqfd/PiqN2xRwAeoq0xpuxTvoZYmVkcjGKsaddyJdISPlHv0ocU42Ki 7M9t+Emtq0SIWwRjt1r1LUIBf6OUHzErkZr4DMo8lY/TcnnzULs+XPjh4cOla3JOqkHd+dcjpV7vQqcEnjAHFfU5PK9E+ Mz6lyYi6NGyPmEdtvUd/atC8tS20jOAecCvWb0PDlsZ+oFjKAASFPPNXNOHyjB49Sad9BJ Gpp4IkJJyc56HNGpSAQnDAu36Vm2lqFla4xEzEM/dPOKb5ZK7SPbLdDTuEbshkJt5yxzx0x3q2l1m1TBOSSOlJo0tZ EbSK+RkA8Z4ogVZAwAJOOKmadroykraoqC0MczbjxVQO0eoFcZ GR8uelU2i5OyHSu8bsM554GOlXLbU9sUasCSOadlYmDVtS3Zsh jO4Kc+pzSzSCWb+Hp3qE0rsrRIrZU8ngZweapX0nmyhQMAdMVU bJBpYZHFnjcfTkVNPZAxBlx/9emyVFmf9gMc2Cp3GrdtbfvlUkc+n0prYqNi5d6arIDwQBxkGq S2xtg3B2etC1E0RG2ErM5B/KpLSTL7MYA7+lRLcNBjhftQJIx6VUvpiM4yDnn3prYpJFnT5GF ltDZ/nW94UvmW6CMqHphj6VotyXqeg6VoqXjp1OOlVPGPhl7eQMUwgA 7Vdvduc8JXkea+JLR11XDR8HoSOafb2CxTKR94nkGsn5nSyU2h kvMuDwemKp+JLUrKzBSvHp1pPQTepnWtsHRQCD15rZ8M6E+p6m qhT1pVJW1NaWsrH098G/BBsbOINGOgPSvQfFt8uiaBKxJGxDzXxWOleTPvMupWgj87/wBprxk2veLJwrkpvrhNDtixLAn5s9a+iySny4dPueDxFO+It2O hgby48k4H+11rS0+FHizjJI9K9lbnzyJ7qNYwORnrgDrUke54V Bzz26UCtpckij8wbTjIPP1p92oVAigEnoCPSlfUaRJaXKmMEjp 6im3R+1scnv6UkhJmLqloIkUIxIqGLAjVQArYx0zRElOzsi/aIYozlwSTzVponDHOAegzQ0bc13cbOojd93U/N9KyNQYzMctxnjjpVEt9CLwvD5euoQQBnqe9e8eE4iscB7Y64N fHcUR5kkfo3BXwtEHxj04/2Yz7cZX0rw2S5/eFXUDDY4PeteEZ81Bo83jSCVaLJmfAIGOD1zSwxkSZJAPp619e vM+KSPWf2YLz7N4+tD0zIB26V+zH7IdysumWrAjoDxWcncwry1 R9e6I+bVMelXiTjtUplQeg00hGR0NDRTQjHk4FMPOKBCEnHpTW bHSiw7DGemsoYfdGfpSEMKD+6PypQgByBzQICOM1XuF4wM4qki ono9FUWFFABRQAUUAFFABRQAUUAFUdbJFsenSlImex8mft06/9g+FmtMTjELc/hX4leKpt99M2QC0hPNc0F+++RlF6tnOymRJTgtjPepJbksqKWy w544rsfkN7lvRLffcE8e3Harl8zLFIFOB/Wvjs+qpux9xwsndHG/EO/EegMpIAxxzXnXhYltQ3hh9DT4Ujam2dPGtRynGJ6Lp5c26sCPz q6H3K2DubGOD1+tfXtXPgraGe4KMWbpns1Jp0hlu8sQADxnnNQ tCIvUtT6kftG18FT0waYhWZX+U5PAyeKY3EzrstAGYbRj06GmW V6TtByCaQtS3aXwmuBtBAHHBrYjPzqgJweTiiWxXQuiINlivbq eM1mSyCN2YqSB0JNC3Ehy3OQvJ6Yz1p9rdlkIIzg9aprQfXUd5 vlR5yFz0wKelv++3A4yOAKykrO4m2tihrDtvJDE+vNUI3eQgMO g6mlFDTuSyPvwWXIx60EiOIHC7s5rTqVbU6v4deJja3saMxA4I z3r6E8GX/APaVhjd1HTNfFZ5Dlnc+5yGvenynA/HnwV/aNmzogJxxjrXzy8DaZfPGwGB1z611ZBXbvE4+IaX2jWtyFVCST gc89aufakEWSuRX1Nj5Nq2hR+0i6JGM9afZbkBHBUdSDTb0I1t Y0LK7WIhSMj2NR6lMFmzuA/HpWdhwS6ktjMXA5yDzyantyZJATgd+vSnfuClqJc2xmkUljjrm mywE24C5UYzzxmo5hxZRecQSBSxJz1q5p1yoDFgOcf5/OtOUGkPkTzJc8Y71mX/+i356EHpxU82tgfYheb59oOVJ6+lXtMAuUByoUDtVELRsnGY24 4A7k80ySYRs7E7vx9ajl1sVa6sQJfCSPJXOeMVD5we49versTb UbdTrFwnB7k81LDefIAACfc8UlrqNNvUiS6ZrjOflPpU8cb+cC eB60no7hdXuak6L5SAkE8YqL7JmFmwuPeojPS6G27XMW8kBugg znHT86n0t1w7FfujjHJNaJdWKxA0Ya43HjngdqZf7fMQDbyehq XtqKSZJDL5FuRyQK6HwrCss0Z4BHrW0XcraJ6FpCz6YUfbu5HG Otdl4gnh1DQ4hNGFOBnNbX92xg9WeceP9HtbgRmFVJ3c+9crH4 baW7Vgh9OnSuac1c3hqi+mgNDdjeAjH+VUvGNkpjCDhV5rJv3t ClCzMO10w7xtUFj0xXrHwG+Gsuq6uk7wnaPzpYqpandnThYOVT Q+qPC3hIaXYqxTGB6V5R+1j41Xwl4PnVmAkcY618PiJ6n6Hg1y wR+dnizVH1zxBJKSXDPwPTmtrRdOAiTjtzmvtsFG1FWPhc5q+0 xEmjT+xgqMZwMVctIzDH2A9q7GeYhLkMFLAHPep4pwtuCcFQen rQ9hrsWrKUTKCvUHn+dQzfvJSOCxPXNTG63C7LKx7Yix4AHAJ5 qsjl1JUndn1p7aE3sjM1TliAylh15qkrNC4zx1A+tMpb3L1nd+ eEVhyPWtC4uxCFGMgjmh6hFpoJ5FmjVnBz9OtZd5IshXZ8q98d aEStWQaRKo1lPmJw3OT1r6K8EQJeafAQMNtA69K+N4sT9kmfoX BM9ZGh8U9H8zwsz/KQUxXzXqduq38i4G3OeVrPg6d4SRfHFPSDIuE2hSF5/OrMNuVUc9scivuD87Os+E+sHw74rs595T94OTX7GfsKeOItZ0C xcSDLID1z2qZGVbofcvha5FzYxlegFa5OalIcNUBXPtTT8rUhj SwApucCmth9Bpb1ppOKBDCcYppOKAEDZFKQcDihB1FLmq9ycJz TQ09T0WiqLCigAooAKKACigAooAKKACsjxNP5Vs/0qZEy2Phz/gpZ4vj0L4LaszMAzoQPevxz1e+SWdmG5vm+9iueC/e38jNNJGdPIJCuPmNU7qcxS5U4PXk11JhfWxreF7nzwecsOPpW hdIZlkJ6D9K+H4jum7H6DwtSTimcD8W43/sgHcF+lcP4JB+2Fjjg8+9d/C38DQz41kvaRSO/tWcWxCDn+VWYbgNBxx/OvqL6HwzehWuZg9scMcZ7etVrQ+UzN7560kyNbDzPuc59sHrU6 XJCcHJGST6/jTe43uRzMHGOATnntVFogIyUJJNJt3FrcsWQMEu4naTjpzW7ZY kmT8+tDKS6GhdZaLIXb71n3VuWCYBHripb1sKT6BMm1jgknGDz Ve3mwzlvm57HrVk36D5btUxjrnv2qVr8kHbhcioeiL2Rmz3kk6 EDnsaImZSOvpVWGEi7dnTJoPzJtOMY6YprUnmsJDdDTr5GViSD 6V7Z8HvG5mREZunUV83ntHmjc+o4fq2q2PRPFmnf21pJyN52nt XzZ8SPB50zU5JAPl3Z5H414+T1vZ1T3M5w/PRuY9vGI1B2r6ZqWR8QnPavuE7o+AcSnHEDIcbh7jvU8SlIGxy B1560N6C6iaRMouTnnniptZPzA55OD70paBYkt7pYYiGwDjnin JcruB7cZzTmruxO5JFclm68ZzV2VUewBH3tvesn7qG46GJcKnn klgcZ4FLbXgEpUAMB+lau7Qlqi/DJ5IJzVW8iEs4c5I7e1JKzEkynNGkjkh+2RmrGl/ukCAj1yO9Jy7j6ougsYwTjOOc81Uu+rHI+h7U7XAjc7AMsC3UV XupNhHzYY9e9NMaWhGzLK5y2P8APSpQyomUGe1RzW0BOzHWFwo mG5Tn61akmHnpjOMjIFDsDSZoXc2IgQOvSqtxeEQY5GeuKmK6D asyhK8b4YjDk9adprKQ6gjHQnNauWgmtSO6RTOMcAfmagvItki MxzntjHNSndFS7sldw3A6YrW0G/OmX8Jc5X8qqL1Jep9CeBfDcet6PDKpDk4yK3PGPgK4vdGLRxnC r2Fdyp3icSlapqeUaz4budMlLSo3B4U1f8D6THqOqRpKnJPQ+t eXiW46ndBXZ1nij4dRtOGEROR2Fcl4u+Ght7NcxsXI6CuCjVle 5s4MPA/wZfVr6MBCUzX1F8GvgsNDsh+6O4jrilmVa0D1cnpqU7s7nXNLX TbBgVACLluK/O/9vH4oNq3iSezjk/cxkjg18rFOdVI+yqfu6bkux8t6UHmvgxAfnJwa7TTIvItQCG3e 9ff0o8sUkfmtablNyLgcy7Sv4+9X4iBEE4LDritXqZ7izwKICe pz+NQJbk27bvu9qL6DehY0pW8rgbgOM5pIIt10WxnnnHP1pcyE mizNuMewgfTPJqGZVt7fccjHXNJq5KMi6jyS49MgY6VVEhAHXJ PenfQE2T25C3Dc4NXbgg7V4IA6dc07FJaElzExgCgnHXHSs2cC NsgZ7YHNAlcpWcxt9SVs4O7Iz3r6O+FN8JNIhIOSo4NfJ8VK9F H3fBbtVZ2njGBb3wpJuHBGMCvl3xTD5OsSKBgEkLXlcGTtUlE9 fjeH+zxb7mdMhhzycZxxU0aBY15OcZzX6Eflz3NHTHaO+gCsM5 596/UH/gnP4jmi0KyDZ24GMVMjOs/dP0z+Ft+bzSIz/s9a64ikmKD0EIyaaRQWRsME80wtg9OaQg3ZB45pr89KYyN1qMv jrSEKp47U4cDvTQACAp61BcAlQe9UNWPRqKZYUUAFFABRQAUUA FFABRQAVz/jSUR2MvPaplsTPY/Nb/gr14nay+GTwq3+scDGfevytu77DMRjms6Vm2ZpXRTW8VJRkjPU mlmufMQnaoJHcVrJCvqa3g+FpXY9FAroWs2MBBBIJ9K+H4jacm j9M4RglBNnCfGq3EejIAw3n0rz/wAG2RExbbk7snmvQ4WX+zs8/jV3rRSOvgV4FHPH0qWGfbzg4HHPWvp7aHxEthXG5gSpPPQZp8a CP5iNqjmleyJRTlXdKx468DORUiofs5znnkAGquS3dkaWxK9yf XPSq+9o2Ze4PIzzQ0W0WY38+VMkZ46VswSJBcL8vOOpoaKauaM V8PLCnHXA55pzW4mDMgwR+tBFupQvIWweMH3rPuD5ZYDjHPAoL TQsaCZgdxwOee9PluwsLj7wPpUvUjcpxSiJgc98ir1k6TyZGCC OPaq6DauhbqHbN8o47Z71BdSeVtIPAODSjsJq2hnakX8ksOvf2 ro/hT4rNjdruO31GetcGYU1Ogz08qq8lZM+lfBeuprOlqu4EBa5D4 v+C/tcUkyplh0xXw9J8tQ/Q60VOieJXtg+nzspU7c45qOaMeV3Ge+cV99h3z00z81xdPkm49 inbjbMCSfoO9WUiI7Zz6fWtUtTla1G6XgXTq3B6D3o1yMxgYbJ 3elJ6uxd7IhLsIgVI9MYoN4ERTu4z3q7kqVyRr4GM54ye1XDIz 2qsGPT86zqK5WysZ99LtGPX0qrpkxikDZ4Gc1onoZydjWtn89T jJHpTHiaWQsCFRR+lBRTmTjdzx61FDqDRXG0An/PeiyGXjqDBySPfg1W1HUTIRjO2pktbisRRS/u13k8npnpTLjbK+S+Pxp7DWkSvdXghHyYz2x3q7p0wltufujv6 1EkSu5JZzia6Y5GAcdKv7g2CeVJyCKGtSx+o3qxuBsJGMZNROv n2xbaMfWkvd1YS0djMubsTggcYPFP099qbs7iBnHrVomXcgmu2 W5cZO3PXFJeym5b7+WNKQ011HOXgjBPJ64q3psjB42K4BPc9at MJaHt/wAIviI+m28UOSFHrX0b4a8cabP4cY3Bizt712Up6O5w1o6po4j xBY2HiHzXXywAflFcbpWnHS9fZxCxUPxxXlZhOyPQwyu9T0LRr kajfKZk+X0rqb3wTb+IIUMduDxxha8ShzHdVhodj8H/AIDeVexu0XA/2a9iGgQ6M3lRxLuC9MUswldHtZTTs0jyX9qnxdH8P/h3eyl9tzIhwa/I740+JW8U+KLhmbcWc9TXBl1LnxCXY9zM5qGDk+pi6ZpQt4Eyo zgE4rpootiAYGOvTrn1r7aGx+bylcaJCJgVAIB5PtV+22wplzj v0ptFeQ6RU8jOcg96jh3XEGFccn0rNNvcls0NNjxasrbgSMECp 7OBIj83zHoBQkOJFIuSSCRz3qlqUnJXqCeatbie5UEfmqQDx6Y qqUxKo9+ARTUiojLds3I3KVI5qzK+1xkAHI/Ch6jeupYW7yny9O9ULl9wZhgMR1HFCQJaXMOV2F8WBBA9q+gPg nqay6GihySuD9a+b4ojfCaH2HB8rYhnq163n+FZUGfucY7V8v8 AjoGLX5wVUAHP1r5vhF2xDR9RxnC+CT8zIZt6ZLDFSQbZQcEkZ wCOtfpJ+S9TR09sahG4HfFfpf8A8E7bzdoVmpxxgHFNkVVpdn6 d/B5wNEjAP8IruOMVm1oZ01oBGKY3NI0GH60wgmmgEIz15pGAyTx RYbQxlwMcGoXGBSECAg4HNPLZp7hca525qC5fAPf1qkCPSKKZo FFABRQAUUAFFABRQAUUABOBXJePpymnSVE9iJ7H5U/8FlPEO7SLOyz8zyetfm/PHsdstxtx0qKEt7kRloZ06+YwCkjB78Uk0rIyABuRkmt2hRjY7 P4dwi4iY449a6xrILaZwNx4B9a/OOJazjVaP1HhaLdBI8x+PFobbTIiwwRXDeDVMsv3QB1xXu8KSv hmeNxi/wDaEdfBGBtJBJPUGmXlvlSRjI64HIr6m58bLYhaYpGjscH+VSp cLLluSccipkTbQj8nfJlRnJwCKdGio6gjIzzVpE7O5Zkt1WPby azntPMnYkHg9T271LdxyaBIiLxSBjAx9a1bW3DTZOVB71OpSZN dr5S7cY79KmsrorBglj6kU3ch6SsThkkhLOwBHpWDqbCSciPHX jnrR5BfUqrdtFICRxjrRFO8wJcYGe3rQ1qPrcXygcANgdhVqCY Qrngc+nQULUe46e4Ro8Aknk8HpUH2pZGVdwY+poeo3uPvohLpr jHzH0Fc9btJpd+pR2xnOOmKzmrwZph5ck0+x7d8D/iL5EkcEkvfkE17PqFqmv6UWADFhxX59iqfs6jbP03A1vbUEzxn 4meDmtJXYJwOVrgb6ApHtfk9cYr6fKcQpQsfH53huWpzIzfLJn IB5HHWr1nCZ8kt+HpXts8CwyFR9rO0/NzzVLXXZJAM56Yx2rJJtmck2U2vXiQqTj07UQzifDZ5zzitdbF wSJJkWdDn05FaD33k6aAWJPGcnrSV+pd+hQ+0kgOCSPp0qvbnM uPxPNOK1MorXU07eZoYQASeKR7p95yPY0NlqzWpFI+3O5geemK qpKI7kc4Oep9alaiVyeZluI/lBAz/AJxVaWJllDZ/CqS7gr3uBLEqFYEnpUZUuuGyAPajl0K6EMto3BDHPvV6zbyrQg/lSbuhJhpzENt2556gVet5X5HYdAetK+thuRHe/wCsUAMRSfaG2MpLdTQtUKxSuJN498cjHWnWdydrMqgDpRzKwiQ Wxmwx59vxouoSkqkHBPtSktB8upJOC8IOef5Ve0ycbAGUNg9aa 0diZa7nb+GLtLB1Zj8px1r1fSLqLWNF/dXBU4wozW8ZLZmFWDumUrzU7jQb2FfNLBhjFek/DmK017yTMqt3+prixiOugz1Pwn8HBqt4ZlUbWOcele4/Cr4KW8u1ZVDEH0rkpQSszplPmZ63afB6PTLIvFGqjGeBXGeMNO j8M77m4BCrk9OtYY+hzK6PXy3EcmjPzs/4KHfF+fxNqc9rFuECjChTXwtc6O11qZdly27r3Nc2T0mpubN86 xSlFQRpHQDDbLIF78k9+afchlthuYDjvX0x8s0VkuvLIJGB3OK uJMrQZJGCDVBYef8AUgDIGOhFPsg0sbooJJ9KhhZGjF5kUQDA7 vapGkIG48ntjiiWgWK884X7wwRWdOQ7k5BHfilF3JjLWw4BdvC YzwTmoY7UNLk8sPX61UBp3QsdsGu8gDOecii+sd8Ixszng9KOg 9itbqY1wCc+1NlOIyOx7mmJMw7iD96SDt559q9f+Ct8ws1BYA4 5wK8PP43wrbPp+FpuOKTPbNHu/tWiyJk8r3r5y+LMBi8RzAHYQTXyPC/+92Pu+LlfAM5XeUTBB/xq7aS5UY6ntX6XqfjxatZfLukbJJDDp3r9Gv8AgnHr6XOl2qBu QRnmh6mVZXifqf8ABidX0qPv8orv+3WoIhsG7J56Uh6UI0E25F NZQBzQAw8HHNN+tO47iMMjPeonXGaSEMxg96Xt2oC42QjNU7py inJqkOJ6Na3okHJ5qwDuGRTKTFooGFFABRQAUUAFFABRQA2Q4j NcL8SrnydPkyRUSM5n4+/8FgNea98b2NqHBHJxmvhu5TahPIwaigrXFGNkZsx2tjAJJ69jU BSRCMDI9BW6IvK9ju/h1bstkXIwPp1NdsUMlpECAeelfmXEkr1pH65wlH9xG55f+0zML aGEAAAAZrz3wM4W33liD0r6PhSP+y3Pn+NP94il2OthffGpbJ9 DUoy0LHcCcdcV9NJ2Wh8TO9iK+gWVFVTg8dhVaGIxSsoC7e+RT V+oJdyN51V8ADA5JzVq0ukkUBuefzp3Jk7F11SRQAcsRxxVNgu DlWDDqRUO4uW4eWTOo3Zx7c1bs5ttySBxjqOhoRSjYj1K7Clcb c+mahh1JZWXblQOpx0qvMl7kt3eGWPCMFHQjpWZdSMUzlskfn9 KaZSdyCa7MrjA+UdBUqyo65fjHoKdgi7jreJpBxkjJPJ61IyhI yOhx+dTfUdis1wyzNnrjnHen21wJNvYnOABTE1cfdgoCoJ59TW Vqr/Z0y2Seo9alq5S1HeEfGB0nVVYucjGK+ofg78SY9asUieRWyOea +RzzDW1PueHsRelydjpfHfhRda05nQckccV4d4w8OPYtIu09e4 xXPlVZRkkbZzg+am32OLNi8M8hC4x+VSQzGC2IweT09a+zjJSP g2mh2lJvlOOuOxrP1ncLwls7QOCeaX2iHe5lO2W2McYPpUtvGI gTk++2tG+g1YmUmOM5wDjHSpjGTbBiwYDoCahk3szOluGYMoH6 1FYOfOyeP6VpYGrs3rV9424x6Z61JKvmyDJBJHbtUu10OJTvIG jmwAGX1zzis26wt6jEgHH5f5/pSi9RNlpHO04JxgdOlOWLfKN2dg6exqxx2J0ijVTkZweOOlJdo r7WAOf50r9ykrkMw8uM55B456ipbBVa3IXksCetRFWQ5uxLaFT IRjHPQ1Y2C2OcgD9aGhO1rENxMjTpu698VWlVZGkAOCORnqayV 0S9fUhkxKpXHvk8VDEPLjY8hQMfStErouNi3pl550PJbAPWrrC Ms2fmOOKblZlKN0RXnNv9480mm3IthjuDx9aUW2zJpm9BqwNsA QTk9Sc5rc0XxPc6THlHIIGRzTb6oJPQ3ovHxvbMyT7Wf8Ahz1r S+Hnxvn8L6iizjEW7r6VjVTki6cdD7G+BHx5svFVpbQQupmfAI r7Q+EvhA/2TBdOvyEA1y03du5006TST7nYeIfGVrp8H2dRvIHzgDpXg/x68VQeILV4Y8L8pAA71FSrzaI7oU+RX6nwH+1P8MF1CWWbhsk9 e9fK+p/DWe21gKYwAG44pYdqN0jnry5tGL4p8NnTtNDN09cd65TUY18rB AP90gV6MGzzZRaRnzxqigY+gI5pkrHygGVQRxnGK6EJMkhl2w4 IIPfIrV0abbASRgjkA0S0GaFiyyPliCB/KmalcJ5hROR9P0qJAY+rXPlwli3OOO2KzxO0atzgk8U4LqJWJr a+BQORyw6elT29yMnJ+f6dabVloOyH2UmZGGM+v/66j1KYiPaowBwMetEUVuUlmEcTZyeeTUEk+ODzxTJsZ84+9njP 516H8IL1YQcHB4ry87jfDM+i4bf+1pHtfhW+L6e6kkLtwRnrXi Pxgby/E8gPGTzgdq+J4ddsdY/QeK43y5/I5F4TcICD3qa0tvJjX5jnPfvX6Zc/Hbl62IeVRgHB/Cvvb/gnKDBZwBS2Tg5zUszqW5T9XvgHcNJpURJyNor1MHIqDOnsIBkU EnaaDQTI6dKQ/MKdgG4HXrTCMUIEJg5pjDA6UXAYajk4zQBFJJhSMgVn3UuPlNU ho6Hwb4+sPF2nR3NjcxTxOMgq2a6mzvcqORTB7lxJA9OoKTCig YUUAFFABRQAUUAR3T7ITXmvxau9mnuAcDHrWcmZTep+Lv8AwVN 1lr/40iHjCRk818j3cyhCM4JyMk96mg/ddu409EZV1KYmABUD3OaY18ZLhQS4UCtntcLLc9C8DTeVpSgEA c/5/Suxt70O8SjkYzivyzP6jdWR+x8MQth4pHk37SWpRtqccR+8BXF eElPlYAIx15r6vhWPLgz4/jOVsZbyOm3mFFXaCB1Ipz3ZEG336D/Gvpz4+w+O4BugysDGB1z1qpeXyGWVTwMYzSewN2RlNIzzccBuz GrllOEcjDYx2prZGMHc0Y7oIpUnae+OlJAwdOoXPIJNDRq2KJd 0qKPuD9at2xWOOQMAvy8HFS2HMZupTGXp+GKrRk9eSRnr0FCaI sTm4eQDk7cDHzc1FeXHnJ3BHNUC0YtpH5vDKMAd6keyYr8vUHO KaKS00EZWtoQp3ZAyAKq/aFkXLZGPfJ/GpBbEU8pyFGGHf1/zxUtvC+4EkjHQHtRuEdyaW5DDDjtxVHVQk0PTBP8AdNCRZzt+r WBLjBODjPHJrs/hN8Qzo17Cu84yBxXm5nQ56TPayTEezrJH1h8PPGsPiXTY42cFi Pzqh8RPAS3kLSRru79M18LTn7OqvU+9r0/aUrHjniLwmbOYgqTzwawbyy8jcpz14Ir7jB1lUifnmY4b2U2ir bzGJCc47jHSqF9KJ1OQOeMkZxXel1PLV1uUZLdY2D8D23U6B+R ggE+9W5JgrE1yqkqqgkKcnFVjKYrU/NgAkUmrrQGupUZ1I3DjqSBTUcNMNuE47iqS7iNbTWLMABjgfWr lxPtZhwTjPFDZS7lZrsSSfMoHHFZF4yyXGIwSSc8npSSJbRct/MiGCvJHpVmPD7unv70MYkiBGHB4/wBrrRuVuNwGO4pCvYbPKlxFgMMevrUcBVLUruK4Gc+tTbULOWo 3S38y54HzfWtMo0k+c5GORQx3uMvrNUcY5461lTK0O/5iAB/ep3Q33IVumYZ3cdwf61IjBYX4GMdO9WkkJai6XJ58e0KC3U47/wCea1IYzLKOcr7Cokle5XNoS3UyyuY1UFcc81Uit1jTjb17VMJ Wu2S30NCGZvlBYsPcVoxPvtiOc9yOtUnZCWhbtGygDEcdQf51t aP4XfX7yO3gjDvIcAY6Vm5cquzSlBt2R9//ALAv7GdxYG11K/jZUGGwa++Y7ddM0mOwtFUvtAwO1eZ7Va+Z9DCg0l5HMfGO+0f4 LfDu61jVpY1mdT5as/LNXxPq/wAfLTxDcSlJVwSTwc1niZxhNQXRGLhKVJ1PM8Z+LvipNfnZc/LzgenvXkeo6KJbpdy5DHgj0rkhU5ZXRnKEWtDnPiv4ciGmI4C7 R0215JqlvHCuMhuvPSvfw8uaFzypx0aMeSxRlPzYz29KgntlkX AII9M11LyMErIntEVYlBBz/Kr9pAEibPPpzTe5VrjrYPGc45Pt+tMYf6Sc44wTzUtiaaRkalL 9oucchufpUb25CbT8qnjryaeyE1oQO+w5OMfXJqWGdd2AcH1Jq 7D9CxZNjjP/ANen3k22Ikja2fX+lK+pSKMw3ohAUjOODzVK4UoykAYP600Cs2 VbgMU3cBumc11/wuvNkvVPcZ6V5ub/AO7M9vIXy4qLPZ/CGrbIiox05Oa8n+MEyyeImJI4OT718Lw8uXG3P0XidXy6TOZt8 7wRgL6DpVh5Np24yo68V+mo/HErD7aQNN1wT0z1r7l/4J16oY1jQknnoDSkRVXus/Wj9n2736XCAc5Ar11TgCoIgLjJpu6kjQM5NITgHsKdx7ieucYp pXn0oENYcd6jbgUIRG5GKZI2FzmgZUnl25HP1qhO281SRUT5E8 C+Pde+B+rCWxkeWw3Ze3Y/yr6u+CP7SOkfE6wUJOsN2oHmRMcEGuahWUtHudFen1R6xYais6 B0YMp6EGr8c4Yc9a6jnvqSUUFBRQAUUAFFABRQBX1FtsBryP41 3nkafIfRaymZT3PxD/4KJeJxqnx3vSDnYNvH1NfOVwfNJbllHXNLDL3PvBO0VcoX0GST wVJwRnvUDIJApB5yP8/59K2logjrI7jwrPtsUA4BGT6V1Gmaj5V4mT0XivyviGNpyP2nh u8cMjxL9oLVGv8AxOduTzgEnpWf4SdkgUnjpzX2HDEbYCL6nwP F1VTx8rHTm7BXBAHGD3qtPJvUEEYbk+9fRLc+Zb0Ej1Hy5ApOf Q9e1QNMsrOd+TSV7mZHbLhznB5/KrduoV+dpwOKtkxVhHYsGKnII7dqseb9mtQSc89DS3LJLZ2luB 0H1qzMfLTJztHOamIRuZk0yyOSxBGf4qY9wFypwf59adtQvqOh 2ygrk49TUptY1IBcENVXsJoswQCNACOnvVq3hMjpxzSb0HeyG3 1mGiBwF9eawr8eUzZwSO/SkncIyViir/vAOeD37Vft7lyQD+XpQ0FixIw2kEBecZ9apX+ChKjijqUzG1HE 8ZAHJHXFYcV1JYXQkGUXr9aVSPNFo0oScaikj2D4K/Fs2F3EjyjGQOtfUng3xTa+LtLA3KzEetfnmZUPZzZ+o5dXVWkj nvH3gH78iRllPORXles+FtjurLtI9RXbleNt7rPCzvCcyuc1Jp Rt2KnPXHSudv4HR3PyqRx1NfYUZ3PjakWirL97b1P1qSOIJGCS ORwBz/niq5fdMIjJpilufc9c81HMPMiOB0HSriiumpUWHPUAL3OeKS1b YTu6Z5zjim2Tc19PnUz5cY+lWC/mzDDMVzWbTNIbFO8VYVxjLZJqiqiSfJyMU4vS5LWppRESHIJ6k nAq5bWpUZI78+1J+QtRt2WjOT8wHI4rP1BS4HUZxyKaWhUuw6K ECEqOB65xVaHzBvU4+XvUNsmMnawzTVCXIG7DE9hzW3GSJl43Y HTNU5aXKS1ILu6LOM8c1TM/nMwOADxjNLREzZE9uEUhSSR2pLS1cSMOFGMAYzVS0sxpaGho2k FmbIwf5VrRaObWNSwOCOR6VM2mio2SKdyiRjd8xOTiqsxcFDg4 9KlbikkXDBv2lSSCBn2q/aWrsFA7nnHNWmtwUdLm7oWhy3ZiijRy7YGBX2Z+xH+ye+o6jb6 lqMQEQIPzDpXn42tZWR6WW0nKdz9G/B0Vl4c0KG0s0QSgBUVev1NdQ09j8O/C11rur3CRQwxmR3c4ryYVU3zPZH1U6L5OVbs/IH/gpp/wUiufi98QJLCxufL0uBjHEgbjAPX614j8MPixPqkMbi4LEnnLc 4rHCRnWvVfU5839nQpxpLoej3dzJqUPm7Swxk/SsKWSaS64jYoOK0jB81zwYzXKzmPi/I9vo8aMx3uentXjOpHzGIOG65Ga+hwr0djzqz10M27kUF1zz64 6VR84xLtBB9/WuqPY5VJ3sySynYyZ5wD+Valo7Mr7cZGcknrTa0NloT28xjiJH 86pXd6W3ckn9KndsTdzK8wyLv8AvDOfmp63QnAAB9+KtIlCOoM XzEZzx3xVW4cRzKAC2Opz2qk+w0y7YThR/dBPX0p858xA3ysSenpQNalNmLr8pIx+dQXTB2G0tj9aENR0Kep yLDEUDHAGTjvWz8P7sxSBtuTnnHauDMo81FnrZK0sTFs9Z8Jag QzLyQB1rz74tEDXcsuQT0r4nJKbWNP0PiFv+z5ehj6dcYQBiPU 9qlugrkBchuwPGPxr9FW5+RXuQQEh1XsDknua+y/+CeGq+TfIhcbieRQxVPgP14/Zvuw+mwAH+EV7fG2UGKgygxSR70GkaCHFNJGOaAQhakYn0poQ1 jTGG4cHNDAhkyozUUsmF9qfMO9ildPlsCqMxI6ZNNFRPDfF/wAPN+9WiKSD1FeYax4Wv/B2sJfaW7wXCHPHQ15NS8J8yOyDTPeP2fv2wbfUnh0fXVFleLhV Y/cf8a+j9J1yLUIFlidXQjIIOc16cZc0bnNVhZmnBfAjBqdJg9Wm QmPoplBRQAUUXE2FFAylqrlYzg14d+0FqP2bSLs5xtiJ/SspGMmfhP8Ath6z/bHxp1p8/wDLYj8q8jWTyQ2RuJ5Aow38MLX+4hkPnhsjtyMVWht2W5UY+Xp jHFXN6F09JHX6TJ5AVAAOwNaNteMtxK24bcda/Ls5d6jbP2jIH+4R4X8SdTN54vlGcEH8K1PCp2WYPP0r7vI4cuD ij8z4jlzY+bN8sSpIyMDmq1yxkQDlc55r1b3PGlJcpHDGWmz95 fftSJEVRskAk9jWlrMmwkDfvcc8dMdRU8e7fu9W6UW0FcsynMH LFTyTj0qJZGuGRQBj+lQgk9B1rOI5SC24Drmrf2oPDtByO+BSi hrRGZdldxIxuz1HaokuNi574xk9RVCvZ3JLe6KvkEFSe9XFnZc ZwoHrTHbS5PHeLgdTxxipra/fzmA6Y9ODSauK6aLDv9ot85PQ4zWPqcPkrnIwfb3p2AxdzeYGB/LrWhZzkgYHXikNK7H3iOzg+n5VA5O0HaWJ444wKnm1GzNvEIh+ UdPas+Sz+1QEkfvMdcdatiTMq2updAvgQWGOSQa9p+CvxwOlXM ayzOF46mvm85wfNHnR9hkGNa/ds+qPAnjKz8aaYitKpcjGKw/iF8OWJaS3jypGelfHUanJOzPqcRSVam11PJPEnh57Z5FdcHpnF cBrWnvEzYGFDfjX2mBxDlG58HmGFcGjCu5JFmI4OO9NE+VC8Ae vrXupniPSRLKA6qx57VH5h8gHOR6k0+YcmmVGummTK/Nzz6VHbXJ84hgCe5xTsSkalvMFK9u+auJIUKAFR3wahsZHdJk5 BPIxVJrcRz5ycn0NKOlhPexPayYccg+1X4LwMg3nA6c8USGmTN KpA6cjrUJjWcHOAuOM0m7Ayo4LIdvI/nTbFvs8cnmIDxwTS5b6iRXsmMt4cFhk9OpFbTfI64zuI+tFtgv Z2Kd4xLhXGADnHSsu4mxfvtHQcAVNxtaE0IYKWDd+PWtzQdK+1 lS+Bng//Xq7XCO52ei+G0a1d0C7wO3Ws7XNIvWyUgbYPbOa5ZS9+xs1ZXZ zL28guCrryeOeMUt9YMgRVwTkfQ1tvsZS01LRtvJs8ggtj0roP CmjzarIkcabieAVFTUnyxZdFOR9Pfs3/s1NPLDe3kQCDDYYV9ufDvVbHw1o9vY2gRJNoAUdc+9fOY3EXZ9 bluE9256r4RltfD+ny6rqF0kUcal3dzgYr88/+CpH/BTu58RrdeGNBvBHp0eUYxv9/tzXnVJe6qa6s97DPlk6stkfl7rviO58Vas0ssjtuOea6XwDrt9 4YukMTyBcjcOvFfX4XCqFKyPg8xxjrV23sfSfw7+N8E+lrHMu6 QDAGOldi3j/AEiHSN58sSYyeK5alFxvZHJFty0PE/i34+HiXUX2NhF4XHSvO5rjLevr616FCPLEidrlG5/ekkYC44qosJ2ncAB0+ldEV3MEtSW0doD8q7lOM5NaNqSlsxKqP pTaLvYfESVyflNZ1zJvLYYqCcYxRETRVZt8XJGQeuO1OgTbAxJ AOOOaqTsLqNjOFOSSu3rmoZIWMpB6+vrVIbVtSazk8teCPbC1N 9sDuV4ByMe3WpYiK4ZXJ24xtqhPIN3CgnOM04s0TKWoz7UBKjD DHy9a0vBk7JImc9Oi1y46P7hnoZZF/WInqHhO9HqGPQnFcr8T9p1kZznp6Zr4vK2/rh+h5408vaZiQiNIgcH2J4pXkO4E9Pr0r76J+USWogO1gcgt24 r6u/4J93Srrsaufmz6YxSexNR+6fsB+zLc5063Gc4UV9BQv+6HNQY0 xwbHpRvoNRN+QKQ9P8800wEzSE0A7jc981HjuCeaLARspHXmq8 8nbvVWAozZDHFQlM+hNMpHSfEH4UW3iKB5IlCTY4xXg/jf4by6fcPDNDgjvjiuKtGwRm0eS+OPhgGzJEPLcHIYVtfBj9qD V/hLqMWna6ZLnTc7VlJ5Qe/qKyoz5J26HXJc8T648DfEnTfHOlQ3VjdRTI65G1s10ttec8EV6 DONqxfgud2ATU2ePWncExetFMpMKZJkHgVMiWCS7mxtI96cTSu FzM1mTahzXzl+1Tqktr4X1F4yvEZySegrOZlI/Cr9oPUxf/EnV5Aetw3I+teeSyZfvkdqvDK1JGklbYjjuBbq27GCcEipLN/PcbQM9SMVVSVo3Kw6cppHSWu5RjqQOSahlvzb2dzIewPNfl2Z+ 9U+Z+1ZNBKhZnhmuXf2vxDI+7BDV1WhHy7dFyQO9foeVx5cNFe R+U5xLmxk35mqzbTwxABqK4udzgHAA/Wu+Op5m5LBIBnIGaSRtsRHPPWrtoC1IrXIk9c1cgfMwwBk0mS0 WlVJIznv1GaltrZUiDgHGOBU+Qygse12PGT1NTgAKfUdc0BqVL nBkwQQOnPeq0w8uMj+I8cik0waGQBosDOOQBmrsMu6Pb6989ao FsI6OkQ2njOPSrMV55acZz0oBJF5pzcQArwcDGKi1H5owP4evI pCeuhkTWaknr26U5E8lvXHp1pXsJablqKQyRkkZGODmq7xkpna cZzwetSnqaWKc0G6PBwCf880yLTvMPJ57j1rVE6XKep6KJX4x1 445rk9Umn8O3+5WYICKwr0lUhys6sNXdOpdHqnwS/aGm8P3kQeZioOOTX2P8K/jBp3jnTY4p2TzGXoTX55mOGdKo9D9Oy7EQrQTRP8RfhHBrFsZ7 ZA2RnA714B428BT6PM8bxsQpzkjpXRlWMs7M4c2wXPG6PPtb0B owwRML69MVz88bW5KsDgdCO9fbUqqkj4HEUHCVgSZwh+YgHGDU d3cEQbevPbuK6Yo5rWIJmWKNc9DjGetRRyCaU7AcZzn0pi3NO3 Uom3kmrqnLKHJz2xUNgBfzht6AYwSetRyhQ4DZUjgn1qU7Cemo 61VWZl688Y9KWeUqjE8qf0FDd2F7guohVwTgDpViwvlmTBO5h1 HpQ9xp9BASqsDtyD3qsCZYsFcHHpVR2BrqRQReXcgo+SOmOK14 pfMcMQOgzUvYcUrkN7CUkGR34PesW8QC++QcZ647VDdmOXw6Fu xXzkRi/TtW3Y3DWXIAPrzVt6Dgrm94W8ci1vAJnURjnB6VrT/tB6MUltUSOabpuHQV4OOqTjNcp6FKkqkXfoVNMt7fxBK0sQJJ9 Ko+JtLa0nCqpGBn6Gu7DVW0jjrQtM1fBvw8u/F00cMULsGI59K+pfgX+zNDo9tFPdRgdD8wrHHYiyaR6mX4NtqR 7xps6aJAtnaRbiB0Hauj07WrHwfYPqOoTrDsXJZjXy9WrzSPr6 FPkikfKf7aX/AAUK1B9DvtN0y7a3tOVUK2C1fm5498c3fjHWpWnlZndiWJNduU Yb2tfmfQ580xXssO4rqO0Ozw0QAJPrjHNd9pdvHBZ5Pp6V9hFa HwEndlzSdSezd3iYg84HpV//AITmSW3dJGZuxOarkTCMrGLJc+ZdEktyc4NRzKtwOGwfrRYW7s QTQkGTHHPbpis5nYswOTg846U07ilox9vKxuFGDjPJrSE+VGRg dz0qmKw5plVBtK4PIrPDlpWJA254z2qUhy3K7MQ+4/jT4n3xtgDHfJ7VVrk2HZViAPu+9OSANMR1z602NBPGsW0nDEn6 4+tVSSrfJye/GaAuJIrOuPnYkdu1U76QuSoy3pj1osW2uQz7kF4uCckdzVzwlI Vkw2SeQK5sc/3LO/KpWxEbno/hCUtcDjavXINY/wASpDHeKwU475HSvjMua+uaH6Jm6TwDfkYlsCB+8BP1qwkSuuc DHfmvu4s/KVqNdDFOHYcA/hivpb9grUBB4kjUkrlhwapvqTOPus/YH9l67V9Otsegr6Ptpd0Q78VmYUyTdkcYpQ3FNWNRA2DQDSAQE fhmjOTVAIefpTCSB3zTAilkwD0qpOQzcfjTuK5VkBJOc1DMjIc 0FRZ66VDVg+LPA9p4ntHWRFEhHDY5qJxuEkeA/Fv4XXPhSOSTYZIBkhgOleF+M9Gg1W2dDGo/nXm1VZ6m9Btnn3g345a18B/GO6xuWksGOZLdjx+FfafwF/am0T4uaTEYrlIb3H7yFzhhWuDxKnHle6NcRR+0j2Cy1MOAQc1o W+pDoa7DiLaTrIBjFO3VTAQtS5zS3AUcfSjfxmnsBka6+Im+lf J/7aetjTvh7rEhPHlN/KsaiujKbPwu8e3Tal4lvpdxO+dmyfrXNzgyAkZHTn2reg7wRs9 tSrOrIcryOtafhofvFLKu8CscS/3TN8D/ABlc6Fsxg54xzzwTWH4qma30GYlj83SvzPF0+auvU/ZMHHlpaHjCE3Gqu2SGzgccfnXV6cjLAoJVK/SsFG1CPofkeYz5sTNruaKzABTu3EmorkqXT0PVs9K6bHGh8VwZ QNxyc8kDipp5lSDqemc96u9iU9RLGQRE8ZPfHc1bijEhUdGJ59 RUsW5LIHRM56ccHNXYrgvaBRjleMVLv0HFWRRn3tKxHQenSoPP 8tfnxjsKbWo7dSpdXwZjtBLZ7U2a6WTAYAjHrwTTfcXNcIrzEo J3Ek9+tWbKcM7YAx6elFtBk00olUEAD2FSJmTnjA4GOppJhYtW rKqls9P4Qc1FLelmYEDGc1NhLuUmcyt5ZDE1NDCGJBDKf7wpCT 1Joovk25ye/wDhSqhETgD8O9S43K5uxVktn2sxX+mKhMZRyQNpxzgZxVpitpc SFNz4wMkdOoNY/ifQRdwkjDHvhafUfmee6jaTeHr/ADHnGe1eh/CT47XPha+j3zFVz0Jrxc2waqQbW59LkeNdOfIfY/wM/aatvENpHDdSISR/Ea9H8S+DNP8AHmnGWDYWZex5r4RxcJn3zUK0Tw34j/BS40Z5HSLcvbArzDVfCpjba6bW719VluOUlys+OzTAcl5GDdaG 0KtgFhmsjUrN4YiZEO7pX0kah8nOm09TInvd0RBXIFS6TdAFgR znuOldCM7m9YbZY8cDPTHGavWkRcnILA8ZrKUrGis0N+ziHOEH sKzplLXZBI69DS3M5bDZJxHMWU59cd6gn1EuCoDfiOtOwmhiuF i5O3PerGmyeUuQ2T3FHKUtCxaziSZt4H+NaAgRYQwGVC1OqCWu xQifNzuAwucYIrQife4YYB6nii1yFuLcAuMkHAwRxWVfqr3AAH sR9aUoljbbLShQThTz6Guj01POsWXJz2PTFEnoLaVznte8O3jQ ukTHkdR/hXO+APAc/wDa8jSMzkNk5rzJRTnc64VuSDSPcPAujzQKkVvE7SHAGK9Q8M/AO98Q3ccl1CyK3JyKwlUdNXOxUvaNNn0B8MvhDpvgqyiLxIXA6 YFek6Zby6qgjt12x+oFeJiq7lKyPqMBh1GFy74n13SPhToEl5f zxBwMgMeSa+G/2q/25W165ntLGVvKBKqFOBXFJcy5I7npWUYc8nofHPjzx9d+LtQLv KX+Ynk8Vk6bpRmmDNhWf15r7XLcMqVNLqfDZpjPbSdtjq9H01b dUzgZ5x68f5/Otl2OwIMf4V6CVjxkiSyk2iTGT6d6gtCyXLEjgHrTV7jsRi5db lkZsjHPPtTb2byGwuTzx7UmwuluGn3Xmo5YgnODUUQUuxwfQcG mm7g3oOt4V8/Ix1xVm6BZQcLjHHaquJMguGLBR144pluAITtI9+KEimrFO4k+Y 7VwffvRbOCxUnB71TJJYBliOWz1FWVUoSN2GOBxSYWCRVZSAvI HY1UiiYg/MRjt6UCuI7LCjBSDg9u1UruDbGNpwaEaJ9DMusxx5JzjHU1d8O 3H+lBRzjn8a5ccv3TO3LEvrEbnofhqRUmXdkMegxVL4kkCYNja QMAGvi8FC2KP0nNIN4CVjnIbgEAc59xVmG5EaKARuPBJ6V99A/JrNMcXUqMd+cV75+xVcrF4whBOMsD+tKWwpPQ/Xz9lW9JtLcE54GK+odOmBt157UjCLLHmAgelODg0FimT5fSgNk UBYRpOetNEmGouF9A3ZpGPyimgZBMTz1qAqD09afkLoDRLsPQ1 VuRtGaLFI9XNNkYKKGxtmJ4n0uDXLF4LhFZGGDkV8l/tKfB648ONPdaOpkTktGOw9q4cVC8S6UuWVz5U8Q+C73V5Xmfe8 uelO8GaHr3g++S+tnmtJ0OQ6ZGK8uinB3R6ftE42Z9U/s7/ALa6zyQaT4lZbe4J2pOfuv8A4V9R6Jr9vq1ok0EqyIwyCDmvdp 1FOPMedWp8rNm0u+nNXkmDjrWi2MR4PHNKOntQApUmlwcGkBg+ JH2wv9K+JP8Agot4hGlfCXWGJ2nym/lWNZ2iZSPxM1m8EmpTEsfmfgZx+tUXclGIKkE+tbUtIo1ndtsg ktjJERjB9T6VseF7FkcEZHGBissZK1Fs78rhevG5uXkBSzJPJH cnpXLfEaY2fh0ZOQQc81+Y1J82JSXc/X6SUcI5LseUaLAj6mrYHJ6dO9dgluBFjHy59a/UaN1TSPxrEu9WTBgxlXaTgdBUMqEyKAc45ra5g3oOAHQMQB605 p3dlzhj3I707JhJFyyzIVHTjp0/Cr1qjLKPlyMccUhpEl3gxFhwTjvT7Rs27Y3ADJHNSxXKyXQTIw Bg9PaobydZO3IGAfSiQNGZc/Pkqwb15xUGTITncBjtVRBbXBHLoQMZFXLOUq2FDA9/emNk8sp+TPrxntUiXLR4OV680SSDlsSRXjS59RnvTRP5LZJA9B 1qQaITJsn5zj6Vb3EqGBA4yMip6gO0+4CM244Pb3q4JVkJwAfr Ra7CKGzuUI2k9OeaouFMrZGD1696IoFtYgMDeeRjGD6daZeREx sxHU0+ozntX0OO9gbfkkde1cDr+iTaZKTET/h7VElzI1oVHGd0angr4tXfhq9UecUKnqTX1L8CP2uGgSGOeYFQ B1bOa+MzjAOLvFaH3eUZhzWi2fSGifEXSPiJpwRniLMO9cx43+ BkWqhp7Vc9+K8WhVdN3PdxVCMo6nlPiL4Z3WkSMGhYgHt0rivE PhlfLIKhCO+K+rwOOUrJnxuOy9JtnJ6n4PYDjJY8D3rLGkSWhO Q3HbHIr36dVWR83Og1IvWatFt4G3PQ1p2F20Aw3c5xVyMVcbd6 jibJA2nvmqd/ebwOrAjj2pWE0VJGGA2eoyRmoppBIuAwHf8ACtGguRTOflVckZ 6+tW9O+dMHgnjHrUa3NFtqSrj7YACdo6cVqkA2Y53H+71zSTuZ 3d9ClES0jEAYz3qRXKYGSvPbtSloHLqXYpTINjHIFQC3V5mIUg/w59e1Q3YGzOhZoLpiwwM8kGtfS71mlG0MxPXmqklYaizqNFtX1 YCNo29OmK6z4ffAWe+1IzbG2Hua4Z00ldGylZcp9J/Bn4T6R4fnWW8WP5Rk7h1r0K91S0u73y7GFQgOAQK+fxdZr3T6L LcO3LmZteHvD3mDzb2TbHnPLcVzPxk/av0D4R6TJDbTwy3QBwqt0rx6krM+qowTdj4Q/aT/AGx9U+Il7Kr3REPPG48V84a34ifX7xvmZjnr6mvcyvBt2mzw88 xyhH2aZJo+mtLN8wIPXjJrp4NHEUZYjDAdK+tilFHxMpX3L0UR k2kcbatktHb5wCadxJaEdtdgpIBnf+dVre4b7QQCME9T0pg9yS 0cm4bLAANn60Xy+fsIyRz3qWgnYjjHknJyCRxjvS2iq8jHdj05 q47BF6XJvsyxSAZzg8k1M1yAMDGOenQVMgTKUs3mIdoB9hTYpB twRkj060JDk7srzSZ3EKB9T0qraFdxJJBz2NUgRoWLHzWJxgDG AP61YVN6E56DnPcUXsNCXL7YAFHbk/0quzOkhAwMc9aXmJLW5HPIHiB4OT3qjeRyCQZLMCeKpCKN3GX+ 9ySOAad4fI/tFdzBR1HpWGKf7pndlzSrRPRvDoIZCF59Kb8QYw8IYZx33civh MLNrFn6hjpOWBaXY5KFFUqAuSffOKew8jJGMDGc1+gQ2PyN/FYSGdkYjJPavcP2O9UEHjWCNm29OpoaInrGx+vf7KGo5srbkEE Dp2r6w0ucmyXOelJbHNDQtLMdoy1PWcUjVocJulKsxPOc0xCGT A6/WkEgJPQCkG44NnBzQScDpTQNEUvK9uaZs2e5pjsMYk59Kp3TZy QaEOCPVpJQgqpc3WBntSbBmFretCNSAcV5Z8UvEFvb6fIZ2DM3 Cp3NYVdUOK1PF9O+Ev2+ZrowEKzFtoHSqvinwEv2RgkYHHAx0r mqUmoo2VXU8h8ceBzCHYJh1PUcVvfAj9rnWPgzqcWn6vLLeaVu 2qSctGP6iualXdKprsdHxxsfbfwz+MOlfEfR4rvTruOZXGcBga 7ez1AsOtezfscMlYvw3meCasLJketIlDhLRJJ8uetU2O5y/i+7KWcpHYV+en/BUnxH9l+E2o5PJU8etcuJ+BmTV7I/H/UZP9JYs2G5696qrICuMY55rsWkTdp8w+RSF+XBweABXUeF7TzI ASB0yT3rgzKdqLPUymN66NXWLfyrQ9fxrzv4x3jJpKRsQAelfm uHXNjVbufqNb93gJPyPPPDce+735PHTiurmTZCjEknt3Nfq8NI o/Hpu8rkbOFuQMEZHJpZrlUlKjkAA5HGKuGxm2RNG0xJVs5qeOEx Im5V561dtCZJ9CwD84G5hxnir9peK3duncc1ncu9iW7l3gBjzn kZphnV4NqhS3fJzj2pCbGKI5VH3iM9c9Kqaim0MUJ25xnPWi4G RLebCOw9OtSQxnbz3OOOMCmkLqLMuXAVQR6HvTo3YAA4GOeBTT 6A0TqpI8xt4U984pPMZJRyc5wOeoobKvoWorkAYBU9jVO5nMrF geR056VKXUEJEWjG45Y4wK07NAbUE5wRRdAmLJbhYlJAU47moJ Ll45wuGA69aTKLkd0WYE/pUczAsoOSPWhXIu7kTzguDnBA5HrTZbgyHB+nHap5nsJS6FSVV YkYzgfnXP6zp4u0ZSgK4GAo/wAavqUtDhfFnhAxSNIgJOSc96x9N8QX/hxsb3UAjAFZVqMZwaZ3YXESpTUkerfC39py98OXKK852g4Iziv q74N/thWmtRxw3MqEHAwTXwOY5dKlJuJ+hZZjliadnuj3LSbjQviRZr hoiWHauW8dfs4RXkTy2gQjqcDNcFKrKnNPsd2IwiqQatqeReKf hBdaO7qbdyuf7vSuRvPBmybLoQ3uK+nwmP5oq58ni8v5bopXfh NUX5UwRyD6VQ/4Rh4lY4KjPevahiU1c8GrhXGRjaxpkkLD5Txz06VQuVcx7cbSD nOa6oz0R504NMpRyu6DcOOgzRPCIySABzWrl2Etx7MUUF0HXjA 61NFOrQgqp3DsO1Id7ihJHmQgc89PStIO1vAOScDrUrR2RSaYz TJ0XcX2gZ6fj2qRpB9owABzxg9aGtSX3Ltha/apCu0KB6Glh0mR7nCxu2Tziodr2Y4wuXdP+G13f3PyqxDYxxXo ngj9n26vSC8TbT3H9K5auJUdDppYdy1Z6n4G+B0WlsrTJk579R XeWmk/2TOkUMRxj+7zSlJyiZuCVQ6Sw8MvMqySv5SHsaZ4i+Iei/DOIySzxF1XJywr5fMPc1Z9dlM3VtFHzt8df2+5pIpbPTJ1jToC hNfJ/jz4taj4tv5JXleVmJPLVhgMFKvJSlselmGMhhqdlucPfxz31z+ 8JYeuMVc0zw/I5zj5cDBxgivt8PTVOPKfAYvEe1lzHR6ZZCzcBgWPY1qjzFi3Y 5J4zxXVozlJrZvNw2OKmDDy2zjjse1LY08iAgCVyFGf0qnbnyr okkH1FNPuRYnim3z7sZXoSf5UtyQYyowPX3qUPSwq2xcsSeAvP vVe0Hkbm24OePWrewlYc16/mDkbc96juZi6sQWxjsKS3HbUrrcEMqqTgDkYpUmygYthxzjjmm wluElysgAIBHTtxQjGM92OCM4pJWBFm0cRSgYxn9R71PLMWXCj joOKmW5PNZh9oMcYAwATgYz+OahkuBvJBXOOBVWHqZ1wWaTIzu xwMdKia9yqggHnvVMd76la9nEy4U4IH4VV0WURalkgDLc1lW+B o68BJRrJs9K8OXIcx4Ocr2HQ1b8dwq2mIeOB1r8+hK2Muu5+q1 Fz4PTqjhrWQ7m2MOeORT7mbAAKrlenvX6JF6H5DUVpNIrwS/vTkZPcY617B+y3ceX4wtlyANw+tUyJtJH64/sk6qUtLdc5HHPrX2PoNyGsI8ntUW0OOnqaHmA4x09KaGKnjOap LQ31Fjcr15pzTUhIX7SQOtOjcuPQUmJIlRip6U4yd6SB3GscE9 x9ajkbAqxogllwOPzqnOdxzzTLjuelXN2F5JrD1nXxGh5rOTEc D43+IcWixnd88p+4grjdM8KXfjHVhd3g35OVTstZQXMx3seo+E vhwvlKHQBB7dam8YfCXT9V05kWFY2x1ArSpG6IR87fFP4QnRbh 1ZC0Z6MB0+teDfEX4UGVGfaRg9MV5VeGh10ZnMeAPiVr/wACtcWfT5pjEp/eQsSVYD2r7W/Zz/bD0b4s2UdvLOttqQHzwucHPt610YKtdcki61O+qPdLHUUuEVlI IPQitO2uscGu9nGXI3DiifiM0MVtTjfHUuzT5TnHFfmL/wAFf/ELWXw5eFHwXcDHrzWFZJqzJteSPyymm3F8jLA49qZuAI5Cn611 s2vqLDI6SrkAkmu/8LbZLNeOSOc15GcSUaB7/D0FLE2NXVrMOI0IB57dBXkP7Q9yLe4jRTghfSvzzAPmx8X5n6T ma5cul6HE+FysrHnPf6V01w2+3Qc4HrX6wlofixXhmPn5wGOMH vUZDSSE+h5qoIVmWolZYcNjA75p8QeYADOM9utNINUPMbEjOWI 4xUyB+eqgevQ1LKuLeSAo2SSc8980xQwBOAOetK2gDrZwX4Yjt xUOob2JDHjtQJGbcwr5vYZPU1KI8EYOBVoIjpVLyrggcdR3pXb YcsMt2pW6j3JGmcqBlTgVEQxlyxCj1pPe5NrE9od0TYxk/mak2JtUkAN9OlBSK9yzI6qCM9q0bVjHEN27GeopX0BbFmZQ8ec gkfr7VQvY1UfdJI96V7g1cjinbIwOg6j/ABq3FchkLMc+pxzTGVZ13kMMnHApqShAQDkcn60mkyWrlaadS5 AAB7kDNU7lvKk3Z4HSnYdupn39ulyTlVI7ZOa5vxB4QjvLcOil j/M0W0sXdnFan4fn0vLKOB6Ck0H4i3vh673eYyjP3emK4sVhI1I2 PRwOYTou6PZ/hH+2Lf8AheeMG5cKp5+Y819Y/B79u+y1uKKO8lT5gBye9fFY/Lp0ZXR9/l+ZwrpX3PcNF8c+GviJbqWkhJcdyKoeJvgPpmtR+Za7DkZ+WvP p1nDVHZWoRqRuea+J/gDdafvKRllzXI6j8PrnT4mDxMTnpjFe1QxykkeDiMvb1Rzup+E Q0Xzx7c+orFufBKPGV2kHPWvcpYpM8PE5fZ6GNd+B3t2IWNs9s 9KpzeDJSOE4HXFd8cRF2PLq4KUWPvvBU32EjBOR1xVODwjMluV wyv3x2oWIujH2LvYVNCuEbYsZ69v5Vek0GVoQoVgx6/8A1qqFZPRE+xcRNO8DzSyHCsMnGTWvB8P57iRVAGPXHWoqYhR0 ZdPDSbOs8OfCaeYj5GyeOnWu+8E/AWSadJJYyR9Oa83EYzsephsA3ueteEvgZao0SiAFs8givUdM+D 0OlW8RWAAkZOBXmxruT5mejUw3JDlQ3VvAqLdFkwm3qR0rifiP 430/4aWyXFyVDZ6BvvCvZoVVKLkfPYqjKM7Hz58Z/wBt2SHetg/lqo6g18zfE/8Aaa1LxeW3XEjZ9DzXkYrCTrVUe7l+Ijhqd09TzVLrUfEF2ZAX 2Hrxmuw8MeGWNl58yhifbBAr3cPhlSgkeHjMZKtK7LVz4bXeGC 5JOemKktNPEEZUDk9Riu2GmpwStcmt441uM5+X171LLKdjDfkY 6Y61puKw6IKDxj+WKsKwaIcrjv8ALRZForM+QwOB7c9Kqoqrc4 HrTIYsUYR3JJYk1I0m7AyoOfSm0A6Bm8l+RntRaQ+Yjsctjk1L 3BkEoEkwVThfaqd3My85/HvTZd0mVkuWLA4I45O2nG6AkXB56dORTJbuxJGBlGCzcdTVpbk pheAc8HFKQmx9pIFm5U57VaadVAyAFz2oauxIRpoyg35xnHFVJ x5zggmnsXKVyGeMiLdgD1GaozxmQj5sHHHFOxJVnby9ykbiBmo LS423+Dxg9M1nUV4s2w7tM73w/qODEfun+db3iy4Eui5PTHWvgKkUsX8z9WhK+Fsux5/ZXALt0DHnr1p144Rs9vXNfoEFsflFR+80RqSE4I28fjXe/AXXf7L8Z2rGUq27nj6VdjKSufrN+xt4wF1Z2m1w+VB6190eEJm uNLiOeMVKdzlibQJAA79qRpjghgaZsOSTcB1Bx3pxz3NJggyC3 rUkb49OKRL0J1lyOhp2/v2+tCQ+hGz4pkj575qxFeYkd+KqzybR1pJGkTqNa13ZkA8V594 4+Ia6bmKM+bdNwqr2rnnISRg+F/CNxrt79rvXLyHseg+let+D/BQtI0Zlwo6CtoRSQTd2dhBAsaAAAD0pZbdZVOcU2TY5Px14Ah8 QWTqY1LEV88fET4VT6ffSL9nYxE4BIrkrQ1KhKzPIfH3wgS7Vw I1Dc9ua8hvvBmoeDdX+1WTS2s0bZWRWwQa8qonGV0d0JdD6F/Zv/bim0yeHSPFTbGyFS5P3W+tfXvhrxda+ILKOe1njmRhkFTmvYoV lVhdHPXpcrOgtbzAHNWZLn9yea2OdHE/ESfbpcuD2r8mf+CyWvlbK1tg2A0w71z107aCXxI/OidFLEBTt9apzKUf5Rn37V2Gr2Llgd00QJ/i5J7V6d4W0vdHFxkk9B0NeDnsrUj6jhiHNWZr6jY/6Up6qF/Kvnz4/XIuPEjqSfl4FfD5DaePTP0POvdyyb8jnPDUYit92SMj0rZiutm Axzjp+Vfqx+KJkkE6tMSMY7DNSCVHLdwD271UXoCsT20W6E8cZ NTW9psUnBDA9M0tg3HiN0f5uh9aXeV9SvoRSF0BoxI2Rx7560r xHyQo6896V9RojgVzKeAMGopW2TkE9TzQyrWRUvU2v0I/rRGpDgjkY5OaEyG7Esgxj7oH060yOXzSqrjjrVIExrABjhAB/KmSsxyWAIPp6UmNDbS5wmc5x2zV6zmErZCZGTikg2GsnmXfzAE da0EiAjJ4IpPVFWB2CQlhgHHT1qg75VixJz60k+hLdmMJG3GcD jv1pIQ0h2n9Oh9qcRWsSIrK21icNTyibT0xjoe9Nsozro+Q6ja fc1UuFWQluQSc8d6dxeRTkbaxUg8npmpI51+zlXHJHGetBTKOo +HI9USQhB7Adu9cB4q8CGKRtoY9896XUE7HF6lp8uk3R27wVOS KvaJ8QbzSHTy3dCO2a5MTh1PVndhMZKhNM9T+Hn7WWqeHZIlS5 cBfVjya+kfhL/wAFBpIUjS5kLjaMkt0r5DHZU4Scon3mWZvGrFcx9E+AP2vNB8W 26ieaIE+prvrC68N+NUGJLdie4IrwW3CTTPYlC5T1j4AabrCE2 5QnGRiuO1f9myaGQmFNw9q7cPjZRVjz62ET1Zzeo/A28gbDQMR34rHn+EVxbjDW7D2xXoUsazzquCYx/hvJHBtaDJ9hUB+F37tt0Jx7iulYpXumc/1JLWxVg+GBt7nJjPX0q5J8NlmIwmPUEVUcZaW5isEnPYuWPw5R H4iPTqRXQaZ4FWCMfuc4PTFY18W3qzWGCtZne+EvCUbYzGoyOS RXqXgHwJFd3EaNtRSea4J4m7PTp4flR7FpvwjsdPjjnVkfC5wT zR4lvbbRbDe6JtHcdq6acW1ZHDUlFO8j5++OPx80rwFoN1dNcR ROR+7Td8zN9K+Jf2gv2j18RWgM04LNnaoPAr18PRcHbyPBxtRT 1PmPx343fxBMYrXcYQfmPqfSszQNNE1+omJbkepr18PT6s8yvU 93lR7d8PvBFnqdmu0KrHpXpmkfAyC6gDqQAoy2DxWjepwLe5xf jXw1Do968cRGAMc1x8sZUnjd24rWEk9S7Fd0/fbSM8cjFWrQBRk8g9M0Sv0KSGSxhtzYJfoMGlkJVAOnrzVEq9y BrzYSDycYye9RIRJO3PHrnmnuDsxJiUOSTnHTNOhJkTBOP0p30 uJvYtE+XCMng5AOaLWTy4yqqFzUgV1jCy4wOvNUrza1yenpn0p 3Ka0KkwATOeP4qjgAUtnI68076kh5m+XGDg9z3qViyDPzD0FNh YIr0q/P1PNWoLsSqBnJ9RTY2h85zECpOQMkGoPMaMg8lR1xU3ExJJd9t 82dwPGB1qurk8HJx36YFHQZHNEoVuVPHasmXi+z0PTNTJOzCn8 R1OiX7IVO8+mCehrp9YuftWjuoHGOxr4LEU2sSmj9Qw9T/ZEvI4uCMx3h5YkjnAp075GM/L0r76m7xR+ZVE1NoiRArkgYOM11nwstxe+JLePJyzjketXJ3Il sfpp+xv4futJhspIJmdSB8pr9FPhXPcz6LEZBghRyahHK53Z2Y YgYOSaUyYBp7msdRRPxnFPWcHrimIkjUMDipFjGPShoGhQMD2z 60EkA8UAI0gYe9RO/Ve3rQSlqQt83aql0PlxTNInOeNviI0E32WzPm3TcZHRaq+CfA0 17c/abrMkznJPrXOld3FLQ9e8K+D0so1eVACOgxXTxRBAMcVv0Afgg UZpMBGQMMEVh+KPBtt4gtWSRBkjgiplG4meK/EP4NS6asjoplX2Ga8a8b/DgyxsGj/SvNq0tzenM8f8AHHw6aJiyoMD25rS+C37Tmu/A7VY7a5eW80ndgqfvKPauOhVdGd+h1v342Pt34RfHvR/ijo8VzY3KOxHK55B9xXfzaji2ypzXuppq6POnFxlY4L4h6sX0+ VQSOK/H7/gr74jMvjSztmO7DE9OlYVkwpfHc+InKuSRn61Xdd3G4g5wMGus rcs+H4ydTSM4Zc9K9g8NBfIjHAAHPFfL8R1eWnY+x4USVS5rTW v2mR9u4gD0r5f+O1wjeMplztw+OK+S4aSeYpep9vxK0svkijoN vvtMkDPY+tXvIBZsjn61+rH4xYqxho3PUg8ZqzbSjAwevOSKpo lX1uaKXPlwrwBzRFdl7nIPyjnOakaasOuL4O4JwoyM4olvRngh lzxgUncbI1u2xksQen+TViK73nGckEe1FwZagdFABGSTz7/jUN1NHJKT0+tQlcbRXv1Xy885zkZNVzgQZ6Y5+lUiFqNjmBjG/KgDPPakEozjHOeavqNtIl8veWBJ596bc2xYFwfu/pSY72ZXMSQxM54z27in2NyVZlxt46jrQNFpZcz7uSPXNTtNiNm 56dDU2sBG10HQnGD7nNVwm9yAcZHQ80wJPsrKA3BH8qYH8gsOh 4HHOKSY90Eku6Q7DhM889KeqDywSc56nNFxWM66k3zBRjA5Jx/WmtGrLlSSuMcU29RmVey5dh93HOagtAgYEnGf8KexJqW0iohIz gVR1W0W6OCAevbrUNa3HY5nxH4MivSzKPl74rj9V+H7RoxjjJH YDpWkrNDdrHOXPh6azc4RhzmiDULqyPyMxA4J7VhVoxludFDES pyujovDXxe1DQ34nkjwceleqeBP2xdZ8POp+1ufYtjFfN4zKov 3kfXYDPXzWlse2fD3/gopfWColxPuGB3r27wR/wAFEdNvYlW6kjB757V8rXwc6bsj6ajiaNSyXU9K0H9r7wpr8QD ywDPfIrpLP4v+EdaTBmtsHpk1ipyWjOqdFL1NCHUvCuoJlZbfn 3HFNey8OzDaJIMdjurohXXcw9gupVu/D/h8RFvNhyPcVnXFhoVvyZoTxgcil7eKW5H1bXRGf/bWgWOd00JwO5FVb34reHdMGPOgLfXpRVru1lqxTw7XQ57XP2pt C0QN5M0eV64PNcxf/wDBQWLRC3kSKCDx81YKNSa0RskoL3titpH/AAVcvLK/WGe4cxk4J3dBmu28Vf8ABTTSfEXglo451RQPmZsbmPavqMqjJQ 95anxmeTUp+49D4X/aK/acuvHGuSSpcylM/KhbivJn1e98Tzr58jsegHvXvUKXU+drV9Da0bQHFvllz7E10ej 6Am35kxnpmu1SvocLlc6Tw/rM3h+6UxOQE616RpnxsuU0kRp98jBOcUqkLrQ0i76HJ6vr8+p+ Y7+tYyz+ZIeoFOGkUiZ7kVyyxsGG1ueCafDc7zjPRuvr7VoCYP cbhz1I69O9WBErQrkgEcKRQO+pnyWZmZiMjvycVXikMMwUnLZ7 DpTRNiSa4UcHOevvin2cbAhueelBTH+awbAwfxpHO1GOOT6dqU iWUDdlJmAYnH5VGtx5gZT1649KdupVyvdgxA7lAUnOPaiOYnnj GMDsRTsJqw9JDJMvKkAZp8pEgYgqR7cUXJTZUkcOMhiRT7a4CA ZPPHSmU2WBcebIMHIPFMkuXiDZIAPQmpsT1AzARANg+hxxTY0L RgZBFUPqNaQMxXofU96y7+TZcA7SR35qZvQ0pr3kaekXJAQsQR 7Cuvif7VphUgEEde9fF4xfv0vM/SMD/ASZzbwlJ5SORzileFWAPXBr66jP3Efn+LjavJeY9IQ0fUgdT2r p/hEFPiy1K4BD+uc1tJs5fI/VL9jg5t7HOPug5FfoH8Ngv9ix4xjFCZxJe8dIY9xPGRimsm00z VdhMAD2pVXnnkUIfQcoIPFSJIe9MCYMDQXyOtAakbn8c1E7ZP8 AOgCF+Mmq85AXpx9KC4o5X4efDvbKssoaWZj1bkmvY/DHhKPTYFZlBfHT0otYmTuzeRNq8U/pz3qbMBwbANIWpXATdSMRj1p2Ap6jpiXcZVlDKeoNcB43+EVrq 8LmBBG55wBWFWHMgWh4H8R/hbJp8sySQnHODivEfHPw23u7eWcewrza0LxN4VGjhtI8Va78F9 ejvNHuXjIOXiJ+V/qK+tP2ff27tK+IVnHp+rkWGqAYKO3De4NaYCt9hnRXhzw5j0Dx 1rsOoaa0sMyshXII6Gvxn/4Kq+I/7T+NUcG7hVJyPrXZV+JI86F+Y+WVfcQMhfTIpdoHoCR3FdLVzW xY0CFv7WQ43HIr1TQZj5SnGMD+lfJ8SK8bI+y4XXK+Y24p0i02 5ckZAJFfJfxP1D+0fHM2cFQ/PPFfO8K028dzH1XFdT/YH52LeiYWEKrnAYY96tmQrLhe/TPav1DrY/Ir2ZVkiEa9Bz3pYY2dhsc8dsVcdgkzQgQyAZ55zn1qZ5AgPAyP bGKgLIqmcM7hgVJ9etIsiBgABj24oSY1uLK4Hy7gWznOf88062 yY8ZIORnmkkJJovW8p3YZg2OgJptydsm4N+AoZch08K3EQDcrj k1Ru18sDGWHPUjNLyIlcqB3YAcgY79vrT23/AC4J9z61S1DcsCN8j5uvXParfkiSMKAwY4696Gx2KsyiNckAVU tp185iSwGMcilcpMuWuGkXBU57VdmRnGAduB60uYkpXGYiD95u OlR27AyZwMjrzQmCZbXM4CghfXP4USoFAbg5GM4zRpsMhSMbgA y89vX/ADmnmVYYjwN1K+ok7sz2l2M5yFY8imBSUGRnp+FO+oO9yjfwb3 YDr7jgVXRAJRhc5Pb1qh3LlmnlnKBSAaZcRs8xAzkc5A7fSlLY dylfbo4iBgkf3RVVLMXMKgoPQ5p2JZSufCUd6oUovTpxkEVi3/w7MbMNoxx9KTV0UtUcjr3giWEFSNuOmKxLjw/cWpwrN7ZrPkWxUJtbDILu7tTkl9qjkkYq9b+Pr2zjR1d8/wCfSuCvgITldnpYfMp07GvpfxmvrFFAnkUdflJro9K/ae1bTyqrfS7uBy/SvMq5NGoe5Sz5uze50em/ti65aMFW+lI6EZ6VuW/7cetW5UPeSLjp81efPJLtpHqf6xJqxc/4bk1m6Xi7k3f71Vp/21NZuEw1447n5uayWTPZo6P9YKdtjMuf2rtUvJApvXyexbkVl3 X7Qd9cPIzXMhPf5+lbQyblloedVz7W6MnUfjLcTNlp3fPHJ/Wsa++I9xehcSuWI4Oc8V6VHLEtzyq2cykndmZcapd35Vizgjkn NT2epXzJtMspUHoTx0/SvWWGSVkePVxLlqy1b6Y95cEyMZC3BzzxXZ6Z4XDLGypzjsO9b NctkjglKz1Or0jTfs1oNwz7Yq+sZnl2jA+vrRy2Q3Zqw5bRZpy OvOK2rGyIh3NtAAweKrZAu5HdxYgZfy561mlSGU/MQD2FOLG11GTRFpucsB6CpBb4IXG0Hoc1VxaEUyrv4LdMZzTxN iEKGPU4yabRJTN8yPhsc4xn0qJm82cdCT+lM0eoXUpBAzlscGp LOYybgx4HNQk7EJk1uV25OTjvTWviAwzx6EdatIq6KE0TyynBL L6ZqGFjFJyvy5ONvWi+gmJN85I27lx60MgRWBIJI4JNK9gsQwl lfJGxvSpWuTNuDOSMdc802riILggAn8OOtERLMpGd1NqwJk8bM GIGCVxRc8OQNrMBkilbUVtRmfPQ8YNT2C71JOQKRS8x8MayyEA HPPOMVj61CEucE8N+tTLUtJN6GhpNvm3QnGPrXY6ImLVjndx0x XxGZOUa1z9Iy2LeGTOeu1BvnAPB5A7VJbspILAEZ54zmvrsL/CR8FjocuJkmOkkUxc4BH61r/C+5e38WW2zGd45zXWcLVj9Vf2Lrjfp1huAztAr9CfhrMDosY9q LanF1OmxkU0rljk0W0N2wEYz70vl96FsTcCuO1L0XnrTY2GcDn rTi/r0oC9yGWTHpUTXBHHWixQ1pcrz6VWuCSM0yonf+GfC6aZEGZQZ PpW+ihV6U5Miw7aCKOMCpTGBHFNIyKQDTxSFwKVwE3g9DUctus w5FIDnvFXgm21+3ZJEGSOteCfFL4HzadJI8cZePtgZrkrU+oRd meG+MvhokokEic57r0NeL+P/AIcXGl3oubPfFLGchkOCK86rBqzidlKozM0X9ufXvhXK2m62Xv rXGMk8gV8S/tp/FW2+J/xTl1OzkJhYd+vuK9CjN1UpdjGULSujyOxna8nCoQWJxx0rrNG8 E3dzNEJI2YFhx7V39TPY9Ktfgj9j+zzBQdwyMV0Fv4LWyjA6gA Yrw83w/OfRZFiuV2KfiPS/sPhy62nBK+lfJHi/SFGvyvhmUPnJ+teXw3hHCrJn0HE2LTwqiWLS5EFuo29eBjpUsJ Iw4wQDyM9a+y2Z+fyVxlwSUYjPHH4UWOfIBHJzk/pTiyUjVtiXAzkDtTDGwmIBY5U8UNINxrRLIO3A5yetJ5CohK5J J6UkxpqwmzuASe+RzT4x5ZyQAfSlLcV7k1uxE20kEgc57VZIEa DAbHfpipbZTv0GXUn2i3AQknrjNZT744+Wzg44NVbUjmsQPdFF A2HJJ7dqfbXPl3C5IOOwqkio2NB7gAYHXHc9Kcl15cbjjHcZ6V m0BXllDxDcchuwqvIiq2QNzUNBYSxvfLbBVfXrWuLtZbfCbSc8 7T1qrFK1itcrwuSeR0qpIS+eAT6jqKSJJLOfyY8k7mIwAamn1H zYsNj3OOtKRSI3nKS5AOMdqe8o8kE5GetCWg9kVnVPLJDDrnnv Udu+WAOwrjI5zxTExtw4YHCj8RVWFF7Lz0NDZDXUfbLmZcjHYV PKmyVQgyucnPrQy7lK5gE5yVJOT071C8YiQdFOOOOKFsS3dlW3 uH3ow4GauRbZXG5B2xTloilZ6Mqano0c6sdqg88Y5Nc7qXgyOd Q20bifSkBh3vgVlbftwAccc/rWFqXhIoNhj49egqbE2MG68NiOXBDDkkH+dUrjQynJD8+2KbWp op2IGsmXGWPBpyibIZyVwcjNRUirFxqMu29rK6L9/k84PXtUiWcyhjhuTyc4xWbpp+oe2ZLbaXMsnBcn6ZrQstAluGO S7HHUEfypxglqKc3IvHw4wONuV6Y9Ks2HhnzJAVA4GCR2qoozU nazNu38NhVClQWPTC1eh8JeUowoC+mODTinYpyua2m6AkTKflH Hb/Cuq07TAYUO3DKBScepjKN3cuzuIIiMYPT0FTQKJVVh8uSe1VY0 EErQy+YfmPb/AD+daen32606kH0IqLXHcVXQ4GMn1qrJFvnz94ewppWYNkcjLv BI4/vCmscvn+L0PpVW0I8ivcbWlCnOfrUGo/KCwO3P6VSH1KURbzRgkjd27U9TvlI459R/Wi+otbhdkcEdR2qO0kCBOGYD17U7DaLdu4C4BY5z1pQy/NkDb60JiTuVEk3z/KGAHOTxio/LVn7YHYdqHsXNpoSaAoFwTtzxSEMkIzk/QcUlqLUrvGykksM46mnRrvjPHOKGG6sAgOwZwMnGeCakWEA546 cc8VUiSNv9HZgPlGehPNMaNivIJ6mi4NlhFXyhtU5Ix0yfyqbT 0ChyF4B6VCfcaYzzgLjdxz1JOKxte+RyZCzDt9KT2LhuXPD84S BFJXG7HXpXdaO6iyHCnj1r4vOL+2Vz9MyaaeGSXY5vWZGivuhB Jyc1DDdFN2OD/KvqcvX7hHwuaJrEybEkuBJ0zkdc1tfD3UBYeILYudqB8g4967t 0eXe5+pn7EniKC606wG9QSo6V+i3wxlWfRIsHkip9DmtZnXqhR PcVGUzxwKpbFXFAwck/SnjAoQaCFRnrQ6AiqTGmNIwajc8j1pC6kTvt+lRucGmUiN5Aue 1V55aRaR7BGoUYqQCkQDDmm5OeaWwBupu407ANZ+KYzAmoFYY3 y8inJJmgYpTcOgrP1TSItQiKSRgqaTVxM8j+JXwFS+86e1XJPV SK+Xviz4Gk0iSdZYirKcGvPqx5SoTsj4d/a00tLfUiQCuetfGPj+43apKc5YPWmB0bRtJ+6YuhaxJZ6zbuDj 5xxmvqzwd4YfxBpNncWygkgE7eua9JapmEu57F4Q+FeoeJrJR5 LHyh35rZg+CBkBEg2HOCK569NT0Z14Wr7OaaOY+JXwYiTRpUVg CV9K+Tfid8ApLa8lljODkkAVOX4VQvY682xzqQjHseN+NPDt74 eU4UlQ2SBWBpvi9kOyQZPTPQGumd0zy4yTR0um3SXlttKgn2FS 25MQ6DP8qEK9mXVmK49aSa6yVznniiwyJp2Zvu5A5PFSiQvAcn Ldl3U4ieqJkVWiwG4HTP8qFbP8PzZwWpNjUuwsAELYI69DjirY YTL0bPQE0ikySLYqDJyfX0rO1Y7mJUJg96TEzJOSGAU/U806GL593Of7x4q7WJi9TQilHkqcH3yabI8bAcL6kDFI0TKk7t JJtB2jHGDxVdZmSQ5yc9fWm2SmE0nyA8gZwT6VaivfKgCkFT1+ 9xTQx09+Si559MHgU2IkSYBLADv3qbBbS5LtDg8gH+Go0UhCWI Azwc1LVykx2N204GcduOKnkJVM5AH86Itmbu0QYQoTklepGOlN jXy4/l69evNU9iiO4gKnPfOKrFSx2gYAP0ouVfQlik2qzFFOBjHerYz cOpYFgan0C5DPC4kwCufXHUVUlhdk3dOf1osIqPIEZvl3H19al SETsrjGD1ouF0Sz2/mJwVz6HvVWYPhsLj8KEK5W8tXf517dfQVSv9Njl4wrDOScfypg rmVf8AhO3mt2wBgZBHrXL6t4fUZ2rkj07UmtRNHKajClrO4I2E 9DU+krDd7Y9+W796mY07M6jRfC5nuAEXKBeCO1aZ8Esj/dAA64HX0pKOw7lnT/CBEy5VSAOQV6VrW3g4/eVVUfrRLsJXuXX8HoExt5A54pln4ZVCpAG0+2eaIKw7K5oW+lR wFVckndjpWj9kjKgKpzjg+lXfUXKXVtBHDuC598datwz/AGO3Drwc9c1N7q5TRWmuROxVwMk5z0q9HGyRo2Rt9cUnpsNu1i aONGPIwRwDSW0G+JuflPI96mxNncDhD04B596VJlWTOQufXpVI qUrpCMEdhgDp09arzzEDuTimkSlcz55t6KCMNjj3+tQTzE8jLf VeBV3EtipFOfNYbjuJ44oS4w3OevPHP50wvoSzOzMG6j03dKs2 aK0ZKg5A6YpN6Dcr6ljzAsQJwGzj2qEMCpHB5pJE2I0BVtwOB7 iohE27djn6U7DI5Dvcgnt0FWI8T25I2564AosORWEPmSbQByM8 UiwGMdAR09c0dQeosW5F2sflAzuC8VGCyBT0XqW7D8KpCQkrB4 werdjSLvYFud2OfpUoRZtwqRgFB1+uKtW6eZbnHP8AwKlIu1jP eBop2VTgZrN1bd5wUlyPc+9CkiovcXR5svydrBuprtfDty6Wyc 54A618fnSUp2P0PIbewszI8VxEXLNkhu5x1rJhmYjOQfoK9/KpJ0EfIZ5FxxUixChA6lueRVzRw0l9Fj5Tv7fjXpnjJ6n3z+w1 ca3o6Wkm7zohiv1P/Z+8Wzano8KMhDBQDWexzuSbPYEZmQZ4NKAMelW2W9xNoPXpR5e CDycUCd0Ip9+O2aQsBnv9KY0MdyFpjMRknk0ARO4ByeajagpEM vPSoJDuzxxQWmeyp0pwOKCAJphbFS0AjHNIBSAjcYFR9+9IQZy eKApU+lAx6Egd6VlDAUC2IbiyWVPWvKPjd8KbLxHpk+bdS7L1U c5rKrG8SbtH5Lft+fDnVPCWu3G6CQxox2tt6rXwF4pQ3WoTFxg 7sdK5Mud3JPubyleKMW5hEDhskEHt2NfTn7HvxpsriSDTb2RY5 o/u7jwa9Nu0rE2urH6J/s43Om3nhnUJmSB32kjoa4XxHqpj1G52DChzx+NcmKq8rR2YGje ep5p8SdYljspCwJ45zXzz8SNYZ5GyvsOK3wFYrNaeh4P8THN7F KQoK9DxzXjWraZ/ppMaANnGa3rNM8yjF8uptaAzW7KMAZH+eK3/AJVjB77eM9alGz1Eic+XuPvj/P5U3zjLJ2bB5wOlVcbsiaJcvhgCR3zUqAFuVzz3HShqxMWOmyu 0Lkrn06VJAgHzMdq+xqSrCSyN5hBxnPXFKlwS6n0NAkXI7tXXB wOD+VUdRAlY84XHpnIqE9Qe5lSzLGcBhjp70m90Bx8y+ucZrRo TV3oSSzblGcj1FOimIRnGDjrSY2ExVIcgYOfTiqjHy9/v3I4FEtEO4xpE3AFfqO2KlkuBKQFCnC9CetUloT0I0ffgDO3oO KljfBzk49Klsad0XYyoC4AHHXFOCgq0bcfjmgaFgTykw3X3qW4 IaDC4znP09qlsCoz7dxI5J6U60G1dvBB/Wm3oJ7EisGJB4qrMw89yfU8jtUxfMi9iBpDFKDxj+VXrGUFhkt uHTFPZEx2J2Ks4BADHvUeoW6wxk8jmhXKWpmHSUnlHy4yeTUkt sluxQEDtg0CHPbCVSTt7dBUD2nlrkYwD37UcwjPuWNtuJwF68i qFzdbgAB39KpDuNlsmaJuDhlyRXP6wQjyZUcDBIoBpXPJPiNq5 t7xlXgMevbrWf4OvJJbwvlmPselR0FfU9r8AM+I1I+Y9TnJr0W PS0lhjyMHH/wBepkwab1Fj0ETyq/ATFXo7IKcIOAeuKvcE+o+608OmduAOoqpBZDDA9D6VCTsU0Qz2 wSXgAHPT0qdYDypIIPc+vtV21B3uXjGpg2g7iDkimyQEoBkBQc 81JL1M6Z2STGD+WMVradOZYAjEAjvQ42Ki9RHby9wBJ5plpeFw VyVGOBmlbqDui/sDxqOcH3/nRPZlWGB1qb3BK6KX2k/aGUgcfhSag+5lxxk5zntWqEilcLuVcjGDxjvUNzbBu5IA45oTG mUbmBs4yS3XHeooFMJ3EM3fk8UIhotKTgHjHYGrNoQltkrwe3r VdAC4k8k4yV7VXiuv3oxjn86Udhl61+QZKgkdhU0qoUyWxzwMc GmVfUqFI97fd3g8HtipEhQx8Y4qU+hJWBUSMQQfY1JbqZI8rja OB7UykEyqjMrYwOcYqpPMHdsgMOooTuKxXkZ0U8FhyeKW1mAQb gWPpQmK+pZiUugO7bnqc1LazeWrZI5/holsOUrqxTmuispGByelZ+rv85YkkcEDHNS9xoboZHmY2klj1z 7/AP1q7Lw2CWxg4B6V8nnMeWpc+/yCTdBFfxxHs+fJGeQc/wA65i1nBI6AgdPWvXyTWhqfPcSRtibl2AF+d3HuK0dEYjVYFA2 sCOa9iVj55NLc/Rn9he6zpdoDgjiv06/Z/hiGmxEIM461EXfc5pK7ueqgHHTFIScdKpmgE7aRm596YSYwsSc gYFRs+MnOKEwVxrPgVGz5PXBp2KGF88Gmu+AOtCYETkYqGVgMn P4UMtHsmcHFO7VDIDNNIpsBuaQtipbF0GP81RMhP0pAtgiUg1J g4FAxV4PpS5Ap3AQkgccVheKUEsDZHOKTJkfFH7efhawv/B+pSz28TssZOSvPSvw98eosHii9SI8eewU/ia5qMFGrp1HS1RgXEJmRxhiM8mk0i5n0C7WaCVlkXkMvWuySLi rH0p+zV+3zqvw6ItL6VpYNgV2avT9Q/bq0TU7l3R1Xeema8DMsQ4H0+UYF1ZXRxHxX/bK0qGw+UqzMOAK8I1/9q/T9dunwMHFPKMQ6t2h55hFTSRx+v/EWDXEcohyfWuVuJY7x8KB9a9y9z5i1nYtaVZbJwAox64q7LPlt u85XjNUhsZK3zAfMB/OnW0rq2Sc4HeqIki7abZZQcYqbZty+SwzTuNaDpCvPy4PbnOaV 2y2Ayhem30qCmxGO1QV+nvVa6kCDCkCgG9REuWWNeoNQy3zNIQ AcDrn0/wA5ppIasQSzIyscc5yTiobi/Ebj2/OqTuRK97oQakrLlQWB4Oe1It0FBC7kJ45pFE32jAUMeCfyqCWY xuwB3D0zkmiSJ6FZmbzMjAPp6VLHKCT1wec56UIdiUuN3A5Jxn 0FBk2IoJ2n1A60mhpFm0nAk2k57fWr8MqvMw6c8UguOeHzJNwI PoKikhZCPmwe+etJdgTGKgOWJPA6Utnjbk9v0pNFpDkG6XC8ZO PrUV9Hh+nQ8FfzoTsS2V5FwufboKdbSlSDnntmq6BYtwSCU9x0 P0qe823afMuGHGRUX5UC8imkH7rJbt69/wDJpotd827AxTuhXJTII1wePrTZ4POgLZGQOKl9xpJsxtQgImw cNnrVCWDZu3EjaM9K0i9BJk8H7+E8dfSsLX9HF1FKcY7fSk2Jn jfjvw+8uptu5XORxTvCnhhoZUKgZPXpT3QS1R7B4C0aSB1Lgpx wK9HggUWy9Ao/hrKdrD1egR3iq20jYePQ1pQgLtYdT1x3qo7DatoF9CyR/LnH05qklsdwcjK+4ovZD6ala9hLuMIMd81I9m8kKuTgAjj0pqX cL3JAhWHeMk5x0pYnDRHcVYnmhMERT7Btz9Kl06IeXjLLn17UP zFuMfEpK4Y81HGNrcNnHrU7DVzQjLrtOTjHFTFiwwxJ79KlFJW VirJHvuC2MY6/Sq1ySdp5UAZAq42vYhdiu7KNpPynAzmqdxcKFbaSQepNUtxXKU jbpCS5BxxmmIC0mQPYZ6YpgXUc+aVxyO2M1OFVlVc8n8qAeiuV 7ohY1yep7dahtxgDOD+GaL6XBal61b6rj9KsSEFMc5pN21GtCn NuLDGAfQd6Yt23l443Yz1p6DsMM2FDEDI9s061uto2fdHvQ9hB PKC20MdvfFU7iZYWIDDkYGTSW9ht9BFuNw2kNnGD/n1pIWJccnGOOKexJIknmIcHHPQ9qlWXaV7ikK2pA0geU+1Ur2U OhBzj6in0NL3ZHoI3X33SvOMGu88MwHzsHPPPAr5fO1aTZ99w2 06QeP7RRbgD5j6iuCiz5pABA967chnzUDxOKItV0XUuDbQgkgN 1+orS8PXDLqkbYwSw7+9e01Y+XP0V/YZeNtItMMQRt69q/T/9nrK6TF838I4pRZzPsesghl/CgtzVM0GsxNMJIBxmhDSGOTjk1EWGeKENIYzccA5qNmyelUhkb SMD0NNaXPSm0Fxjy/lUEtxjP5Ui0ezh8+9OzxUdTJ7i7vzpC3HajyKGeZhulNcbvpSY DCpNKoIpCY4D14pfNA78UDAEMeKGXIPFADT8q1z/AInk2Qv9KCXsfGH7et+sPw+1d8gHy2r8MPF7m78TXjnGDMckde tYU4r2txU7q5RyM84wW5HrU5tFdc4Bb0z0rpZqtSlHpcjXDfK4 GemadLpbWsIBY7jzzXzmaXPtuHpNRv1Ob8duW0484XsN1cHo9s JbhxyTnqeKvIKfLTbMOKpWkkjsNDsUEeOMd/St+LQI9gYYAx1r3up8eOaxa1i6YB5qGVNgLDnj+HtV3HbQrs+9 j0YdMZqWB9zbSM4/OqtoJaIu2wC56AZxx2qUuIyRkH3BpPe5Vxk1yQ+QAR1yev4U6C 8UwkvknjO4UMNbkqXBkQAge1Ub1tz4U89ADUxeo0QvceWoDHcO p74pszFAWH3scCqAqSzKQS2VwcgEVBeP5aFj1Pb1qrEpmfFqDx XRJHPQ+3FWI78sQNyg55Hf9adgbstTTinzGo4X/wDVUZRSmT1Geai4oyVik8vkTjnPfk9RVu2cHOW5Pfqadiuo6Ik zZBOO4brUhmDbu3TpUtFJXHxAxEHBzn1qSG+EU/CgjIHWlqJI1VuUmHy4H4U51V4DyAMYyOaLDKqo6xkNzxzUNjJs dg3GexosCJ0lBcNyQf0p92FIBO4cZFDC1yJggibkHnpj+VVEhU vyQcjgE0XBPQRJvKBIzjtVgXnlwNzgDrz2pOLYRdmVxdFnAQjG c8GpWnMT7STnHSploKQyZt7LzjHQZqeEMsG1SBjue1U9EOKMmW Mx3Bckkn1pTs1BguFB71W6EPfT00+3+Y9iAcVg63qsUch24x09 DmgEzy/xrJFPeOWO1s8g8Ungu6h+1gNgAHqO9JLoS9Ee0eDPsl0I/mUsOQc9a7G7tII7JSGA9dvas5x0Gnbcx4JIUuCHYdcfWtSDUo0 cbQABVqNtBv4rlm71hEXOD04yMGqkGpKyZZec9Kiwpoinut+AA uM8U+ZxsBPKjoc0dCo36CSsWtgehxg89Kbb7d2DjPBoXkGuw6a 3V/v7Bz2FNgUQxt1HfjpTvfQuKVjNmvHilPzEfjUguATwcjPY07dh OWtzThmdbbgYXrU1i3mOSzYJGKj7Qk7oiuZmFxjOPxzWfeXOH+ dlUkY61drg1YqXczDgDJx1zVSY7AxHQ8YzWhJWliBY87sevFOg JiIBwcUk7hzFq3O8DBGG6nOOKnVA38Qx2I6UbCloiveN5bfKVz 3z/n2qIXBEpUDgHg5pIOazL9q7MqkgFc8kdTUzyFMkjOR8vpSY79y vcyqz8Db7ZqsIiqFvvLjpVJWRbWgx5D129OMdzSQzFpB0Oe4pk JCzOcdkPfnrVGe4Fx90BnB/Ci2pT7DBKEGT16/jSq4Q53c45GaHYnqL5pVDk84p6zmNRuLAZpJk82thiTtg8gHGf eqU8yhsEDkdxTsWh2hXY+25yvy/w16F4YO6VeMDGK+Wz7zPtuGJKzTL3j23V9JG0jgcjPSvNNmJm2 KOPU9a6eH2nTZjxbH95EshSIwWBBPUnqPwq5pjH7fGQQRnpXvy Wh8YfoF+wpqyLYWqlxnA71+pf7O+pCTSofmB+XnmoSsznlGzPY bctIc84qV/lXmtOhpe5G75PTHpTZGORQgQwjk80xuaClqxjEBqikkxTiNvQi eXjv8AjUby8j1qkhN9SOSUYOQMGqs8qkZOaQ07o9tBxTt2BUiY obPtSE4FStQGuNwqGSV4xkcipAat8ucEFfepFnXsc0APB83pmj ygD0piFCZ9qCSoxg5pAhHyFJrmfFkhW2f6UMmR8If8FI9ZFj8L tYbdjMbda/E3WF87UZn6Zfkk8dTWVJ/vGXS+G7KrjyiCMjuTV1JGEIXpxx7V0stFq1nQRHGCcdaqajci4 UYwMHgV8pm7a3PuMgasjk/Hj7bTk845GK47RLUS3GAT15wK78jX7rTY4+KX+8SR1ukp5IAbv 3NbP9ohLdfuk9+K9ltHySS2CTV4i4QntnpjmqWoXG6I7epHrVJ FszYDsc5Ax14rRtJ8x8D5sflVS0tYh7qxbhH7ksfm/wAKfcZSBVxjnkA073GrXIZH3Ecjp0pTMrggnIJxjsBUtg3Zgso iiAVmUdwB1qtdTYcMwLn0Hal1Ktcj+0CWVWwRjjn/AOtSzSZJOc+uaLiImjEhDEEAnHTioNTG8oxJ4rXoElrYova7P3 i4B6fjTEXY4fa2M5zilfQiWppW10Rb7iBgdOP1zTxMZIs8A4xx 0/Gs1sKGmhWZAsmB1x+v+c05F5OG5A71Vy9SZerndjjn0p33GUDB ZumOAKTHfsTQRMwwzd/SorhVtZ1BOXHHvSvqPctx3rJggsAD2q9DcKyrnLORRsF9BZpF2 EckkdB0qtHBtkGc5PQ5xRuF9CYjgZBzkA81PdkC24PJ/HBqZXsCZWzmM7c8DvWZfOYpCu4H2zUxb3BLW5FDMTkY6cgZ5qy s7EfMDtrQLkYCkrjcB1yDUqRl2zjJAA69KlNMWzK10zRSKOfb0 q3bXZ8rDYyeoJ60S7FJlKeUtLwRt7jIP4GniUQxs2MMBnOe9OL 0CUbFPUtbd4NhDDAzgVyOvu+x2LE88H0+tDEmup4/8RtSliuGC5HPasnw5qs6Xigl15G7HT8aUXdkX5j2P4e6vMWRQ+ FXnPavVbO/eayRy30FEloVa41G82UlW4PvVtIzHGrZOe3FD2Bp20JPM22/LZbOMUtsWljLZz6iosUkrEbSsk6gEHn1q8WMkJBc5xxSWwotpW GgskW3BbB654qSDYn3gS2eoqtblRWjY4Nt3MQMdRUcMuSVX7x5 IJ703HqF09ChdQFpA4ORn061C1vJuBPTtiqUkFuhrWiv9gLEEN 9elFhLIrsSp2Y6k1HUdklcZNOFn/h/Hg1nTTN5/wAuD3x+NPbUTdxl2vygAYOO1V5V3Idpb6etVclajG5fLf8A6hS EKzDk4PU9aYmuxYgYPlR8wHIx61JFMfKEeM4HH/66JO4XuUzFmYk9cjn0pqoWkODkHoO1CG9y35rQIxw3I6etSW97 uIJ64xx1oQulguNszbQpOASCaWBHWM5UgdxQ9g3Ip4jwRwD7dD VFGaKU/qeKF3HcWLDpjOee/FQzo6ucsD6DFF9Rp9SKRSiHgg/U0hbercZ54oewtLDoyzgbl4z1OPzpzhcAq3I78daXQmwrW7LHg gEdeKzLoEqVAAXp6U0OxFo4C3YJyMHgf4V6F4Zu/njGPkxk896+Zz6N9z7Xhh3bN3xe/m6E3I4XvXmLMsVwznGCcEGp4ck2pIfFrTaY8S+ahJY9celT2E7 rdR7OQPpX1K2PiEfW/wCxr4p1a1uIFjidogf84r9Yv2T/AB08mkQLKjBto7VlfUwm1ex9MaNqLXsAbGBirryDaMVomVEjkw e1Rs+BjmnYCNnznvUbnIoKRG5PaoXJ9qpIZGzH1qJ1JHpTJbK8 7Y54qlNMc9TihhA93Dc07dkZrJvUYZxilDYFDuJjSeaY5FJgII Ek7CnxQKv8IoYMlCADApQKQICOOKTHNAEc5+TI5rkfGE4WCQc9 OtDJktD87f8Agqxqv2b4Uaplgv7thmvxvlnDXDHLE8/SsaKvUfp/mVCyhqPYiZBk7v1p0m54QcYH61vzGsXcSBiyEFfl9zUd4SUGGU E181nT1ufaZA0mcv46uPNhKrhjisHw3lLnIyoPeuzI1akcPEr/AHyOlDGMAYDZHJBpbi43DG3ofUdK9hRuz5aO9ynPdkspXI47/wBaZeXTSAnDBM8jpWqVtylcI77G5lU47enSpba9/ckg5JHGTTbQNmjaajmPYMhs/nTpboPuwFBPaoW4mluIJPMlIwDlcfX3qaGxVskqAM5OKb2H6jr tRDCoUhhz0HNUN+JTnkk96W6KUiOSbbOpUDaDkhRyatwn92u7b kn+7RYSYG0E5I+br07c1X1CyKnAYkZ9Ov41dwloylLGI48Ec5w M9KjhjUR4UEnPrmhEtXJYcAYPX/PWpEh8tBjPtyP5VEYpExiooa8auCdwBznjiq7MIQQDuJ9DxVXK vcnjwCQWC9vXFT2+RwTn0pJaalJFi3ZlQKwB3c8jpVe6jxcLnA I7HualvUVxs8xhYDAwOD/hVrT74HOTz/KqbQ0XbZhIp3Mx5xmpgnlRevPH9alMdyEXGZOCvJ+YetJcKd5x zx6ZOKLiEX90oZiA/v1rPvFEkgJK4+lCGtxvEcZOMn+VOCiVNxPQU+gMkSNdnTIxwQK sW64cAfMNuT2qG09AvdIrajdCOXCgk4HU5pFB8jA4yepHenZA3 1Kv2Y+ZhiBntQz7pgMEY4J9vpS8guQatZq3OMPj06VzetaPM9u QowOvT3pxVlZkSPMvGPheSaUlkB2njA6isrSvB8iShgjAZGKd7 CXU9L8GaK9gULYHQEV6DbNusevAPOOKlsa0RPYTI0hU5Axn61r RMI4wAWHAPHFRK5S2sQXigqSW5AzzxTtOnV4ckbvUn/P0pQd0ayFaRZ5R8wKjjOOT9KmKlYvlbag4zmrUuhn1HPKEi5BL eo71HCwLZ5K07aFNXiTiRFztIIxzUdsAXZwen+f8aWttSE2Qzt 0UAPkZFMmR4wCcZODwO1O2pd9C7HqYS1x8p55zTbe9812xjHbB FLYSZXuH/e4YEjPSq1wmZVIGTjuOlWttQk7PQinCpLnJwT/n+dNYCOQEbSOuMUIV9SN8SnIBU+h7UCL922SowOw4psJDQp3KQ xCg9jT0mzxjgkiixNiCRnf1AOCRT4nZHIbA9OaFoU3rcnkw6AD IGOMVGo2KSAxOPvUWJldiG4MMhwcD6cZq9b6h5ifNhs98Yz70d BwHX17G8Q2qOT2rLdNrkg4/4FQmCFC+TwQMdPrULY3EDgdc0IfQaypgFmJB7EcZoWLczBRkdh ih6isDQ7T0XC8jFCYWQnIIHahvQfQGmLpt2gd8571m6hKolOTl cdcdqFqymtCtYEyXSscbSc8967TQLgF0JzkAfjXz+dwutT6vhq WtjpPEE/m6A3Ucc+9eV3EzG4IYA5bGSaw4cklzJHVxcklGxbt58AdOfyNW bedUnXZjdkAjHevqD4ZPU+2f2FLyOaG33Ip5A6Cv1Q/ZgsLSS1t3KjJA7VmmctRLmufSNjtECqgAHtU7YxirRrHYYxyOa iY9fpT6ARtjPoaY+RTRSehG2O3IqOQHr1pphYiZffAqCVtvuab JehVuJCVIrPuyck4IoZcT3wD1NKRtPWsnuTYcOVpc02MG5FRle ahkvUVRjoacrMPcUxj1Y0oz7UhNi0YzQMiuOIzzXG+Nm22cvQZ FDJlqfmb/AMFctVW3+Ft/8/UEfSvyHmndLkjkrjPSs6DftGXG3LYs2k2xTkAc/iKnjlCwk8Fug2966GaR0GK5weMgnt2qrqLhZsZBX+VfMZsk9D7 fIoL4mcf4uuHaY8ttPbuKh8NwZUHoo7+9ejlELUTyeJKvNieXs bkqrlB8x7cjmopwZvQ44Ar043Vj5yOhUlbyn4IPrkdaV1ygHBP vyKu9wTTEiTZkkdsfSpLcELkAA554pNA0SPdLGV4GccE1Pb3AD ggZGOhxVdBN9C7E6khgfxBq3ExKAHB4z7c1KRSQ77OJEPBPPaq RUecwdTmlsLW5WuYPLlBztGenrTVm8pg3IxjvyKodjSgulUBiC M8HFJdssrb19OAKlMIu5kXUCtKwPAA7HpTIVVVGTkeuKu4wL5O OuOhFQ3UnlxKSeg5PcUIkaLz91n5RkfhTZMIAcj1obsDdhRJvb Jx/hViCYLIck44IGaTYdS/HIGZSdpBxmm30qB1ZTlvapitBIoX+JNzhmOOenNJDLtJ2uSRxn +lN9yy9aXRZcZxzn/IrXimEiKNwz29ql2C+pXdFWYDI6c05ZtzpkEHHJ64p3G2STxrd qCuA3tVGSwM02GBKAcU7iuLLDGkLAFN/51HCUaB/k3Vne0hMjcgKBgn1H8qs26NIgC53DkmqS1uOxHeW4aYKTlwc9c 81K1tgZABHU8VLegm7kCW0jyE7QVzz7f5zUEsflXO3Aznqfzp8 pVtCS704TWnYDqfeq1vZNNGylU244/2hTi+5M3cx9W8JpdOThFJ5JrFl8MppU4xFweeKNxNHR6FpKyHc VBBHXoelal5bLCoVMAAdutSmuYfLYS0f9782BjjitAuoUjfRJF Ihu/ljLI3DD8qSylKwfLxnrwKTYIWG4DXP8IzxVqSVlGM5AHrT0Bp3 I0maQDgHDc+9P84RpjgY7+lC7FX0uSCcBeec+/AoS4EcrZwc88CmtiY6DUHmOpbkdsinyqM7ssOxFNKxS2HeQrQ5 bDZ79RUdnAYF+Ude/oKhasi1hs7M5DYO3HftUTctkDnHpxVKTKaRBqOcgqFweozVdDv +72NEY6EobJON5J5ZenHahZFwQuB+HWtL9A8hPtJA5PfNNjuCz 8HbnjNTK7CTB7gsrYAU9896jNzuIPBbuKI7CbJILhY24VSMYGa ejMz8A9MinYbkV7gl7gAnGDkj+lSNOdm0nr+tUFyWBww3fL9R3 pryfP0AHc5qUgSJmhV4txYZB5GaryRpkfxHoMcUD6ELoUOCxyT 27UsRCEhss/rnk0xW1uID14wcccU2dCxHI5HPH8qldxrawjRvJGexFULtCWww xwcEUXAqQjddIO4HQ8fT+VdZ4elIMZ2k+oPc+teFnOsD6bh9tV LI6zVpi+hvkkfLjFeW306yXrZAxk9uPxrl4ejZyPQ4svyRJrJF MgBOQDnntVu3OLhTyMEcdM19S9j4fofW37FHi2G2u4IieAck1+ sn7KOrR3WnW/zHlQaz0OerDU+ntMcPApBJFWi/4VqWthpbj1qPPBxSHYaQAaY3WgERsM1G/A68U7jIJW46f/XqtNlhVMiTKM7bB1INVJmA78UmzWK6nv8Amlz+dR1JDd0xg0oO BU3EGeKaTQAq9KUNxTsMcOnc07NSxMM5NFAkyK7bERrhfiDKY9 OlI7CkxSPyp/4LHa2YfAMsO7Jd8V+WLktMQFIqMN8TKhG8SRGyMKxwBUokZI8D IJODkV0yVtC6aJZG2QAcHvnpVO7xIwwQB0HHWvmc1s3Y+7yODt ocd4sbdMV3FTu4FP8ADabyQflz2Ir1MsX7k+f4hf8AtTZ0Xl71 yQAccDHaqM8bKxZj83p3r0EeJErtcCEtuHH16VH5fKnaPwpJDs iZmEbBB+PFOi/eRgcgnrjuKoBt3CHIBY4B9aZaqwZgSPqBS3ViJJs0LSQ7wS2Tj t2q/DOBE2DwBgCi+tjRAl2EOM89OelQpOJGYkrk9sYFFgY2eQSsQwy p6HNVmjCSEnJ984pia1JFlEakvgnjjNPW5BjYEg55z60DKYywb bgjPU0yGJ2GNp68HNVEZIVVCq447ntUF/Ejx5GQMjnFG5KK1xGUQIMc9KhnBMWMA/Sk0TKwQt5UeCGyT+dW4FxhvX1peY33JFheNgdxII5yetPulYL8 2OF6il5hFXKdzITBzuyveqxuMAEsqnr1qlsNjrfWDbr9/nPT1/GtnTdVDR7mZ+QBiokJuyLsXlyShs+vANDmJnyucgZx60LUadxG uir7c4Y46HpTbm6ZYyw3Djn3pNFNWKCzMJD1GfQVPaFnQgEZ9B RJK9wHSwtKgGMAn06Ve01hGBwQQPXrRew27Iju1D3ClRk9z70q 7wvzHAPJpJrqT5iG4yQqrj3H86gmP7/cAAT3NJ6M1hbUfNMPs+2Tj1pNInUuwbC/7JppX1MnuJLskvCF7e/eoNZ09fJBxn8qp6Dt1IooDDagqSMDrnFRw3SSkBhkkdCf8+1Sx smjYSS/LwPSiZHRQUPGeeaUl7yFDzJUk/c4UckZ+tLZfNCwY4H86TQ5agziPB53Y47f561O10yRDccc4PtT SBqw6Ft1qeQCTkCkyVTPfGMUuazCFkiBbnbGVwc9Mmltrxt4yR g8H1q+XRgSJN82M8FuAfSrMhDBdxCtjpU30FEcJ2WA8HOOcU61 vgEycMSeaSWo3rqF0FlUheo461n3gKMSOO2c9RWl0FtSC5uf3g U/PxyO1V4wEb+eelMGtRWYAcNgY6gcio3nDocdM8c1PmJqwxJlDE 4yPc0sSM+Rtzg8DHWrvoTcfcZSAhckk857VXWMlsBjt6HAqNh3 JljZCNxO4HJ+lPWYtuxkED5aZNuoLCZZw3BPI5HeiRA+RnBHTJ 6/X9Ka3KVyxaxAxZbGQOh61G1rmUHJCjr3BoHcekZ2hVwFzk06NC WOcnvn1pPVk9SvLaMJW2kc54IqGcGFWwMHOPxqjRldH23AxjdV oJ8gUcE9/rUyIaaGlgMjv0OTms7UegC7vf1/GpekinsUrUmSfcee5rrNEZt6A5/+tXiZz8CPqeHLc2p1eoYGhvzxjNeYX8Wbk/Kchs89BXPw878x1cVtuER8DfJuXkY65/z61YhkzIMkEDqP8/jX09j4hH0X+x/o9zda3FLGzMm4ZHr3r9ZP2SrueKK2SQEAAZ4rLW5jOV3ofZXh5 2k02PIwMVcYgDnk1qloOOw1m69KYx70FIbuKnjpTXJHpihFWGP kHpUReqERTMCO1VZySDzQiHuUrgYByRmqFyuAT+tDLi9D6BU0v NZvcT3EzgUvXNILiA4pR81CQIUDIGaQ8HPShidx6nAozzSHYcG pM+1AMhvTiI9K89+JVxs0ybnsaT2IlufkN/wWR1ciwjj3A/vemfrX5wzy4kJwo6kEVjhb80r/ANaGkH7iGwTFXAPK47cVI0oDYJAbPQ12TjoOG9iaQIkQOcY5zi oXjLq3Iz2Ir5bMZuLbP0TIklG5xXinaNQBxlc9Qau6CqmRTgAH 3r2csb9grny2ff7y0zoFjDqSRgY6d6zblDCTjAB7+ld63PGiUS hJCn5TuxkCpon/AHgHOemRTe42tSwIQ6ZICnpz1NLFBmRPlyPc96kljLqLdIGGM1 VlVopN3fOMU0UTwFiBllILdM81ciuGVDjbt6UArjGnVF3Ocgjo O1QpcZwvO3HJxQkyXe5L9oAx1b2Pp9aR5cjp3607FXuVkRmZuT tIwc0RybDtYsR2JHeoluK2pMkf7s5PfrV20twFJBU4HQDpVNjb KlxafvlxnJ5UDvTHh2x5HOOOKa7il5ESWal8swUYyBVUwlZDsb gk8EU22S0NmT92RnBzg+1OsVaNhk5wOuelSPVo0rWbe4DDOB+N O1U4gOQKkqKsZN+4QcHB/OsyacyDIHXtVEuOtyETqdpZeQe/FatrPtKlSSO9JrQmezNCC4Ma5U5Pb1qxHdkNk5J7c0lsUmkhJx vGSCCeOKcznYD/AA/560ilqyvNMJ0Crx607T7coSCWA680720Gt7F+Bi8G4N9Mipocx sA+SMelQJrUjnBS5A4I7YNSy3A8nB4A7D1qk+odbECgSEcYJHU 1HNvWYfxeoIpW6jQ+Z48FevA6HmqER2TO0bbCf5UA9GQic2sm0 sDk96fe6gblkUkkdME03dspEikyRBQwYMOn9Kq2yqCSvAz0xSb ZBbjUtKuNoXP0qa7JY4bnuKizvcSWpNDapJAGzuGPoafFbhT1A J9KfMy1EoSkR3GM/N1FTTT5hBB/Tg0+bUNhkU524BHA61dRS0eSenaoekriciHOeMqR7moQm0HA59 a1B6MekuHALAVYaY7gflPAxj+VJO24nvoK9wdpGDj3NV4rja23 n398UeZSV1YuySgpk4/OqF1NuQMFzg55HFMgpT3GJNvU47jmplkWT7pO/wB+KooJlUIV2gAenUmq2wZVByPWpVyV5jEXa23jIPIq1aRh298 4xniqGhJk8pAM8nlqreYN6fKMfXFLrYEyzHKZGDEYp8iAEbWQD tx1pPcCuwYOCCQDxn1/zmlclThhwR69fSquDZes909sMgDH4ZpgcCUjlUzmpV9hLQlZtn I7/rRCvlIDkZU9KGNpEU8gL4+UFT82e9V7iJXlZs5PXFUirNoqiP8 Af5GMkZwTU5w4J547A0uhJXZ2UMVBAX+IdKo3WGXrgnqQOtNLQ roVYJUgu1JypA4wOnvXWaDMpK8g4PXHX614Wdv92fT8OL32jqt QI/sIkDkrXmeoALcOF4Gc4bmuLh6Wsj0OLfhiCgxx8japHOOKUs/mKVOB+Wa+rufCn1f+w3cBdQiU5zuGeK/WX9lWKOe2gOBnAxWakcrVm2fWWmECzQdBipWODnj0rVPQ0i9Bj HPv60xm5wM1LZSGM1IWIAIFESrkZbPXPFRO/NXaxLZBJJg9zVaeYnODQmJtFG4nyOQDWfdTbR3waGVFH0Mh3HN OHQVDAMYoz60mK2oYz3NCnHGaA6jloIyPapEtBQSKM0xi5ozik SVtRk2xGvNfinP/AMSyXkDilLYUkfjb/wAFh9RaXW7WEMP9YSc/Svz/AJ2cEqoAb1PSowi+L+uhol7qBXYFuwHp0NShg7cncfQjpXS3oX AvwRtJBjlj7Clax2ozEZOM18jms2mfo2QxvTSOC8ZQeXfPzjL8 EdcVY8O4CJkkn0PavdyuXNQR8nn6ti5HR27mSNsZwB1POar3Kr KcDBxz6V33PGjsZ9xGUbPAPfnrTIo2jzuUketPoLoTRRgxYO8D Hbk06NNoGPz680DT0JIxuUOcLxis69m3MTjJHcf1oB7EllKJEX uMZIFTxkvEVAyB7YNMCO4mIZfwz7dfzpiyOHA/vdMUmDeg+cvuwRlSM5xxTQ2VBUEg8YzwKCW7kqRsu3OM9qbIjL hiAMHgdaTLQ6KQqozzWjYgeTg7VJ4OKGRK9wkjWPPUMP4gKjaP cwwCe+SaaLsUbm2JJKgYP5VAd0ZI2jI4qovTUNCFcyS5U7j3zV i1iJfLKSpHIqOgrF63tfugBQehyOtLrMIEAwpbnPHGaSfQcWjG uLZihJLY7kH/AD6VmzgQoOuBmrIkZ80pZwBuGfUdauWEZGRnH1B5okrC5rmkkv lRZOMdD7VM96Y8A4AGMZNZ7g9SZrwswXO0jHpxT7iUgZQ9T+FC 1ZSYRw4XzBwQat2iNcy4YHpyM9aOoJ9S5NCkMJAIOF4JpuXYKS Aue2eBUSemholqQXUuSGPHbIpcCO1T0JycVaVibaj4ZF8lwFAP rjtUFw587DD8AaXWw9LDWTMZZT2wcciqb/KzKvXoDzzVp3QivNCCwJ79cih8bVJycg5GKhsOhPZSN5a4wOOc 0ltbgtuJwM5wBS5tRFlHHmqvVe/rVwvsi4YD0NDTuPrcmEQktwwz746UW6kMSANw9aT2LUkjIuSWn JIB5xnFJPI2QxXjsBzmnGI5xGRTtuIOCCOoFaCviInr/dHrVSV0ZWvoisJt5UDIKnOTQ9wFViPn9eaOa2gX6CwtufAOF7H FWvMyQAOKT1GnZCXdztBCnnucdarRS5HU4HHFJPTUqyuaUThoh 0Ixgj3qCcqkHyk53dB+tUlclsoSQKsp3ZBxg8UvOV5yc561TBD Z8tk5AbP5Uixk7OADnoRipctSdb2EigDXB3D8B2qzsAwqMFHc5 zTsNDHIL5bGO2KjhUTOerDPpxUx1DZkj2zoBjn0Ipp3E4Iwew9 avzACcs2flYZ6moCDuBUkfSi4JGhbysIehyw5HpVeUnzO7euaS BbCG5KqMNz61O87RO3OWPTvQxshmGXU5GT61FcZQZYHBHrRHaw RlbQqxSDzOhC8gdKmkn4yNuB2HWjYbRB5gPPUccZqlfuVdmDDy 8Yyf8/WntuS7p2M8zg3BPLDI685rodDvzFJknIPO48Zrw84SdPU+kyFy 9podel55mkkEnGO/auC1BMXjHG4g/lXBkLSqNHrcVRbpRYgOfp7dqZ5485fmLH34r6xHwtup9J/sUeIRba5EjDHIB54r9cf2SNUSa3gA6cc+tZdTlqK0vU+wdGkEl in0FWSoPetUykxpGTwKjcAsfak0WtyNiTwKRjREroRuwPaoZXx nPBqyWirLIFFVZ5cMaGiLXZRubjcazb18g5ot1NU9bH0ahx2p+ 6obJYGgnjvQhiA0vXpRYBytwKXdmpdgAnI6UA0iWIRg8UKTjnr QFirqbYiNeVfGGcx6XL245pS2Jkz8UP+CtOttd/EW3hJJUEk4PSvi25iCuCSQvU80YW1r+ZTbjFELn92TzgnjIPrU sERBBP4itpmsHc3NMQPZknkgdeoNXrGz8+NwMMfevis0b5mj9N yCn+7Vjz34iWZtr3aVyG9OD0qroJAt92MHqCRnNfQZK19WR8Zx GnHFs3beRY4NwGQenrUfMoLEkKPxFeo0eLTdiMbCxLBmPq3agR jcAASQOQx/Sp1HbWxHNEVxxg5+bnkVNYqJMnaTTE0yNiFBPUdTjiqFzEzK25 cgnODzTWo2QLctFGVwSQSM1Y+3rE3fjHFDWhDWthLqQTSZzz6+ tPt3EgAA5PfPAphKVixLIIwAckn72KZuCQEYPqMUPcrzGBpFkG dvr9KCPNPBAB7+lHQfQfKzRE5IJA496msLtyVGCFx+dJiuWGlG Q2AeMc09ZsEhecDr2FSxkM86+UAi57YBqtIqPHnow96bE22MSK MuCCMgZ/Gp7eIxOecH86la6MLmhbhFXAAU5703VlJg+XsOMnNNR1KitTn7 mcLldwGeeDjisvUZBOcLtIzyGzxVEysimJEyevU8k9T7VNbXoJ zglvp09qrqZxehoR3AKjo3GfqaQy+bOqleKjzHcsrH5jkKORj0 5FW4AzqV2nA6E96FqrlRLcEYSNQBnBye1W4P3bL8qAjOfasU02 7grMfI6+WwLA+4p4uIxF1LccU4rSxUd9CtcIgfggt2HIpl0wEI AAyo6AVSG9xLNhGmWXbgdKZexsZdwHB6DqDSl3Jae5VkJjt/m5BHp3qnHcZbALDnNVYroRNKTnJBHapmjGzPLEGpaEy1YQhgOm B3FMEJWVnwAT1pRsJE6Qnz87ck+p6VK8bMBx6ZPTiqb6lJXLsL boDjC44470rxbfugke1Zz1ZLRkzkG5YFTxzwBROojGDhl6g4x6 Vql0KuQxlWQcfge1Wo33Q8gKf0pSuJqxSuJdpOWC/j1qOabZEo65GMijluLqOtJMNg4ZepHSr9vcBnCnoTnI7009Bx2 LgQOQ2MJ14aqtwhBABA59OaiOr1HoWMlIgOSvck0x1D9VOOpNW N7Iz5gCjE8j2pkIw6spI7fT8ardEkjgOnypyOtR7CGyDk/wjuDSG2LGCh3DJY9AT0qyylOFB+bkEHt/nNT1ItqQXc5VQpK4HAJ7UWku1M5yAOcd6a0G2+pdS8UoOd2OlN eQSAMpAz+dNgiNsO2NxHqDxim+TvIwG29qUdEVcs2jiCNgRkno SORVaeMBySck9KSWoJX1Ks0m25jwq4HqcChpHacsW3DPGe5q7o LiGZ7icHjPfPQ0sjruHyqcjqOBU8tgdr3IoxvdiCMDp70TNnop z3PcVN3sJye5HGBtxjDHrnpVG/tzGp252/nVpsvmMuRHhlLYJOSOOK29HJfYVYj+teRm0LwPcyOTVU7SzDHT wAh4GRzXH61GYr2Q8FScGvKyRWrNnvcSXVBditJyoA3AEcnPNQ K6mYBQQM4yODX1yPgZn0L+x0I5PEMWXUNuA6da/WP8AZIldFtwCCOMGsZJ3OeqnzI+2fC7E6ZF34rSTit7jjoIXAw OtRyc0mtS0RFvSmswJOMU0luCbIJJOM5Gagkk9xVMTZUuGzjHJ 7VUncscUhx0RTus4ySMCs66JBPemiup9Io/FOzWLJYgfNG/B+tNOwwMlOWXLdKQmPBoxRYGhQcnnml25oYB36UmcUXF0KWrPi E15F8Z5tukTHP8ACamWxDPxB/4Kn6mknxcCYBIDY9q+SLhfOYKcDjkEVGE0i/Vm0YWikyBwVUgNnA/SlW5LRYJwT056V0vYuCszqPD0YmtAF2gL1rf0qBEJG3n0Ar4jO nabP03hz+Gmjzj4v2Zgv1YgDPWsHR5laHa3yg55PINe9kk08Kj 5biqFsWzViYSRNkkDsakt5S8TcHHqTXsHzMSAkhxkHB9KvWnMA yN2Bmkirt6DblFYEk46YphjMMTbTgdhmh9gRA9viPad3PU96py RskbqByRye1CQPcgMLRqOCWxnrVTexnLHKnPUjrxTtoSmwVmEu AcE9M1ctZRuGAq+pFBK31NGKyzJk5OOMgUSWuQPlz14pN6mjKT REsSVI78800NtbaQcDuO1NAWHUyruPRcAZFTQqqIDgkY5xQwZK VAizgZJOeabGVaIZLAZzyamLFFoa6iSMnjjkE/nUbxZRTgmqGRRw75vmH9KtW67HOSAe4NJolxd7lmKRgRuUsD6d 6NRYrYc5LYyKTKb0OZuS0gfBxz0IrLvBIYwQOemc1VtBWuijOh jI3NyPXqKs2cwd/LGSc5qk7Gb0uacLGJWyuTnI6E0QnywzFUfPU7ePWskhUySC4Du cg9RwBWnazbFJwQR3z1p20NVqWHvltYTltvy8571WfxBHuIWQA 7ec1lLSw0tBTq2YxgkgkZBPBrVgukNrjHrx6f54qktbiTsQea7 TKF4UdyajvHVWGSRx+FO7Y+bWwyylLs2SikfrUrMfm+6COmD2q raFWsrEdwQ8LLkfd69qzJV2TcH6gc1KRFhY4i7EkgZ96unbGoL Abceue1O99BpkloigbuV+XgelQmYKx5yOvqaElaxSemhahdJJN 3I45GeRT570bRjGM4zipkiVLqOQq6qwJBHbNSRsxjPzc7ThmpP zKtqUinmXDEt0HAx0FV7kszHO4jg1othNWZFhYN2GwfrzT0f5f lJZh0J6VMmOKuVLmQOx4Xrz3B+tLDLg7to2gYIAxiq6Cmie2Hl yYGBzkc1ZEJkPDDnqQahuwIvoMAZ4HX1x+FRXUYc55zUqQ35il TEpLEEdh6VBJcr5Z5xntnpV7sNkZ0rF5B6jJPPFPify5DkgL+e aoVyaVCQOSST0HBNPLkoHAGD7076Bci3l+Tgkc+tTRyHAJw3p7 1KBrUZK6yJgghuecUy1jBHB5PTtQkAeavnkA5AHXPSpW65zlu9 F3YlX3HRdPXJ7VItwqgbCM9MZpyRSZJHN+6IA47+tVHmcsSmOe oNJaB0I5ExKpYZP8qa8+JBvIxn5cCkkJIiLgyc5I6Z6im3Z3Ig A4xyOxqtx3IIS4mIfIIPQVPMAw4+bnpTHdWGwxhXYnbknPTrTb oAqR6nFQ5W0Eo9CjLaiSQAKDnoK09JsHlUHABDZyO9eVmtSKp2 PoMkpSdS532leGJI9I37WAAz061574nYDUmU8KG5Irw8iq81Zs +i4lpNYRN9yi+CATyyn8+ajjVhnb8ua+1Wx+fNaHv37H1ks2vR fMdufvL1r9Xv2SongjtQp44x2rFM5Kjsz7e8Kuf7Ki3Z5XmtQN xxWqLjsNLfpTXbA5NUhshZ+tQzS7cZ4NOwosgklycciq88uR1/ClcRWlckk9KgmfdnBGKVy4oq3B3ZHQdazLpsHg9atMSep9Hhsd 6dvwOvFZsGwEmO4pc5pILiupKnrTUbAFJivoSBsYp4bJxxTRQo OKXdzTaE1oJuoyDUpCRQ1g4hNeO/G4bdGnIyPlNRPZkSPwt/4KXXP2n42TbjkLmvmC8IkAJ69getRg1+7fqyoN8qRT88OznIz6 AdBSRDb1Ybj2rsbNuY6jwrdZTDA/nXXaSFF0m3HPHBr4XiGld3R+m8OTXs42OR+OOlhgkqqCfrxXnW iFiNpUBi2Aa9fhqNsNqfPcXwti7+RsF2iYqAWPTOOKni3sAcbS eozXvs+SQyeUblHygrVi2Xgnlc9QKZZZSFWToeeuD0qK+uQiKO +Km2ohkblow7E57CqssAl43MRnjJqihJ7DOPlyMVlXVuyzblVM D2oTE0RwqZ5AcY44Ga07OAjkgEdu2Kb3JsadqhVSGVMmlWM+V1 4H5ms3uDRXvI2QDj5PzqmEUSkLkj9atdh6E0sRQZzgdyaSxfz5 eF46HFAImuZgilFyQexqFWO4N938KSQWHjLzE9eeKMnywe+aLh cRPmyBuzng1NBH5ZGD+FF+gXLCoBgjLccZqPWB5tuFG7BA4pW1 GlcwbqJ5AQxxn1OOlZerL5AwCMjpV9LEmRIfPmAYAexPIqeOSO 3xkgk+/Whsm3U1LErLEdxGfXrxzViK2lPyqAy9qmSsZp22FMf2WQKSWJO c4qcXHlqeckjg+lKOxrFFDV9Rb7NuGfQ89a5O81yW0RiSMFuoo dkWi1oXiZr14yzE475r0bw2qz24ZnBbHrWauZvcklAWZlG7PTI 6Cq14nl8EA5GM5q9C99SrbsVkBGRg4PNWpWDAHOOcH/AD+NPdiV+ok4PlnEg6jv/n/IqkivvPy4HUH1oTQyWzw4ba2CDV0xiKJSOvrSk7E3sxiyFTIAT nHY1TlZYp8c5xQloW7Fu0bJVgBwOlPvI/3QVeOQTih7gyMSNChPWnQXzPFjIxj06VnJ2kOTJIJVVskjIH51 Xu5OclSCBjPvVRYIzppVeH75APAIp8UwSFfmJwOauQkyJ1yOAT ntmjz8MSww2PXioWxKY+xc78jnHBHpVuKQPLgYH0GKUh3szQVz GiDjk96cB+8ycjJycCqUkUtQkjEgK5yM4FUL0lYycZIXnIxTW5 KZQkk8yTqwJ9qbDIQVYkkelO9gTtoTpfnzQHPAHWrX2oNajBz7 elZvayG9dhkKs+flJB6Y45pyOGkGVAYdapsWyI7lxvLAHBOBil iwCpVuB15zir6DsIg8xiTjPbHWnuSoByADwOKiTsS7jZLkRAcg hRxioZb2MJjI9KHPQGx0N/uIKhgT260+R2ccDvTuW7EE93tKqQdw5qKZmlYbckAetOySFdjF f58gqDn1p0sxiDZPTGP9qluSkJY3AaU4+bdwatTIDggBSO1D0K RFGOSeuBj61HcSN5pGSP64pSVy0m0avhLwxc69dLsRmXPYepr1 3wP8D7q9vYt0JAzyCtfGcSYuMNFuff8AC+Dk4XaPRviX8P4fCf gQDaFmIPO3OBivkjxVLjVpNp/irzuEqjlXdz0uMKfJgY3KbjDdx8vPNMVWDk84Bx0r9HvY/K7n0F+xzfxx67Ej92GT+NfrB+yM6Sx22wg9Kx9DCrqfbPhwAaV EOo21eye3pW/QIPQaWKrgDmmSN6Y/GrWo2RSN7nH0qCVsqeaGrohFeU4GM/UGq8hLZGagSIJGOOtVZpNnrxVJGjlYrSybhzjFZ91JgnvzRYmP xXPo8P8ASnbxjvUSHIQtnGKVOW5pdQ1JgMionJXIoY7Cxy5GKl VsipGP3UmabE0AOO9APX1o6C6FHWBmE15B8aIy+h3PU/KaiWxDZ+EH/BSaCSH42XTM2Bg/jya+YrxwjsPmHzAjPSpwPwad3+ZqknFMqyORIPUdz0phkYOM8N 7V2WSVyraG74WvTHOCcbfau803PmRyLux+Yr47iGDtdH6BwvV5 opdhnxJ0YatoZfAGF59q8isbLyZ2VWxjitOGa/NBxM+MqTcozNdbA+XliSPrUnl5i53YHTFfUNnwqZHbwgljjLA5 zT0Uom/Ofx6mgbLYUvGB8uPQCq95b/L0yemaVxMoysUbGeh6USysHznijzHsWEm8xMkfgarSxoIwGVfx 7UJBuPi0mGVeDtA6H1q1a6C1uMhlPAxxzTuC2LKWjIduNwqORG ifAHf8BSuAXCeZtyQAPSsy4RBcHJxn0oXxDSW7Fud0jgghsDse lSWYy/AB/DimxJDrhTIc9TnqOwqGVduMZxj+GpsKwLnZk9MUNKzDAwRx9Kb QBEhbgH5RzVyzVfmyWGDzgU33E0TAbzhVAGeCe1RamViUZ5z0q W9RtMwb27K7vlyM8cfyrF1EiaMMwbPQVQntYzJTsk24JOKrQr9 onyTjHajW5nJu9ka9tIWB5Jz0Iq3bX7wgKNrc0nsJaFpGeZhIR kdCOlWJID5OcLz1JpXtoaX1MXxDZyNE3AOegrhtY0+d7j5ywX+ Ln9KpFJ2NDwxYyW7gL90EZz6V6T4ddorYjHIqL9iLX2NJJFUjG 488jtVbU5t8id88/Wps76jVzOlmxIAc8tk1P5yyW4dS2O2TVopklu5YknG0dDTGKyz YGMjvmkn1JjJNXJo0Qxs3O7OOKSVX2nJIHTFPlGxtvLtz2PQ1R uJgZyMnr19aFoMsxXbRyIy8fTv/AJ4qZ9TOApOfXnmluxXGzzxxR7c49c9qdYhY8MScVMnqVJ9BBK GkJLZXPH1/zmm3Dgnj6Zpq4LQqTAPEq5x2qEjycgYzjHJ61bDSwgdmUZ4JHH 0qH5s5I6nPHc0o2sSy1p6/MxJDDv8A5+lXLaFmlHPfjjpSauFi3M/lYyoDZ4GalR8jJYfQ0cpV2mSSOBHnP3eCDWdqEixjdhff/wCvTQ1qZxgd2DZzu59Kl+zbGDEsO1NoUmSpbrnAw2fartvpck4 UKgNZRVndgrI2rDw1IYGLKR3BrNm0ZoLliQetOSuNK+hTntmhO ACD29qba2DzP0yT2qk9BuOuhfXRiQR3z24NQ3mjtuYopznA54q LpuxXs+hnT6RLCmQCfX/P51jXmmXnmHGQM9zmi2onH3Tb0XRJmij3Ak4HQVsJoB+VjnPYU 3a9yYwbKGp6Q0U6gIQOv1rOuLWQM2A2B3zV8ytqVyMjWylaXDD AHpUrWUkUYymOcYqFUHGjIhs7RoudrAZ5INXJYmkxlSOORU85a pNMbb2UhhxyOf0q3pXhebU7mMYIHTBHNY4jExhFtnXhcLKc0j6 q/Zj+C1hLbrJcqvmYBUV9J+E/glE77rdVfYOcDvX5PneJnVl7u5+w5LhlSp7Hm37b/g+P4deBTc3EiiWRcKncfhX54X16LjVnYhSC/HtXv8GUWqknLojwOOq98NBdx5GHbacDqcjtUJ+8ACcnoT61+ib n5Sz6O/Y58NJqeoxSMNp3DHtX6n/sneH5rRrYRucAis476GEpdD7Y8NxNFpsW/rtrR4I61shx2GsOPaoWbBq4ldBjnCnNV5WIyCaZEiCTkGqspwe tSECCR9vsPaqk8o/HvRE0exRnnCKeO9UZ58g9+asmOx9Jq+acGzioYMF6ipIzikMmX 7tRT/K/SpkAyFv3pHTNTx8jFCBMcOO9Lu9cUNivqJ0oJqRlXUVzC1eWfF u183SZxgfdNKexEj8Nv+CqWgtpfxWkuCnyEsAa+PLmQtM3JJHP JqMv/h6FJ2ihjlp1blSR1zSQxNcMCDnnoe1drSZXMWdIP2a7Ug89hmv T/BsY1K1H8Qx618zxDTbp3PsOFa3LNwOrXw417p7RsMk9CRXkfjr wBLoerO2z92Tn0r5rIcUqeJtfc+s4kwntsNfqZrrILQqUIwB1p bFVcZAHI6DrX6JdNH5VyOOjI3snglIDDGef/wBdTPb7CnzAZH4U27olK5NJGgjB3HBOQMdKp6lKY3whXGcDnvR dDRl3MrBmyqnI6k1EGbcxAIPXJ6UySwkrbBjLHPIBzTX3Sk4Vl 5xz2qGtbj6E1sDGwK45HX0q1HdSW+5zkLjjB6VKumJFy2vmkiA OcAY4qvdy+Z90gHvVXGmUVuNwZcOR2zVa7AE3LFuwBFWF9BZEB VecHtg1NYMShyR+ND1Em7kshZgD1brVeZi8g4xgc4GKQw2F3di eCO1MSMphiDz69KdxbiQOYdxfPU9sVbtmO89Dzk56UMCdQQTls Hvg0zUgXi4OWxx/n8qQzFntldMdW/vCsTV1KYOcnr1pol7mHNcbXbcSAO9MgKmT5TnJ4H86YuXW5tWt qSMqRyOAavApFgleCMgdP89amTsLmXQs2n+k8hzgcj2q8m4tsw TzxxUp3KQ280prhWOQyjtWSfDUDt88fGehXmiG5S3Jbfw7HYYY Yx9Ola1iwEJXnBHbv+FJ3sQtCSMsk4G1hgc+9V7+V2lUNkgcjF Jp2BJ8pQuJA8xOTjjr3HtTnm3Ns+YL1wOaq5TuS28hm2A5YdMg 1KIwJcYxz/nFNK2gkg3mOQgnb9RUvRF/iB6+9C1GiKUYbbnaxHTsazpcxy5GevIXvUxTsLYswTsFDEAHHb tTmlDuTjOO5pLexTKkpPnkHkE9Aalg8wttRmAPrVCHfOshZgDt 5z3qVZvO5yw7n2pX7AmMjt96E5GD0Umq88ZUc5de9JPQTEibci gDAxjr1FIrgT55XsOe9PlTDcns4mJyOSTk1dssjk7h+NNj6FmZ wxxnn3AqOVtqEjBBFCH0GiVjHkkYx6+1QXk22P1H8uKad2O3Yl sIRMoPRs9fQVp2nhWbUMeWpc454obsRG7NzSPAJDAMh357969H 8J/B9dQhDKgGfXtXPUqJK7NVDqdC/wCz/eC3LBX245wOgridY+El7bXzo0TY+nFcjxUea5rGi5uyMS7+Gks 9wVMeBVqy+FslswPlOx6/drlq5kraHsUMrbjqT/8ACs7p3z5TYPrxUN/8P5oEVGiOBzwtRDHp6jqZfyyEsvAjvIplhwAcc8f5610+k/BG31gLmNTnkcV6NPFRkkzkrYKUZXtodppv7KKT225VYZ6YFZHi L9m+fTJSyozKD2zWeIq8rudGFwlzznxT8N5rC7KbGAHBzWOngN mA2qx+orzJ5nd2PWhk99bD7b4dOVJZCQB0AqLUvBDeUFWIqe+R S/tGNtzop5Pd81ijF4KZGOIm+pFPXwW7fejZh06dKmWaRte5ispb lsW7Twa2AuzH4YrqfC3hPyZlYxceuK8bH5nzK1z3svydL3mj13 wXr0ukMgQmML1IPSvWfDv7TVt8PdJ82edG2AlQTXw+Jc5VOaJ9/haUVFRPkL9s/wDa2vfjd4gcmdjbRghE6gV4Bp8oeTcfmfqM1+rcNYV0sNzSWrP yTjXHqrXVKO0S/buxhPJPPPHX6UtvDJNdKigEZ55r6CV7HwrR9g/sVaGS1vKqjBwSOtfqT+yZpBEUHy+lTCNonLOPU+sbQFbdQfTpU ofA610pGq2Gs2Qe9Rs/OQKdgbIpWIGBVWY4Ynt25oWxDdyvLIQevNQO5yO9JIcSpcNjPP aqNzPuzz9DTRUmZ9xcHPtVC6uSAcCmOOh9O7uB2oLlTgVD3J6j 4slcmpY+gNBTJ1PAFMlXIBxUbiRGQA6nPGamGPWgdhc0ueaYxG bp6U0uCalE3IL3mEivNPihG0mmzKMEkYpT2Jmfjb/wV88LNFr6zBMKHPJH+fevz+uotsp+XB9c849ajBP4r9y0rwRH5 aoehGByKljj2ngHJ7V220HbUjYMpVuj5OOK7/4T+JPsl0kT4Vc45PBNebmVH2tBo9jJ6/ssTFvY+kfAnhiDX7aMxEE9wMGtDxR+zc+uQF0hDf8AAa/GqtWWHxF7n7VDDLEYY5Cf9ju5u02i35PH3eTTJv2Jbu2tnb7O4 HX7tfUUuKOVWufIYnhmMm7o5LX/ANlnUNMbKxOMdAVrltW+AeppgRwyHn04r2cLxHCa1Z4uI4ZlHY rL8ENUcACIgEdQO9Of9mvX71SYbdiB3PevSpZ5SnKyPLlkdVRc jl/FXwc1rw9IRNauhHfFcvN4evbInzUcDceor06WNpzdluedWwNSE bjbezlcj5SDnGMVPJaPuLckDsRXRKaRxqErXRas4PNUHjPfI5p 8kahNmxTk/wCcUoSISGyRtZqBGTyMYNU7pWAB6DH1q1uJdiHDbWYFTxzzVKS TORlWUcg55FUMtQFZ41Vuo61diQInO5mqb6kojuQPNALAgdOcV FcARqSAPegY2FSHBJypHT8KmSLMYUjPpmi4DVKoQA2TjpT4Its h+XZ3wTVAyYIxkORgemBUd8cRAY4zgcdKQXM6Yh1Zeo/TvWTqduJi4C81TsOdr3MS70dtjH5VGemaqW1iYZSeWycdKDNt2 Ok0azaRASBkjr/KtcaVERIrYOR35x6CstWRGLsKlh9njzsyeppbW6RAC3L55prc2 SLpZQMgjJ6DFQLAJ1DttPYZqRpBdqqwc96gt5lCOF68Y5qpPQp WIjK4nIOVGeQTS3oCoHB5780le5JntCUy2PlPT0JqzFA7SPknb j0/Q1SAWNQCMDGRweDxSzz+REozweKFsQnZD1JlbJA5Gee9TtIltB 2BPP8AkUrWVjSzZQnmEkxAZlBHJqnKFkmfB5Bx+FNvUlrQmZlO 0khcAYwaeULLkAE+xwKloSZXYlZ+oUn9KsJ8uCDkY7dKdx7Ekb LMG2kMvbIwabcKFALN9amKZLWoWY2TNhgQPUdOamuof3eCcd+K L2VjSSSVyBIhEMjAGPrVUxEEsRjnpjNVGNiXpoi1axuJQEGSy1 o20BLEj8QT+lSxWdia7sCxDEDJ7DvUV0MDy8KO/WmtSkitcHEeCQuD2AxUmm6Q2pvGsabiemByaAlc9L+HnwI1PXG iH2aRFY8MyHmvo7w3+ywvh3w0buaFQ+zIIHeoc7N3IUr2S6nD6 j8O1/tuaRUXbu446/hXZ+CtG/s9I8spX0r5/E45PQ92jhL2TPQrbxDAtusTqoGPzrJ1Wx03UZc/uwxPTFeNiMwUlynt5flEmzjPEehWdtcFYVTI/Gs5Ut7c/OF685rw5ZpG7R9fDJ5ezQ9tf02KQCTyt3Q4pq67ol3L87RhenO K6oY6yRy18ps0OuTpF/GFgaHdjHGK2PCdhb2EisMYGNtdlDMJRkctbBq3Kz13wlqlrJaK HKg46VPrUGn3MblwmMd69DFYuUqdx4LBwTPH/iBZaI9+VLIOeegrD07TPD8Wd8kOT618VWr1PaWPrKOBThZGhHo GgyJujaInqKy/Euh6FZovEPmdqcvbRXMtyaPLCpZHNznRIN5/dgZHFU577R4kPzQk/SsVVqW1OlYWlKXMZ9x4o0i243xKAe1Ubr4pWFmh2bT2HNJwnPV Gl6NNWuc9rXx3EGREwQnPQ15r44+NFzqLFDcuQeMBute/luUOc48yPn82z9UabUThTeSajcl3yQTwe4rQt0FpF8u3JHOe1f pVGmoQ5T8fxuJdao5vqSLeFz0LDPAxwKveG1M+rxKocgsOBWsn aJzX0Pvz9jHw8sFjbEKc8Z4r9O/2XNFC2cLbMcelRHVnHKWh9BDhQKUt7810GsdEMZ9vrUUkuAcdf pSbsJsheYEdeMVXllyTmjoJFWaTk9/wqvJIScE8U+lyrFWeQgYrPu5PpimgfczLqQA81nXc2QMfnTsPq fU4biggnpWYmPiyRz0qwnA4oHsSBqdncpqbj6kMkWc4qRDuAz1 pCuKc56UFsD3obGIX/GmscUhdSOf5kOa4Tx5a+ZC46qB0pNXIkflj/wAFiPCu/QGuAvI5yBX5bXsC73zlm5xjrWGBdnIuGtNFPl+Hxu7cZpfIOTn OeufevRZTloRzyMI+W2ueg9Kfa3cmmSpIGIkzUtK1maQbi0z27 4C/tE/8I9fQxXT5TjPp1r7w+Bnj/QvH9nEFngdj2zX5FxdlMoTc47H7ZwnmSxGHSe6ParP4JQ6zbrL ZiJuOMc1na58DNbSIrFZ+YPUCvzf284O0j621BvllozgfEvwX1 i3lYTabJ3/hrl5PhS8M2yXTmXPXMddlHNFy8pEsuhPZ3O18Cfs86ZrADzWSZ PYx12rfAPQdCt2L2MAAHUrX1eWV48ntWzwcfhJRk6cUeIftD/CvQpVLRWceSedor5e+Knwt0yGx2RwhJC2AB1r6DCY5e3ckz57G Zco01GS3PPZfhAAoZUBHYCm3PwojaM70ySOoHSvZr5xeSseBSy ZW2Ob1T4d/YWKoPfiuf1DQ3EnIBI5x0r28Divao8HMcA6Luinc6a7jOxgM9h UEzk5Qx8/7vTivTvc8aSsVAoRmRhhcckms+WBC4IX5TVJgloLDblZBt6Z7G tSCAbckjjgdqlu7FoVdQcBsjHHbNU55MYP3ieAM1Udh21LljEJ k+UE1ftdOdyDtGeny02GhLJ4flRgdo/LpTL7SJbWNWwRnHrU8yY2tSFEa3bnp3BqO/UGJgmRnpV21JtqU5IY3Ug7SfTGKqyQCOPGWXnpmgTZTe2MrsCj nJzjtUb6ED8+0nj0pSfYFsWLS2MMYX5lwfSrlsPLclmI/rUvQFoy1cTBItpIAPWq1okLOSSoA5pRVgtYkeXbgIf8AdOcf57 02N8ocsD+lOwLVle5uNjHeR6Co7eXLjPyg8896m+oXsOuFNxMu VwCBzTp7RmiC8ZzwT6VT1DfYlW1L4ORwM4BpqWbXLKEULt5Dc0 ctykRSwfZ2KyHABzkHFPmRZZNx+YdxVEsgFu4YsBuXP40k+AAR nHck1JV30M67zAWww29aq2jO8rMQufXsP8+lNaMVtC3Fc7yoOM r1wODVgDEZbBH0qJNpkvSVisw/en7h59OlTBFn5LN15+tWymWo4iUBX5ueM09YQ6MWHGccflWd2T cS3jSKVhuwCfWpLggxFRjpxnqabV3cu72ERSgAOAcZAxmqbqDI +GbryQOKfUlJIs2rNGx3BQB0wauWZKsoOceuOaGveK5rKxclZZ I9oPPXmoJ4vMjOcA4456076CSe5mXTFsr8pxx0r3f9kDwHp/izXALopgMPvY4qkk9zOq3y6H378PvgzpcNrDHBDCRkDBHP4V32 ufsv6l4k0DO8Q22CdhON341lXoOrojHC1/ZtNnyh8a/A1v4S8Vy2kF0nycuu7O0+ma4S98Tx6HFuM6n8c5r4fMsPKM5JH 6Dl9WFSmrrUyLv4x2wwTKuf4RnFZM3xrtIXLi4A9Rmvl8TSm3Z n6DlMKKjdnM+JP2lbWyD+VIhOOzZPSvO/FH7UMlyWWJiAO4PWrwWTzmr2OnGZzRoQaRx2oftD3dzcNiRgc9 Q1Z83x2u5H4nkjyeM19XQyG1tD4bE8SQVa6Nrwn8bL6W9Um4fb 3x0r3b4YfE+51UxRu5ORwSa66WSKLODG8RKWx754d8RBdIVicE Lzg1yXxB+I1xZW0pE2FA/vdK7K2XKUOWxw4HO2mfKfxR/aEuIdZlhS4Zjk8bun41wNx8f9Ra4ZVupdoPI3V5dPI1Nts+g/1plHRMv6Z+1LqOlA/v5G/wCBUah+1TdX53ySuXPGM9K66WSrlscNXia5np8fZtTyWldO55w Kral8Z5/Kby5nz2JPNOeQ0pK1iKfE9S2phz/F28nlGJZPxOajPxLvLkZDN6ZPUmtqOSwhE46vEc3fsNbxFeak4 wzYPOeQDV+xsJJWBkUv3+tevSwsadrHz2Jx86u5s2mnLbcnaD7 daSVwpw2SCPzrpijhTuiJZgw3fKAeMn/Cuv8AhLYf2n4kt1bJBYAYNKovdsRLSJ+kv7Jvhspa2oVMHjtX6 R/s9aZ9i0eNiuMADHapgtTA9V87P/1qaZeT/WuhGmyGNKD78VBLIwPb8aHawrEDy9cc1Wmm561CZSViB5wR2zU M1x144qkS3YpXEw25yaz7qcHPPSrBbFC6IYE4HSs65O1juoRof VG/BPc06OT1PFQyLWJo2+WpUOKRTJA2R1pwNAvMCu4Uze0LcgYqWA 9JA/TilLZpWBjG4prSY60MGRvl8jBxXMeMrINA3HakKWiPgf8A4Ki/DL/hJvhneyrGXKIT0r8XPE9gbbVJ43DDDEflXLhtMRJeg6bvCxiXF u0bswOcjrimpMxGTgGvTtoLyEuZtrc8rn1qIyZOfvccDvUp6Gs npYr+c9tKXV2U54wa634f/tC678N7mOW2vJlKnPDYGK8rNMBDFU2me5kmb1MFVTWx9W/Ab/gsFqng0Rw6oGmQAAkHOa+qvhz/AMFsvBeoQRrfHyyR3WvxzOuFcTSk5UldH7VgcywWPppylyyOpv v+CsXwz1uMk3MHPqKzP+G//htrFyD9rsl57kCvlnlddK7ie1RwtKCXLUTudl4M/bY+HMV0gF/YgdMCUV7t8Pvj78MfiJEkb32nOzdmlU16WVVpYeap1Y+7I4czy nEThz0ndnoF18Hfhj400h2aPTZgw6/LXzb8ef2Nfh2b95LR7VZOoRXGK/QHldD2KnT3Z8LDE4pVXCor2PkHx38JNC0Hxbc2VvPEUQ4+8OKx bj4L2OqQYikQ8cDPSvAx8KmHd0z2suUazs0cN4u/ZzuIkdomLDHavLPEHwivdLc7oiR6kV7OR5ztc8TP8q0ujA1DwP LbhfMicHHGBXPap4QdHJVeRmvv6WJUldH55iMHKKsc5deHpTLI FU7ieKrweDru4m8uGJ3c9gOorpp109DidKS3Ov0P9nzWru1jme BlRh2Sm+PvhVceD7RXmBUHseK2lGyuczqK9jz6+gk3SAKcAZOa pwxlQFIzk8Zq1saKRueGrcTFQSQM46mu68N6JBK68Ekj0yKznd FRR0s/gMyWwdVX6VzevaFJAW3oSAOpWuSM020Kadjj9S3RzMwHA96zLq UuOFBXHFdsGSmR+SJCTjgjtUMsQCjgHnj1zVlbsrwMqy4/iPHPrU0kZMhGGHPIPNJAnYktIC0gx071HcIbecqANv8AsjrU31 IurjXZZ4+nzd8ioViB3BGwh96tFAWAwoGQBwB2p0Ks0QUMNxP9 aTYkraFLUcoWY8e9Rx3mMdev61CiDSbLS3wOMDOMcH/CrKTmVewJ9KFoPqWLJyvzMCT156VdgvUSJRtAYD05HFW3YDH1m cTSkBcc/iaqSXTKcOMDtmlugbJbfUCqlGICk9zVa4l3SDhM9OlLS4nJFCZ mYgHJAOMgcUsQ3kAdTwcHn8aoTeg9oghwQEOOAehqaEsyhSyjs MDpUvUS1V2RyRh5TzgZx9aQykKTjGewPFJPoEexesp2HGBkjJG MVOkpdm4AYtg9M02htaDGXE5AAz3xUiptiPqR09aV9C09QERli OC2MfLjpVaSIRzNwPbFCeo13J7CTeyZBGenFXlCLIMgZPtVPfU jqTTsy42Mo9c1BdXBiA7jHK5qb3di1d/IzpyfLAHTqT2/Ot74efFe8+HOqw3EBYYIJ+bqc1XQl2PsP9nL/gofa2V5bJqk4jwRnf0Fe/8Ax6/4KmadpHwlmtdHuEjneI5IIPPtWNSvyxZcMOnNM/NHx7+1Vr3i3Wp5/PlAkkLZJzmuQ1j436jKCj3TE4x1rw6mDdU+jhjoU3Y52/8AipcyncZnII9ayLn4l3kowskgGBjLZ/SpjlCk9TqWfyhFqJk3mu3d2SSzqc9c1DcQ3Eo5Vs161LCRptKx 4mLzSpU1JItBe4YKclQetWE8NtI25QQgbt2rtSszypzbdzofDG iC3kTKjbjivdPg3p2+dGVsc8c9MU1FXJ9o2j2a/wDFK6JpShphkjgV5H8WfiMZtPlBbIweM0nFIum+XU+Y/Eds2r6lLKxBOTg1nv4aaQPwMtxxShFalSqXKl74ZkiTAOSegql LohhcFlxzjNWl2M3IYujSpgncM+o5FWYdHknJ8z5l74H9aOXQH J7Fq38NsMYGRWjY6EIOqDgZPPPSiRXQ1tM0uMkOB8tb9papGqg BcDhTnpUu5FxWl2LgAAdyPWs25kMpO5RjpnPeqTKS0uNtodww2 enpzXuH7MXgd77VoJNgZQcVnN62Insfpx+yp4KJktBsO1QO1ff Hw30r+zNDiAXBK0RObmudF5+wfT3pRPnngitY7GltCKWbHOcE9 RUIuizYK4HeqCI2aVS2e31qpPMOvFTYuJUmuRjI4+tV5LoYI5z TjYm2jKc11t6E1RklBGc89uasmy3K88vy8Hge1Ubxt/OcH2oKi3c+olfIzmpFOQKhhYmibPfNWI+gpAx64zTloGhw4GaU kMBUg0MMIzxxQUYfxUrMQhT1OKURqoosO2oEgjtWV4gshcWrUS FLU+cf2p/h2vi/wTf2xj3Fozj8q/C/9qj4Sz+APiHfwNEUQykqSp6GuNvkrp99BUtGzyC/s1Q8ZBzwoHFUZItsmSRg9K9O+hbXvaEcgVz8vY9SKhbO3eQQce lNRVinuRSQKy5I5zxVO/sDKrDBYAcCly3Kv1MC70+S1wA8gOTnBqodUubbOxpDjsK56tKM 1ZnTDF1IK0WKuvXkcvM0pPYA1IPFeoW5BFxKGxn79cE8sovoep Sz/FU1pIsWvxD1SAgi5nUHn7x4rW0r45eItIk/0XVb2LaM5WUiuKrkdCe8T1cNxhjaWvMdfoP7c/xG8NIqW3inV1QdB9pb/Gulsv8Ago38QWz9o8Q38pYYO+Usa4v9XqcGnA9n/XKddONXXzKtr+2Rql7O0s99I8jfMzF+TXX+Gf2473TFA+0GVPd ua8/HZPzU+VhlnEEIVW31O10v9vqO9jCT/KfrXT6L+0noni1lEpiBbnk185RyyWHnsfVV8ZQxdF2ep1yWOie LbZfJeIEisPWfgfHc7zFtII65r6SOIajofEVaK5uVmFoPwKQeI FilQFSeeOte8/D79mbRrPyJpbGJxgHla97KKiqwvLdHzub0HTtY6n4m+G4dE0eO DTdPaVwOkMWcV8s/Gv4W+K/HkjtHpFzDBEc5ZOtevOrz6LofOQio+8zwDW/Ck2lXTQzR7WUkHjnNYQ0kwvnZkdPrXQinOzRcsZRZgn05A6Vp2 Hi8W0uSwXPFRJXN13R6T4V+L+mWVgEuHU/LyTXRXGsaF4k0gurx7m5BHavMq05XujX2b3PMfH2g2FlpsjwMC w6YNedzKA2AAxzx7120rtmU46XHQwkHBIwQc5FJOvXA+UCtr6k opOBE5+XOOacCBg8E+mDTSGixaDe/JUZ7ClltQ7Zxz29DSWgoxSKLRbmBYnHU470qlQoCgKcUIE9SRo 1cby3OOKhkeMIxA74PNK+o7FO+2yhVIALdutVHXgEcr9elJJ2J auIl0wfOFOPSr0M5U5y3PI75pvsO7LUUzh8jcxPv0q3DcjcePf PWna4b7lDUgJCHQAHOearSW6uoBAc9QSelOKDlsPlt8q3OB3xV Vogz/N1Hp2qG9BOzRBcKp5G4++Kktothxxt9MYNWthrYfLaGRcgjJ6e gpYbchccZAye9S7kJPcjDhZM/eweM96cipPKCQUB7elHL1KS1uXYYVgHA3Dpn1p1tHtZiMjuSaz 576IG76Dg26QMQQuc+5qYpuQEkY6e9NM0giS0g/dk7twHGRUBtjJctu+7nnFN2QWshscfkFsfNzkVLA4FwDguvQUR ehnfYuXSeYuCOfUjpxUExBt+TnI5b1oaNU7GVJJuT5cY9KqXUA kBIAIyOtXYzcVYy9Vup7FPMVyF+vNZ1x40vZEVJZ5XTsCaxq01 PQ1jLYgm1+RIwQNzEYx2FZV4lxfzFywAOD0qaVOzFOabsPg0l3 OTnBOABV600AnGVHpgVvTiZc0rmlHoaPCcjuM8VYTSo4IsqBnv 6UNik7uxNDZJFnK4UnI96uaPpf9oXAjyoycYNOSuKSPSfDvwfm S2SQRhwBnjsK6bR2uPCSN5VpLI4HRV5FStCaLurHMePviPqwBa eJ4YRx8xrzLxP48k1QbFbKs3U046rU6EjIs4lMTHOAT1PWppwr yArgHHPbtRfUzlK2xDw8iiRdxA4welVpbKNiSykc9Gq7iT01Ej sA3BXkjIyKe1msQOME/TjNJ7CSb1JbaFIlDLtJ5Bx1FSxrnL5wT05pXG7qyRLbuRklgcZ 6dqfJfcbRwOuc0PVlbjbi+JXaoyxHWoVVmYfyNDVmFzT8M6XJq GoRRKCwzwAPevuX9jz4PMIbeR4jk47VlUauRVeh+lf7NHwwGmW 0DFQpwD0r6a0+AWNoiDjArWBhGKuSSPjrn+VRlwRnGB9Ko0toR tJ2qN5st1xTZViCa4yD09s1Tnuwo65FBLepnXd1vOQarfbOTnH FZrcroNkffnn86qzLjOMVuZNalSSUgnPrVK9k4+970FJn1OCOt SRyZbB5qZA3qTxYJ54qzE4UVJbJFfJ607ePWhisOB5pwOKXkIN 2KQHimUmIXxTSc0iRp60yWMSIQRSA4P4j+FBf2co25DA1+ZX/BQv9ktdVvZr+G3yecNtrirx1T7Ga0kfnF8R/hTdeGr6SNoW2BvSuBvNMKHDLjnk4rtjK8TWXkVAm5nyN2BgfWo im7jbzzwK2dzRPqQzKVPKge570xiCdmADjHrnmjzG9ileW0bsW KgfSqNzoiMhOPbgdKSQXKyaBuUn5ic8imT+FBISQpAHPHFKSsy b6EMPh5lkClQPXI61DPoJjkYopK+mOtRYcpaEF3ocmcBf0NZt3 pbJCMCRRggY6UWCMnylJreWMHkg4wQDwKYk80IzvYHHANS6SZf tHHUli1yZXBUn5T+Rra0nx/c6RPlZWJ47964MVgoT6HpYTNKlKS1PT/h/+0teeH2XzJ2PTGWr2Pwr+2Q0ixmSUYzg5NfOVstqQufWUcbSre 8eheF/2lLO7uFlldFI5Dele+fB39rfQJnihumiwON7txWOXVKtCrqtGa 47DUsRRZ9dfBj42/DK80aS9vbnTUjVMs8zrgevWvG/2mf24vhPpei6hFp1xZzy4IXygOtfcOpCMVbdn5pPAVpVJX2R+Y fjP4j2PjTxVe3cYVVkmO0f3RWFeXdrCjDcTkdfWrSsgnFX0KV5 c2zQ5VhkjGPSuY1zWo4UCRsCT96n0NovQhZZb2OOQMzDoQD0rS s/E13ZWqwxNID/AHfSs5RVrMtSZci1661BAszOExzmoVtGducHuaG0tjOcnYnVgQ FGCDwMCmXKAYbAI7+9ORXTUrSxLKQep7EVBIn7rGcfN16ULYEi C2uSrZ+8F6+1bVvIs0Iyc8Zz0x/nFD2GineQhMqmOR0qq9mBKuDznv6URRFluJKAIdvOemPSq86lY zgDJNND1RnTZFyAe3Oae1u3ksWHA7EU7IVtCOOMRyfdbJ9O9XI sAgLz9aHqUrI0LVc4UnOenFOMAyCWwPbms3fcSTK93aAKpd+QQ MdxUHmGObg4IOc+1Xe5S8yxbx+bEwyq89WqjNb/AL/hS2c+2am9yLEDWbCcDHJ6jPWrMMBxj8wRQ3qTKLvoSyxMFAAAA 55p0SAksykEDtSStsaxjZlcW6ggkL1yMmmSDDkhQpJxjvRzO5E k76F2GERxryBgdOtCRMg4I474qbW1HbqMeT96VPANLcnyoPvYH oBTUgsSaK4ZBkBuMkZqw6bZMBiQTj0zSvdlOWhIkGIC5GCaguE 8iYAZye9OKuSktywTvUMW6dc1DdRYAXBCnnFDXRFTvYpz2g8rj OB+RqrJHnjDA+vbiqWpLWxWvbESR9CMevasbUvD4fDqAF7dh9K rzCTsNtNAIfLAHnnFWm0mMRKAuRnHPSpvqRfW46DSQhyMEd/arsNqm7KgMc0Jl7oe1oGboSu7tUTxAMqLg8etVa4mSeQOTjt6U tpLLb3IkRlyDzgVNtR2uegeDvjfceHmCTx+ZHkAhu1e0+Ff2h/CdtpLy38cPm7emORV8yW5nKjd3R8//tFfGG3+IV+bfS4Ft7XOSeMmvMrDTfmyxDr1z6VEddTocVFKKLs dsrDrkY4GKrhhFKcjIGCMU/Iwe5HNOo3HcMjtj+tPLI1uSRz3pvRFNqxEkuzA56/4U5rgMhJJz9T0pWsNKysMa5USE5JGcBqkBBAGQFA/KhpktaiOfs4+Y5HH61HNcGMj0z09aSY07ixXIkjPGW9a1fDejz azdxpFHubOM8/lSk7XG9dD6e/Zo/Zfn16+t557eQ5YHG2v0d/Zs/Z4TRbe3LQkEDstYxXNuc1TU+yfhn4PGjWCMV28cV2E8oA4x6cV 1JWQ4rqVZJjj0phnJHJIqmrGnQheTGehqF5+DzxTJe5BPdAKc9 DVC4nBHGcHsKhC1uUnb5z6elQlgrnApuw5CGQBMZqvLIMjBqkQ 5dCrcNtHU+vSqN852HPpTZUFqfVETZ4PrU8RH0qWDepYjbI6VK hJ6VJRMjcdjTg1AhQuD14qRWwBzSsMQkDtSBvwpisIaQnI60mF hpYijdkUkJEF7ZreQlXANeQfHL4HW/jTR5omi3ZHXFZVI8yB2ufnH+1T+xdLYzXDJbFo8k5Ar4m+J/7PN1ok8hjhb2GOtY0ajXukudjyDWvB11pszLJA6DudtZH2Nopw 23j3HSvQg11NbEF8pyBxuAOTiqyoyKBg5qlqWtiN4g4Ygucdqi khyQfxxjFDWtmKLuPt7Y9NvO7rU62wcD+fr9PzqGyiKOyiiudx 28dzTjYxB1xgDPAyKG7EqJE+lxbC5CggYwax5tHEkvQYJ5xTiN My9Q8PhWJRfrke9U5fDodQCQPepsK6aKj6E7xr8o5qhNojiQ4B 68471LhcSV9StJaT25OSR7CpLXWrnTwH3OMHu1Z1EmrG8MS4LR mxYfFa9s4Su9t3c7untWno/wAcb/Tp1DzFgevPSuSWDg58x6Ecyny2TO00/wDaQkvdN+zteXCqV5HmEf1rmPGvj5rq2zbzlj/vda7ORWOKrWk1ocva+Obi3kBDsgXnntU8vxTuBwZCx7c5/wAitHscz8iVPHEt5Gm5yfl9elJH4h8+UBmH3s8HvU6saOs8LeK Rb7Q2xkJw2416j4PGi6hE8s3koVHXuaydRLRjlrsYV9DCb+4kQ qqE/LntWWLo+YcruPTr1+larVDS6D7dUMyg8cY4PWrN7OkkYXA/E0mitynvQh8cVVjCyIzYUYBzmqHuiqJExgE5PFaNkTbgLgMcc5 60pbEqJHM5NyRggjnPYiq93MVUAY9qaWgrqxXuHZkUbAD+dNi3 bGXHAHPvSUSYvWxG9vtkbeDyOCT0p8kO9SRnnqSafUYyCHcMAA H61PFD5Mygbc+hOamTsS7pFxLgK5HH0qF71jKOwPb1qEhxelxZ ZCyAqy7Rzj3+tQyNsA+XDZ9atjauAJOeo5qJZlMpzjI4+lSlrb sFyOUeblQA2B2GDU0B8pAMZJ64pJl9CV33FRt49QaS3gLE8kAD nJ6U7okSeAADb83tmo2hwmD8o79/Wi7tcV7omtYQ4LLhqctuyEnO4MOM8UubUrlGTRlpd35kmi9iDw nKkknpnrTjoxrsJosHLE4UGriooIGQcnt0H+cUOyZLWrLPzMik 7QTxiqd6jRT8Yznv2oitbCQ7c7Q5xkCmqflAA38YAGeKbaSGpd SAoPKcjA/2arPAJWA5JByPl6ZprTUaEkIZPvA4HOTwKqXMCuAVzuPTFCZM0 O+z+XHyFHrUTkxvktkbeBim7PQndA0mzBBXB44FRrNtYgbTjjB 6ihRRXWxM8pVehG0DJBoCEsCWC5bPSnsJsmISNcgqW7eo96iZN zqwTdzw3ekty76DbvIzu4JXPqDVC9k3vsORj0NCJbaMu6gcyDb ktnB96ltQwY9BnpnFK+oua5NI7REZwXPTiq8rD5iD859+v4UhK Niug8xORz0NBDwr0YfLnB6/SqYmNMTYwwZe5ye9V2jYsRkDnjvin0KY9AWZflZWJ57jpU9vCe e5/r9Kb0QLUsG3Z87MEemM1CmlySjaFbPUkdam6G1Z6HT+CfhTqHi m/iiihkxkAnFfXP7N37GNx59vPcwbycdRXO5OUtCJStqffPwA/Zyi0aKH/RgGGO1fV/w5+HEWjW0byRgADgYranBbHMkd0hWNNo4UenamPKAM5FbnQlZE EsuPU1WkuMjA60wuQPcktyTimSzZBI6UiClPNtbrVaR+TjpSSs K+hXd8k84xTGYCTGadhzehBNIVOS2TVeW5HOeSKaIVrlWeX8qo 30vy46U7FxPqqOQseoqzG3OcGoe4upYiP4VMj8DFI0RKrYpyyH PFILDlcE9cU/J20BZBnPWjOKCWBbIxTTSEJnI7UmcUIaYhbPaorq2W5QqwB+tJ oVjzz4nfBiz8XWMitBG+R3FfHPx//YkUzTSQ2gZTkjC9K5KsHF8yM2uh8kfE39jSVp5S1myY6DbivE/Gf7IdzZuTDbuMdPlrojK6uU52POdd/Zr1a1ZwsDg5/u1zuofAfVLeUZtpcAY+5WyloXGasZN98ItTs3+W3l4PXaaqj4b agPmMEueeaqM+Z6jdRX0IZvBN7CoXyX8we3Sqtz4bu4XO+Jl6j kdeKhtXDnV7Fa40eduqP0znFQtps8ij90/GRzxmq0sXFj5dMnlhLMrKo6/Sqg0h415Vic/55pxfQaIrnSW8sMRlM+mcVSfSvtGQV244pX6k8utyBtPXfjGR3 wp61Wn0nC52EDsCelKOob7GfPpAuY/mQAfyrO1Dw2oVj827/Z9abVjPXlsZT+HZIgSFGTyRj2qjNpkqkrg7c8f571m17xb8iKS 2kTHlhiD/ACps0cpQAsSPr0/KqNHIqTRyNgjII/HFV1tmVsEs3OMnPNCQlEsxPIjB/mwORzU63sqEM2c9alp3DW5o6TrlzbyAAkg9ehr0Dwx48MUO0bc 49ccVE6akik1Y24/Ecl9ERn5T+dOSURRkZJGfSnFWViW2tAS+U3Q2n5f7uas3l7+5Y dRjsKc0yrlKO4zI3AIOMHOBUZmKg4IXqOvX8apOyGmyN1US7iR z05q9HfBAqglmJx16nNZyu9ES2yKe+EkpJJP4c1BNceYTgtg9i KroDVxkpBQNgg9OT0p/msI9pGBTv3GtyrNdbHBI5xjjjNPa9URtluQOuaLiT1sxtveruA BPWp45v3o+YEYyM80PQLkzHaqsVwM9hVeecMMbWx1PPtUx1YWV 7EsEwMJJOMdFPamNceUnTr19RTdkMLedNoZsDPQA1SlYyXBY8H PJxT2dwGG4yucsCp4FSDUREFwAH9RzUyQmTxasuz5sLjr/APWoTU2fO0gevtSshvyFF2AWbdv29MnpTvtAbdwCuODwau+tgW 5LbTbYd2GX3qeCZZJjgk47Z61D3Q29iG8O6QZGCAcA96jvJWWH aoyoqtBrck0WXGedzN0HfFaCHeGO8gDqD3qbX0Yh7X/7o4+b9D+FUr6cy7tvLey9KPQJ+Q22uSqqOpP8NOfLr6e/vRYSZBO/lqw2nnqMdKgMpYZUgew6U7AQlzcPgAsDgccg01EbPOMDoKtpA0 mGGUgnBGO3eh7bzVyd2M+lFhJWI206dlJC4Hb3qGGxmRzlCD1J 7ChNXsStGWHtJFjbKO56jjrUcdrOzYVZNxOOOOKBpplqDSri4/gb6baZNo9y7FPKIA56damUR9B7+Grto9xjfB46Zqt/wj91MxCQsSewWhXRLbtYQeE7hzhY2BHoOBUlx4NuogG8o/XFFrsW+5IngO7uFJEbgjvg8VXj8A3bzlNp3Drj0p7lN3JE+Hd/hiI5Dzj5jUM/gW+trjY8Tbh3xwaGuoNiXHgPUJYQPJbI5xjgVVT4d3zz7XjcA8 jjOKb0Rdupq2nwovJowvlMB0wQRmrlr8INRmmVY4HbH3vl61K8 yVudV4Z/Zq1XWpQot5BuHYGvZvhf+wdcXssb3Fu2fcZrJq8iZ1FFn1H8G/2JbXSGib7GhcAfw19T/CX9nkacIQtuoXPpVxSWxzuXU+gfBXw/t9Bt1ZkXdjpXUBljTA4FbxVkVFPcjkuM9DUTzc4PWqNGQTXA3Z zx6Z4qrJc8nk9KCJFae6JGBjFRG74IHI7ilYLEU0hbknOfWoHk y2CAD1oBvsRyEAHHTFQvJyfpQS7PQrzTA+oJ7VTuWBDHrTFbUq yS7UPPGeKo30wIIJBBqluaJrY+sIZcnpmrcUmO9ZyIbsyeJu56 VNG+MUmWnoSrJkYp6vSKTHKeKcp7UBsPU56cU7ZuXqKBPQbgL1 oYgDrSsSRlt3WjcO9KwBtBHWkLc00NCMquKy9Z8J2usRMsiIQf UUnZiauebeOf2aNK8QwuVgj3HnpXjfi/9ieOXeY4VIP+zWXJbVGUk7anmfiP9jJonO6xDepCVxmrfsgIHO 6wPX+71rSMu5ly9jB1P9ji3dWBsjg/7PSsa5/YztAuPsIDDr8lVGSvczs0cxrX7GFrFcE/YwAexSuY1/8AYkhu2BFtyMnO2kmkjWnPlMK4/YXhfj7KCfXbVC9/YaVAxWD06jpR0LjWkzKvv2MgIXiEJOfaudv/ANiO7RyVibb6baae5p7Vp6k5/YokubEbYMN3+Ssa4/YVug77YnAPZRihvsUqpSl/Yku40J8l/XpyKzLn9iy8nLAQnA6CqRKrXMIfscXq6uIhCyL3GM1Y1D9iTUH lOyB8diRSu2Cqq9ikn7D9+7nfbsABxgHFZ11+xBehuYWJB4O3i jclV09DmNb/AGONR09W2wOTzjisPVf2R9WS1ylo5Y+goafKUqhVt/2PdYubRS1tIc+1QL+x/rH2rYlm/HHC8U7NoqVZRVy/D+xxqina1pJx0H+fwqjffsm6rbuNtuynoeKnldhKdyrP+zFqlr OP3EmO+RUc3wYv9Kl2bHBz120rGkZXHnw3d6MmWRx6e9JNHOI9 pB9we9Fy79SLzJCATwc9AOBTXvJHLbgSe+KL3KTuNhWW5m+UH6 VKbOQ53Kyk9fem2BWlDKVB3AA547GpVugHJJGScg9M1LBkU14o ZsYU4PHr71EmqbJAo3E8DHYU4iSb1B9TJDEY57Z4NPjuy8W8Db 9KTfQL62KkuoESFQQcdc9qY1+uCM4HpjOKlq6sJq7G2mobrts5 AHcAgYq7DqILkbh171d9LB1NF7pSyx9ML07U8xF4Ttb5hyRUpp bDSaZVmgl3MqjAGD05qC41JIdocHeOue1SnzDY2G789CyNgd+c VHNMTJuABzxwTQ5NOxDb6Ebb5IiQCDjGBUEitGeckY+lU2NXYN JiInDHj8RUttFJMpfB6/3etSnZ6je5ditnONqkDsD/AEqQQsrHahBJwaSGvIsQWe5QAnAOSatwWks27aGGeCQtDeg+fU cdEuHmyiEEeoNW5fC0v2YjDAY9O1PmsLdiWPhWYnKKxOO9SSeG LoSg7XJ+mPzq09B2LH9iTC2I2sMDjK1nSeHbi6zhGKkenIqW0F 7Fuy8K3AjA8t29T2NWoPBd3KwBibGeBt60PcXmSL8PrqckiMke uDwaD8LbplJ2MgPXikpK4x1p8KruWHiI5DdcdavQfBm7MIPkOC e4U0OXQnmsa+m/AC9uipETE+610mnfssXl1tZo5Bk8jbQqqbshSmrnXaB+yPL9mK vbu57ZWrE/7IbO277P82TghauJnz2Bv2P2nUL9nyB2C1LB+xm8eD9nOMYORV W1uZxkaNh+yBJGh22pwevy+lOH7IEglDNbMT14Hak5alKb2ZYm/ZAklhH+inJPXZUtj+xqyo5FqwB7AGpT11JlzXRZg/Y0keQf6I4APTbVyT9jRuA+nsPX5OtO5opa6lpP2O5JYsR2Tk47 pUEH7F08UzN9jwcYxsqVLUj2ltC1Z/se3JGTZDA6ZXNJN+xvI8uZLI5JPO00lPWxUJMu2/7GDyooFk4B7basWP7CjzXKsLLkHklKTnqHM7m9ZfsNTvLzp789 Pk711Hh39hXypRvsO+fuUczYSkkeq+Bf2KxaMjGy/ErXsngn9lSGyCb4AB9KqKbMnqeoeHfgpZaLGu6NCR6CuotdGh0 5dsSBcVooWKhG+5KwI6VE7E4JyK0uaMhkb/8AXVaeU5zkj3osLyKjyOzjJ47Ux5Cx7DvTB6ke7jHbHeo5OAcU AiInLdx6Ux23HoPypNCIJGIBAqCVyVHJ5PJz0osSkVpnAJ5ycV TuJC3TgU7i1SKk0mVJxg9eBWdeTkrjn3q4blxPrW2OOTjNXI2x xmsmKS1LET5HPSpY2yakaJQ1SKcjmmX1HK3NPDZFIXQXcF5zil ScdM0DB5dvtQHyvtQTYTOO1GcjgUCsIDg0pIIz3qSr6DRwxpDy KVhWGsu7rUUlqkoIKjB68VXkFkypc+GrW5GHiQ/hWfcfDzT5uTAn5U7Ihw1KM/wn02QH9xHj6VQm+CulzP8A6mPn2pOKM3TM3VP2e9KvVwYEzn0r E1P9mLTLiPCwpn2FL2aJ9mYcv7KVp5p/dLj6VVuP2UbVhjyVA9hS5dAadjH1L9jm0d96xDJPOBWTd/slQy5XyQPwo5Rttkdh+x0q7sLn04xVS+/ZINuD+6DEnjiizQ2rlWX9jZ5oyTDjPTisSb9jKeCd/wBwpU/7NVZktK1jNuf2KHikDi3BP0q9bfsdyi3GbcZx/d6048yVhJ2AfsbyOmBbAH021R1j9iOcDctuMY9KTTISOa1z9iC SQqRZgjHPy1nN+xZ5ikNZAEdMLVJvqUncgt/2NiX8tbAcf7FSp+xUYJCfsKZ7/JxVKWpPKr2I7n9iyeSTIsAwPU7axtZ/YrlhYM1hnHT5KTbG3ZHI+J/2PZViZxp+RjrsryXxz+zAtpIxktSp7fLWV7F03aWh5d4y/Z02RM6xjOOPl714140+C1zpUjyRq2fvEbeDWbm9jtgrvU44eG5 EumSRCGHqOtTxfDi5vJAUiOPQUKaRqo2LH/CBXFtIq+WwH+6aml8CzzRHMZyOnGKOYh7lO98DyRqPkJP5VhX3 hFoVJAIHb3p86RW5j3+htGX3KQD68fWqkOklpvmLADsT1pKWoW vsQ6pC0CBEBI7H0oZHj0LzW3AFsfSrulqI5uS8Yu2Hxj07059R KoF3ZHU5NVzahbRsbHqpt1bDAr681LBrh2gndyOlQtSIMng1/dIGDgAjAyav22uSxBQrg9MjNJPoxxmmmuqNOx1ppADt+fGNtMb w9carLv2kZ6kVEH1EpM0bPwTOlsGERbLZye9W4/BsqvnaT+HFL2jvYtrTQlg8FSzSnKdeo7Uk3gOdnyqNlRncaHKx ajbcWDwDL5o3R8Hr8pra0rwIzoq+UT227aHO4NKxuaf8IrmeX/VMO+MVqw/BGXeAIDu78VnKsr3RE5JLQ3NM+Askgx5GffFa+l/s6TLOcW+cN3X/AD61LrRtca3sjYtP2fZVcZtT9MVrW/7NU91b/wDHuAfp1rD6xqJ2T0HW/wCzbPbsP9H5z2FLJ+zZdM5Y27LnqKtYq+hryEg/ZhnkTLW+3HQBaZF+zTcRvlLVuTydtRLENaESilqa1j+zVPjBs8 HPHy1v6L+zBK0ny25yePu0KtOWrJhd7mu37Kc4cEWuSf8AYq9Z fsnTtgvb5GeOMYqI1G92Dsje0j9kaMj/AI9k49VrVtv2RcsGEC47cVbqSUtCZX5tDrPCP7JsYmTfAAPpXr 3g39kOynRSYV6f3etdFBamdWOzPQtF/Y50oRDfEue/FXpP2N9In4ES46Yxiu1QOdpkUn7G2lwISIUB7YWnW37Jemxgh4 UI+lNRBJ2L8P7KmjomTAmakh/Za0czhzBH1/u03BD5ZNl0/sy6IUAW2T/vmlj/AGYNHgz/AKOnsMZpqCGk9ie2/Zz0cNloIyf93pV1P2fNGYAfZox9VpciE4O9yYfAPRkUAWsefXb SQ/ATSA4LW0R/4DQ4oHEm/wCFDaMTkWkWe3Apg+AWjyON1pDj6UnBDcZdCynwN0iNflto/qVFT2Hwf0u3k5t4x/wGm4LYpRZpwfDjTYl/49ohj/ZqWLwHYIPlhjz9KLIrk0Ldv4etrYDbEn5Va8lI1wFA/Cq6aEOPUjkx2qpMnPX9KGap6leTOOKik5BxzTuUyrKQB9OeKrT HIOOF9qZmmV3TnuDUJB74oLGvx2OajbJfBwPwoE0NMRLZAqvIG V8n8eaCGyCSTk449arzyhM0rAk2ijNNgYyfSqcsxAJH6UwuVZJ +DzWffTYiJ6HsKqLsVFn1pDKcAk/SrUM2D1zzUivctRS5xwasK+AKm40SpJnoalD/AEpN6jQqy4PfFSLKOnQUihX+ZDUUIy2SadgCa3ZsHJNSwoY15J zSRK3HFjShsmgYnQkGjgmkxWAc/WjdQkCXQQ5wcUzd8tMdhrE5A4pSxAoG0G7I5pjcg0CsMODTT04 p3E0MwO4pCinnApEqIxoFJ6Dmq0+lI5OFGaT0BxIBaCCXkDFWW sYXGSin6ihMLXCSzj2/dUVXnsICMbASfaquHIVbnSImU4ReKltdMhMABjWmmKUESJpUAA HlrT5NOhZeUXHSmmS6ehUn8PWsoJMSk/SqD+DrUtkxIPwoFyDU8H2kMhbyVyfakl8KWrHHlKc+1DkP2YDw 3aovEaflVW/8KWV4hDQpn6VXMJ09Dm9Z+H1iqEeRGynsRXmfxQ/Z90vxJp8nk28ay46VnNXQQp2Pkj4tfA648JXkwe3YxDvivB/HngSO+tpB5Ue/HSuKqjsik1Y+efiz8NHsZneNTG4OQRXG+Hfij/wgupRw6rGrxE4EgXn8axSdjrp0uZcp61pt3pHjWzjltdhc84zU d1pEVshQxLheMn604XsZSp2Zk3nh6KaRiUByTWRrHgy2lichQA DWrkkgcbHG+I/CMQYLt2kj865S/wBEjtHYrjOMAYqFLqSoa6GNfCC2uDBguwA3YFM+Jaw6V4Itio2 yMC3NdaSaFJaniF94jlRBtOw554qlH4gu43VmBbPGc1ql7tyZN bIbP4jmjlIZiRnoe1Qt4kuI2bDuFHQjtQo6cxK3JIPFlxG6j5Q x9e1aFr40uA+QT055/lUJCTRt6J46m89SSc4xjOcV6l4F8TGVArYbI4+tTKHumko2Wh6 poVqlzpyF1U56DFX10yIRAbFyfUVySdpFRely5a6VCoztHvx0q/aaXCyAlARmlN2RUYNu7NODw9bXHGxVJHp0rY0nwvbW4B2KD0we tZOo1oHs2dTpekwqRiME5GeK67QfD1vdyKPKQknv2rlk9S40VF HZaR4StcKfKX8BXSaZ4XtBz5a4x3FKTWxCpq5q2/heyLA+WMj1Falpo9rCm3y1Gfas4t3LhRuyeLw/b5J2Kc+tXLfw7afxRR+3FJNpop07suDw/aMoQxJn6VZsvCVkrj9ypx04raTuTKipI0F8N2ZAHlJk+3Wrun6 FbQSgiFM9qtVNAdKxq2+mW+clF3fSr0emW7JhFT8qyvcUqexZ0/S4YwSVG36VpwRRbAFRQO3FXqiuSxcs3SJ8gAD1xXceDtdWMqDg CuijP3rGNSnoeg6beiZFYfoK0orgAYwa9RMwaJTMNmcgiq8jZ5 IIzVNkJEW8n6UqnccU0irEykKxPela42jnJNAuWxGrg9Rg1PG2 SB0psTVyQEBfb1p20ADnrQ+wnEFI9R9KSVycLnmhq4ashkuXgB wNxzwfSnJP8pzgGkXayJtwXqfwzTWc89KaFayIzOcEelNeXaOp x600Jx0IZJsZGc1Wck5Ge1JFJEbZNRyYDc+tCG1oV5U6YyBVaf 5SeeKohKxUk5zwKhc5PFJPUpIjkPA5NRudwIH6dqYkrEJmeMnI 3CmNMXT5x83WhvUSVypK/JwR0qhNcjcQaaRMCnc3GVGSOvFUp5tx55o2LsVJ7rDdR+NZ11c h8jOcjtQlcFE//9n/2P/bAIQAAQEBAQEBAQEBAQEBAQECBAICAgICBQMDAwQGBQYGBQUFB QYHCQgGBwkHBQUICwgJCQoKCgoGBwsMCwoMCQoKCgEBAQECAgI EAgIECgYFBgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKCgoKC goKCgoKCgoKCgoKCgoKCgoKCgoK/8QBogAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoLAQADAQE BAQEBAQEBAAAAAAAAAQIDBAUGBwgJCgsQAAIBAwMCBAMFBQQEA AABfQECAwAEEQUSITFBBhNRYQcicRQygZGhCCNCscEVUtHwJDN icoIJChYXGBkaJSYnKCkqNDU2Nzg5OkNERUZHSElKU1RVVldYW VpjZGVmZ2hpanN0dXZ3eHl6g4SFhoeIiYqSk5SVlpeYmZqio6S lpqeoqaqys7S1tre4ubrCw8TFxsfIycrS09TV1tfY2drh4uPk5 ebn6Onq8fLz9PX29/j5+hEAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSExBhJBUQdhcRMi MoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nz g5OkNERUZHSElKU1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOE hYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3uLm6wsPExc bHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/8AAEQgB4AKAAwEhAAIRAQMRAf/aAAwDAQACEQMRAD8A/tOs7PnJPI966SztSoHpW7aOWUrGzDBtOR3q/DAOG5HNCKRqxRkHnkVoxxnHH4VnJroNOxMIxke1SiPjJ+pqCuc nSMsOM4FaMKYAxnnpTDnLHl4xzxS4Ax83WpbH7QeMdjmjg4OOa Y+cXA5B6VJsBAIJpJjUkwCjnNN2qMgd6ZRn3VxHGCM5Jrmbq6e UttOB3qOdEOZyOp63Zab/AKxzLcOPlReSax7TStb8WSAyhrDS36r3I96cHcXPoeq6L4asNG hVbeJTIOCx610IjAAxwRVttgpkyqrAqwyK5zWvBug67GyX1lGx P8Q60Jlp3PN5vh34i8OO114Q1qby15+zTHKmpbX4g32mstn4w0 a4smztMyDKGpk+oPRHeafe6PrEKz6ZfwzBuwatRHubcjP7xB6U lNMSmi9HfRuAGypq4GVgCCDmhS1sCkmOphbBx0qirib/AGqPcegPFJO5CmKrkehFTA5APrTKTFooGFFABRQAUUAFJigCNg Bx+VZ13cpApZiARSbQm0ea69roCuzSbUUdc15/bWepeKLnyl3xWSnk9MihPUTkj2DRdBtNJto4oYwCOp7mt0RqOB TcrgmLsBySCajZecYJBoGncZsIJJyaQIM9DQMNo4GKjMQzkd6E yeYiZMDoQTVZkxnGaAuRsB3BIHeq7qMZ6jtTTGmRFcjjIzTCg7 8ii7E5DAg79KjaMHIKk+hoUmhpkBiH4CoWjU9qfOydio8IJyCW qCSEN8w4I60+Zk30M6ZFTqpyaoTAMjAMRjpVqqwdzJK7ieTxWP eQ9lJBq/aWVibnPz25JJLdelZF3a7VJOTx2p0qrSCUraM5y4g+9lSPrXK6 laYQsgOetaOs7lKR9fWltyCAwz6iugtoGwAwz+Fci7mCd3c1I4 WGAFODV6KIDBI5p+hdjQSLjGB+VXEiYY4AxWTGOw3zBl24qdI3 KqcFlPWkmBKilTwODV6IHg45poCY9uD60zOAOwPbFJg0OXHUZp 3pQ7sdhR0AOKeW4GOCKa0BSsQyXEaD52UGsm61FQDtkAFZOVwc jmb3VraBXkubiONFGTk1xba7d63P9k0CIvG3BnxwPpUXu+VBbs dlo3gqxtWF1qTC9uzyS3NdvEsEICxqqKgxgCtrpaDTJhKnqMUN Kg5yKfMO/QejrkEMCKsAg9KIyuOD6Bkeoqrd2FnfRtFd20M6MMEMuao0PN9 T+GNiZTeaBd3Gi3nUeW3yk/SsJ9d8d+E/k1nTv7csI+PNiHzY96wnS1ujOUOp0Wj+O/C+u4jjvEsrw9YpflYGuq3TQ4aGTzUPoamLuZomj1QLhZsg9Dmr q3Ucgyjqc+9aRfctPuPMmRx+dNySTRHQlE0aZA5zVkADpVpmkW LRVFhRQAUUAFJmgAyOuRims4XvmlcVzIvtRigU5kXcOK8y17xI IkZmkJ5wFB5NYzkjKTRzelaHqHiO4W6vA8NmpyE9a9dsdMtrCJ IoIgoFVtoI0QABjHNLgEZ5HFFirDMH0zimcnngYqk9Rp6jsZpM d8cVZoR7Rg88imEEfWkiERuOhqmwByCPwpLQE7bEJBIHeo2Ubc cgiiTCQzAxkgioyARxjmmhpCFBk8j8qiZcHpmlImREUyCSDn0q JkyM5xiqQtyEqhz04qvIo5Axk0DT6mTcICpU45rnbvcN3zbRnt TuTYzl5PLZFRyBWXoKuBKMmaEHJ6EdKypkwCCvB9ulJOxVrmJd 2qSAnaB71zF5bD5hgD0qpdhRZ9iwWgUnjPPWtSKADAIGCai/YlIvrbg9vzq2luAM7am4y0sPccY9KtLEevUClcEQTXCW7gTRvs c4DAZq1EJQwXYGibkMP61nrcCcpzyOvtUiJt75xWiY0iVlBwQT im4wPWk9BtaiAAHIzzTqoXQQkKCTwBWHfaxFaqQCCaxchNnD6n 4rht1d5JEQD1avl34i/tJ6L4euTpWn3SajrUvypbQnc2f9r0/nXNVq2fKtxrcw/CjeJfGDR6v461h9JtC26O2D7cD0I/xr6M0zxL4a0G2+zW+oWkEUPJO8fzrWCUVZk8x0B8eaZtDrqlud 4yP3lRx+NrWRgV1CEg9PnpuSIdRLcmPjOBg22+h+X/bqePxfBJ8ovYifdqaaK5kOj8YrG+DdRFf96ti38XxnH+lQ89t1 P0Fz2Jn8VRLIBJcxKGHB3VoReJEdVdJ4mVhx81A3MmXxFk4Mkd Da5HKNsnlSA+vSnzaFKpoedeJvB3h/xCryLCljeHkSwnawNeA+ILr45/DbN54YaDxro0HJtpXxJt9AaznG+wcyehW8O/tk+CLueHSPHmm3/gTWi3lsl7GVj3ezelfSmjeL9H1y2jvtC1O01G1lGVeGUMP0rGn WfwyHJWOuh1xSmHwSO+aeuuRgj5Tjp1rpFcux63AQBuxVpdYg4 +YZoAlGrwHjcfzqYarAe+KfOyudjxqUB7jNPGoW5H3gDVe0K9o Av4T/ABpTxexN91lNHtA9oSfaYv7y/nUL3cfHzAUnMTmRtdoBjcBt7VgalrSQq4Rxke9S2S2eMeJfGq2 8wiilM1xJwqqau+GdBm1aRNR1XdsPKqain72rEeyW6W1tEscSK iIOgqcyqcHnHWtGNoXzU45xxTgy9cn5aTBh5o9j+NMLgfLwM1S ZSYZB6UpIwPbpQ30BvoM68imFgc5zTXYLdCFgT9KhZeCe1C1Ey LYvXIyBUZXOTjNHUq12Rn0A6VGVDAZqojV+gx+DUBBJ7j60xS3 EK44/vU3aORimN2ZXcBW6AA1C6KeccmgTizPnhUg8nPWuWvrYktnoKp JEOXUyQm3IxgD2quVUkgA5FGq0EpdypMABjA4rMlRSCQQT1oGt UY8qP8wbAWsC+AMbb+1F2NJXPsiOM9cZz0xV+KI8Eip6kl+OHv jjrU4Q8dM+9NoCwicYIqXaRwRjFZp6jFCEnkAgetSgYp26iAHn GcmpF/nxVDTsSZBBxzURUjpnFBpNaDearTXUcIOTkiok7akdDldY16O2 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 up07/gqnocnl/afDt8hcZOOaylh6q6FSqLa52dt/wAFPfCLFfO0XUlXudproYf+Cnfw5JCyWGopk85U/nSnRqJbA60b2TOptf8AgpL8KJgpZr1C3qmK3o/+CinwfdULX88ZY9wRUNSXQ2ctTbs/2/vg1cKD/bqrk8g11enftw/Bi+OE8SQISe5pXlvYfNpc6u2/a++ENzgDxXZKx9XrUj/am+FVwVRPFunDf0PmipdR7WCMtDUX9ob4cTxlo/FemOMZ5mAr5r+Kv7WvhbTJf7J8Pata3+o3J2go+VT6kVDqOVkh qaOh+FWu6Xexxa74j8Q2s91c/PtaUH/9VfUNn8Q9BChI9Tsgo4G2QYrSLUVYlSv7xtJ450x1+XUbU/8AAxVqDxjYPnF7ASePvU1Uiy07l0eJoGIK3EJH+9Uy+JLY8iVS R71fMPmJ4/EMTD/WA1KNdhbguOKE+o4vqTLrMJHDDNA1eNsgN9apDRKNViAA380HV YTgF8Uk7CTsNOpxk4D80j6lGeA4BNUitwGoRnHzcil+2qM/MCO1PmHzCG8QjjGaBcRkDpzQnuKLAlXGVOTSYOcYq0NtkgVcZ6 01hnle1MSWhXaIMe4NV5ImXoARQF+hUli+U5wQaxZ4A24elNOw ld6GFc2xVsgHArLlwmeuBWjd1ckouQRkDJrPmj+YHbgfSouNMo yxD5l4rntRgAHBwRSRdrH2PCmM8HFX40GBxQkZltEI7DNWAhIO 0AfWhgShAOvNSAZ6HmpsUtQCnr0A4pDx6GmJoTHOakXsfSgEiW oJmVBuJxSZrJaGTPekbgCAP1rnb/UVtYJZ5XCxoMkntWMpdTJs/N/4/ftRXWl3134X+H2mz+ItfYFdyA+VGe5J74/Kvw9+OPxA8V+PPEt1Br3iKTVry0Y+cA/7qMjqqDpgV52H/eTUmTJNRcj5kvvHctlcRadpjmIqPLeTPJ57VhXGo32o6jc3YmZ 2V9p3H0FfTYakpNHnVZK1zU8LMPsz790ctxOSDjtUurQtHdoFL FRluD2r1lSTjG5x8zUm2YwK+RdFWDOjErnr/nmm6XY3KEXBUhbj5uayopOTKqttI7fygZrcrIDLGpOBVVGkZ/s9xGQJD19eadSn2JjKz1OsisZBO7RFVjVdxxXPamJYZD8xKR56 dDxXRGHuNmXM3LY8s1qa6nQFpmILDH4Grtz4imTFosxjXPGa87 CVPfaZ1VqKsmZwy928yEsqjd1zk1zN5qM9pGxnlk8xmyfat665 U7GNKN/eZuprRS3UzPhETg5xUOmX8jarbmYeZHJ91sdOawhK7sjWpTvr2 PoSxuGGjTiOISeYOpHTmuRmhSaSZQrDBBAz3r1ow92xySl77M1 ryWzlnKsAyORnH+faqU2qurrFOCJLk4BNclVO1jdyslJD9SdvL EhRjEIQwrO0vUgLqNnBMaDPPesHTV79BpOS8ztk1kTwpEgCOBn kU26uZI0dQ+doGSKVZ6WKdNxdmRRa6Y/k81tm3PWop/EbRrbv53VvWvOktTtdS0bsnsdfI+YuSd3QV0lnrkvnhi+ArZYd K2hFPYwnc0rvxHJGGMcrqQOx6Gqh8TXccMJNzN5m087uairCN3 oaU6jSvEltPGWpQohOoXg2joJD6/WpZvFF4JIpYb2VJAc5yc1Hso22DncdGzqtO+J/itLF2i8Q6pH5bEDbKcVPb/HT4gwxskfinVVCesprL6nDc0U5JaGzaftK/E9HVV8XajGIwc5et+w/az+K1somPim8bDYXJ4/nWLwkS41TpY/22Pi/ZFdviN5Aq5OelWbb9vr4vW8u861G4xnBBrKGD10ZaqdWdZY/8FGfilb+WXlglHua622/4KZ+PYgBcWEDsB1DUfVJLVMpVVeyOgtP+CpXiK22m70hZAB2bm ustP8AgqzFFh7nQpDgZODSnSmthKrF9TrLX/gqv4Wlitnm0u4R5RluORXQ2X/BUz4dzkJcx3MRGMnHFZSjURo+51tt/wAFMvhbKY911KGlIzz92uqT/gox8HJJEQayqvM2MlsYFS6rT2G2dpY/t7/BO4KxnxTZq2M7i4xXWwfto/Bu48rb4y00K3J/eDilHEX6Cuz0HQP2lfhpr3lfYfFmlSmY/L++Ar2vSfFen6nEktpdwzxuMgq2c1tSqxkNPudLb6iGbhhhq3Y ZllUZOK6I7amkWTtjaBnI7U3O7qelUNrQMjB9elQt0II6dKAe5 QkAycZJqhKoJOOooBGZcx8ZIJrnru33EnbimuxPNqZbwsOAAQD 1FVpIjt7knpzSa1GpGdKgywIJxWNfR/KThsDpRcryPryJeegJrQjUDHFO5kWgMkdxU4H4UmOwuD6VKowo 5oLirDWJ5B71HQKTdxcYzzSq2OvSpvqTsQy3aICF5NYF7ctIrB Gw3UelS5FOVzlbjVjaq63ZSW4Y/IkfJNcZ4p0bV9f0m4W9nbTtPkU5VepFYSjzaEysflD+174v8Of BXwXPpfhuO3tfEXi1jCJiMylf4jmvwd8Va46LLFbyuLy8kLSuD 29KrC005y8tDCvUtG5xZshM8TSkSM4DZB6H611Ph60muVmiRTM WZs45Ir6DDU1zxRwVZWjc9L0Hw61vBEwiO4EnlaxdZ02/a6klmtnCSKEUhcivWxKcUraWPPpV05W3Mp9BuI7PcttcHfkD5T Wnb2M7va2j2so8hcEkdTXDHGwUnqdqwU5RtY1Bp7RLKs3DNgKQ KradaXdxdiOVS1vDglzWkMTCT1Zm8NVUtjuNN0mS2F1cmZjHMQ MMOMVh+LtNuUt7iW1g271AAA/OtK1aKpOzFQw8udNo8F1q0vZprC1ihlidZWYnHUVz0en3cksgn iYMp2jivnMNiYqpc9eeGlKFjas4riN5FUNK0YKjP0riPENret5 QRXGMg9xXfVxis0jB4J203Gyxal5NjGkZk8xApOOprr/DFjefarf7RETHGQoyP1rmpVoXTTNq2EbWp9RaJo8kuh5ZSsb5A HT8a4eWyvrK7cMEYOcAd692pi4cqVzx44KfM00Ymq2c9wskgXa CSQCMDiuN1AXAuYklt1eMdCBmuSeNi3dG0MDJx1NqCd3gMTxNt +7npxWebYJKpMZwDwcVk8THlsi6dCd9dzQaRo1LorJnmp5JJ3s f3kRO8bs+tYzkmr3K9nJSs0eXap4gFvdzRklDGpOPx/8ArVyt141twIELhiWz1rz/AGuup308PK+p3vhjWk1GZVRzgEGvT7e4I3xsnJ5zmumnXSIqYa XQr6jI/lEcluvXmqq3LbIpJC25RSnWTZNOhJ9C7DIJ4kVW+Y8jJqtLPIk pQEFQMAiojXTQfVW2X7KZo7Zl35cuSOOnrWabzezkYyFrWFZJa mSw8osox3OXIBwc8g1JLOyQcEkI/OKynUtobOm9kZxvhGZSxYkqcZrm4rkyyuAxKFT14q0rgqaTdyC 51KaAId2QoqjLrcgjEgcq237vvVaXJlBrVGXLr0gQbiSrDoTWX catcMGKvhWXO2tqbS3Mad3qzKl124RI9pYfJgZ61jprN5GgYTO QpyeaUnHax0uLtds3rbxLKSCkrDBx05rN1PxndgIA2wZ4965LJ 7GilJxSOfbxlfyrt8+VQDjrVabxzqi7FF7cJsH9/qac6EXoVCbOw0D4yeINLESJrWoQKMbSkpGK+zfg9/wUa+K/wrvrRJtYm8R6HERuhmkywX0Bry8ThLu8NGU6ibdz+g39lH9uj4 b/ALQOnW8NjqttY+IFUedZyOA4Pfiv0MtL15dkkUgdH54NXh6qkr PcS091nSW8zSDGDmrYbJxg8V1LyNExxBOOMDvUMisRnOKqwr7G fIcEnHFVWPU4FAX7lSR964bAPSsmZDlupHrVJdiZNrQx5I8E4w T1qm8bZ4xx7Umu4XKM8ZIzwMVhXaMVYDGe/FSax2PrqKPAO7mr8aDpQZsnCgdOKeF5XjAoGkScYx1pcAdKDRI Y/Tp+tIoHGSKCXuQTTRxgnIrHuL7nG4/QVlKRDZj3F+sSGSWRY075NYC3Wp6xKbfTYZEhbgykdvao30QLs dfpXhWzsiLi5H2m6JyS3PNcZ8TtVSy0ySNXCZ4wKuaSRU1ofyo/tufF2Xx78bNX022Mk+leEf8ARIsN8u4ffP518Um0lu2lklTmQ5 HHWt8sjeLkefVkrWZqjTUcDerxIpHAFej/AA3tLSGG4EcH2q4cs0fHP0r3cPaM+aRwVYScbI+1vAnwE8SeJ7 Gx1e5sf7O0tY/meVtgOa6bxH8Ovh3pFu1pqXiS2kMZVSlsm/Bz0zX55xdxdOKcKO5+ocG8Dxk4zrrfU4jVLD4V2sENqYdVu1By HEeAK8T1bW/BMNxeR2enX0g6BmFfnmD4mxc5+9Kx+n4vhnBxi1GJ5pqGu6SJf KjsLvn9KoaB4s0KW7lheGaNTLsUt7da+wwOdVLq8z4vH8PUm2o wPZbG60WWG1Lx3JimyCccZpmqav4XNtBbCOffuJJxn/PWvWxmbVYp+8ebheH6N7NM8c8Q3Hh06qXeC5VoIRgFenPWuAk1 Dw7JcooS+Xe2B8vSviv7aqxqu8j6j+wMPyK8TPvb/QrJPPcXweflWC9s4rJuL3w5cPFGVuRzk5FbVM+rRbXMR/qvQfvQidDYr4TuLaOSU3geFemzk1qaBeeFbVN7/wBoSFOgI60qGfVfafEdP+rNCz909nt/EOjyaZHDbW12piYDbnjGM15rqPjPSZ76e2eznE8MpG8dzX00c5 aScp7ny9fh6KbUabZl3ut6eUdHgunBbbnB/Gsk3misFKi5GAcgjoK1WcxV05HK+HGkvcZNFeaKbd2Wd8qcYPX jrVWTVNNkFwWLgAbgcV1RzS8dGcEsltK3KYtzrFoCiDcQny49a ik1kzWx8hnwo2jjitJZiuXcmOR3m9Nj5u8a6opvmiVrgSNwxxX DW8KSOGdrjntt614lTM5c259LQ4bg0pNHt/gJ7aL7OsckoZj82R1r35LmzxuLSfKMcjpXbhM2k42bPHx+R2qP lQk11BLEGVJGGOeKrpcRJEqm2kbeCBgdq3nmavrIzoZD3RD50i BRFazhm9AaoTXVwhCfZnBRc5xWdDN6b1ciKmQVV9ksWmqQ+RcJ JHIkm/jj27VizXMaMfInKgKc16VDGxkk0zz6mUyjfmRHDfBl3q+7PP1p 73ZMGwyBY9w6mnUxseZJMyhlsrKTRn3rs7yFZIwFHAzxWD9quI 51ZnRlI/hreGJVrsweEu7WEu72J44nVkcgdM4rkrzUI4w0XBPTNX9ZXciW De7RThuI5EPzruIyapu4dipkwW+UD0rWNfW7IeD7oxp5WO2NH2 lV6jjHasxpxEXiLAhuRnvVOtdXuc7wtySOfyXckqQccZrB1OXM vloTJsPXGaFVi9SPZNbnPzXEijfgbUIxz3qjPI03mLkop5PP86 q6uYuN9GZ3mScgsAynj3rObVZoJ2SYmNVBVTmhlKKTsdN4N+LP jH4beKNP8T+DtevNK1a0cMjRPjOOxr+rf/gnV/wUg0P47adZ+BPHGoQaf4805FjZXYDzyO49/avHxsXSmqy22f6Fz1jp0P260u681YpElEkUgyCDXUgbgGG3mvR Vr6DVraDtoxzgZqI8lgV49asrlRSlhznAzWdLAVBqkD2M1lwdp BGKqyruGCOO1FxLzMO4UA4I5HQ4qiFY/NgmqUdCJEc0BaMnIXFc/eQMAcnINSaU2fXEajHA6GrSjAHAzSsSrEoAHB6g08dM4yaC4vo KOcHHXmloNCORgqnJxmsyS8Cgqh59aicuhlPcxLq8Lccketcle 62BKbazVru7PGF6D6msn5EGrpfhe91B0vNblbb1WMdPyr0K2tY LSNYreNY0X0raMLGkF1JyQASegr4s/ab8ZQeGvCXifV5pAkek2UsxPvtOKxxD90VXY/kH1/XLzWdX1XUrh2mutXuXkZzyTk5qPSneZoIZ4mR1J59a9bLKT9mu Y8qrK90zuNM02W+u4oiT8+5myOBgV+gf7LXwBs7C1t/G/jOCCCzSHzYkk+6FySWavF4szf6ng5VOvQ+j4Myf65jIxl8O7+4 +ptS1u7+IWqr4W8PWdxb6UBshWJeWUd8dh7mvKfida/s9/s72FvJ8WPiRoxvb19zadDIJJkU88471/O2Z5pKrQlGjrP8APyP6bwuA+r1oOpHR/h5s+WvEX/BQv9iLw8ZrPTtMvtbhi+Xc8XX86+aPGv8AwUb/AGZma5fw/wCAZXaUZH7rFfntDgniatVc4waSPoJcXZTRuqlRX+R8qeIv+Cg fw6mlk+w+AZI94JGU4ryC6/bn8Ou7yW/gkIF+YHNfaYfw6z9ayn+J51bxIyG7VrnR6R/wUD06LbDN4VleBBxg5wK7e1/4KFfDsSp9q8G3AZRk8V0YzgHiGW1QjCce8O/C42ZFe/8ABQH4S3TyXX/CJTNPKvQr1rmrj9u/4VSsJD4KuFfOc4rx4+HnEUpOTkej/r7w8o+6UG/bs+Gs42HwRKyIcDK1nS/t0fDCORFbwQytuA+7+tdMfDjP3rKehlLj/IYv3TorH9vT4TRCGCbwdLljgYQV0J/bw+EakLB4GllK9MJWy8PM9ba5tvMdLj/IGrlW7/by8OrEw0vwJtj2lxnrXmWpftsyXLTTW3gq1jBBfLDqa9vCeGub VOX2tU+dx/ibk0ValG/yM6H9s/UnBM3haExE4xjNbFp+2HaSzMbvwum08HivYn4b42KvGoeZHxJy yTtKGhr/APDVfhuZHNx4d8kMMZxjrUtp+0v4VvQUi0sRbRyGoo8G5pSes7 nPW40yepduNmZdz+0d4fmJEejhCT1q5ZftA6QkSyDTlaP0r08P wvmPJaUjgfFeVXVkLN8Z/Bt9MstzokLs/BOOa0YPip4Li2v/AGDCI8Z6VjV4XxyW+p2f66ZXypG1ZfHnwTYZmTQER04zjFW2/aW8KqHCaN05PFGH4YzCK3Mp8W5W3qiCX9pbRRCy2+hqm7gViXX 7S0pUm30qJBGMD5eK7qXB2LqfHI8upxxgaafs43ObuP2ltdZiU 0+FCvBNZw/aS1x5j5ljE2OCQOK7VwNJL49Tkl4iUG7ezLUX7Su2dVuLCMk8H aK0Yv2ivDkxaO404Q+YMMcetc8uFsZTb9nI6ocZZfUXvx3NC2+ O/g9ZT51sqoOAPwraPxt8A3KhCrxKT24zWVbAZiknHodFDMsqnu0 Tr8VPh1dRsrXnlO/H3qc3jPwDcqjQawi/L3YVLzDH0lyziOOX5bUfNCSsZ82teEZTEY9biQnkDcOazpU0S9 8zydbtzk8fOK5ZcSYin8cTslwnhqjtTkNtNNiVCsOp20mc/wAVQXGlagWcxSxS7jxhuK9GjxrDRTVjixnAFRP927o5u4s9Wjd nEBkXH1rGuI9R3KDYyxgAkjrXtw4noSVkz5evwfiUr8pyd1d3t q586KeJ3PHHaq8Grm4kKMwI34PPWvdwmIU7NO58pmGXVaTcZRs S6hesTxGu1m4+tZsjhtpO5GkOTzwK9T2lnc814W6uzLnZo5sQu WAHpxmuY1W9lMsO9cBck49f85rdO9jz9FKxktOUQXMq7z94c11/gb4l6/8ADPxToPjXwneXFjqukXCynymxnmssRTU4OJVtW+h/dH+wB+1Rpf7Rvwe8OeIFu45NYWJYrqMNkrIBzmv0is5S8eTjAr lws7xV+hNKSu12LO8HHegjOcnFdid9jbTchl3YOMHAqo67kwet MdtNDOkhOSSM1nzQsB8oyKaJaM6SDcc9AKpNalCCoxmrT0IepF JEpHIPvWDewAe3NTIcI63PqZADz0qwozjAzik2NLUcSMA5waUN 7Ej1pFKSQ7cBn2qtJdRqDgkkVMpWBz7GNcX4zgnJPauYv9Thtf 3s8mxD0A/oKxbM2zLtodW8QyGO3je0sieXPBIrvtH8OWGkoNkSPN1LEVpTg 1qy4RudDRWhqQznbDKScYWvx4/4KQ+Nz4e+EPi2JJCJtadbGMA4Pzda5sT8LSMp2ukz+bZVBjSN1 wzvn3rrdGgjJk/dCRkAwCO+a97BNqNjxMSryUl1Pqb4G/D5/Fuvo7wL9itgWckV+ictzpt7YWPgDTY1lvb+5S0gjBwpIHLMf7q 9a/EvFPNoqpGhLVJNv7j958Jcom6c68VrdJHxn+29+2H4c/ZvsLj4I/ArU4ta8eXEAXXdbiwzI5+8iEdMZNfhFf8AhXxv8U9UudY1+91T U7zUpC7PcOWPP1+tR4S8GqU5ZhV96+kfTv8AN3+Rp4o8azhFYS i7N6vutdF91m/Uq6l+zXerNH56hVkBLDsKqxfs1iGKKZWRoXby1Hev3iWBteJ+E Rx7k1Jsp3H7Nsj22WSA7TsUA8nPasK6/ZxW3vI7WaJWWIbGYYxk1zVME+W6FHGe84s1Lf8AZysVguEJiGZ MIwFVLr9mq3jjR2ZXZweQPwqY4eyN3iLvc5//AIZvtVE8bDa8OMDrxWTc/s8wPIbcSxKZem+k8Otrl1K0tOXY2rP9na2SKOGYKZXG7d7dq5r UP2frG3ubkzYPl8qT06UnQ01NqlVu6TMqP4E2is12zLtQHHy98 13ui/s9QSTJL5mVkUAc/ia0p0F1OatipWstz09P2cRcxxmAx7iu3kcdKp3n7PUiiCIKN4y mf5Gu+eC9y6PPeNbl7xnr+z9byQs7zLEVPb61QT4BqXaJpQHC7 wSOK4p4dNKJ2fWWruxleI/g1M8cX2UgRABS2OtcxYfCwOGVZNk8TYasKlCzsbxrO1jbi+Fy+ bKPMVm9/SuytvhJG8BdWWNQoPWlTo33JqV5LVGevwsihk3SPlg+BzWzH8N f9GZldchsjPNZ1qSWw4TbsyG4+GPnGYx3BzGOhFZ3/CsJBMyliqpgj3qqVLmiaSqWdjTj+FpkBdWGxeMYrRHwmurgfLI hg4w2cfWr9klZIzU2ZOofDK6SGXy1HmD0/SubHw9uAHjVFM6/f9qxqw2ZUJJvQ4++8A6gkrkIrtzj3rnm8F6iHdmj27E9M0Kmiv a20Em8F6u2WMT7cccVVl8ManDy9vMB6Y/I1DgtgVWWphTaTqaSbNsqADOAawLi21eNQiG5XI5INZPDKT2Om FdpXuYE7eIE3mKe7Cr0w2cVWfVvFlv9y5vEK9DuOa5p5dRqfFE 9ChnFem04zY8eMvHti6bb67CtxgGprf4xfEKwyhvbmQjpkkV5W M4VwlW/un0+C49xtPTmubtv+0L40siJZyZCOAp5rRX9qnW4AwntEZx1yK +cxvh9TlrTex9Zl/iVJTbrxujpNI/ao0G/KRa3pMeHO3cAM16FpnxB+F3iGWNoLuKylY7jzgV85WynMcBL90 7o+mWfZVmTtPRndtouk6tDG+la1aStnIUsDmuW1fw9remuDPbb 4iQqMvPFezkvGVOrU9lW0Z85xD4fzoU3Ww+sSW40K6mhtSiSxu 47etee61ot7brhoncqMcjrX6PQleKZ+P4ik1PY4C/nZIJIXby2XHy9utY9tqLsZYtoG3nGa1voc7Wx+8v/AARF+NWqeH/iFrvgKa7lNhdYljTdxnPav7L9DumubCKbBAkUGuOlG05GMZWqM 2Fk7EkE81OjqccnFdCub31A88kjmoGBGSBxVD1aKcu4dutU2Ld 1oF5ELgfNuA49az5oi3K/doBLWxnzx7VPXIrAvBweOKpbAk7n01G2SASOtWakV9RT2HFNZw o5PFJsd9DLuL7ZkBlUVgT6gTkqcDuTWLd9STmJ9ZmuZvsemQm6 uCcFhyo/xrotK8Iea63usO08x5CHtThC+rGlc72KKOFBHEioi9AKkrY2SC igZT1BttpO2cYFfzv/APBVLxI8dn4O0GJg4vr17p03dQv/AOuuas1dGFWWqPxZub62mmUsVhZOB9a7Lw/5uo3wtLUeY2RwBzXp0atmedUpN2iz9hfg34Cj8B/C6bXtRhEF7d2BuFY469q+Vv2gfjPN8BvhbfeL1u2j8a+Mla20d T96JT96Sv5W8R69TEZhUo9ZNRX3n9feGeHp4fLovold/cfiR4M0rUPG3iS78R6/cy3kuoymaWVzuJJOT1r7b8OWelW6WdtZRQpFs2scc8e9f1zw1g oYLBU6NNaRSR/JfFGYyxeNq4ie7bE1+aPN3MY1VNpRf8/hXn0C+VbSyYRoVOemeTXbXq+8rHz2GpOzK6IskiRRH77b8YpJL RZxPczBPNYbxk9a5qsnbQ6adNSbbKccEcaxQTJs3gkcVV1S2nS SFY3VlQA7azWm5bTl7q2MhZopGu28lmdSS9cVqqW8ksHznz2U4 AGMHNO6fzNoSukn0Ou8P+RPChuAXdAQMDr61yXiTy5DcyvGrOp IUD696Ky5Ytoad5NxMiOC1uLa0hWOMTOwDAdsV6tpVrHFIm1AQ ikHjvU03Fs2qx7HoFvefZRbeXbAoqcH3rOlMbxi5mwhXOBnOSa 9OU+ZI8dpq6MO1gSa2lkuASWfKEe9c/rcaW+oHy9nk+WB15Irzm4/cbLnejOC8UanHa6TaRWasxbO5vTngV5tpN88Fzdl0DbiPwrGd3 7zPUw7vE7C2eGW7nkRMARDA7e9dlDJKtglwq7fMH50Sje9wnon cxXkjuJf3jgNGPlAGOla0Uwezwg6nAyOaqUFyuLMpu8lK+hgv5 q3LROSyycntir9qfPeZHAyBxkc5+tcy00R0Sg3ZpmlLm1gO5iW HoelaNlehsRuxRmQHHpzW6pJ7GdK6VyLUJQtpKRsG9utcKjSJM 2U81puSc9K5JLQVOV9zn/MU3sokORgjGKVLeCecDbGQY8EUQ1LqpW5jVubKBNrRxIsaoM54 NI1hZyRbyiHYo6jBrsqNczaMqU7OxyFzpFnNIzvbxoy5A96w7r QrSaALFbQ56bsDt6Vxyelzqk9bs4TUdDsYJHCwKQnB4xVCXRLK eNiYoRIccYqIz0FUWhirpETOiTWsRC8DI5qCTwhp9wo820RMZB IH503ZuyCLad2ZVz4I0h4HLRpleACMV5xqngLR2yI4/MYnOAO1VUlslsHPJrl6HH3PwysJ1WWAPE+CSPf1rlX+Hms2297 CaeMRkAANg1nUpqSs9TqpYtrRD7e7+IXhWUXEVzqCoh6Bjiv04/ZEuvEHxfsZdL8Q2rzSxnEZdeTXwHFPCFKqvbUNJRP1TgrjWtCp 9VxErwZ9ta9+zjr+lQeYmjTNDbr5uQO1fLfxB8K2mlWkhvbGax kjyCWXA/WvfymvKVFKa1R8dxHhI08VJx2Pgnxy9m19LHaXcbRIeg7k1ykR kVXmZlJ4xtPvXtJ31R8+0j9MP8Aglz4kfQ/2lvDamUxvqZMZA4r+93wFdG78NabNncTEOamcbSsccn+8O0bPb FRZb3NF7aG5LuK4ySfSpkYMMU7lpoV0BXpzWfIhHYYPWmmD6Mo XCllZU+UkdazoBc7W+0bOOm2plfoDelyGUg7uhrBvIyw+QAYqh RbufRsYbpg1YGQPm6CgkgluQnCjNY11flcjOT9aylIRyOpatFA czuS7fdReWP4VVstH1bxE4aXdZaf/dHf6nvUxjzPyGz0vS9EsdKjVbeJRIBy3c1sV0NmsY2CikUFFAG D4kn+z6TdSZIIU1/Ld/wU48VQal8XtH0QTnGh6fuKg9Gdv/rCuTELWPqjnquzTPxv8W+KJBqVpY2+9snOQe9fo5+yv4B07VbO 11m/b/SHC4VzzWtKpZuUhRhfU/XfRfDsfi3w9o3hW7DWCNOkG9zhTHkFmz9K/m0/4KqfFAar+1ZJ8OdLkA8MeAwthZ7f9W+PvEfjmvxLG8NVa/EdDFr4btv7n+tvvP3rCcQwocP1aK0ly/nyr8mzD8DWNlZ6BarDjzAmXb1Jr0vQp4lctGzkW3TJr+k8NK9r H82YlNxfc3LyNbu1uDPtDL0xxXA3ULQ2k4WYmGbgY6VWIkmYUL rQz7W6QTJBu37Uwz5710F5EDbRBiFDDGa5+ZPQ1i2k/IwtTumS/SEbXjEZxz6CqblkjE7O2HXHJ9qybTi7lU3t5nHtP9nhumQPvXn 8+lcbLcC41i3a5A27M5WiEVZXNIyUmz0XS9tvZKVIZdo5zyc15 Z41vkyYopSpJx8vYZ71rUlaDUhQbvoQ6K8aT2x85mBOcntXtuh yRzXG8OTGq5weanDLew8Q3HU7dLlUjQKm5U59hVG5szdwoN5G3 356V6lRXSPPqdzDjjKRKrS7Y0fHJ61wHiq9/wBIUJJjYuD715tRJI7aM5RexxcUqT6QsUwMnlktk1xKq6T3LNG Crc1yVY3SZ302ouzOn0+SRnuWQ7k2YBXk139leKmmWMEynldpO eT+Fa4dc1zmrS1RkXUKtO0kKF1DbfT61K9+kViDFhXBOc1dfRF 01ZWMF7oM5lmJaR+ntUlrfKkz75wdsgPHeuOpE6VK+vQ6WecTW DyJIplbsetULK8DXMSyMu7yskdCK1hUdk10ORKVtC8LhJ7WSMk/KO4zWBCpS6iYH5QcdOvPNKvtc6ElrY5e5GL2RgQCzE5p8RdEWR UbL+9Z07WsU4Lc6W6ctawqsedqZJx1OKwPtaxIzyBiCuADVpct znjFXaRmfubsmQthiRgVkvckBoULKITtLfjWEpO1jpUub3TjL/YWmjYsGY9B+fWuZvWe3Zgq7pQcnsKx0N4wexHbGOWSFpGMbjrT 7y8QxAR7cK2W9cVSMJXvcw5tSjuY5GYeXz68fWsF7dJ3LxkpuF W13FJ3ZI1tlI8Io98dapOhHCKAqv1Iq7q2g4y6A8lpMhW4hicM SAD1r9M/2EdR8K6Trmm2cBtft124+XiuLMa/JQlM7MvTdePqj97rfX/hnLp9xpmtajYW1wsWyQyYxn0r4X/aV+DngrxP4S1e80G40y9kdGMbQsOtfnnDfE1OrNqOqZ9txZk1W hKKqI/ko+MEfiDwF8U9U0uaWWS0hkJ29+tek6Rdw3ul21xtGZ+SCc4r9 IhOMo6HxNXR6H2n+wvq/wDYP7Sfw8uPN+Sa62nPvX+hT8GLtL3wXpEg5/dD+VKqrTOF29oj1llIGB1qqykHgYPrSOvcQE5wRU8QKkDHWk2U mWeufeq00ZxwetNCepSkhJHToKzZiFB3bhTEkY87cMQTWJNJv3 KxxikilufSzSxx5zgN6Vm3N8qg5YAD3qW7EHO3eqBVZjIEjUck muTbU77U5fsujxNLk4MpHA+grGzbshHZ6L4OhtyLrUibq6bk7u a7lERAFRVRR2AroirKyNYx6jqKZYUUAFFAHCfEG5NvoNxgnLjF fx3ft3eIpdc/aJ8byRzBo7OZLcYb+6vP6muefxowmlfU/NHx2upafI9zbo32mKYbWx0B61+pn7CetQ+LNX0DR7q9Hlx/PKN3p2rlxVS1KcvI3wSUqsV5n6yfFr4maN4P0uXQLGe3a4W0dg yn/VjHU1/Ld+3hZ2XiLU28XaXcrNqSAmK4j5JI9T/npXxfCmb08TXlFO7jc/Q+KMvq4bCxc1ZT2Kn7Onj/APtbw5a6dr6+beLHsVgea+krd7azkeRUHlXGAK/W8FKSSZ+P4iHvtX3N6Sa3uoGEcikOQcZxxWFrcMJgtLWzDFwpL HtXoV4pRPPpyblbuecANHqOEZixlCECu0/eXcFpvBVd2QK56cbxdtzdJKxzWokS3FwYmJmj4B96ru09tDLDf QltqllI5NYuzKhfSxzxijETqnIyFHGM+1Y0dgW1m3hMSxsq9T0 x/k1cIyuhzsuZo7Se0nsIpJFUPDH19B714l4gtCRBcQgvFLKVJPX mliY9R4SslKzQtvYFJ0kt9y4Gdv8An616RpGptasUbCnG44PGP Ws8Pe7udFd3ud5pet22oPPbIxcqOSOBWne7ljYo5RnQhc816FO TUbHBVovm3OUla6dohKT5YJJIrzrxK/mSSFVPPUmuKSSTR0UNfeMiCFltlWNdwX5iM9hXLajDdyXF4/CxgciuWo+jO5L3jZ8ORzSJcKshO5QSPSu3ggIghiI2t0BYe9TQ k+bQVWCW411ntpRlDIrckVBrNo4so5IlUsGJ966JNtXM41LOyR yNs0iHM4O9m4B5qkJFivb8SAqFcc56VyzbNoNo1o5pVtpXZZGU sehzgdqsQRKl+k3mNtEeMZ61UZ8o5pt6HRWUQa0klYNk52kd6x ZbhkltrYkqA+M5/wA+tFVt6MUaWpgXzRm6lPykZ4PakjYoQv3UjHHcisoNEy5lE05 7p/ssUiuzkDLZ71yF/enYxY4wMAAcVtOdncIpN3Rh2t/Irysh8wIMDHQVnalqmyNd7Y3Pkn1yeP61hN+6aaJmUstvL508s gAP3QTzXL6neNjCMJPObJ9qhWNFJlH7cV3Myc4xn9K5+e7WRwq P8rN2PSqja9yY7alnyYHt5i0qAocg+tUJpRbtGZVJiC7gMdal3 5mwj1Y261JFgDAgqOfpSi7We32oqiOLJyB+VI0ZkELIszlMukm Tiuj+GvivWPBvjbw/qmk309mqXiLLtPUE1x5jS9pQnDumd2VT5cTTb2uvzP27+MVxe6/8IL7U9Pu54r7yknMyOQx4r8ULT48fHHw7qOqaJZeKdQuLRZGUR zsSAPrmv5o8HcM6mNxFGfQ/qXxvp0/7Kw9anHr+h8x+N9F8SeKteudd1uV73ULqT5mPOPpV/wAPQT6bItjMxadW2sD2r+oaFJRjyI/lGpU1ufVX7OV2NP8Ajj8O71SY9upRrg/Wv9D79m25e58A6KzbiBEv8qdR3mclWKU4tH0gUXIJBIqCWIH5g MVJ07FPaQc45NKPMUklsLSaKRajLN6nFT7ARyBmmlYbTRCyAA4 HuKyLuEFR8maBX6nPTRCNi/II9axrmDJJUDaaEioxPY7jUgmVUhie9cvqOuxwN5fzT3DdI06/j6VjJtMztqN07w5qWvyLNqZNvaA5WMdP/r16hp2k2WmRLHbRKmBjOOa2jGyKirmnRTNQooAKKACigDyD4v3 4svD8zscKilj+Ar+JP45eIZfEXxi8c6nvMhl1abb9Nxx+gFYuz mkceIv0POLa0tdVguBfqkgcnBHoK90/Zw0mfQPFdteaBdz2DRQsx2E4JNeTn79ngK0vJnt8M0OfH0od2j 6K+N/jm50HwD8WtWvLl5b2HSPs8cjNzub/APXX4TeGfGmratpraL4rtbnVdKMxJYjcQua/n7wKoSnj8ZVb7L8Wf0X48qMMuwlGKt/wEv8AM+j/AIVeDtOtJrvWLCN7awRyUjJ6e1fQ8jRBovLjBRXyQ1f1tgr8qX U/kbGuKld9CtLcxGRI0coCeQp6+1Ou7lUuo4mk27Ixk1o6nMtDj5 JQdjk4Y45biS6DFfnJI9a63zAltaKriMlMsB61VKrrbubKleKl FHHSTQQR3DyEMzPnJNZ+o3LfZTI7KwcZIP8AKsMQkmVRaaasc0 s07FYwwEbvuxnpW7Yy263TXEmRK0YUEitaUgxWyViXxBcyWen3 AjmwsxHyk9eK45YlurW0XyVYbh1HQmsK6fM0a0qaki5rHh8QwL LACnybsiuF1Oe+tAI7USuBCRk9alLXQ3px5kjn/hx49lOsX1pPI7Oh2gHivq6a4R4LZ2Idgu4D/GtcNU5tWceLTi0kzkJZ5HdTtEWBkY71y2tNbFmklXHYcfrUTuk PCRd21sc5PMHVPsxCse1cZfr5s12gnYY4OK46qaVz0qUm3ZnR+ F5o4Vu0dWHAx78V3qToggVlUAgn1xxWdBtO5nOPvXbKt5d+U/mSAMh6dwaq3F75tvCQy/OckKOntXVUmrEUINa9TK2KS7fLtc59cVzVyyfaLtVB3TODkj+t crvoa0tVqzUike3tLw48yNTtAI6UKBJNaupZWYdjxmiM7lzg+5 1OitMYLpOJEjBHNcjq0n2S5t0Dly8h3H8amtK+oqN+hSup4hcr wGAPGRVV5VRZWWTY4GQO9KE9DSUW1YgkumNpExK+rHPQ1zWsTL cwyYCjcQAa21ejMkoxehzmkyLm6i3MVi6HNVNReItCkjruZtwI 7YrLnuOM1e6RmSzW8JuXbPlJjnp2ri7m6VpQ6OXjzjCnNRsyoz S1XUr37qFkuYpAyAYK+n+c1zNteRTBpXU7kYBcYq4a6FyVkrGv cSR3EMhjdg55OOlZ018JJoRMN+xcEVMt9RRbQ3UhCICse1WlGS B2qtYJcKqBRlHP3SKUX3Ki+rJ1E0UrLJ1lPQVZEnlT2kqxxo0c ysW9weKmUdGaQ+JM/cnwtdL4h+D1pDKQ6z6XnjnOB/OvxS8bQLYeMtV2RlcyNktwOtfzX4VylTz7E0X5n9WeKydXhrD1 PT9ThdTvZFkia1w5zk5rEe0kErXWw75DvOBX9MRifym4pHrXws u1s/HnhG6R2t5ra9jPH8Pzc1/oj/sf3/8AaPww8OyMQ2+0jbI/3azmryuck2nKJ9gvBkcGqjW7cfLkig7GipJbuDnAqi5Kt0Oc9K LDsWo48gYyuas8AZH8PFCEiFgeMHiqjhTlWIzSDUy57ZDlSKx7 uzBQeXgEVRcWEE+q67M0GlRyRQt96Vh8x+npXpOg+D7TTQk1yq z3PUk880oQa1ZnHVnagBQAoAApaZsFFABRQAUUAFFAHyr+1Fr6 6H4C8TXzuFSw0+WUk9sKa/h/17WpLvxBrGokhjfTyN09STXFJN1lbszkqJtl7QZY4dLWZxkqWL GvsT9nOzt5G1S7xmS3CoufSvD40q8mVVn5H2PAdFPNqK8zi/2zdZi074M/EC937W1fUUtI8cZ2gf1Ffnj8E7KGfQZTeWkc3mREBiM8nvX5V4 CUl/tc13X6v9T9h+kVU5aWEin0f5RPddEt5dIURxELbzvymeld5Neq THDHgx4JI7mv6ZwuiP5YS5tzgtT1Mi9V4HKAFV2ninNrUnmoJG GbjOQeeK5aXxs2iny2sWLOSP7JL5kpLsMAZ6CuqmyLc7GUlE45 9q6pQaSsYN3bRxNwC9vloWkJcbRnjrVq/t41SBps/v8AnbnjisXNO3kOlyr3kcs5LyQOFzHHk59e1V/ta218VkVzjkjHFap6XNFTvoTarq0GoLKjKQsSEEkd8cCsLQbua L7OxYnLHGR2rlcryujpskmj0O7nlntFkjIJDBGUDr6VzUwia8e 3uYzuCHOTW+sXZnNSlqkcZpfw6trPWzqyYVLtw5w3b/Oa9XutRhjZI0ldAvC+9XR+CyM6kXOzfQhlZpZEdgGhOQKpXcEU tvMwJlc9AaTiXQjyqzPOtW2xzohSS3ZhgBhzjNZENqzTSmTG2U 8+1ceKve510Wk00dHaW4tGuZDtSNgMEnBrakuEjWzZ2UM45BHb FcMG07o1qQcr2K4kgulnVZFCrnIz0FYU96bZNhO5B6muupG5jT WiS6FqO6tzGqruUsce1YV6GtzLJHBwWUL6VjKeptSo2vY3bLE8 d4sy+Y/UfWmizlW2tpo8byMEelY00rij3sW9AuLqBr6KbJUsevTFQa1ZJ czW6qu1lcknvn606qasKmre6tzn7xPs9wu9sAHI4rMmmR0nflX ZSeelJy6I3qRu7IyBI/2NJdoYshP5VjS3CSoqPuUBemelaKprYx5HfU5N2EQuSruqtkkV RuJluBEFL7lUqvPT3qVIcVrcwb9bvy3RS/lEcnrn61zE0bpGw7Z4pRTvcpxvqwKtKrKyhSFBrjSs9rNNNh1Q HK8c1Ud3YzTau5FiG/aZRCBJ5jnPXFaLWJdS5AzGcZz1p3uaN9yj508ZaNQzHcCAfSt2 3fEKKpOed3t9KerTuRDZIuxoJrqS4TLny/l3CoNakjgtbdmyJTyaEtGbO10fr5+zt4lj1b4S6TG0gJS2MO78 K/LL4trFb/EHWbVwViiduPU1/MfBE5U+LcRS9f0P6241arcGUZdrP8zySaJ5JBINyrtwoNW7RlV QrKN0owc1/TcU+h/I8neTTN3wjM1trmmOjAObpDvx/tCv9Cb9gDWRqXwd8IOX3FtPiyffaKis/eRz1Ek1Y/RHhhnAORTdnPtQnc9BO6K8iDBGOcelYU0L+YSo6GlFkJbokjVl +8akBB44JFNC6EbDJ4Oc1XeNCdxHzdqEhryK0qDtjdWVc4UNz0 plLc9bsNOtdPiEdvEsYrQpt3HGNgopFBRQAUUAIBjuTS0AFFAH 5uf8FCvEv9ifA/4k3SOI5F0ySJTnuwwK/jev382OQopeSEsCR71w3ftbo4q12nFD7a/CWEdrtcSMoHNffvwC2WPhk6k6ZknYs30Ar47xJxPssoqt+R+je F2H584h2R8d/t/+NoD8MvAnhC1Lfa9X1B7y4x6c4rxb4PGPT9AjSVA6pGPf8K+Z8 BMMo5fWq/zSf4JI+u+kLiOfHUaS6R/r8j1m+uYFEMyKzDcGIFLY38El0F3EBVYkt15r+gk7O5/O1FOS0ZwviMk3XmQ5YmTAOPaoEu9trCJTulQBRk15inq2junTb 0vudJp9tI2fMYqo2g+ldFcSb2kVXw8S5UCvUjJezTOH2idTU5a 51C5EUYuS0RRwR6VoaldJM8AlLGKNTwvfiuRK6NuRcpysOqRGW +ii2pDCQFJ69aydVv5Rcbc/uWx25oU3Zo2jFJ2fUqSymTSbjycu6MduOa0dK3w29jC+1Z9obj pXFGTua1KaSZo3+tzwJMsilPsEgPB6mleY6pP9uWNkjkj3HjrX VGbcjlprljqieyv28y3VWDOAcqemBWTq7TPJvjWQtK3Pat6cmv eRsuW6N2K9mmNugVQkSZINTXE3ncoQhhPGa1n7xhCm1Js5bXLa bUbwTF4nkUKDkdBiqthauVubiVl4GVXPU15uKvJOx2Relok10z SiYFcR7RjjsKin2qltIzbkAO3HXpXEpaG9NaWRg2s1y7XnyuYy cdO1VL2WadNttE7NERzitVUVtSVG8vQuWdnqsmn/AGlraQhZAMhTxWj/AGfqMkqL5D+WWUZI4zWF9dDV6anS22lz2z3xZPLU84PFWUjl+x WqRABl6j0qHKzJ79jD08Nb6jdrkFnAGM1o3wmlhgyM75CASfWt qtrJma0l7xyuqlYrlvOwTjj2/GucuWiUyFcfdJ61EkaNNu7OLOoeWYo432s0bYXOagVmK27uVMj qcim+6M53uYl5EUW6IViGHJNYdrcNDGzsg3OuAv41UVfVCc9ma yz207psjWMqvPHBriNbdF8wIFV1k5OOnNCVioxtomOtLBWWNmd HymDuNczqOniHezSLJvPIz0pqzVyJNWTOMYmK5baDjdgYrtY2u LW1glBWZXGWXOaq/YvleyKvN2zSvGUklfLDGK0IZYclFCp25ak9RciunYvoogkyMFF TkjtWRrVxbyWLu6+Y/YDsKbNE76s/Q39kvxJFc+BbeweQK1rMQee1fKX7RNguneO9TuI0CiaRjn09K/mnKKbo8aVJP7X/AAD+rcY/bcER8l+R4BbSNMrkhiwOMjkCoJjh3ZWcgcCv6WSZ/Kkk7F7TLuWO6tpomDGOUMNo6c1/e5/wS08TLrfwM8FyMQS1goBznoP/AK1TWepyVHe1uh+uiv8AKvTGKlByM1KZ2IifB7cGoCignIzmgO hBJGg7EVnSggkgU4vQSfYhEgP3jzSORweDTZSelyBsYrOugGGM A0yl2PZKKCgooAKKACigAooAKY52o59BQB+J3/BV7xW2lfA/xJbCQxtqd1HbjHpkE1/K9LNsju2ifaZDkjrzXBTdqjOSLSlclcTC3s38oGaR169OtfoF8 Mrs6Z4FSSWP5jAWXnua/NfFyu45Xy3P2DwXpOWaKT6H5t/8FBPEdnP8Sfh94YtFQJpemqZAuPvE1F4Elj0/QrTB3DaAQWxT8CIuORxnJbtl+PlWLzrl7RX6neSambskRtjC4w OCKrW955FyHkRVkePHNftqn7t2fhdONtDBubqKc7sllQs/oM1XnYi2txsDIzjp3xXBzas6VNctjqrKeaVCsT7kiYEDvW9ul3 SOsZLGPHFepQkuVpnn8l/eOO1V7ia3gWY7FWQAcc1mXOqm1lxIpWIA5JrnjPlTaOxR5kZ9o jTJczxL887KME+pqt4mju1mghCgOU5rnu2nYqUrTsyvok8sOj3 AkjAEbENntXQafNKDbzhUkKjlfQYrOMbG1f3noVdYnWQXTsSFb qD3NbVjJGLezRQVtohtY9M05SfML2WiEuYoobhViBVnHXOO9Yd/cyqJAJfMd3wMHoK7VUvE5mnb3dzVsdSAuo7Z4yJCoBNb9vDcXf mpb2shzgHjGaJ4lcouaXNyo0B4RvrmQhVKOfvcUtv4B1JWISCe RS2OBgV41fHQu7s97C4Gc7JI6ceALuZ1jW0AjjTbz/8AXqtdeAhCtqZzbxCI4Ir5fEZwndRPpqHDT5Pe3Mz/AIRK1xP9nmjUlySFHaul8H/Dez1PULeNjKVu5AoAXgk0Us4jOagcuMyb2UOc+nx+zlLouhalA La4jlnlGwvGcdjXJReANK0bSJ4ruSK8v0lPyBcEHsK66eZc1SS XQ8SeElGCm+p8++MtF1XSr28uJtHkggcbVOMkDr/hXl/9rWttboglcSgnKEdDXXRrKzjLczVJJ6mKt9HJfzE4UsuAfWtRN SElrAhIDmTIHU13e1TiS6dnc5DWpCbmRpHGAuf1rg7vUi2/zcrHsP4Y/wD1VSd/eMVO7ucr9oU3lpLHGzB0ZSB2rQhW4a2jkXBk3EYPHeqfkZ1I66 MqXrSC2u0kYRNHkNuHXtXI6fehhtkK7yh2Z6Z5FOjJoFG6sy1c r5dxG8XMqrjjue9YssCyvdCdQJJDhc59abkPrZFOZX0yWDMqYc Zwe2K5ZbwzTAuxVGJOKd7qxN00Ys7bJnVkUhmHJ7Vuw3P2NFiI E2/kegp67hDubsEkMsSkhcgdv61HLbxSSkwHB7jtST0uEHbcvJFbr EkRLkYO89K57U4reKB38xARwq/5+laub2Kimpep9nfsa3NhqFhr+g/aPKvoZRICTxiuL/ax0F9O8QF0O5ZHUo3qDX8649qHGKt1t+R/VeQJ1uC6i7Rf5nyqsDxWzSqvQAnnp+FY8Re4kfeF2g59q/oqOrP5XqPsTxW7WiIoEoZzhnPQ1/bT/wAEb/Ea6h8EPCUJkLGCMx81lWWtzkrp7s/emNwUU9Rin+ZgUlvY61sRmXB6gZp28Ecc5pplc3QiY8Hj9KpSc ds0kgvYoXEYJ3K2DUCvjAOauwPQjZ8cg/e61WlcEelBUT2BfuinUFJ6BRQMKKACigAooAKr3TBLaZicYWk2 Js/nH/4LE+JceEfDWhpMR/aOotKQD1Cg/wBcV/O/LbSpDAS52yv1FcGHs6s/kYxS3Z2NgkWqS2VpCo8wsFUelfctjYSad4ZsrWdvK3LHGAR781 +SeM1RLApM/cvAvDuWPnJra36n44/tT3y+I/2j9ZCss0WnBLdQOcY//VXo2hM9lYQxYbDYAUj24r63wmw3ssjoo+V8aa6qZ5VivI6PT7y UNdTSY+U4H1qyr74naRwZCeSRX6PdqLsfldOMYu7M6+IhIQRNt aPA55qOed4TpyqQ5lbBUnnpXLzvmNFFJcljrtEKSSMbd/mydwziuqE9156xohKp1OK9mi4tWPOrX5lFGbrAillT5RGIGHGO tcNr8a3KOYVQHAzjms6sEotnVRsN0U5t1RnDS3Fx8gPfAra1q3 DyCWV0ExHGa56UW4mdaXLOxy9pZyx6dexOhw02TxitCxhuWQyA qkKLluM+1EaerNpVH0K2obHDEssqSkHNdr4a0H+3B9nO+KCFNx YVwYqqoJykddBOSLur6XM10thY200kcIy8pGc1R0/4VeMPEWZ9L0+5ng3BRIqZFc9DMIqDnfQ6YYKUpqnBas9x0j9n+/tJIrrWUFsQucyHFejWHg/w5o8KxMWvpg2SEXg187mPEVrqB9lk3CTm/aVFqdS/hXUpon/sTRFRpe+3moLbwZqlvlNXvrTTQ3J3MBivhcXn6V23qfomA4e00 jobS+GfAdjEJNQ8c2AZhkgSiuC8S33wL0hGN740tJHj+bYJAc1 8niM/n9k+oo5BFL3tzxvVfjJ8CtF3G01CG5VTgkPmvX/gL8evhPrniHT7a3t7cpaThwR7HNaYXMq8pXPMx+TUpw5ban69S/GbTNT0LX9S1HwpYL4d0i1Lw3LYCgAck57/AOFfnR4t/bQ/ZQ1rT/EYTw8ll4ttZSsLIMIzD+LPSvrMi4gVer7NLW2rPzniPhaphqXt YvTTQ/Hv41/to/2h4n1u3s721sNJttyRrnOSfSvFdC/aE8L3wD6q6PNKcI+eh9TX1VShW9k6kH7x81hoUm1BrQ9Q0Pxho 2ruJLO9gbcMDB5wa7eC6a3W2ZyWRWzkHPFb5Zmja5KysdmZZG/ipaoy9dm87zZ44yqqM8Vwl1byTkMhYbUP0r6SNeOyZ8xOi46WG W1iTqFmAwxEMEZrSkiVLVHVwSsueB0FXVklscjWtjk729R0mgu grKz4B7nvXISWkkdzbzw/6leAAa2ptWQpJWsbsAEzKEdZHUgPkd/xqhr8b280twMOFyVxUSWpMY3OTnu4poluJiTKw2jJrigzJPLNu VkJx9K6FuKcbrUxL+6mE5Yg+Wg4K1oRyyy2+RI+ZkyDnkfhT0H Ja3Rd02+kgUI0pZHGPxraN1ny9jeXGBkEdaVruxUkjdjvVcIPk IAzz/hXF6zcsspZH3qRnI5FLqRHa575+yx4ot9H8dTQzycXkeTzjJr3 L9q9Ir628PX8EnmNKCGA5+lfz7xdSlT4poVrb2P6i8Oqyq8K16 PZS/G58RxS3E1rcQoCzA4JFZtvE0Bk3RvK27HFf0FTl7uh/MmIauy3KTLakxyZKkDJ61/XJ/wRG8TJcfC/TbB3w1jPs69c0qi2scGIfNBSP6VbaXdFGe2MUkryfw898VN+p1 rYWMv/ABcZqMSXKybSoaL1q2ilcmJJ5zUDEN14oSsCVmQSgbeByKzWB4 PNMBhIKc7eOtU5mXGRzmgcD2ZTlR0p1DLQUUDCigAooAKKACsv WJDFp9y4/hUmk9hPY/lJ/wCCwPiB9Q8c+CvD0JOba3kuG57lgBX45FGja0tfNG6JcsetcNF +/JmDloj0Xwbp8V14n0SKMuGeUcgV+h+raP51poMLoq+ZJvI7AKu a/BfHTF8tGnG/c/pD6P8AhVOrVm/L9T8AfGF/Hr3x98bzFxJF/aLBc+m49K+nVtLFLG2K5BbnkZr9W8OLrJcM2re6vyPyfxVmp57 iGujM1UMVneMymMysWUVFbux2CWQhn4xivu5vTQ/O1e9iyfMF5ExUSiTgn1FPvbNri/geJNrWxLEe1c+t0zpTaWptaErQr5iDczNyMcVuG9lS5dYCV3Ak gDivXoR0TR51abvZFa5laVUWWQK7Elia5a/hmUmOMhYWUEnpRioaFUJRuolvRbF0ktbv78MSHHPTJ61e1NfOd pVc7V+VcmueiujJqpOepkWYm+x3G91Ks3fnNbdo6xi3t0VTHKv J7/jWsY2WprWT6GT4htrUPbC3EizO+1zmvoH4Y+E7zX7/AE/TrA7IrjaG29TXzXEEUqL5T1ssjzSs9z9WfB/7Ovh2+tdE0a/0eGOa/AWS4CZY163rvwz8N/DHw0vhXwP4TuNR1ieQnzpIc4PtX5zisxqRj7Pofp3DeUxdbnZ8 w+LvhXfWIk1/4h63beG7BE3mOeQKenpXxL8Qf2uv2e/hVLc2li8fiO+tjjcpBGa+bxmMm/cjufpeX4KKTkz4I+JX/BU/VY5blfB9nbafbOuyPaM4zXwZ40/bh+KfjK6nmm16/RZc7dr4rpyzhCriHz1tDzM64xw+Gg4U9Wjw7Uv2gPijcyJONb1 Mgno0rYzXNyfEb4g63eGW41S7lnmGeXOMV9xQ4PwkUly6n57je PcTK7i7CRa/4rkYpcXF0UVvmGa/Yf8A4J7eHB4h1TfeymEFctK/O33rxuM8uhh8BKdFWPc4Eziti8eqdV6H6X/taeFPiTZ/CJ00X4lW2m+H5E2m3D7Wm46cda/m18Z+JNW8N3N5Yy6mbi6WfARcnJr4bwxxMZ4iVNq7f+Z9n4sYJ rCxnTVknqeJa9omv+IZ2v7lJGV/mAHeuJ/sXXbFyV81dvQHiv6CWFjycnQ/nJ1nzXidDonj7xL4YlikWaYAc8tX1D8Pf2pmg8q115fPjGAWbr/nrXiYzLWleJ9Pl2eOK9nM+zfDni7w147sg2l6pBFMy5KE4NabW NzpjBLpAyDIBH6V52HxjhPkmenmeSqpD29Ew7sxQ3sUyHlfvdq gunf7GjwglmbcRntX0UWnqfA1qS3OAeYzXlxBOCp3ZIpBus5Yy 2GtgDkeldsFZGMl0Y+S4hEhMKgKQDgUaqyTWkkYEjbhgnv0qW7 OxjBtM8p1IvCEIcyMeACfese2jln+0GQ7FR84Nbp6GnkZBy010 gVcnJwa1RAY0iZ1IVV6/hT82NOxjQySJ5ayAqpz+NdTprhYhAygqwxmqZLlpc0BCpmAjfa rHBB6msTWS0Iji28tx17UhtNXSIvB+ty+HvE2lT2zMrlivLds8 19t+NJ5fFHhmze5XcbSPzOfwr8f8QsHfH4asv61P6G8IcU3l2J w/df5nyTasVuri1QgxibmtKcBEMcKq0jE5J5x0r9Xw75qSfdH4Hm NHkqzT7nMtvaZs7hufJA74r+nD/giT4gaDS9S05n+aG7XCk+1ay2ujy8RZx0P6v7GYPbRPnqAa0A4 bpUrVnRTeiHkgc8VGWIOeoqos0iAlGcUhCsCc4pp9Ba7EDAZxm qcoUHkYzVjb6FZ4uCQflrLnQ9OxoTHDue1RknPoKkoKgFFBQUU AFFABRQAVzHi6f7Pol4+eiGpnsTLY/je/wCCpPic6p+0XeWUcm5NGtI4sdhySa/OfTsDz7ycMwc4FcNB7yRzUp3Vj6A+A1pBrnjrTVdCYrc7gD1GK/Q/xZEljp15eDbGuj6VNcMT2461/NHj7Xu6cH/Wx/Vv0e6P7qrPz/Rn8x3gnWW1b4oeJr6Qq7XGoO2cdsnvX3BauJLK2lDDJBbHpX9A 8FwUMowqf8kfyR+A+IUufOMVJfzy/Bla8ikuER4JFKRcEZrFhCzSHc/Kt37V9bK9kkfFq1uU1IYPKnwCzeXgLjvV9riX7UQBncu0g0Km7 amcZPW5saa7W4O/aSGyT2xW0lxFPqqBCjFoiT+dehh+iRzVUpXaOZ1mQhGkjyHZu/HFYNs8xWdpgCn3QM/rWGMnJK0jXD2vc29MuIltXWGRmlMmAvoO2aqXUDbDJOzRlcjHb JrGhL3NQqwSkUoEFrbMsTtIQc/U1Zs9YjtLZw4DXSkqTjgVrOfKrFJOa90q2kGoa7qlvYWcMt3eT SYRVXJLGv2p/Y//AGfH8MaNN4s+Idk8F7BEDbwyHB6elfHcUYz2dCz3PseE8snXrX 7H6a+FvEvhl9Mj1NbGTTorAeWJHTADDtmvmv8AaD/4KLeEf2e/DPim7bwdbeIfEghMdlMcbEPqxr4fETU6C5NWfa4GnKni+So7I/kI/ap/b7+Lfx38UapeXet3gtrpziCFysaj0AFfn1c/8Jb4huZZb25nYSk4yxr0+GeHvc9tX3ZpxVxck/q2FeiLMHw3v5yDKrui888Zr0Tw58HJboIUsnxkAkjivvadFJqx +X1q85y5pHT33wYukjCRWoQJzk966/Rvg35ctrJLEkcjL8vHB45rScUY8ye5or8KIGluVkQLtckHGO3F fa37IreIvBfie2GlWguNOD4uM9NtfHccQi8DJs++8OMS45lGPR n6uftI/EP4SX3wrs9OTTI7jW2hMkkhkOI+K/nI8R+EdM8WeJ9RvtLRDGJTgE+9fkfhVRazGTitLH7R4vVpf2Ze b6nf6P8AD2KN44buBBbqAAMdasXXws0LUZLlY7dEXbg8V/SF0tD+TpTtseVeKP2f7K6gkazABPI4x+VfK3ij4M69o0s00EMq hBuXBqnZ6m1OprY4/RvGfizwHqVvLbXNzB5XJBOOhr9A/hF+1FpPiGK10nxPIsVw2BvY5z718dn2W80fa0z77hPO1H9zUej PpO9021v7VdU0q5W6tZBuID5rm7mGeOMbJDGzDkVzZPmSnFwe6 FxPk6pP2kF7rPMrm8uFvJQjb2ViSaty3RuIXDjAVeRX2VN3ij4 Was+UrWU8fmxxM7Acj6/SrV7qMMBkIdVV8ZyKuzurmMYvS5x+o2xnRLmPayl+nSsqaB1N0 HRcJhif1qk0W31Zylxask91Op+ZgMc1OZGkhgaVmULywzVKSZa 2ZWkszsW7BcnnaOnvWhbz7B825S3H0qyWlfmN/TZllDGQhUXkc1X1JPtMxAXOD8vHPtSeiFK9rnKfY5INT0+RVyw mB5r9ItD0r+0fBySrtkR7YDJ57V+aeIzUKVOo+jP2fweq/va1F9UfI3ibw8dI8QyBI/Lj27+O9Y9xKGheOKIq+MAnqfrX2HD2IdbBQmmfnPFuEdHMKkPM 5bEkVyC/SMjOa/fD/gjT4wt7LxTrunSThJZJUYKT29RXtyhaFz5SqlaR/YpomqJLYWhVid0Y5x7V1EFwTjLLisL6HRF+6i1vHHPWnb8gdxT i7FJ2ImXOTzxUYkKkDJP41oirdx1RFOvIwKoTempDgKCB3FY90 wyRgce1BUWz2dAcZ461JQOC0CigsKKACigAooAK81+Jd01voVy AxAYYNRPYio9D+KH9unWh4p/aN8e3UeZY7e7MQZf9gDNfIZS5FvbsuWDMzECuPCOThrvr+Zyxd j6c/ZTBl8WXEsqALaoTX2r8cdeTRPhH8X9ZJUGx0Q26HOMMwP8AjX8 rePE+bGwgt0j+xfAShyZfKfe/6n80Pwh0+Q6jf6ike8zuzZx3Jr7Ht76eHT7SA7UOzgn3r+osjp OGBow/ux/JH8t8XPmzPES/vS/Ni3UjQo4jdiYwMkH9abbum6HYpd85PY17kn1Pl1DWy3Nm0uWhu maVQUJ6H1qu80j3bTZCIh4ANbKDskKTszsdPkjEBabhZfmIzmq kbxx381xtC+WpC8110ly6s5E+aTaMHVrzcpRwcqNxO79KpaXdJ d+fwTg4HpXJjJ82rO+lBJF2G9igsY3ZNkhcnOc96WW5Oo+bK1w gWMDaoqKE1a7MJpp38wEieW8WB523huwrkbe3url7SxtYZbi4u Z+i8k5NZ1p2OjD03e5+wf7Jn7NNl4LTTPid4/gTMZ8+OJ15A7cGv0zPgkfEszeLz4pi8KeD/DcRvJpXcJGqAd89+K/HOLcx9rifZp6H79wTlfsML7WS1Py4+OX/AAUd0a8uIfhN4HeA6B4evGEl6nEk5BwDmvhH47a/qHxd0w2WZJoblMhuwzXlZZim4NvQy4nwyhXsnqfmXqXwCudDv7 m2kh8xiSytxV3QvhZFa3BF5GIVY5x3zX6/lFWM6KlE/HsenGo0z0I+CtPt5Qq2yOkQ3ZOD9P612ei6bHbWxjhgSMFgAdv GK7qjPPlK61F13SysARFiBOM81V060hintJJQT5KYPFZP4U0XF 6XRympXjefOqqqxhyMV+g/7GV94Ju72ay1aG2nuLk+WscjAZ4r4zjv/AHCSPvPDuN8yi0fbP7VHwh+HGi/Cu18QW2gaib28O35eI0Ffz96nNZaT4hvbawsmtLGOTLAnmvzfw mrVHiZJ7WP1vxcill8XJ9f8z02PUbO8FpFbKhWMAsd3Jb/Jq/ZW6vPcgZ464Nf0FGdz+YYySuVr2EvEixtgZwxJFcdqWkWsyXaX ixzqRxuFVFdGSk09T5x8efB7SdYltnslWGSVScbR/Kvk7xL8Ndc8KutxaxSBY+QyccVjUWjZ20pOM+ZbnsXwa/aI1bwjf22i+IJ3k0+chDur9F7O50fxdpEWtaHNFOWTO1W9R/8AWr80zjDywWJ9tT2Z+p5ViY47CuhN+8eSahpey5dQrJcFjvzV CEutxNbLGkgHDH3r73AV4zpqUXc/Ocxwzp1HdbEF5Z/L5oPKkdO3tUdwou7d1k8psYPzHrXfTv1PNje12VTE8GUfAjQhs Vn3sMVxJcHztgeMMVz0OO1TJK9iHqrHDzrKhZedjjgn0qDyrho ly6MhYE5raKKgdJJbHy43QhETg5I6VgXKzefcMdqh/lAodhzt1H2E9wo2qNwIyM84rpIrb7SZ5iwXYuevU+wrVhCKa5T I1OKWGQyqq74/mBJ7V+qH7Pfh9PGfwu0eWEjzJG8uQ1+VeLdb2eWc/Zo/ZPBRKWbum+q/yPmv9pDw3J4S8VKiowjQeXj196+dJr5Z7VY4tvmSN94ccV7Hht jPa5TSmjw/FnCewzmpG3b8jCmlKlld1O45wR/n2r7j/YF8f+KvBPxPn1fw/CL+OzAeaBTglc9jX3FRNxaR+Yzjo2f2nfs7ftM+EPiN4b0+C5n bRtYhiVJLe5O1s47etfYFvqcUiLLBKroe4Oa5qc3szVRsa0WqE YB/OtaK8ilAIYbq1Anyrc8/nUTBieGHrVBcA+PlJxnrTtxA4PWqi9NR30I3JwRxWLeKwBJxVj jvoe3dKKDUKKACigAooAKKACvD/jZfix8OXcrMFRELH8qmexFTbU/hz+NmvrrvxX8eXFu7SSy6hPMWHTG414/5zWttGZij+VEWJNcuB1ppnM4rmT9D6p/Zqit4o5dTBaJ7kjOTXWftdeM4tM/Zu+IO+5w+vXIgHPOBj/Cv5H8YlKecwgu6R/a/g3FU8lc3puz8e/grZbraKUxkrKu5uQTX0He253qZQinACkdq/rvCRtTgvJH8a5zXc8XOfdszcKt3KoJwwxhjWuWiVraYBRztr0n K0Tyd9SKG8WR7h/lcg96itLhluJQ+3Ej4AJxzV/ZImktUj0GIwLboBj5VyTWBLfRLNP5alnA5yPfpW6fu3OelJxna 2jMfXpRMYlt1O9hzg9/WqOiTzQ2F22N8gcf/AF686vN2uzvoJrUdfKy2icKo2ZAz3rG0q7ilkh/ebXGTtB/nVUttCqsOqO3E6ra4VUDOCp471+qP7Df7Itp4ntbP4k+NrFBpU I3wq6/ePXNeVnePVCi5Hr8O4R16/LJbH3ne6gmpa3eLeWB0f4feGQI5rhxtjCjuTX4ef8FF/wDgozLr9/qHwg+CF/PovgXTozZym3fb9qPdiR2zX4tWw88TJQW8n+B+/wBDExwlH2rekV+J+VHwkW+1fUop9ZlZp5ZPMXceWOea/UbQtKu77SksrCGLzLhRtkP0r6fOsl9io06a0PyWtnssTOdSq9T zLxh4A1fwvJ9t1i6inkvFyqg814ZcWkz3sgfZ5W7p619hw/HlocnRHzWa141J3iUpbeXz7gxkooAABrodOR300biqmMcEHivX q9jy+pm3axSOY5sneOMHiqGVguYyJMRRj73+frVtrY6Voc1qwg eC4LkZLZyOtfTP7KGkwT+INmnyD+00k/cyH+Fvf9a+O40jz4KR9rwDWtmEZH6KftLaB8cn+Eem3nifxRo7 eH7M4jjjbb24yM9a/n08W3MyavqyXF6txMkhPBPH41+Z+FUYRx00nrbT8D9b8WXz5dB wXXX8Td8HapgxQzMPMY4PNe1aZKoe62MIywAANfvyeqP5pad7F G/uxa2haTD/ALzHHHWsC8RTNKWcbJV6Z59auEvedib20OQuILl7iycsjIh2EY zUV9oFnqmkz2l3bo6PlCWGT+H51nV2uh1JO6aPhz4zfCaTR7qT UNIDPxn5ew+lWP2fPjfqvgTVLfR9TuZmsnfawfoO1eVmuBVfDu LPpeHcwdDERb2P01urfSfFOkw+INIdZGnUOxQ15ff20lpNchWI yvzdq+T4Nxys8PPdH1vF2VrlWIhszCmuVWKGNGdvMG5sD8KM5R GZlGExkHg1+gLSyR+aSVtCPU0LRtKr5MgwAPpXLTW1ylwHjfzH EZJIGR0xTlfoZbamJLE0ywq+0MxJNRusW2FTwV64Oa2T2NEuiN Q3QS3RHUOzHAI5xWZfJ5shNvJ984z3/Khxu7mfK29R9pEEdVPBY4H+fzroI4jHbebE253GAO54NU2CSWp zuqSF0c73V1TDL6V+wf8AwT9kXV/hzd2zAOtjcgAdK/JvGSCeR1G+jX6n7D4HyUc+g32PLP8AgoHpSaL4v09iqpFcRbif wr8zzqCYCRMWj4qPBWu6mSRb7s6/Hehy549N4o1UkjuosGI72Gcjiv0Q/wCCYclpD8fjpV9FDc2uow7XV1yOo7V+tSbtc/D617Ox/ZZo37NngHxF4UsbvR7RNE1GWMESQcc1yM9h8bPg5N/osr+LPDsJ/wBXJksF9jXPWpcyutzWjLmieo+Cv2iPDHiGWPT9XMnh7Vwdphu Rt59j0r6G0/U4LmNZraeOZH5BU5qKdXXlY5po6CG/YYyeK0Y7yN+GIH410xaHFrqOMijkHIpVck8dqtCegpOeQeaqXJ 4+Yimhw3PZKKZqFFABRQAUUAFFABXyh+1VrMei/DvxVfvIqfYtPlkyf901lW+Ezq7H8MfiLUS2ra7fuxee6mf5yec kk/1rFvU+0WpjYiQkAHB6VnhF+7TZzNPmsj6V+Ft1LpmgxlkaFMn7 p9K+ev28PGwg+FHhnw3HP+91aYyspPPP/wCuv5H49ouvxJSh3nH8z+0eBqnsOGpvtB/kfLXwWZ7PSVckPtAX3r3C4la5lVhIhQSAE1/XluVJH8Z1pXm5PzCeNTPIzAKxyMk1xWtXtxoenPNJ5rpBmRj7V 31k+VWOKFm9zmNE8WxX0bsjsHul3IDXYwSGBUmug6+Sc9OprOl Le5tUVmrHpkN0ZIkQgqDGDxxyawQT9ouMsDuYIOen+cVtc44yc Zakt3H5NushMYbcec9Kz9LlSytL6SYEJI2VBriq33PRhqriawo uo7V03BbePcwU98f/AF68702Rv7RlG9ldFzk+uamErIhy+yfd/wCyn8GNU+OXi3TLAWxfStNfdcPt469K/o30LSNL8K6f4e+FWhxCCO1jXzHQcL9favgONcY3HkR+m8C4FqL qyR+P3/BYH9t7w78PtCh/Zn+Dd7BJLABJrd7A3MkpH3Mj07/hX81Hhfwvf+LNUk1DUGZpJGLZPPNZcH4P21WWJe0dF+p38YY32 WGjhlvL3n+h9neFvBdhpVhFLcRhZok+UqO/auxi8ceJdAdE0zUpIIrfkZOa+8xlCNSNpH5LRxF5MnHi/U/El6kmtahJfS7eCzcCuc1a3VL9HiJRGBHHQ0YbCKEeSOxtUqKT1 IXdZZJ0wsmxOTiorV0gtPLfOTk+3XNXNXZEEUL1ggjlJQluccc 1kSqJ3t3JB3HGKm7sax1TuclcwzW9yY7lDLAD0r6e/ZTBs/FEbCdIbWWQmQE4P4V81xU08FK59bwZO2PhZH6A/tK6r8NI/gzdxzar4s1bVbcZW2jLMsfHtwK/mv8AEnidY/EmrJYW1xDCzkqsn3hzX5B4bKUca5JWVj9v8TnKWXfvO6seh+Cb qa51HTZCSgkGT82RmvojR8yteFXYAr1/Ov6Fck1dM/mWS3RVv2Y2lwjNg5DA5rGaZ2vAVVZGKgcn26VVOSu2c19GypOH XMxLII5BjFSxXZaSQSOqx88E8mp5YtaChBWOC8Y2UF8ju0Xm7k 2AdetfHHjv4XvbQvqelK3mwneQo5//AF1Sslc6ISs+Y9o/Zz+Mt1o8tv4a1yUiFm8sbzxX2rrWkpdoNUtf3kVwnBAzX5pjcP 8AVcd7aK0P2PLJrHZa6X2jzO8sIrBYnkUKWyAT2rnPLjUrmYMr Mfyr9Dw9aM4po/JcRTlGTTEngKJExk+YnAHtVCS6FskjIAu3gjrmuiWiszim01Y5 69mhlaFYpFjcEtj9ayzdQuFTblweeOtVGPRlRjYjMrhkj+VgO4 rQeNSked24nLNWqRUl0JrQpA0hZmcrnbjtRd3MtpaJIjneScki ovpqTF9TyPVdSv7madIpZCznJIP8q/YL/gmb4lMejeJNPuGJdJAwJr828VoOWSVrLofqPg5WUc+os6T/AIKYIk994VvYm+V7cZr8h4JYy3kglCWwSe/TivA8CqreT8vZs+s+kFTtmsJ/3TsbCcAbAkgRMjHWvtX9gXVv7I/aK8MTkukMzlDhfpX7RNaM/n+tFuDP74vgrdR3fgzS5EYOPKA/SvWZbWKdXSWNZEccqe9RfsZ4d2joeHeO/gD4L8ZxSTNZR6dfMDiWJcHNfON54J+M3wfuftHhvUJvEfh+Dny Jctgex7UpQUvU6oyurM9A8HftK6JfzLpXiuzn8M6qDtIn4Qn2b/8AVX0ZYa3Z6jAk9ncwzxuMqytmsaNSy5ZbkOJrR6lt+8wLVpwa hHJ1YGt7ktl5ZA3IIwfSo55F2ZOa0TuaxZ7TRVFBRQAUUAFFAB RQAV+bX/BRTxGNE+BXxJuRL5L/ANmvGrZ7nisMQ7QbMa/wn8Xuql2eVFw4nk5OaijR/OiVSSxcACnCNo+VjGm+apyn1BBbzaZ4VLktH5ceeRzk1+XP7av iWXWvE/hTQVnlcWiqMY6f5zX8r+y9vxRRvraX5H9fUajw3ClZv+T8zQ+F xEGkxZYDz2Cjn0FetwBUDN55DmTpX9WVVqfyE5q+qHXWomOUxk Zdud1R6p5V/btbTjzYplwfTJrrpX5UefKykrHALoCw6jaPYFEWE4wBxivQbS3 Dwub1QU3HaDWEU9mdVSd1qdLDPINrAjaMAc9qrXDMyzSoQsm7c fbiuqU0rJmMXrbcXzs2FuJJdyTDp6VTu7qA26RJH5sbOMgVxS1 0O2grxMG5u5o4rhCcQhjuPTisnT7aS91mytrSMvNeFcKPfpXPN 2CNO8rH9N3/AAT9+EcPwv8AhSniTVbWKC81ZfMkdhg16B+2h8cvDn7K37OniL 4i3N5D/wALC+ICtb6bGzfPHHg/MPwx+dfknEeOdScprp/SP3jIMA4UIU11t/mz+JjU/E2ufGb4g6p4l1i5ub6a/ui++Vs9TmvrDwv4Uj0mxR2XGRnAWv0jhzAfVsHCnLf9T8u4tzJ YjH1Jx2vZHoEN3GIhCz5QDBrB1gmUHy8OuMD9K9qpE+XjGKWhg 2MrRXkQLqpiHUHgmuqu5ftPkuxLxoThh096qDbRCndpMybWaM/bJCIyoJFKXVLKNtxYrx71yte9Y1SdtDnrySMzRbuCuVA96iuLZ n8mWJirKMnJ4qqkbK5q1poQStHdfNMyrI44yO4qTwl/wkum6vay6BcTJdtNuXax6V4We0YSwslPZn0HC05QxsHHufbXxO/ayu/Dnwbu/CGpaDpMerXMYje4aMNIcdhxxX4UeJ9fufE/iK+v5ovJ88kjauP0r8j4GyyrHGe2k9Nj9s8QcZQjgFGPxNnsXw 8tpBcach3PIykg45H0r6P0K2uUS6VsqWz1Ffuas1dn861JWTua N/YSNaHEa5kXa2KxDYwSyRuY2RlGDVRdkY8vu6mDqMZjjmZGyiuM A1keRPeTTKTtKrwc/wCfWqmrK6Jkmk2UL6zma3itp51ExbIrnLvQPL821kZHRuvvTem i2HKVtEfOHjrwFNpD/wBt6OjQyQNklB368V9f/s3fFG18WaaPC+vyoL6FfLTceTXzuf4VVIXR91whmTp1eRvRnuX i7wrHZszSwCW2K/IcV816gVtZ5YlJCbuAK5+GMa6lP2b6GXFuXexrc8dmZt3fLGqK gG4Pkc81kC/WeWW3wnmcE19clc+LSSszPvrMPMsiADcOQOKqS20kYDbUAYeve mtNypLqWY7YPgh8Oecn0q/cw+TbqobIHetdLFSV1cqWsnko2XDA9Qeop+ooZ7dPL+bPzEd6T SIgmkzzz7I6XMzNEI41OD3Nfoj+whrken6/rVqknlLOmee9fD+I9PmyasvI/QfDDEezzug13PoL9vdpNU8K+HNRA8x4127q/JS0trcNmZs4OR6n86+A8Bv+RdUXmfpH0h6LWNoT7pnR2UiWzEY V43PXPIFfXv7JF/Bpfx08CTr+6R7pVwenWv3KpFuNj+d503ytXP72/wBnG7S58E6cy4w0YPH0r6L255yQRUvc5sN8JGwIzmqssaSBkkR XU8YIqlI6uY8h8b/BXwZ40gkF3psNvdOMiSMYOa+XNS+FHxX+FUz3/gbV7jV9HhOfskpLLj29KmcFJa7jUr6M6Pwt+0VZ/aE0jxxp0/hvU1O0tLwh+hr6Q0vX9N1SBLnTb2C6icZBR85Fc0ajT5JkSizo bbUJkxls5PrV59Tjddj8EV2Q3Khe59EUVoahRQAUUAFFABRQAh OAT6Cvxe/4KyeIxpvwN8RWzSlRqk8duB681yY12pszqdD+Tu/bc6tFkIMsfatrwlbxX2r6XC/DMwIB71WIm1Rl6GODjerCHn+p9f69o8c+jW9hGQWuJVXGOw61+ HX7RdyNV+POrWisxg0lvK2jpx/kV/LnCVq3FkbdLv8AB/5n9ecYzjQ4Vml1SX4o9j8F2EVvpemqqhJUBlx0xXYQx3Zu7INu EYDO3cV/V0o7H8fKS1uR39yqOYwpBY5yTWgqO0auo3I/IHX6V1R1iclTRoS1RrZzNsBklydp5xVdHufLzJvAL8jFZHVF63 Z0lleKU2ozb92CD3qW4Dw2wkwd02WIqJyVyIRsrS3MGCUSiGPG 1ossBV5pEWVSib0Qiueo29UddOOiaKGoQm5tNRnZdpxn5T+lfQ P7C3wyf4sfHXw3pd/Bv0/TyJZCR1A9a8zM6zp0JSPWyfDe3xMafS5/WKvg+TT9F8O+DNKtwlk5824K8bYlAzX8g3/BY79qWb4v/He/8D6DqEr+GPB+3TraJXyg2cMePVs/pX49GEq+JjRX2n/wT98q4hYfCTrR+yvz0PgH4OeHWgK3bLkbgRkbcmvsGeXytPLRt td05A6V+6t2XKj+bqkry1ObS8njWKN1JLYJI5p8t0JrZ0ZwkYP XpVcuiZnypasyVaNZAI/nC8k4rZe9YW0ZTIQ5JGOTRG9mZRi+YxJbhNk/lthV64PWtJGUWoXdKypyuelcjbTdjsSsUblIS9u2BiRuufWprp ViKCMbo0GTkVcNdxtmPcQRpJHN/Ao3AAfpVnwx4in0/W7F4IXmk35CnvXkZ3T58PKmz1+HakoYuDXQ+6b/AF34FD4ZazrPxG8LRSa2Lc+VHIo5bFfit4+1jwtr3ia9l8MWCa dZKSFA6CvxzhOOI+uqEPhR+5cbSw8cA5y+J2t9x6n8OIk82yeR FDRofmxX0FpFqiG4LMzEZ4NfuTd1dH88V4u5ZvQv9ns8bAlHIO a5iNyXe32MZCvYe1OLu7mVluzndUtwts6svy7gSxHWsAKInuXj cFR2PpWy1BMsTwW00FpIkg884APQiqEdst1PcNLKMrnpUc71G1 rpuUL7QYr7TZoJgJATgmvkqeDUfhp4tXWdPuJfLE4YY4wM1zVq DqJxOrA4j2VVTXQ/VH4eeMtO+JvgqB2eN7pY9rHOTnFeA+OPDMtpeS7FKvG/PHvXxeUVPq+NdN9T9Rz+j9ZwMa/bU8v1SydGRmDF17Dp71LYWKeZcMoLuU+8Dmv0ZPqfkb0lYoyRi Oby5HOZRxjmqCCWJmRS0iO3zH0qgRstapGxbKgOuSc5POKy9QW VbdDHIrO3QE1EmKT912OehZyjb3/eM2PWuhE00SovylCvrWrQKVh1paw3PmrKPmlHUDNe+fswTNofx Ga3Sb93cRkEZBH+ea+a4wpc+WV4/wB1n1vBNd081w81/MvzPtv9qKB9Z+F8EzEt9lOBivyDuGmsS8TeZg9G61+U+A8v9mr x81+p+w/SCTdfDS8n+hasLmZVXcQVbnfmvpr4Dap9j+J3gi/jcDybtCMH3FfvE1fVH85yhpc/vq/ZF1Nr7wHphzkGBD+lfYjLxxz61kkcmDj7livJzkDgiqW5t2DVc p1cpKFOM54qKSKNgQVBH0pxQI8u8Z/Cbwd40hlj1TTLfznHDqoBr5R1b4IfET4b3EmpfDjXJ7mxU7vsc xLJj0A7VFSmprlZUZdGafhn9oWXTLiPRviNpFx4fvkO0zMuYj/wLtX0dpniDSdftYrnTNQt7qGUblKuDmsadVwlyTG422Psmiu4s KKACigAooAKKAI5TiKQjsK/na/4LLeK0tPAehaU0pUX+pFyvqFU1yYxXhYxqu1j+bK8n82DeqhQR j3rp/BJX/hI9MlyY0Qc85qMdLlw82+zNMqi5Yqm/NH1k/iC3SF7iWXAsoHlAz6Cvwo1m7HiP4t+JNSlJkM943OevNfzZ4ZU ObiSpN9Ez+pvFGry8MwgurR9LaSfKdI4WRfKjA29OK6C2upHiZ Q/BGBX9S1FsfyTG9ynd25kkUseQQoGP1rf05nzNGwyi8DFbp2MKi VtRTEqOsqkjapGPSq0oa4WMgFEI6Z7U7JrUanbQWxdGhcQryXJ yfSny3MhYvI5UQrjrXLP4jpg1Ipo2UWRWHHJJFXJL2O2S2Td++ LlyB+lYvsb0n0Kz3y3dpNGodHbIya/cT/glB8IUWxuviBNaRpczyCGOQjBIFeFxBK1Bx7n1XCdO+LUux+q3 7Unxu/4Ul+zv8afiVdRpa3VvYtpWmS/9NGUjI/Ek/hX+e94i1q8+IXxF13xBevJPJcXDOWY5JJOc18Bw3QdTMYuS+G7 +/Q/SeK6/Jlc+V6yaX3a/qfVHgSBbaytkUbSw24xXrN1dRRW21mzgYGe9frrWlkfhretkYx kjkiikCspPAFN6Da28tnpVJowUdUJaqjGZYzjC8mpLrdHHBhso Bg9zScrI2Sd7lCAEo2f3jO2M+grWV5ooQDGwiXnGK5JastJXKd 5KDHbPIpZhJgDNWXuIoJApyAw4704R6DdrWGyzRTCDcoJY8461 mxaimka1p11HCjLbPvxjIIFcGaUuejNdz0Mkmo4mEuzPvfwtoH wM+Nvhu6m8f3U2liygLPEGxkgdgMZr8efjboPgnQfFuoad4Gt5 Rp0EhQMT2zxX41wvVrxzD2C2ufvvFVGhiMA609LL8Tsfh0gla0 GMAR8f5/OvedFmRBMrlW35AOO9ftjh7trn87VdFqSTRSDTpy3Cb+vvWD5q 2rs21S8wIDHsKq17ozijmNUlkSCUMyyx+g4rlyTceZKoxkYAFb SVldETaI0jnVrfzlKBlx1qOaJ2u5HgfMeeRngUlJbsV1a7HWF0 8sV1BuG7d0yeleYeOdAh1awux5QEyDIIHNOD6oUHbYP2fvGdx4 O8RjQrydhDMwGGOMGvtvxtpq6jaLqMKZDLzgcdK+DzfDqli1Uf c/WchrfWMudFvZf5nzTqkSmd4SFPc4Fchazvb3LqH2o4xz2r76jL mpJn5hjYOM3EozsoniZlZsHHWoBJut8RBk8tjyf8a2guhzRaTs XzOFDCbLCQDHOcVm3TOwj2nODinza2Dm0KcUDhpHcEBz27VHLM 67B85Q8Fu9UkW2ieG8aFmZXKq3IXNerfA/UJLb4l6aeEVz0zXj8QQvgqy/uv8j6DhiSWY0H/eX5n6JfGi5W5+EGsesDZI61+R+oGK/kkcgMDwOMCvxTwLT/ANq9V+p+5+PlBKlhZX11/KJHYhbeBEaQlScDJ7V6h8OLx7Dxl4Ymik2Fb1G68YzX9CX0P5t cvdP79f2FtVa++HmiNuyGtEP6V+gJctwtYI5MLtciZG25Jwfaq kiMPmppnSmRJKRlWOFFSGVRnnNO4XITIrcHIFQyIrA4AIPrVPX UG2eeeKfh74W8WW8lvq+lW8zOPv7Oa+TPFH7P/jXwdcPq3wu8S3NkoO42rndGfbBqJQU1ZlU52dz9baK2NAooAKK ACigAooAqXz+XaTvxwtfys/8ABabXHu9c+H+iK6gRmW5YE9un9a5cT0+RjUV2kfg1dXckieVk eSjYOK7HwRcg6kzIysyJnmss2VsLN+T/ACOvJo3xlNeaOq8aeJ307QNfuEmw6WbDA+lfk/4EjlvvE95cSsqtNclic9RzX4V4TQTzbFTS2sf0R4wYpxyTD0o9 Xf7l/wAE+nY77yprgqvK/uxgdq1bXUZACAV5AOM9a/oh6n8xObSsaMd8Z54wzHHUZ71vQTvDFcKPlYn5a2iuhzVH7rK5 1IqkqSsNo4zTZdSLxMqkMF54H9aUnbQtWctC3bTTRWURUcuCTz 61DOw+zTSBlIHeuOpOx1KPK/dMmW4ZLeKJCCjMM81k3mqpNfoySBUAOP6VE2aKeht6NBeXq2kC kMZiCSevXFf1W/sM2Vl4O+DvhuxtoQHW38yQd9xr5Dims404tH3fA9LmrTZ8Lf8A Beb43jwf8JPhv8FtI1DbLqsL6nqSBuSx4TP5v+dfyi/Dix8+d7t1OZ23HjmvP4Ppc1epVfRJfr+bPa47lyYalTXVt/p+h9TaDPMbaBIcIycjnmu8u7ho4gsg3Pt71+iSZ+UTk29Cqlwy LA+8kdSpNStcNNK2cIABwelSr7syhOV9SxE+yNwjAdPzp4naSM CX/VgbRjrRZM2fZlaK5EaqNodC3WtOTUym9WwV4JrnlZmrfVmfdzQ SQWkhAUlyQoPX8Ku77aaRsqwEQ5B5pxutiOe6sQWx82bzEAVs8 Vr6Po9trd9a288iwhpAu4nArix07UWj0Msk1iIKPc/RXw9+zdbaz4M+y+GY511O6t8CdRxzX46/tC/BjXfhR4z1C01jUYrwRNtwBjk1+G5DnDo5k6b6ux/Q/EuTqvlvtKb2Vyp8NG8hkdyoPlEjPXmvcNNZWSKbCnLNk9K/dYS93U/nGu1sac1xItvLFMP3bPgcdsVys14kc6b0UqqnOaHs3Hc507vRm BdyRGGZoyrlxkc5FcbNcEkodwToa6IRbWo5q6sW5LmOSS2R5CS FxwKzblvLllS1mOyQ5JPWskujMUm9DMsLiaHUbmNFO91zkjj61 qX0Ef2Z5DmSY8/hWvJbQ1a15T5+8QWT6Pq9vq9sGiMT7iTX6DfDvxHF4r8HQRlt8 gjCsCR1Ar5rifDrSZ+icB4le0lSaPFfGdqthqEiAmIOdpOOa8r u0KyryH3jp0/z1r2MkxKqYZNHy3ENHkxUo+ZTldVkUYI2nBOM1Nbjzop4xuILZ +leuu540Vfca94qPFGSHPTnFLsWZWKkcHkZ5osrijEcWUIY8fe GWPWsa6IVDtf5sntTWpDTMeN5dzRncSDlTjgV2Pw41eTTvH+kX MjMAJAAp71wZnS5sNUXkz2chnbF0pdmvzP0o8aatFqfwv120+8 8iZHNfmDJGkJdWLAIT261+HeDMPZ18VT9P1P6A8c6nPgcLJf1o jDZi8vyNId5716T4VlSLW9EkIZWhmRs47ZFf0BN+7Y/miLvof3i/wDBOXVmvvht4ZYnh7JBn/gNfp7Pp00kyywXTxgHJXtXKo3VjkwqsmjQVGjXazbmHeoHBIbN aWOqxQlT3wKqNv6enpVKzYPyK7NggZ5qRWbkgjBNNxFbqI7bl4 5I71k3I+XDAkGnGLRUFqfSuBnPelqzYKKACigAooAKKAMXxBN5 OlXb5AIU1/HN/wAFgPEn9q/HOy0xLg50XTtu303N/wDWrixUleK80YT+JH48QXEiFQzh4y3TIrtfDM5W4upo3woXpnr UZvphZvyO/h1KWOp+qOL+KevvD4Z8QOko2rAEr5B+Flkl5dCYZ+Yl2P8AU/pX434SU4/XsW15fr/kfuvjJUSy/Cw9fyR7av8Ao32tlj8wquRioVuZJYUQRbGxtJAr94inJn853s7 oksby5TUCpyoiAGTXYC+mlt8xPtZzznmumLtqYSgtEzIWeVQ5m G/nqO1OF2kcJc+agPAB4zWVZrluKjFpXR2toYGt4ANxO0cZrMnls lW4VC4PLHnOTXlzlZ2O6NtDmrqdJk08QMA5b5ue1YVzFPDPJLG dxPykfWrjK8bM1k0tj2z4UWb32u6XA4D/ALxAR07iv6YPgZq8mk6LokFg+Y1RAV+lfn/GlVpKJ+p+HNGM5Tcj+aT/AIK+/GW/+KP7SGrWt9c+bBpBFmiBuFC//XNfEngHRz9iikhARyuDiuzgOlahOp3b/Q8/xErXxMKXaP6s9f09VtZraJtgliALbR611V9cxzRIgzuY9+MV9t ze8fnLk0yi1yqFMpkdBx/n/IqrJeYlYEL8xHXsP61uyIvUv2t6ihh1U88VpRTxyQtLk/MM1jKVlewuVN6mbdTBrW3VSYkhkycVC1w6XdwJSsqkA8H2rKTX NY3uiO6uBtgYZAznFakTSSB/4QVB96S21MZJ7DrCWVbmJHyOa7bw1qWl2uv2l7fACC0cFvrXFm qaoycex62T+7iYSP1U+GvjDxjqPh6Wf4deKNC0uxigJLXP8PHX k1+HX7TMfiDUPGWrap4g8Xr4p1aS4bc0bZUnPOK/Cslor+04ymr6/cf0NnOIj/Zso09NNWcn4IklimhE0ZQ+WQQeK9h0+9+W22oFiL7T2NfvjhZa n81Yl3943tRuwbZcMdiE9RxXDXNw8s0iDcibM8jFFPXUyUr7GD c3cSRPEzjYFySa5AstwjxRuPMZs7s9a6ubS5blodJDYOUsZWJb aNoOO9QSweWspdW3yHGCOlRBK2hFOKd0jmtr2urOoKK0i5JB6j 0roOWgjUtuLDOaq+lgU9bHn3iLTTdWdwzAg8jdXqvwB1lrVm03 zeFHG4/5/wAivGz+lfDuX9bH0/Ctb2eLVup6R8V9CEojvAAmec5r53aExSxu7Egj5ce1c3C1ROg4 nocaUXHEp9zKdizSlVVlY81LZAr5xfgNk4xjivpraWPiNWuUuX VpDKyPGuwDrWdLE0SsqIyAnim3qa3toOEbeWTArvuGTnmuelt5 vPYByGDZPNCu0Zp3LCWAjPmELkD1qlp0zWevadeAKpSUdB0rHF R5qco+R2YGo4VYyXRo++l1U3nhTUrfPmSSW+4/lXwdLNH/AGhdwMCpQkD0PNfiHhYpQzDEwP6F8XZ+0ynDSf8AWiEj0zfcRs BnzeQTwK7rRIGt721Iy3kuHPHP0r9257o/nGEVe5/bz/wTA1MXHw18JYDD/RUHP0r9m0AwD2NZRt0OWjbmY1h+XaoXXI6Zp3N7lGZGb2FZ7xs Bg9DVpdiloQFQ3BBB7VIqBeQetCIsIynnIAFU5olPJH0qyk7n0 VRTNgooAKKACigAooA47xxci30G7YnGVNfw3/8ABS7xWmtftT+OLcSiVNKMcAUHg4Gf61wYr44rz/RmFRtXaPzuupog+xM5DZNdp4TuImEzY6jBBNYZ8rYKfoelwxH/AG+lFLqeWfGSRf8AhHNfMW0YABPavCPhRD5ULScKWHJP+eK/LvCNJyxM1vdfqfs3jTUvQwsPJ/oetXEhC3LlyinbGT71NJMXWO3U87txI+lfsyTvdH8+zjaV0NjW EPIY5QWPJx6043M0cSLvOVPUV0Np7DikldliwmeUsJHjdEGBVX VL63SNDIFSNDyc1En7t0Y0Vr7ppw+IbNZbYrcxqwQA88VRu9WS aK+COIxD8uQcZrzKkbSO+MWuhwN14rXTdRlhldAnlhUOc8/5xXbWV0s9s00m+LCZy1U53SsaSVtj6D+CKRf8JFosqy5DOrYzm v3S8BeKpNE8N3N5HNta1gL/AEwK/MuPqtuWJ+w+GaTjJs/k/wD2r9fk8W/HLxDf3MplkmvWbPUklq6vwXD9nsrdVDKWCjA7V9VwVBrAJ9z5L j53zGUe1j0oQA3HnFFLDGSOlQTzA3ADRFlU5Oe1fUReqPhrWV3 uQSXITcMqNmfzqhLcQmJyrANjnFbT20Ik7OyKkdw8WA5LGTk85 rS/tJ7dFTcWR+MgcZqZaxsWndEsk0E8UZ8wI6yDgN1rR3rFdyMrlh syeOa5tdxx2u0MnFvcW8OQyOSeP6VqaXbzSuF3OY+uR6Vad9GV JxOmttOleR1jibcPlyBWRdabqJguILS0ma7J+UqCea8fNcaqUL npZVSlOqT6dpHxGi0W7t9O1bX4I3G2ZIpCoHscda+X/GGjappVzdTXy3Uzhjuc5JJ/r0r5jB4fCxqKcV7x9NmeZ4pwdGT91G14Ru3kurWVzt/d7WJ/lXpNveRiSORHVSJMEZ619xG7jc+MqSVjp7zUGkhO8BY259gK5a/uIWnaPeCirg4OKqmuhyxb2OBv7lUhkijQSjOXOa5yCfzJGG4xK hyMN/n1rWPW5aVtWeiWl06pZsZGKrzjOahmuRKXYESl3wcDpWe2pMU7 3Oe1KLN7Dc/LtcAc9K2IQJIA0Y3EkD3FbQt0K5EncytYQXFnco8ZRVzk45Prz VH4YXRtPECJCPLDMRk8152ZS5qMonqZJXUMXBvuj6w8exi68ML d4y0YBHFfGs195twyB8M3AbtXzfCE/flF+R9rx1BPkmiS3sjeM0p2+WpySO9aUFmVmIJ8xBzgelfc3sf nStudH9jE0UTbBGrHk1z2pABLiOBgpUckmsm0yJ2Ob05ZPKQeY 772ywqd9OkiaSdpMHd8gNaqWmwlF21MnUtRjjbyiGaTOAOlc5H fQm+tmeVVaJh7d6JpuLSOmhL31c+3PCMj3emhElLxS2mM9e3/ANevkbWbMW3iS7h2lTHKScd+eK/E+ArwzjER7n9D+JmuQYefp+RuWUQkiUyMUEfTnrUtteumoqC44 I5Hfn1r9sltY/nSW2h/aP8A8EoNfW/+GfhMykpIsKqAe9fu/GwKICcZFZU9ThwyfMxCSeATTC2AM5yKux1WImXcOCMiqMsZBPP H0oSXUEkUyCM9DjpSBv7ucHjFU1oIsDBQsQTmqFy2Fx1zVRHDc +g6Ko2CigAooAKKACigDy/4q3a2vhu6YnACEmv4BP2y9dOu/tI/FjUIJJJkk1eRAQey8f0rkqQvUi+xhJu7PmJH/cSysfmZ8ZzyK7/wiCYbh9oJY4rg4mk1gajXY+h4Mp3zOn5M8j+Mkklv4b1Z5ANl3 Psryz4bWbJpcrbcAvnOelfmvhCkqeIkur/zP1TxqmmsMo72f6HbOwntijTgI85bOOeKJlMTvMsmRIMcGv2Xm 0sfgdRuNmyxp0Uv2dmJbgnGRzn1ptxN5FpiU/M4I96lO2qFKncdpU5RQC5YOARnqKzPFtwx06QKo8yQ8DpRJ30Q owV7vQ8t0Dwv418ZahqE/hqxvdTFiy+aqc4HrxXvnxZ+HOofD/wjoPiScmE6wFRoyehxWMrNczOuFXU4/wCDPwQ1j473d/8AYJJkn0VhJII0JOK+u/jr4A8O/DnwZpAt1LavJCIGATBLYxz+tYtKMLmMqz57RPO/g1qq2Wr6DChcSEjIYc1+u1h4qNr4C15ml2t9lbgnpxX5V4ippp H7P4ZtpST6n8yfxKuVv/i3rk4YgtdN15HWvoPQLRxY2brgBFBwfpX3PBqtl1O/Y+O41s8yqWOpS7CSuiKrnkGsvUbvfdqY18uNV44719FTWp8XbV plcvGiFSxBPPNZk7KIoiwzuOMGtW9LsLJMms2+0XCrt55xkc1Y vZre1hdJQQVOeKicmtgvrYoCNVFqqP8APIAxUdq27YTrI0y5O3 jJPFYtaaA4uxM1zPODCIwqqeor0Dws8LzBJEBD4xngUSXVFct9 T23wL4G1Pxf4lh0zR1E0srBRgV+tfw2/YhNh4YttW1/R5b2/1RgFYJ0rwMTh1UvI7cNivZzSW5hj9mHUPAPijW9I1Dw3M1lqEZ kVmj4HvX48ftaeB9P8Lya+sEtvbzWUpLLjpmvisRGdLEwXmfUR ca0XNdj4R8P6oZp7FQWRSMEnjNejfaiZF2HaNwr9Rwydrnx810 Ota+eWIRlwQo5Oa4q+uS17JH5hywqqZjCe1zPnijSB2V9zMvbr 71yjqkTPKZCrDngZzVLsNruddp7zNFExbCqMc1Bb3E4nuQjZVP mPpRNa6GkgvTLK0E8yOi4/pW7aSCJh8uFkYEcc1ScbaE35tDU1OyjurO5ZRlSvyjHWuJ8Haf Nb+ILfaMKzEGuHGQUqUkzqwFvbQa7n2Fr9o9x4Iujux5cRyRXw CY2N7fFSfLVs8dq+U4UqpV5QP0XjiFsNTlfsbegagZbtdLUn7S 7BQpP3q6vxJazeF9TtYLptkk4D7PWvvZ3tdH5jfoTJ4hsTZPDI AksbbueK5zU7sQEAu4Scbgc9awjBpaFSVtihZDzVzC3yq3U966 KaHbCdznd16da2m9LkeZ5dqRdr8lo9284zWDqJgRFkxsZXB4+t XCWiKpr3k2fd3wsspLnSdHdNypNDj618wfEiO4sPG2pwImWDng Cvw3hOolxFVp+p/TnHdP2vClKb6KP6FGzumjtSXwqt2FRwxl7vz45Twc7a/c+XV3P5iaVtT+xT/gkNqyz/AA78LIWBMShfxzX9FMBzCh4ziuenFpWOSjG0mh/GQOwoYd8gZqmdDImHIweRUEhBHOfc07aDtoVNqsemAKb5WMben vTbE3qMeQKpPXHesW5nDEjg9j61auOOj1PpGiqNgooAKKACigA ooA+ev2h9WTSvBOsXDjK29s7n8FNf57Xxi1Rta+JfjTWQ0hXUd SmlUZz1c1yXTqcrOWS948wUv9nJVSfnz1r2TwPayf2dFKynLEk 55r5vjOq6eXTbPr/D7DueawZ4L8fLjyfDsUEpA866zx35rjfAeI9DiCMxEuWI6ZxXx 3hAr4OrNdZH6J43NLE0ILpH/I6ryIZItPjYxldpZiRSiG1SOQM6sqnKqe1frcZPZn4VJvZlrTJ CYt2RsUnJPFY+vSRSW+6M8R56DiqVkxR3t1KGkuA7RqXG3AJNX Ndhhnlto35t96g4HSiq9LoUG2fUf7H2vaH8MfivrOha9ppu/DnjkKkNwyhkU45z6V+lPxz/AGDPCPxY+BviL4oWXxEjtdP8Mq93bQLKNowDxXLOSasQ+aDUz8 gv2R/i9c/s+fENLjUJlgsNVmMLvIoMbDOOfav6A/iBc/sx/Er9m/UfHGv23hj/AISAhntMyKGZ8dcU/a3RviIW96O5/Pb4X1cP42E9siCA3jFNo427uMV+m2laqLvwZrERYs7Wp6j2r8q 8QZSUISl1P2TwwulKLPwC8bWLr8TtWRv+fk8enJr6K0Qlbe0hU Fl2AHPNfccJy5sBTT7HxXGKf9oVVfqXpruITyRIOIzgtjmsqef z53ERGIx/nFfS0ld3Z8hOLtqQb0eJnYZcVmzm4CpggFyP1pz2Cldo2LC2ur mdI7UO9y4Cqqjk19yfBP8AYm8efECKLxJrNm8GlKgcBlPIqIx6 Euaimmc7+0T8DbL4Vab/AGrtihmgkCAbfve1fKdm008RuFkUwtjoelYp3vY2hfluiaRlSQ Dhtw/hrpdEu1t4meJVZjjGBU000mjOPMlZH2X+yD4+0TQfivoM2uMi2 c0wXe3rmv7TPgZbeDvEvgW2u4UsL+KSIPGQAR0rKmkpNMKj965 5d8XY/B51OGHU4bK3a4VoQ7KAfbBr+OH/AIKV+H/D/g3x/wCNNFj1OKQ3UhuUKtnOeg/Svk84pxnUjLqmj3strShF9mmfkTpT3jXFn5Z/dIc5HSvUIbwNIoyu7AOSa+zw9+U82e500d8pTBDE44XtWdK1tJ eyMHUBeoxTgrPQ5eRp3IbyIeU7Iy4CnODxiucjhjuY1DBgyHJq KburgnbVnU2qtZglzvQLkgmsl3zcS7GZTL1A6VV3zWY3N7F1pZ ntUXG5QcYHOK3o44JpIXeRUO0KB602lFXDmS3LUzywRyNE4KYq HwWpvfEdqkkZTnAFc2JTVJ+h14CLVSCR9ia/pbx/DrWpVGFWM844zivzRgmhbVbyLzCMyYOD718Vwm1LEyT3P0zjRS ng4P0/I/T74X/sYN4y8DeH/G3hz7Nd6tPiRSRkbj05r89/239G8efDL4g6TomtLbLfrGUwnHpiv0Wro7H5Ngpc82pHl/hvTvGOp+BbnxNdWU9zb7vLMkEe4r9R2rI8ReNG08aJY6paXlrO AoVZYyGK+uDSSui1Pn909J8PAXdqJ0JbHUDtWlrE0sNv5YG0k8 YNOT7lyOEklh8xRdKuX6DHSud1ZQxBjVioO4DOBirSCNm7o/R/4BrFfeFtBlwCUG3mvnH496clr8QL9xGVjY5yO9fzbkdZw4rlB9 3+R/Vmf0fa8Fxb6RT/ACPHrq9VYY1VVGzrnrWZYXN2kykMCQ3ev6TUdT+U3bof1w/8EdNYiuPBOjKswDo+GGelf062LZtYDkHcKxfY5IW52WVOcZxQz AcUWOiwzINQycgjoaVhWKeNp5AGKY0qr1HWqjpqHQzbmTOTnAN UDCXGQCauK6gnrdn0rRVG4UUAFFABRQAUUAfE/wC2l4gj0T4TeOL18BbXSpn/APHTX+fn4lvZZ9Z1Cfgl5mfB56nNcNr1vk/zRzct5NmHFO7u0WFQv14r6o8B6eG0K0LIf9Wa+P8AEeso5bJPq fo/hXS9pmsb7W/U+RP2px9hTw3ZgEJI5duK5XwmXt/D8QQq6mIscnnnFfO+DX/Ipcl/Mz6bxzfLmdOF9karyOkNsAVVRGB8xzjNVTN5arF858w4yOa/XLdWfiLdty9BextbEQMjKo53DmsnVLry4tpPmLgHOOlVz6J9TH ls7ok0eeF/MZQvzkDr/OtSa4DvHHOoK+Ycc80VGmbU0+pb0LWfEnhbV7PU9Cu45lBLJFK N6qSOvtXX+HvjN8Xo9L1XwXP4z1eTwrqEjNPaCU+Wc84+nPSuK Ued2ZrFO+qOX1PSbXWrJPOg8lwfl7GsLUpNTsLay0ptc1KbTVO fJ85vLH0GcVFl8LBSsm2aXhu7a01nT3WQFSQw6etfpv4K1EXXh ycEKxeHbkc54r828RoKVKDP1XwykpVZxf8AW5+NHxc09dO+LGo yACJXnJU/WvU9OuIltoNjfMsYH14r6fgx82Ahrsj5jjjDuOZVPvK41C3X7U CMyYwCO1YDSM0h2yLGx569K+xhdnx1R23LDtNHblIWJdeQ1QvL K7WkcrMxPfqM8UOSJiegfDPV9P0Px5ot5q4SWwglDyKeRgGv7M v2DtR+FvxP8FWEFjLo1zbxwjzEBXOPes/aLaxhWg5fI8d/4KY/sSfCDxl8NfEPi2zvV8OS6DC14GSXapYDNfyTW1k9nZXFsrE8kL k9QOhrmc7SaXU6sO2otGfGHYzSF2UkDitDT7q4t4puVctwgIya qor6XE2tUdBo+rXFk8d3FI8dzG2VKnkHNfrb+yh/wU0+Ivwbsbfw9rNx/aukxALtkbDKK48fTmknT6FUmr8p3v7Tf/BTe0+KejxWuiR3elX1hKJDJH1yPev5+Pjb8Rdd+KvjLUNf8RT3 V3NM2A0jk8duteHgsJUrV1VqqyR60ayp0XCL3PPdLsLdZLaGFN oPUkV2ksUKMGiIf1wetfW0npZHm32JCsbKrM+1xjgnJ/8ArVk3GYrgkAxoox9ackiXBPVgly0kahA4VwRgjrShUiVlG5CX +bFJR0Jd7GpBeiNkMyllPHSq0rJNLNJHHgScADtWcYaExjrYtw MYLdlQhmYncM0txqSp9mIDhgMY6cZq2tblJdx1zfhoWWNyjg/MCeDXo/wctDq/iuKN4lYIeeK5scv3Mrdjuy/+PC3dH3b8SdKj0v4OeIblo9m6I89O1fiPaXUn9q37K4mG7PB6D vivguEJXxcrH6lxo4xy6Cfdfkfop+yr+2340+AYg0i9gXXvCof d5TgFlGe1eWfttfG3wv8AtI/EPSvEum+HJLF7KApvYckkgn+VfpUldpH4/ToKEudGV8C/GWnfDtbzSdZhF3omrR/MjdEPuK439qe18H+JvEPhbxPod7Fc3MsfkPBCPkSMdMD8amTae gRVmn3OR8Mo1pYxKQVIwxHIxVrWpXaPcpJbHBqqjVzRJNabHC3 KCQ5QONp2nNYt5HKgYbl2j15z9K0ikKEIpaH3f+zJr6Xfh+3sn kVWtZh07Vzf7T2nRQeInvEKnzY89f1r+dI0XS4vu1u/zR/Vsaqq8FuEd+U+TbqWO7hVAyKwXIwepqvZDyrnc2UUjGO1f0dSb P5Pk2mf0+f8EadUvIdFiUurxfaOFzyor+trR5DLpdmxOHMYJrC Xc5oyvNmnHuUHcwY9qGc5GTwaLNHTZoAcjjGKaxyCODQxMz5OG POfSqMw9CfemkJlXaxO04C1MNqp3IzTW4ovU+haK0OkKKACigA ooAKKAPyu/wCCnPiQaH+zz8TbkSFXbTWiGDjluK/hovPJWW5lmAdnfb16muGDftnft+pjFbyZSslt/PxM4dQ2Melfangy0t4dAhfeoV4eBX5/4r1bZbb+tj9Q8IIN5pzo+Gv2wTDHr3ha0J+Zo81xWgIINKiVws kYiUDjpXn+C1O2Spvq2ep46SvnNo7pIranO8163kEpGgwFxWcl 9Mu1AoZiuQfWv1tWPxeUbPU3tNWGRMShkfZuIFZWrTIgiixkZC ii/Qlb3ZPaxW4fELSfIcgZxWqP9ImjwhBGQef61Mnd6grnQW5jWGF VUhApUE9qoRPHYXRj2eZtOSQPWsVvqaJN6M0Lu9hcgpxtTHXiu V1RVkZXe43FQcYHH0rKMtdROVkZVpdvb6rFKuBHEAMZr9Lvg9e nUvDsHlggBNpwfavhvEOjfDKSP0/w1qpYpxfU/Ov9q7QLjRPHkWomFvJlfdkDjrWDot0JbS2kjJ3Mg79TXR4eVIv L0r7HP4k0lHH3XVfqxcSCaWQqX3nDcVnTBsOSrq69sV9/CS3Pzpy0Vy3Ek4CJ5uFI6f1roZEiWS1OQ7cAcY7VjWSITVyvFC v2q5cLgAYyP8+1fQnwc/aD+LXwT1BdQ+HPi3UdIWXAeJZCUb2IrKtrFo1TR9CfGv8A4KHf G746eE4Ph94s1H7Lo64+1GNjunx2PtXxFd3G9Li5iIDZ+Rf6Cs qELavcqnojCsJXczJKSvm4IFWVBEM7ITuUnjoDVxtZIy5VdMra fftZx5k3bpHPGa2GviEkuFciRgMA9MVrInlb2OY1LxFezAx7VS M8ntXLTRwE75VVvM+bPT8f8+lEIJIuKauQ2Qhh8sx+USOQAMGr F/krE4Uj5u3FVDaw4La5AJPPn2lSDgAcf59qndGDqGH3uOT3qJWW o+VXNIaTcywRNHE/3sArWrPojWYBuY+nzke9U0mianvLQ568gDCM8gYyFxWFG7w+cq KzsvIBp2toF3azJUu3VbdlkJVj8wqrqFx5ggWJSWjbk+p5pJII +8tShJJMm4mRgpOSK+sv2WtNa/8AEM1zgMkS9a5M0tGhJnq5JSviaafc+2f2pLu30P4B6ihCLLdJ gfj/AJNfgZ4deR7q9uF3fex618JwVZ4qq35fqfpXiFaODow83+SOys 5nVImMmdvYE1tpKszRlsq3cV+lryPyOMV0OhJHmQ7mAwnTFcys qyN88CthuCeTRHXUcmawuzb2rEqYwOB2qgb6R42ORz3Pp2pT0K v0K7IDHA24Ehu3rWVqsKzxnhZCmBgGri9BR7Hq3wC8WPomo3dm uQu8MDmvbf2gdUtdW8P2t/EgMzR7XPUgV+N51ShRzyNXq3+h/RnC0/a8Mzox7NfmfCqvKLkMC6qDjNdDayPIzHJC4wT2xX7Utk0fzjJ2 uf0Yf8EcPE0cch0tnAliuASDX9i/heTz9FsJFYNmMfyrmlqzmbvU0OhD4HPaoWlBJ5HtSv0N79BUY4 I6Ckdto6gYqWSVXO49uKgfAA4607g1cpSzKikhulY9xqW1GwuD 6k8VpG+5UI9T6hoqzYKKACigAooAKa5wrE9hQB+F/wDwWM8Vppf7PPiq2WULLqcscCjPX5hX8ad+7EGOQq5c7jnrXDS jetJ+S/U5oy5otMxIrrE8SAu29+SDzX1x4d8SRQ6bbQM4j+RU+Y/SvzjxYh/wnff+R+s+DlZRzFprsfFX7XOqW+pfEjRbaOUMsFuvAGR2rM0a6 2abAhU84GSfpV+ENJwyKnfu/wA2V411ebPZW7R/Ip3s6STzmXcv8IK/41Vt/MW2klUhkU8e1fpcFqfkbtq10LukX/mSYaX+EA57+lXdWMU7FURXZsEcdK35k0ZxbepDpqgSzbc/KME9ea24HIZio4UEdPespPXQ0g1fuW4mdd22UbRxg9PaqcsiC6 cMxy2AxzUc13saRld2RYgQu+xtrRL3B4+tYmrBIpW8lQwwTXL1 ViXBdDCu3ctbiBOUUE8c19ufs7eLX8mPTjdhAmAysea+c41oe0 wUl2PtOBsS4ZhGK6mV+1/4NGr6LBrduBJNb/MTXwloNyRZQqjsJEGNoPFeD4aV4+wnBdz6HxOo3xEK3dWOztZn VGG5nI5NRX05MitwSy8Y7Gv02z5j8rmnua9pAbm3iZ1HJ4PetC 4h8qWF8DBPcfX/AArOtIUTPtbiQXsu+IAdMHpWnCC1wPKkY7TkZrPltqx7amNfXV xFcnMfBOcY61Yj1Et+5dSU4yMVM9k4jlq7omicyXMvJWJFGCBT D5pE6LI5UEjcOeaqnK6uKKdtSrHvMMeVDY4J7496ZcSNEDswcL wD+nAqlK+wubUwJZWnkkdwfnxkAcVXmIRNxJIzjHWtHsVzX6FC KFkEbxucq3rmta6dx5aqS5J6YrO1mPmtoIu1LweYqqHHHapdWZ IrWJ1YszN3qHZuwJpnU6F4jbTni+04uYM/MDzg17tbzeC9XtWaZWW7ddyr157Ct6Gl0zhlCa2Z5N4m8HTxbZ 7JkMb5YKh6L/SvHriO5gvHhmyjOMg4pcjT0O26aUk9CFLa4a0BZWB39QKpamrx SwRRkpGx+Y+v+c001si1boQyiZzEqDJcH/61fo3+yf4XuLazS4kjbNxg5C14PEWI5MM13Po+E6PPjI8xN/wUB8b22neCdK8Nx3Cq8/zMn8q/HLw9JNDDOVIbc3c8V8vwJHmqVanoj67xIrqMKMPX9Dq7JpAFll HOT34xXQgM+ZHOHH3Rniv0q1kflqNq3uHtnQXARjUAiEuTEpy5 yOOnWnFroNpMz9SvxbxiFiwwPvHmscXBkkUZ8xVGMr1ppX3Kbs maotJX8to2McROeOaZOrEtu+YkcnFF0mK/U0PhvJHb+LDFk7ZQeM4r6W+IOmC/8DlwW82AHnvivxXxBqRpZhSmuv8AwD+jfDG1TJq1P1/Jnxf5DAujSFSDg/NWhYXCmVQDjtuJ4NftdJ3gmj+dK8Wqk49mfvl/wSDvrU+I7q2fMc/nAg9K/tT8Bhf+Ea03Y+/MQrKW5wNWqnVsCc9ahMbbsAgCkdAp4xg9epqF8kEDOTTsOxTlc xgFjhayrjUbLBLXABHBAbOKSdiWZpvUmbbZwPO/QHGRWZqOl31+hWa4+yo/ZPvVcXcuLV7H1xRWhqFFABRQAUUAFVL2XybaV8ZwKTYmz+aT/guD4r8n4Y6JpMbANqeqjj2AJ/pX8pVxdhnZGlCOf4Sa5MK05SOOk1r6mcqGC5CoQ+GGMHJr0e41 iaC1hxJ5bqyrjoa/PPFOHNgkvX8j9Z8JEvr2nl+Z8ifFDWZtc+I0TSzbzCAnI9K9O0 2RRbRIzAMg4HrXseH+H9llFKK8/wAzg8VaznndZ9rfkUNQANwyxnaD1NTWcRms5U3hcnBxwTX2MOr PzlNJ6IoGH7KH2KcDuBnJpY77c7YkbcR61pzGbbexraXKyFlUK HYgnjpWzPG5hHkFgrDLEdKxV0wV09CfTr1IowJQXePpnqarX0a 3ERe3zuc5JFW1rc1jtoTwzGFYkkYkt8pzWBqUq+dKGkTKrtXHe uaLSlqNK2pgTLd/uZoJSjk5K+3pXr3wl16XS9dj+0uFEh55xxXHnFBVMNOPketktb 2eKhNdz7t8Y6fD4x8C3MMWJnaE4+uK/KC7s7nQtdvdLlhK+S7AA+lfmfAlZU8VKk9Nz9Z8SKCqYSFaHQ6 fS18wOJPlYrgYqC+ikTylJJWLlietfr6d2fiMtbXOh0yYZhBfO DnpWjqFxE00cRbqcsSKxqS94lWvoMaFSxYEZk5Jx1plvK9veGM kvkkk5ol5mkO7InuYJWJIUuOabcWokigmA8pR196izumiUrSTM VpJ4rq5XzHRVT5TnpVywvZ0Mq7RIGI71SgupLk+d3NpJoEtmYx jzCMZqnMULP8ALvAHTNZQetik4po57YJJGkwFVjkBelSz2Uc0A ZJMHHOTW7fYUY9UV7W1WPydzDDHH4VsXmmIWjMROeCPelzplJJ q5hXFuiSFpgUYcKM9afc4azjaZSoY8cZrOSSfukRtczrpp1nj2 B1QNk/Su78O3FwmqQlsyRswBz2/Wt4K70Kdnoj6c0bwmniCyuxaHzboR5AY9PevnPxt4S1KwvrSSW zZLYMV3ngg/wCc10ThZJo5cPJ3akYMWnmS2MUe8J5mDkc1leJtJkgmtGMRRJA CoBzxXJGSTOqMtUkXvCnhefXdY06yhQu87jA21+xfwl8C/wDCI+GYZZIVUwxjnHtXx/GVZxpKB9/wJh+etz9j8ZP26viC3if4jyaNbTebDpzbNoPpXzHodvJbwISW2 gZ5rbgXDcmDcpbyZp4iVb4uNPsjvLCCKSBXkDIW5rQtFLrKFAK 7sDPNfaXR+frXY1I4gEM0wJKjAyafZyOkR3orKDkelS3poN6GF rEMEsTTM370j5eBgVzlmqZSJCFPcjvTjuSm1PQ6+BWaMMkm0IS vTH+e9VNRWWNZIog24t17URST1NXKyMvwUjJ4w09ld8zMBgNnN fedzok134Q1aDygSibgDX4l4sNQq0Z/10P6J8GEp4KvTPz8vEkivriCWLPlswBojTfKG4+U9q/aMtqXw8H5L8j8DzamoYurF9JP8z9u/wDgkjrNrF46uLN3QTM6nGeev/6q/t8+GdwJPDGmbWJHlgda1qNt3PDrTftbHohwOSKiIBOQMmoZu7E Jz0PGOtRE4GTg0AV5PmBBUEHrWebO1ySLaEE+1IlkiQxp9xFXP TFQ3S/KcnPrzVwWo4b3PouitToCigAooAKKACsbXJxDYTEjjaTUz2Jns fyT/wDBb/xZb/aPAOiC4HnS3MtwUz2AI6fjX839yySOrAhmBweK4MG2pTfn+iOG K3uQ6deq+oRxS8szdc8V2Gqq0iMQpADAcGvzfxSk40U4+Z+y+D 9ByxbkvI+L9Vkkn8fXKzDJWTH4V7jZzhIrdCu1T8pO39K+04QS jltFLsfLcfSX9sV0u42/lXEzptVwQM55rPiuStnHAcJznIFfQRSbPiUtbourcK8Lq5LGTq TzisCeMx3Lywv0GcZ9KTkrXJeupu6LK6mZZGO6QHknmu/UFbFCoJZlAOQeKJ67mrWmphmGRXlIJVY+Bz19ajhnAabccYbnP SqjK8TPn7FpLyHDEkuwbjiuavJVvJVcRvjnPP5VioXlqVyajXU Kq7Vwp4GfpUi3UtlOl7E4RoSDgnHSnVgpRaZtTrJSR+g/wS8b2/iDRhps5DuVwQTXzV+0H8P5LDXG1i0gCRSEsxHH+etfhWDf1XNv e2ufu+Kg8Zk2nY8WtVKImXboMADFUpA7zyHeXyOjdq/dFK9mfhM4dywszQNbRofLV+pzz9a0NQkb7VbjzMq4/Gs2tU2ZqNtUXku4ldSrI20DrWhbSJdSAHEZfqazqRa9AhHqjnt R3JdYEixoCcgH+lXbK7WaJBktEvByf5VopNwVg5m1cz7+PzLkz qyojLj61W0t3huMsUZcYHNJSSRFtLm3IcJvC7S/NYxcgszO/wA56Zp9bl7uxntOVWWAMBk8nNAlKwbWff24HSk5JMSgk9TUgMC Q27Al3JHJFdLPcIkqbvmUAHpxXPLe9xqD3OR1J1uJjNu8sDIC9 qJMtZW7o6sI1word2jGw1DWxQlLtcReZtVdny103hu9Sz1CGaU kwPKFYntVwlZhy2ufoh4G8CXE9tBq9huPn2+UERzya8b8d6NrY untNYtJUgtpTj5efwr0cRSahc8/D1Lza7FnQPhLDqnh2fVLQnzEccYziuJ8XfCzWGm08vESZ+FGzj FfJwxydXlZ7Xs9L2PrL9mX9mW/l1ODXdUsncJyuR3r6x/aI1Ww+E3wv1vV5VETWkBSMdy+OlfEcZ4zmq8seh+t8CYBxpe1W 7P5VPEuu3XjDxzqOrXRkuJLidnBzmvRrZI44hGFBbGcetffcNY f2WDpxfY/O+KcX7bHVJ9LnQW8CmJFUqrtywz0qMQyRPcrGcA857A17ve54S 7l9XkbT4yMl2OMmrhUpaiMLh3GM4qbxtZGbel0YOrZCLBGUdwM njJxXKBVLBl3KRnGD6URl3EpdDo4ZXNmihiCT1Bp2ovPsRM7Vx jr1q0u430Rk+H7s23ijSpWZggkUDNfqd4aht9Q8OXUZAkNxb5y w7Yr8O8ZY/u6U15/of0P4Gzv7ePp+p+avjLT/sfibVrcbmKyNn0IzWDaLxJwuQccnmv1rh2rz4CjLvFfkfjnF9H 2eZ4iP95/mfoB/wAE/vF1/wCGPjpocdm7LFc4VwOc81/fP+zzr39ueDtNlYszCJc8d8V6s9z5HEaVEz6H/nUD8EkYzUvU6HqVi5BwTwajYgjIJoQIqOxHb8Kg3BiB3HWlcRK TxngYqrcn5CB+YrRIS7n0XRWh0hRQAUUAFFABXJeMLgQaTdHgE IamexFT4WfxJf8ABarxRLd/HPw7pIkEkdjYtJtB6En/AOtX4gXF/JFMrOCSTjNYYRKzZxvSKZo6K327V7WEHHzAN8uO9e3y6Wy24kc MVzX5N4p1UqUYs/dvBeFq05+h8M39rHN4/wBSf7u2YhVPPevTY7WZI8xklV9T/KvvuFIr+zqPoj4Djd82bV5LuPDLNt3Muc45HFMvIi0aKAdobPB xmvoNnZHxrTS0IEtXlTywrFgd1VLy1lt3j8vJzwcU2tNRQj7tz R0x/wB7cM675FUCu3gv3ggQSoPLOM//AKqm6buaTSauy1NDFconlH5nGcY/lXGXx+zT+U570X10FCS2I/tsQQJAykupOCcmqttKyv5fljaw5zUx31FF21Nq4aHbHIFZQo5w KyLiGW4MqowK4yOfak3ZaEyVtjrfg38Qm8K66ltcyOqmQdRjvX 6F+MNIsPH3hBLmArM7x7lI5wa/HONsP7LGqolufvPAOJVbASpPofn9rfh640PUZbOdRtUnBI/SuNOFuSCrANxg1+l5TiVXw8ZLex+R55gXRxM6bLbxEG2kRcqrd CO1V9XngS6t2UsuOTXoOWqR5DnZaFFr4KzrE5kJIxitCxvnkvY omBAZT8w6Vc5K1i6V3qVNUnEnmxxyA4zknvSaTd/IkRJ2jk5op6LlMW9bF65kgfzGEuccD0ArFkmlhmjELFFLdTTlJ dTa/cuz6pNEJVy+WGSQKyY7vy1DuxYtzSaV7omKTZSubtUDNHG5Zjn cO9XrO7dNOLthnzgE1M49QUNbs6K1uY/LjjOAccZ71PNqQkvSjgpHxxt5qOQ1e3mc9qFxliqEGIN8uODTZ 5mNtAkUm09cA5NWr2uzJpuz6kPzyTw+cWQheOc9q1NMjmkuXKu MxMMKeKIS1aBzXLc/Rf4A/EvVNHazt7pRdW1qu3y+vT2r17xX430LxjqF3HfaaljNcMVhyuM GvSqVv3VjzYw/f3Rt+B/BfiKwsYYYIEuLK5mGAi9a+zPCX7Oup/EKKymk0RIkgA3YTB4r86p4apLEOTfU+tah7NI+0tI+FFv4E0jT 9LtbNYZ0HzuU6V/P3/wVf+LkU15B8N/D10s8enki4MbfKz9818rmtCU8XGDW7SP13IMXSo4J1H0R+IWg6 C0Cw3EkRV5X3MSK7uYBSI1kVWHJPpX7FhaahTUD8NxFSU6jm+r NeCQIkYK+ZvPzc9P84pykPLOpyqY/hNXKDvfoZNNrQ6O3iiMFujFXMYyOvNPumQsZAAAOeDjFQlYSVk ck4aeVmGdvT6CsiS2kLTCMFdo4OPetVJ3si46EgEkVrG5XO3k4 qSW5a4gUFRhv4SOKqy3C/U4yWR4dbtZixURSLz261+q3wn1ZbzR7VSQGktgp5yM4r8f8YaP PhKb7Nn7t4HVrYqrDvb9T4S+KyfYfG2rRsSTJISK4O2ZZGbgbK +74MnzZZRb7I/OvEKi4ZziF/eZ9kfsX3gt/jl4aYOql5B19zX9937KVysvgmw24O6JTn8K+lnvY/P8AFW50fWwI5FRPzWSRuVmU89cVGwGDnvxVLUaK8i9c8Z7VRK7 WLYNKwiXecHPQVn3UuFOcDPNVEEtT6Etb+O4AyQGNaFam6lcKK CgooAKKACvNPiTdfZ9FvWzgCOonsZ1fhP4Of+CrfiFtc/ao8SQiXMOnW8cPXOOSf61+VF6T5z7Tl24GDWGEjaByJOMbo3PB MUsniO1AChwxYkf4V9XRQrPbQmRRjazH34r8V8YJJumkf0L4H0 XL2kj86pJVl+IOuSbRsjmY5xkHmvUoW3IigBQ4AwBX6jwrG2WU V/dR+YcbW/tTEW7shurWN1Kwna7uWbHtWbJP5MaCU/OPlwT1r3Yt7s+Riny6l/T7m3mZWLhW9e1T3SxmXdy3GQeM/jTqTdzHlvdIjgRYpJHAT5uBjv8AnWjqV8sUcPBJHUZqU7bmtmo 7iWusZV5ImKsOQP8AGuavbuRpN8wMhfqPX/PFUn3IhYoRSA72YNG3rjP4Yq9E0gVZZJNoPI5omrK5pHVIrzXr pn5w8Q9D/nFWYrhxDI0TY28EHmibHLe5x2q3TafKt0gIlHda+5P2bfjHZXk Efh3Vp9xddo8w4r4PjnLXUwzqrdH6J4dY/wBli3Sb+JHqvxg+HUd2o1rT4UkikXJKDNfD+p6bdWd9OGTAAwA frXmcC5kuR0m9j0fEPKZQqKuupEzySvbW+0qqEZ4rA8Q71upGK oRGMKRX6LFLmVj8tqLU563V2lEoLkN2xWrDJIssSl1Vz3NaSSe wn8OhlXlzIhljTJJOSc5NXNFnYpiTBJ7CrjG6TFJ3eh0M1vknY Arha5a/lljaFmYo2/Oc5rK6umU5aXRaDyvGNi5UDjI71NHBCOJJGfb2xWoQempG8Cq0 hVd0ac/hTYRDJaMXbd83fisLatlyikl5m7AkSxRTJt2YxVC5lh3ysrbWB GOKzkmndES62Mm5G9ZBvyx6sOlPtbry5oYmUESJ6cVpCN9Soba m8EikZWG5mwAAOmKrQTrb38nmEYH8OKlSu9CqkOiPYfD/AIw1LSrq1uLCaS3kjAJ54NerSfFOXUrdZryFTeWJ/dFTjc3vWiqWXkc0oJyTPur9lr9pbw/Nqdp4d8SWLi/4WNcbgx9q/pX+CHhy103wtYeKtUhW2sbyMSbSmP0r5+K5JNS6ant4XDzn7y9 Dz/8AaH8W6JJo19aWNvJp+o3iEoxGCFx2r+S39sb4OXmo+NNR1VJh ezTuZDk5PWvLrSpyrQqy6HuzrSp0XRT0Z8W6x4Ek0HQbaS4iVG ZgDxzmvKtRtIxMxdWGOACP5V9hhq7aPjqt4lFXeMW6LuAzwM5z XQ6YI3uWaaLKqO/TNdk9rsnm0uzqYjaC3knfbuXhQK5PV7ryY1KYVnOFA/nWNROUlcmpqrMxI7wq6rKuRgEn/P8AnirqzwPHLj5Sa2tbYpWvoWblwloBHHk49c1zUtyscYDcMvJ zTV7aDcexzt06m5WTkAkEV9//AAY1gCw0lQS5EeM1+aeKdG+AT7M/ZfBapbHyXl/mfPPxu2jx3qIYDLnPIryu0tpY2eQkbM56V9FwNK+V0n5Hy3iW7 Z3XXmfTH7MbbPjH4RlilaJ1uV789elf34/saX00/gzT1lYELCv8q+pnufm2KfvI+5iQcHOO1NJ4HtUI3S6DDyMHvVd lAGeueTxREERMCD0AFVHUAmhCK0jFB7CsDULjA29j6VUAitdDx L4C/tdaR4zmtvDPjpYvC/jJPl2u2IZz6oT/ACr760/U47hI2EgZHHGDU0K6qLmidNak4SszaVlYAqQc06txJhRQMKKAC vCPjJffZ/D+oEtxsrGs9NDGtsf5/f8AwUD1+LWf2nPidcrOZfJvBGvPTAxX5/6gZQysMqSecCowN3TTfn+ZhCS5Uzo/AUrwa0zyN90EgnuK+lo9aWHTr6aRwn2W0ZsfgcV+DeMDaqJ9LH 9NeBsI+wm3pqfnho2pf2l4l1K4kBJads4HXmvXWnVArxy7sdBm v2PhxcuAoxf8q/I/D+KainmVd/3n+ZXh1HBBdsOudoI61z93LLMYkdiVOT6d69rd2PmK0m4tIv2Z kh3sd+AOgrUguzIZJZAAEGM44/GqvcIbJF60l3tLJvZsY5HAFUdUmNxMc9Tzx2rFXeo1dozUcKyo rrgjnnHP+RUjwXMxjDAoEPGa1i9NSbJao2IrKOVVRgWPT8Kz9T tJLZVKbgi4xj0okzSy0scw9zvlEZG1R121tQFPLHkOUA55FTbo xrcwtYVZVjjm2muK0bxJe+E9eiu7ad8KwIwegFc+Mw8a1JwaO3 AYx0K8asd0frZ8Dvi5pHxB0GPR9VkhacptXeeelYHxS+Fi2NxJ e2sAeB/mB9a/AsHXngcdaWiP6MzXCU8dgedanyxqmi3llcLujKqOAcVwGpNKLh 45VZ9hPJHWv3HA4iNWClE/nHFUHTk77mTCGLsVC7B6dBTriVZHQ8Bz82Pxrug3ezOeDvuYE0 km6TuVJIPpWhpWNyOXIZ2796uyitCL21OruWlJKxswKDsa5TUH eZ44WZGCnkA1lGpfc2qRfQ17e3ZcLGXwOBzmr9xbhBGxbaOv3c inKWpO+hmedKZXiCqExhm9azJpSsE0QTY8b9MVEmk7MiFuu50d gwe3tt6n5SBnPFQ6m9tKz4IUcY4pNtPQ1irK7ObeGSN5Gz8uci preK4nnszHuG8YwR71rzWsRFu1ztbeznhjaUx7Hxhcn8KzJtqM N/zOMAnOa5nK0ro0lF7m9YtJFKiqmMc+1d1oVnc3c8cVvA7vM4CK OpJq5PTfREKD0R/QJ/wTi/YXsNTuLT4ofEexjiWLEltBKuOnNfv94g8ReC/hz4C1Hx349ubfw/8AD7wdAZTvO0SYHAA7k9hXxeIzROo3J6Lf0R+oZZkjWGXL8T29 Wfy//Fb/AIKQj41fFrxPd6Ikdp4bimNvZwp0WMHC/wCNfNPj/X28RXVxqF/IZBKdwPf2rxp4upWj7Vrf+kcWZ4WOHxHsIu9kl87Hzb8WlsovC tt/o6ttfCtjrXxVqbCSeR3jj2Z6EV97ksn7GzZ8RmKipM5lp4AQWj CNGeg7V0Wnzo67iMl1zwK9t7HHBJq5ccxR2xO9lJ7GuR1G4Se6 G9h5URCmoUtbhNJPQpyRK2fJ5KjOf8aqpO6S+S5U5GeeK3jZaC jFLQ3JpD9nIjc4IwT2rnrjEink529qaTRor9DmrwLFEruSMsCO a+sPhNrjQWmnoZNpU4OD09q/PvEynz5c0fqvhHU5cyv5HA/F67Nx42nZyAJRjPfFcUyGKBGjO5R6GvT4ETWWU0zw/E239tVWvL8j174A6j9l+J/hSTgEXS8g9Oa/vo/YY1MXXg7S/mLBoRz+FfWT3PzbEpXTP0XzgdQRSe/rWZuhhY4PaoywPBA9aYNkLEY4wM1TlbbnAxmna2hPUzriUBCQc cVyl3MScsSVq4pGkbXPz/8Aix8CbmwuZkns5bG+t23I6cHI6FTXRfBf9qXxR8KLy18I/FJLnUvDpcJFquSZI/QP6j3r56hN0Kzb+FnpJqrHzP1X8KeNdI8T6Xa6xoeoWupafeKH SWJ9ykGu4gvI5uOAa+gizzU2tC71orQ2CmhgeO9S5WJcrAx2qS e1fKn7Q+pfYvCWqSlwAsLN6dBWVaWhjWkf5337TurvrXxt+I2p MxAm1WYjnqAxH9K+eJmF0ZU4Axn/AD+dRgH+4Ul5nMqfu/d+RseFYzbzzSnY0n8P0rrvFGuvZeGvEE/mj5INgz9K/C/FFc+JjB+X4n9QeDk+TBTl6nx74IuGmuLm4dsliSc/WvX2nV/uMC3Uj0r9qy6ny4anBdl+R/PeYzviqsu7ZmKDKWcuSCpOSKjcrEYQGJOK9KMbHnKOlzUg3M5P BU9scVZbzJJGijX905HJ9KGtQ5tNCWyvWiJH7w/Ngc1nalKSxkXcG65BxzWcY2QculjO+2bHjUfKxGQcVvRXoURys Vx93j3rVWDS1zVtdTLSIYSu1T8xzVy/K3MSqzkPtzipst2Tvqea3KyJdOVG1VbjituFmltmRCiseOKl6D i9bmXdo5j2vg4Pr71xd7YC4eRJVQAjCmnTd4lXs7ieDvGmufDj WI7iGaZbWNwchsV+v3wP+OnhT4raRFomsXETXzJtAcjOa/GvEHJnCaxEFufunh9nXtKDws9WvyKvxR+D1/pqT6jZ2/n6exLKyDOBXwv4q0e6tLiZwrfIx6jnPvXXwZm7mlTvseFxxw97 GTqxWjPNDcSwl0c7SMA1L5qM8bowckYPNfqt+x+Vr3dLGRPdM7 SKuMhsZx1qbTboEYbAf2q3G2olBI66K4BAwxPmDsKxriJPMDhn G044rnS94cmadhcSRAMMgf0rWa7hmjO5SeTkNTktQT6FO4iUFH QfPLkk9qx5iYbe4R1V5JG4J61ly82pMdza0n/jygKFS+cAelZGrt5aTttBYAYIH60pqzLgm2UrRnk2EPkthR3r2 nwjomlXElt9okQFzxnoDSm/duyqMG3Y6nxT4H1+Cye+hSBbGLgbTzXlU+kXUdoZZlaF3YA56V 52DxUai0epdam0tTpNE0e91DUbCz0+3lupZhgAL1PFfrd+yt+y 3HDcWfjTxtBiK0YSx27jrXFnmO9lT5T2+HsueIqpNH7w+BfHnh HRdEi1PWtTg8I+E9CjyxdggIUfrX83/wDwVk/4Koa38cdTl+DXwz1aWw+G2hymJVhYg3DDI3Ng81+Z0pSxNVUI7 zevp1P22ny4OjKvJXUF+J+Knw51TxNpWox6zYXcxlLbpFJyDzz x+dfpX4K+POiajp1hB4g0y3L2ww/qWxX6rWymPs4xh0PwPEY2dao6kt2eLfGb4nWnim7XTtIgW0s7P O1QMZ9a+ZbyZpSY2yNrdz0ruy/DunTUe5y4l3djnXQbiC4Jzxiuj09pAjynYpVcfKOtepZWMIpJE l7KwtlyTkn8q5afeTJG3DN83vRTasEkth5RlKKu7Yq5ORwaotb yNIzqSxGD71pDbUlLS5o/aSgWMpjI6kf596zLt0IIQDg5xmi9ma079DkNRn3RjOwkcH2r3f 4b6n5KWhYsRu4x0r5DjmK+oNn6J4ZNrMotMg+JZWbxOJXBKFOp NchltqhVYKOQK04If/CfBM4fEmN82qM774VzG28feHHBbCXaZ9zmv7zP+CfeoeZ4R0RA Ww0C9foK+qqH5zintc/VbfnHHApS+McDAqDawxj6Dk1Hu9s0IVyNjwcY5FU3VscMSKpIL GJevkMv3cCsGQAnDYq1GxcNz6F8Y+BtG8YWEtpqFvGZCMJIB8y n1r82Pjn8D5/DkF5Ne2CXWlHO2dVzx715OPw+jkVTk4TTR8YeH/jV41/Zn1Yah4eu5NW8GXEoNxpkz8YyMlD/AAmv1x+B37SXgL40aLBqnhrVoDehf39nIcTRN3ytY5djlJui90 duJwzcFUSPp601WGRVDucGtlJldQVIOR1r2YyPPTHFznioioY5 OR9DQ3cG7izMojbkkmvgz9sDVotN+Hfie4lK7IbGVzu6fdNY1V pZGNZ6H+eB8TNVl1nxj4l1Mkn7beyuCPdya8tuJJkJwj88YXrV 4SCVGNiqyurs9A8OQr9lM2C7Oee1cT8VL9rXwrqCrlBdybeD2r 8L46TqZlGPmj+nfDj91k8prqn+p4L4MaSO2LY5POc8V6S1yXR8 smWGeOa/daFO0In8315J1G13ZFa3ZICj7x61PLIDcIuQQetdV9DHmtc14G O8uh3Adu+K27Ofc1x5gPmKMAZrKVyIp3Mh5mhdiqNtzjNZd5fx eYDuBPQj2p21sU7LUzHnhZ3cnnoDjpWxaTREuNzFF46U0hpX1L URyzrHlcnJx0rbW7CW4eRtxxtGOvvUS20JknsjCuJFeVgi5Y8j 6VLbxHcr/KQex45+lZSZKtcWa1DRvmNnYN2/wrIa3aKTPl5YHnI606TaVmU23exj6ro8OqWdwrRqXkGOmK8e0n xR4m+GGvw3lpc3UUCtkbSeOa4c2wEcTRlSkezkuZzwmIVaDP2D/Zu/bK0Hxdp1p4W8bTRStMojJfnFe2fE74FaV4rs5PEPgt4bmKdd+x D/AIV/PbhVy7GM/pOpGnmWDTju0fnj4w+Gl/pd5NDdWstnPEcdMCvLbrR7u1AHlyE46j+dfuGR5vCvS50z+e8+ yeeGqtNHD3V35StErMrxt1xW3onkTIm1mLsMkmvpN1c+dVlozs o7RmhkClk2jBx0qhel4WiRM5JwSa5Lp7FVKVtCq1+kCujneobg jvWb9vmKSFHAGflBNVytaoyVN7G5HqDGK1WRlZzwWPSrU1usdq 8+8fNkjA70N20NJJKOhY08hY0AADZ5FN1aMSRTEgxLIMgetRJN ryFSk7GLpjGGRY1UEHB5HQV1+oHVLKO1vNLjaR1G7APQ1z4qVq ZVG8ZWOf8ACPib4n+Itdv01m/mj0+3m+WEH5QPpX2nofwp8Q/EK0sbbTtKuhESA8xUhSfUV8jh4LDNz76n0FWKxKtBbH6P/Aj9mfwv4Bjs9R1uFNR1xgMKRnBr7H1/U9A8AeHJvFfjbUrXQtF05N0UO8KWx7V8dneauvUabP1XhrJlSp xlbVn4Tftn/wDBQ/U/Hq3nhHwZfPb6Da5iiRGIB7ZPrX5AWVnfa1qralcySSyzncN5ya +j4Gyt80sVP0X+Z89x1m6jH6rB7bnuGhR/2bYlIsbm4yPWtd7y4SzieNnD+ZjK+lfpcdj8p13K815IbpUZ5G kZfvE1TGoLJMsMgGc9elErPQfMr6mZJbqz3DK+SDxWnAhhtF25 LL+nWrTViVbYguZnmdI2ZduRnNZF24jcgBy3TpzVRikimnuxUl LLEQVKvwcdTWogK5Zgucc8f0qpak6mbcRsZChBkXG7nis+6XKG NWBfHJFSpDhPW5xt9wGR0UITjrXrXgCSMrbsGISNhgt0FfJ8bJ/UmkfoHhsmsyikbPxGWJtYtJXLEtHzXLW80XVmJU9BU8DX+oxTF 4mwazed+x1/gmRIPFuhTxsF8u4U8dOtf3H/APBOTWnm8KaArOGBgU5HToK+uqPU/NsU1ZI/Y+OcFAfUZqVZc8E8e1QCAODkDpTGkA4xmmK/cC+c8VUnY44BJ6VUdQk9DHkQyEjP3qzbqBUBzk471Wo4XufVss ixgliAK4Hxeml6npl1ZarDBdWc6lWRxkGoqtNWZcmfhv8AtOfA Yt4kQaHeTvo2osxW1B+4fb1FfO2h/DPxz8HL2LxR4a1+903WIGDIYzgY/ut6j2r4yeGlTqurE9nC4v8AdqEj9M/2dP23dH8VXNp4I+Jph8OeM1xHHMxxDcH1B7H2/nX6T6XrkE0aNHKJEkHBHQ19RgsXGtDmXzPMxNHklpsdRFcpIPl Oc+tWgQehrrVjnTIbplSCQk8AV+U3/BRTxOuifBX4g3CSASR6ZKBx/smsMRK0LmFd2Vz/AD99TupJ7+5cgHzZS2c46msl40kLb2++3euiguWCR0ON5NnrWg 6f5WnK2GKgZNeE/GqdIdG060D7jO5LDrX4FxDVdTPacP7y/Q/p3hpxo8PVZdov8mef+GokXSYSUI9sVusNxm524x34Ffv8G7I/miW9yqWSDCZYEDqpxWha+azs7uOe2Oa2cbLUyck2kdhZBeXVto cdGWpImMctxIcbMH2rORo01sUHe4WNvkUooPb+lchfTozPyFIP H/6u1S97kS7lJQ6hZgVKnqSK0rGfaB+8JGMcVqmg5kX47sx4JJQs cjirj3DGEvLICQe3Wpm0XolZFNb4SzBxnKDnNa5d0eORAzKPmI J61FhOPRGhHqULuI5Nqt9KrXOW2NxKD0yP5VmrJjdkzNEMYaXM nyse46iuI17QodRhuI5o433Dr6VSl2Fz3Wh896lBrvgu/bUtImm8qNt2EY4x9a+4v2df27tY8HNbaXr15NPaq2xlkJIFfBc ZcNfWaXtaW6P0zgrib2FSNKq9D9SNE8X/AAi+P+mxTLdafa6pOOCCAc15b45/Zr1zTYprvS7ZNTsCMgoM8V+W5TnVTCVHF7I/VM9yOnjYc0Fc+MvEnwqu4HmW4sntZQf4h0riI/BeqWbErGSkfvzX7XlWe060E0z8HzbIJ0ZtpGlEl9axyqyMAevp +Fc7c30zwyIxCmM817KqRloj5yrBpamG0+4FohvwMnB71W2NIq 7GCAH5q6p2asEb7mw7COBUkC7lIyR1xW9LMj2CqMBvU9/8KxT1sVKLbuh/lSxCIlkzIMj6VoyB5Lc5BkVSBk84FZTfUyStojKNndtqAa1ilY uowNvH517f4H8B+LNYktY47GYxznunGPrWGInDl5Zm1Kk2fa3w 0/Zx0XSbw6prcaNd3BDmHFfoRoU1rBpWm6TpWiWeh6VaDDzuoBPv mvgOJqjppqGx9pwpQjWq883szzv4p/td/Cb4B6PcmK+tvEvixVJSNZA20+5r8Gv2mP22/iD8bNRmjudSuV01mPl20bYjUE+lfGZPgJYzEKMfh6n6xmmaU8D Qc5fF0PjXS7S61a7FzcktJK+WGODXsFnp1vbLB5ZQSr1NfvGBw io0lCKP50xOKnWk5z3Z0MMOyJ1jYhmHGaz7uaZbVVfClZP4e9d cWZSVtB8Tt54YuHLpkc45qvIoE8jAZYnPT+tS1d2Ikm7C2rRt5/nJtAPJzVj7bHDCBG2UbnIrSTu7FtvcymvBI6sCPMX+HFVbxmlR 2QqNwxjbilawSu3qFmrRmIEquGycVvHCspbYXLZ9qcpNbD5kmU 50cOx85fmYkkfSsO5lScsjO0Zx19TTiKNrHMajF5cQcuGC8V6F 8OZA8AHC4bgnua+a4xV8BNo+98OJNZnBo7T4ixgfYJzGXQqO1e dblWNZFZPMX0FedwBV5sCm3sdnipFrNOZ9UjY8KXkkWtaZIjEb J1IJPvX9rP8AwTP8RLceFfD25ihMCDGfavtaisfleN0imz90ob gtGrA5UgYqdbzbwcjB60rE30JRdjAJJx14oa5Bx83BpNA31Jkk D9wCaSQ7s4bOaEgdim4Cg4wCevrWLeyAjaOT6+9aKLuXBao981 XWo7ZHZnUnsK+b/iB8SIbEfZYla7v7r5YYUPJPqfQVyYipZaFWucD4N+FeqeKdRfX fEX+l3Vz0DfdRfQCt74k/s2aNqGiytpO+O8VSWDcg+w9Kirhk6diebU/In4yfAm/tri7a2hms760bcGAwwIPau0+AH7anjP4N3tl4M+LX2/XPC8bCKK/YFpoR/tf3h+tfN4et9WrX6Pc9aNqtPl6n7YeAfiR4a8d6PY674Z1iy1X TrxAySROCOfWvWbW8WUAMw3fWvrU01dHluPK7MXUjizkI54r8K v8Agrh4lbRP2e/iLMsiiWWzMK/jxXNi9YNHPVhdWP4abiZZJDJKwG4nPzcU61cyTwRlVljZgMCvQ eiO2OrPpTTLWI6RI0eQI0x718g/tCGCz1bRdPT+GLLCv5xdRVOIaaXdH9SVMMqXDNVx/l/Q5vSCg0oIpx5gBxnpTyzOk+1WJkIBI44r+jYp3sfyxK9ixArCN zJtcjnrmtCNZXRmATbJ6VtK4Wd9TUt3lgGQNq465zzUfnzmSVl clf51itSpJMcJpDbybSDt6BuK5G7hZrhGbcCx544pQWpG6LAVi j8AtxjAp64RkZ0Uj/x38a0sr3Lcb6DpJGba42Imck1aiKzRorvlWOTz+VQvMUWyKRdj xRqqkSn+KuqgcMGV2VGxjP8AhUydi4oxrllhmSRcluhwRU8V2r riUqNvPWlFEpa6lJ5GDbt+UbsBVC6nBcxqTk8dMijk10FyWdzi NStrS7jlhdIpC55IHGP8/wA68W8TeACyi80vdG2T0GBQ4Xjys3pTcXdHP+Gviv47+FuqQy2 d9eQpbnJ+c1+pH7P/APwU3nsUtdG8aKt/a8ITIcmvy7i3hFzTr0Nz9h4M445Ixw1fboz9KdA+If7O3x4tEm jvdO07ULoZzuAOf8msHxR+y+sqS3fha/t9UtH+ZQrA8V+dZfmdTCz5ZL1P0PNMppYqHtII+dvEPwU1zSUa G70adcnkhK8N1X4XfvZlWGSIk8fLjBr9LyjiOM1uflGc8Iyir2 OCn+Geo2r+VHBKB0yaoTfDfV/sLMlu/mBuMCvrY5zS5bpnxeIyOrTb00K58GavAUBtmkJAGCuCa15vBus zQRRfZZIpMZPy9PpW1LMYSkjllltSL2Ol0/4ZeILxIvkeV8g85OK958J/s8a/q0UMDQEJM+WyteVjc9hFNRZ6OAyGrUabR9sfDX9kDTpJtOF1Yv JOxHG3ivsJfgFpfheyWCCzitJojtjYoB9e1fLQzt1KvPPY+oxH D3sqXJFas+evi18V/AvwUmhudaVL+/ZDsRDkAjpmvyd+OX/BRPxZr8WoaB4ccaXEGKqImw3Ndee4OWKpKnS6nk8M1o4Ws6tb7 J8FJf8Ajjx9qRv9cku5Ib5+WkY59/610tz4FghaORIiBH6/419Hk+TwwlNUobnk59nlTHVXOTNGHTre2SNAqp0BwOtbDBNqCM Dy0OcqK+ki7I8CKtqi/DJG6MfMU49D2rLvGBhPzOhDZ4qki2ivGwjcOXOGUYxVuKQ+cpU AqPX/AD6mqceqM7W1ZEI1ME0zkBVbAA7GsW7laGLP3hIM4qU7q7Li+5 kC7K5aQCNicgnqKcLgl4mDlc4JzxWttRNpu5pR3EZZcLtVWAPN bBuIty5LZ65FZcvMkZ2TepRuZAxAglcEHmsG8QrgADc3zcdq1i tS29dDnLoyLkEF2Ixn2rqfAOoLE0irkZIGM8D6189xRBSwNRPs fV8D1lHMqd31PVfiFdpNo2nTk4bgcHFeWT3Aa2RwW2gZwBXheH i/2N+rPp/FeXNj4t/y/qP0q7NteW08bLhJASVGT1r+u3/glp8R7PU9C8OWwureS5SNVK7sEfhX3s9NT8jxkLq5/SLps7SWsUm9GDL/AAmrvmtuAKE5OOKQo6omDPgEjApyM2Qw5x0qWFkaUcoKjIzSvI e3NERdLlOaTcvasS5lKhmIH4VrbU1pbnMePfiM6XDaXpSte6xc nCxjkIPVqn+HXwvutRvP7Y1h/tV9cENJLIOnsK4aUeadx81tD610rSbbS7dILeIIijt3rTliSVG RwCG9a65O+hCWlj51+K/wR03xhBJd2iiK+QEjH8Vflt8Yf2fUc3EF9pctrcAnBK18/meEutDfC1OV2PmTwV4u+KH7NniIal4Tvrm40Rpc3OmykmGQd/8AdPvX7Jfs+ftV+BfjRpcZsb2PTfEduALnT5mCyI3sO496wybG tP6vU+R3Y2kpR54n1VqGsxLp7MzAqRX85f8AwW28WR23wF1izV zH/ad0kYJPBG4Zr1sw/hSVjyLc0kvM/jsul3hyTuDHtzVrw5D5mrWVuQVJkBye/wCVd1edoM7aCbmkfZenaYn9lmNVyJMAV+ff7QxaT4jC0ZgREq8 DnHSv5w4dqe14kTR/WPEa9lwzUS6o5m3iliSLy9qnb6dqlt72UhkbCszZJNf0ulrc/ki9rI6G1MbIWYt85x0q8stq0O4kqI+B70pMcdRXnjiIO5gWGcC ljlgdSoAXd16Vm31BblgWa/Z5D5qhjzyaxby2IijfzEYp2qXK5VSWmpWXYh8onHmDIBPX/OaRRzIDJnqAPStk7GautWRzQuqeZhzj9KrQtNbqhkfarHsOoqW i076G6rxtcxPvyFXOSetaZukTCrhTtwBnrUSV3YoxGd2chF6nJ IqNUCurSgqvpQlrqTyE6OqStHGpY5x7Vk6izGVFU7WY54P+faq v1KS7nNaipjBYsA3asy2nlm3Q4CLknJPNNSVrg3oc74t8G6Zqs AZYkSYjBOK+ZvEnw61fSr2aawZlUf3ay9mpxcZFQk1qtCr4e+I Hj3wVdxtYalfW6wnICMev+RX3f8Iv+CjvxM8ES2VtqOo3F/ax4G2Vsj8K+B4j4QhXTqQWp+ncI8cToNUsQ7o/TT4Zf8FPfh34jhitfGuk25d8KSR1r6s0P4t/stfE0JLFqWn6dPMAT8wBya/HMXgsRgZ++fsGHxOHxlPnpvc60fBv4S68vmaN4t0t0k5A8wVG/wCzJpsiMtlrWmzR5zw/Wu7C57JdTkxPDsL3Ma9/ZjjcDy5rCQIOOazpPgRDbASTvYr5YwCSK9H+25J3PNnw3eV2bF p8NtB0uMSXWradBgdSwrttO+I3wu8DGIazr+mkQnkhxXkY7OLz 5UztwmTRhI+hfCP7fH7MNotn4fOoWNlqqfIs5YKCfqa+df2xv+ CgfgnwDo1zP4P1rTvEM1xF/o6o425x14OSBX1fDVFYin7WXT8T4zi3FPCVPZR1v1P5wvij+0/4u+Kl4rRPNIed8rnOSSeleT6D4auZtQS6djLOG8xvMJJNfqGWY JU4py3PyTHY5SbSPuz4UeJ/CEC29l4i0+COSEbdxGQfWrnxM8QeFdTvJI/D1mltZwLtXAx+Nd8oyjNLuedGn1PDpgGiMiElVOeamhmQROgJw 3U4rscebUcZJocqmUSsgBycn0PFYVxNMAQwbys4z6U0thbbCzO jIrgqv86twSrHHuKFWYYHtV26A49RJLsRQOWyyjoCcVjXN7HMs arhdi5571KbuVGSsYMsqs4XGCvoOTUoG+dPmPzE8YrSCtuZz03 I5pGjYFNwPYVbs9Qk2ZlAOOcVV3Yt2HS3Ee7dtdSwyMetV55d4 hAJOwY46ipiib9SrcDdG6HAbb07/jWVoU4t7mZQ4Y56j615Od0k8LOPke7wymsdTku565rUxvfD1tu xIIQOM1xHlOYkVSoKAA5FfNcCpQoTh5n2PibTbxNOo+qLFrbyJ NA2RgsDk1/Uh/wS58P6fc6R4ZuEiMF0QMuvBPSvupyTZ+VYxtRuj+pbQLP7NpVk qOzMUAyetbJVwMZIxTRjSdkOVnGcN16VcinAwCOaqLLLa4YAgj nr7U12Kj5W3DHejlE+xRmY81kXZypHAzweaqxpTWpW+Ffwo2Ea jqfnXNzM26WeTlmPtX1XZWENlDFBBGsccYwABUOCWiFzXlc0Bw QMZH1pCxHao6jGFlZcEVwfizwRoniW3aO+soZyehxhhWdSmpKz Efnp8bv2cJYIbq70+0+3WLAk4Xla/Lzxd8P/ABT4A1oeJfB15f6Nrlg++KW3bac57juPavksxwrhrDdHdhcQ1K zPsX4Kf8FBopYLXwH8cLdNB1pFEcWpjiCXt82fumvy4/4Lc/ELTdU+GPhG10vUIb6z1nUBIrxuCpXrwfwr1VjVWoXW+zMcXh+S qnHZn8ycckUg2EqdvGK6vwzpN++rWF3HaSmDPynbgV6uO/hyfkb4GKdaGvVH11oizQi1WeGVADkgDHavzP8AjDfPq/xb1mUrKywyFUOO4r+feCsvn/rDzPZJn9KcaY+P+rnJF9kHmkCJQTvJrMcLHJGgYhs4H1r+kINn 8vuTs0zoLKMmJRK/mRj17/hUk8wwgiQbFOSBRMFFIrI45G10Ud/enQPIX3Esm/p7VDjrcfK1Zm7HL5sTqWLMeM4qOZUFoDOSioc9ahrsXO1znLmS QynynG09DmnWu5pY0SUAqOe1aRI9Tct0+R0kkyzDAPTFYt8Aqq FUPjqQanm1sUmlqWrCYSyqnzLjG4EZFaN+hTc5Yl8ZAxjFS5MH 3Rlw3XlyFpjt5xnnFabhZIzMzCTHP0zS82UtStFsByCdyn7tY9 65eSVtgzjaOM0k2CuZ17bPNCQMvzxWBDaeW5/dEKvfpWiWhMXa1zTmgeZIthHPGcYrmr60eSeNDEron3sij7Rcj lr/AMFaVqjNHKkKSSc5A68V5r4g+ErfZmkswG2gjKipnBSViE9NDy G78JeINIcG3uLtTHyBViy8XeONABNtfXg8oZDKx5rxcyySjiI+ +j3Mvz2vhtYSO/0P9qb4peHVQW3iDV4hDgACU+vvXsWh/wDBQX4z6b5aL4q1NVOAQznAr4zG8AUajco7n6JgvEyunzVdf+H PQLT/AIKUfGYq0ba/esM8tv6cVUvv+ChnxcvYyJtevQgOCVbFeK/D5KW+h7NPxPSj8Opxd9+2T8SNXC+f4g1Ms4J2iQ/415/q/wAdPG2qs/nXWoTGQEkl89q9XBcDQgvePn8Z4jV5PlhocfJrvjDVGW5F7eQu hyCrHP0rZB8V6+kKarqF9fKmOHfcPoa+1weUUqSSitj4LMM3qY h3mz2Pwt4LWBLWRU8o7RuPrXr8NkkREccaRgn5mFego31PCg1J G1pdjG9yzMwXDYB69a3L623JNHEpbPXFVzLS5tFO1mc28Ejxup AOWx1zR5CxhgMKQueD3rojIjTZFVbjyInG51Ru+axpLySeKSNi rr6g1aWo00tGRTuUSI8AqOv9K0IJ2kEO8sSevOBU8rvqK4y7ke SGVChVCcAkA4rnzG8TxtuWT6CtC2tL2IGQyyEsBuPK5/z7VX3GKd2DDB4AHNSm9iGr2CUmQKXBD7eBjAqKJJFBcqFYLnHX 6VaStclNMszOPL8ssHYjOMcfjQqPugcjYW/lQxo0ZbeLzJFkQIQudzVymlrGdSuI95J6D3rys1u8PJLsz3Mha +uU7d0ezpB/xTc+VOFAwSOlcjashKb1Vwwycn9M18TwLUb9rF9z9C8TqDU6Mv J/oPkkRpbdY0UOrcema/qW/wCCUtxJL4e8ONLskYYAI/Div0ho/GsYvdP6mNDO7TbQbCpEY6VosmTg5Iot2Mad+UcIcjIyKUKQemc dQKtIrV6CqzfT2zUcspwcE5oSY4t3syg00mSOCp71nXb8ZzgVS RtT3Pq+ztYbWNIoUVEjHAA6Ve7duazk7kIj39eORUbP1zwBSad rgyBn9DgVD5pDAMc1ArMr3llb3sTpNEkiOOQRkV8e/GD9nXTvEEc2oeH7aKK7OS0WOD9K5MXQ543W4ua2qPxY/aV+Dq6RDrFvqmm/Z7q3VgCVwRxX8yP7UPjfxVOI/Cmp65fX+jaVcu1vBK5dUIOOM9K8LA0orEW7neqqkrdjxP4HWWn eL/FMmhahEXllj3Q8gc+lfql8NPgheanoVvZWfhyTztPJkMhjydv1 r62cE4s5VJqSd7Hfap8A9bt7Ca6xBFtQ7VIr8cPjX8F/FWieJ9V1f7KksbyFsqf0+lfLZLw8qWNliFrofc55xQ6mWQw/W58qTeKDpupT2Gp2zwSKSBu57108Tx3Udtcxscg8gdq+o5tT4e U1udHbTpEobYBuJpr3KKWEagnPStZSfUWm44Sq6J8wQg9+Pxqz sVGKgAE85HP/AOqpe1mF/e1Llm20tuyGY9APyFXTCkscizS5jPRc1CVncuyepxV+ixy+Wvm YxjI6/pUNi8qTq5OxcY4rSDdjODs7I2mlChgs2GPHzDmse5vZVJCDKpx n+tKyNdEVBdFJBPGSjEgmt06qroysSzhOvejl0B7WKQk84sdo9 eDUzyygsu75SM7s1E0NR7k0Tt5gbBY4zj3xVad2ZJVEoGePUii nsJTbfkQOGEWxBkJyeOKydpBZWViM5NGlirJo1YlWWJIBuOxvy qhcWxUkeW5IPBzS1vcTjc56SGKKcvIzBiRnvWlHFI8TKdjqOmf/AK9EnoPoczf6VZzIUltWb14ri9X8GabdIHjjRWPPy8Y/D0osS9zyzXPhylshmWTfE+cD3rxzV9JhsLhopBsJH8Qxn8aHe7 Y22mbuh+F4tQ2yWpEySELhea79fhrMrZMEhzzk1zKNylK+p1ml/DMhY3EEhfHK9K6d/h0YWUhEO44PFJr3tCE76s6rTvCUEbRLNsjHoO9dpZeGLQSuY14 XuBWslGJSi9mdnaLb2douUZnP3ccVYsSXMsynzULdfSk9AUUkz RSHynilib95vGFz+daDXEqtiVhyfSs7dBxWrTKzFHTAcK2ecGs 27n8pWBDFhxW0Y30Jtpoc9PeloXj4Zc9aw1u9qMABlmwea1STF a+5Ye4M0cQ6JjsOlasEQRUPmOARnPaiT00BtNaDJmLxyKrEFzj g9u1UWVgY9gOEHI60D1tYhRlkmG4IATj8arTW2ZHjUDcozzQti rJDQjcboy3GPpSeYBlSo2Hv2/A1bQmu5VAJLLt8zGeelbFuiyGEFm35HGMVDV1ciEbu5FemdLlg EByOOOlcVFKY9SLqSgclAOwrixai6Mk+x62UStiIOL1uj3HTLp rnQpImAJ2cYP615l9qkimkh2gbDzg18BwM+WvWg+5+o+J0f3NC p5f5FyOWQlGkGWY49a/oT/4JSfEzxJpj6VaXemzTaVFIAsyc9fWv0x7WR+J1ppRdz+xzwBrU es+H7G7jicI8YOW47V2ewHOKSasc8XorAFYDqB+FIH+UHjJq0V d31IHk9QSSapSPwck7qZS3KMjH72eg61l3DMcglqZvB2PsdDgE GnEnBIqG+hmQknvjFMboe2ahoGyjIQrcjimjEmR0qQRMmRxwaW SKNwd6jmglxufHH7Uvwc0j4ieC9bszFb219LAwjuAnzK2ODX8A/wC3f8J9c+Evxc1Dw1r1xFciXdPGyHI2ljXj1KMo4uE1sFOTV4d z4m8NeJdQ8DeJtL8RaQo+0WUgYg9CO4Nf0i/sV/te/CvxZ4a13R9QvdP0jxHdad5CQ3OAQ+OcE9etevWq8ibexvSpe00 SNnxv420d9MvGXxDp4WNSTiYYr8l/jL4usb+a7EGtafcMuR8sgrw8hzdSqtXuz6niHK5LCxdrH5ffEP S4r7VZpomifDZ3ADNO8OIYYWSTOxRwD619G5Xlc+UpQtBI3Tci PcSXAY8cdKlt2Mi796uc9K1TCc+hrpGd7KVBwPp+tSoPLYtKQz A8A96hmmyuwd3RmYE8nP4VPb6qoTacFQcc1EtdENI52+lWVy8G Hcnkk1nIxDJ+82kjJU81pGOhnKNmkx6XAVmYtgYJBBzzTLqSNo 1YYCAZP1qbF3szLN0BMuSjZORnvUpleX95wueT2prYzkn0LNvO quhblSeh6V0EaiUIRgrIMHPp/k1NzaxNGwtwF2lhH3x1rOkDMHK/MCvJI6Co5nuJvsWlysUTYyowPwrOu1KyNwGDgY5qUtXfYfLpYb YzGOQK5GAep/nW/EFnMu9VOBlSRjmm3rYaOcezgln8yeE/u25AH+fanW9sJdxKKingDNDfYT8ilfWSxRkjCh8jgZrh7z7QxZ FPy9R34p0pN7iTMrV9Pb7EZI8Ox46cV8WfF+XUBqEMFvGUcn5g BjjtVPVitrodj8Hbe7je2Eu8M3G3rzX3zZ6XE9nbtLGu7bgsa5 qra1IvdXRv2WjQRqqQKFUHknrS6hp0YdcgB15IArRq7RtFaWMq 5s0jlhbaqqxHQ1fs1RC67GY425x2pJK2g2SywLLFmNgeduewP0 pmkrPDJJHICyvycUSS+ZK01RNPLIrKI/lAOfWtm0kilRA4zuOT3rGT6g3qiK+jZMNbsQN3OfSsu9Ys8Yx8 wXoPWtaTKas9DAuEiVGDqQMk1zFwI2dmBcBT6da2V2Tc0IMyRD D/ADEHH0rUml8tSu3lRwcYz/nih2asQl0M+2uHaVg2Qma6MSK0P3NwQccY/wD105SRpHsZaSwiXY8agn9arzTRmR2jQFcce9EU+okmmTtJCsY bLPkZJ/mKxbiYs+1gqHIHPald3sV5lVHeOYgkSFugIq+kyZTJfcuGP+fy pp6akczSIrueZptwOFYZOK452MeoxsFVhu+UkZNc1eF6b9Dsy/SrBruj3fwtA0ttOgyVK44HbFeR6m0ltq1xE67QGOK/NuDXbH1I+R+x+IlL/hNpyZoQSoqBg2XcZwTmv6Ev+CU07RwWSnMsXnDrz3r9PqSvsfg 1Z6WP7J/hw0beFdL8tVQeWM4XFdwT0OcY7Vb2RjSasrERfjqKqtKOcEsSc +lNPW6LvrcqvL1wcVTeYLjnHtVpGqK7zD14rPmkGCcrn3oNYI+ xVkJJOQKk3nHJ61k9HqYrcjkfbzgE1XdicspGKmQNEW1mPzBWz ThtTqAMdOakEPDI3Q4pSOeTgUB0PHPilOI9D1In/nkfwr+BT/grxqS3X7TVxaRyqVtbVc89Dk1zVV78THVTTPyvihhnfy+O/SprODWNOvjcaPdT2coXAkjfac/hSzJ/uZHu5ReWIh6ljXvGPjS206/tpPEusSK8eG/fnrXyhpupa1e6nd+fql+26Q8Fzj8q/P8Aguh/tdWdz9Z8RqvLgaXKewafoq3sazyTy+Yg7mtd7JraMxcASDJI71 +l030Z+KQdzJknXzfL3IHi4x3rVsmzsYnZk9K6YrQS8zaNzjBL h9xyDjjNQw3oG4uGSNRu4/z9KzW1mNbKw+a4RoDIML8uMg5rCFwRtU4bzDxjvSgzRIoXE3lY AzgdxWBqNxJFErgMWZdwHT8a0SZEnrqUodUcpGWQKzcZ9ea6Tz DIg+8u4AE96JOy0IlU1SMqaUxz7M716dKuxuvlJtILMcMO1Bou 5aDK7YUkMPer0F8Ld4QSzFTjGaylcpxOqSaGX5gSFPXPWs+4V0 W42lSh6Giw9tiKGZGiiVyWYccVZu1jfynYsN49KiSKauZM4jjn JWTy17nGM061vmTaincp5/Cne5Dl1GtqBaZlUoC7c5OKHvA0TDcqhOhrLk2iDWugs0srWDBJ Iy3Yk5rlzBHPiCRWWU8BxWkErsbRW1SO30uzCzuZCq7gccf561 8i/E+60qa9hmd4oiAOG705bkNXPQfhFd+HZvIWa5gikbHIwSPxr7H uRZQ6bAba9WQbc4BzWVaFwpys02O0zUbOGNFDu+485rVvtSs3l j2xb+eT2ApyTVgV7GbNLazSR7Y+QepqYuGmcYAbbwP8/jWK2HTva5FAAwZC5BHIGcCiFPIlZ1dmOM9Oa05rKxrFX1ZgtfM JHjdVXac5xXQWN2zWxfCvhupPNKrHTUlztsjQnmUWscp2u7HPT 3rm724XzMYUEc8D+tVTV2huPU5e6meTc3IwOmc/571kOJd5ySVU9D0rfbQi6RrWzKdrj5VUbcnt3qzeOYoSJJAC38 J4pTWhE+hn28o8wIY9oHqa6RWIRfl3H0B/KnMftNLsyrnDyGOPcHJ/i69KozllDAxsQpyc96cdNzWWyQ1ZcQgZI54+bisS6lZ5Cf3gx8 pzkD681XKrpisMW4KFSPlC8cipkuZY9q9ABzUStexjKdtSGW5L eYxUD5ccjtXPNdRi9g3kby2Mt2qai9xnThvjVj6b8DMsyLyVEi Dp9K8c8WwCDxDcKB8wY4HSvynhaaWb1F6n7vxpH2mQxn6foZ6c SKWwJAOMnpX70/8ABKvxDHaz2ltNcLHIJhwT71+rVVfVH891ouUbI/tL+F96brwrpbRYKmMYOOK9Jclc5DZNWtUYU1dFZmYjgA44NVXJ OcnBp3NUVXKZ5OeKoSSKcjbkVpE0ZQllVQQOB3rKubhecFgvtT kiISV+U+1lYdKduzjOawkw6gxAA6kmqM0TE5jfY2amWuoJ3QRJ dZCs8Zz0NX1jbA34Y0rW3Dm1sO8s4waYVwCSSxI4FIR4B8YLgR aBqZ3BWEZ96/z3f+Cmus/2r+1b40WQgi1VIxk/WuSq/wB9Bef6Mml8bfkfAMW2OdXDHGPpV231B081F2oT+f508ztKjJH vZPJrEQa7nL+JLgtY37SBlYr1I614X4YtkuLq5Zhk5yMCvhuBf 4tVn6d4lVL4ShFnqUN8ba3KRyDnj3qCTXXZpEkkUpjgD/P41+iU7vdH43CbtqYS3UTuZzLsZucd66ewv4meISuMgcEnpXRN bMpq7uX5bmJhFgk+Xnr/AJ9qijMzhREqMpGee1TzNolN2sxLwtAoSQDdgdqyDK0cke6VpN 3Q46VPXQ1urXLDW7EZ3A5H3T9KydRt5N0e6PDIPrWkNEKXS5it afvH2FUC8jnNacbShIFDM4U4bmpne6aOacW5IJFcjcELY65pIZ RuA2jcpGRTbsjVvsXUO4DcjAJwVHrVq7wEj8pVyT1qJaGm25Jb 6h5c6gklx17810XmmcOowxA68c0PQcBrKsKYy2SM4A5FFxcEiC Ix52dCPWpqRTVib9DF1YH5Agw2eTWbCmwqpkYsxyBUwjYvpoWl DyNl9uR61LdW6fZSzSGMj9Of/wBdK9nYVloyl5jraFYyXVvWqceYo9nKtKeBRqncfNpY5HxDBdN vWRmmGPqcV8W/FfRr68u49izII2zyMUNuS0Mak3ayLXws0vUbS6gWRZmUMGOPSv vTTLlk022UsCTwSTxRNq1h81jqbKJXhyQACBgjrUkrhZYI2CeW DwfWsJTTlY2jG92ixIuLiIqcnOcA8Vf8xXJbb5eF+8TjPtThax Fug6CdnBiUAoffrTmlc3CBOVIyfUCqVlozRzs7GLPHGznKksw5 ArRsBbLZTAyMjvjj0qm3aw00nckmnVLWJY3Zk9Sawp3Yz7yAxK 54bg9acY6aEz21Mt13Kd23a55OelViDuITaUP8Q5rVX3BbEiyt GfLdCR93jtSXM6skRJZyM4x6Ut0Zw8yO22PKXxhvyq3HcyxyMw bavUZb2pvcG7ak8U8c8xErujKeMdKnv4IGh8wyI5fgCiXQE7q5 zkYdCoPAXrxVeaNDIzKu1s84NO+pZVMLZfJPzdgc4p6KyBlPzY GDnn6/zotdiSuOdIhEyqdsh7Vxs5AuIZAdxVuMnJrN6xdi4KzTPofwHe mN7dWfhlCnJrz7x/drB4kuQv33IKmvybI6Tjnf3n7xxK2+HU1srfoc9E/mxjDAMo5PrX6+f8E1dDGq+Iobu31i6s5oJgAqthfxr9aq7WP58 rSag+U/uI/Z8s9Uj8HaWb/UBOkSAADqeK+inY4Uk5FVBHPQldXKcrMMjIBqi5PpkVdjWDKUg zx0HaqEg5PB9xWsUuo230M6Zgucgg9q5m+m2kkDODTb0Jpq8j7 tAI6nn1p6njk8jmuZPVlpD8kjkcGoCoJyahomWuiJVDjoenrUy sx70g6EucYyevtUbdCTzx0xQC2ufMPx1ukt/DWrSFgp2Gv86X9v7VTqH7U/xMmicN5V2Izn2Fcs/wCND+ujJptXa/rofJFtchVRWYE56irJkJeSTOI92DirzFL2Tse9kKjKvBdP+Cef +K7mQWVyoYZDdSf0rhvCcQcu3zMzHOB+dfF8GUUnUaP0HxKrJU qFNbWZ1M4KrtZihbPfmslldGLndsHcjmvv4SaVj8ni7JWRGkOQ 7AAiQc54q6GMEbELjAyaprqNov2d8sr5b5s8EZ711Fm4K/JjZ9PzpNq9kKLuOu4ong3qylgcYrGurYJ5cqIUIHI60orWxVmP s7kqz7wWGcjPc1Zv5IZojKF2Y+U5qle44u78jlhHGkpJDFupoI lHzKpA9utaa2CVzLF0xVw6jYTtBpvnKJDEpwcgjIqW9SW7NJGt Z3SxsCxbauBmtOS6t3tQQPMZGyD2rPlu7slMwLidfPWQOSJBnH +fxrY07VF3j9+CoIPJpyh1NXojqp54JollJZ8nAx/OiOcCRRIhOBjkdqzT7jvoinc20EhGJVEROW56e1Zsj2m6ExEHa cEnjNTUk7XQnsEjhGJHyq7Z4Oav3FuWs90gZlb5Qo7f5/rQ0tZDUbK6Ivsw8lViZWcjGPeqdzaGLyANjuTgkdBUtdwjC9yC +sAXgdXBdxznpXIeIvAdlqUoE1vGWb/Z61cXpYiau72MHRfCcWn3r27wIiRnIb1FeiSwQxKiWhYxxjLeh NTb3hxp9TVtrqGCAKzspwRweKSeQtPbyZYpuyNx5zWbtduxava 6LCTt9qBbCqeC3vV6SaZpMb1JYYzQknqDavzDftKoAPl2Z5qYX S+aCu0OOCM1omOS1FgdH3neSWHY9KcIYpbdyR97ipntoDV0Pkh lW3RBtMeOtZRkTI3nAZe/pTim1ZE9DEaQrIUZjnqDtqPzmBJCMNx9cZ963j7q1CxEbo/PtAI64xSR3BKjIVsHJyOlTUT3Qr9iot58wJYZA5wcVoJcGQJyi DoavS5PNbQqrJIJppVy2zj2/CrcEryIzHc5HtTsmUlfYLdo381HOFII46VFLCuGdFZe5Oen+c1 OxVylE+xt+Tg5PoB+NMVhIpCksQSOneiW4JWInRzE+ZenOeufW uRuwqSjB2yE4Yr165/xqJT0djSK2uez+BpmSW2YlG4zyc1yvxIfHiB/3eQcEkV+WZVTTzu/a/6n7bnXN/q2+Z9vzRzVsUEZ3s27jknoBX6tf8E4vGkGjeNLbS34aWQHrzX6 tVsfg04po/up/Zw1aLU/BemtCxZhGCefavpNpPXtTp2sc1BWVkVnYA44Gartgg4xTTNkux VcdT0GKoTFgMjmtIspnP3ZIBJIH0NcvdydQwJAqpOxNJ6n30CS PcUAnvmuaW9inuOLEYJOcUgIPvUpakpa6DuR3xUyklc96GxJti g9xwabIxCNjpSBKx8eftI3wtfB+svnlInI59jX+cN+1fqS6t+0 D8UNQkLFn1aUdeODiuW79vEmhL3mfPsMwKktncvc9KuK+bcMrq AG45qs4bVGTR9Hw1G+Jin/AFqcN4yDppbtuIZj6ZxXP+EoUAO05DjPTrXzHBrTVRrufdeJ8E pUYrsdRqSFMNw2RyR1rmVUl/nyAOo/GvtEla5+Wx+Evi3EkSsrMFUcVYaFhA/zZOeMinJ6A77GcheCb7g+c5565robO7dVwRwARgEUOCeolGz0G TXzKFy55OQopPtYYhmIDU1cObUpyTvGUMIBqMXErpJC5G4encV MpWsVexct7NJpSzBPl7A1C8U6yuMrg9fp2q79AlrojLktC4ILB VQE/N1rM8kjLMNhAxkHinPyMpLW5c092wPOj+VT2Oa3JYIFsGmUYI5 BxWTepUYvmbZxuoypG6qGJYfdNYa3riYL5jJuYAkjGa0uKSd9T vtP1WXCqXyF9ea2l1Azg7s5boOuDWMUk2KlLdsgE7tFJG5LAHB OaznYh18gb1BBJINFza+lzfjQSh8xozoecGr8zsLTaQSF6gmsm E027MY5iSNdpKM3BqpNkJHuBcE9f/rU3G6sVCVtUU79gFRknXMZAx2qGTVZhdI84XaeF5q4NBs9St9s S4u55ljTb0xmqduZFkmBkJAYj6VHqJu2hqlQ1sC6Dk49qupaMy QyFlbGCO9Zxl1aFTcnGxBcyNHcKkjKVIz160ou/KuBgqWxgc0JpaFSXRlxwskAZvlU+9UWLLIHBJwMgetOi9NQbLl rOFaQgjIHGSKsS3C+W+FOWGapRTVhRetie1vDKjBnbC+vSse9n UMrqMYyOlUnoDlZ2MaN0kUFXOQeAeppLgMhXDsQOTmtJMOZlIA +ZtbPzcge1aKx4t1YY2MvJz19KFsSkUI2iWUKQW47CrwiUr5gY ZORtz61N/dCyepGJGAkURgBecjrWjZYeGVlUEA5JxVN22B+RJEI5ELYBA5I qQBBG7OFCnOfb/IpX7Db6mRcwo8eECIDwcdfas62TY8hYgljgcdKtvoXK/UJ5im7jOwc9gDXIXmBMrOwAyMnGc+tZqCtcIR2sex+BzEZ7Uo4 zwBzmud+IuP7dlJCuCB14r8ryuSWefefuGeK/DvM+y/Q45WKqBht+PxNfqL/AME4bSx1HxsjXsStIHG0nqOa/Vqtran4FiLqLSP7rP2WNMisfBViY3dl8sFQTX1O7nJHGD0q6aV jGjZJlZ24xjk1Bv54G7NJS1OiLK0jggjAGKzZ5sDII5rW2mopN GHdzKFOFziuRv7hQGJ5qmyYLXQ/QCM5wT1qQsORyTWD3LEJB+U5pRxx0BqWmLlJOMdaXJHGePrUrQ VrC78ZyRgd6jnk/cuRxkdaRPU+DP2s9TSy8B+IZZWZVS2kbP4Gv84H453p1H4p+PL 2OSQrd6pOQ3/Az0rGmr116EU2rs8pWQqcfOck4HSul0yH7RA+N20cnFYZ5Plw8 j6zhaP+2QOe8e6bs0Peo2g/MO3Y15/4T3RwjCEsOOtfK8B1HKFRN9T7nxWXLUo+h293IG2oPnLDnnNc9 LZSOQV3qhPXHP5V91zWPye+iYoQRq4cqQ57f/rq4qFVjZ8+W+cACruO9tDn76ZvPLZX5XwRV2GdG/5aYDDBIOef8mm3ZXJlK17kEsrNPIm8gEAAjirJSR4lIcMV4Ixk GhoblfQaSkXMkg+ZcqM8UpKbxiRmJ7+1NocNNzV0+5jRyHYMX4 HNaDBWJVVAA55rLZiirGXe2isN7SKo4GfUVhzW87FUIyU5NNz0 sU5Iv2VqWdgx3Enj5a3Ly026dKp2q3qf8+1S3roCeuh55fwxgB lbJTOST0rjJFaWRSHXygeoPat467mVWTT0OjsCI4xh/mUZ6/lWvHdyJJGiuCQMnHOP8msJLUk0IZZJ4WQkpJnOc/nWrb2smFKlU8wfMCetTLSOpSberOhMSrCohG1+DnrzxUNzBOsb AEuH5rG7lubwaKUhMUUC4TLZz6daW9ZtqSMQBJ1HatZvqTzJIx ruVPLjbHLflmseYxlg2SXznkVXNpqUySFZPtB2KUBzj1q7EqxT TFlZpFOSfX/OKxjJt2Ivqa0ExSDkkue4NbDIGWFwOdvOOlEvd1KUrbGFqQke8 DKXyAMA9aynEofKSbg3PWnSta5U53imabSbbRcNgjqTWd9swjl eCvOTz+lO9r8pi32Ldjcq4ZlbBPHJ6VpSrcyxKqYAI9eT9aUnt JmildaiWEjRvIrlflHJxSX5DJkoqqMnirj5jknYxFdF+TYyAYG ewpJSquC5bkZ69a0lfYhq6EhMRlTcpYbcDI7+lXGZNpbIAPPXj 2FZyemguYjtQlwxZuNx49qsPaPHj5wVJ6VotEO9yrLG5UqQODk kcVdslcWzqXKBeTu6molP3bsbVjPeZokZ2YqByO1SfbUJMLSth QN3fJxVyV0VvoVDIskQKHJyeCapwNIgk46n1xio5u4oy01K5lk YO4UNt4HvXF6hcFXVMsY92cnr9P1qne2hSjZp3PQ/B9/KtxbqrHDYI5q347YyalDIduSvB9xX5ThW1nSst2/1P2zFuM+HWr9F+hxUsrKrAKWbHIJwK/Rn/gnjrN5ZfEaBUXdE7DcMdOa/VqusdT8KrxXK4s/vI/ZK1lL7wRYLgkmJc+nSvrssrA8YNVRd4pnDQd4laU425wQKqFup z0ppanXF2Kk0oGckDFY11PwT3Fbcvcio9DnLu5+9gg5rj9Rnyv vQkXBcq0P0TRh04qTeeQOcVzO9we43zBjkcinpIGyOtDYN9iwC OueDS8UrAn1A+nUVWumxA/figi+h+a/7b98lv8L/ABbLI21Us5T6djX+c78QbpLrxZ4lmj/dpNfyfMf941zU3/tC9P1RFKN20zgTKInjJKEL8p7V33hRY7qKfcygk55OOPSsc/jfCyufX8JLlxtNeZs+PdMSTwTdtGm5YVOW9q+b9AkjWLbjaVbP 1NfC+HGIjJVknrdH6P4x0dMPPy/yOwWQGUkgPuXGTxg1BFt8wJKoCMcn0r9NbPxaD0NGe3gYbVJB6 HHOarywOpSPB2wjpSkuhWvU5y7gcjySFY7sZIHT/OaxLnfEyIq7UJyfetERJa6odBPI0jLJubB5A611MFs1wiO5G1V zgdqV7XIgvebYy6tpl4RCVfrxVSGSRZCMOSAff8DSjK+xroy5b xKsjMTl8jGKvsdnlZbAb71TN62E3ZkMvzqwBPHIyMZ/CqcscocBCeDjOapxG0aNvuBbhWJ45rSuJXNjOx4QLxz/AJ4qJOyFFOK1PKNRack9QWJGCcGuJuJZRIpldVDnoPStEjKpG6 v1N7TJFZAwOFPUZ5rVSUxCSURhi/TA4FZSu3boZQ+J3Oi0+bhWdPujjIGa0bnXbTT1XzZArkdcZNZ1 Y3R0qKYyLxPDcMqJOCruBw2MD2robi5LIrQGQq4AyTxUR8wi7a GdfXCrs5VwuCBjjNS+fviTLRsrDP6VpFcydy4aq7MbVEjdFZSF KCs6GJpJAxyu3GfWhbai1tqbEMCLcIFVlPAzjINL50XnuG5+bs OlJQVx2SVzSM0KW65XfxnParcNwSF2SBlbjH86zmt7jV3oULpP MunkwvA42isOU4fzJGK7T0HStqb0G1bYabn/AEZirZQ9e1ZayB8h1aRWbJyf5UotK4ThpdGpaKjIRuU89c101o W8kBnWQZ5IrKb6WCMdLDVV1eQhgYzyc+lZ13dAQ7QeX56dqtNt ai0SuYkc37xXcoSxy2efp0rRVGMuzGQRkY9a2TQLuR/dkG1ApTpU0rxPGQ6H5zyVPGazSvsLlW5WhUJE58xiF545NWYpm Kb9zZbqP8ap3RNtdCdHjUZkJwec44qxHPEUkZFQMOcKaJReyL6 mTOBKrq4RVTnIPJ/wqnNJApdGG04yMnr/AJxUp66A97kDuDAoQncvTn86it2ZkYSnCgnGOf1q2k9wsnuLEi lzkDJHT/8AVWNfWUc7sRHn6D/PrUTmolU6b2R3fgfw1qV1e2Vva2spYtgBV3Vp/FHTJdIvoLK5jdJlXB+XoPpX5GswhPO4wi+5+7zwFSPDlRy6Jfo eTzgOARyMgn2r9BP2AobkfEWBoZnhCMM46fSv1+o7RPwKvHS5/d3+xw0y+DbQPjasY5r7b8z5evymqpao4qFnrYhdwAckVnySbc1 ukaSbvqZU1wT1OD3rEnuCxIBz9aly0JbuzFuHB3MPSuT1FvmyD u3HpRBmstGj9EVcHtinhzkHI5rKa1IlLUmjO7qOhqPf5ZwR901 Mh7lpHB7g4NWC3HBBzTUtCrjdx59qrXhLW7/SpM7H5cf8FAHdfgx46lVSXjsZf5Gv86TxhcsNc1fcpBe4c4Y99 1cdNf7UvR/mjKlC8nJHBtPjKuA205HH867vwVqCreCPJRpcZ5yM1tm1O+Hkf U8N1/Z42nN9z3G8tG1bwxrNjtzK8ZIA57V8dabp09pe3du8chZHYYPY 1+W+Gs4QxFamtz9h8WqLngcPV7XR1ENm67i7Ox64JpY4JC/muxIPAX296/XU9T8HirbG1FH+6bGSemMVk3JeK4d5AHHYelSrJ3BKzKoaJpU8 wDD88VRv9Njm4RwqoN3pzQpWKKtnod2jBvKNxuPOK662tHiUo4 kDOMEHvTk7olx0Ekt0lil674x27msPyDHd4cCRQOwpRdnYFF9B tuu64UhmWIH7tWLhXaUjedgGQMYpt2AhQgg9uMDFKWy42Z49qT bYlc1bSLhnARNnUGpruPdZyAkGInqRxUt2WoJ23PNNSNunmKjb nPyjJzXmtwdknmykYGTtzkVrzdSJ23Ze0m/kMm9kIjBwo9q6+2ubJt5nQh5OcdqynK60OX4mXoPMMRZScjrgc j2rzTxleTQqu5JXKDPBxmhW2R1x0RyHg/UNQlv1M5lWN2yFIzx719XW9wJ9PtVUJGUXJYDHb3rJqzuzOb96 5n6oERlRW4K5qlb3I8lgoVlX3/WqjK+pqrPUdOI54/MBMZXjI4NOt4ipeQrGU4+U9RVKXYNGtCy9yplAK7QxB59O9Zb3 GLzaCFA6560oJrcIO8Vc1ReW8tttZiM8YqvK7K8SxMAR1APFZz 1iy1PRlzz2SQpjJYZJrEvS7OzBgSAeozzRRbuF9DKWVkiEciqo 6EKM1A85jcAFgW5PPFXa8iZJ31NGxd/JLAEEnGMV1EEoijiyGQt14wahp3ugTd7mgpBUkIMZz05rnNWba MpnB5UDv/nP6VpGT6lrV3RgRq7FX2bTnqeMVq2q3KSfe3DPQjJ9qicnoiUt bG7a6NdXMctwElG0Z6Y4qjNBcCLEi7CST079qTdrLoCgtEiCGG actGsZJ6A4qzPaXEERYwZxVVX0KdNyVkc7f391aAyG2Yf7IFO0 ee91EbzDKgJPBFQpS3YnFx1Nm9069gieX5o2zj14rnZ9yOSyuX UYz2reMtCnEQLIYz8piOPTNT6bJJ5cm/P3c47VnKrGwRpSstCdQ4aUiNsrxkeleq/B74R6v8S/FNppcELJGz8s3AryM5zOGGw8qr6H0GQ5RLFYmFK3U/Yb4W/sff8ACPyR350uW+uIY/kwoOT/AJFfkn+1UiW3xU1nSCY4p7WYrIqj7rZ6V/OHBmYTxfEcZtdX+p/UnGWCpYThut35V+aPnGaIcu2cA8//AFq/Qb9gG21NviDHNYRrLGjgFTX9T1ZaaH8aTnY/uw/Y5nmPgq0E1s8UgjGc/SvtUnJ3YzmtKNlHQ5KTtcqytgnPU1QnbC54Gea6o7FSRiznhiB kCsSV1GMggCsmiab1uYV7IVyVY4HbNcvf3IYkBunHFaqK3Kt7x +iwk7YHFPVu2RuHWspLUrroX4OQByKiuAd2B0Ydazn2ByH25JR c/SreeBgg4pJqwXYZxjGeagmIaNgTwam435n52/traQmq/CnxpaYBM9lIo+uDX+cB8VtPk0rx14p0uWMA2N9KjcccMa5KK/2v5fqYUnaTZ5swEmGC4PQ4TnHrWtpUi6dfwOHBGRnA4r1MRBTi 0d+FqtTjLtqfbfgfRDrlhBcwATLMmH7/AJ/nXjXxD+DOs6Frz6hpunyyW1y28hUwAa/nDKs3hl+eezqO19D+pc/y3+08hUoK7tc86/4RrXUunWfSbsDgkhDjpzWeNHubeR1ljmRF5GV5Br99pZnQnZxk tT+a62W16TtODQ+FIkgB2SLg4OBiuY1FpmL/ACjYjd1rpjUizklTavoYSTZfPmRnb2BzV52aQAMyYJIBz/SrqIlGtZpdIu2JioPTvWtb30n70S7VKE4B6/nWUU7EpmNdXf70eWxHOCM4rFkdJLlcMWDfKa2iHMyxaK4mJLNg Z+91qzMzAMqhS+3nA6Gi6BPuUh0kQuAQn3fxzmgxSxvGASQhz9 fxp37g7s0rV2IkB3RgcnNWLlhLaSIXzjkZ5FJpMpPc8+1O2Hls 4DF1FeSajJJFKwdX2qMdapETj9llvQ4vOKEFgoxjHeu6jtZIQr i13kcFh61nNpbHNzxvZHT21s+FjxuMnUGqmr+HYLxd0qrIGOCP 89ayutzeK0Mu18KWOn4ube2ZGbAxjNdYX8uCHlIj068D3ptdhS g/slDUpm3MxIZdmBgVjwuyrhcAyHk5wSOtEb9C7bl+ItJEFk4Ixg E1aDsjLsYsGHY96rRbEqKUbIfckoodgVx055xXNs/+mAxMGMh6kUlG9/MpaO5f89WVBtBVfaqCyymZ3WRwwbg5qY36jbRf3TgiQSiXbzg0 0tHK0aMzIemD/Kok+kSU+hUuIZY5A2C+GqCQlWiyB83IwKttXsFtbGpYoVjXa/Ab/wDX/Ouhd8LArRuSRwQM0+ZXshqWqInmeOQgPsRBzmsyZmmlt1jjZ+c g4zVc6uir6Hp/hj4Za94qGzTdPuGjXqdnAr2DwZ8GYptTWyvoGWSNtjkjoRXNiM RGMeZl0KTnofWVv+yq13o8l3YXUSI68Jgc14Jrv7OGuWYdJ7bI 3fMwHAFfJ4viWFJczPeyzJKmImoJWKWnfs/3artgSMvIOSxq5c/AHWI7f5LZZ2bA4rxVxfzTdz7GtwdyR0WqE074DKbuO21zTQpl4 B2V9LeEv2L/AA7qWmfaoMwyMCQFxX0mDz+nWho9Tyq3CVWFRaaM8r+I37K2p+ HrSU2sD3CluuO1eDJ8AdduQzR6VcEqeSUzXxeYcdQoz9k5bH3G A8PpVYe0cQv/AIBa3a2pRdIuCrY+bZ3rm0+CmtIu3+z5Fwdua4f+IjUf5j1Knh nL2SlGOhftPg/fROvnWQVc96+i/hzaxfD947pJLaylUhi+7BHvXxfEvGbxVP2UWfd8I8BQws1VnHU +hfFH/BQsfCrwXqmm6Fdxaj4huomjSRjnYSMZ+tfhj4i8Xar458V6r4k 1aWS7vdRmaZ5GPUnkmva8Hchqe2njK2ttvnueR448Q0aWDjgaT 96e/wAtUQPIPJQeaoZeM9ea/Xz/AIJteE5bnWkvli3F5ANwHB9K/f6sG2r7H8k146an9wH7NWknTPAVhuTy2dFzx7V9FmTC8Z5712U V7upzUFoVnbnJwfc1mXEhIPzKMVshzbvYwp5iDjdj61iXMo2nm pHT0OTv7ggMeRiuMvrwjcQQDWqXQuMtbn6aFjggc1JATyMDJrF 73FfU1Y22rnOCRT5BuXI4PXNZO1xpojhJG5SMYORU4YjPUetJM pNvUQyZxzz2qBmJVgT1pXJfmfIn7RGipqvhbXbSRcxzW7j65Br/ADk/2ufC6+Hvjx8RdL2CJYdRkYZHqa4VJxxUfRmdL4mv63PmBVYnKA 5HYnpUcpKDOzLE9PWvcmjojL3tD6S+BPxmi8Eaza2GtoJNNZwr d8Cv3w+DHgr4Q/HjRbKbT7rSLu5kUEpuG4HHSv5c8a8ir0KyzDDLc/rbwRzulisJLAVN4/8ABPe7/wDYh0qzs5Wg+H51QyA4eFM/yr5Z8afsV6P9pl+1eBdV08L1zAa/CMu8RMVSqLnnY/V8TwTgq8bQszN8F/8ABOfwb4rnylvPZLnJV4hmtH4q/wDBNf4R6D4UvJCyQ6pBGWBWPB/Q1+wcMceYmrF16lTTY/NuIPDbD026MafvPU/Ij4lfsraX4duIYtJumeWdz8uMHFeXt8CNRSJ1JaPaT1H9K/WcDx1FYVOq/eZ+PZnwA3iXGnscXqXgfUtGRopkDiPjcB3rk59OuBGivCxWI/Mdtfe5TmUcRT54n53m2UTwlT2czAuLeISJIFcx5wylc1zc1uRO xWUMM8ECvYi+55Mbm/YLM8f7zAx1Oaq3cxjmkC7SW9RUxlroKNraEVgn2ncyDcyc8Cui TRruaLzIo5cDrgdqqWmrGkMl027tPLLwNicZy1VrlAbYhSQQPu +9OLuhNM5m6tDIuBKSG646iuQu9Dhnd1VAxbncBn9cVoiJvUZp 2gvp9wHKFhjjPQeld1aHf+7kVFU44A61zN394iFNJkbojXZWGd YVbqM1ZknBZAdr7D60oxdkjRT01KV9chVWMnap5HvVMkS2+cO0 idKE02kP2lnYfLbzT/Z1kB2jrj0pItNMbBY0LyH5gD0x/wDqqop2sgVxqwlDJG+EkA6H1qCOOWAgAeYq9WNW9BJK5T1C4nO SDuAP3Qe1c/BeNJLNLIh2Bhzx7VMVsU9VZGtA4dGJw6kZORVaMjzX27QW4AqY O912M4O6aRrW6OylmIk9QOQBTjbsrxyO6gOQSDU31HGeuhcnQP 5SKdzE84FZV1BGHTGGLL1zRF2Kk7u5pWSImT5Z3k9D6f5xXUFY zDGFSMspzihx96wtFZIwb5TDnj7/AEx1r7T/AGO/2d9K+NWqPJq99HHBZH5oy3Ld60jTUjLF1XGm2lqfvN4E/Ys/sXwXqVt4I8NWd60ic3EmPkHfnvX56eLPDMHgTxVqthcHS5ZNOn ZXdXBy2ea+J4vpYiFJThsfTcFqhWquFTd2MGb46aNpK+SmpQQG LKld38q878T/ALSvheOxK6jqlm5JJ+Vhk1/Pmc47GTfs4bs/qng3hvBRpOvUex8v+Jv2wvDenM66UrMEHJ6ivNJf23dSidHgfv 8AKGPFe5kfCGPqxbkzHirizKcPP2cdT1r4c/ta3Hia/jXUrSGbJwGzzX6ZfDz4lTR6A2opMIww3bMV9zlHCOIpTvUZ+aZ tx1goVEqC0Pl79oz9ribwnZLC/kRqzYAzya+GE/b/ANasrplS2tGgjPzZHWvn8w8Pq+Irua6H3GX+J2Bo0eWUTU1b/goNZ39mLcW8cMpOXO3r6CvPJv2zrq7BmglhSPsCOTzVVPCt1Pe vY46Pi5hqUrRV0eeal+2Hr08zLEQgIwdvpXGan+0P4k1pXWN7n c/T5jXflnhdaSdZ3POzjxnThKNJHKSXes+JZvPv55wHGdnUVsLAl nEkYIwepr9gyrLIYWCpU0fgOd5zVx1eVWqx1owmmhiUtmVgBzX 9IP8AwTR8CGGz0KQRyP8AaGRvzrurrVI+fxMtEmf2I/DC1TS/CGk22NreWK717jG7ngeprspvQxpaRKE85OeMg+9ZE90dpOf1ob sxqN2YktwGOSy5HWsS7uFClR8vpxTgipu2hyF/cBs7SK4nUHYkh2Ow963uXGx+oSygscE4zV+CUEc5rnCLV7mmjE DjJ+lTh+w7UrAtRGUnEkZIb0pBKRkOpB9e1ZSFfoNaQH7oyfpU ZV3HOFFIa7HjvxQ0f7Zpdyvlh1kQqa/ga/4K0fBu88B/tE61q6WXlaZr/wC+VtvBbvXnYvSrTn2f5qxnCXv27n5E3Vq8Dll3IpOTkdeapz+ ZsQ9B7nivfmtrG1PSTv0M2cMyDhiVO7A6113gz45fE/4RX0OqeDvEuq6bNbuCBHIcdeOK8TPMlpY6hKhWV0z6PhriHEZb io4nDys0fpl8Jv8Aguv+0h8Ora10/WbXSfEttagLuuEIY17fd/8ABwR4t1n/AJDHww0N/XY2P5iv5a4i+j7N13PCVPdfQ/qjJvG7J61pYyk1PunY7jwV/wAF9fD+j3VvcXvwshLLy4jI5/Sv0H+Gv/Bwr+w9rdvFbfFX4Ta1azONrulhHOh/8eFefkXhjmmWV/eiqlJ7r/I9zNOMuH81o2w+IdOp0vseOfHn/go5/wAE0fixa6rqPgvwp9g1WeEiLdZCJix6dOBXw1o3xn/Zx8S/6PcXFtZCQbdzEAZr28/yBypSnh6bg+x4eVYmFLE06Naqpp9TE8WfDj4O+KIxJ4Z8U2TSy HKr5gI/nXiWtfs76jHatdWJg1CDJwUOeK9Tw74jxNNeyxB894k8JUpTVa nsz568R/BfWo544U0+dS78/LxXpfw+/YP+I/je+tt8UWnadNhmld+SK/b8nzhYmfLT6H89ZrlLwseeY/4yfs16F8JfD99DLrC3+swybFRckmvhLU9HnjbzGLHax4A6V9JC 3M0j5qlWk1zSNzwzZrFOXuRF5YweTwK+ovAmn+HteT7BuhilI4 zwPzrDGxai2jthZu5J43+F2q2lm93YJHdQMdqlTnFfKus291YX M9lcK0UkJwQa48vxSl6mMouOqMfy0kUv3Byc9qy9piuOVQKeCa 9bmLb6k0ap5iA4HOPenXiNFK0iAqmO/rUyvfQi75rGeyiRi5jKjHJ6Zo8qUOvoh4xVylpcbV9TL1POFeI sxBxzVGC/eMEMUGcdTWFkJyVzchuhJGA8jEeo6GuktL4gL5Zjww28jmtE3Z 2GnpocpqMsr3ch6SkZGB2qnHdTxxsWB8uTggHp70NXVw530Mi6 MkqswDAEk1Xt49wYuOFGcEZpwd0ZtNont+GZCHUDhgDxQUJ8x1 +91P8AhWMn1RnfZo1bD7RGjkl0GCfSrpJeBWO5XGOD2onJI2lo 0WSgRAg9eSPrUN3aEPH5a5d+gxz0puT3Rt2J7JmSJ2lG5sYwRW 677IYm5X120+a+qM476GFqLOrESMQpBwR2rpPh58ZfGfwl1iHV vC2oy2hTllB4YZzzTjrHQqatofpVZf8ABaD4jaX8JNZ+H9lbHT 9b1GA2/wBrjbnBGM56ivyT8U/Hvxzqs99qupeKr+6ubty5XzT1J5/nXgZlQlXkoTWh7WV4tYVSlTWrPI734l+JtSLut5dOzZOXY4/GsaS58T6wp8+7mdR0BY1z4ThbDxlzNbHrT43xTg6cJWQxfDN7M sUk8j5Az8x61tW/g2FikeNz9RjqTX0VGiqcdEfH4nGzqtyk7n0R8M/Bt1YXlnLJamODcCWYYx/nFfc+sfF3QvCGhW2k2mpRtdFMEB844rZONjCnNySbPzl+M/itvH+tKhmWeCI8kHj8a8Nl8I2hCid9pIz1pRglLU6KlR2szAu/BhVjImxi53AdvzqtF4NkVgUlbb7Vqkr6mEps27Twlb7jvCoATn iup0/R7eBoVaNCvUArzSWtkWpppI7qC4tYIkjVQrsOOM1k314kzsgk3 44PGeaiLa1CC01PSPhJ4Vl8WeLtH0+3geUNKu7HJ+lf2Nf8E8P g1cafbaGZbPZHbqv8PBrKpdzOTFtq1j+hCyRbKzt4E+VYlC4qY 3WAQxY8V1wTW5lGL5dShJcvuB3EKOorOubxeRxhvaqavsarTc5 i91ERnB4z6Vg3N+ZAGBBx6GlTavYJx0ObubkqWLDknrXO3867T nLAmuixNO17o/T5JNp4O6tOBydpJIBrGa1Li7tpmukikAdTVkOOOcGpY9SVWBBO cmlL8Y71CVxX7kbMACOKiZjnIJpNWBsxtZ09NRspYGGSw4r+fT/gqr+xqPi34Tm1ux09m1PR8urKnzYHvXm5lScqdkYzbTTR/HB8UPhD4i8Cavd2WpWM8SwMVDEHmvCprPyndJQ2VHf+Verh63M lI6b63M6W3cIZViLKBg47VnTW8UyOjQ545Nbpu1zoTilocZeeG becOQjAgY5HWslPB7Orsu7LDriodNWJ5rbFEeD5YpjExLDk7gO f88VQk8MXixsCjjHAJ4rnlRTD28o/Duc7d2GsWZBikuI2U4OO3NVYvEPieybMeoXYVQP4jzXHiMrpVF aSPQhmlem04yeh0ukfFfxlo8oni1TULcRjjLkCvsH4Vftw+K/C5gh1i9kvLRTja5z+dfEZtwbBy58KrM/Qcm8QKtSP1XFu8T7U8Nftn+CfFSxJqljYpIrBt2QDX6VfAT9s7 9nq7NjpHi3VE0uFMRmZXC9fpXh5JHFYLGpSj7stD3M6wuExuCa hP3o6ntP7RXx+/wCCXvhjQZpLGaw8VeL5LJncxIZsSEdC3TNfzbeIvGXgnxPq+r6 hpJhstPlneSKLI+VSTgflX63RjBNqn0PweeArQi3WlvskcLe6r oUcMrQ3iIxyAMjn6Vxtp4s1N764h0S+nhfA2FW5JracFJWZ2UZ NI9J0z4lfEOx09dPM2pXcVvy7SAnA+tc/qFzd6xdG7u3Hnz/M2a5IUYwvJI0rVm02NjRZgUjG7AzxWRcQLJkkFXWuhfFoSo3sj MeWSGRDHk7+ldBG8F5a+YxKnGTj6/8A1qc3oPqYUtvzvRyoBA9qrTsSYow/T3odrJERVjnLnz2lWIg49PfpVWWBt0ZOWyAcLVKKFdmxZR5ZVR WYr3x0roRBhUKgxcelZTfLsO2uhl3MDRvuJLkr0A4pI4/MiZXwhUe/6VUp9xyMKazlKMeoBPU1ctLM7UAAIXgYqFKySRk4yVkizHApkY OmNueh7VnmzUD5lLMemKOZrY2cNNNzRtY90I3N8x6KeoqV90cS kqGC8Db0rGULNyZmovdjbmeSCOBVfaHNbLnzVgl3Auwobukkjb 2jSsxZbMJF5jBg+CSc5/CpIm3W8YY+WB26VUFpoRTilqjKvoPOkJaQBgCF9K5+a33kR4YE 8getaw7D1ejOC1nwxHK0sqZSR23HJ6/Sqlv4SiYhrkEt+NEorczqTb0L9t4at42DNH8qnJBHSugh0u3SN WjUBgDgk1UJp3Kir6jvsiiQRgFhH3Iqzbb7C8t7iJV3xnPzd6H G2iIjDSyPrPwH8aPAzfZ9M8e6CI7SIfNPCcH9K8k/aK+IPwx8RTwab8KtHn06DdulupSQT7KPxpTt0WpVCg4y390+a7 Ox8pVleXMj8kjp+FEp8t5UcM23im0rk1XeVmVEeJlkXptHBHU1 Gk8SKVJUbj16VT1egKzYguYwdoZirflmrXnMwEiSZC9qlrqVLu VXvcOOrB+pHWuo8MaFqniTUrbTtKs57qWdwFCrn8+KUpWiPdH7 0/sF/sMavPqWn+I9YsJkmlIb5l+7X9cX7O3wntvAmhWe6BYRGo25GCa 5sPFzlzs82rJymfS084GducHvVB7k7eoXFek1bU6o6IzJrvHRh gVhXl8CAAxz1yKJIzbZytxO7MSWYA9jWcJwoBLEfWpSV7hOVlc zbqZm3KW/MVy2oT/I/IAXIroMqer0P1Igl5wCQByM1s28mQKxkjWD11NSKQDpVpZFbg+ lSXysnVxjKgUpk3cj+dSooTXcaSCM96bnORSkiSLdxyeOtcZ4w 8HaV4u025sNRt4po512kMuc1nON1qN7H4F/tp/8E09N8SDUtc8OaTG5fLsixfyr+bv4y/sHeLvDOpXg0+wuVaInKlOBXBhW6c+RmFOdp3Z8T+I/gZ458PGWCfSLs7SRlYzXl134F8SWoKNpV4vG45SvahWu7s6qVR WMKTw5qeSpsLhCp6bOn0pP7HubYKHt5/X7vSiT0uio1Et2V5IHiKyLblWAxgio1TczfuCwHKgL1qHsNtNN nOT6P5xmeS3AdieMVy914Yi3OFhBYn7rdaqQ25Jo5658IwvFtw C4wCfWuSvfB4BYQffXggCs3HmV0ZufLaxzktlrWmTILWaaLAz8 rE8U+y8U+KtHuRJZ6hcRuvJBJwa5JYePMnY6qONqRXKnozZ1X4 oeItZsZbTUd0xcbS44Oa4B/E+q2+fIknyxyGLV0pWehNR3d0XLPxXqIXbcyTSZ5JzXVaH44ks Z43ZpFIbllPIrOUOhK0Prjwt8WIrrw5cadcSWztdKFLFMuBjtV afUkuJQ0P7uJAFXBxn/ADmsaPOm1IvSLLNlqPMyKyjb3xms6bUdzTIGU5Xg5rZfFaxXPY yp7lnWMoACoxkj9a1IJ447bBfyy6HhSPzpVJWVglJIzbmZWjCB 8se+aoPtd0Bk4xwc5q20ZzTZFLJBHICCdx459M8U13hMinIAIz 160aXKsmy/A6K5MeVG3AIJpbi6ZQuXGU7A1k4+8ZxhrdMcZlkEcp4LjGQarr Ijq5DhlQZJNOcG723NXFGT9tbaqMF4PGD1q1b30EaoBIVXsM1D jazHfoXRc2yspZzK3UDrTTcROxdht2joDQk+pNtbk1o0QMqEKQ OMCrEixCFWUKM8BQ1Lls7NlWS0M69kj8qFWyC3of610caKyxBA BtUZ45qnFpWQ59Lli4aDyim/LFep5rHgmjaNly6kHAJNJS5TNxSdgllCkMeEXPU8flWQ8iKpYB SQMj5elWr21LWhmSsJvlKHa/PAz9eaa6rInlhdoAxg1ok0ZtPm0KEolRTujcleTtFFsXZDlXBb g+lNK1xJ2bRLbzKGT91vbGM4z6flVmUyj5jE+5+QBkZqJK2pau ijdxXLg7YZUDdDXPy6Jc3LoVhkILcYXmlze6ZSmuhPHo2oBTFH bTeYvAIBqhNoerSb1+xXIaM55XkGqs9ylHTzIZfD+oLs32t2jv xkp/KqV3od9GoVLO6dThs7aqO44q9yza+EtanVWWwuGUHO3bmuo0vw B4j1CRYLfSruViQuBGf0qZT90dONnY+kPhn+xX8TfiBd2xXR7m ytpDwzociv3V/ZC/4JqWPhyTTbzWNINzqQKneUJ5/ya45RlUab2OWtWS0R/Rp8EfgBo3gXTbNpbOKIRKNqBa+pvOS3jWOMKI0GAB2FenRppIy w8VuUJ7vgkYOPQ1hXF4MsCxwOhrY1k7GW+oKQykkY4FY1xcZJ3 dCaVtbsza6sy5X5yeRjvWbNKNuPl9c0IibbSsYF1dOuQSGBrnL +5PlsATjPHNWh01fdn6oWkxbOOMelb0EgP8WMVjK1xt2lY0opv QgirayD8DUG6ZaRxjg8HtUyuhJUnBoBocSi8lgw61C7f3RUuJm yPOOoNIScDbyDUIcddjPvtPstRheC6hSSN+CCM18z/Eb9lj4ceOorhrjSbeO5mz84XBrGdNSMpwvsfC3jr/gmt4c1B3exs7K5DZOHjr5g8Qf8EvrWR5MeFLSVM4BCCrhzJ6nD OnLXoeR6r/wSx08SSlvBcRL9wgrxbxD/AMEsIEkuI08ITJ5oyCsdDmrJWOeLkt2eIX//AASrslldP7Cu1bPTyzXE6p/wS8XTiZYtFvSBx/q6anodtPEzvqeaXv8AwS/vIJo52tbn7NuB2GM1lar/AMEtpriXzYY7mHIzjaar2misbQxcla5wmpf8EwdQtIgUjmBJwT srgrr/AIJka1Hq0Max3H2VvvkITVqdloZ/XH1RBcf8ErdflcNhyjf7J6VxWtf8ErtZQTbYpzIeVwmTSa1FLG tO1jxzUf8AgmD47cXX2S1f5flQlTWA/wDwS1+In2WNzBI0+3kYPWrUeqNPrllqWY/+CWvju3iH2iEkuueAetclff8ABNvx9YCeUW0gEbccVE4NbijjL 6yOKvv2R/Gfhecx/Z5/lGSdua4rVPCviDQy1vfQvCOi7lrOTtqd9OqpK6MAw6lAjyRrgH 7xAFJBZandS52tCpHBJ4Jpqa3Z0LVXYl1pV/GsihZG4wwz2rPa4mgDLLG5YDB3f59qhu+wnqroyW1Z0lVVVzux waX+1pTNCjEJ5vHQ0Kfuid7GVfa9Ek5jklUsvXIqlJraNJCqMC 7EZJPahxfUT3uzfsdft1mDPMFQc9elbMWp2F2GzdIkkgyCRUuW txQWlxl1K1tFJdCZJYU42jr61k2upG6LmNJE2HnC5zURndcxUn fWIFZ3x8hEbHA4Oapvb3aMFxI7U4z0SZNNMuWWm6pdSOYo5Qn8 OB1ro4NB1NlBW3lcoegzkVDnZalqOuxv2XhbXJVYiwuWx8xwD/KuktvAPiO8t0EdlcKjEcbeKmVRdx8z3NaX4Ua+0UO+zuC+cnC4 rQPwq8RxQwhYbhVAwF21UMTFq5UVdDLv4ZeI2SOKOwnDjqdv5V a0/wCDPiqUMfsczknqefypPEwtuS3rY6iH9n/xbcQRlrKRg/UgdPwqcfsx+K7hQsNlcSsxztVMis442mna40dPa/skeL5gTJY3K54Tchr1rwp+wb4q1xlC2FwSRziPmiOPTehlKrZM +jvDX/BMrxDPbOJtAvLlm5GYs4rY/wCHYOsrI0f/AAjV8oYdouldkZ9Thq4ndGnY/wDBLbVztMfh+8kDcf6s8V05/wCCXGvSNAD4ZuXI6DysVblpZCWIaW5qSf8ABK7xFM8PneGbpIw ASPLzW7a/8Ep9aknVv+Ebk98p/Opvvch1ndyvodFbf8Eo9eSeRl8KN5h/j29KfF/wSc8RpJM8fhve5IJ/d8Um5FyxOt0Xbj/glDrsqRrL4V81F7eV3rXh/wCCSWo3SIs3hhIwf9gVCnO1rFxxGiSep6No3/BIK7jWANoNqsKADJQD8a+iPh9/wSr0rSZoWu9EsYzFg8pnmklN9BSq6aH398Pf2J/CHhWKBrizt18sDhUFfUOifD/w74Yjjj07T4I2Xo20ZrohRtqzKnT5mdE4K/KrBV+tZc8jDnJz0zXUrs62rGBczy8ASFcelZ0kjFjk8VSE02il KRjIOD0qjI/yvnHp602iOmpn3DEbgDxisS6lAOWzyeBUJK5m0c1dz5Od3A7Vy 2ozPh+h9DWtPVlQi7n6uWtyVwBtFdBbzghSCefasZxRWjdzWil GAMjPtV9ZPlHOKhpGi3J45VxjPtRNK6hSpHzGkXyISSS4+TYFI qwrkgbhz6UiWrsXPGByR70ZOMA9eMVMmK3RDT069aacAE4zSS0 1EkQMVxnG6mFIiBujU59q0LdO61KslpasRmGMke1Z0+k6dMfnt IGH+6KaMZUEYc3g/wAOzOzyaZbbm9UrOm8A+FpVYNpdowPUbBUOK6IxWHT0OXu/hL4TZ3kGkWjhjnBQVXf4Q+CNQgAk0e0QgbTiMVDtsNUehSu/gd8PZohFJoViIyOcoK5e8/Z/+HjqNuhWTKpyP3Yq+VCeGuXl/Z/+HjbG/sa1GF/uVFffs5/DO7RA+h2YdOh2CteSL0MPqr3OFu/2UPhuZi0Oj2qhuvyCs2L9kv4bxLIH0u3cscjK9KSgkrC+rOw0/so/DBl/f6NbuR0+XGK868Tfsb/DS6WZ49Mh8lwcqBTcIsVTDS3R8CfHn9g7RodPutX8K263TQgs0 JQE4r8UfjR+zbo5bULa50o217ECChTB78V5eKTjc9LB07I/Lvxr4Ej+H2tTJqOlvd6OrEyAfeX3r0Twx4M+GvjfSrbUfCt7HP Ko+eHoynvxXnxxU7pns/Vm48yLOpfC3Q1QxwREPjacr2ryzxD8IrVFLxyKUJ5GOelbe292 7ZhCg0jwHVvBI06dpC0ZVSSoFcrZeHrK+1tQ9wfMtMu5HIG0ZI rowtTmdifZu1z5W8UeLl0/Vb+JIjMYZSi59veuVfx7OEZ3tNjq3zgj+VdkYe7e5jNK3KV0+I 1xE3lrAxXPBBPNblh8TVCoHtycn/8AVSnQs7Mz5VdO5654O8cadrFxDb3NuXTIwpboK+w/DHg7QNWsftMdtsXcNvv+Fcdek4xsbQpqLSO2t/hvozygbQAh5OK6O1+FPh68dS8ZUk8EAGuKda0eZG8afZHb6J8F tEWVH3bYT0weor3vw78GPCkgERtFVn/iA6Vw4jGO1ol/V5yeh9DeGP2dvCJSJzbLg8nKivYtM/Zu8ELDEDaxKUHXFcNXFy5bXJWHaeh39l+z14DW28l7CGRzyMrW xb/s3eAJeHsIgfXArkVeS1RvDCuMTbX9mP4fzBI0sowqnLDFdNYfs u/Du2WLZZJuGOq1u5Jzu9iJ4SUmux6TpP7Pfw+jt1hk0yF8nkla7 O0+AXw/t1R7fSbbcvU4qnUtL3SZYZ2R6BY/BrwGoAfSbVpABj5BxXsHgXwT4L0W8hEek2ip0+5XVQrcs7smeC tF2PtzwtpPho2kTW2m2aqwwcJ0rtV8PeHpRg6ZZ5PfYM19hTld XPIqYVLco/8ACN6DA26HTrVR2+QVIulaZvBFlahiePlFap3COGRoLpum4Je2 t2I77elNWy08OxSCFc/7NWmH1dI0o7O0IwIYgpz2qQWFmgDLDCAf9mjpqQ6VtRxs7JVVz bxFhwDioSLQuEa2UMOc44pao0hRV72L6+VtyBFj2FNaVFwCi88 dKEilHQryzDHG0elZNzLuI2qMU2tRwp6mZJzyRWRcoT904VvSn HcqpB6HP3G0HaOKy3IBIGMdzV31CEbKxRkbJJ+UkHIzVOSdGXa 8LDnk0zNxvoYlzIELkYYKM1y15dhlYliABnrQkTCO6OXuroYc5 GPXNcrqN6GRlB5cY600tdC1Cz0P/9k=

[Morgan]

My Zahori found a can of old paint to 50cm deep water 3 meters distance

this is a good start.

[folharin]

[quote=folharin;135027]16730

[folharin]

16731[quote=folharin;135027]16730

[folharin]

[quote=folharin;135031]16731
16732

[folharin]

16733

[Morgan]

16733

hello

very nice,but i see 3 pcb ad 3 batteries...

[Qiaozhi]

16733
Don't you have any battery clips? :eek:

[Morgan]

Don't you have any battery clips? :eek:

i supose this are rechargable batteries...

[Morgan]

16733

hi there!!!

i think we dont need the big coil.
do your tests without the big coil.

regards

[folharin]

I use 18 volts to the main pcb and 9-volt beeps generator , vu led.large coil is connected to gnd

[Morgan]

I use 18 volts to the main pcb and 9-volt beeps generator , vu led.large coil is connected to gnd

yes,but you must disconnect the gnd big coil and i think makes device more sensitive.

[aft_72005]

Hello

I know your skill in electronics. Maybe you can help,today i try the ZB in the fields and at some moment i catch Radio Frequency signal RF(music). This happens becouse i remove the wire who connect to BIG LOOP L1,it becomes very sensitive but unfortunatly RF enter the Zahori. I ask you if you have solution,maybe some low resistence in between L1 ?


Regards

Hi Morgan
As you said, seem there are VLF or MW transmitter in your area.http://www.itc3.com/images/smilies/K%20(5).gifhttp://www.itc3.com/images/smilies/yahoo/39d.gif
Are you know on what frequency broadcasting??
Best regards.

[Morgan]

Hi Morgan
As you said, seem there are VLF or MW transmitter in your area.http://www.itc3.com/images/smilies/K%20(5).gifhttp://www.itc3.com/images/smilies/yahoo/39d.gif
Are you know on what frequency broadcasting??
Best regards.

Well,with Zahori sometimes i listen the radio,i will try to know what is the frequency in transmiter.

[J_Player]

Well,with Zahori sometimes i listen the radio,i will try to know what is the frequency in transmiter.Hi Morgan,
Do you hear music from the station you find on your Zahori?


Best wishes,
J_P

[Morgan]

Hi Morgan,
Do you hear music from the station you find on your Zahori?


Best wishes,
J_P

in some places it catch music or voices,yes,radio.

[WM6]

in some places it catch music or voices,yes,radio.

"Radio Renascença's (Rádio Sim) most powerful mediumwave transmitter is situated near Muge (http://en.wikipedia.org/w/index.php?title=Muge&action=edit&redlink=1) at 39.119939N 8.711472W (http://en.wikipedia.org/w/index.php?title=39.119939N_8.711472W&action=edit&redlink=1), which works on 594 kHz with a power of 100 kW (although currently using 60 to 80 kW). It uses as antenna a 259 meters tall guyed mast radiator, which is the tallest structure of Portugal."


It can be received by simple diode detector.

[Dedevil]

Hello Esteban
I'm just wondering and it may be a bit off topic for this thread, but most of your pistol detectors are using LASERS in the IR spectrum. Which is good for gold as it reflects IR very well. I guess your doing this because of ease of sourcing components. But have you ever tried any other frequncies for the Tx. I only ask because where i live the paging system frequency is close to Infrared but unlike Inrared frequencies which bounce of the ground surface, the paging system frequencies are known to penetrate hills. The only problem i can see would be making instead of a IR LASER to change the frequency and make a MASER. What's your thoughts?
regards
DeDEVIL

[Max]

Hello Esteban
I'm just wondering and it may be a bit off topic for this thread, but most of your pistol detectors are using LASERS in the IR spectrum. Which is good for gold as it reflects IR very well. I guess your doing this because of ease of sourcing components. But have you ever tried any other frequncies for the Tx. I only ask because where i live the paging system frequency is close to Infrared but unlike Inrared frequencies which bounce of the ground surface, the paging system frequencies are known to penetrate hills. The only problem i can see would be making instead of a IR LASER to change the frequency and make a MASER. What's your thoughts?
regards
DeDEVIL

what's that stuff you say ???

first of all Esteban is not here to answer, it's some time that he do not post here...

then what's that exchange you made ??? IR and microwaves are not same thing... then , how to say that... I think either ways don't work :lol:

[Dedevil]

what's that stuff you say ???

first of all Esteban is not here to answer, it's some time that he do not post here...

then what's that exchange you made ??? IR and microwaves are not same thing... then , how to say that... I think either ways don't work :lol:

First of all i haven't heard where esteban is.
MAX THE GURU?:rotfl HERE JUST FOR YOU LIKE IN CHILDS LITTLE SCHOOL EVEN IN BIG WORDS SO YOU CAN READ FROM BACK OF CLASSROOM
IR AND microwaves ARE THE SAME THING THEY ARE BOTH ELECTROMAGENTIC WAVES
JUST DIFFERNT FREQUENCIES
F=1/t
IR laser is called a laser because it stands for LIGHT AMPLIFICATION THROUGHT STIMULATED EMIOSSION RADIATION

a MASER IS MICROWAVE AMPLIFICATION THROUGH STIMULATED EMISSION RADIATION

try looking up on wikipedia lasers, masers and electromagnetic spectrum. goto www.wikipedia (http://www.wikipedia).........

and dont send :lol: you make yourself stupid and everyone is actually laughing at YOU!:rotfl:rotfl

Dedevil

[Qiaozhi]

IR laser is called a laser because it stands for LIGHT AMPLIFICATION THROUGHT STIMULATED EMIOSSION RADIATION

a MASER IS MICROWAVE AMPLIFICATION THROUGH STIMULATED EMISSION RADIATION

try looking up on wikipedia lasers, masers and electromagnetic spectrum. goto www.wikipedia (http://www.wikipedia).........

and dont send :lol: you make yourself stupid and everyone is actually laughing at YOU!:rotfl:rotfl

Dedevil



I see you still haven't found the dictionary then Ernie. :shrug:

LASER stands for Light Amplification by Stimulated Emission of Radiation, as anyone who has studied physics should know.
And MASER stands for Microwave Amplification by Stimulated Emission of Radiation.

Notice how I have the ability to put more than two words together that actually make sense, and do not veer off into complete gibberish. Your reliance on wikipedia is appalling.

[Dedevil]

I see you still haven't found the dictionary then Ernie. :shrug:

LASER stands for Light Amplification by Stimulated Emission of Radiation, as anyone who has studied physics should know.
And MASER stands for Microwave Amplification by Stimulated Emission of Radiation.

Notice how I have the ability to put more than two words together that actually make sense, and do not veer off into complete gibberish. Your reliance on wikipedia is appalling.

gOOD lrl Q - E

Whether BY or THROUGH depends WHO you studied electronics under. Some teachers are BY and prefer there students to be BY whereas some teachers are THROUGH and prefer that thier students to be THROUGH. The test is; put them all in a round room and tell them to **** in the corner. The students who PASS go THROUGH and the rest just become BI STANDERS. So i prefer Amplification THROUGH stimulated Emission.

Regards
Dedevil

[Qiaozhi]

gOOD lrl Q - E

Whether BY or THROUGH depends WHO you studied electronics under. Some teachers are BY and prefer there students to be BY whereas some teachers are THROUGH and prefer that thier students to be THROUGH. The test is; put them all in a round room and tell them to **** in the corner. The students who PASS go THROUGH and the rest just become BI STANDERS. So i prefer Amplification THROUGH stimulated Emission.

Regards
Dedevil
So you've changed your mind ... NOT LIGHT AMPLIFICATION THROUGHT STIMULATED EMIOSSION ... as you said earlier. ;)

[Max]

First of all i haven't heard where esteban is.
MAX THE GURU?:rotfl HERE JUST FOR YOU LIKE IN CHILDS LITTLE SCHOOL EVEN IN BIG WORDS SO YOU CAN READ FROM BACK OF CLASSROOM
IR AND microwaves ARE THE SAME THING THEY ARE BOTH ELECTROMAGENTIC WAVES
JUST DIFFERNT FREQUENCIES
F=1/t
IR laser is called a laser because it stands for LIGHT AMPLIFICATION THROUGHT STIMULATED EMIOSSION RADIATION

a MASER IS MICROWAVE AMPLIFICATION THROUGH STIMULATED EMISSION RADIATION

try looking up on wikipedia lasers, masers and electromagnetic spectrum. goto www.wikipedia (http://www.wikipedia).........

and dont send :lol: you make yourself stupid and everyone is actually laughing at YOU!:rotfl:rotfl

Dedevil




you the GURU ?:lol:

microwaves and IR are NOT the same thing and you stated that : different frequency

then make a maser for what ? are you planning to make a radar ? :razz:

don't you know that microwaves have the tendency to bounce over solid obstacles (like soil...) ?

what you wanna measure , you GURU, the height of soil ? :lol:

you're a non-sense science fiction character and a clown... but I will not put any images to mantain an hi forum decorum :D

[Dedevil]

you the GURU ?:lol:

microwaves and IR are NOT the same thing and you stated that : different frequency

then make a maser for what ? are you planning to make a radar ? :razz:

don't you know that microwaves have the tendency to bounce over solid obstacles (like soil...) ?

what you wanna measure , you GURU, the height of soil ? :lol:

you're a non-sense science fiction character and a clown... but I will not put any images to mantain an hi forum decorum :D

I wrote; they are the same ( electromagnetic waves ) Don't write crap on this forum without a quote saying that i said this as it makes you look foolish. This is your misinterptritation due to your TOTAL LACK of BASIC ELECTRONICS and Chemistry. Do us all a favor and sit in the corner with the dunce cap on. And Yes it is a type of RADAR. But FAR BEYOND YOUR KNOWLEDGE OF SCIENCE. It's called the transreluctance of soils. With it i can look into a hill and SEE the heights and composition of a hill and therefor know where to mine. HOWS YOUR BIG CLOWN NOSE GOING NOW? MAX the:rotfl guru?:rotfl
Dedevil

[Max]

I wrote; they are the same ( electromagnetic waves ) Don't write crap on this forum without a quote saying that i said this as it makes you look foolish. This is your misinterptritation due to your TOTAL LACK of BASIC ELECTRONICS and Chemistry. Do us all a favor and sit in the corner with the dunce cap on. And Yes it is a type of RADAR. But FAR BEYOND YOUR KNOWLEDGE OF SCIENCE. It's called the transreluctance of soils. With it i can look into a hill and SEE the heights and composition of a hill and therefor know where to mine. HOWS YOUR BIG CLOWN NOSE GOING NOW? MAX the:rotfl guru?:rotfl
Dedevil

yo funny clown deserve a picture and I will show you're real appearance at the end of this message, but, before that fun I must tell you that if you're so sure this "transreluctance of soils" is so effective locating buried stuff like gold coins or rings (mines are big stuff... and this is remote sensing section for treasure hunting, not for mining...) and you can make such spectacular radar thing with a built in maser ( :lol: ) why don't you partecipate to the challenge and got that gold ? :razz:

yo funny idiot are so proud of what ? of wasting your time posting BS here ? :lol:

c'mon and do it if you've guts and radar with maser in your hand, prove me and us we are the *****holes and you are the guru...

till that you'll remain a clown!;)

regards
Max

[MIJ]

yes,but you must disconnect the gnd big coil and i think makes device more sensitive.

Hi,

This thread was started by Estaban in 2005.

I wondered if there are any new updates on field tests with the Zahori unit, as it’s been a long time and new improvements have probably been made.

I would like to build one and would be grateful for a point in the right direction on the latest circuit and antenna design, “also a parts list�

Any help from you guys that have made one would be great.

This would be a good beginner’s project for me over the winter months.

Thanks

[Morgan]

Hi,

This thread was started by Estaban in 2005.

I wondered if there are any new updates on field tests with the Zahori unit, as it’s been a long time and new improvements have probably been made.

I would like to build one and would be grateful for a point in the right direction on the latest circuit and antenna design, “also a parts list�

Any help from you guys that have made one would be great.

This would be a good beginner’s project for me over the winter months.

Thanks

The Zahori in wet country maybe work as LRL,i have received news that it works as LRL.
Try this simple circuit as your first LRL.
Note : box for circuit and antenna miust be made of wood,or it will not work,if metal or plastic.
Make one antenna identical to the Mini Zahori,i mean with silver SAMPLE inside.
Use one speaker(or headphones) instead of buzzer.


17418

[Morgan]

The Zahori in wet country maybe work as LRL,i have received news that it works as LRL.
Try this simple circuit as your first LRL.
Note : box for circuit and antenna miust be made of wood,or it will not work,if metal or plastic.
Make one antenna identical to the Mini Zahori,i mean with silver SAMPLE inside.
Use one speaker(or headphones) instead of buzzer.


17418

The ANTENNA

17419

[Morgan]

The ANTENNA

17419

the big antenna no need. Only this one you need. Sample is in the midle,can use silver ring.
Wire dimentions ,have a look on Zahori threads.


17420

[MIJ]

Thanks Morgan,
I will have a go at building this and let you know how I get on.

[nelson]

Hi Morgan.
LOng time that i don´t speak to you, but on this time of the year, i had lots of things to do. So my time to experiment, has limeted to a few minutes or hours. I hope after i finish some work, i will be back 100% to conclude my pdk.
About zahori antenna, you said that the external loop is not needed. So can you please let us know if the center antenna, plus the ring that i also have set up like the one on the picture you post, have the same dimensions? What did you gain with this mod?
My mini zahori, have both antennas and the ring at the center. My expiencies are minimal with it. I had detected a saml aluminium foil about 1 meter distance. Also i got power lines from about a mile on the country side.

Regards

Nelson


the big antenna no need. Only this one you need. Sample is in the midle,can use silver ring.
Wire dimentions ,have a look on Zahori threads.


17420

[Morgan]

Hi Morgan.
LOng time that i don´t speak to you, but on this time of the year, i had lots of things to do. So my time to experiment, has limeted to a few minutes or hours. I hope after i finish some work, i will be back 100% to conclude my pdk.
About zahori antenna, you said that the external loop is not needed. So can you please let us know if the center antenna, plus the ring that i also have set up like the one on the picture you post, have the same dimensions? What did you gain with this mod?
My mini zahori, have both antennas and the ring at the center. My expiencies are minimal with it. I had detected a saml aluminium foil about 1 meter distance. Also i got power lines from about a mile on the country side.

Regards

Nelson

Well,this is good results for the Mini Zahori,if you catch the aluminium you will catch the gold too.
Try the LRL near your TV,if without the Big antenna become more sensitive to TV screen radiation use with the small and SAMPLE only,if not,let stay like this.
In my Mini Zahori it works 3 X more sensitive without the big antenna.

[Morgan]

Hi Morgan.
LOng time that i don´t speak to you, but on this time of the year, i had lots of things to do. So my time to experiment, has limeted to a few minutes or hours. I hope after i finish some work, i will be back 100% to conclude my pdk.
About zahori antenna, you said that the external loop is not needed. So can you please let us know if the center antenna, plus the ring that i also have set up like the one on the picture you post, have the same dimensions? What did you gain with this mod?
My mini zahori, have both antennas and the ring at the center. My expiencies are minimal with it. I had detected a saml aluminium foil about 1 meter distance. Also i got power lines from about a mile on the country side.

Regards

Nelson

Would you like to post here one photo of your Mini Zahori ?
For others to see how to build the BOX(wood only)

Regards

[Morgan]

Would you like to post here one photo of your Mini Zahori ?
For others to see how to build the BOX(wood only)

Regards

Here my Mini Zahori
very easy to build,i buy one nice and cheap wood box(in the chinese shopp) and cuted two discs in wood,inside is the antenna. The handle is in aluminium.Just take a few hours to build.

17445

[Tim Williams]

Morgan the larger outside coil is still connected to ground or is it open?

Tim

[Morgan]

Morgan the larger outside coil is still connected to ground or is it open?

Tim

Hello

As i told,after disconnect the large coil i get 3 times more power in the MINI ZAHORI(locating my TV screen),but maybe lose the LRL efect in the fields,i need to make more tests...

The Zahori is the best LRL for the beginers,but i have the PDK´s for my TH,i´m not a beginner ;-)

[Morgan]

Morgan the larger outside coil is still connected to ground or is it open?

Tim

Better you follow the Nelson´s clues in building the Zahori,becouse he already found something,silver paper,but this is better than nothing,it means his device is working.
He well constructed the Mini Zahori.

[Tim Williams]

If I get any real indication I will improve on it, that's for sure.

[Morgan]

If I get any real indication I will improve on it, that's for sure.

Ok,

i think Nelson build his LRL better than mine,becouse most of the times i can hear the radio with my Zahori,dont know why...

[Morgan]

Ok,

i think Nelson build his LRL better than mine,becouse most of the times i can hear the radio with my Zahori,dont know why...

Well,this happens when i disconnect the big loop,yes now its open.

[mesy64]

hi morgan
I want to combine them bfo with Mini Zahori .Please help me to make this plan.How to incorporate it into what is antenna type, it will be like?Whether its sensitivity to small metals goes up?
waiting for you

[Morgan]

hi morgan
I want to combine them bfo with Mini Zahori .Please help me to make this plan.How to incorporate it into what is antenna type, it will be like?Whether its sensitivity to small metals goes up?
waiting for you

well,this is much more dificult,and the BFO+Zahori is unstable becouse BFO drift a lot.

Better the Mini Zahori alone,TURN ON AND GO,is automatic.

[Tim Williams]

Well I'm cutting out a 8x5x1 wooden box with my laser and will start on the circuit monday. It's the weekend here so it will have to wait. Morgan The BFO is like some vlf detector LRL I'm guessing. The BFO is set near or at the gold frequency and also is setup to detect the changes in the effect. Any way I'll test the unit and keep updates here.

Tim

[Geo]

Hi Tim.
How many watts is the laser cutter???

Regards

[Tim Williams]

40W. I use it for many different things. It's very easy to use. I draw out the design in auto-cad and the laser program cut to scale.

[Geo]

How much time it need to cut the wood at your photo???

[Tim Williams]

2 passes @ 20% power. About 20 seconds. That's the sides of the box that I will glue together to make the 8x5 frame.

[Geo]

2 passes @ 20% power. About 20 seconds. That's the sides of the box that I will glue together to make the 8x5 frame.

Fantastic!!!

Thank you Tim:)

[Max]

40W laser is not a good thing to mess with :rolleyes:

think about reflections it could have , can hurt... your eyes and make you blind if you don't use special glasses, forget about if you're not trained to use them at such (or bigger that that) power

just my 50 cents

regards
Max

[Geo]

40W laser is not a good thing to mess with :rolleyes:

think about reflections it could have , can hurt... your eyes and make you blind if you don't use special glasses, forget about if you're not trained to use them at such (or bigger that that) power

just my 50 cents

regards
Max

I agree, unsure if I had something similar I think it will work properly:examine:dance....

Regards:)

[MIJ]

Here my Mini Zahori
very easy to build,i buy one nice and cheap wood box(in the chinese shopp) and cuted two discs in wood,inside is the antenna. The handle is in aluminium.Just take a few hours to build.

17445


Morgan,

Thanks for picture of your mini Zahori just a couple of questions.

Could you show a picture of the front?

I don’t quite understand why you need the front wooden disc covering the antenna, as I thought that the timber would dull the signal strength as this is a directional antenna?

Also using metal bolts & nut would this have any affect on signal strength?

I hope that this doesn’t sound too stupid but I just want to understand.

Thanks

[GOLDENSKULL]

Hi to all friends that make mini zahori...

did you really can detect buried gold by this device ?

How can we calibrate mini zahori for detecting only gold or only silver ?

Thanks...

[Geo]

Personally, never tried Zagori or mini Zagori or .....

[GOLDENSKULL]

Personally, never tried Zagori or mini Zagori or .....

Thanks Geo,

which LRL, really work for treasure hunting that you try it ?

[Geo]

Thanks Geo,

which LRL, really work for treasure hunting that you try it ?

I use many...
One of them that there is the schematic here... is a modification of Alonsos's PD. It works also without any modification but it is very difficult to adjust it.

[GOLDENSKULL]

I use many...
One of them that there is the schematic here... is a modification of Alonsos's PD. It works also without any modification but it is very difficult to adjust it.

please tell me where is the Alonsos's PD schematic and...

you think, which LRL is the best choice for real treasure hunting ???

Thanks from you... :D

[WM6]

you think, which LRL is the best choice for real treasure hunting ???



Homemade for sure.

http://img215.imageshack.us/img215/5500/alonsopd7.jpg

[Fred]

Homemade for sure.

Absolutely! And the simpler one, to begin with. :D

[GOLDENSKULL]

Homemade for sure.

http://img215.imageshack.us/img215/5500/alonsopd7.jpg

ok, which Homemade LRL is the best choice for real treasure hunting ???
Alonsos's PD or mini zahori or ...???

[WM6]

ok, which Homemade LRL is the best choice for real treasure hunting ???
Alonsos's PD or mini zahori or ...???



Better price / performance ratio you can get with mini zahori or ... this:

(Green light is gold and other precious metal, res light is ferro.)

[J_Player]

Better price / performance ratio you can get with mini zahori or ... this:

http://www.geotech1.com/forums/attachment.php?attachmentid=12318&stc=1&d=1275319146

Green light is gold and other precious metal, res light is ferro.Hmmm We can see this is good for sensing the charge in the air.
But how do we stop it from catching too much stray static charge to become positive or negative too much, then miss tiny variations in positive or negative charge in the air?
What happens when we catch strong static charges from our feet friction on the ground during a dry day?
If only there was a circuit which can remove excess charge and reset to zero charge at a very fast rate...
then we could detect even very small changes in the air charge without overloading the circuit.
Wait... I found a circuit that can do this right here in this thread..!

http://www.geotech1.com/forums/attachment.php?attachmentid=715&stc=1&d=1148419022

Hmmmm... we are back where we started. :shocked:
Well, it can find the tiny changes from the air charge, but it does not have the red and green for gold and iron.
So maybe better the red and green zahori :)


Best wishes,
J_P

[WM6]

Hmmmm... we are back where we started. :shocked:

J_P

In meantime a huge of changes, schematic I posted was further developed to GIM (look at my post again)!

[J_Player]

In meantime a huge of changes, schematic I posted was further developed to GIM (look at my post again)!Hmmm....
What is GIM?
Is similar to JINN?

Best wishes,
J_P

[WM6]

Hmmm....
What is GIM?
Is similar to JINN?

Best wishes,
J_P

Look at drawings, GIM is Gold Ions Monitor.

JINN is prior art of GIM.

[Geo]

Alonso's PD is more critical to adjust it and to work with it but it is better.

[Fred]

Better price / performance ratio you can get with mini zahori or ... this:

(Green light is gold and other precious metal, res light is ferro.)

:lol: Great circuit WM6, i like the discrimination function!
But i have made here a really super long range version: when the green led is on it means there is gold somewhere, so sentitive that it also detects it on atomic form .

[WM6]

:lol: Great circuit WM6, i like the discrimination function!
But i have made here a really super long range version: when the green led is on it means there is gold somewhere, so sentitive that it also detects it on atomic form .

Thanks for upgrade Fred.

What do you think about thirth UV LEDs to not to detecting gold teeth?

[J_Player]

Thanks for upgrade Fred.

What do you think about thirth UV LEDs to not to detecting gold teeth?I hear stories UV-A LED is good for discriminating between dental gold and jewelry gold.
But UV-B LED does not work well.
Best performance when less than 200 nm.

Hope this helps.

Best wishes,
J_P

[WM6]

But UV-B LED does not work well.
Best performance when less than 200 nm.

Hope this helps.

Best wishes,
J_P

Thanks for hint J_P, assume that "nm" mean "non modulated" light beam carier?

[J_Player]

Thanks for hint J_P, assume that "nm" mean "non modulated" light beam carier?Exactly :)

Best wishes,
J_P

[mesy64]

hi dear wm6
Can be identified with the orbit of gold in soil????

[Fred]

That´s great information: we are progressing.
Please dear Mr JP, where could i buy 2 leds for detection at less than 2km with "nm" option (green uv kind pse)
And one white uv-b for night detection.

BTW, i am patenting an idea but i will share it here before as i know it will not leak : I have invented a BFO that uses a yellow led, and will frequency beat with the yellow color of gold.
Optional white plug-in leds can be purchased for silver, platinum, aluminium and stainless steel, and red ones for copper.
I need funds, anyone ?

[J_Player]

That´s great information: we are progressing.
Please dear Mr JP, where could i buy 2 leds for detection at less than 2km with "nm" option (green uv kind pse)
And one white uv-b for night detection.

BTW, i am patenting an idea but i will share it here before as i know it will not leak : I have invented a BFO that uses a yellow led, and will frequency beat with the yellow color of gold.
Optional white plug-in leds can be purchased for silver, platinum, aluminium and stainless steel, and red ones for copper.
I need funds, anyone ?The cost of green UV-A LEDs has risen dramatically since the WM6 circuit and improvements was leaked from the forum.
I don't know where you can get one for less than 19999,99 £.
But the cost will probably go down after all the world treasure is found from using the WM6 LRL.
For night white UV-B LEDs you are better to not use these...
They will load down the circuit and make your batteries go flat very fast.
Better to wait for a full moon when you want to go for night treasure hunting. :good

Best wishes,
J_P

[Fred]

hi dear wm6
Can be identified with the orbit of gold in soil????
Can you count fast enough ?

[Fred]

The cost of green UV-A LEDs has risen dramatically since the WM6 circuit and improvements was leaked from the forum.
I don't know where you can get one for less than 19999,99 £.
But the cost will probably go down after all the world treasure is found from using the WM6 LRL.
For night white UV-B LEDs you are better to not use these...
They will load down the circuit and make your batteries go flat very fast.
Better to wait for a full moon when you want to go for night treasure hunting. :good

Best wishes,
J_P
Thank you for your answer.I like the price.

[mesy64]

Can you count fast enough ?

yes i have enough

[Fred]

yes i have enough
Not money, spinning electrons !
It was a just a joke.

[Leto]

The cost of green UV-A LEDs has risen dramatically since the WM6 circuit and improvements was leaked from the forum.
I don't know where you can get one for less than 19999,99 £.
But the cost will probably go down after all the world treasure is found from using the WM6 LRL.
For night white UV-B LEDs you are better to not use these...
They will load down the circuit and make your batteries go flat very fast.
Better to wait for a full moon when you want to go for night treasure hunting. :good

Best wishes,
J_P

Found discounted UV-B LEDs for 19998.99 BRL
http://www.hungcorp.com/UV-A%20LEDs_discount.br/
The site server is slow so keep trying..

[J_Player]

Found discounted UV-B LEDs for 19998.99 BRL
http://www.hungcorp.com/UV-A%20LEDs_discount.br/
The site server is slow so keep trying..Thank you Leto,
But even the hungcorp UV LEDs are too expensive for me.
Engineers in the secret bunker have been experimenting with single-sideband non-modulated light beams, and they discovered an ordinary red LED can discriminate the difference between dental gold and jewelry gold if gold from a tooth filling is placed in the sample chamber to be ionized by charging it with 5 volt pulses.

How the non-modulated light discriminates is a single-sideband secret.
But it does not matter because red LEDs cost less than 0.01 eu.
One important tip is you must use a lens to make the red LED to focus into a beam.
Or you could use a red laser pointer which is already a good beam.
But the red laser pointer cost more than 0.01 eu, so better to use the red LED.

You can see it is no longer necessary to spend 19999,99 £ or 19999,99 BRL for the green UV-A LED.


Good luck with your treasure hunting,
J_P

[WM6]

Hi J_P

be carefull with all such data, patent troll is watching everywhere.

[Geo]

You have sufficiently large ability to parodies and to destroy any matter which you do not like:(

[WM6]

You have sufficiently large ability to parodies and to destroy any matter which you do not like:(



Me? What will you say about the global financial capitalism that will destroy our lives?

These are just harmless jokes Geo.

And version of Zahori I posted above is clearly serious circuit.

How with your PD project are there some progress?

[Geo]

Regards..........:)

[Rudy]

Thank you Leto,
But even the hungcorp UV LEDs are too expensive for me.
Engineers in the secret bunker have been experimenting with single-sideband non-modulated light beams, and they discovered an ordinary red LED can discriminate the difference between dental gold and jewelry gold if gold from a tooth filling is placed in the sample chamber to be ionized by charging it with 5 volt pulses.

How the non-modulated light discriminates is a single-sideband secret.
But it does not matter because red LEDs cost less than 0.01 eu.
One important tip is you must use a lens to make the red LED to focus into a beam.
Or you could use a red laser pointer which is already a good beam.
But the red laser pointer cost more than 0.01 eu, so better to use the red LED.

You can see it is no longer necessary to spend 19999,99 £ or 19999,99 BRL for the green UV-A LED.


Good luck with your treasure hunting,
J_P

Very interesting JP. Does it matter wether the upper or the lower sideband is used? I think the lower sideband would be better as most targets are low on the ground. What do you think?

[J_Player]

Very interesting JP. Does it matter wether the upper or the lower sideband is used? I think the lower sideband would be better as most targets are low on the ground. What do you think?Well, I was thinking the same thing... It is obviously the lower sideband...
Until I read some science books that say you need to have some modulation in order for a carrier wave to work for sending signals.
But then we are talking about non modulated light beams carriers... not strictly considered RF, so the rules change due to relativity effects on the subatomic level.

Conclusion:
Upper or lower sideband cannot be determined without secret light carrier SSB explanation.
The best we can do is to make a wild guess.

Best wishes,
J_P

p.s. After reading science websites, I concluded the sideband must be either a UV sideband or a NIR sideband. Do you think I got it right?
If so, I hope the UV or NIR LEDs come in red or green so they are easy to see where we are pointing the beam.

[J_Player]

You have sufficiently large ability to parodies and to destroy any matter which you do not like:(Hi Geo,
I think you have it wrong.
This is the thread Estaban started when he wanted to talk about the Zahori circuit.
Esteban's thread was destroyed long ago when LRL experimenters decided they don't like his Zahori circuit and want to change the thread to the charge detector thread.

We see that The Zahori is a charge detector which has a special digital filter which discharges the antenna at 50 or 60 Hz to help stability.
The Zahori is not a simple static charge detector. The Zahori is different because it has the added digital 50-60 Hz filter.


Esteban and Carlos originally talked about this circuit in 2002 http://geotech1.com/forums/showthread.php?t=6664
Then Esteban posted the Zahori schematic in 2005 here http://www.geotech1.com/forums/showthread.php?t=10601
Then Esteban posted the Zahori a third time in Ivconic's negative ion detector thread here: http://www.geotech1.com/forums/showthread.php?p=40864#post=40864

But Esteban knew the Zahori is not a simple air charge detector because it has the 50/60 Hz discharging filter added to the circuit.
He wanted a special thread for only this Zahori circuit so he could explain how the 50/60 filter works and details of this circuit.
He did not want to confuse this Zahori circuit with the static charge circuits he saw in Ivconic's ion detector thread which did not have the 50/60 Hz filter.
So he started this new Zahori thread here for only the Zahori and not the other static charge detectors that I posted in Ivconic's thread.

This Zahori thread became a very good thread where people can learn about the Zahori circuit.
But then some LRL experimenters decided they don't like Esteban's Zahori and they want to change his Zahori back to the circuit which I made for the Ivconic static charge detecting.
You can find where I first posted this circuit here: http://www.geotech1.com/forums/showthread.php?p=41405#post=41405

http://www.geotech1.com/forums/attachment.php?attachmentid=583&stc=1&d=1142476924

Morgan calls my circuit the "Mini Zahori" when he connects his antenna to it.
But I can tell you it is not called Mini Zahori or any kind of Zahori.
I know because I am the designer of this circuit..!

My charge detector circuit is based on a simple static detector and negative ion detector by Andy Collinson here: http://www.zen22142.zen.co.uk/Circuits/Misc/staticdet.htm
I never added a digital filter for 50/60 Hz to make it into a Zahori detector.
I only added a versatile audio amplifier to replace Andy's meter, and connected it to Ivconic's antenna.
I would never call this a Zahori because it has no digital discharging filter that we find in the Zahori.

But now Experimenters make a joke with my circuit and name it "Mini Zahori".
I begin to wonder why they are making this joke.
I wonder why they don't make their posts about this circuit in the ion detector thread where they found it instead of in Esteban's thread for the Zahori.
I wonder why they don't call my circuit by its correct name as the "charge detector" instead of pretending it is a zahori circuit.

If we read the thread from the beginning, then we see the reason.
It is because they don't like Esteban's Zahori discussion.
They want to change to discussion of my circuit and stop the talk of true Zahori circuit.
You can see for yourself here http://www.geotech1.com/forums/showthread.php?p=88749#post=88749
Where my charge detector circuit is called Mini Zahory if an "ionic chamber" is added.
But adding chambers or samples does not change my circuit into any form of the Zahori circuit.
Not unless a 50/60 Hz filter is added to the sensing circuit.

Esteban quickly tries to get back to the Zahori circuit which he wanted to talk about when he shows more details to the true Zahori here and below: http://www.geotech1.com/forums/showthread.php?p=88930#post=88930
But my electric charge detector circuit comes back again here: http://www.geotech1.com/forums/showthread.php?p=122861#post=122861
And it continues to be called a "mini zahori" when it is connected to an antenna with a sample in it.
But we see there is no 50/60 Hz filter circuit in this detector - no Zahori circuit at all.

For me, I do not care if people want to call my circuit Zahori or not.
I can play games same as the people who do not like Esteban's Zahori circuit.
But the difference is I do like his Zahori circuit.
And I can see very well that the Zahori has the digital filter in it, which makes it as a Zahori, and not a plain charge detector.
Esteban knew this too. You can see the two circuits Esteban posted were both using 50/60 Hz filters -- See below:

http://www.geotech1.com/forums/attachment.php?attachmentid=715&stc=1&d=1148419022

http://www.geotech1.com/forums/attachment.php?attachmentid=716&stc=1&d=1148432640

When I see the LRL experimenters do not like to talk about the Zahori circuit in the Zahori thread, then I think it is ok to make parodies...
My purpose is not to destroy Esteban's thread about the Zahori circuit -- his Zahori discussion was already destroyed long ago by LRL experimenters who did not like it.
My reason to make parodies is to protest against the continuing attempts to hijack Esteban's serious discussion of his 50/60 Hz filtered Zahori project.

The only question I have is: why didn't people make posts about this charge detector and other ion detectors in the thread that we started for these?
Why don't we see these charge detector circuits in the Ivconic's ion detector thread instead of in Esteban's Zahori thread?
Why hijack Esteban's attempt to discuss the Zahori circuit?


Best wishes,
J_P

[Geo]

Hi Geo,

The only question I have is: why didn't people make posts about this charge detector and other ion detectors in the thread that we started for these?
Why don't we see these charge detector circuits in the Ivconic's ion detector thread instead of in Esteban's Zahori thread?
Why hijack Esteban's attempt to discuss the Zahori circuit?


Best wishes,
J_P

Hi J_P.
Realy i don't know

Regards

[GOLDENSKULL]

Hi dear J_Player,

Thanks for your post and design ...

if you like please start a new post for introduce your static charge detector and give me us to share our knowledge to improve it ... ok ?

did you think by this device we can detect gold treasures ?

[J_Player]

Hi dear J_Player,

Thanks for your post and design ...

if you like please start a new post for introduce your static charge detector and give me us to share our knowledge to improve it ... ok ?

did you think by this device we can detect gold treasures ?
Hi Goldenskull,
My static charge detector was already introduced here: http://www.geotech1.com/forums/showthread.php?p=40864#post=40864
There is no need to introduce it a second time.
It was an experiment I added to the charge detector which Ivconic designed and built here: http://www.geotech1.com/forums/showthread.php?p=40864#post=40864

If you read all of that thread you will find the Ivconic charge detector is much more sophisticated than my design.
You will see that the Ivconic circuit is described in detail so that anybody can make this sophisticated charge sensor.
I made my design only to make a more simple version that would detect the same charge in the air, but maybe not as sensitive.
I did eventually build this circuit on a proto board and it was working after minor tweaks to the component values.
I found it would detect charges in the air as I expected. But I did not find any buried treasures with it.

You can read a lot more about this in the thread that I linked above.
Read what people found with the Ivconic detector - My design performed the same, except not as sensitive as the Ivconic detector.
You can read my summary of the Ivconic ion detector performance here: http://www.geotech1.com/forums/showthread.php?p=125115#post=125115
And you can read many tips for building and making improvements to the Ivconic detector.

But people did not want to continue posting improvements to the Ivconic detector or to my circuit there.
They posted their improvements here in the Zahori discussion instead.
We see the only improvement to my circuit which is claimed to find treasure is done by changing the antenna, not by changing the circuit.
So if you want to learn the details of my circuit or the Ivconic circuit, You can go here and read: http://www.geotech1.com/forums/showthread.php?p=40864#post=40864

But if you want to learn about the Zahori circuit, you will find it is another more sophisticated circuit than what I designed.
I immediately recognized the improvements in the design of the Zahori circuit.
But it was not until I received an email from an EE that I saw that with some modifications, the zahori has much more potential for studying the signals received by dividing them in time domains.
This zahori circuit design concept proved to be instrumental in developing some circuitry which was later used for observing some very strange small signals which are believed to be associated with long range detection.
I have already hinted about this kind of use for the zahori several times in this forum.

But then I do not claim the zahori can find treasure, nor do I claim that my charge detector circuit can find treasure.
It is other people who make those claims.


Best wishes,
J_P

[WM6]

Funny that only complete LRL circuit design in Remote sensing forum was given by sceptic.

[J_Player]

Funny that only complete LRL circuit design in Remote sensing forum was given by sceptic.Hi WM6,
I see more than one complete LRL circuit in the remote sensing forum.
I see a circuit by Ivconic, by me, and several by Dr. Best who is rumored to be skeptic, as well as several by WM6.
We also see Qiaozhi's Avramenko’s fork LRL http://www.geotech1.com/forums/showthread.php?p=39945#post=39945
And several LRL circuits given by Carl-NC here:
http://www.geotech1.com/cgi-bin/pages/common/index.pl?page=lrl&file=/projects/mfd1/index.dat
http://www.geotech1.com/cgi-bin/pages/common/index.pl?page=lrl&file=reports/colorado/index.dat
http://www.geotech1.com/cgi-bin/pages/common/index.pl?page=lrl&file=reports/vr800/index.dat
http://www.geotech1.com/cgi-bin/pages/common/index.pl?page=lrl&file=reports/escope20/index.dat
http://www.geotech1.com/cgi-bin/pages/common/index.pl?page=lrl&file=reports/escope301/index.dat
http://www.geotech1.com/cgi-bin/pages/common/index.pl?page=lrl&file=reports/escope/index.dat
http://www.geotech1.com/cgi-bin/pages/common/index.pl?page=lrl&file=reports/ls50/index.dat
http://www.geotech1.com/cgi-bin/pages/common/index.pl?page=lrl&file=reports/examiner/index.dat
http://www.geotech1.com/cgi-bin/pages/common/index.pl?page=lrl&file=reports/tscope/index.dat
http://www.geotech1.com/cgi-bin/pages/common/index.pl?page=lrl&file=reports/me2/index.dat

But I also see one complete LRL circuit is given by Esteban here, which is the Zahori: http://www.geotech1.com/forums/attachment.php?attachmentid=748&stc=1&d=1150380983
and another variation here: http://www.geotech1.com/forums/attachment.php?attachmentid=716&stc=1&d=1148432640
I don't see any other complete LRL circuits given by LRL builders.

Best wishes,
J_P

[Tim Williams]

Interesting! So Morgan which one of these circuits is working? Which one are you getting calls claiming they found gold? I don't mind building and testing, but I don't want to waste my time either.

I've been building and using LRL type systems since 1985 and I'm yet to find a instrument to detect the anomaly. Ideo is the feedback in dowsing using any rod system. But if what you claim is true, that a static field surrounds a long time buried target, this should be easy to detect. I have found silver coins and rings. Some gold. But nothing big yet using my system.

Maybe a new thread with the correct circuit should be started so everyone is on track.

TIm

[Tim Williams]

ES2 ,9 on esteban circuit go?

[J_Player]

ES2 ,9 on esteban circuit go?Hi Tim,
That was originally connected to ground through a switch. It was originally intended as a means to switch the sample and hold on and off.
The Esteban modified version removed the sample and hold feature by deleting the lower switching to ground.
This Esteban modification causes ES1 to remain in the closed position, and allows only ES3 to operate at the antenna to discharge it 50 or 60 times a second.
You should get the equivalent Esteban modification by removing ES1 and replacing it with a direct conductor from IC1 to IC2 + C9, and removing ES2 and pullup resistor R8 (15k) completely.
The unused cmos inputs should be pulled up or down so they aren't floating to pick up charges from the air.
See the original circuit below:

http://www.geotech1.com/forums/attachment.php?attachmentid=720&stc=1&d=1148598254


Be sure to read the original translated description for the circuit in PDF at this link: http://www.geotech1.com/forums/attachment.php?attachmentid=721&d=1148598254

You can see the 4066 data sheet attached in PDF below.
Be sure to use a good quality 4066 from a major American manufacturer or Asian manufacturer.
Poor performance was reported for some generic versions.



Best wishes,
J_P

[Tim Williams]

Thanks J_P.

[Morgan]

Thanks J_P.

the claims of treasure was with the J_P circuit using my ANTENNA with SAMPLE.

Maybe this people found treasures by chance??? dont know,but you can see most of the people who build the MINI ZAHORI claims have found something,and all the people who build the big zahori claim to found nothing...

So,dont know,make your choice

[Geo]

I don't believe that ion detectors have the ability to find gold from long distance. Maybe only over the buried object. But over the object if the depth is not high then a metal detector is better. I don't know what is happening if the depth is very high......
If ion detector has results over the buried object at high depth then it is a good utility for lrl who have pinpoint problem.:rolleyes:
But what is happening with electron emition of silver and copper???? maybe J_P knows.

Regards:)

[J_Player]

I don't believe that ion detectors have the ability to find gold from long distance. Maybe only over the buried object. But over the object if the depth is not high then a metal detector is better. I don't know what is happening if the depth is very high......
If ion detector has results over the buried object at high depth then it is a good utility for lrl who have pinpoint problem.:rolleyes:
But what is happening with electron emition of silver and copper???? maybe J_P knows.

Regards:)Hi Geo,
What I can tell you is I never found any buried treasure with a charge sensor.
I found a lot of detection of charged objects, of old crt screens, and I could locate power wires that are hidden behind walls.
You can read the same things that Ivconic could find with his differential amp ion detector.
I found the same kind of things, but not buried treasure, same as Ivconic did not.

Here is what you need to know about buried gold, silver and copper:
1. The gold you hunt for is not pure gold.
It almost always has some silver and copper alloyed into it, and sometimes other metals too.
The same is true for natural gold deposits under the ground -- almost never pure gold, and always some silver or copper and maybe other metals too.

2. When metal is buried in the soil, it can corrode because of the action of chemicals in the ground.
Water is not necessary because there are microbes which secrete cyanide and organic acids which will attack gold, silver, and copper.
If water is present, it can help to dissolve and suspend the ions from these metals and other metals in the soil.

3. The metal ions which are formed from shallow buried metals will quickly combine with other chemicals in the soil to become salts.
Or gold will convert back into the original metal in the case of gold ions becoming micro gold particles if they are close to the surface.
In order for these ions to remain as ions in the soil, the metal must be buried more than 10-12 cm deep.

4. When metal is buried more than 10-12 cm deep, the corrosion will take a long time to happen.
This is because it depends on certain microbes to find the metal and produce microscopic amounts of cyanide and organic acids which very slowly dissolve the metals.
It can take many years for enough microscopic drops of cyanide and acids to dissolve any measurable amount of gold ions.
And after hundreds of years, we see that not enough gold has dissolved to see a difference on the surface.
A quick polishing will make it look like new. The amount of gold and other metal dissolved is extremely tiny.
This is how fresh buried metal is different from long time buried metal.
Fresh buried metal will not have the microscopic corrosion that long time buried metal has.

5. When metal is buried more than 10-12 cm deep for long enough, the ions that dissolve into the soil will begin to migrate upward in a column toward the surface.
They will continue following this column until they reach the level of 10-12 cm depth, where they will combine with other chemicals in the soil and will stop being ions.
The size of this column is much bigger than the size of the buried metal.

6. When gold dissolves in the soil due to microbe-caused corrosion, only a very tiny amount of gold dissolves.
The amount of gold is somewhere around 0.3 parts per trillion.
If this piece of gold is 5% silver alloy, there will be hundreds of times more silver ions that corrode into the same soil as the gold ions.
The same is true for the copper that is alloyed into the gold, and other metals.
So when you are thinking you have a rich concentration of gold ions in the soil, you really have a weak concentration of gold ions.
But you have a very much stronger concentration of copper and silver ions, and even other metal ions.

7. Gold, silver and copper do not simply corrode into ions then convert back to hard substances at the surface.
There are many ionic chemical changes happening under the ground.
Gold ions are usually suspended in sulfur complexes and organic acids.
They can convert back to gold, then back to ions in their journey to the surface, depending on how the chemical and electrical environment changes during their journey.
They can attach to many different kinds of molecules and complexes before they finally reach the last 10-12 cm

8. The trails of ions that are formed by metals in the ground can travel for over a thousand meters upward to reach the surface.
But it does not matter whether it is traveling 1000 meters or 100 meters...
The scientists who measure these ions must dig a hole and remove a soil sample to take to a laboratory.
At the laboratory they have special instruments that make chemical reactions and measurements to the soil sample.
After they take these laboratory measurements, then they can detect the 0.3 parts per trillion of gold ions to show there is gold below the hole they dig.

The answer to your question is hidden in the 8 paragraphs I typed above.
But you need to use logic to figure it out.


Best wishes, :)
J_P

[Geo]

Thank you J_P.
So i must looking for something else as pinpointer for my LRL

Regards

[teknoloji]

Hi Geo,
I think you have it wrong.
This is the thread Estaban started when he wanted to talk about the Zahori circuit.
Esteban's thread was destroyed long ago when LRL experimenters decided they don't like his Zahori circuit and want to change the thread to the charge detector thread.

We see that The Zahori is a charge detector which has a special digital filter which discharges the antenna at 50 or 60 Hz to help stability.
The Zahori is not a simple static charge detector. The Zahori is different because it has the added digital 50-60 Hz filter.


Esteban and Carlos originally talked about this circuit in 2002 http://geotech1.com/forums/showthread.php?t=6664
Then Esteban posted the Zahori schematic in 2005 here http://www.geotech1.com/forums/showthread.php?t=10601
Then Esteban posted the Zahori a third time in Ivconic's negative ion detector thread here: http://www.geotech1.com/forums/showthread.php?p=40864#post=40864

But Esteban knew the Zahori is not a simple air charge detector because it has the 50/60 Hz discharging filter added to the circuit.
He wanted a special thread for only this Zahori circuit so he could explain how the 50/60 filter works and details of this circuit.
He did not want to confuse this Zahori circuit with the static charge circuits he saw in Ivconic's ion detector thread which did not have the 50/60 Hz filter.
So he started this new Zahori thread here for only the Zahori and not the other static charge detectors that I posted in Ivconic's thread.

This Zahori thread became a very good thread where people can learn about the Zahori circuit.
But then some LRL experimenters decided they don't like Esteban's Zahori and they want to change his Zahori back to the circuit which I made for the Ivconic static charge detecting.
You can find where I first posted this circuit here: http://www.geotech1.com/forums/showthread.php?p=41405#post=41405

http://www.geotech1.com/forums/attachment.php?attachmentid=583&stc=1&d=1142476924

Morgan calls my circuit the "Mini Zahori" when he connects his antenna to it.
But I can tell you it is not called Mini Zahori or any kind of Zahori.
I know because I am the designer of this circuit..!

My charge detector circuit is based on a simple static detector and negative ion detector by Andy Collinson here: http://www.zen22142.zen.co.uk/Circuits/Misc/staticdet.htm
I never added a digital filter for 50/60 Hz to make it into a Zahori detector.
I only added a versatile audio amplifier to replace Andy's meter, and connected it to Ivconic's antenna.
I would never call this a Zahori because it has no digital discharging filter that we find in the Zahori.

But now Experimenters make a joke with my circuit and name it "Mini Zahori".
I begin to wonder why they are making this joke.
I wonder why they don't make their posts about this circuit in the ion detector thread where they found it instead of in Esteban's thread for the Zahori.
I wonder why they don't call my circuit by its correct name as the "charge detector" instead of pretending it is a zahori circuit.

If we read the thread from the beginning, then we see the reason.
It is because they don't like Esteban's Zahori discussion.
They want to change to discussion of my circuit and stop the talk of true Zahori circuit.
You can see for yourself here http://www.geotech1.com/forums/showthread.php?p=88749#post=88749
Where my charge detector circuit is called Mini Zahory if an "ionic chamber" is added.
But adding chambers or samples does not change my circuit into any form of the Zahori circuit.
Not unless a 50/60 Hz filter is added to the sensing circuit.

Esteban quickly tries to get back to the Zahori circuit which he wanted to talk about when he shows more details to the true Zahori here and below: http://www.geotech1.com/forums/showthread.php?p=88930#post=88930
But my electric charge detector circuit comes back again here: http://www.geotech1.com/forums/showthread.php?p=122861#post=122861
And it continues to be called a "mini zahori" when it is connected to an antenna with a sample in it.
But we see there is no 50/60 Hz filter circuit in this detector - no Zahori circuit at all.

For me, I do not care if people want to call my circuit Zahori or not.
I can play games same as the people who do not like Esteban's Zahori circuit.
But the difference is I do like his Zahori circuit.
And I can see very well that the Zahori has the digital filter in it, which makes it as a Zahori, and not a plain charge detector.
Esteban knew this too. You can see the two circuits Esteban posted were both using 50/60 Hz filters -- See below:

http://www.geotech1.com/forums/attachment.php?attachmentid=715&stc=1&d=1148419022

http://www.geotech1.com/forums/attachment.php?attachmentid=716&stc=1&d=1148432640

When I see the LRL experimenters do not like to talk about the Zahori circuit in the Zahori thread, then I think it is ok to make parodies...
My purpose is not to destroy Esteban's thread about the Zahori circuit -- his Zahori discussion was already destroyed long ago by LRL experimenters who did not like it.
My reason to make parodies is to protest against the continuing attempts to hijack Esteban's serious discussion of his 50/60 Hz filtered Zahori project.

The only question I have is: why didn't people make posts about this charge detector and other ion detectors in the thread that we started for these?
Why don't we see these charge detector circuits in the Ivconic's ion detector thread instead of in Esteban's Zahori thread?
Why hijack Esteban's attempt to discuss the Zahori circuit?


Best wishes,
J_P
I Can not type because of the language.

My opinion is missing zahori circuit.

who knows the subject to answer questions vermemektedirler.Boşa time to prevent the growth of labor to progress to keep you entertained.

Zahori sensor operation to be done, is.

Rod antenna for wide-area search may be.

My opinion zahori detects gold and attracts others.

But the ion sensor is required.

[Morgan]

Interesting! So Morgan which one of these circuits is working? Which one are you getting calls claiming they found gold? I don't mind building and testing, but I don't want to waste my time either.

I've been building and using LRL type systems since 1985 and I'm yet to find a instrument to detect the anomaly. Ideo is the feedback in dowsing using any rod system. But if what you claim is true, that a static field surrounds a long time buried target, this should be easy to detect. I have found silver coins and rings. Some gold. But nothing big yet using my system.

Maybe a new thread with the correct circuit should be started so everyone is on track.

TIm

better ideia,build both ZAHORI and MINI ZAHORI,make the complete field test and post the results here ;)

[MIJ]

better ideia,build both ZAHORI and MINI ZAHORI,make the complete field test and post the results here ;)


It’s been awhile since the last posts hear, just wondered if anyone has any field test results with the ZAHORI and MINI ZAHORI ?

[Fred]

It’s been awhile since the last posts hear, just wondered if anyone has any field test results with the ZAHORI and MINI ZAHORI ?

Many rumors, but no proof that ANY LRL ever worked.

[MIJ]

Many rumors, but no proof that ANY LRL ever worked.

I think Morgan has shown proof of a working LRL ;)

[MIJ]

Just thought I would give you an update on some small tests I have made with the Zahori I bought from Goldfinder.
Thread hear http://www.longrangelocators.com/forums/showthread.php?t=18457 (http://www.longrangelocators.com/forums/showthread.php?t=18457)

I’m not really into building electronic circuits, but it looks to me to be a very sturdy and well made unit I am very pleased with it.

It’s very sensitive and picks up the static from walking along my carpets in my house at about 3meters, also when I comb my hair “yes I still have some� it picks up the static from my comb to about 1 meter.

It doesn’t seem to pick up any electrical interference in the house, just about picks up my cordless telephone when it’s on charge at half a meter, so it certainly seems to filter out unwanted signals.

I also note that the 5mm solid copper antenna picks up static signals from the sides and not just the tip, its 100mm long.

I have tested it over my gold and silver targets in my garden but it did not seem to respond.

I think that the humidity was high at the time I tested it, and maybe this was the reason, also my garden where my targets are berried is very wet this time of year.

It has a “microamperes meter� but no LED light and no beeper, it’s a bit difficult to keep your eye on the tiny meter all the time when searching waving it about, I think it needs to have a beeper and LED light, maybe this is possible to fit some time? I will have to get some advice from some of you in the forum “it needs to be more users friendly�

I wanted to test it at home more before going out in the fields; I’m still trying to find out the maximum range of detection.

Any ideas what I could use to get the range of detection?

Some of my questions are –

1 - How would I fit a buzzer and LED light “where would It connect to?�

2 - Would I need a different sensitivity knob?

3 - Would it be possible to use a different type of antenna “possibly a Ferrite type� to get more target range?

4 - Is the above possible with the original circuit “or maybe not worth it?�

Regards :)

[J_Player]

Just thought I would give you an update on some small tests I have made with the Zahori I bought from Goldfinder.
Thread hear http://www.longrangelocators.com/forums/showthread.php?t=18457 (http://www.longrangelocators.com/forums/showthread.php?t=18457)

I’m not really into building electronic circuits, but it looks to me to be a very sturdy and well made unit I am very pleased with it.

It’s very sensitive and picks up the static from walking along my carpets in my house at about 3meters, also when I comb my hair “yes I still have some” it picks up the static from my comb to about 1 meter.

It doesn’t seem to pick up any electrical interference in the house, just about picks up my cordless telephone when it’s on charge at half a meter, so it certainly seems to filter out unwanted signals.

I also note that the 5mm solid copper antenna picks up static signals from the sides and not just the tip, its 100mm long.

I have tested it over my gold and silver targets in my garden but it did not seem to respond.

I think that the humidity was high at the time I tested it, and maybe this was the reason, also my garden where my targets are berried is very wet this time of year.

It has a “microamperes meter” but no LED light and no beeper, it’s a bit difficult to keep your eye on the tiny meter all the time when searching waving it about, I think it needs to have a beeper and LED light, maybe this is possible to fit some time? I will have to get some advice from some of you in the forum “it needs to be more users friendly”

I wanted to test it at home more before going out in the fields; I’m still trying to find out the maximum range of detection.

Any ideas what I could use to get the range of detection?

Some of my questions are –

1 - How would I fit a buzzer and LED light “where would It connect to?”

2 - Would I need a different sensitivity knob?

3 - Would it be possible to use a different type of antenna “possibly a Ferrite type” to get more target range?

4 - Is the above possible with the original circuit “or maybe not worth it?”

Regards :)Hi MIJ,
It seems you found the same as what other builders of the Zahori found.
It detects charges in the air, but does not detect treasure.
You are able to detect the faintest of charges from combing your hair, or any other source of static charges.
But your buried gold and silver do not produce a static charge that you can detect.
But also remember that I have seen no example in this forum where an experimenter built the original Zahori design without modifying it in some way.
The original zahori circuit is a very sensitive static charge detector.
It is so sensitive that it has an electronic provision to drain any charge from the antenna 50 times a second to keep the charge from building up too strong where it could damage the semiconductor that is detecting the charge it collects.
It also has a sample and hold module which will remember what charge it detected while the antenna is being drained and preparing to take a new sample from the air.
Most of the projects I see people build have either deleted these features or modified them so they cannot work.
And I see many builders add on additional control knobs to make adjustments in the circuit that were not intended to be adjusted.
Nearly everyone who built the zahori, modified it, then after their modifications they say it does not work to detect treasure.

Of course, Esteban says it is possible to detect buried treasure using the Zahori.
It seems you have identified the question... how to make the Zahori detect treasure?
Some basic theory of detecting charges in the air:
If you are not drawing in air samples to check the charge of particles in the air, then the ability to detect a charge is related to the surface area of your charge collecting sensor.
This means a larger surface area will be exposed to a larger volume of air whereby it can collect a charge from the air.
But large plates or dishes are not desirable for a portable detector tool. So we have small versions as you see in the telescoping antenna.

A second principle is that when you are outdoors trying to detect a charge, you are grounded because you are standing on the ground.
The metal box you hold in your hand is also grounded by conduction through the saline liquid beneath your skin, so you can consider all your body and the metal zahori box to be connected to ground.
(This can change indoors, but we seldom go treasure hunting indoors).
Any charge in the air can be affected by your body moving through it, which brings a ground potential up to nearly 2m height to create an artificial ground in the air.
The part of your zahori that is not grounded is the antenna, which is insulated from the metal box.
The antenna will have whatever charge it pics up from the air around it.
Some of this charge will be from the negatively charged ground that you are conducting to the metal box.
But when the antenna is extended, the end away from you has penetrated through a voltage gradient to reach into the area where an air charge can be sampled.

It is as you say... the antenna can pick up charges from the sides as well as from the front. In fact, we expect it to pick up more charge from the sides than the front, because the surface is greater.
The front only has the diameter of the antenna (a few millimeters) while the sides have a surface that is over 3 times the diameter, over the length of the aerial.

We see some versions that show the antenna placed between two similar grounded antennas.
This greatly reduces the amount of charge that is collected, but it allows the small amount that is collected to become more directional.
This arrangement will collect more charge from the front, top and bottom where there is no grounded conductor so close as there is at the sides.
Another configuration is to place a grounded dish around the antenna so the antenna protrudes from the center of the dish.
This can have a focusing effect which causes negatively charged particles to congregate toward the antenna.
Of course, you could electronically charge this dish to become charged either positive or negative in order to repel particles that are charged oppositely.
(This is the principle of the Ivconic charge detector antenna designs).
But remember, neither Ivconic or any others who built the zahori or charge detectors with these kind of antennas ever located any buried treasure.

As far as modifications, there is a lot that can be done.
But in order to give advice for modifications, we would first need to know the circuit diagram.
This is because everyone builds different variations of the zahori.
We see even in the variations called "mini zahori", there are further modifications which nobody really shows the exact circuit diagram that is being used.

For your questions...
1. It is relatively easy to add on a buzzer circuit that can be adjusted to beep when the circuit finds a signal above a certain level.
This kind of circuit can be added as a separate add-on that does not influence any of the existing circuit in any way.

2. A different sensitivity knob is not needed except to add a knob along with the new buzzer circuit to set how strong the signal is before it beeps.

3. Antenna for more range detecting static anomalies begins with surface area.
But range of detection also includes directional properties.
When the optimum size is figured for an antenna that is not too bulky, then the next consideration is how to make it as directional as possible.
This approach is only for increasing the range at which you can locate a charge anomaly in the line of sight directions from the antenna.
There are other concepts of more range that are concerned with detecting other things than charges that are in the air or on the surface of objects in the line of sight from the antenna.
But these other concepts are not charge detecting concepts.
A ferrite antenna usually is used to tune a frequency in the VLF or MW range, similar to AM radio broadcasts.
Ferrites are not used for detecting static charges that we look for with a zahori.

4. Is it worth it to modify the original circuit?
It really depends on what is in this original circuit.
If you or Goldfinder can post a circuit diagram, I think some of the modifications can be done fairly easily. Others maybe not, but it really depends on what parts are in the circuit, and how they are connected.

If this is the original zahori circuit unmodified, there are some very interesting features in the cmos antenna-unloading switches and digital filter that could lead to some strange experiments with minor modifications.
Other later variants of the original design without these features do not have this opportunity. But these "interesting features" would be only for theory experiments, not for treasure hunting.


Best wishes, :)
J_P

[MIJ]

Hi J-P,

Thanks for your reply and answering all of my questions so well.

Goldfinder has said that he will try to find the original schematic for the detector.

Yes as you say it’s very sensitive to picking up static charge at small range, but I wonder if normal static charges are the same as ions given off by berried precious metals, as Goldfinder thinks that ions-charges have a unique signature.

Also Morgan told me that the Zahori needs low humidity 30% or less, this could be why it didn’t respond to my gold & silver berried in the garden.

Regards :)

[J_Player]

Hi J-P,

Thanks for your reply and answering all of my questions so well.

Goldfinder has said that he will try to find the original schematic for the detector.

Yes as you say it’s very sensitive to picking up static charge at small range, but I wonder if normal static charges are the same as ions given off by berried precious metals, as Goldfinder thinks that ions-charges have a unique signature.

Also Morgan told me that the Zahori needs low humidity 30% or less, this could be why it didn’t respond to my gold & silver berried in the garden.

Regards :)Hi MIJ,
Ions that are given off by buried metals would not happen if not for some chemicals near them that cause them to corrode.
These chemicals are organic acids or cyanide which is produced by microbes that like to eat metals to survive.
It seems weird, but it is true according to scientists who measured what is happening with buried metals.

These ions that are given off by buried metals never reach the surface of the earth because they become neutralized before they can reach from the depths of the metal that they came from to the surface of the earth.
These same scientists who measured the ionization of gold and silver also measured how they neutralize before they come up to the surface of the earth.
This is sad news for treasure hunters... unless you look farther to other consequences...

For example, what happens at the moment that these ions from a buried metal are neutralizing?
At that moment, there is an electric charge transfer from the ion to the compound that it attaches to.
This transfer of charge is insignificant... unless there are a lot of these ions doing the same thing at the same time.
But why would a lot of ions from corroding buried metal want to neutralize all at the same time?
There is no reason I can think of,,,, unless someone zaps the ground where these ions live with some RF energy.
That might do the job.

If someone was to zap the ground enough to cause a lot of the corroded metal ions to combine with other elements sooner than they naturally would combine, then I would expect to see a strong signal from these metal ions that shows they are becoming compounds. But this strong signal is not really a strong signal.... it is a weak signal which is only slightly stronger when you zap them.

In any case, it seems that buried metals might be able to send out a signal to tell where they are located if someone would zap them with a jolt of energy that is strong enough to get them moving faster than normal.


Best wishes, :)
J_P

[Fred]

I think Morgan has shown proof of a working LRL ;)

Morgan has shown the most interesting and genuine videos but i cannot qualify them of proof.

More generally, the problem that i can observe with LRL is that they work very, well but nobody knows for what.

[MIJ]

Morgan has shown the most interesting and genuine videos but i cannot qualify them of proof.

More generally, the problem that i can observe with LRL is that they work very, well but nobody knows for what.

Hi Fred,

You have seen many videos of Morgan’s tests with his PDK; you also have seen two videos of g-sani out testing the Crypton.

Now as far as I’m concerned if a detector can locate a metallic object buried in the ground from air at distance of 3 meters or more, then that is classed as a Long Range Locater in my book.

Also there have been several reports of coins located with the PDK.

Regards ;)

[hung]

Talking about long range locating finds, check this guy's video bellow. He's from state of Parana and found some diamonds with Mineoro's DIAS2005. The bigger one being 1.6Karats found at 600 feet and 7 feet deep.
Reaaaaally nice, eh?
Go to top of page to watch video.
https://www.facebook.com/MineoroIndustria?sk=wall

Before some muffin head accuse me of Mineoro propaganda, I am only posting the find. If it was with a coat hanger or NASA's latest nuclear powered spectrography rover scanner, would not change the fact that it was detected long range by a regular joe.

[Fred]

Hi MIJ,
Yes i have seen several interesting videos, but none of them showing unequivocally the detection of and UNKNOWN target and its recovery.
I saw many beeps, most random, some from causes that can be simply be the magnetic field, that that the mind unconsciously associate to a target when we know where it is.

Regards,
Fred

Hi Fred,

You have seen many videos of Morgan’s tests with his PDK; you also have seen two videos of g-sani out testing the Crypton.

Now as far as I’m concerned if a detector can locate a metallic object buried in the ground from air at distance of 3 meters or more, then that is classed as a Long Range Locater in my book.

Also there have been several reports of coins located with the PDK.

Regards ;)

[nikos]

TO GEO and WM6

Hi guys.
This is my first time in the forum and it seems to me that you two are the most helpful of all in this forum.
I have a few questions that I would like to ask you. Can any one of you people provide me with any help? If you can my e-mail is: nikos0817@gmail.com
I would be very thankful to you if you help me.
A few things about myself: I am new in this field but I have some technical background since
I am an M.I.T graduate in a different field ( astrophysics ).

Please get back to me when you can. Thanks. NIKOS

[WM6]

TO GEO and WM6

Hi guys.
This is my first time in the forum and it seems to me that you two are the most helpful of all in this forum.
I have a few questions that I would like to ask you. Can any one of you people provide me with any help? If you can my e-mail is: nikos0817@gmail.com
I would be very thankful to you if you help me.
A few things about myself: I am new in this field but I have some technical background since
I am an M.I.T graduate in a different field ( astrophysics ).

Please get back to me when you can. Thanks. NIKOS

Welcome Nikos.

I think here others most helpful people too, which are willing to help and cooperate.

You didn't mention what is your interest or problem?

[nikos]

To MW6

Good morning my friend. Since you have a lot of experience with electronics and having worked at ISKRA, I would like to ask you if you know if there is a way that would show me the direction of a treasure from a distance. I am asking your personal opinion as to IF that can be done,and if such a machine exists that actually works ( not just rumors ).
I am asking you these things on behalf of a good friend of mine who comes from Tashkent but doesn't speak much English. He has some information about a certain location and for the last 10 years he is obsessed with it. I want to help him either by telling him to go on searching or to give it up before he goes crazy.

[WM6]

To MW6

Good morning my friend. Since you have a lot of experience with electronics and having worked at ISKRA, I would like to ask you if you know if there is a way that would show me the direction of a treasure from a distance. I am asking your personal opinion as to IF that can be done,and if such a machine exists that actually works ( not just rumors ).
I am asking you these things on behalf of a good friend of mine who comes from Tashkent but doesn't speak much English. He has some information about a certain location and for the last 10 years he is obsessed with it. I want to help him either by telling him to go on searching or to give it up before he goes crazy.

Hi Nikos,

you ask most exciting and universal question between treasure hunters.

Personally I didn't saw any convincing proof that really working remote detecting device exist.

What we face today's in the field of remote detection are only fraudulent LRL from known scam producers or self-deceptive creations from LRL enthusiast.

This not mean that working LRL's are impossible. I believe that our LRL constructors as Geo, Morgan, J_P and others will find some solution for remote detecting. I am working on one remote detecting project too (hope to finish it this year). In case of end-success I will publish all project for free.

What is impossible is to detect single coin at 30 or 100m distance in soil. Such hype are scam only - go away from those fraudster to not lose your hard earned money.

[Fred]

I agree 100% with WM6 statement above :)

[nikos]

Dear GEO. Please send me your personal e-mail or telephone number so I can get in touch with you on a personal level.
My e-mail is:
nikos0817@gmail.com
THANKS
Harika gia thn apanthsh soy!

[goldfinder]

How good is it at detecting ghosts?

Yes - it will detect ghosts about as good as it detects gold :lol:
Goldfinder

[MIJ]

Hi MIJ,
It seems you found the same as what other builders of the Zahori found.
It detects charges in the air, but does not detect treasure.
You are able to detect the faintest of charges from combing your hair, or any other source of static charges.
But your buried gold and silver do not produce a static charge that you can detect.
But also remember that I have seen no example in this forum where an experimenter built the original Zahori design without modifying it in some way.
The original zahori circuit is a very sensitive static charge detector.
It is so sensitive that it has an electronic provision to drain any charge from the antenna 50 times a second to keep the charge from building up too strong where it could damage the semiconductor that is detecting the charge it collects.
It also has a sample and hold module which will remember what charge it detected while the antenna is being drained and preparing to take a new sample from the air.
Most of the projects I see people build have either deleted these features or modified them so they cannot work.
And I see many builders add on additional control knobs to make adjustments in the circuit that were not intended to be adjusted.
Nearly everyone who built the zahori, modified it, then after their modifications they say it does not work to detect treasure.

Of course, Esteban says it is possible to detect buried treasure using the Zahori.
It seems you have identified the question... how to make the Zahori detect treasure?
Some basic theory of detecting charges in the air:
If you are not drawing in air samples to check the charge of particles in the air, then the ability to detect a charge is related to the surface area of your charge collecting sensor.
This means a larger surface area will be exposed to a larger volume of air whereby it can collect a charge from the air.
But large plates or dishes are not desirable for a portable detector tool. So we have small versions as you see in the telescoping antenna.

A second principle is that when you are outdoors trying to detect a charge, you are grounded because you are standing on the ground.
The metal box you hold in your hand is also grounded by conduction through the saline liquid beneath your skin, so you can consider all your body and the metal zahori box to be connected to ground.
(This can change indoors, but we seldom go treasure hunting indoors).
Any charge in the air can be affected by your body moving through it, which brings a ground potential up to nearly 2m height to create an artificial ground in the air.
The part of your zahori that is not grounded is the antenna, which is insulated from the metal box.
The antenna will have whatever charge it pics up from the air around it.
Some of this charge will be from the negatively charged ground that you are conducting to the metal box.
But when the antenna is extended, the end away from you has penetrated through a voltage gradient to reach into the area where an air charge can be sampled.

It is as you say... the antenna can pick up charges from the sides as well as from the front. In fact, we expect it to pick up more charge from the sides than the front, because the surface is greater.
The front only has the diameter of the antenna (a few millimeters) while the sides have a surface that is over 3 times the diameter, over the length of the aerial.

We see some versions that show the antenna placed between two similar grounded antennas.
This greatly reduces the amount of charge that is collected, but it allows the small amount that is collected to become more directional.
This arrangement will collect more charge from the front, top and bottom where there is no grounded conductor so close as there is at the sides.
Another configuration is to place a grounded dish around the antenna so the antenna protrudes from the center of the dish.
This can have a focusing effect which causes negatively charged particles to congregate toward the antenna.
Of course, you could electronically charge this dish to become charged either positive or negative in order to repel particles that are charged oppositely.
(This is the principle of the Ivconic charge detector antenna designs).
But remember, neither Ivconic or any others who built the zahori or charge detectors with these kind of antennas ever located any buried treasure.

As far as modifications, there is a lot that can be done.
But in order to give advice for modifications, we would first need to know the circuit diagram.
This is because everyone builds different variations of the zahori.
We see even in the variations called "mini zahori", there are further modifications which nobody really shows the exact circuit diagram that is being used.

For your questions...
1. It is relatively easy to add on a buzzer circuit that can be adjusted to beep when the circuit finds a signal above a certain level.
This kind of circuit can be added as a separate add-on that does not influence any of the existing circuit in any way.

2. A different sensitivity knob is not needed except to add a knob along with the new buzzer circuit to set how strong the signal is before it beeps.

3. Antenna for more range detecting static anomalies begins with surface area.
But range of detection also includes directional properties.
When the optimum size is figured for an antenna that is not too bulky, then the next consideration is how to make it as directional as possible.
This approach is only for increasing the range at which you can locate a charge anomaly in the line of sight directions from the antenna.
There are other concepts of more range that are concerned with detecting other things than charges that are in the air or on the surface of objects in the line of sight from the antenna.
But these other concepts are not charge detecting concepts.
A ferrite antenna usually is used to tune a frequency in the VLF or MW range, similar to AM radio broadcasts.
Ferrites are not used for detecting static charges that we look for with a zahori.

4. Is it worth it to modify the original circuit?
It really depends on what is in this original circuit.
If you or Goldfinder can post a circuit diagram, I think some of the modifications can be done fairly easily. Others maybe not, but it really depends on what parts are in the circuit, and how they are connected.

If this is the original zahori circuit unmodified, there are some very interesting features in the cmos antenna-unloading switches and digital filter that could lead to some strange experiments with minor modifications.
Other later variants of the original design without these features do not have this opportunity. But these "interesting features" would be only for theory experiments, not for treasure hunting.


Best wishes, :)
J_P

Hi JP,

Goldfinder has sent me the schematic for the Zahori I bought from him please see attached image.

Regards

[J_Player]

Hi JP,

Goldfinder has sent me the schematic for the Zahori I bought from him please see attached image.

Regards Hi MIJ,
The circuit you show does not look anything similar to the Zahori you described above.
This schematic has a single field effect transistor with only 5 components and a meter. and a battery attached.
The images of the detector you showed have an adjustment pot, a switch, two 9v batteries, a trimpot on the board, 3 transistors, an IC, and a lot of capacitors and resistors that I don't see in the schematic.

This schematic is not a Zahori.
It is a simple charge detector with a meter connected, without any switches or control pots, or extra transistors.
Maybe there is an error in the schematic, or in the photos that you showed?

http://www.longrangelocators.com/forums/showthread.php?t=18457

http://www.longrangelocators.com/forums/attachment.php?attachmentid=17612&stc=1&d=1324064909

Best wishes, :)
J_P

[MIJ]

Hi JP,

No this is the one Goldfinder sent me “hummm maybe he is having some fun with me?�;)

I did think myself that it looked completely wrong.

Come on Goldfinder have you got the schematic?

Regards :)

[J_Player]

Hi JP,

No this is the one Goldfinder sent me “hummm maybe he is having some fun with me?”;)

I did think myself that it looked completely wrong.

Come on Goldfinder have you got the schematic?

Regards :)Hi MIJ,
From what I can see in your detector, it appears to be a basic charge detector that has provisions to keep the power supply extra stable.
Just guessing, I think it probably has a very high impedance transistor that is controlled by whatever charge is picked up on the antenna.
So when you get more charge, the transistor passes more current through it.
Then there are probably 1 or two more transistors that amplify this first transistor current strong enough to drive the meter so you can see how strong of a charge you found.

If this is the basic scheme, then I can think of one easy modification that could be useful.
If you need an audio beeping or an LED to light up when the signal rises above an adjustable setting, then this circuit could be added.
Of course, the utility of this kind of circuit will only free you from watching the meter while you are scanning for charges.
I suppose that could be worthwhile if you are planning to spend a lot of time using this detector.
This kind of beeper/LED circuit can be attached the same place or near to the meter in the circuit.
The beeper circuits can be made to consume very little power except for when they are beeping.
But we will need to know the voltages that are present in the circuit before any beeper is soldered in.
It is something that is better done by a technician who has the detector in his shop where he can take measurements to find the best way to wire it in.

Something else to consider is maybe you might want to investigate more about what does detecting charges in the air tell you about buried treasures.
From what I have seen in the Ivconic's negative ion detector thread and in this one, it appears that detecting charges in the air does not show you where treasures are buried.
The only exception is Esteban claims treasure can be found with the Zahori.
Yet everyone who built the zahori and other charge detectors say they find only charged things and power lines, but no treasure.

The other kinds of experimental locators we see are operating at VLF frequencies, similar to a radio.
These are not designed to collect charges from the air and display how much charge is collected.
A few people actually have shown some believable videos that these kinds of locators are doing something related to finding buried treasures.
If I were in your position, I would be thinking it will be good when Morgan comes to visit so you can see one of these in action and compare it to how you see your charge detector perform.
Hopefully you two will find some good relics in the places you know to go hunting.
Be sure to take a video camera so we can see what you find.

Meanwhile, I will see what I can do for your charge detector after we see the schematic.


Best wishes, :)
J_P

[haver]

Nikos wrote to me.My e-mail is :haver.alex@yahoo.com
.................................................. ............................Originally Posted by nikos http://www.longrangelocators.com/forums/images/buttons/viewpost.gif (http://www.longrangelocators.com/forums/showthread.php?p=141881#post141881)
TO GEO and WM6

Hi guys.
This is my first time in the forum and it seems to me that you two are the most helpful of all in this forum.
I have a few questions that I would like to ask you. Can any one of you people provide me with any help? If you can my e-mail is: nikos0817@gmail.com
I would be very thankful to you if you help me.
A few things about myself: I am new in this field but I have some technical background since
I am an M.I.T graduate in a different field ( astrophysics ).
.................................................. .................................................. Hi WM6.Hello Friend, await your answer whether you made ​​the device? I urgently need it, I'm sorry for bad english, I write through the translator.P.S.pomogi!!!

[J_Player]

Nikos wrote to me.My e-mail is :haver.alex@yahoo.com
.................................................. ............................Originally Posted by nikos http://www.longrangelocators.com/forums/images/buttons/viewpost.gif (http://www.longrangelocators.com/forums/showthread.php?p=141881#post141881)
TO GEO and WM6

Hi guys.
This is my first time in the forum and it seems to me that you two are the most helpful of all in this forum.
I have a few questions that I would like to ask you. Can any one of you people provide me with any help? If you can my e-mail is: nikos0817@gmail.com
I would be very thankful to you if you help me.
A few things about myself: I am new in this field but I have some technical background since
I am an M.I.T graduate in a different field ( astrophysics ).
.................................................. .................................................. Hi WM6.Hello Friend, await your answer whether you made ​​the device? I urgently need it, I'm sorry for bad english, I write through the translator.P.S.pomogi!!!

Hi haver,
It is hard for me to understand how you were able to graduate from MIT when you need to use a translator to understand English.
But it is even harder for me to understand why an MIT graduate would look for answers in the long range locators forum.

Can you give some information to help us understand how you were able to understand English well enough to graduate from MIT, and to tell the reason why you decided to come here to learn the answers that MIT Astrophysics department did not teach to you?


Best wishes, :)
J_P

[WM6]

Hi WM6.Hello Friend, await your answer whether you made ​​the device?



Which device? Did you mean zahori? No I never build zahori as electronic dowsing rod, but I build different static electricity sensor in past. No one for treasure hunting.

Zahori is electronic dowsing rod only. You need to be dowser to use it. I am not.

[nelson]

JUST TO SAY THAT WE MISS ESTEBAN, WHO IS I THINK, THE KING OF LRL.
I HOPE HE IS FINE AND BACK TO THE FORUM SOON



Zahori means the person with ability to find water with a rod.

Remember Carlos post only the schematic because three pages is heavy for the forum.

I repost in thread Confused on detecting noble metals at great distances...

http://thunting.com/geotech/forums/showthread.php?t=6664&highlight=ZAHORI

Read all the thread.

This schematic I have in Spanish, and always claim for the version in English. Maybe, nobody has here. This device was designed for to find water. In this German article (the original is the German magazine Elektor) assume that water in movement below the surface produce ionic interchanging. There are a Russian version about another title, a copy of original Elektor magazine of 1987 in the thread Remote Sensing Diagram:

http://thunting.com/geotech/forums/showthread.php?t=10601&highlight=ZAHORI

Original web page http://radiotech.by.ru/Shematic_PCB.../biolokator.htm
(doesn't work?)

Compare the both schematics, are the same! But the Russian has the title "Biolokator".

For to control a pronunciate arrives of ions, the 555 discharge the antenna. The article said that at major oscillation in 555, more sensitive is the device. The 15 nF cap is a kind of "memory", good quality requires here.

No synthetic clothes, no build in plastic.

At the end, the article saids that is possible to detect another type o field, include radiactivity (in theory).

I has done many modification for to convert simple and usable device.

Later modifications.

You can download complete Zahori article (include the Russian article) from:

http://www.mytempdir.com/686740

[WM6]

JUST TO SAY THAT WE MISS ESTEBAN, WHO IS I THINK, THE KING OF LRL.
I HOPE HE IS FINE AND BACK TO THE FORUM SOON

Me too. Any news, you are a little closer to him?

[Seden]

I too miss Esteban. I wish for him a speedy recovery! Come back Esteban.

Randy

[Morgan]

JUST TO SAY THAT WE MISS ESTEBAN, WHO IS I THINK, THE KING OF LRL.
I HOPE HE IS FINE AND BACK TO THE FORUM SOON

Of course Esteban is the Master of LRL´s,we all missing this person.
Unfortunatly when he was here,many people call him lier.

Hope he return very soon !

[WM6]

Unfortunatly when he was here,many people call him lier.



This was lovingly only.

[Geo]

Of course Esteban is the Master of LRL´s,we all missing this person.
Unfortunatly when he was here,many people call him lier.

Hope he return very soon !

Did you contacted with him lately;;;
How are his eyes;;

[Morgan]

Did you contacted with him lately;;;
How are his eyes;;

Hello geo

I heard from other person that he is missing the Geotech forum,unfortunatly his eyes recovering very slowly...We hope better days for Esteban.

Regards

[Geo]

I will try to call him on afternoon

[Seden]

Thanks Geo. Tell him Randy Seden from Simi Valley,California says hello.

[Geo]

Thanks Geo. Tell him Randy Seden from Simi Valley,California says hello.

OK....:)

[Geo]

I called Esteban but no answer. Maybe he was not home. I"ll try again

[nelson]

Hi Geo and thanks for keepping us informed about Esteban.
Will follow any news you can get from him.
Regards
Nelson


I called Esteban but no answer. Maybe he was not home. I"ll try again

[Geo]

Hi.
I just spoke with Esteban.
He is ok and as Morgan said his eyes recovered very slowly. The positive is that there is recovering so one day he will be again here with us.
You have his best wishes.

:):)

[nelson]

Its good to heard that Esteban is recovering and will be back soon
Thanks Geo

Hi.
I just spoke with Esteban.
He is ok and as Morgan said his eyes recovered very slowly. The positive is that there is recovering so one day he will be again here with us.
You have his best wishes.

:):)

[Seden]

Thank you Geo for the update. I pray Estebans eyes will recovery more quickly. He has been a real inspiration to us all.

[detectoman]

GOD put healt on our dear good friend esteban

[aft_72005]

Also , I hope health for Esteban .

[Sneshko]

All the best for Esteban!
Missing the forum.
Regards!
Sneshko

[Anwar2]

today I complit my ivconic Zahori and MiniZahori
the both device are working but the ivconic zahori only maks sound like tik tik tik but when ipush S2 buton Iheard ring noice..... Idont know how it works can some one help
and the mini zahori is working very nicely but still Idont know how it will work
or it will detect any treasure or kanz:lol:
ilike to who made this mini zahori to advise me how to detect the gold or treasure:D

[ayoni03]

hi esteban ,my english bad.I'm sorry.:frown:
I want to buying zahori.8)
please help me.
trona03@gmail.com

[reza vir]

Hello Friend
Zahori mini circuit of 3 potentiometers for what?
What is the connection 2n3819?

thanks to all

[WM6]

Hello Friend
Zahori mini circuit of 3 potentiometers for what?
What is the connection 2n3819?

thanks to all

Those 3 potentiometers are to manage stable work of circuit and sensitivity.

If you mean gate connection of 2n3819, it is connected to sensor in form of telescopic antenna inside reflector-formed ion router.

[reza vir]

thanks
1= 5K = ?
2= 47K = ? sens
3= 20K = ?

2n3819
D=?
S=?
G= Antena

[detectoman]

we await soon brodhy esteban he recovery complete eyes vision, FATHER GOD DO miracle amen amen

[Morgan]

we await soon brodhy esteban he recovery complete eyes vision, FATHER GOD DO miracle amen amen

We all hope a complete cure for Esteban and the return to this forum.

18630

[Geo]

We all hope a complete cure for Esteban and the return to this forum.

18630


I spoke with him before 3..4 weeks.
The problem remains serious :frown:

[Sneshko]

Esteban much lacking in the forum !!!
All the best wishes for Esteban
Sneshko

[detectoman]

FATHER GOD please put eyes healt to our dear lrlsta esteban, amen y amen

[Tim Williams]

Yes all the best for Esteban. Speedy recovery.

[Nicolas]

I wish good health for Esteban

[Nicolas]

Hi morgan

In this video you can show the ion chamber maybe like Mineoro :lol:

http://www.youtube.com/watch?v=DtQ746MPrNs


http://www.youtube.com/watch?v=tX4FC-Xcg9w


http://www.youtube.com/watch?v=snNwE6txxP0

Good wish for all

[okantex]

Hi Everybody ,

Nicolas , where are the 2nd and 3th videos realted to first link?. (http://polyestersepet.blogspot.com)

[detectoman]

hello brodhy okantek, the other videos you like want, these you can see open the youtube page, this have total 115 videos aditional of same autor here is the other videos inside, best regards

[Nicolas]

Hi all

I put here Mini Zahori + Modif

[iron1944]

DEAR NİCOLAS:
Can you let me weigh?
Zahori + modifi of the circuit PCB board forum put here.
antenna will be like?
ferrite?
Telescopic?
One coil?
Thank you.

[iron1944]

Mr. Nicolas.
Large master.
I'm still waiting for your reply to Zahori + modif.
Thank you.

[Nicolas]

Mr. Nicolas.
Large master.
I'm still waiting for your reply to Zahori + modif.
Thank you.

Hi my dear the Zahori LRL is not my project is for Estebetien and Morgan and Geo

Please read since first comment you can understand.

we will not respond to each person alone. should read the whole topic and if you do not find the information. everyone here will help.

Good luck

[iron1944]

Mr. Nicolas
GREAT MASTERS.
Can you help me?
THE RECEIVER CIRCUIT schematic of ZáhorÃ* + Modified could you put FORUM SECTION
THANK YOU in advance for his answer.
THANK YOU...

[nelson]

Hi Geo

Since last time we know from you about Esteban, do you have any extra news about his health?
regards
Nelson


Hi.
I just spoke with Esteban.
He is ok and as Morgan said his eyes recovered very slowly. The positive is that there is recovering so one day he will be again here with us.
You have his best wishes.

:):)

[Qiaozhi]

Mr. Nicolas
GREAT MASTERS.
Can you help me?
THE RECEIVER CIRCUIT schematic of ZáhorÃ* + Modified could you put FORUM SECTION
THANK YOU in advance for his answer.
THANK YOU...
Here's the original Zahori article.

[king40]

Here's the original Zahori article.
hi Qiaozhi
you test orginal zahori?
its working?

[Qiaozhi]

hi Qiaozhi
you test orginal zahori?
its working?
No, I have not tested the Zahori, but several others here have built copies.
This was an interesting idea that was published in Elektor, and I translated it into English for other members here.
I've attached the English translation.

[king40]

thanks
zahori detect water!!!
or for silver ... gold??

[WM6]

zahori detect water!!!
or for silver ... gold??

If it can, no gold will be left for you.

[king40]

If it can, no gold will be left for you.
interesting :lol:

[reza vir]

hi morgan and nicolas :)
My circuit operates correctly or is it working? :nerd:
http://s5.picofile.com/file/8119838584/video_test_zahory.3gp.html

Thanks and regards

[khuben]

Me too. Any news, you are a little closer to him?

I did this Zahiri and I was pleasantly surprised to work. Then I tried several times to do it but it did not work. I think the reason is in 4066.
At the first project I used an old brown scheme, from the first where at the entrance there are no protection from static electricity. I can not find such a scheme.
Someone to Share Your Experience!
Good luck in the ventures!

[HaFar2010]

Hello
Dear All

Does anyone have the Inside of metal detectors, First Edition?

[khuben]

Hello
Dear All

Does anyone have the Inside of metal detectors, First Edition?

Maybe there is, but I do not know in which brand and model metal detector

sorry :)

[Qiaozhi]

Hello
Dear All

Does anyone have the Inside of metal detectors, First Edition?
The first edition of ITMD is sold out. You will have to look for a secondhand copy, or buy the second edition from Amazon.

[Geo]

So for information, do you remember how many copies did the book sell in the first edition?

[Qiaozhi]

So for information, do you remember how many copies did the book sell in the first edition?
We had 1,000 copies printed, and they've all gone.
I'm not sure where we are with Edition 2 at the moment.