CXC.Ob CRE IEEE,AOVEy BEXFV requires a very large number of training instances to cover planes,each of which is a feature map.A unit in a feature the space of possible variations.In convolutional networks. map has I 5 inputs connected to a 5 by 5 area in the input, described below,shift invariance is automatically obtained called the receptave rel of the unit.Each unit has 15 in- by forcing the replication of weight configurations across puts,and therefore I5 tiainable coefficients plus a trainable space. bias.The receptive fields of contiguous units in a feature Secondly,a deficiency of fully-connected architectures is map are centered on correspondingly contiguous units in that the topology of the input is entirely ignored.The in-the previous layer.Therefore receptive fields of neighbor- put variables can be presented in any(fixed)order without ing units overlap.For example,in the first hidden layer affecting the outcome of the training.On the contrary, of veNet-5,the receptive fields of horizontally contiguous images (or time-frequency representations of speech)have units overlap by t columns and 5 rows.As stated earlier, a strong ID local structure:variables (or pixels)that are all the units in a feature map share the same set of 15 spatially or temporally nearby are highly correlated.vocal weights and the same bias so they detect the same feature correlations are the reasons for the well-known advantages at all possible locations on the input.The other feature of extracting and combining local features before recogniz- maps in the layer use different sets of weights and biases, ing spatial or temporal objects,because configurations of thereby extracting different types of local features.In the neighboring variables can be classified into a small number case of veNet-5,at each input location six different types of categories (e.g.edges,corners...).Convolutsonal Net- of features are extracted by six units in identical locations works force the extraction of local features by restricting in the six feature maps.A sequential implementation of the receptive fields of hidden units to be local. a feature map would scan the input image with a single unit that has a local receptive field,and store the states B.Convolutgonal Networks of this unit at corresponding locations in the feature map. Convolutional Networks combine three architectural This operation is equivalent to a convolution,followed by ideas to ensure some degree of shift,scale,and distor- an additive bias and squashing function,hence the name tion invariance:local receptge rel s,share wegghts (or convolutgonal network.The kernel of the convolution is the weight replication),and spatial or temporal ab-s amplang. set of connection weights used by the units in the feature A typical convolutional network for recognizing characters, map.An interesting property of convolutional layers is that dubbed veNet-5,is shown in figure I.The input plane if the input image is shifted,the feature map output will receives images of characters that are approximately size- be shifted by the same amount,but will be left unchanged normalized and centered.Each unit in a layer receives in- otherwise.This property is at the basis of the robustness puts from a set of units located in a small neighborhood of convolutional networks to shifts and distortions of the in the previous layer.The idea of connecting units to local input. receptive fields on the input goes back to the Perceptron in Once a feature has been detected.its exact location the early 60s,and was almost simultaneous with Hubel and becomes less important.Only its approximate position Wiesel's discovery of locally-sensitive,orientation-selective relative to other features is relevant.For example,once neurons in the cat's visual system.].vocal connections we know that the input image contains the endpoint of a have been used many times in neural models of visual learn- roughly horizontal segment in the upper left area,a corner ingBl,1,F],.I].With local receptive in the upper right area,and the endpoint of a roughly ver- fields,neurons can extract elementary visual features such tical segment in the lower portion of the image,we can tell as oriented edges,end-points,corners (or similar features in the input image is a 7.Not only is the precise position of other signals such as speech spectrograms).These features each of those features irrelevant for identifying the pattern, are then combined by the subsequent layers in order to de- it is potentially harmful because the positions are likely to tect higher-order features.As stated earlier,distortions or vary for different instances of the character.A simple way shifts of the input can cause the position of salient features to reduce the precision with which the position of distinc- to vary.In addition,elementary feature detectors that are tive features are encoded in a feature map is to reduce the useful on one part of the image are likely to be useful across spatial resolution of the feature map.This can be achieved the entire image.This knowledge can be applied by forcing with a so-called sub-samplang layers which performs a local a set of units,whose receptive fields are located at different averaging and a sub-sampling,reducing the resolution of places on the image,to have identical weight vectors.Bl, the feature map,and reducing the sensitivity of the output 15],t Units in a layer are organized in planes within to shifts and distortions.The second hidden layer of veNet- which all the units share the same set of weights.The set 5 is a sub-sampling layer.This layer comprises six feature of outputs of the units in such a plane is called a feature maps,one for each feature map in the previous layer.The map.Units in a feature map are all constrained to per- receptive field of each unit is a i by I area in the previous form the same operation on different parts of the image. layer's corresponding feature map.Each unit computes the A complete convolutional layer is composed of several fea-average of its four inputs,multiplies it by a trainable coef- ture maps (with different weight vectors),so that multiple ficient,adds a trainable bias,and passes the result through features can be extracted at each location.A concrete ex- a sigmoid function.Contiguous units have non-overlapping ample of this is the first layer of yeNet-5 shown in Figure I. contiguous receptive fields.Consequently,a sub-sampling Units in the first hidden layer of veNet-5 are organized in 6 layer feature map has half the number of rows and columns￾✂✁☎✄✝✆✟✞✠✄☛✡✌☞✎✍✟✏✒✑✓✏✂✏✂✏✎✔✖✕☛✄☎✗☛✏✙✘✛✚✙✏✂✁✢✜✤✣✥✣✧✦ ￾ ä✥ï✒➍✐ÿ✙ø➀ä✧ï❞ê✇å❭ú➈ï✖ä❺✘➻û✓å➄ä❘✂➈ï♣é✐ÿ☎î➉✡◆ï➊ä✛ì➄ë❇è✧ä❿å➄ø➀é✙ø➑é✗✂❙ø➀é☎ê✤è✥å➄é✥￾❶ï✖ê✇è✥ì➚￾➊ì✠ú➈ï➊ä è✧ç☎ï➔ê✤æ☎å➎￾❶ï❨ì➈ë✎æ◆ì❛ê✥ê✤ø✠✡✙û➀ï❨úrå➈ä✧ø✓å✠è✥ø➑ì❛é☎ê✖ð❀➏➠é➵￾❶ì❛é✐ú❛ì➈û➀ÿ✂è✧ø➀ì➈é✎å➄û➇é✙ï❶è④ó➵ì➈ä✥ô✂ê✄➌ ù✂ï❞ê❺￾➊ä✧ø✠✡✎ï❞ù➵✡◆ï➊û➀ì✠ó✌➌➇ê✧ç✙ø➑ë➺è➵ø➀é➇ú✠å➄ä✥ø➀å➈é✗￾❶ï➔ø✓ê➵å➄ÿ✂è✥ì➈î➓å✠è✥ø✠￾✖å➄û➀û✙✘➻ì✑✡✙è✥å➄ø➀é✙ï❞ù ✡☛✘➷ëíì➈ä✴￾❶ø➀é❼✂➲è✥ç✙ï✿ä✧ï✖æ✙û➑ø✁￾➊å➄è✧ø➀ì➈é ì➈ë➉ó➵ï➊ø✠✂➈ç✐è➚￾➊ì➈é✦➞✗✂❛ÿ✙ä❿å✠è✧ø➀ì➈é✎ê✒å✑￾➊ä✧ì✐ê✧ê ê✧æ☎å✑￾➊ï➈ð þ➇ï✒￾➊ì➈é☎ù✂û✠✘✑➌✙å➻ù✂ï✄➞✥￾❶ø➀ï➊é✥￾❯✘➽ì➈ë❀ëíÿ✙û➀û✙✘❩✝r￾❶ì❛é✙é✙ï✒￾❶è✧ï❞ù✢å➈ä❘￾❿ç✙ø➑è✧ï★￾↔è✥ÿ✙ä✧ï❞ê❫ø✓ê è✧ç✎å✠è➔è✥ç✙ï✌è✧ì❛æ✎ì❛û➑ì➎✂✑✘➽ì➈ë❦è✧ç✙ï➞ø➀é✙æ✙ÿ✙è➉ø➀ê➔ï➊é✐è✧ø➀ä✧ï✖û✙✘✢ø✙✂❛é✙ì➈ä✥ï✖ù✝ð✇ã✛ç✙ï✌ø➀é✦✝ æ✙ÿ✂è✇úrå➈ä✧ø✓å❄✡☎û➑ï❞ê❷￾➊å➄é➝✡◆ï➔æ✙ä✥ï✖ê✧ï➊é✐è✧ï❞ù❭ø➑é➓å➄é☛✘➐➪●➞❼↔✂ï✖ù✥➶❦ì➈ä❿ù✂ï➊ä❣ó❨ø➑è✧ç☎ì➈ÿ✂è å♦➘✟ï✒￾❶è✧ø➀é❼✂ è✥ç✙ï❖ì❛ÿ✂è❘￾➊ì➈î➻ï➲ì➄ë➤è✥ç✙ï➲è✥ä✥å➈ø➑é✙ø➀é❼✂✎ðòý♣é➘è✥ç✙ï➛￾➊ì➈é✐è✧ä❿å➄ä❘✘✑➌ ø➀î➻å✑✂➈ï❞ê➉➪íì❛ä➔è✥ø➑î➻ï❯✝♠ëíä✥ï✒➍✐ÿ✙ï➊é✥￾❯✘✿ä✧ï✖æ✙ä✧ï❞ê✤ï✖é✐è✥å✠è✥ø➑ì❛é☎ê✛ì➄ë❫ê✧æ◆ï➊ï✒￾❿ç✈➶✛ç☎årú➈ï å✿ê④è✥ä✧ì❛é❼✂✳✑✑✧▲û➑ì✦￾➊å➈û❯ê✤è✧ä✥ÿ✗￾❶è✧ÿ✙ä✥ï✻✰♣úrå➈ä✧ø✓å❄✡☎û➑ï❞ê➑➪⑨ì➈ä➤æ✙ø✙↔➇ï✖û➀ê✴➶➉è✧ç☎å➄è➤å➈ä✧ï ê✧æ☎å✠è✥ø➀å➈û➑û✠✘✒ì❛ä❣è✧ï✖î❭æ◆ì➈ä❿å➄û➀û✠✘❙é✙ï❞å➄ä❘✡☛✘✒å➄ä✥ï❨ç✙ø✠✂➈ç✙û✠✘➚￾➊ì➈ä✥ä✧ï✖û➀å➄è✧ï❞ù☛ð ✗❀ì☛￾✖å➄û ￾❶ì❛ä✧ä✥ï➊û✓å✠è✥ø➑ì❛é☎ê❫å➈ä✧ï♣è✧ç☎ï➳ä✥ï✖å❛ê✤ì❛é☎ê❫ëíì➈ä➵è✧ç✙ï➤ó➵ï➊û➀û➟✝⑥ô➇é✙ì✠ó❨é✶å❛ù✂ú✠å➄é✐è✥å✑✂➈ï✖ê ì➄ë❯ï❯↔➇è✧ä❿å✑￾❶è✧ø➀é❼✂➻å➄é☎ù➙￾❶ì➈î➑✡✙ø➀é✙ø➑é✗✂ ✲✙➯✒❄✴➢✲✐ëíï✖å➄è✧ÿ✙ä✥ï✖ê✔✡◆ï❶ëíì❛ä✧ï➳ä✥ï✒￾❶ì➎✂➈é✙ø✠➽❯✝ ø➀é❼✂✫ê✤æ☎å➄è✧ø✓å➄û❣ì❛ä➤è✧ï➊î➻æ◆ì➈ä❿å➄û❣ì➎✡✔✓④ï✒￾❶è✥ê✒➌✏✡✎ï★￾➊å➈ÿ☎ê✤ï➵￾➊ì➈é✦➞✗✂❛ÿ✙ä❿å✠è✧ø➀ì➈é✎ê➉ì➈ë é✙ï✖ø✙✂❛ç❩✡◆ì➈ä✥ø➀é❼✂✌ú✠å➄ä✥ø➀å✑✡✙û➑ï❞ê❹￾➊å➈é➣✡◆ï✬￾❶û✓å➈ê✥ê✤ø✙➞☎ï❞ù➻ø➑é✐è✧ì❙å➞ê✤î➓å➈û➑û✎é✐ÿ☎î➉✡◆ï➊ä ì➄ë✞￾➊å✠è✥ï✄✂❛ì➈ä✥ø➑ï❞ê➙➪⑨ï➈ð ✂☎ð ï✖ù❼✂➈ï✖ê✒➌➜￾➊ì➈ä✥é✙ï➊ä❿ê➊ð➀ð➀ð ➶❶ð ❃ ➯❄➨✍♦➯ ✲✡✦➺❩✣ ➯♦➨✇➢✲➜➸➑➳❯➺❩✭ ➻➜➯♦➡❺➼♦➩➤ëíì➈ä✴￾❶ï➓è✥ç✙ï✶ï✄↔➇è✧ä❿å✑￾↔è✥ø➑ì❛é➷ì➄ë➔û➀ì☛￾✖å➄û❣ëíï❞å✠è✥ÿ✙ä✧ï❞ê➓✡☛✘ ä✧ï❞ê④è✥ä✧ø✁￾↔è✥ø➑é❼✂ è✧ç☎ï✌ä✧ï★￾❶ï➊æ✙è✧ø➀ú➈ï✞➞☎ï➊û✓ù✙ê❨ì➈ë❇ç✙ø✓ù✙ù✂ï✖é✺ÿ✙é✙ø➑è✥ê✛è✥ì➵✡✎ï✌û➀ì✦￾➊å➄û♠ð ✚✜✛ ❃ ➯♦➨☎✍✪➯✬✲✡✦➺✮✣ ➯❄➨✈➢✬✲✈➸➉➳✄➺✶➻➜➯♦➡❺➼♦➩ ☞✇ì➈é➇ú➈ì❛û➑ÿ✂è✥ø➑ì❛é☎å➄û➘ñ➔ï➊è④ó✇ì❛ä✧ô✂ê ￾❶ì❛î➉✡✙ø➀é✙ïPè✧ç✙ä✥ï➊ï å➄ä✴￾❿ç✙ø➑è✧ï✒￾❶è✧ÿ✙ä❿å➄û ø✓ù✂ï✖å❛ê✺è✧ì✻ï✖é☎ê✧ÿ✙ä✧ï ê✧ì➈î➻ï ù✂ï✒✂➈ä✥ï➊ï ì➈ë➓ê✧ç✙ø➑ë➺è✒➌✒ê❘￾➊å➈û➑ï➎➌✒å➄é✎ù❲ù✙ø➀ê✤è✧ì❛ä❇✝ è✧ø➀ì➈é✾ø➑é➇ú✠å➄ä✥ø✓å➄é✗￾➊ï✻✰ ✲✙➯✒❄✴➢✲t➡❺➳❄✴➳❖➤✇➺✮✣✍♦➳✂✁✎➳✡✲❨✪♦➩✹➌➉➩❺➥❼➢❄➡❺➳✱✪ ➻➜➳❪✣✥★➥✦➺➩➛➪⑨ì➈ä ó➵ï➊ø✠✂➈ç✐è➉ä✥ï➊æ✙û➀ø✠￾✖å✠è✥ø➑ì❛é✥➶✹➌✟å➄é☎ù✫ê✧æ☎å➄è✧ø✓å➄û❀ì❛ä❨è✧ï✖î➻æ✎ì❛ä✥å➈û❹➩✒✡✤✯✡✭❖➩✄➢❄➲✛➤ ✲✣●➨✵✥➈ð ✕➘è❅✘➇æ✙ø✁￾➊å➈û❼￾❶ì➈é➇ú❛ì➈û➀ÿ✂è✧ø➀ì➈é☎å➈û✂é✙ï❶è④ó➵ì➈ä✥ô➤ëíì➈ä❫ä✧ï★￾❶ì✑✂❛é✙ø✠➽➊ø➀é❼✂✞￾❿ç✎å➄ä❿å✑￾↔è✥ï➊ä❿ê✄➌ ù✂ÿ❼✡✗✡✎ï❞ù ✗✝ï❞ñ➔ï❶è❺✝✝✙❼➌✛ø➀ê➽ê✧ç✙ì✠ó❨é➘ø➀é ➞✗✂➈ÿ✙ä✥ï ✑✂ð ã✛ç✙ï➲ø➀é✙æ✙ÿ✙è✶æ✙û✓å➄é✙ï ä✥ï✒￾❶ï✖ø➑ú❛ï✖ê♣ø➑î➓å✑✂➈ï✖ê➉ì➄ë➃￾❿ç✎å➄ä❿å✑￾↔è✥ï➊ä❿ê❨è✥ç☎å✠è✌å➄ä✥ï❙å➈æ✙æ✙ä✥ì✪↔➇ø➀î➓å✠è✥ï➊û✠✘✿ê✧ø✙➽✖ï❯✝ é✙ì❛ä✧î➓å➄û➀ø✠➽➊ï✖ù✺å➈é☎ù✆￾❶ï✖é❛è✥ï➊ä✥ï✖ù☛ð ✭❫å➎￾❿ç✺ÿ✙é✙ø➑è➉ø➑é➲å➽û➀å✪✘❛ï➊ä❨ä✥ï✒￾❶ï✖ø➑ú❛ï✖ê✛ø➀é✦✝ æ✙ÿ✂è❿ê➞ëíä✥ì➈î å➲ê✧ï❶è✒ì➈ë✛ÿ☎é✙ø➩è❿ê✒û➀ì✦￾➊å➄è✧ï✖ù➷ø➀é å➲ê✧î➓å➄û➀û➏é✙ï➊ø✠✂➈ç☛✡◆ì➈ä✥ç✙ì➇ì✂ù ø➀é➓è✧ç✙ï➳æ✙ä✥ï➊ú➇ø➀ì➈ÿ☎ê❫û➀å✪✘❛ï➊ä❞ð❇ã✛ç✙ï♣ø➀ù✂ï❞å➞ì➈ë❀￾❶ì➈é☎é✙ï✒￾❶è✧ø➀é❼✂➞ÿ✙é✙ø➑è✥ê✇è✥ì✒û➀ì☛￾✖å➄û ä✥ï✒￾❶ï✖æ✂è✧ø➀ú➈ï✔➞✎ï➊û✓ù✙ê❣ì➈é❭è✥ç✙ï❨ø➑é☎æ✙ÿ✂è➜✂❛ì✐ï❞ê❷✡☎å➎￾❿ô✌è✧ì➤è✥ç✙ï✬✓❦ï➊ä✴￾❶ï✖æ✂è✧ä✥ì➈é❙ø➑é è✧ç☎ï➵ï❞å➄ä✥û✙✘ ✓✗✘➈ê✒➌➄å➄é☎ù✒ó➵å❛ê❇å➈û➑î➻ì❛ê✤è❣ê✤ø➀î✒ÿ✙û➑è✥å➈é✙ï➊ì❛ÿ☎ê❇ó❨ø➩è✥ç❭õ➉ÿ❼✡✎ï✖û✙å➄é☎ù ✎ø➀ï✖ê✧ï➊û ❁ ê✛ù✂ø✓ê❺￾➊ì✠ú➈ï✖ä❺✘❭ì➄ë❯û➑ì✦￾➊å➈û➑û✠✘❩✝⑥ê✧ï➊é✎ê✤ø➑è✧ø➀ú➈ï➎➌❛ì❛ä✧ø➀ï➊é✐è✥å➄è✧ø➀ì➈é✦✝➠ê✧ï➊û➀ï✒￾↔è✥ø➑ú❛ï é✙ï✖ÿ✙ä✧ì❛é☎ê➔ø➀é✫è✥ç✙ï➑￾✖å✠è✽❁ ê♣ú✐ø✓ê✧ÿ☎å➄û❯ê❇✘✂ê✤è✧ï➊î ✞❜✻✘✠⑥ð❇✗❀ì☛￾✖å➄û❜￾❶ì➈é☎é✙ï✒￾❶è✧ø➀ì➈é☎ê ç☎årú❛ï❷✡✎ï✖ï➊é➞ÿ☎ê✧ï✖ù➤î➓å➈é❩✘♣è✧ø➀î➻ï✖ê❇ø➑é✌é☎ï➊ÿ✙ä❿å➄û❛î❭ì✂ù✂ï✖û➀ê❀ì➄ë✙ú➇ø✓ê✤ÿ☎å➈û➄û➀ï✖å➄ä✥é✦✝ ø➀é❼✂✷✞❜✗➾✡✠❖➌❵✞❜✵✑✆✠❖➌❵✞➟➾✒✺✠❖➌ ✞❜ ❜✠❖➌❵✞❜✫❝✬✠❖➌❵✞✑ ✠♠ð ✎ø➩è✥ç û➑ì✦￾➊å➈û➞ä✥ï✒￾❶ï✖æ✂è✧ø➀ú➈ï ➞☎ï✖û➀ù✙ê✒➌✙é✙ï✖ÿ✙ä✥ì➈é☎ê✔￾➊å➈é✢ï✄↔➇è✧ä❿å✑￾↔è✛ï➊û➀ï➊î➻ï✖é❛è❿å➄ä❘✘➓ú➇ø➀ê✧ÿ☎å➄û✟ëíï❞å✠è✥ÿ✙ä✧ï❞ê❨ê✤ÿ✥￾❿ç å➈ê❀ì➈ä✥ø➑ï✖é✐è✧ï✖ù➤ï❞ù✦✂➈ï❞ê✄➌rï✖é☎ù☛✝⑥æ✎ì❛ø➑é✐è✥ê✒➌♦￾❶ì❛ä✧é✙ï✖ä✥ê➜➪íì➈ä❦ê✧ø➑î➻ø➀û➀å➈ä✝ëíï✖å➄è✧ÿ✙ä✥ï✖ê❀ø➑é ì➄è✥ç✙ï➊ä➵ê✤ø✠✂➈é✎å➄û✓ê➏ê✤ÿ✥￾❿ç➽å➈ê❫ê✧æ◆ï➊ï✒￾❿ç➽ê✧æ◆ï✒￾↔è✥ä✧ì➎✂➈ä❿å➄î➓ê✴➶↔ð❇ã✛ç☎ï✖ê✧ï❨ëíï✖å➄è✧ÿ✙ä✥ï✖ê å➄ä✥ï❨è✥ç✙ï➊é ￾➊ì➈î➑✡✙ø➑é☎ï✖ù➝✡☛✘❭è✧ç✙ï➳ê✤ÿ❼✡✎ê✤ï★➍❛ÿ☎ï➊é✐è❫û✓å✪✘➈ï➊ä❿ê❣ø➀é➽ì➈ä❿ù✂ï✖ä❣è✧ì✒ù✙ï❯✝ è✧ï★￾↔è➔ç✙ø✠✂➈ç☎ï➊ä❺✝♠ì❛ä✥ù✂ï✖ä➏ëíï❞å✠è✧ÿ☎ä✧ï❞ê➊ð❷✕➉ê❨ê✤è✥å➄è✧ï❞ù✶ï❞å➄ä✥û➑ø➀ï➊ä★➌✂ù✂ø➀ê✤è✧ì❛ä✤è✥ø➑ì❛é☎ê➵ì➈ä ê✧ç✙ø➩ë➺è❿ê➏ì➈ë◆è✥ç✙ï➔ø➀é✙æ✙ÿ✂è✎￾➊å➄é➣￾✖å➄ÿ☎ê✧ï✛è✧ç☎ï➔æ✎ì✐ê✤ø➑è✧ø➀ì➈é➻ì➈ë☛ê✥å➄û➀ø➀ï➊é✐è❣ëíï✖å➄è✧ÿ✙ä✥ï✖ê è✧ì➻ú✠å➄ä❘✘➈ð❨➏➠é✺å➈ù✙ù✙ø➩è✥ø➑ì❛é✏➌✙ï➊û➀ï➊î➻ï✖é❛è❿å➄ä❘✘➻ëíï✖å➄è✧ÿ✙ä✥ï➳ù✙ï❶è✧ï★￾↔è✥ì➈ä❿ê➵è✧ç☎å➄è❨å➈ä✧ï ÿ☎ê✧ï❶ëíÿ✙û✂ì❛é➞ì➈é☎ï✇æ☎å➈ä✤è❦ì➄ë☎è✧ç✙ï➵ø➑î➓å✑✂➈ï✛å➄ä✥ï❫û➀ø➑ô❛ï➊û✠✘♣è✥ì④✡◆ï✛ÿ☎ê✧ï❶ëíÿ✙û✂å✑￾➊ä✧ì✐ê✧ê è✧ç☎ï❨ï➊é✐è✧ø➀ä✧ï✛ø➀î➓å❄✂➈ï❛ð❇ã✛ç✙ø✓ê❦ô➇é✙ì✠ó❨û➀ï✖ù✦✂❛ï✎￾✖å➄é➚✡✎ï➔å➈æ✙æ✙û➀ø➑ï❞ù➉✡☛✘✌ëíì❛ä❘￾➊ø➑é❼✂ å➤ê✤ï➊è➏ì➄ë✟ÿ✙é✙ø➑è✥ê✒➌➈ó❨ç✙ì✐ê✤ï✛ä✥ï✒￾➊ï➊æ✂è✥ø➑ú❛ï➃➞✎ï➊û✓ù✙ê➏å➄ä✥ï➵û➑ì✦￾➊å➄è✧ï❞ù❭å➄è➏ù✂ø➟➘✟ï➊ä✥ï➊é✐è æ✙û✓å✑￾➊ï✖ê➔ì❛é✫è✧ç☎ï❙ø➀î➓å❄✂➈ï➎➌☎è✥ì➽ç☎årú❛ï➞ø➀ù✙ï➊é✐è✧ø✁￾➊å➈û❇ó➵ï➊ø✠✂➈ç✐è➉ú❛ï✒￾↔è✥ì➈ä❿ê ✞❜ ✑ ✠✶➌ ✞✙➾ ✙✆✠❖➌ ✞❜✬❝✫✠♠ð➵→➔é☎ø➩è❿ê✌ø➑é➷å✿û➀å✪✘❛ï➊ä✌å➄ä✥ï❭ì➈ä❘✂❛å➄é☎ø✙➽✖ï✖ù➲ø➀é➷æ✙û✓å➄é✙ï❞ê➤ó❨ø➩è✥ç✙ø➑é ó❨ç✙ø✁￾❿ç➲å➄û➀û☛è✧ç☎ï✒ÿ✙é✙ø➑è✥ê♣ê✤ç✎å➄ä✥ï➤è✧ç✙ï✒ê✥å➄î➻ï➞ê✧ï❶è➉ì➈ë❣ó✇ï✖ø✙✂❛ç❛è❿ê➊ð➵ã✛ç✙ï✒ê✧ï❶è ì➄ë✛ì➈ÿ✙è✧æ✙ÿ✂è❿ê✌ì➄ë➵è✧ç☎ï➓ÿ✙é✙ø➑è✥ê✌ø➀é ê✤ÿ✗￾❿ç å✿æ✙û✓å➄é✙ï➓ø✓ê✌￾➊å➈û➑û➀ï✖ù➷å➝➫❯➳✴➢♦➺✡✦➡❺➳ ➲➵➢❘➤◆ð⑧→➔é✙ø➑è✥ê➻ø➀é❑å❖ëíï✖å➄è✧ÿ✙ä✥ï✢î➓å➈æ❑å➄ä✥ï✢å➈û➑û✩￾➊ì➈é☎ê✤è✧ä❿å➄ø➀é✙ï✖ù è✧ì æ✎ï✖ä❇✝ ëíì➈ä✥î è✧ç✙ï✿ê✧å➈î➻ï➽ì➈æ◆ï➊ä❿å✠è✥ø➑ì❛é ì➈é❤ù✂ø✙➘✟ï➊ä✥ï➊é✐è❙æ☎å➈ä✤è❿ê➞ì➈ë❨è✧ç✙ï✢ø➑î➓å❄✂❛ï➈ð ✕ ￾❶ì❛î➻æ✙û➑ï➊è✧ï✌￾❶ì❛é➇ú➈ì➈û➀ÿ✂è✥ø➑ì❛é☎å➄û✟û✓å✪✘➈ï➊ä✛ø✓ê✩￾❶ì❛î❭æ◆ì❛ê✧ï✖ù✢ì➄ë❦ê✤ï✖ú➈ï✖ä✥å➈û✎ëíï❞å♦✝ è✧ÿ☎ä✧ï➤î➓å➄æ☎êt➪⑨ó❨ø➩è✥ç✿ù✂ø✙➘✟ï➊ä✥ï➊é✐è❨ó✇ï✖ø✙✂❛ç❛è➵ú➈ï★￾↔è✧ì❛ä✥ê✴➶✹➌✂ê✧ì✒è✥ç☎å✠è❨î❙ÿ✙û➩è✥ø➑æ☎û➑ï ëíï✖å➄è✧ÿ✙ä✥ï✖ê✬￾➊å➄é✫✡◆ï✌ï❯↔➇è✧ä❿å✑￾❶è✧ï❞ù✿å➄è➔ï✖å➎￾❿ç✢û➀ì✦￾➊å✠è✥ø➑ì❛é✝ð➜✕ ￾➊ì➈é✗￾➊ä✧ï➊è✧ï✌ï❯↔☛✝ å➄î➻æ✙û➀ï➵ì➄ë☎è✥ç✙ø✓ê❦ø➀ê❇è✧ç☎ï➃➞✎ä✥ê✤è❯û✓å✪✘➈ï✖ä❇ì➈ë✴✗✝ï❞ñ➔ï➊è❇✝ ✙➉ê✧ç✙ì✠ó❨é✒ø➀é➝✜❇ø✠✂➈ÿ☎ä✧ï❙✑✂ð →➔é☎ø➩è❿ê❣ø➑é❭è✥ç✙ï✎➞☎ä✥ê✤è❣ç✙ø✓ù✙ù✂ï➊é➻û✓å✪✘➈ï✖ä❯ì➈ë ✗❀ï✖ñ➔ï➊è❇✝ ✙➳å➄ä✥ï✇ì❛ä❺✂✐å➄é✙ø✠➽➊ï❞ù➞ø➀é ✓ æ✙û✓å➄é✙ï❞ê✄➌➇ï❞å✑￾❿ç✶ì➈ë❀ó❨ç✙ø✁￾❿ç✶ø✓ê✛å➞ëíï❞å✠è✧ÿ☎ä✧ï➳î➓å➄æ✝ð❷✕❲ÿ✙é✙ø➑è❨ø➑é✺å✌ëíï❞å✠è✧ÿ☎ä✧ï î➓å➄æ➽ç✎å➈ê✄✑ ✙✌ø➀é✙æ✙ÿ✂è❿ê➃￾➊ì➈é✙é☎ï✒￾↔è✥ï✖ù➻è✥ì❙å❄✙t✡☛✘ ✙✒å➄ä✥ï✖å➤ø➀é➽è✥ç✙ï➉ø➀é✙æ✙ÿ✂è★➌ ￾➊å➈û➑û➀ï✖ù✫è✧ç✙ï➐➡❺➳❄✴➳❖➤✇➺✮✣✍♦➳✄✁➃➳❪✲❨✪✒ì➄ë➏è✥ç✙ï❭ÿ✙é✙ø➑è✖ð ✭❫å➎￾❿ç✫ÿ✙é✙ø➑è➤ç✎å➈ê✒✑✫✙➻ø➀é✦✝ æ✙ÿ✂è❿ê✄➌➄å➈é☎ù✌è✥ç✙ï➊ä✥ï❶ëíì❛ä✧ï❀✑✫✙✛è✥ä✥å➈ø➑é✎å❄✡✙û➀ï➃￾➊ì✐ï✱✯➣￾❶ø➀ï➊é✐è✥ê❇æ✙û➀ÿ☎ê❦å❨è✧ä❿å➄ø➀é☎å✑✡✙û➑ï ✡✙ø✓å➈ê✖ð✒ã✛ç✙ï❭ä✧ï★￾❶ï✖æ✂è✧ø➀ú➈ï➑➞☎ï➊û✓ù✙ê➳ì➄ë✔￾❶ì❛é❛è✥ø✙✂❛ÿ✙ì➈ÿ✎ê➉ÿ✙é☎ø➩è❿ê➤ø➑é å➽ëíï❞å✠è✧ÿ☎ä✧ï î➓å➄æ❤å➈ä✧ï➙￾❶ï➊é✐è✥ï➊ä✥ï✖ù ì❛é➹￾❶ì❛ä✧ä✥ï✖ê✧æ✎ì❛é☎ù✂ø➀é❼✂➈û✠✘➛￾➊ì➈é✐è✧ø✠✂➈ÿ☎ì➈ÿ☎ê✒ÿ✙é✙ø➑è✥ê❭ø➑é è✧ç☎ï❙æ✙ä✥ï➊ú➇ø➀ì➈ÿ☎ê♣û✓å✪✘➈ï➊ä❞ð✌ã✛ç✙ï➊ä✥ï❶ëíì❛ä✧ï✒ä✧ï★￾❶ï➊æ✙è✧ø➀ú➈ï➓➞✎ï➊û✓ù✙ê➤ì➄ë➏é✙ï✖ø✙✂❛ç☛✡✎ì❛ä❇✝ ø➀é❼✂❺ÿ☎é✙ø➩è❿ê❭ì✠ú➈ï➊ä✥û✓å➄æ✝ð➒✜✙ì➈ä❭ï❯↔✙å➈î❭æ☎û➑ï➎➌➏ø➑é❤è✧ç✙ï➙➞☎ä❿ê④è❭ç✙ø✓ù✙ù✂ï➊é û✓å✪✘➈ï➊ä ì➄ë❅✗✝ï❞ñ➔ï❶è❺✝✝✙❼➌✝è✥ç✙ï➻ä✧ï★￾❶ï➊æ✙è✧ø➀ú➈ï➚➞☎ï➊û✓ù✙ê➤ì➈ë➵ç✙ì❛ä✧ø✠➽➊ì❛é✐è✥å➄û➀û✠✘✫￾➊ì➈é✐è✧ø✠✂➈ÿ☎ì➈ÿ☎ê ÿ✙é✙ø➑è✥ê➳ì✠ú❛ï➊ä✥û➀å➈æ➐✡☛✘◆❝➙￾➊ì➈û➀ÿ✙î➻é☎ê➳å➄é☎ù ✙➽ä✧ì✠ó➔ê✖ð✬✕♣ê♣ê✤è✥å➄è✧ï✖ù➲ï✖å➄ä✥û➀ø➑ï✖ä✒➌ å➄û➀û➔è✥ç✙ï❖ÿ☎é✙ø➩è❿ê✶ø➀é✻å➷ëíï❞å✠è✧ÿ☎ä✧ï➲î➓å➈æ✻ê✤ç☎å➈ä✧ï➲è✧ç✙ï❖ê✥å➄î➻ï❖ê✧ï❶è✿ì➄ë ✑✫✙ ó➵ï➊ø✠✂➈ç✐è✥ê✛å➄é✎ù➽è✥ç✙ï✌ê✧å➈î❭ï✞✡✙ø✓å➈ê❨ê✧ì✒è✥ç✙ï✄✘✢ù✂ï❶è✥ï✒￾↔è❨è✥ç✙ï✌ê✧å➈î➻ï➉ëíï❞å✠è✧ÿ☎ä✧ï å✠è➻å➄û➀û✇æ◆ì❛ê✥ê✧ø✙✡✙û➀ï✶û➀ì✦￾➊å➄è✧ø➀ì➈é☎ê✒ì➈é è✥ç✙ï✢ø➀é✙æ✙ÿ✙è✖ð➷ã✛ç✙ï✢ì➈è✧ç✙ï✖ä➞ëíï❞å✠è✧ÿ☎ä✧ï î➓å➄æ☎ê➳ø➀é➲è✥ç✙ï❙û✓å✪✘➈ï✖ä➉ÿ☎ê✧ï➻ù✂ø➟➘✟ï➊ä✥ï➊é✐è✌ê✤ï➊è✥ê➳ì➄ë✇ó✇ï✖ø✙✂❛ç❛è❿ê♣å➈é☎ù↕✡☎ø➀å❛ê✤ï❞ê✄➌ è✧ç☎ï➊ä✥ï✄✡☛✘✢ï✄↔➇è✧ä❿å✑￾↔è✥ø➑é✗✂➽ù✂ø➟➘✟ï➊ä✥ï➊é✐è➔è❅✘➇æ◆ï✖ê♣ì➄ë❣û➀ì☛￾✖å➄û❀ëíï✖å✠è✥ÿ✙ä✥ï✖ê✖ð✎➏➠é➲è✧ç✙ï ￾➊å❛ê✤ï❙ì➄ë✄✗❀ï✖ñ➉ï❶è❇✝ ✙✦➌☛å➄è➳ï❞å✑￾❿ç➲ø➀é✙æ✙ÿ✂è➤û➀ì☛￾✖å✠è✥ø➑ì❛é❺ê✧ø➟↔➲ù✂ø✙➘◆ï✖ä✧ï✖é✐è♣è❅✘➇æ◆ï✖ê ì➄ë❇ëíï✖å➄è✧ÿ✙ä✥ï✖ê❨å➈ä✧ï➤ï❯↔➇è✥ä✥å➎￾↔è✧ï❞ù➣✡☛✘✶ê✧ø➟↔✢ÿ✙é✙ø➑è✥ê❨ø➀é✺ø➀ù✂ï✖é✐è✧ø✁￾➊å➄û☛û➀ì✦￾➊å➄è✧ø➀ì➈é☎ê ø➀é è✧ç☎ï✿ê✧ø➟↔➷ëíï❞å✠è✧ÿ☎ä✧ï✢î➻å➈æ☎ê✖ð ✕▼ê✧ï✒➍✐ÿ✙ï➊é✐è✥ø➀å➈û❫ø➀î❭æ☎û➑ï✖î❭ï✖é✐è✥å✠è✥ø➑ì❛é❤ì➈ë å❖ëíï✖å✠è✥ÿ✙ä✥ï✢î➓å➄æ❑ó✇ì❛ÿ✙û✓ù❤ê❘￾➊å➄é❤è✧ç✙ï✿ø➀é✙æ✙ÿ✂è➓ø➀î➻å✑✂➈ï✿ó❨ø➩è✥ç å ê✧ø➑é❼✂❛û➑ï ÿ✙é✙ø➑è❭è✧ç☎å➄è❙ç☎å❛ê✒å✫û➀ì✦￾➊å➄û➵ä✥ï✒￾❶ï✖æ✂è✧ø➀ú➈ï➣➞☎ï➊û✓ù❢➌➏å➄é✎ù ê④è✥ì➈ä✥ï➓è✧ç✙ï✺ê✤è✥å✠è✥ï✖ê ì➄ë❇è✧ç✙ø✓ê❨ÿ✙é☎ø➩è➉å➄è✬￾❶ì➈ä✥ä✥ï✖ê✧æ✎ì❛é☎ù✂ø➀é❼✂✒û➀ì✦￾➊å✠è✥ø➑ì❛é☎ê✛ø➀é✶è✥ç✙ï➤ëíï✖å➄è✧ÿ✙ä✥ï➤î➻å➈æ✝ð ã✛ç✙ø✓ê➳ì➈æ◆ï➊ä❿å✠è✧ø➀ì➈é❖ø➀ê♣ï✒➍✐ÿ✙ø➀ú✠å➄û➀ï➊é✐è♣è✥ì✿å➙￾❶ì❛é✐ú❛ì➈û➀ÿ✂è✧ø➀ì➈é❀➌✎ëíì❛û➑û➀ì✠ó➵ï✖ù✫✡☛✘ å➄é å❛ù✙ù✂ø➑è✧ø➀ú➈ï➣✡✙ø✓å➈ê✒å➄é☎ù➷ê❘➍❛ÿ✎å➈ê✧ç✙ø➑é✗✂✺ëíÿ✙é✗￾↔è✥ø➑ì❛é✏➌❦ç✙ï➊é✥￾❶ï➻è✧ç☎ï➽é☎å➄î➻ï ❄✴➯♦➨☎✍✪➯✬✲✡✦➺✮✣ ➯❄➨✈➢✬✲✥➨✇➳❯➺✶➻➜➯♦➡❺➼➄ð❣ã✛ç✙ï❨ô➈ï✖ä✧é✙ï✖û✂ì➄ë◆è✧ç✙ï④￾❶ì➈é➇ú❛ì➈û➀ÿ✂è✧ø➀ì➈é❭ø➀ê❣è✧ç✙ï ê✧ï❶è➤ì➄ë➜￾❶ì❛é✙é✙ï★￾↔è✧ø➀ì➈é❖ó✇ï✖ø✙✂❛ç❛è❿ê➉ÿ✎ê✤ï❞ù↕✡☛✘✿è✧ç✙ï❭ÿ✙é✙ø➑è✥ê➳ø➀é➲è✧ç☎ï✒ëíï❞å✠è✧ÿ☎ä✧ï î➓å➄æ✝ð❜✕➔é➞ø➀é✐è✧ï✖ä✧ï❞ê④è✥ø➑é❼✂❨æ☎ä✧ì❛æ✎ï✖ä✤è❅✘♣ì➄ë❼￾❶ì❛é✐ú❛ì➈û➀ÿ✂è✧ø➀ì➈é✎å➄û➄û✓å✪✘➈ï✖ä✥ê✟ø✓ê☛è✥ç☎å✠è ø➑ë✇è✥ç✙ï➻ø➑é✙æ☎ÿ✂è➞ø➑î➓å✑✂➈ï➻ø➀ê✌ê✧ç✙ø➑ë➺è✧ï❞ù❢➌✝è✥ç✙ï➻ëíï✖å➄è✧ÿ✙ä✥ï➻î➻å➈æ❺ì❛ÿ✂è✧æ☎ÿ✂è➞ó❨ø➑û➀û ✡◆ï➤ê✧ç✙ø➑ë➺è✧ï❞ù➣✡☛✘➻è✧ç✙ï✌ê✥å➄î➻ï♣å➈î➻ì➈ÿ✙é✐è✒➌☛✡✙ÿ✙è✛ó❨ø➀û➀û✈✡◆ï➤û➑ï➊ë➺è❨ÿ✙é✗￾❿ç☎å➈é❼✂➈ï❞ù ì➄è✥ç✙ï➊ä✥ó❨ø✓ê✤ï❛ð➳ã✛ç✙ø✓ê♣æ✙ä✧ì❛æ✎ï✖ä✤è❅✘✺ø✓ê♣å➄è♣è✥ç✙ï➚✡☎å➈ê✧ø➀ê♣ì➄ë❣è✥ç✙ï❭ä✧ì➎✡✙ÿ☎ê✤è✧é✙ï❞ê✧ê ì➄ë✛￾➊ì➈é➇ú➈ì❛û➑ÿ✂è✥ø➑ì❛é☎å➄û❫é✙ï❶è④ó➵ì➈ä✥ô✂ê➤è✧ì❖ê✧ç✙ø➑ë➺è✥ê❭å➄é☎ù❤ù✂ø➀ê✤è✧ì❛ä✤è✥ø➑ì❛é☎ê✌ì➈ë❨è✧ç✙ï ø➀é✙æ✙ÿ✂è❞ð ý♣é✗￾❶ï å❍ëíï✖å➄è✧ÿ✙ä✥ï❤ç✎å➈ê➛✡✎ï✖ï➊é➶ù✙ï❶è✧ï★￾↔è✥ï✖ù❢➌❭ø➩è❿ê ï❯↔✙å✑￾❶è❺û➀ì☛￾✖å✠è✥ø➑ì❛é ✡◆ï✒￾❶ì❛î➻ï✖ê✺û➀ï✖ê✥ê✢ø➀î➻æ✎ì❛ä✤è❿å➄é✐è✖ð ý♣é✙û✠✘✻ø➑è✥ê✫å➄æ☎æ✙ä✧ì✪↔✂ø➀î➓å✠è✧ï❺æ✎ì✐ê✤ø➑è✧ø➀ì➈é ä✥ï➊û✓å✠è✧ø➀ú➈ï✢è✧ì➷ì➈è✧ç✙ï✖ä➻ëíï✖å✠è✥ÿ✙ä✥ï✖ê❭ø➀ê➽ä✧ï✖û➑ï✖úrå➈é✐è✖ð ✜✙ì➈ä➻ï✄↔✂å➈î➻æ✙û➑ï➎➌✇ì❛é✗￾❶ï ó➵ï❙ô➇é✙ì✠ó è✥ç☎å✠è➤è✥ç✙ï➻ø➑é✙æ☎ÿ✂è✌ø➑î➓å❄✂❛ï➚￾➊ì➈é✐è✥å➈ø➑é✎ê➔è✥ç✙ï➻ï➊é☎ù✂æ◆ì➈ø➀é✐è✌ì➄ë✇å ä✥ì➈ÿ❼✂❛ç✙û✙✘❭ç✙ì❛ä✧ø✠➽➊ì❛é❛è❿å➄û☎ê✧ï✄✂❛î➻ï➊é✐è✇ø➀é➓è✧ç☎ï♣ÿ✙æ☎æ✎ï✖ä✇û➀ï❶ë➺è❨å➄ä✥ï✖å✗➌❛å➉￾➊ì➈ä✥é✙ï➊ä ø➀é➽è✧ç☎ï➉ÿ✙æ✙æ◆ï➊ä✛ä✥ø✙✂❛ç✐è➵å➄ä✥ï✖å✗➌❛å➈é☎ù➻è✧ç☎ï♣ï✖é☎ù✂æ◆ì➈ø➀é❛è✛ì➄ë❀å✒ä✧ì❛ÿ❼✂➈ç☎û✙✘❭ú➈ï✖ä❇✝ è✧ø✁￾➊å➈û✎ê✧ï✄✂❛î❭ï✖é✐è❫ø➑é➽è✧ç✙ï♣û➑ì✠ó➵ï➊ä➏æ◆ì➈ä✧è✧ø➀ì➈é➓ì➈ë☛è✧ç✙ï♣ø➑î➓å✑✂➈ï✑➌❛ó✇ï✞￾➊å➈é➻è✧ï➊û➀û è✧ç☎ï✒ø➀é✙æ✙ÿ✂è➳ø➑î➓å❄✂❛ï➞ø✓ê➉å✜✔✂ð➔ñ➔ì➄è➳ì➈é✙û✠✘✿ø➀ê➔è✧ç✙ï❙æ✙ä✧ï★￾❶ø✓ê✤ï✒æ✎ì✐ê✤ø➑è✧ø➀ì➈é✫ì➈ë ï✖å➎￾❿ç❙ì➈ë☎è✥ç✙ì❛ê✧ï➵ëíï✖å✠è✥ÿ✙ä✥ï✖ê❦ø➀ä✧ä✥ï➊û➀ï➊ú✠å➄é✐è❦ëíì➈ä❣ø✓ù✂ï✖é❛è✥ø➩ë➭✘➇ø➀é❼✂➳è✧ç✙ï❨æ✎å✠è✤è✥ï➊ä✥é✏➌ ø➑è✛ø✓ê➵æ✎ì➈è✧ï✖é❛è✥ø➀å➈û➑û✠✘➻ç☎å➄ä✥î❭ëíÿ✙û❢✡◆ï✒￾➊å➈ÿ☎ê✧ï➔è✧ç☎ï➳æ◆ì❛ê✧ø➑è✧ø➀ì➈é☎ê➵å➄ä✥ï♣û➀ø➀ô➈ï➊û✠✘❭è✧ì ú✠å➄ä❘✘➻ëíì➈ä➔ù✂ø✙➘✟ï➊ä✥ï➊é✐è❨ø➑é☎ê✤è✥å➈é✗￾❶ï❞ê✛ì➄ë❇è✧ç✙ï✌￾❿ç☎å➈ä✥å➎￾↔è✧ï✖ä✖ð❨✕ ê✤ø➀î➻æ✙û➀ï➳ó✛å✪✘ è✧ì✶ä✧ï❞ù✂ÿ✗￾❶ï➤è✥ç✙ï➞æ✙ä✥ï✒￾➊ø➀ê✧ø➀ì➈é✺ó❨ø➩è✥ç✫ó❨ç✙ø✁￾❿ç✺è✧ç✙ï➞æ◆ì❛ê✧ø➑è✧ø➀ì➈é✺ì➄ë➏ù✂ø✓ê④è✥ø➑é✥￾✹✝ è✧ø➀ú➈ï♣ëíï✖å➄è✧ÿ✙ä✥ï✖ê✛å➈ä✧ï➳ï➊é✗￾➊ì✂ù✂ï✖ù✶ø➑é✺å➞ëíï❞å✠è✥ÿ✙ä✧ï➳î➓å➄æ✢ø➀ê✇è✧ì➻ä✥ï✖ù✂ÿ✥￾❶ï♣è✧ç✙ï ê✧æ☎å✠è✥ø➀å➈û✙ä✧ï❞ê✤ì❛û➑ÿ✙è✧ø➀ì➈é❭ì➄ë✟è✧ç✙ï➔ëíï✖å✠è✥ÿ✙ä✥ï❨î➻å➈æ✝ð❣ã✛ç✙ø✓ê❹￾➊å➈é➚✡◆ï➉å➎￾❿ç✙ø➑ï✖ú➈ï❞ù ó❨ø➑è✧ç➓å✌ê✤ì✑✝❖￾✖å➄û➀û➑ï❞ù➵➩✒✡✤✯❪✭❖➩❯➢❄➲✛➤ ✲✣●➨✵✥ ✲✙➢✟✑➳❯➡✴➩❦ó❨ç✙ø✁￾❿ç➻æ✎ï✖ä✤ëíì❛ä✧î➓ê❣å➤û➀ì☛￾✖å➄û årú➈ï✖ä✥å✑✂➈ø➀é❼✂✫å➄é☎ù❤å➲ê✤ÿ✗✡✦✝⑥ê✥å➄î➻æ✙û➀ø➀é❼✂✗➌❦ä✥ï✖ù✂ÿ✗￾➊ø➑é✗✂➲è✧ç☎ï✶ä✥ï✖ê✧ì➈û➀ÿ✂è✧ø➀ì➈é ì➈ë è✧ç☎ï❨ëíï✖å➄è✧ÿ✙ä✥ï❨î➓å➄æ✏➌➇å➄é☎ù❭ä✥ï✖ù✂ÿ✥￾❶ø➀é❼✂➤è✧ç✙ï♣ê✤ï✖é☎ê✤ø➑è✧ø➀ú➇ø➩è❅✘❙ì➄ë✟è✧ç☎ï➔ì➈ÿ✂è✥æ✙ÿ✂è è✧ì♣ê✤ç✙ø➑ë➺è✥ê❯å➄é✎ù✌ù✂ø➀ê✤è✧ì❛ä✤è✥ø➑ì❛é☎ê✖ð❇ã✛ç✙ï❫ê✧ï✒￾➊ì➈é☎ù➤ç☎ø➀ù✙ù✙ï➊é➞û✓å✪✘➈ï✖ä✝ì➄ë ✗✝ï❞ñ➔ï➊è❇✝ ✙❭ø✓ê➔å➻ê✤ÿ❼✡❼✝⑥ê✥å➄î➻æ✙û➀ø➑é✗✂➓û➀å✪✘❛ï➊ä❞ð❦ã✛ç☎ø➀ê❨û✓å✪✘➈ï✖ä✛￾❶ì❛î❭æ☎ä✧ø✓ê✤ï❞ê❨ê✤ø✙↔➽ëíï❞å✠è✧ÿ☎ä✧ï î➓å➄æ☎ê✒➌✂ì➈é☎ï♣ëíì❛ä✛ï✖å✑￾❿ç✢ëíï✖å➄è✧ÿ✙ä✥ï➤î➓å➄æ✿ø➑é✢è✧ç✙ï✌æ☎ä✧ï✖ú✐ø➀ì➈ÿ✎ê✇û✓å✪✘➈ï✖ä✖ð❦ã✛ç✙ï ä✥ï✒￾❶ï✖æ✂è✧ø➀ú➈ï✞➞☎ï✖û➀ù✢ì➄ë❯ï✖å➎￾❿ç✢ÿ✙é☎ø➩è➔ø✓ê❨å ✑➉✡☛✘ ✑❭å➈ä✧ï❞å✒ø➀é✶è✥ç✙ï✌æ✙ä✥ï➊ú➇ø➀ì➈ÿ☎ê û✓å✪✘➈ï➊ä✒❁ ê❀￾❶ì❛ä✧ä✥ï✖ê✧æ◆ì➈é☎ù✂ø➀é❼✂➉ëíï✖å✠è✥ÿ✙ä✥ï✇î➓å➄æ❀ð ✭❫å➎￾❿ç✒ÿ✙é☎ø➩è❹￾❶ì❛î➻æ✙ÿ✂è✧ï❞ê❇è✧ç✙ï ➢✍♦➳✄➡❺➢❪✥❩➳✛ì➄ë❇ø➩è❿ê❫ëíì❛ÿ✙ä✛ø➑é☎æ✙ÿ✂è✥ê✒➌✂î✒ÿ☎û➩è✥ø➑æ✙û➀ø➀ï✖ê✛ø➑è✎✡☛✘➽å✒è✧ä❿å➄ø➀é☎å❄✡✙û➀ï④￾➊ì➇ï❶ë●✝ ➞✥￾➊ø➑ï✖é❛è★➌❛å❛ù✙ù✙ê➏å➳è✥ä✥å➈ø➑é☎å✑✡✙û➀ï✎✡☎ø➀å❛ê✄➌✐å➄é☎ù❭æ☎å❛ê✧ê✧ï✖ê❯è✥ç✙ï➔ä✥ï✖ê✧ÿ✙û➩è❣è✥ç✙ä✥ì➈ÿ❼✂❛ç å➳ê✤ø✠✂➈î➻ì➈ø✓ù✌ëíÿ☎é✗￾↔è✥ø➑ì❛é✝ð❷☞✇ì❛é✐è✧ø✠✂➈ÿ✙ì❛ÿ☎ê❀ÿ☎é✙ø➩è❿ê❦ç☎årú➈ï✇é✙ì➈é❼✝♠ì✠ú❛ï➊ä✥û➀å➈æ✙æ✙ø➀é❼✂ ￾❶ì❛é✐è✧ø✠✂➈ÿ✙ì❛ÿ☎ê➉ä✥ï✒￾➊ï➊æ✂è✥ø➑ú❛ï➉➞✎ï➊û✓ù✙ê➊ð➝☞✇ì➈é☎ê✧ï✒➍✐ÿ✙ï✖é❛è✥û✙✘➎➌✝å✢ê✧ÿ❼✡✦✝➠ê✥å➄î➻æ✙û➀ø➑é❼✂ û✓å✪✘➈ï➊ä❯ëíï❞å✠è✧ÿ☎ä✧ï✛î➓å➄æ❭ç☎å➈ê❦ç✎å➄û➑ë☎è✧ç☎ï❨é✐ÿ☎î➉✡◆ï➊ä❣ì➄ë◆ä✧ì✠ó➔ê❦å➈é☎ù➑￾➊ì➈û➀ÿ✙î➻é☎ê