Incident angle-dependent dynamic tuning of high-purity structural colors with an array of nanovoids on a dielectric surface

Incident angle-dependent dynamic tuning of high-purity structural colors with an array of nanovoids on a dielectric surface | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Incident angle-dependent dynamic tuning of high-purity structural colors with an array of nanovoids on a dielectric surface Hrudya Radhakrishnan, Tummaluru Khadar Basha, Junaid Masud Laskar, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5606019/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Aug, 2025 Read the published version in ACS Photonics → Version 1 posted You are reading this latest preprint version Abstract We demonstrate incident angle-dependent dynamic tuning of visible structural colors with an array of nanovoids fabricated on the surface of silicon using focused ion beam nanolithography. Enhanced structural purity and resolution achieved by this method are manifested as sharp peaks in the experimental reflectance spectra. The linear correlation observed between reflected wavelength and changes in periodicity or incident angle demonstrates the potential for efficient tuning of structural color through manipulation of material or instrumental factors, or a combination of both. Two distinct physical phenomena, Mie resonance and light diffraction, were employed to elucidate the source of reflectance peaks and their shifts induced by incident angle or array periodicity. This analysis demonstrated that nanovoids, the fundamental components of the array, serve a dual purpose: they act as Mie-voids while simultaneously functioning as elements in a crossed-diffraction system. Our findings also show that for smaller angles of incidence (below 45°), the Mie resonance linked to individual nanovoids is the primary factor. However, when the angles exceed 45°, the structural color wavelength is predominantly influenced by the periodic arrangement of the void array and the diffraction of light, which depends on the grating constant. Nanoscience structural colors nanolithography subwavelength nanostructures high-index material focused ion beam air-filled nanovoids Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Colors, particularly their hues, tints, tones and shades, represented by different wavelengths of the visible electromagnetic spectrum, are integral to human life. Hitherto, two approaches have been, in principle, adopted to create colors. The first approach, based on the natural or synthetic dyes and pigments, regularly used in textile industry, has disadvantages such as fading of colors due to radiation damage (photo-bleaching or heat-induced changes) and contain hazardous chemicals posing a risk to health and the environment. In the second approach, colors emanate from the physical interaction of light, particularly the visible wavelengths with a nanostructured medium. This alternate approach, also termed artificial structural coloring as it utilizes the advantage of geometry-dependent spectral resonance, has been gaining popularity in recent years with the advantages of better fade resistance and viewing-angle dependence. In fact, the physical color generation approach, is inspired by nature and might have different origins depending on the dimension and geometry of the nanostructures. This approach may be broadly categorized into (a) multilayer films interference, (b) Fabry-Perot cavity resonance, (c) dielectric metasurface and photonic crystals associated Mie scattering and Fano resonance, (d) metallic metasurfaces associated localized surface plasmon resonances, (e) guided mode resonance structure and (f) grating structure exhibiting light diffraction by periodic ordered crystal lattice nanostructures, e.g., the colors of insects, butterflies and plants [ 1 ]. Structural coloring, in general, could be achieved in transmission or reflection mode (depending on the nanostructured medium) and tuning of the resonance in visible wavelengths of light is possible by modifying the geometry of the nanostructure. With the recent vast advancements in nanofabrication technology, both reflective and transmissive type of color generations (often referred to as color filters as well) have been demonstrated with a variety of materials, including photonic and plasmonic materials [ 1 ][ 2 ][ 3 ][ 4 ][ 5 ]. As the structural color filtering technique provides resolutions much higher (about 10 5 dots per inch) than the other techniques, it is preferred for applications that demand high spatial resolution, compactness, high stability and reproducibility compared to those based on pigments and dyes [ 6 ][ 7 ]. Recent developments in color filtering and display technologies have focused on high-resolution, color vibrancy and high efficiency with slim dimensions [ 7 ][ 8 ]. To achieve these objectives, nanostructures of noble metals utilizing the principle of surface plasmon resonances have been extensively investigated [ 9 ][ 10 ][ 11 ]. Expensive metals such as Au and Ag were frequently utilized for plasmon-based color filters[ 7 ][ 8 ][ 9 ]. However, optical losses and Ohmic heating, manifested as broad spectral line-width in the reflectance spectrum, were reported to deteriorate the color purity, resolution and degree of monochromaticity [ 12 ][ 13 ][ 14 ]. On the other hand, high refractive index (HRI) dielectric metasurfaces showing resonant behavior due to the oscillations of bound electrons are emerging as alternative candidates for the structural color filters [ 8 ][ 15 ][ 16 ][ 17 ][ 18 ]. The optical losses are minimal in the dielectric media as the displacement current induced by the bound electron oscillation is not effective in instigating Ohmic heating. Interestingly, Mie-type resonances associated with the HRI nanostructured metasurfaces were reported to offer stronger optical responses and nonlinear effects due to their magnetic and electric counterparts unlike the localized field enhancement induced by electric resonance in plasmonic color generation. They further offer enhanced flexibility in tuning the interplay of different resonances, manifested in the structural color tuning [ 19 ][ 20 ][ 21 ]. Being the most abundant and commonly used material in the electronics industry, Si with its high refractive index and low loss ( n ~ 5 to 3.5 with 0.2 to 0 in the visible wavelength range of 400 to 800 nm), is the most preferred choice for dielectric nanostructure based structural coloring application. There are several reports on the high-index Si-based color filters with various types of subwavelength building blocks such as nanoparticles, nanodiscs, nanorods or nanowires [ 21 ][ 22 ][ 23 ][ 24 ][ 25 ][ 26 ][ 27 ][ 28 ],[ 29 ][ 30 ]. The actual geometry of these color filters consisted of solid high-index subwavelength nanofeatures in a low-index surrounding (typically air) to fit into the classification of HRI dielectric nanophotonics. They often performed based on wavelength selective visible light coupling with guided modes. A strong coupling of visible light with the localized surface states was shown mostly with restricted viewing angle dependence. Intrinsic losses are, however, still possible with these structures. Although light confinement, through excitation of resonant electromagnetic modes, takes place inside the HRI medium, a fraction of the mode extends to surrounding low refractive index medium, mostly air. Though such weaker mode confinement effect is of less concern in the near- and mid-infrared (IR) regions, the loss becomes a crucial factor for the visible and UV range, due to the larger imaginary component of the refractive index of most HRI dielectric material including Si. Towards addressing these shortcomings, alternate strategies, using inverse nanostructures such as low refractive index (LRI) air-filled nanovoids, acting as nanoresonators, present on HRI surface (Si), are adopted in recent times [ 31 ][ 32 ]. In this case, localized electromagnetic dielectric resonant modes such as Mie resonance are reported to be confined within the subwavelength scale low-index voids and hence expected to have reduced intrinsic losses [ 32 ]. Structural color generation with efficient tunability is realized and attributed to the nanovoid diameter-dependent excitation of dielectric electromagnetic Mie resonance modes such as electric dipole, magnetic dipole, electric quadrupole, magnetic quadrupole and overlap of different modes. These modes are correlated to the polarization of bound charges inside the dielectric nanoresonators [ 33 ][ 34 ]. As the color variation, often manifested as a peak in the reflectance spectrum in the reports, is independent of the grating constant, i.e. the lattice array periodicity, the role of light diffraction on the emitted color is ruled out for normal light incidence. However, controlling the electromagnetic mode resonance by varying the incident angle (a key parameter in the dynamic tuning of colors in the HRI subwavelength nanostructures surrounded by air) is yet to be investigated for the LRI inverse nanostructures. Moreover, in oblique incidences, the role of the nanovoid dimensions, particularly the void depth on the Mie resonance, becomes ineffective at high incident angles, greater than the half-angle of the cone-shaped nanovoid resonators. Therefore, it remains an open question whether, between the two possible underlying physical phenomena, the light diffraction originating from the array periodicity of nanovoids or individual nanovoid dielectric electromagnetic Mie resonance modes, dictate the resultant structural coloring characteristics, manifested as peak(s) in the reflectance spectra, peak width, peak shift as a function of incidence angle of broadband light in the visible spectrum. This article addresses the above-stated research problem by designing and fabricating 2D periodic arrays of cone-shaped LRI air-filled nanovoids on a HRI Si substrate. The arrays were fabricated with various periodicities using a focused ion beam (FIB) assisted nanolithography technique. In order to enhance the possibility of efficient light confinement leading to stronger excitation of resonant electromagnetic modes of different orders, dimensions of the nanovoid fabricated in this report were smaller compared to those reported [ 31 ][ 32 ]. The structural coloring characteristics of the nanovoid arrays fabricated on the surface of Si were systematically investigated by measuring the reflectance spectra in the visible wavelength range (λ = 400 to 800 nm). The spectra were recorded in the direction normal to the void surface, upon irradiation by a broad band light source for different oblique incident angles and nanovoid array periodicities. We demonstrate that the nanovoid, the basic building block of the array, not only performs as a recently reported Mie-void[ 32 ], but also simultaneously as an element of a crossed-diffraction grating. Experiments A nanolithography technique based on a FIB was used for this purpose. Exposure of a 30 kV accelerated Ga ion beam, in a controlled manner, created nanovoids on the surface of a crystalline Si (100) wafer by ion beam induced milling (sputter etching) at nanoscale. A cross-beam system (Model AURIGA by Carl Zeiss, Germany) consisting of a Ga ion and electron beam, controlled by a RAITH ELPHY Multibeam nanolithography module was employed for this purpose. 200 by 200 micron sized 2D square array patterns of various periodicities were exposed on the surface of Si with a 50 pA Ga ion beam. The fabricated arrays were examined using the scanning electron microscopy (SEM) component of the cross-beam system. The shape of the nanovoids was examined by the FIB cross-sectioning method, where the voids were cut open along the plane of symmetry (which is perpendicular to Si surface) by the Ga ion beam milling followed by polishing of the cross-sectioned surface with a lower ion beam current. Tilt-view SEM of the cross-sections revealed the void shape and dimensions. Dwell time and beam overlap function were the key parameters to control the nanovoid dimension and achieve the desired periodicities, respectively. A home-built bright-field optical microscope with 20X objective lens and a white light illuminating source was used to view and record the images of the arrays. Reflectance spectra in the visible wavelength range (λ = 400 to 800 nm) of the nanovoid arrays were recorded using a UV-Vis spectrophotometer (Avantes) with an external white light illumination at various incident angles (θ = 40º to 60°). The schematic of the experimental setup used for recording the optical micrographs in bright field mode and the measurement of the reflectance spectra are shown in the supplement (Figure S1). The procedure for determining the color coordinates of the measured reflected wavelengths on the color spaces (x, y) of the CIE (Commission Internationale de l'Éclairage) 1931 chromaticity diagram are provided in the supplement. Computation Computer simulations on the periodic arrays of conical nanovoids, supporting electromagnetic Mie resonances, were carried out using the frequency-domain solver of the finite-element method (FEM) in the COMSOL Multiphysics software. The nanovoids, also known as Mie-voids, were modeled as conical holes within an infinite solid Si medium ( n = 3.88 at λ = 632.8 nm), embedded within air medium ( n ≈ 1). Floquet periodic boundary conditions (FPBC) were applied to a unit cell (i.e., the conical hole in the Si medium) along the X and Y direction. In order to compute the infinite extension using the FEM with reduced noise, perfectly matched layers were applied to the top and bottom of the computation domain. The depth and the diameter of the conical voids were considered to be 80 and 254 nm, respectively, as characterized by cross sectional SEM measurements. For the case of broadband white light excitation, a periodic port was placed in the air domain above the Si Mie-voids. In order to match the experimental configuration to the best measure, the nanovoid array was excited by white light at various oblique angles (incident angles of θ = 40°, 50° and 60°) and the reflectance spectra were simulated. The reflectance was defined as the ratio of the power reflected back into the zeroth diffraction order with that of the excitation power. The excited resonant electric fields were computed over a range of visible wavelengths ( λ = 400 to 700 nm), where the reflected wavelength peaks for the specified nanovoid dimensions. Results and discussion The nanovoid dimensions and the array periodicities were measured from the SEM micrographs. Figure 1 (a) to (d) show the magnified view of a part of the 200 by 200 µm sized square array with various array periodicities, viewed at a tilt angle of 54° with respect to normal incidence. The tilt-view SEM of the FIB-cut void cross-sections reveal the void shape and dimensions. The voids were found to be cone-shaped resulted using the Gaussian nature of the Ga ion beam. The nanovoid diameter ( D ) and depth ( d ) were measured to be 254 and 80 nm, respectively. The half-angle of the low-aspect-ratio cone-shaped nanovoid was measured to be about 45 o (see Fig. 1 (e)). The array periodicity (P) measured from the top-view SEM (shown in the supplementary, Figure S2), was found to be vary from 500 to 800 nm. Illuminating the nanovoid arrays with a white light source at oblique angles resulted in the reflection of unique colors (observed vertically above the surface of Si), depending on the periodicity and angle of light incidence. The insets of Figs. 1 (a) to (d) show the bright-field optical microscope images of the 200 by 200 µm sized nanovoid arrays with various periodicities. The images shown here were acquired at a specific incident angle ( θ = 40°) and the square arrays are visible, in the low-reflective Si background, with various vibrant colors depending on their periodicities. Figure 2 (a), (c) and (e) show the reflectance spectra of the nanovoid arrays of various periodicities acquired at incident angles of 40°, 50° and 60°, respectively. The bright-field optical microscope image of the array corresponds to each reflectance peak is shown in the inset. It can be observed that by varying the periodicity from 500 to 800 nm, various vibrant colors from violet to red could be obtained, showing the possibility of separate out various vibant colors in the visible region. In fact, a shift in the reflected light towards the red part of the spectrum (red-shift), is observed with increase in the periodicity. The reflected colors and their shifts upon the tuning of the periodicity are depicted in the color spaces (x, y) of the CIE (Commission Internationale de l'Éclairage) 1931 chromaticity diagram in Fig. 2 (b), (d) and (f). Interestingly, the periodicity tuning from 500 to 800 nm at various incident angles, covers the entire color space. The calculated color coordinates for experimental reflectance peaks are located at the edge of the diagram, indicating higher saturation which is further confirmed by the presence of sharp peaks (narrow band width) in the measured reflectance spectra [ 35 ]. The influence of the incident angle on the reflected light wavelength of the nanovoid array is shown in Fig. 3 . Figures 3 (a), (c), (e) and (g) show the reflectance spectrum corresponding to the array periodicity of 500, 600, 700 and 800 nm, respectively, and wherein the incident angle variation for each periodicity is shown. It could be noticed that the reflected wavelength shows a ref-shift for the increase in the incident angle in all the arrays of different periodicities. The bright-field optical microscopic images corresponding to all the reflectance peaks are given in the insets. The reflected colors and their shifts upon tuning of the incident angle are depicted in the color spaces (x, y) of the CIE 1931 chromaticity diagram in Fig. 3 (b), (d), (f) and (h). The calculated color coordinates for experimental reflectance peaks were found to be mostly located at the edge of the diagram, indicating higher saturation. However, it could be noticed that the increase in the incident angle from 40 to 60º leads to the degradation of the color purity. It is interesting to note that the periodicity spectaral tunability, which is the variation of reflectance with respect to the array periodicity (∆λ/∆P), incresases with the incident angle. From 0.58 to 0.75 nm red-shift in the reflected wavelength per unit nanometer periodicity variation is observed, where larger peak shift is achieved with larger incident angle (see Fig. 4 (a)). Similarly, the angular spectral tunability, which is the variation of reflectance with respect to the incident angle (∆λ/∆θ), increases with the increase in the nanovoid array periodicity as depicted in Fig. 4 (b). From 2.5 to 5 nm red-shift in the reflected wavelength per unit degree variation in the incident angle is achieved, where larger peak shift is caused for larger periodicity. More pronounced peak shift, compared to the previous case, is observed for the incident angle variation. An almost a linear increase observed in the reflected wavelength upon varying the periodicity as well as incident angle, indicates the possibility of efficient color tuning using the combination of the array periodicity (the material parameter associated with the nanovoid arrays) and the incident angle (the instrumetal parameter associated with the measurement strategy). Discussions The resonance peak positions and their shifts upon varying the periodicity (P) and incident angle ( θ ) are explained by simultaneously considering two different physical phenomena: (a) light diffraction originating from the interaction of incident light with the array periodicity and (b) Mie resonance originating from the individual nanovoids (the nanoresonators) due to the excitation of electromagnetic modes when light interacts. Considering the array of nanovoids as a crossed 2D grating, the light diffraction equations are given by Table 1: Comparison of the reflectance peak positions derived from the experiment and computer simulations. Diffraction and Mie models were considered in the simulations, where the nanovoid diameter (D), depth (d) and periodicity (P) were considered to be 254, 80 and 800 nm, respectively. The data for various incident angles θ = 40° to 60° are listed. Incident angle ( θ in deg.) Reflectance peak position (in nm) Experimentally measured Mathematical calculation: Diffraction model Computer simulation: Mie-resonance model 40° 600 514 541 50° 650 613 591 60° 700 692 651 In order to get a deeper insight into the reflectance spectrum peak positions, the possible contribution from Mie resonance was investigated using the FEM computation in COMSOL. An earlier report on this topic revealed that the light-matter interaction of the tapered array of conical nanovoids, acting as nanoresonators, filled with a LRI medium (air with n = 1) fabricated on a HRI medium (Si with n > 1) could show higher monochromaticity, compared with the nanoresonators (e.g. Si nanocylinders) made of the HRI medium surrounded by LRI air medium [32]. It is also observed that the constricted nanoresonator shapes such as conical nanovoids showing higher monochromaticity (i.e., spectral purity), in contrast to the less- constricted cylindrical, square or sphere-shaped nanovoids at the normal light incidence [31],[32],[48],[49]. However, it should be noted that the reflectance spectra reported hitherto, for the arrays of both conical and non-conical shapes, were measured for the normal incidence of broadband light source [31], [32]. Computational FEM simulation of this work has given focus on the evaluation of different light scattering parameters, including scattering cross section and scattered electromagnetic field distribution as a function of incident angle and periodicity of the conical nanovoid array. Fig. 5 (a) shows a schematic of trapped meta-atoms (conical nanovoids) and the relevant details considered for the computational model. The nanovoids were modelled as conical holes on a Si substrate ( n = 3.88 at λ = 632.8 nm) [31], [32] with a finite layer of air covering the entire nanostructures ( n = 1 at λ = 590 nm). In computational simulations of an array of conical nanovoids, the excitation wave was considered to be a plane wave propagating along the Z-axis. Figure 5(b) shows the influence of the incident light angles (varied from 40° to 60°) on the reflectance spectrum of the meta-atoms with an array periodicity of 800 nm. Figure 5(c) shows the simulation results of the electric field distributions over the nanovoid resonator of diameter D = 254 nm and depth d = 80 nm, respectively. The effect of incident angle and nanovoid periodicities were investigated numerically. In the computational simulation, broader scattering cross-section resonance reflectance spectra (large full-width half maximum) were observed (Figure 5(b)), as compared to the experimental reflectance peak width (Figure 3(g)), with an approximate error in matching the spectral peak position of about 55 nm. The resonant reflectance peak positions derived from the Mie resonance model are also listed in Table 1 for various incident angles in order to compare with the experimentally measured values. The observed small difference between the experimental and calculated peak position using the diffraction model at higher θ (Table 1), it could be perceived that for a higher angle of incidence ( θ = 60°) diffraction dominates over the Mie contribution. In this case, light diffraction, i.e., the interaction of light with structural periodicity (array of nanoholes), plays a dominant role in determining the reflectance peak wavelength position. It is important to consider that at high incident angles, only a small fraction of incident light can enter into the individual nanoholes resonators to excite the Mie resonances efficiently. In other words, the nanoresonator depth contribution to the Mie-excitation becomes less effective, and the incident light only detects the structural periodicity. Therefore, the diffraction involvement becomes dominant in deciding the reflectance spectra peak position. An average value of about 55° peak shift between the experimental and simulated Mie-resonance could be attributed to the possible deviations in refractive index values of the nanovoid boundaries from the crystalline Si matrix considered for simulation. The inner wall of the nanovoid resonator is not essentially composed of crystalline Si but is a mixture of amorphous Si, Ga inclusions and their oxides[39]. This modified inner wall layer is because of the Ga ion bombardment on the dielectric surface during the creation of nanovoids, as reported previously[40]. Conclusions In this work, we have demonstrated the incident angle-dependent dynamic tuning of visible structural colors with an array of nanovoids fabricated on the surface of silicon using a focused ion beam nanolithography technique. In addition to the high precision in fabricating the nanostructures by this method, prudently designing the nanostructure geometry and their spatial arrangement resulted in sharp peaks in the experimental reflectance spectra. The potential for effective tuning of structural color using either material or instrumental parameters, or both, is suggested by the observed linear relationship between the reflected wavelength and changes in periodicity or incident angle. The origin of the reflectance peaks and their shifts instigated by the incident angle or array periodicity were explained by harnessing two different physical phenomena, the Mie resonance and light diffraction, indicating that the nanovoids, building block of the array, not only perform as Mie-voids, but also simultaneously as an element of a crossed-diffraction. We further demonstrate that the Mie resonance associated with the individual nanovoids dominates for smaller incident angles ( 45º), void array periodicity, the grating constant dependent light diffraction dominates structural color wavelength. Declarations Acknowledgements One of the authors, HR acknowledges the Department of Atomic Energy, India for the financial support needed to conduct the study. The authors TKB and JML acknowledge the High Performance Computing Center and Center of Excellence for Electronic Cooling and CFD Simulation of SRM Institute of Science and Technology, Kattankulathur, India for providing computational resources and financial support needed to conduct the study. References Z. Xuan, J. Li, Q. Liu, F. Yi, S. Wang, and W. Lu, “Artificial Structural Colors and Applications,” Innov. , vol. 2, no. 1, p. 100081, 2021, doi: 10.1016/j.xinn.2021.100081. Y. Yu, L. Wen, S. Song, and Q. 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W. He et al. , “Mie resonant scattering-based refractive index sensor using a quantum dots-doped polylactic acid nanowire,” Appl. Phys. Lett. , vol. 119, no. 11, 2021, doi: 10.1063/5.0061416. V. Garg, R. G. Mote, and J. Fu, “Focused Ion Beam Direct Fabrication of Subwavelength Nanostructures on Silicon for Multicolor Generation,” Adv. Mater. Technol. , vol. 3, no. 8, pp. 1800100(1–10), 2018, doi: 10.1002/admt.201800100. M. Hentschel et al. , “Dielectric Mie voids: confining light in air,” Light Sci. Appl. , vol. 12, no. 1, p. 3, 2023, doi: 10.1038/s41377-022-01015-z. W. Liu and Y. S. Kivshar, “Generalized Kerker effects in nanophotonics and meta-optics [Invited],” Opt. Express , vol. 26, no. 10, p. 13085, 2018, doi: 10.1364/oe.26.013085. D. . Aspnes and A. A. Studna, “Dielectric functions and optical parameters of Si, Ge, GaP, GaAs, GaSb, InP, InAs, and InSb from 1.5 to 6.0 eV,” Phys. Rev. B , vol. 27, no. 2, pp. 985–1009, 1983, doi: 10.1111/j.1468-0130.2010.00653.x. D. Wang, Z. Liu, H. Wang, M. Li, L. J. Guo, and C. Zhang, “Structural color generation: From layered thin films to optical metasurfaces,” Nanophotonics , vol. 12, no. 6, pp. 1019–1081, 2023, doi: 10.1515/nanoph-2022-0063. B. Zhou, W. Jia, P. Sun, J. Wang, W. Liu, and C. Zhou, “Polarization-independent high diffraction efficiency two-dimensional grating based on cylindrical hole nano arrays,” Opt. Express , vol. 28, no. 20, p. 28810, 2020, doi: 10.1364/oe.402131. J. Yang, H. Wang, J. C. Y. En, M. Hentschel, and Y. Kivshar, “Structured Colors with Dielectric Nanoresonators,” Opt. Photonics News , vol. 35, no. 4, p. 34, 2024, doi: 10.1364/opn.35.4.000034. J. Hecht, “Is Nothing Better Than Something?,” Opt. Photonics News , vol. 32, no. 3, p. 26, 2021, doi: 10.1364/opn.32.3.000026. M. J. Theisen and T. G. Brown, “Optical properties of gallium implanted silicon,” Front. Opt. FIO 2012 , pp. 3–4, 2012, doi: 10.1364/fio.2012.ftu4a.3. P. Li et al. , “Recent advances in focused ion beam nanofabrication for nanostructures and devices: Fundamentals and applications,” Nanoscale , vol. 13, no. 3, pp. 1529–1565, 2021, doi: 10.1039/d0nr07539f. Additional Declarations The authors declare no competing interests. Supplementary Files Supplement.docx Cite Share Download PDF Status: Published Journal Publication published 06 Aug, 2025 Read the published version in ACS Photonics → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5606019","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":387804711,"identity":"cd53d3c9-0313-46a7-9956-24d0e6372f10","order_by":0,"name":"Hrudya Radhakrishnan","email":"","orcid":"","institution":"Surface and Sensors Studies Division, Materials Science Group, Indira Gandhi Centre for Atomic Research, A CI of Homi Bhabha National Institute, Kalpakkam 603102, Tamil Nadu, India","correspondingAuthor":false,"prefix":"","firstName":"Hrudya","middleName":"","lastName":"Radhakrishnan","suffix":""},{"id":387804712,"identity":"0b246057-727a-4419-a514-9524c0100360","order_by":1,"name":"Tummaluru Khadar Basha","email":"","orcid":"","institution":"Nanophotonics and Quantum Meta-Optics Group, Center for Nanophotonics, Department of Physics and Nanotechnology, SRM Institute of Science and Technology, Kattankulathur - 603203, Tamil Nadu, India","correspondingAuthor":false,"prefix":"","firstName":"Tummaluru","middleName":"Khadar","lastName":"Basha","suffix":""},{"id":387804713,"identity":"6ebf96d4-4f86-4550-9e14-572683e18937","order_by":2,"name":"Junaid Masud Laskar","email":"","orcid":"","institution":"Nanophotonics and Quantum Meta-Optics Group, Center for Nanophotonics, Department of Physics and Nanotechnology, SRM Institute of Science and Technology, Kattankulathur - 603203, Tamil Nadu, India","correspondingAuthor":false,"prefix":"","firstName":"Junaid","middleName":"Masud","lastName":"Laskar","suffix":""},{"id":387804714,"identity":"9c81df88-20c8-42fc-9fe2-e4326df1b4f7","order_by":3,"name":"Sandip Dhara","email":"","orcid":"","institution":"Materials Science Group, Indira Gandhi Centre for Atomic Research, A CI of Homi Bhabha National Institute, Kalpakkam 603102, Tamil Nadu, India","correspondingAuthor":false,"prefix":"","firstName":"Sandip","middleName":"","lastName":"Dhara","suffix":""},{"id":387804715,"identity":"2497cdb8-15c6-42bd-8679-dc2512dd57f0","order_by":4,"name":"Ramanathaswamy Pandian","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYLACHgMGBn5mJIEDRGmRbCZNCxAbEFYGBeazm589eFNgl2d8nP3ih597GOz6JRIYDxfg0SJz55i54RyD5GKzwzzFkj3PGJJnzkhgODwDjxYJiQQzaR4D5sRth3nSGHgOMCQbnDnAcJgHr5b0b0At9Ymbm3nSGP8QpyUHZMvhxA3M7MeYgbbYGRxvIKBF5kyZ5ByD44kzDvMwS8sckEiQbG9swK9Fun2bxJs/1Yn9/ccffnxzwMaen5n58Gd8Whgk4CxQhDJIJDYwMDbg04Cshf0BiLTHr3wUjIJRMApGIgAAoB1JBpU2gX8AAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0001-7393-7441","institution":"Surface and Sensors Studies Division, Materials Science Group, Indira Gandhi Centre for Atomic Research, A CI of Homi Bhabha National Institute, Kalpakkam 603102, Tamil Nadu, India","correspondingAuthor":true,"prefix":"","firstName":"Ramanathaswamy","middleName":"","lastName":"Pandian","suffix":""}],"badges":[],"createdAt":"2024-12-09 05:46:18","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-5606019/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5606019/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1021/acsphotonics.5c00885","type":"published","date":"2025-08-07T00:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":71099142,"identity":"fb7bc233-60f4-45c2-a178-17161c00155f","added_by":"auto","created_at":"2024-12-11 06:34:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":258265,"visible":true,"origin":"","legend":"\u003cp\u003eHigh-resolution SEM images of the conical nanovoid arrays viewed at a\u0026nbsp;tilt angle\u0026nbsp;of\u0026nbsp;54° with respect to normal incidence. The FIB-cut cross-sectional images show the magnified view of a part of the square array with various periodicities, P = 500 to 800 nm, images (a) to (d), respectively. Bright-field optical micrographs of the 200 by 200 µm sized square arrays on the surface of Si with periodicities, P = 500 to 800 nm are shown in the inset of the SEM images. The optical micrographs were recorded vertically above the surface of Si, which is illuminated with white light at an oblique angle of 40\u003csup\u003eº\u003c/sup\u003e. Magnified view of a single nanovoid is shown in (e). The nanovoid diameter, depth and half-angle were measured to be 254 nm, 80 nm and 45\u003csup\u003eo\u003c/sup\u003e, respectively.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5606019/v1/9c3b530fb89c26d405e32e2c.png"},{"id":71099019,"identity":"a6798625-19c5-42c8-aa23-b5bdc52a503e","added_by":"auto","created_at":"2024-12-11 06:26:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":276817,"visible":true,"origin":"","legend":"\u003cp\u003eMeasured spectral response, in reflectance mode, of the nanovoid arrays (with various periodicities from 500 to 800 nm) recorded at different incident angles, 40\u003csup\u003e o\u003c/sup\u003e, 50\u003csup\u003e o\u003c/sup\u003e and 60\u003csup\u003eo\u003c/sup\u003e are shown in (a), (c) and (e), respectively. The bright-field optical microscope image corresponds to each reflectance peak is given in the inset. The CIE 1931 chromaticity diagrams illustrating the reflectance peaks, recorded at 3 different incident angles, for each periodicity are shown in (b), (d) and (f).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5606019/v1/978839cf2ae43cb11d68d333.png"},{"id":71100316,"identity":"df075f44-a1c0-4c70-8e89-935ef7d6a5e2","added_by":"auto","created_at":"2024-12-11 06:42:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":217761,"visible":true,"origin":"","legend":"\u003cp\u003eReflectance spectra of the nanovoid arrays with various periodicities, 500, 600, 700 and 800 nm are shown in (a), (c), (e) and (g), respectively. Reflectance spectrum for each periodicity was recorded at 3 different incident angles, 40\u003csup\u003e o\u003c/sup\u003e, 50\u003csup\u003e o\u003c/sup\u003e and 60\u003csup\u003eo\u003c/sup\u003e. The bright-field optical microscope image corresponds to each reflectance peak is given in the inset. The CIE 1931 chromaticity diagrams illustrating the reflectance peaks, recorded at 3 different incident angles, for each periodicity are shown in (b), (d), (f) and (h).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5606019/v1/35d9a61ae18aa28095b067ad.png"},{"id":71099021,"identity":"87952872-989a-4006-82fe-ea30642bf21d","added_by":"auto","created_at":"2024-12-11 06:26:43","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":56951,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Periodicity spectral tunability ((∆λ/∆P) as a function of the incident angle; (b) Angular spectral tunability (∆λ/∆θ) as a function of the array periodicity. Note that the line joining the points is a guide for the eyes.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5606019/v1/01754bbc52ecae3df08cbd9d.png"},{"id":71099147,"identity":"b3d579db-4772-46bd-b288-fc7e930b0d24","added_by":"auto","created_at":"2024-12-11 06:34:43","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":279722,"visible":true,"origin":"","legend":"\u003cp\u003e(a) schematic of the COMSOL model of Mie-voids, (b) simulated reflectance spectra for the nanovoid array of periodicity, P = 800 nm. The nanovoid diameter (\u003cem\u003eD\u003c/em\u003e) and depth (\u003cem\u003ed\u003c/em\u003e) were assumed to be 254 and 80 nm, respectively, as in the case of experiments, (c) computationally simulated electric field (|E|\u003csup\u003e2\u003c/sup\u003e) distributions in and around each Mie-void for three different incident angles\u0026nbsp;θ = 40°, 50° and 60° (left to right). The color bar represents the electric field intensity variation in V/m.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5606019/v1/44ede2a4df475c84b891fab4.png"},{"id":88631430,"identity":"a1ccf5a7-fab3-48e7-892a-9c20105e35ba","added_by":"auto","created_at":"2025-08-08 13:58:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1619307,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5606019/v1/0ae6dcc4-48ed-435f-9dfc-7265137f4222.pdf"},{"id":71100320,"identity":"4809d0e7-0b14-44e1-8fbc-37c0dd56c636","added_by":"auto","created_at":"2024-12-11 06:42:43","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":316757,"visible":true,"origin":"","legend":"","description":"","filename":"Supplement.docx","url":"https://assets-eu.researchsquare.com/files/rs-5606019/v1/ad8faef64d8676f42f2e5ddf.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eIncident angle-dependent dynamic tuning of high-purity structural colors with an array of nanovoids on a dielectric surface\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eColors, particularly their hues, tints, tones and shades, represented by different wavelengths of the visible electromagnetic spectrum, are integral to human life. Hitherto, two approaches have been, in principle, adopted to create colors. The first approach, based on the natural or synthetic dyes and pigments, regularly used in textile industry, has disadvantages such as fading of colors due to radiation damage (photo-bleaching or heat-induced changes) and contain hazardous chemicals posing a risk to health and the environment. In the second approach, colors emanate from the physical interaction of light, particularly the visible wavelengths with a nanostructured medium. This alternate approach, also termed artificial structural coloring as it utilizes the advantage of geometry-dependent spectral resonance, has been gaining popularity in recent years with the advantages of better fade resistance and viewing-angle dependence. In fact, the physical color generation approach, is inspired by nature and might have different origins depending on the dimension and geometry of the nanostructures. This approach may be broadly categorized into (a) multilayer films interference, (b) Fabry-Perot cavity resonance, (c) dielectric metasurface and photonic crystals associated Mie scattering and Fano resonance, (d) metallic metasurfaces associated localized surface plasmon resonances, (e) guided mode resonance structure and (f) grating structure exhibiting light diffraction by periodic ordered crystal lattice nanostructures, e.g., the colors of insects, butterflies and plants [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eStructural coloring, in general, could be achieved in transmission or reflection mode (depending on the nanostructured medium) and tuning of the resonance in visible wavelengths of light is possible by modifying the geometry of the nanostructure. With the recent vast advancements in nanofabrication technology, both reflective and transmissive type of color generations (often referred to as color filters as well) have been demonstrated with a variety of materials, including photonic and plasmonic materials [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e][\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e][\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e][\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e][\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. As the structural color filtering technique provides resolutions much higher (about 10\u003csup\u003e5\u003c/sup\u003e dots per inch) than the other techniques, it is preferred for applications that demand high spatial resolution, compactness, high stability and reproducibility compared to those based on pigments and dyes [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e][\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Recent developments in color filtering and display technologies have focused on high-resolution, color vibrancy and high efficiency with slim dimensions [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e][\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. To achieve these objectives, nanostructures of noble metals utilizing the principle of surface plasmon resonances have been extensively investigated [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e][\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e][\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Expensive metals such as Au and Ag were frequently utilized for plasmon-based color filters[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e][\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e][\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, optical losses and Ohmic heating, manifested as broad spectral line-width in the reflectance spectrum, were reported to deteriorate the color purity, resolution and degree of monochromaticity [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e][\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e][\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOn the other hand, high refractive index (HRI) dielectric metasurfaces showing resonant behavior due to the oscillations of bound electrons are emerging as alternative candidates for the structural color filters [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e][\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e][\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e][\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e][\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The optical losses are minimal in the dielectric media as the displacement current induced by the bound electron oscillation is not effective in instigating Ohmic heating. Interestingly, Mie-type resonances associated with the HRI nanostructured metasurfaces were reported to offer stronger optical responses and nonlinear effects due to their magnetic and electric counterparts unlike the localized field enhancement induced by electric resonance in plasmonic color generation. They further offer enhanced flexibility in tuning the interplay of different resonances, manifested in the structural color tuning [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e][\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e][\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBeing the most abundant and commonly used material in the electronics industry, Si with its high refractive index and low loss (\u003cem\u003en\u003c/em\u003e\u0026thinsp;~\u0026thinsp;5 to 3.5 with 0.2 to 0 in the visible wavelength range of 400 to 800 nm), is the most preferred choice for dielectric nanostructure based structural coloring application. There are several reports on the high-index Si-based color filters with various types of subwavelength building blocks such as nanoparticles, nanodiscs, nanorods or nanowires [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e][\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e][\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e][\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e][\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e][\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e][\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e][\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e],[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e][\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The actual geometry of these color filters consisted of solid high-index subwavelength nanofeatures in a low-index surrounding (typically air) to fit into the classification of HRI dielectric nanophotonics. They often performed based on wavelength selective visible light coupling with guided modes. A strong coupling of visible light with the localized surface states was shown mostly with restricted viewing angle dependence. Intrinsic losses are, however, still possible with these structures. Although light confinement, through excitation of resonant electromagnetic modes, takes place inside the HRI medium, a fraction of the mode extends to surrounding low refractive index medium, mostly air. Though such weaker mode confinement effect is of less concern in the near- and mid-infrared (IR) regions, the loss becomes a crucial factor for the visible and UV range, due to the larger imaginary component of the refractive index of most HRI dielectric material including Si.\u003c/p\u003e \u003cp\u003eTowards addressing these shortcomings, alternate strategies, using inverse nanostructures such as low refractive index (LRI) air-filled nanovoids, acting as nanoresonators, present on HRI surface (Si), are adopted in recent times [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e][\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In this case, localized electromagnetic dielectric resonant modes such as Mie resonance are reported to be confined within the subwavelength scale low-index voids and hence expected to have reduced intrinsic losses [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Structural color generation with efficient tunability is realized and attributed to the nanovoid diameter-dependent excitation of dielectric electromagnetic Mie resonance modes such as electric dipole, magnetic dipole, electric quadrupole, magnetic quadrupole and overlap of different modes. These modes are correlated to the polarization of bound charges inside the dielectric nanoresonators [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e][\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. As the color variation, often manifested as a peak in the reflectance spectrum in the reports, is independent of the grating constant, i.e. the lattice array periodicity, the role of light diffraction on the emitted color is ruled out for normal light incidence. However, controlling the electromagnetic mode resonance by varying the incident angle (a key parameter in the dynamic tuning of colors in the HRI subwavelength nanostructures surrounded by air) is yet to be investigated for the LRI inverse nanostructures. Moreover, in oblique incidences, the role of the nanovoid dimensions, particularly the void depth on the Mie resonance, becomes ineffective at high incident angles, greater than the half-angle of the cone-shaped nanovoid resonators. Therefore, it remains an open question whether, between the two possible underlying physical phenomena, the light diffraction originating from the array periodicity of nanovoids or individual nanovoid dielectric electromagnetic Mie resonance modes, dictate the resultant structural coloring characteristics, manifested as peak(s) in the reflectance spectra, peak width, peak shift as a function of incidence angle of broadband light in the visible spectrum.\u003c/p\u003e \u003cp\u003eThis article addresses the above-stated research problem by designing and fabricating 2D periodic arrays of cone-shaped LRI air-filled nanovoids on a HRI Si substrate. The arrays were fabricated with various periodicities using a focused ion beam (FIB) assisted nanolithography technique. In order to enhance the possibility of efficient light confinement leading to stronger excitation of resonant electromagnetic modes of different orders, dimensions of the nanovoid fabricated in this report were smaller compared to those reported [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e][\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The structural coloring characteristics of the nanovoid arrays fabricated on the surface of Si were systematically investigated by measuring the reflectance spectra in the visible wavelength range (λ\u0026thinsp;=\u0026thinsp;400 to 800 nm). The spectra were recorded in the direction normal to the void surface, upon irradiation by a broad band light source for different oblique incident angles and nanovoid array periodicities. We demonstrate that the nanovoid, the basic building block of the array, not only performs as a recently reported Mie-void[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], but also simultaneously as an element of a crossed-diffraction grating.\u003c/p\u003e"},{"header":"Experiments","content":"\u003cp\u003eA nanolithography technique based on a FIB was used for this purpose. Exposure of a 30 kV accelerated Ga ion beam, in a controlled manner, created nanovoids on the surface of a crystalline Si (100) wafer by ion beam induced milling (sputter etching) at nanoscale. A cross-beam system (Model AURIGA by Carl Zeiss, Germany) consisting of a Ga ion and electron beam, controlled by a RAITH ELPHY Multibeam nanolithography module was employed for this purpose. 200 by 200 micron sized 2D square array patterns of various periodicities were exposed on the surface of Si with a 50 pA Ga ion beam. The fabricated arrays were examined using the scanning electron microscopy (SEM) component of the cross-beam system. The shape of the nanovoids was examined by the FIB cross-sectioning method, where the voids were cut open along the plane of symmetry (which is perpendicular to Si surface) by the Ga ion beam milling followed by polishing of the cross-sectioned surface with a lower ion beam current. Tilt-view SEM of the cross-sections revealed the void shape and dimensions. Dwell time and beam overlap function were the key parameters to control the nanovoid dimension and achieve the desired periodicities, respectively. A home-built bright-field optical microscope with 20X objective lens and a white light illuminating source was used to view and record the images of the arrays. Reflectance spectra in the visible wavelength range (λ\u0026thinsp;=\u0026thinsp;400 to 800 nm) of the nanovoid arrays were recorded using a UV-Vis spectrophotometer (Avantes) with an external white light illumination at various incident angles (θ\u0026thinsp;=\u0026thinsp;40\u0026ordm; to 60\u0026deg;). The schematic of the experimental setup used for recording the optical micrographs in bright field mode and the measurement of the reflectance spectra are shown in the supplement (Figure S1). The procedure for determining the color coordinates of the measured reflected wavelengths on the color spaces (x, y) of the CIE (Commission Internationale de l'\u0026Eacute;clairage) 1931 chromaticity diagram are provided in the supplement.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eComputation\u003c/h2\u003e \u003cp\u003eComputer simulations on the periodic arrays of conical nanovoids, supporting electromagnetic Mie resonances, were carried out using the frequency-domain solver of the finite-element method (FEM) in the COMSOL Multiphysics software. The nanovoids, also known as Mie-voids, were modeled as conical holes within an infinite solid Si medium (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.88 at \u003cem\u003eλ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;632.8 nm), embedded within air medium (\u003cem\u003en\u003c/em\u003e\u0026thinsp;\u0026asymp;\u0026thinsp;1). Floquet periodic boundary conditions (FPBC) were applied to a unit cell (i.e., the conical hole in the Si medium) along the X and Y direction. In order to compute the infinite extension using the FEM with reduced noise, perfectly matched layers were applied to the top and bottom of the computation domain. The depth and the diameter of the conical voids were considered to be 80 and 254 nm, respectively, as characterized by cross sectional SEM measurements. For the case of broadband white light excitation, a periodic port was placed in the air domain above the Si Mie-voids. In order to match the experimental configuration to the best measure, the nanovoid array was excited by white light at various oblique angles (incident angles of \u003cem\u003eθ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;40\u0026deg;, 50\u0026deg; and 60\u0026deg;) and the reflectance spectra were simulated. The reflectance was defined as the ratio of the power reflected back into the zeroth diffraction order with that of the excitation power. The excited resonant electric fields were computed over a range of visible wavelengths (\u003cem\u003eλ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;400 to 700 nm), where the reflected wavelength peaks for the specified nanovoid dimensions.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results and discussion","content":"\u003cp\u003e \u003c/p\u003e \u003cp\u003eThe nanovoid dimensions and the array periodicities were measured from the SEM micrographs. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e(a) to (d) show the magnified view of a part of the 200 by 200 \u0026micro;m sized square array with various array periodicities, viewed at a tilt angle of 54\u0026deg; with respect to normal incidence. The tilt-view SEM of the FIB-cut void cross-sections reveal the void shape and dimensions. The voids were found to be cone-shaped resulted using the Gaussian nature of the Ga ion beam. The nanovoid diameter (\u003cem\u003eD\u003c/em\u003e) and depth (\u003cem\u003ed\u003c/em\u003e) were measured to be 254 and 80 nm, respectively. The half-angle of the low-aspect-ratio cone-shaped nanovoid was measured to be about 45\u003csup\u003eo\u003c/sup\u003e (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e(e)). The array periodicity (P) measured from the top-view SEM (shown in the supplementary, Figure S2), was found to be vary from 500 to 800 nm. Illuminating the nanovoid arrays with a white light source at oblique angles resulted in the reflection of unique colors (observed vertically above the surface of Si), depending on the periodicity and angle of light incidence. The insets of Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e(a) to (d) show the bright-field optical microscope images of the 200 by 200 \u0026micro;m sized nanovoid arrays with various periodicities. The images shown here were acquired at a specific incident angle (\u003cem\u003eθ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;40\u0026deg;) and the square arrays are visible, in the low-reflective Si background, with various vibrant colors depending on their periodicities.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (a), (c) and (e) show the reflectance spectra of the nanovoid arrays of various periodicities acquired at incident angles of 40\u0026deg;, 50\u0026deg; and 60\u0026deg;, respectively. The bright-field optical microscope image of the array corresponds to each reflectance peak is shown in the inset. It can be observed that by varying the periodicity from 500 to 800 nm, various vibrant colors from violet to red could be obtained, showing the possibility of separate out various vibant colors in the visible region. In fact, a shift in the reflected light towards the red part of the spectrum (red-shift), is observed with increase in the periodicity. The reflected colors and their shifts upon the tuning of the periodicity are depicted in the color spaces (x, y) of the CIE (Commission Internationale de l'\u0026Eacute;clairage) 1931 chromaticity diagram in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (b), (d) and (f). Interestingly, the periodicity tuning from 500 to 800 nm at various incident angles, covers the entire color space. The calculated color coordinates for experimental reflectance peaks are located at the edge of the diagram, indicating higher saturation which is further confirmed by the presence of sharp peaks (narrow band width) in the measured reflectance spectra [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe influence of the incident angle on the reflected light wavelength of the nanovoid array is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Figures\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (a), (c), (e) and (g) show the reflectance spectrum corresponding to the array periodicity of 500, 600, 700 and 800 nm, respectively, and wherein the incident angle variation for each periodicity is shown. It could be noticed that the reflected wavelength shows a ref-shift for the increase in the incident angle in all the arrays of different periodicities. The bright-field optical microscopic images corresponding to all the reflectance peaks are given in the insets. The reflected colors and their shifts upon tuning of the incident angle are depicted in the color spaces (x, y) of the CIE 1931 chromaticity diagram in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (b), (d), (f) and (h). The calculated color coordinates for experimental reflectance peaks were found to be mostly located at the edge of the diagram, indicating higher saturation. However, it could be noticed that the increase in the incident angle from 40 to 60\u0026ordm; leads to the degradation of the color purity.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIt is interesting to note that the periodicity spectaral tunability, which is the variation of reflectance with respect to the array periodicity (∆λ/∆P), incresases with the incident angle. From 0.58 to 0.75 nm red-shift in the reflected wavelength per unit nanometer periodicity variation is observed, where larger peak shift is achieved with larger incident angle (see Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e(a)). Similarly, the angular spectral tunability, which is the variation of reflectance with respect to the incident angle (∆λ/∆θ), increases with the increase in the nanovoid array periodicity as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e (b). From 2.5 to 5 nm red-shift in the reflected wavelength per unit degree variation in the incident angle is achieved, where larger peak shift is caused for larger periodicity. More pronounced peak shift, compared to the previous case, is observed for the incident angle variation. An almost a linear increase observed in the reflected wavelength upon varying the periodicity as well as incident angle, indicates the possibility of efficient color tuning using the combination of the array periodicity (the material parameter associated with the nanovoid arrays) and the incident angle (the instrumetal parameter associated with the measurement strategy).\u003c/p\u003e"},{"header":"Discussions","content":"\u003cp\u003eThe resonance peak positions and their shifts upon varying the periodicity (P) and incident angle (\u003cem\u003e\u0026theta;\u003c/em\u003e) are explained by simultaneously considering two different physical phenomena: (a) light diffraction originating from the interaction of incident light with the array periodicity and (b) Mie resonance originating from the individual nanovoids (the nanoresonators) due to the excitation of electromagnetic modes when light interacts. Considering the array of nanovoids as a crossed 2D grating, the light diffraction equations are given by\u003c/p\u003e\n\u003cp\u003e\u003cimg 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BMMw0Gq1fOFoNyRlml31Zi8Wi3k3vkIdADeMHNPKyorXSJXxUtQ0rlareOihh2AYBpaXlwFlitVYLOaNVVIqlbx4kicxCoUCpqamAo9RtdM4Hgf7tbx0c++99wIAnn322Y4bmXq97qWLmsf/+7//27ceALzyyiuANtjroPE1Pz8PwzBQq9V85fbixYu+jr1Go4G7774bAPDb3/42UocQEe0OGR9JHZdoVGTMLhmPiGgk9GltiIjo4JGpXldXV73pXiuVimsYhmuaphcm4WhPHaqGu8p2crmcL9xVpuBUp+UMIlPZynobGxuuYRiuZVkd+0ulUq5t224ikXATiYSbSqXcSqXiNptN7ztqGAA3k8n4tiFs23YzmYy3Xi6XczOZjGvbtnfOUaYO3N7edg3DcAG4lmW5+XzezefzgVP6yvSnhmF44bZtB05r6v5rcAHXMAxfHK6urroA3FQq5VtXJ9MfWpblVioV73urq6vu9va2F++WZfmmAc7lcm6lUvFNn7i6uuq6WnpLmGVZrmma3vdVw4rjvTas8qKmiU7SI6gsqfopL900m00v35mm6eZyOTefz7upVKojXdQ8LunebDa9Y9HLWD/xpZPzMQzDLRaL7vb2tot2frdt283n897yXnVLVPr5EtHOSD2iXv+6Ua+DhmFEnnJe1icaJXaQEBFNgGKx6CYSCe+mR26S5OZVbG9vex0dso4sz+VyXrh+gyE3SNJ46XYjIzdaciymabr5fL7rTZRsX72xl5smCZOb8ig3PrJf2afclMnNYC/b29teg1DOOZPJ+I5PVCqVjnWlU0eXy+V8cQmlE6Zb/AjZl5rOss9EItHRIaOSm3k1DuS41e9ZluUmEgnv7zA7jeO9NIzyUiwWfd9X40ziWj7d8uwg5SWMvi20OyKCyqt0dunnEJSHosZXGNmXGpfqPgc93zC94pyI+iM/BkTt8A37hHW+u+3OVAR00BINGztIiIho7OmNItu2O25ypPEU1PGgkl/81Rs9adwFdXDsV3KzGVUikehonJqm6buxj9oJNSlxTMMnN1C9yvFORMnDg5BfxIM+0mHE/E8HlWmarmEYQ+3MVMmPB1E6XYl2gmOQEBHRWJOxCX74wx96Yf/zP/8DaANF/vnPfwaU96HDyAwZd9xxhxf29ttvwzCMfTFoaRSO48C27a4Daeq2traQSqW8v2Ub//Vf/+WFXb58GYjw/vckxDGNxpUrV4AI5Xgnhj2Ir7hy5Yo3GK46jbBt23jwwQexsrKC7373ux1jEhEdBC+88AJarRaef/55fdGOlctlbG1tIZfL+QYdJxoFdpAQEdFYk5vtQ4cOeWHSGaLebK+vr0fqEHjnnXdgmqZvoMeLFy/2HFByP5GOjFtuuUVfFEg6oX7wgx94YbKNb33rW17YH/7wByDCzeskxDENn+M4qNVqXifDfhQ0gOzMzAxOnz6NTCYDAHjkkUf0VYj2vWPHjiGXy2FpackbhHwY6vU6fvrTn8KyLJw9e1ZfTDR07CAhIqKxFnazrXeG2LaNW265BY1GwzejRiwW882QsbW11XGj3mq1cPPNN6NeryObzfqW7Ud//etfAa3DoxvphPrmN7/phQU9kdNoNGBZljczjcx8kkwmvdluMCFxTMMn0wHreeeguO+++4B2XbUfZnMi6tfZs2dRLBZx/Phx3zViEI7joFAo4MiRI0in097TZUSjxg4SIiIaa/rNtvzKfPvtt/vWy2QyWFpaQjabxdLSkm+ZkI6S2267zReeSCSwsLCAtbU1PP30075l+9E777wDaB0e3UgnlProclAn1IkTJ1Cr1XDo0CHcd999gY86T0oc0/BJR913vvMdfdGB8+WXX+pBRAdCOp2GbdsA4Htts19PPvkkPvzwQ/z+97/3pqUn2g0x91+DVRERER045XIZjzzyCC5fvhz46DvtnOM4+OpXv4rt7W2OL0ITL5lMYmtrC/l8vmOck3K5jDvvvBNoj4NCRETjh0+QEBHRgfXqq6/izTffZOfICD3//PPY2Nhg5whRD6+++irQftqNiIjGEztIiIjowCqVSrxxH7GzZ8/i2LFjejARtdXrdSwuLmJ9fR2WZfEVMyKiMcZXbIiIiIiIhkBesdElEgn813/9F+655x4+0UZENMb4BAkRERER0RDl83m4rut9Njc3cerUKXaOEBGNOXaQEBEREREREdHEYwcJEREREREREU08dpAQERERERER0cRjBwkRERER0S5aXFxELBZDOp32wkqlEqamppBMJn3rEhHR7mEHCRERERHREDiOAwD48MMP9UWetbU1fOc738HGxgbW19dRr9dRKpXw7rvv4re//S1uv/12/StERLRLOM0vEREREdEOzc3NoVareX8nEglsbm761tHFYjFkMhkAwPLysr6YiIh2GTtIiIiIiIj2QDKZxNWrV3H58mVOAUxENAb4ig0RERER0S5zHAeO4+DatWvsHCEiGhPsICEiIiIi2mUPP/wwTp48iVarhXq9ri8mIqI9wFdsiIiIiIh2wdraGgCgXq/jtttuQzqdRiwWQz6fRyKRwNraGsciISLaQ+wgISIiIiLaBel0GhcvXsTy8rI3xe/i4iKWlpaQSCTwu9/9jq/bEBHtIXaQEBEREREREdHE4xgkRERERERERDTx2EFCRERERERERBOPHSRERERERERENPHYQUJEREREREREE48dJEREREREREQ08dhBQkREREREREQTjx0kRERERERERDTx2EFCRERERERERBOPHSRERERERERENPHYQUJEREREREREE48dJEREREREREQ08dhBQkREREREREQTjx0kRERERERERDTx2EFCRERERERERBOPHSRERERERERENPHYQUJEREREREREE48dJEREREREREQ08dhBQkREREREREQTjx0kRERERERERDTx2EFCRERERERERBOPHSRERERERERENPHYQUJEREREREREE48dJEREREREREQ08dhBQkREREREREQTjx0kRERERERERDTx2EFCRERERERERBOPHSRERERERERENPHYQUJEREREREREE48dJEREREREREQ08dhBQkREREREREQTjx0kRERERERERDTx2EFCRERERERERBOPHSRERERERERENPHYQUJEREREtMfq9TrS6TRisRhisRhKpZK+ChERjRg7SIiIiIiI9tjCwgJ+9rOfwXVdpFIpHD9+HI7j6KsREdEIsYOEiIiIiGiPbW5uYn5+HgBw//33AwA++eQTbS0iIholdpAQEREREY2Rf/u3f9ODiIhoF7CDhIiIiIhojMzOzupBRES0C9hBQkREREQ0Rur1uh5ERES7gB0kREREREQ7UK1WkUwmEYvFMDU15XVwqOHxeBzValX/aqCTJ0/qQUREtAvYQUJERERENKBqtYozZ85geXkZGxsbaLVa2NraQqlUwmuvvYbf/e53qFQqsG0bJ06c0L/eoVAooFar6cFERLQLYq7runogERERERH1p1wu484770QikcDMzAyWl5e9ZbFYDADQreldr9fx3e9+F5ZloVaroVKpeDPbEBHR6PEJEiIiIiKiIfjrX/8KALh69aqvc0ReubEsywsLIq/WnD9/Xl9ERES7gB0kRERERERD8M477wAAzpw54wv/5JNPAABzc3O+cNXi4iJqtRry+by+iIiIdgk7SIiIiIiIhmBrawsAkE6nfeHvvvsuAOC2227zhYtqtYqlpSWYponTp0/jyy+/1FchIqJdwA4SIiIiIqIdkhlqEomEvgilUgkAcOutt+qL4DiON3jrK6+8oi8mIqJdxA4SIiIiIqId+vjjjwEAt99+uy+8Xq+j1WrBsizMzMz4lgHA888/D9u2kclkOCArEdEeYwcJEREREdEOXbp0CQDw7W9/2xf+//7f/wNCxh+RV2sMw8DTTz+tLyYiol3GDhIiIiIioh26ePEiAODQoUO+8H/+85/e/x3HweLiIgqFAhzHwV133QUAeOaZZzA9Pe2td9111wHtp1IajQaSySQcx/GWExHRaMTcbpOxExERERFRV41GA6ZpwjRNXL161bfMcRwkk0nUajWYpokzZ84gnU4jnU5jfX098DsAkEwmsbW1hUQigSeeeIKv3xAR7QJ2kBARERERERHRxOMrNkRERERERLRj1WrVe0JqUPF4HNlsFo1GQ19ENHLsICEioh0pFAqIxWJIJpP6opEolUqYm5tDLBZDLBZDOp1GvV7XV9uX5JxkutDdlEwmEYvF2CAdAYnbQqGgLxo6x3FQKBQQj8cRi8UwNTWFbDY71PErqtWql1f3AvMq0XhaXFzEXXfdhZtvvhkvvfSSF+44DkqlErLZrFc3xWIxxONxbzwelYznY1mWN0U20W5hBwkREe0b2WwWx48fx8mTJ+G6LmzbRq1Ww8mTJ/VVqU/vv/8+DMMInIaU9gcZ6+LcuXN45ZVX4Loufv/732NlZQXPP/+8vvq+xbxKNH6SySRWVlZw6dIlnD592jfo8I033ojjx48D7c4PuX4bhoGFhYWOH1hmZmawvLyM5eVlHD9+fFc6l4kExyAhIqIdaTQa+Pvf/47rrrsOs7Oz+uKhWVxcxNLSEorFou/RXQmvVCr7fhBDeXLkpptu8jUuR00GmEylUvy1bgTq9Tq+/PJLfO1rXxvpTf3c3Bxs28alS5d8ZXFubg61Wg3DavI5joNPPvkEAHa9zI0qr8oN2ubmpr6IiHrodR2OxWJIJBId5UvKM4DQ7xYKBSwsLGBjYwPHjh3TFxMNHZ8gISKiHZmZmcH8/PxIO0eq1SqWlpaQSCQ63mu+4YYbAACff/65L3w/mp+fx/z8/K52jqD9izwA3HzzzfoiGoLZ2VnMz8+PtHOkUCigVqvhscce6yiLkp+G9UrK9PS0l1d3G/Mq0XhpNBre9TmsTnBdt6NzBO32g/j44499y8QDDzwAwzDwyCOP6IuIRoIdJERENPbOnDkDAHjiiSf0Rfjiiy8AAJ999pm+iCL66KOPAADf//739UW0DziOg3PnzsEwDDzwwAP6Yu/9/r///e/6on2HeZVovPzmN78BgB13YHzrW9/Sg4B2h2wmk4Ft20N9aowoDDtIiIgoULlc9gZDlM/c3JzvXeDFxUVvmfoOcb1e9w3EVq1W0Wg0kE6nvbCoA0fW63VsbW3BsqzAX6c++OADYIxvmBzH6RiYbmpqCslk0vtFPyi+RFAcr62teevH43GUy2Vv/SgajQYWFxe9wW6XlpYAAIcPH8bc3BzW1tYipc2ki1JG1AGF1fCgNB+0jLzxxhtotVrIZDKBTx/VajUgwuswUfJqqVTC1NSUt1zFvEo0eUqlEgzDGOj1Fxlg3TAM3HTTTfpiz49//GMAwNtvv60vIho+l4iISLO6uuoCcHO5nNtsNn1hiUQicF093HVd1zAMF4C7vb3tmqbp5nI5N5fLeeG5XE7/SodcLucCcPP5vL7IdZV9VCoVfdGeazabrmmarmma3vHZtu1alhV4zGHnInGcz+fdTCbjJhIJN5/Pu4lEwgXgGobh2rbt+04Y2ZZlWe7GxoZr27b3d7PZdPP5vO/vcSfHO8hnJ/opI6lUykVIHh5GGQnLT67rutvb25HOt5+82m2b+zWvJhKJjnQjou4qlUpgnReV1Aurq6v6og5hdQ7RsDGXERFRB9M0AxsicsOj6tZAksaPfgNTLBZdAK5pmr71g8gNWq/POJLz1G+M5UZPv6GV+NLDJY4BuMVi0bdM0koPDyKdTZlMxguTbas34plMpmM98uunjMiNvJ4P3CGUkWaz6SsHYR/9mHT95lXZrm6/5lV2kBD1r1vd1ot0gEYtu2HXR6Jh4ys2REQUSp9ab3l5OXCgtV5+/etf+x79v/XWWwEAtm0rawWT1wPanfq+z+rqKgDAsiztW+Pl5Zdf9g2QOTMzA9d1e77yoLMsq2OQ2qNHjwIRxmCRgW4ty8Ly8rIX/t577wEAfvCDH3hh9913H9B+dJq62+syIrPJJBKJjvLhui5SqRQA4JZbbtG+GYx5tX/yWtFufIgOgmq1ioceegiZTMZXxonGATtIiIiowwsvvAAAWFhYQDwe3/F7/tdff73v76izechYHIlEQl8EALh06RKg3HiNm3Q6DcuyYNs2TNNENpv1jS/Sr6DxJb7xjW/oQYFefPFFoH0jrnrnnXcAAN/85je9MLkZbrVaXhj5jUsZkU6D22+/XV8EALh48SKgdSoEmYS8Wq1WOzoc5LO1tYWtra2OcPnsJC6I6P/U63XcddddsCwLTz/9tL6YaM+xg4SIiDocO3YMlUoFiUQCtm3joYcewo033tjxa/lu+cpXvqIHwXEcrK+vA8oAbuNoc3MT+XwehmFgZWUFhw8fRjKZ9Aan2y0SV4cOHfKFb21twTRN3w253AwahqGsSapxKyMy3bWqXC6j1WpFHkDxoOfV+fn5jids5JNIJEKfwun1BI2+7ig/RPtZo9HAkSNHYJomNjc3AztSifYaO0iIiCjQ/Pw8Njc3Yds2MpkMWq0WFhYWdvUGUH4dv/nmm/VFeOONN4D20yWzs7P64rExPT2N06dP49q1aygWizBNE1tbWzhy5MiOnjgYlNoglZtL/Qmcjz/+ODB8HBUKhY5f+6N+dmocyog8VRE0Rearr74KAHjsscf0RYGYV4loVBzHQSqVYucIjT12kBARUVczMzNYXl5GsVgElBuy3RD0q7h49tlnAQBPPPGEvmhspdNpXL16FaZpotVqeeNH7Cb1RlduLm+77Tbfconbn/3sZ174uDp9+nTHr+xRP8Oyl2Uk6OkqtH+pXV9fh2EYeOCBB/TFPTGvElFUX3zxhR7U4cknn4Rt2zh//nxH58ji4mLPjuW96KSlycQOEiIi8pH39PXH6mXQyN0kv4p/+umnvvBCoQDbtpHL5XyPvpfLZcTjccRiMZTLZTiOg3Q6jVgshng8jkajgXq9jmQy6YV1a3QVCgVMTU1hamqq47vJZFJfvUMymewYqBJ79Gu3DNZ54cIFL0zGcJG0dRwHDz/8cEfcDjNeHcdBNptFLBbD3NwcoG2/VyN5HIxTGZGnqz7//HNfeDabBQD89re/7bgZCXJQ8ioR7Z7vf//7AIAPPvhAX+RTLpexsrKCZ555puOJT+nM7UUGbGdZp5HTp7UhIqLJJlNpWpblbm9vu257KlGZTnN1ddW3vkzzZ1mWL9z910/0LgB3Y2PDFy5ThwLwTW0axDRN1zAM17Zt11X2p08NaNu2m8lkvGlPc7mcm0gkXNu2vXNKpVJuKpVybdt2NzY2XHSZcrRYLLqrq6ved1dXV91cLuc2m03vGHpNNyjTEq6urnrnWalUXMMwXNM0O849LL66xbGkizr1aRDbtr1pVvP5vNtsNl3DMFzDMNxms+kWi0XfcvV7w4zXXC7nVioV75wknl0lvsZdv2VEzisojcLSPGoZkfUSiYTbbDbdZrPpplKprmkQpJ+8qk7lqx/bXubVneA0v0SDMQzDRY96W8prt0+3sqxea4hGrXtuJiKiiSM3xJZl+RoviUSi44arWCx6jSNZR6jfNwzDuwFUb34AuKZpep0fQba3t70bPrRvvPTj0Ml25eZte3vb+66EyY18r06OoIbZ6uqqC8C7OQ5TLBbdRCLhiyPTNN1MJtNxzmHx1S2O5WZUPt0amG77Jj6fz3ekrcRN0HGp5PiHEa9y7GpnQiqVcg3D8K03jvopI7lcLjSNwtK83zKysbHh21YqleoZ/7qoeXV7ezv02MYpr/aLHSREg5GOT72TV6gdqt0+3eoEqUf1+pVoFNhBQkREB4o0xtSGVLFYdKHdtEuDqxe5sVNvxjKZzL64ke9G4qRbo1Q17HhNJBKuaZq+MNM0+Qshdeg3rw5iWB0kegeS/rEsy3sSjeggUJ9iGwV5gky/XhCNCscgISKiA0Vmvrnjjju8sI8++giGYfjeXb548SISiYT3d5h33nkHlmX5phYtlUp7MjbDMH300UeA8g55L8OO162tLW+sCQCo1+uwbRtHjhzxrUfUb14dxObmJjY3N/Xgvs3OzuLy5cve35VKxRsUeHt7G6ZpYmlpCTfeeCMajYbvu0T70czMDHK5HLa2tlAul/XFO/b888+j1WrhhRde0BcRjQQ7SIiI6ECRDg11YMqLFy/6BtBsNBqo1Wq4/fbbvbAwW1tb3mCiaN/It1qtfX8jf/HiRQDATTfdpC8KNMx4lSlbv/Od73hhf/nLXwAA3/ve97wwIgyQV/da2KC4s7OzKJVK3sxAv/nNb/RViPals2fPwrIs/PSnP+0YvHonSqUSlpaWkMvlcOzYMX0x0Uiwg4SIiA4UvUPDcZyOm/a///3vAIBvf/vbqFarWFxcBJTZSYTcyKtTi3755ZdAe4adUqmEtbU1b9l+UqvVOjo8utlJvBYKBd+sP/I0itq5ItNEzs7OIpvNDrWRTftbv3l13D344IOA0vFDdBBcuXIF6XQaR44cQaFQCJ3JLIpGo4FsNovjx4+jWCzi7Nmz+ipEI8MOEiIiOjCCOjTkcXf18fybbroJlmXhzjvvxB//+Ef84he/8Japgm7kv/a1r8E0Tdx111347LPPcOrUKeUb+4PEk9rh0c2w4/Wdd96BaZq+15a+/e1vwzAMxONx/PCHP+yYCpImU795dT+5du2aHkS0ry0vL+P3v/89PvzwQzz55JP64sjk9UvbtgOnHycapZj7r1HpiYiIJt7i4iJs20apVNIX0Q7Mzc3h5MmT+7IziWgQ8iRapVLxjdGDdj2ztLSERCIxlHFPiIhoePgECRERUfuRXtu28dJLL+mLaAdKpRLuvfdedo4QtV9NW19fBwCcOHFCX0xERHuMT5AQEREREQ1R0BMk1WoVZ86cwdbWFjKZDJaXl7VvERHRXmMHCRERERHREKmDPQvDMHD06FH86Ec/4rgKRERjih0kRERERERDFPQECRERjT+OQUJEREREREREE48dJEREREREREQ08dhBQkREREREREQTjx0kRERERES7yHEcZLNZxGIxzM3NwXEcb9nc3BxisRiSyaTvO0RENHrsICEiIiIiGhK1s+Pjjz/2LRMXLlzAfffdh2KxiFqthj/96U/ess3NTQDAiRMnlG8QEdFuYAcJEREREdEQ1Ot1HDp0yPv7oYceQqFQ8K0DAKdPn8b8/DzuuOMOAMC7777rLbt8+TJM0+RUwEREe4DT/BIRERER7RF5lUaeHMlms7jtttvYQUJEtAf4BAkRERER0R655ZZbsLW1BQCoVqtoNBrsHCEi2iPsICEiIiIi2iPf+c53gPbrOT//+c+xvLysr0JERLuEHSRERERERHvkpptuAgDcfffdePTRRzEzM6OvQkREu4QdJEREREREe2R2dhYAcPToUb5aQ0S0xzhIKxERERHRHllbW0O9XuerNUREY4BPkBARERER7aJYLAawc4SIaOywg4SIiIiIaJdUq1UAQDwexxdffMHOESKiMcJXbIiIiIiIiIho4vEJEiIiIiIiIiKaeOwgISIiIiIiIqKJxw4SIiIiIiIiIpp47CAhIiIiIiIioonHDhIiIiIiIiIimnjsICEiIiIiIiKiiccOEiIiIiIiIiKaeOwgISIiIiIiIqKJxw4SIiIiIiIiIpp47CAhIiIiIiIioonHDhIiIiIiIiIimnjsICEiIiIiIiKiiccOEiIiIiIiIiKaeOwgISIiIiIiIqKJxw4SIiIiIiIiIpp47CAhIiIiIiIioonHDhIiIiIiIiIimnjsICEiIiIiIiKiiccOEiIiIiIiIiKaeOwgISIiIiIiIqKJxw4SIiIiIiIiIpp47CAhIiIiIiIioonHDhIiIiIiIiIimnjsICEiIiIiIiKiiccOEiIiIiIiIiKaeOwgISIiIiIiIqKJxw4SIiIiIiIiIpp47CAhIiIiIiIioonHDhIiIiIiIiIimnjsICEiIiIiIiKiiccOEiIiIiIiIiKaeOwgISIiIiIiIqKJxw4SIiIiIiIiIpp47CAhIiIiIiIioonHDhIiIiIiIiIimnjsIOlDo9HA4uIipqamUK1W9cVEfSuVSkgmk0gmk/qifSmZTO6b8jHKuK/X68hms4jFYvqifaHRaKBQKOybtIxCrb/HxUGM50GNe1yUSiXMzc0hFothamoKhUJBXyWSUdY73TQaDcTjccTjcTiOoy8emX6vCdVqFdlsdtfjp1/d8uuw4pptzvHTb34ehnK5vCd1Bg2X4zhYW1tDPB7f1fxDg2EHSUTVahUXLlzA0tISWq2WvvjASyaTiMViaDQa+qKhqlarSKfTiMViiMVimJubQ7lc1lc7EAqFAp577jlsbW3pi2jERhn35XIZzzzzDFZWVvRF+0K9XseFCxewsLBwYOq6UqmEVCo1VvX3QYznQY17XCwuLuLtt9/G5uYmtre3AQALCwtYXFzUV+1qlPXOQbC4uIgTJ06Mfd25G/l10tuc9C9ra2t46qmnxrbO2K17g/2uWq3i4YcfxkMPPQTbtvXFNI5c6otlWS4At1Kp6IsONMMwXMMw9OChKhaLLgA3k8m4zWbTbTabbiqVcg3DcG3b1lffd1ZXVzvyzcbGhgvATSQSvnAarr2IewDufq5iE4nEgavrxjFNDmI8D2oc42J7e9sF4G5sbPjCDMNw8/m8b13dXtQ7+12lUtmT+AlKq152I78O0uYc5FzIb5zicK/KRBS7cW9wkOxGnUHDwSdI+jQ9Pa0HHXiNRgOtVgtHjx7VFw1NuVzG8ePHkclksLy8jOnpaUxPT+P+++9Hq9XCG2+8oX9l33n22Wf1IFx//fV6EI0A456IBiG/3Kr1xezsLK5du4bTp08ra3ZivbN/BKXVOBikzTmu57KfMA572417A6K9wg4S6un9998HANx88836oqFwHAc//elPYRgGnn76ad8yaUx++umnvvD9Zm1tjY/V7RHGPREN6p133tGDImG9s38cpLQ6SOeyVxiH0Yz63oBoL7GDhHr66KOPAADf//739UVDceHCBbRaLTz22GMdv5b885//BNo91ftVvV7H448/rgfTLmDcE9FuY72zfxyktDpI57JXGIfRjfregGgvTUQHiQwiJB8ZCVoPj8Vi3sjC1WrVFx6kXq97A4rG43GUSiV9FSBg4NFkMol6ve5bp1wu+2a9WFxc9B2rUEfSj8ViyGazOxolPYiMnC77WVpaAgAcPnwYc3NzWFtbG+o+z507BwB44IEH9EX461//CgC4/fbb9UVdra2t+eIpaLDXRqPhjShdKBRQr9cRj8cxNTXlW7fRaCCbzWJqaspLa31bYcrlMo4cOeINsnb48OHAdBWFQgHxeByxWAzpdDownh3H8a03yIwKjuNgcXHR24bsT8+XhULBWx72kXwfNuK+OnK3HKeM/h/T8nC5XPbSTY9nvbwKvazKPkYR91Hy1U40Gg2k02kvbqampjrKuOM4HTNhSPx2O3Y93wR9oo6svpMyIUZ5rtDSc9AyIvVtoVCA4zheHR3rUfcWCgVfPkmn05HjVkQto/V63VfuSqUSpqamEI/HI3UsjzIdxi3PQbluq9uR9FVJfSOv2Ej9EQtpD4hR1Dt6PA6Sn6vt2WH049fzj+QHiZuo7RqJR1XYNUFImVLT4o9//KO+midKHujnfPpNq6jC4lrocad/wvbfrc05inMZZrtUPXbZhl4vlstlpNNpb/tqOyEZ0G4WUfaPgPyj13W94jAoP+vtDz1+9OXq+erHE5Sfw+j7jGl5TQ3Xy+Wg5Px3695g1KJc+xBQDqrVqhcHc3NzoflSbc/GuuRLGlP6oCQHkQz2CcC1LMu3LJPJuABc0zQ7BgLd2NhwDcPwDaYjA+ysrq66lmW5+Xze2waAjm0Ui0XfNiqVijeo0fb2tuu29yPHB8DN5/NuLpdzDcPwbTOTybiWZXl/r66ueufUbDaVvQ5O3ebGxoZr27ZvH/l8fqj77DVgncRLr8HwVHKMxWLRdV3XtW3bNU3TNzCSnIvEcSaTcTOZjJe+mUzGdZXB+FZXV71tyaBpsv0owgZmUgffkmPI5/Pe8cpxiGaz6VqW5RvIVvKfvm43iUTClwflOAzD8KVrPp/3zl0lcZxKpVy3/X0JU8/Ttm3f+eRyOe9c9fgvFotemZL40gfolQEToVVdzWbT+46eV4YV91HylSroOLtpNpuuYRi+siX7VMuH1D39HLvbHuxPrYtkUGT1nFRh8TaMMjHqc81kMh31rmwnSprYtu3bdz6fdy3L8j6yHUu7nkj5tCzLV7bkWIPiJyyeo5TR7e1tN5fLeceTy+XcXC7XdX+qUafDOOU5V9n/6uqqV39K/KlxoAo7pl7CvtdvvTOMOr9YLHrfgZL/9fzTb7tG4l6OEe086Ha5Jgi1rMj2ZbsSP6ooeWDQ8wlLq16CvhcW10LaPGp6ynmYpqmv7u1j1OeiG2a7VOoZuTY3lbakHOfq6qq3v0Qi4dVjcj4IaA+4EffvagMrS7jEo6XV40Fx2C0/V9rteij5X9VsNju+EyU/i0rAIK3qPqUdppN6YxjUeN2Ne4NRkzypHm/QtU8vB8Vi0U0kEm5eaacGlVv1WuO201fdzk7LJ41eZ+19QElh1jOyFBK10SmKxaJXoQspEHqlIxWtWrHJPvWCEFQIXeWGSkbLt23baxxLw0E/Rjke/TgHIQ0L9dykYlYr/X4bZ92ojZluHz0Ou5GLhkriXI8ntVIXlUrFi2fTNDu+I3ESlB5hgi64rrYtSWu3S37NtDtxVJKHg7YfRDoZ9O0EHaN+7q5yzKZpdpx/0DZcLZ7V76jnLxcSIdvSGwsIaXiGpXHYMfUb9/3kK7fLcYaRBoi+raDtSCM77NgNbVR5uVjrjTcpy3pecLvE2zDKxCjPVdJEP245Rn373ci2TNP0bU/iE1r+lPpMb8RLmQtaFhTP/ZRRNVzSt9lsdqwTZJTpMG55zrZt1zCMwOuWNFyDloUdUy9h3+u33hlGnS+C0tVVZkrRz1/SSq2b5Tj19FBv/FVh8ZBodwDqaSdlTj/nfvJAP+fjdjnGXrp9LyyupSNMPV6J06BtyT7CzkW/PnY7pkHIce2kXSrpFLSeepxqeqppJJ0JejxE3b/bjnc9T0mdoJe5bnEYtkzqOz2d3HbZ0MP7yc8Srh+/lDm9g8dVOmX0uBnEXtwbjFo/1z6JSwSUNynPal0ucaNve9B6m/bGRLxiAwAzMzNIJBKwbdv3iNv09DTS6XTgTCnPPfcc7rnnHl+YuO+++3x/f+Mb3wAAfPbZZ17YhQsXYJom5ufnlTX/7329ra2twMetjh07BrSPeXZ2FmgfSzqd7hijQ149ef31133h/apWq1haWoJlWVheXvbC33vvPQDAD37wAy9Mzj3s0dt+fPDBBwCASqWCdoed99ne3vbWu+mmm5RvdWeaJizL0oO7uvfee73/z8/PY3p6GuVyGbZtd+QBSc9Wq4XLly/7lg3q1ltv9dIa7bQH4BsozHEcrKys4MSJE14Y2nn41ltvBYCujyeL6667DoZh4JZbbtEXddBnaXAcB3fddRcA4M033+zIj73ce++9vu+ocXnq1Cllzf/L22qZGoUocY8B81U//uM//gMA8O1vf1tf1EEGLw47dnlEWLz99tsAgBtuuMEX/sMf/tD3dy/DKhOjPNdz584F1rv63/148MEHfd9Pp9PIZDIAgFdeeQVolw2pQ+XYxOzsLFKpFADgN7/5jW9ZkH7KqOo///M/gXadEOV8R5kO45bnZKyroP3LmAMrKyuRXksahrB4HEWd34vUyWHtmi+++MILk/yrvxJ77NgxuK7raz+Eqdfr2NraCmzTBI1n0G8e6Od8dlO9XvfSVz3vmZmZnteWsHMZ9fVRDKNd+uSTT/r+1vO1uPXWW33tgdnZWS9frayseOFR918qlWDbNh555BHfejMzM7h27RquXr3qCx/EHXfcAcMwAuuQF154wXc+/ebnMMeOHUMikUCtVut4he3ChQvIZDIdcdOvvbo3GLV+rn1qHKbTad+yeDwOAPjyyy+9sBdffBEAOtJXrbdp/E1MBwmUyvi1117zwhzHwbVr12AYhm9ar2q1CtM0Oxq6/fjggw9g23bHe4KHDx/21vnkk0983wlTq9WwsrLSsa2FhQVv+U5Igf71r3/tC5cR/L/5zW96YWolvlPyfndQY/4vf/kLAMCyrL4q+StXruDKlStAu0GSzWa9cU76IeOfmKbZEe/6OrtB8srx48c7jkfiUTqcupFGwdmzZwHlvV/ZRjc/+clP0Gq1sLq66mvcT4Jh5aswcoNx7NgxOMr4F8MwNTWlBwEDTDk6rDIxqnOtVqtotVpeo2WU5EZbyo00aMPqqiNHjgAALl68qC/qsJMy2o9RpQPGMM9JvAftf3Z2FoZhAMrMDONgWHX+MEkdGJbPo5Bjl5v8XoaVB/baddddpwd5dhKfeyVqu3R+fh6WZWFlZcUbO8VxHKTT6cC2X5A77rjD+790BkTdvwwmGlT2h2V6ehqPPfYYoHWCS2eJ2l4aZn5+4oknAABnzpzxhb/88ssdPzoNYq/uDUZtlNe+9fV1QOn0pv1pojpI0um018MrT25cuHABP/vZz5BOp2HbtjdA0muvvYb7779f20L/LMvqeDJC/US9OABALpfr+L762Qkp0IcOHfKFb21tdXQUycVJGpQ7Fbad8+fPAwBOnjypL+pJBlFaWFjAbbfd5v3aO4hms9kR1/LRn7DYDRsbGx3HIZ/NzU199VAyyOIf/vAH3H///UgkEvoqPoVCAVtbW0ilUkO58O5Hw8xXQZz2wJyHDh3CRx995JWBnbrtttuAgClLP//8cwDAf/3Xf/nCexlGmRjFucqvWrtBb2z3atB+61vfAgKeTOqm3zI6iFGkA8Ywz/X6EUF+2dutX+T7Maw6fxh6xWMUep6Iaqd5YK/NzMzANE1AaUeJq1evwjCMvtqE4yBqu/TKlStYXV3FtWvXcPz4cdx4441YW1vzbaubsA6kKPvfrU5EeapKOoDQ7izRn1wRw8jP8/PzSCQS2Nra8p7cKJVKMAxjKD9i7eW9waiN4tqnl2vavyaqgwSA18P7xhtvwHEcvPPOO5ifn/ceDXvhhRfgOA4uXrzoPVK4E7VazasodyrKL487pV6EpKAfPXpUWQP4+OOPA8P7JdsPeuSsXq+jVqvBMIyOx9R6yWazOHz4MH79619jc3MT6XS64zHvfkR51HE3/fnPf9aD+uI4Dubm5vDss8/izTffxPLycs+8Xq1WsbCwANM08dJLL+mLJ8Kw85WuXq/jxhtvxAcffIDLly/j7NmzQ2ngQHklZGtry2uUNhoNPPHEE7Asq+8Or52WiVGe626TR+O//vWvAxGeQIjSyTFIGR3EKNNh3PKc3JjK9StM0Csee22ndf4wSTxGnW1jmHaaB8bBm2++CcMw8POf/9x7uqBQKMC2bfz2t7/VVx97/bRLT506hb/97W/I5/MAgIceemigGVbUV66j7F9u4ofxOlo309PTyGQyaLVauHDhQs97iWHlZ3mKRP595ZVX8Oijj2pr7cxu3hvshlFe++hgmLgOErnZfvbZZ3HhwgXvtZv5+XmYpomtrS08//zz+NWvfqV9s39SKevvXYq1tbWOdxXDmKaJWq0W+m7f4uKiHjQQtTNHKjv5JVCWy6tIP/vZz7zwQXR73FQa1I899ljoLwdB6vU6VlZWkMlkQi9KUckNz1NPPRXYyVWv10PTYxS+9rWvAe13cIOmFXPaU0H28sYbb6BWq+HMmTORLgjODscdOQiGma/CPPPMM2i1WlheXh5JHD/99NOwLAvnz59HLBaDZVk4evRoX79AD6tMjOpc1fGdotatg/rnP/8JKI1B6ehttVqB5VOenIgyZXm/ZXRQo0oHMU55TtLp0qVL+iJA+QW/n/GuRm1Ydf4wSYfgq6++qi8C2jf7vUgZePnll/VFgYaVB8bB7OwsnnnmGaAdl7FYDK+//jo2NjZGdm0Zlajt0mq16nWoTU9P4/Tp07h06RIMw4j8mqqku/rKddT9Sx26vr4emH+q1erQfvn/5S9/CbTHwnr++ec7Xn3BCPKzPEVi2zYWFxfx/vvvd4yVsVO7eW+wG0Z17VOfAOsnDWn8TFwHyczMDFKpFGzbxuuvv+6rRKRTZGlpqe+nFoLIUykrKytIp9NeA8dxHKytreGtt96K/I7agw8+CLTfRS4UCl7jX+ZRV3/JLhQKiLXn3I5KBhC8cOGCFyYNSWn4O46Dhx9+GLZtI5fLdTwKmkwmEYvFIlcKctHSB8iqVqtYWVmBZVmRHzMUMm6JfnP06aef+v4OuijpZNCtWq2GZDLp+8WsXC7j7rvv9r0X249BLsYz7YGGW60Wjhw54nuMs16vI5lMRvr1U9JVfZTccRxfnKj/7zbuSKPRGOhcdkJ+gVf3W6/XIz+2PcjxDjNfhZFfwv7+9797Yfr+Bt2+4zhIJpM4f/48rly5Atd1ce3atb4bB8MqE6M6V+noRvvR6zD9bltPZyg3iPJY9czMjPfKlbwDr3r33XdhGEbH4JZB+i2jgxpVOmAM85zcuKyvr3fUAY1GA7Zt990h3w99n1EMq84fJrn5WV9f73hFYm1tLbCs6KR9Zdt2xzaEmu+GlQeiGiStoiqVSrh06RKuXLmCa9euwXVdXLlyZWSdI3Iug7QLe+mnXfrCCy94/0e7/Rf09DAC2oRodxoD8D0ZEXX/99xzDwzDgG3bePLJJ315q1qt4uc//3lHe1bVT35Qy+zKykpgvhxFfpanR5aWlrwn5XWD5IGd3BuUy2XE43HEYjGUy2U47XFnYrEY4vE4Go2GV49JWLfrTaFQwNTUFKampjq+m0wm9dW7GuW1T9oBTzzxROg25AcWGmP6tDaTQKbG0qdrkqmcwqaokinBEDBNnDp/uzqtVtg0tvoUf3JMUKZT08nUdfpHnzpVXaafYxjbtr3pqvLteeINZfrjYrHoW66Taa3ko09lGUamBZNz3tjYcA1tbvJ+qNNpplIpN5/Pu5ZleeljmqabyWRc27bdZrPpTdmmp5tQ00X/RI1bV8kflmW5uVzOi0PJH/qUuep5qPlBzYP6Jyzf6mR6M7SnaMvlcm4ikfDyVyKR8LYl66ZSKX0zbrPZdDOZjDddmTqFmVo+1HjWt6PmG3Xas2az6cVZKpXyxY1MA2kYhpvP591MJuPFqRou3xlG3PeTr1wt36jlvBvZlnpeqVTKN72hHLuUmyjH7mrpmM/nvc/GxoZbqVQ6ymu3um4YZWKU56pOCZlIJNyNjQ13Y2PD26fEQ5RjlTylxkOz2fTC9W00m03fFKNyvBL/et0eFs/9lFF1G/qUur2MMh3GLc+5ylSchmF49Y1t265lWYFTZYZNLxrFMOodd0h1vqvVtUHTCyMg3uUc9Ouj5AU5j0Qi4Zqm2XHdDrsmuNpU2Zn2daRYLPraOblczkunqHlgkPMJS6tuuuXXsLh229PFS3mTz+rqqlupVDqm/uy2j37PJSy+ulHjXK+7hJpe6kfNCxIfqVTKK/cSpsa1Gm9q/SnT+Qbl9yj7d7X8ZhiGV58aWlvc7RKH3fKzSs6jW30cNT+7XeoMnbSz9LpVdNtHGHvAewPbtr00lLhIJBKubdu+/CB5QuIj7LiKxaJXTtCO/1wu5zaV67Fefrrp59qn5h01rzSbTe/c1bRuKu0A0zTdYrHoVioVN5PJeNu3LCtSPUN7ZyI7SNx2pRpU0ciFWicFUP+oFbr6UW1sbPgqcfUi4SqVmvpJaPOdi3w+7xVIwzC8CkIlhdAMmGe9G6logi44lmW5GeUGUCcVgmmarqE0Pntptm+ypdKQY9bPqR9yMVXjWhoapmm629vboekWdNzb29teZSpxEbReN9vb2x0Vqb5vtC8wQflBTcegOOt2sQ4iF1w1D8kFShpcakOz26dSqQSWj0Qi0TWeg86z23eEnD+Ui5vbLhuWZbnFYtGXf4YV91HylRyHvo2w8qxqKh1JappKWg1y7LJf9UYv7CPn2Sv+ZXs7KROjPFc34PjUhlpYHR9E0lIaT7K9bucr9ahaT2cymY5GeK94jlJGg/Kauo1eRpkO45bnRKVS6dhOUP0ZdG6IWJbdIdY77hDq/LDth+WfsPRQ41u9MZI8rta7QdvW405tG0ldXqlUvDyvtzd65YGgfcpx62ESLtvV06qbsO25XeJayLUr7GOapmvbdt/nIsLOpd92YdB56Okn9PpO6itRqVS89qFsKygPy7lZ7Y6JqPm91/5FRWt3pFKpjnrZDYnDoPQIiw+3fY+h519dr/zshqRDWPqtrq66qYAfs0S/eUDItWaQewO3Xe+ZSufOdrsz2FLuw+Tapp+/TvKIep6r7c74oLQME/XaFxT/iUQiMD8goJ0qeTiRSLjb29tuIpFwE4lEaEcQjY+Y+6/MSwdQoVDADTfc0PdgeGg/Bnr8+HHk8/m+X3NJJpPI5/Mdr2MQ0d6QR2Dl8fjPP//c9/rGp59+ipWVFdi2Hfm1v0lQKBSwsLAwUD046ZjniDqVSiV89tln3qtR+sxbL7/8Mo4ePYrl5WVf+LDspF04atVqFYcPH0YikehrnCL6l7m5Ofx//9//1/V1IewwD/R7byBpWiwWvSENZBuVSsU71sXFRSwtLaHXLalck9XrRjabRalUwrVr1/TViQan95jQwZFoP842COlF7dWbq2u2nyQhovGRaL9q0s1O6ouDSn4l6ufXNvoX5jkiP3mSoptK+1H8URnnMidPB3R7MoOCVSoV1zRNPTjQTvJAv/cGcg1Vn+iRp4NUlmVFSvdE+9UolWEYXZ+cIRrExA3SOilKpRJOnDgx8C9zMoBRvyP6P//880OZS5yIhmNtbQ1bW1v43//9X32Rp16v4ytf+crA9QWRinmOqNNdd92FVqsVOnAjALz22mveAP/DttN2IY0Ppz3ZQ71eh+M4+PnPfx44Y45up3mg33uDd955xzfzENrbUAfobTQaqNVqkWZ429rawtzcnPd3vV73BrEmGia+YnMALS4u4gc/+MGORkWXKRmvXLmiLwrUaDRw4cIF/PjHP+arNURjpFwu48477wTaUyTee++9vuUffvgh/vGPf+B3v/vdyGbw2I/kFZH19XWkUim89NJLjJ+ImOeIOs3NzaFWq8EwDKTTaXzjG9/wln3xxRe4ePEiHn300aFP0YohtQtHTV6fME0TFy9eHPgmfhJIXIkoryUNIw/0e28Qi8WQyWS8V8Ycx8FXv/pV3ys68hrOxsYGrr/+evzxj3/E2bNnvXC5TQ16XUfCKpUKPv/8c3zxxRcDvTpE1EF/pIRIHnMc5WOeRLR77PaI8uogefJYKgcL6yR1oP6J+lgxMc8RBSkWix0DP8qgpIO+9nAQ6HUt+GpjVzIIdrdBaYet33sDWV+t74MGY5VX89EeHFXORb4v5HUdtZzY7Vl2ZJBnomHhEyREREREREQ0FhYXF2HbNkqlkr6IaOQ4BgkRERERERHtuUajAdu28dJLL+mLiHYFnyAhIiIiIiIioonHJ0iIiIiIiIiIaOKxg4SIiIiIiIiIJh47SIiIiIiIiIho4rGDhIiIiIiIiIgmHjtIiIiIiIiIiGjisYOEiIiIiIiIiCYeO0iIiIiIiIiIaOKxg4SIiIiIiIiIJh47SIiIiIiIiIho4rGDhIiIiIiIiIgmHjtIiIiIiIiIiGjisYOEiIiIiIiIiCYeO0iIiIiIiIiIaOKxg4SIiIiIiIiIJh47SIiIiIiIiIho4rGDhIiIiIiIiIgmHjtIiIiIiIiIiGjisYOEiIiIiIiIiCYeO0iIiIiIiIiIaOKxg4RoRBzHwdraGuLxOAqFgr6YaKxVq1Wk02nEYjHEYjFks1k4jqOvFtk4l4dqtYpsNotkMukLbzQaiMfjiMfjoefuOA4KhQLi8ThisRji8TjK5XLk5QdFo9HA4uIipqam9EU9OY6DUqkUmjeSySSmpqZQrVb1RZHtRf6Lkn9GqV6v79q5Dpvkp72It0GF1SO0/+ykPpskpVIJyWSSeZ4OnIntINEbrVNTUzu+ASASjUYDFy5cwOOPPw7btvXFRGOtXC7jxIkTWFpaQrPZhGVZWFlZGbgRNM7lYXFxESdOnMDKyoq+KBKJk6tXr6JYLMK2bdx5551eJ0iv5QdBqVRCKpXC0tISWq2Wvrgrx3Fw4cIFZLPZkeWNcc5/o1IqlbC2tobTp0/ri/aFmZkZPPDAA/jJT36Cer2uLx47O61HdsPc3JzX4a1/4vE4stnsrsf14uJix7HIZ2pqCul0etfryp3UZ5OkUCjgueeew9bWlr6IaP9zJ1Cz2XQty3INw3ArlYrruq5bqVRcAG4ul9NXpwmRSqX0oL4EfT+Xy7kA3Hw+ry+iCILi9CAZ1/MzDMNXF0qdmUgkfOt1E3Ru41oepP7v5/xc13VXV1ddAG6z2fTCisWiC8CtVCo9l++F7e3tkcU/AHfQZkU+nx953hgk/40yvkalWCz2nZfH1fb2tmuapru9va0vGjuD1iO7ybKsjjJg27ZX/gC4Gxsbvu+MmpRLNd6azaZbLBZdwzBc7FHbfCf12W5ZXV3dtWtJ0DV9Y2OjI+2IDoKJfIIkmUzCtm1cunQJ8/PzAID5+XlYloWlpSV9dZoApVIJ//jHP/TgyMK+f8MNN+hBFFGj0cD6+roefGCM6/lVq1W0Wi1f3p2ensaVK1ewubnpWzfMpJSHt956C2jHj0in03BdF/Pz8z2X74W1tTU9aGIMkv/2W3zV63UcP34cy8vL+qJ9aXZ2Fr/61a9w99138wnfIVDrIjEzM4PTp08jk8kAAB555BF9lZEKKpfT09NIp9NePl5aWkKj0dBXm3jPPvusHjQSYe2V66+/Xg8iOhAmroOkUCigVqvhsccew+zsrG+ZXDhYCU8Wx3HwxBNP6MGR7fT7FCyXy+lBB8q4nt97772nB/VlkspDr0eLey3fbfV6faxfARg3+zG+Tp48iVQqhZmZGX3RvnXPPffg2rVreP755/VFNET33XcfAMC27bFpB6fTae//77//vm/ZpFtbW9u1VwbHtb1CNCoT1UHiOA7OnTsHwzDwwAMP6Iu9Xyf+/ve/64voAHvyySd3dJHZ6fepU6lUCvy14qA4yOfH8jCeHMfByZMn9WAKsR/jq1QqoVar4Uc/+pG+aF+bnp7G0aNH+RTBLvryyy/1oD33xRdf6EETq16v4/HHH9eDR+Igt1eIwkxUB8kbb7yBVquFTCYT+JhhrVYD2q/b7AeNRsM3Kn+9Xkc8HsfU1JRvUKtGo4FsNoupqanQWRTK5TLS6bQ3oGChUPDWTyaTHQN3lctlZLNZxGIxQBloSx/EsVQq+QYGCxoI13Ec3/HNzc0hm80Gjr7fa3tOezYEdVRtiaNYLIZ0Ou1bP5lMer8Qbm1teduNOltCP99Xz3NqagqLi4v6KkDE9OqHvr1uAxKXy2Ukk0nvPObm5lAqlXzryLKYlt6FQsG3TI0DPb9Uq1UvHefm5nz5q1Ao4Pjx497fsj01PzgBgyzr+aVX+Wg0Gt42qtUq6vW6d+5B20N7v4uLi95+Y+081U/56HV+/ZSHKGR7+oDU+o2GpN/CwgIAYGFhwTu2oPwcZD+UBz1+4/E4/vjHP+qrAcqsFJKOQs5L/1vKQ6/l3fKHqFarvrIo+TiIXh5iWr5sNBo4dOiQd41T01bVq35V9Sp/w9JQZpMIykd6/gj6BOmW/6LGVy9h+UdP/271YT9eeeUVAMCtt96qLwLa51wul7G4uIi5uTkvTI5F/bXecRxvFquwsjmIarWKtbU1pNNpZLNZL7zUnsUoFot1XHMA4MiRIwCAP/3pT/qiSKLWg72uG/r2otQjCMinQfVYvV735fVSqYSpqSnE4/GO4xyFf/7zn97/9Ses94pa/3zrW9/yLRumfuozvb4NWl9Py0aj4ZWneDwemMfR/l46nfblk0Kh4IuHcrmMI0eOeAPIHj58GLEB29+99Gqv6NR40dvbIkr89WNtbc13nnNzc32XrV7L0S7DatpIHaKeo3rNlo963VKX6+lFY0YflOQgk8GpggY02t7e3hcDMolms+nm83lvAKtMJuNmMhk3kUh4f7vt8zIMw11dXXXd9mBcEg/FYtF124M8pVIpb6ClXC7nmqbpbQuAaxiGa9u267YHZZL10R7sK5fLecci62UyGdeyLO9vGbDQsizfoIWJRMJNpVJemAzMpQ+MF2V7q6ur3vklEgkvXvL5vGuapi9uxE4HVuv2fRn4LJfLeXGrxpWkgYiSXv2Q7eXzeS+OMpmMF2+qTCbjGobhDdBm23ZHfhIS9/o527btnZuUMz2/yACC+Xze275pmr7tuF0GSJMBQzOZjNtsNt1ms+mdkxxnr/Ih+1fTwTAMN5FIePkEAQPDJRIJ1zAMb8BASXvDMLz41c83rHyEnV/U8hCFpH8mk/GVG8MwfOehkjw7yP7cMS8PknfUekQdCFA95mKx6OWroHRyu6ShCFoeJX9IHKr5Wb6jp4ucUyqV8p0TtHrb7ZG2UepXdV1DG+Rc0kU/36iCjq1SqXjhCLh2S32jHreaZuq5uwPkv6Bjiios/+jpH7U+7KXZbHbsS2eapneuUn+urq56eQiAu7297TabTa/uQzsfDYOalmp853I5t1gseucQVHdImdCvW1FErQd7XTfU8hi1HnEj1mPb29turj1YKdp5NNdui6nr7ZScS1Celnwp57lbJF/o8eYq9dAgZSKqfuozSXspP82A9oeeltIuzefzXesnqbelTEo5REg9LGmp14tun/V5FEFx4WrXeykv+S7t7Sjx1w/JO1I+bNv29i3xoqeHXrbk77DlUjfJtUbiLyjfqmXbNM3AuM7lcgOnA+2eztx+QDWVxkO3T1AFPc6kgKqNhkql4hU80zQ7LoRSoRnKTZ0aJhdxV7mwI6DykjhTb6iloSGNBb0CCLo4q9sQ+Xzet04/25NRtdWGj9s+PglXqRX8ILp9X00f9djlQqjHadT0iko6ulRyU6E2OCTO9EZYs9kMbKB1O+egi7Za/vR9yPb1m3VZX5dpN1hVcvHS99urfMixJhIJX2MlqBGz3e5E1fcddL5uj/KhLtep3xF6eYjKsqzAhmW3RqfE2SD7c3vkjb0uD4l2B5f+vaCGjghLJ7fHMrfHclkWlD/kRkXNU2Hxmmk37vVzstoztal5Lixt+6lfZRt6fpfjCzvfXsKOze1SxqSc6uVF6hR9W/3mv27HFFVQnAxSH/Yi8a/WdUHkXIvFou9ar+5XwuU49WvmTkl6Nts3gHKuco3W87i7wx+x+q0H1Xwi9OtGUHkJq0f6qcckbqSDqtlsduT7nQgq0+oNpF42dkNQvNm2HdiJNWz91mf9tD/kRlmvV6TeUsuftMv0dd0uHVdh9WI/9XlUQXHhavk4qL2tl61+4i8K+Z4qrN7uVba6LZe6Qt9mULxIWkKbwU5YltVxzaLxMzGv2HzyyScAgEQigXbHkO+TSqUAALfccov2zf3h3nvv9f4/Pz+P6elplMtl2LaNe+65x7euvELUarVw+fJl37Jbb70Vp06d8v6enZ31RhEPG6zu2LFjQHskdHks87nnnkM6ne54len2228HALz++uu+8Keeesr3mJp+zP1sT0bVvvXWW32PicqgdXsxr/29997rO/Z///d/B7QBgQdJr25KpRJs2+4YkX5mZgbXrl3D1atXvbCnnnoKAHDHHXcoa/7r3e9f/epXALCjgTf1WTxU8XgciPjOs+M4WFlZwYkTJ3zh09PT3mPlQY85B5UP1RNPPOEb1HB5eRmmaQLtV/MA4LrrroNhGH3XEUHlo5de5SGKcrmMWq3m1W2qU6dOwTAM2LYd+qjvKO1FeajX69ja2gqsR77//e/7/t5NQfnDNE0YhoGvfe1r2tp+jUYDKysrga+NXrlyBdeuXYuU5/qpX8+dOwfTNDteRdX/3g2Sd/WZFILyvCpK/hulYdWHKhlcWU9D3bvvvgu0x3OQstVoNGDbNizLwieffOK1AeR1lqNHjypb2Ln3338flmXhT3/6E/7zP//Ty6Oyv6A6Vs3HQa9ahdlJPRh03ei3Hhm0HvvP//xPoJ2eoyhb6mtj3/3ud/HBBx9gdXUVm5ubHee1W9TXMk3TxPnz55HJZFCr1SLVY4Popz7rt/0h8SiD34pvfOMbgDamyoULF9BqtfDDH/5QWfNfZKyRlZWVSHVUP/X5sIS1t9XxyPqNvyhM04RlWXpwV73KVtDy//iP/wAAfPvb3/atG2RmZgaPPfYY0E5XVbU9S6Bc92l8TUwHiTQepILQXbx4EQDwgx/8QF+0b/31r38F2hWI/k6cvk436k1z1IZJrVbDyspKx35lfAN5txvt0bFrtRpuvPFGFAoFNBoNb9q5Qba3Xw0rvcRHH30EBNw86BzH8eJPv6ACwPe+9z1gTEa2l47O48ePd8SRzBjywQcfaN8ajDSo33nnHUDpWDp79iygjNsz7JlKopSHKP785z8DIVMoQrnpkRumcTPs8iDpJI3TcXb27Flcu3YNMzMzaLTHytEblQDwP//zP0CXNI4qav0qjTu5id9rU1NTehAwhPg4yEqlEizLwre+9S2vvpeOCdM0feOXvP322wCA+++/3wvbqXq9jlarhbm5OXz22We+G5Tz588DAH784x8r39iZYdeD/dYjw67HhiWfz/t+JNzc3MSpU6cC2wC7Rf8B88qVKzh79uzIZmTqtz4bZftD7kGC2muzs7MwDAOIOJNP1Pp8t40i/q5cuYIrV64A7bolm83i3Llz+mo7duzYMbiui2PHjsFpj3Uo4zgFeeCBB2AYBs6dO+f7seu1117zfnSk8TYxHSQi6CJZLpfRarVgGMaB7NVrNpsdT8zIJ8pN16AXzFwu17E/9SPOnj2LSqWCqakpLCwswDRNLC4udgzuFHV7+91O00tEvdDIRSuM+qvAuMzwtLGx0RE38tnc3NRXH0hQXQFl0N8//OEPuP/++5FIJPRVdiRqeeilV/rffPPNwC7+aj6oYZUH6ejaL2RAuKNHj+KGG27AmTNn9FWGemMVpX7d6RTQwyY3t/pxffrpp0D7hov+j7R19F9OpWPiRz/6ke9m9OLFi0NvF/33f/830N62Wn6lo940zaE+LTDsenDQemRY9RgNj15vRDWK9kevTgvpuPzss8/0RYGi1Od7ZdjxJ4NcLyws4LbbbkMmk9FXGQqnPUj/oUOH8NFHH3n1ZpDp6Wk89thjaLVaePLJJwHliU/9aTIaTxPTQSIXtaBRsF999VUA8B6JOmiCHt8c1E033aQHhZIe8Sjm5+dx9epVFItFmKaJpaUl/OQnP/Gt08/29rNhpZc0dHs9sqg+xt9r9oSgxxH3gvwquBvkcW/HcTA3N4dnn30Wb775JpaXl4d646CKUh56kfT/8MMP9UU+YU/VjYthlYf9pFQqwTRNmKaJq1ev4tSpU95rIKqvf/3rwJAemd6P9evTTz8Ny7Jw7tw57+nGarWKlZUV5HK5od5oHwR/+MMfAO11SemYMAzD97SodKborwDtlEwXKjPuCHmKJehVmJ0Yl3pwEuuxg2oU7Q+z/Urvxx9/rC/yCXqNK8g41+fDjL9sNovDhw/j17/+NTY3N5FOp0N/3NqJer2OG2+8ER988AEuX76Ms2fP9ry+yFMk8mrUG2+8Efg6LI2niekg+cpXvqIHAe0evfX1dRiGgQceeEBfvK9J41kfz0DU6/XA92518l3LsiIXbNM0UavVQrevThuo/j+dTuPy5cuwLAtbW1veDXs/29uvhpVeQirv9fX1wO1Vq1VUq1XMzMx4F+e//OUv+mreL2vj8GusdOasrKwEduY47enjhkHeD5bX7t544w3UajWcOXOm54VxJ6KUhyhuu+02oEtDSX5lj9rg2m3DLg9yA/Tyyy/ri8ZONpuFaZre61xhpMO6VqsF5g3HcbC2tqYHd4hav0pe2draivyL+yhNT0/j/PnzmJqawokTJxCLxXDixAnk8/mecXfQSNqoY0vpLl68CFMbb0E6JvSGu3SmBI2JMKh6vQ7btpFIJDo62+V1nrB2mFoH6N/tZtj1YL/1yLDrMRqefuuzUbY/5Gm4S5cu6YuAdrk2DCPSj5RR6/PdNuz4q9fr3hhco/qxSjzzzDNotVpYXl6OfB8kT5EAwG9+8xucO3fON8YjjbeJ6SCRxyg///xzX3g2mwUA/Pa3v/Vl+kKhgKmpKUxNTaHRniNb5tmWuavL5bJvvu8wjuMgm80i1p6fG9p3+6kQ+nHHHXfAMAzUajUkk0nfvODlchl33313x6CcQY0rGaTy0Ucf1ReFevDBB4H2u4YyjgLaN9vZbNbXw7uysuJrOExPT/sGR0Of29spx3ECK++oBv3+IOnVzT333OMNQPfkk0/64rhareLnP/+519CUx/cff/zxjkacvPOq/uoo33v//fd965fL5cA8NAzSmZNIJNBqtXDkyBGUSiVv//V6HclkMnJDV6XXC47jYH19HaZpehdeabioj7g6juM7fz3u+iG/gEcpD1Gk02mYpolWqxVYx1y8eDHwRmXYxqk8oD2WTlinwU7Sb1jq7TEarl275jueoDw6OzvrdVyePHnS18hvNBpIJpNd46her8NxnMj16/z8vNeZmsvllC357VY81ut1nDx5EpcvX8bVq1fhui6uXr06slcWJL7Gkdw4qYMiqqRzQn9CI6xjolQqea/XqGOPFQoFxGIxr+3UD+mA1wcOl/rWsizccMMNgfWFvAra74CMw64H+61Hhl2PlctlFAqFkefDxcXFjrZtqVTC1NSU1wYWyWQSsVgs9IZ8GOT6ruc9x3G8cSyC0rebfuuzUbU/AOCXv/wl0P5BSx/rr9EeRPmxxx7renMu34tan++EfoxRDDv+pD7RO7ek01MMo6xIB6v6mrm+36D9qE+R6APZ0pjTp7U5qNTp45rtubdl6ix9mj2Z/k6mr8q35y5vNpve9FGZTMbN5XLeNHUImNNc5HI5t1KpeN9Vp9eTaaUG0Ww2ve/Leelk+tagT9C0rXJusi2ZLkyfXkzdbth0VTLFmf7Rp5GTMJlOS+Yx16cCi7o9mULN1OYgV6cJVI9ZDc/lcqFxGSbs+2r6pFIp33dkyjDDMHz5Jmp6RSVTOsq+EolE4PSfrhJvlmV5x1SpVFzDMLxpz1RybpZlufl83k2lUm6xWPSFSz5Xj0Pdb1OZRljfh0yTlkql3FQq5csfskz/qPk0SvmQ5YZh+LafSqU64kjSTI5V0lryZSKR8PYfpXyEnR8ilocotpVputWpOzPtqWH1OqvZbHrno5erqPZLechkMm6lUnGLxaKvbpH62tXqRb28qNsKOpZuy3vlD0kzKVuSt9RjlO+paYx2PpR41verxrOUWRG1flX3l0gk3I2NDXdjY8O7nqKdvvq+u+mWN5rKFJDqtJiuMv1lLpdz8+2psPP5vFupVNyKMi2rbCdsH2H5r1t8RRGWfwapD6OQ+NDzqttuhwQtMwzDtbSpgeW4U6mU184RctwIyF+9yLVHJ/Eh6RdU76jr9KufejDKdaPfeiRqPaZe28LSX743SDy4SjnvlpdXV1fdYrHoHff29rZbLBbdTCbjbmxs+Pat5nF0aQd3I3kzKG+IVCrlpZm+HznOQfbdb30Wtf1ht+850KXe0vOX5CtDa49YltVRRl1lO5ZleXWgiFqfRyXnnNLaK5J2UdvbUeMvCnUfqVTKzefzrmVZXryYpulmMhnXtu2eZavXctmmXAsymYybarcT5djDymReufej/WOwO/N9amNjw1dpqIU8iNpIENJgUguyVBC9SCFRK0spYP3SL0ryCTqf7e1tX2VvKTdfQrYnFa0UetM0Oyp3aTyon7Cbt3w+7zX4jPaNtl45m6bpS5ew9dwI29OPC+2GRK9jVit5vQEZhf79bumjh0m4iJJe/ahUKr7zT6VSoeeoN/JSqVTgDZzbPk7Zrmma3nqJRML3vbC4l/Kgf0Sx3TlnGEbHhUVt3Mr+1XwaJZ5d5djkwirrpVKpwMaW2pCTvCeNM2nshJ2vLuz8+ikPUdi23RFXQdsLSw9EqNt041we1OuANHYqSkegpHtQOkoDSA/vZ3nQdvX8sb297dVz6vla7RtMvTxIGsv2LMsKLLe9bv561a9CT5NMu1Nd/t9v+ujxgXYeCMqTalypN6pBH8Mw3I2Nja75TA+TcDdCfHUTlM7d0j/oXNFn2ZP40POH265XTNP0hUndJflWyI1H0DlLXWKaZsf3upEbRrU9JdR2lb4/EXRj3I8o9WCv/KCKWo8Ivczo9VjU9Jc2Y9Ax9aJeVxBQ7wRBO13Cbl6b7U510zQHOi65VsjHNM2OuFNJnlXzeC6XCz2+KPS06VWf9Wp/hKVllPxVqVQ68oneBhfqdSIXcFMftT6PIqi9op8HutRxal3RK/76IccFpd0mnR3S/ghLD9FruatdC9TjlfwbFP9iu90JR/tLzP1XJqcAhUIBCwsLsG3bG+grm82iVCrhb3/7m/eo29zcHKanp3uOvpxMJnH16lXfKwjxeByWZY300cQoqtUqDh8+jEQi0fM8iA6KZDKJra0tVCqVyI9YE9F4qNfrWFtbw3333Qe0BziUsYPQHpxdv+YedHNzczBNc+RtikKhgBtuuGHX3qmfmppCJpOZuLFl9pq0Wy9fvtz19Q60183n8yN/jSAWiyGfz3uv0sXjcVy8eHFk0wET7cTi4iJuuOGGkb36SaMxMWOQDOKdd96BZVm+SvfKlSs4evSod6Fw2iPARxkBfWtry/f+r7wTfOTIEd96REREFM5xHBw5cgRPP/005ufnMT8/j1OnTuH06dPeZxI7+8+fP4/19fXAcTyG6Z133ulr7IydkLEvfvGLX+iLaISc9hhb165d69k5IuuOunME7XFoZGbKQqGABx98kJ0jNJYcx+HUvvsUO0i62Nra8kaWhtIZIgO+QhkBvtfAQjKg0Xe+8x0vTAYY+t73vueFERERUXcPP/wwWq1Wx+C1qlKp5A1YOClmZ2dRLBZx8uRJfdHQlEolnDhxYlduSh3HwXPPPYc333yz5006DdfDDz+MkydPotVq9exwe/7553H+/Hk9eCTm5uZw9epV1Ot1vP766/xlnsZKqVTyBmN+8sknkU6nd6WupOFiB0mIoA4Nmcde7QyRGS1uuukmrK2teY+1FgoF30jf7733HgDg1ltv9cLkUeDZ2Vlks9meF6BRkuO7evVqx8jMRAdRo9HwHr2X/E9E+4PMPvHd734X6XQahULB95mbm8NHH300kTdP6XQajz766Eim81xcXMT111/fdea+YXEcBz/5yU9w/vz5XXkygYC1tTWsra0hm83iRz/6kfcKlUwzr89e1Gg0sLi4iB//+Me7lkazs7OwbRsnT57ctU4Zoiiq1SqOHz+OO++805vZ6emnn9ZXo/1AH5SE/kUG7VEHi5LBeFQy+I5hGB2DNKkDYCUSicAB0mQgoaAB9XaLPjARAgZtIzpIogzKRUTjTQY0lEH6ZAC9oIEVJ5EMULgf2bbt5kNmtKHRkfKkD4KKkEF794IMdho0GDHRXpJBi9FlsH/aHzhI64jMzc3h5MmTuzaAGRERERHRQZZOp/GjH/1oV55iIqLJxFdsRqBUKuHee+9l5wgRERER0YCq1SqSySQcx/Fe/WHnCBGNEp8gISIiIiKisVMoFLCwsADLsvDrX/8ax44d01chIhoqdpAQERERERER0cTjKzZERERERERENPHYQUJEREREREREE48dJEREREREREQ08dhBQkREREREREQTjx0kRERERERERDTx2EFCRERERERERBOPHSRERERERERENPHYQUJEREREREREE48dJEREREREREQ08dhBQkREREREREQTjx0kRERERERERDTx2EFCRERERERERBOPHSRERERERERENPHYQUJEREREREREE48dJEREREREREQ08dhBQkREREREREQTjx0kRERERERERDTx2EFCRERERERERBOPHSRERERERERENPHYQbJLkskkpqamUK1W9UVDUSqVkEwmUSgUfOHlchlTU1NIp9O+8H6N+vh72cv9V6tVZLNZxGIxfdGB1Gg0sLi4iKmpKX3RnqZDPxqNBuLxOOLxOBzH0RdPjG5pOW66HSvz3XCtra2NfVzScCwuLqJer+vBPoVCAbFYzPdJJpP6aiORTCY79q23Yw4CaaPtVryOA8lXa2tr+qKRU68nrOu6cxwHpVIJ8Xj8QJY9okGwg2SfazQayGazyGaz2Nra0hfTDpVKJbz44otYWVnRF41UUKMxqPFYrVY7luvr9KNUKiGVSmFpaQmtVktfTPtIv2kZlpfC8pO+Tth6UfR7rDQYx3GQTCbxve99D/Pz80A77qempjrSUj7JZHJPbnB2ol6vIx6Pd5yLfObm5rC4uDjWnVhBBkmrX/ziF1hbW0OpVPKFB6lUKnBdF67rYnNz07esXq8jnU774rCfG89SqYR0Ou0dv3x3c3PT22elUtG/diAUCgU899xzbKPtkmq1igsXLvB6EoHjOLhw4QKy2Sxs29YXE00ulw6EfD7vAnDz+by+aORWV1fdSqWiB+9L29vbHXHYbDZdAO5uF5ft7W03lUp5+wYQGs+yXiqVcm3b1hf3bS/Od1CpVEoPIkU/aWnbti/PmaYZmp+azaa3biKRCF2vH/0c617bb/mu2Wy6lmUF1iEbGxuBcb+xseFaluUCcC3L8i0bd2q9rZ6zWq8ahjGUfLubBkkrSftisegLF9J+CMobruu6lUrFNQzDzeVybj6f9/YDwN3e3tZX99ne3vbWz2Qy7sbGhttsNvXVXLe9H+xRO2bUJN0SiYS+iHYoqN3muq6X78LyNf2fvbyH2Av77fpNu49PkNCOPfvss3rQvqX/+gYA09PTetCumJ2dRalUQiaT0Rd1+Mc//oFMJoNSqYSZmRl98YFVKpXwj3/8Qw+mAc3MzOCll16CZVm+sCDT09MwTROJRAKbm5uh6x1E+zHfPfzww5ibm/OeHFFdf/31ehAA4NixY1hfXwcA1Gq1SE8hjIuwelvqVdM00Wq18Jvf/EZfZawNklbT09M4f/48jh8/3vN1myAvvvgi/va3v+Hs2bM4ffo0rly5glQqBYRcM0W9XseRI0dg2zYqlQqWl5dx7Nix0LQ5yMLSjXYuLA9OYj6j3vbj9Zt2HztIaEfW1tYOzGN59Xp911+liWJ5edm7YT1x4kTHY+HZbBYzMzNYXl72hR90juPgiSee0INph+RmCgBs2w59babRaGB9fR2/+93v9EUH2n7Md+VyGevr6zh16pS+qKeZmRkkEgkAwLvvvqsv3rcefPBBAMDFixf1RftWt7SanZ1FIpHAyZMnfeG9OI6DpaWljpvNn/3sZwCAa9eu+cKFdI4AwKVLlwI75oh2alzbbTSe9uP1m/YGO0hoYPV6HY8//rgevC85jtN3w3E3ra+vwzAM2LaNhx9+2AtfW1vDlStXJq5zBACefPLJA9M5N25mZ2exuroKAFhYWAj81TmbzeKFF17ouHE66PZjvnvkkUdgmiZmZ2f1RX0Juxnezw7iOSHkvP7rv/6r4+mSXqanpwOfDvvnP/8JALj//vv1RXAcB3fffTdarRZ+//vf7zjfEQUZ93YbjZ/9eP2mvTExHSTlchnpdNobQbxQKHiDhSWTycAbALQfxZqbm/MGJstms75f8GX0ZxmdXAbBiykDFvYaTVsGP5PjkZGk9ScFhD5YWjKZxIcffqivBkQYOV0/v7m5OZTLZd86QcdfLpdx5MgRbwCsw4cPe8cSNMCoet7q8rDjUgXtX8LX1tZ88SXrTU1NYXFx0bedMI1GA4cOHUKtVgPaN4RyfEHK5bIXZ3NzcwPnnX7MzMzgt7/9LdDuLCmVSiiVSjh//nzHYHr9KhQK3oCGU1NTXZ8YiJIOMkDi1NSULy/JgMJqPtfzmqhWq748ro+unkwmvV+Ntra2OvJZtcfMQ1HLXL1e951zo9Hwjisej/d1o4H2can5Xz8vBNQpaHeESRql0+mO4xRR0zKKU6dOeb9Gnzx50rfPtbU1fOUrX8GxY8eUb/Qn6rEepHxXLpd96T83NxeYh8rlsm871Wo1Up0TpFqtwrZtHD16VF8UmaT9zTffrC/at7744gsAwK233qov2te6pdX3vvc9AMDbb7+tL+qL4zh46qmnkMlkAuuACxcuwLZtJBKJPXtyRNoDUsdI3RlUdtRr+lR71r+5uTl9tVCDfF+t/3rV6Wo7Ip1Od7QjZZl8pM7Sw2NKvVRQZi6S68ww6x3HcXz1s9Dr7d1qt6nt5m7Xbv0akOxyfxDEcRzf9WZubg7ZbDYwTdT2r5oeMa3N3O/9S7/r9+I4Ts/rtX6dlngIWl/dVrfj6dWG7ret1Ov6Le07iaupqamOfSKgnCwuLnrnol7f9e1jgPsf2kP6oCQH0erqqm8wwVwu55qm6SYSCW+gsaDB2jKZjGtZlhe+urrqDYAmg4ytrq56A0ElEgk3k8m4mUzGRXuAw0ql4g1+FDRYVLFYdAG4q6urbrPZdJvNppvL5Tr2I7a3t13DMNxMJuOtr25fHWApn8975xg0MJicnxyTbBuAu7Gx4brtQdO6Hb9sXw23bduLE9M0O87BdV03l8sFnp8ubP9y3nK8uVzOS9tcLueFhw1KF6TbIFWy/2Kx6CYSCV/cmqaprx4p7wxC8oZhGK5hGD0HyOslk8m4hmF48VqpVHwD8Imo6SD5X+Imk8m4rpK3VldXXVfLI3oaFYtF1zAML1wGGJR0FpX2gH563i4Wi14ZVM9BXY4IZW57e9sLl/Uty3Lz+bxv+3q9EUaOV+KkqQxyqua5sDoln8+7pmn6tqGKmpb9aDabvjLmKmm5k3wc9VgPUr6Tc5a61bbtjuN124M5qgPlRq1zwkgeDqrXhJxT0HFvb297y6Lm9V7Ua28/Hz3Oe5HvSb4RzWbTK0t6PtiJ3TivnaaVLFfLr5QxPZ50zWbTLRaLrmmaodd213W9uM3n8157C+18GyUfdlsnqkQi4btGyrb1ukvC5dzVgaqjiPp9td6IUqdL/WNZlu8cgvKtbdteuFpXqXVYKpXqSC9ph9m2PdR6x7Zt37lJeur19qjbbXLcUa/dcg2QtKy0BydW81EviUTCF9eyTfX4pD2ol3vbtr04kGPo9/6l3/VFWDxKHsoo9xwSh5JnK9p1WuJb0lXC5RqZSqV8+cMKGAA8E6ENPUhbSS2Hqma7raNuX85JXVcvJ/l2HaemmxxTWB0p5S5oGY2PaFeAA0C9OEpj2dU6BdSCJJWanoGlklErEXXbUpi3t7d9FZB8Tyo9V6kM9QLsKrOSqMukAOsF2w05LrdLZSA3ierxuEpjWr9ABR1/t3C1otfj0G2PLi43ClGE7UeOV69s5Pz6Gak67ALhah0kKqmE1bTuJ+/0Sy5Wcs47Ieerx6nkGQQ0EMPSQbalHlOlUvHiIKhhrJYbWc+27cA4khkA1PIQlrdF0Dn0W+ZcZSR8PVwaCWp90o1sX427sHOQ8zW0hpnEj2EYvvUHScuo1FkzKu2Lfz9lVzfIse73fCfb0euPZsiNelOZgUX/jqzfT4MdSqd3kKC4bzab7sbGRuDx7RdyTnqZkzjRy/R+sNO0UhvyIqxM6iTe5KPXT67WSZPJZLxrY6V9swntJl4l56aXw37JMehlNKgeybdn5VFJWyuKqN9X652gOl3vfJC2jX4jG9YJJm0ePU93q68ymYwvLoZZ77hd2lS71W4LK+dy7VbPUdJBLwOy/aD4C4KAujafz/uOr1uaBOVRNe9EuX/pd323Szxm2j88qCR/68cZFt+ybbP9o7FQt6PnZfX6LGT76jH221YKi3vpgNHPHwHXczVc/cFD9j/s+x/aGxPzio249dZbfQPVzc7OeuM3qAM9Pffcc0in0x3v199+++0AgNdff90Xjva25V3d2dnZwPd2VRcuXECr1cIPf/hDfZE3tsfKygoajQYA4I033kCr1cKJEye0tf/vuKJ64oknYFlWx+OvZ8+eheu6SKfTvvB+zczM4LHHHgPa56mqVqtotVqBj+b264YbbgAA3Hvvvb60+vd//3egPbvLMOnxEo/HAQB///vfvbBB8k5UMnMI2jMV6I859uPcuXMwTbMjD+h/9+Pee+/1/j8/P4/p6WmUy2XYto177rnHt67sp9Vq4fLlywDgzSjxwAMP+NY9duwYXNfd8Vgr/ZY5KCPh33fffV4YAHzjG98AlEf1ezFNE4Zh4Gtf+5q+qIPMeHDrrbf63t+XOkVebROjSEtx7Ngxbyalw4cPY25ubkdldxTHOu757qmnngIA3HHHHb7w6elp/OpXvwLadbIaLsLqnC+//NIXHmZrawvoYxYNefz3q1/9Kh555BEcPXoUlUql4zj2E3kFNBaL4a677sJXvvIVFIvFHafrXhskreSVovfee09f1NPm5iZs20Y+n4dhGGi1Wjhy5IjvEfS//OUvAADDMLC8vOzVWfPz8/j9738PAFhaWgp9rH4YrrvuOhiGgVtuuUVfFEgfl2V6erprHOr6+X5Yna6Oi+C0B8a1LKujHTk7O+vNIKTOwHTHHXfAMAyUSiVfeszPz8M0TWxtbfni3HEcXLx40VfvDrPe6Wa3221h1+7PPvvMC7tw4ULgden73/8+0K5H9Vctwjz11FO+dfVr0KCi3r+IftfXOY6DlZWVjnuO6elprx754x//6FuGgPiWOIzH4x35TbYzaBu637ZSmP/4j/8AAHz729/WF3UlbaGZmRlv/7t1/0OjNXEdJEHURqu8K1ar1bCystLxLtnCwoK3fKdk9Pyghuvs7CwMwwAAvP/++wCAt956C1AuIoNyHAe2bXdUPsP2wAMPwDAMnDt3znexeO2117ybgoNolHlH3m3N5/NA+71b/X3kKKSSlkbPKP31r38F2h0Eepzo61y5cgUY4fR8/Za5YTp79iyuXbuGmZkZNBoNFAqFjobHIHYjLZ9++mnv/3rjpx+7caxiXPKd4zhemQ/avowLYdu2r2Nur7SfLIXrurh69SqWl5c7bhr2m0ql4p3TtWvXUCqVOm4A96O9SKuZmRmcPn0aly5d8jpJ/vSnP3nLu43tMj8/783IJh13ozAzM4Nr167h7NmzgDImQ9A+77nnHhiGgePHjyOZTHrjE0XtPNvp94NIx21QfQHAmx1InYFJOmX09KhWq16cq9PhXrhw4UC3w/r1wQcfwLbtjmvF4cOHvXU++eQT33eC5HI51Go13HjjjSgUCmg0Gl6ZGYWg+5du+llfzvf48eMd8SJl6YMPPtC+tXOjbEOHkR9Djh075o1t0mscoW4m9f7nIGEHSZeLUC6X8zVA9M9O9Srk0sCQXu6gi/sgolTywzA9PY3HHnsMrVYLTz75JNAeBGllZWVoPerjahR5p1Qq4cqVK3j66adx+vTprlP/9jLIr4c71Ww2O+JBPtJ46FUmdqrX9vUyN2wyCNjRo0dxww034MyZM/oqfduNtAyrI/u1G8eq2+t816u+VX/1Un9FIxpns7Oz3q+k/dSXOxksuF8yYOMf/vAH3H///d6g06qZmRn87W9/Qy6Xw9bWFu68807E4/GeN49ip98PIh23Yb71rW8B2lMnaA+sjfYv8OLFF1/ESy+9BNM0sbKy4rUVXn755QPfDuuXZVkd1wj1E6Xz8ezZs6hUKpiamsLCwgJM08Ti4mLfbbSo+r0297s+AGxsbHTEhXx2OklAmFG0oXtx2gMGHzp0CB999BHOnz+vrxLZJN//HBTsINHcdNNN3v/V3vlRkFclPv74Y32RjzyeNizyiH8/jwwOSnpR5bWFN954A5lMZqBKej8Zdt4pl8t44oknsLm56cVd2NS/40p+FetGykTYLCM7tVdlDu0OLtM0YZomrl69ilOnTu34aTDqba/znfpKVa/XCqI0wA+CoJH+o3zGfdT/g3peYaSelFcm1LCrV696YSp13VFxHAdzc3N49tln8eabb2J5ebnrI+3T09M4e/YsbNtGJpOBbds4fPhw5E6OnX5f9/Wvfx2I8CSj3uEzOzuLRCKBWq2Ger2OarUK0zQxPT2NBx98EGg/OVIul3H06NED3w7rV61WG0qbeH5+HlevXkWxWIRpmlhaWsJPfvITfbWhU+9fooi6/p///Gc9aOSG3YbupV6v48Ybb8QHH3yAy5cv4+zZszuennxS738OCnaQKNPiWZblZVzTNDveK1VFnYqsG/kl5dKlS/oioN3AMAzDq8TkYvjaa69pa/ZnZmbGe5XgjTfe0BcD7Wm4hkF6UdF+X/bcuXO+dyIPomHnnXq9jkceeQRvvvmmr2KdmZnxHuOVqX+jUt+rHfVj/dLY09/LFfV63Tt2eSrm1Vdf1db6l53my37L3DBls1mYpuk99j0su5mWO7Wbxzou+W5mZsbrgJHxGVQSD/rNzrDIdj///HN90Z7Z3Nzs+EUwymdUv1YOy344LykLw+wEVh/bn5+f9zrug8q4vIIzqvyOdrumVqvhzJkzPW9yZKpZKNfUYrEItJ++6GWn3w8iTzK2Wq3ATlUpy0Fjz8lrm2trazhz5ow3rpL8av3yyy/j1VdfPfDtsH7JmBXya79ubW0tMD/r1PZdOp3G5cuXYVlWxxgwwxJ0/9JNP+tL5/7KykrgsTvt6X+Hbdht6CieeeYZtFotLC8v94yXqCbx/ucgmbgOkqBfNaST4NFHH/XCpLf9+PHj3nuEaDdms9nsUH4F+eUvfwm0b271XxoajQZs28Zjjz3mFVa58IVVVuhjwEgptI8//rhv30577nK5ueiXfh7QelH1gZTGWb1eD7yx6mWYeader+PIkSN44YUXAuMtnU57A7Zls9nQfKGbbw/chvajjGEGOX+dDB5Xq9V872ij/Yv93Xff7TWwf/aznwHtMqG+L412A+XTTz/1hakcx+l5/v2WuWGp1+totVq4du2aL071m9ZB4ns303KndvNYxynfyatUjz/+eMe5ya/E6iCtwyQDVfbzGkSYer2OeDyOqakpr/w4juM9OaGXqXEn17tYLIa5uTlf2szNze3rpzvCyOtkw+gEfvHFF5HJZDoGEn3mmWcAbRBRtON7fX0diUQi8HoWRvJX2A2TTjrA1TzvOI4vfdX/6wMp9js+zU6/r5uZmfEGxpZxF1TvvvsuDMPoGFQa7X0b7cFaZ2ZmvLSZmZlBKpWCbduwbbuv+N9PBm23ydhaKysrSKfTXp3uOA7W1tbw1ltvdeTzIOprTGjfJKuDiEN5UvD999/3rVsulwPvUUTQsqD7F9Hv+rqZmRkkEglvMGZ1AOB6vY5kMjnUjlYxzDZ0L3L9lidW1Ndc9Q6xQfLVfr3/oaC5iw4omdoJ7SmoZOolmU5Kn5bKVab31D/61GQyZZkRMLe4q01lpU8JKtOaGcrc67Ztu5ZldUwd5yrTkxntedUr7fnHZQo2CZfjUKfXUo+5qUwXK+eUSCQC46Lb8cvUpVZ7znN9iiwhx6FPHRdF2P7Vc9CnhZMpu8LSJIj6nXw+721TneZUnUasqUzRqU9bGDXvhGk2m24+n/fOW596TqXOyW4YRuQ4Vqd8SyQS7sbGhruhzfGeSqW87XVLB5l+LZFIBJ6fGof6Rz9eyeNo59tEIuGaptkRd+p0h7lczrdvtbzr0xL2U+Zkqjj9nF0l3sPOWSdxZ1mWm8/n3UQi4TvXXC7nTf0m4Xq5Vc9ZnSau37Tsl5RfOc6d6PdYD0q+k+1bltUx9akep5JH9e10q3PCyPHqdaQqrI5TNZtNN5VKuc12vSv/TyQS7vb2dkfZ2WtNZcpSvewKuYZKfKt5Qr6v55O9FiWtwkh9pk9xKeU76Doj10Upq247bmT6z6By5wZMg27btptKpVwjYPpOIeVHbUeoZQoB094GkWNGu5xIOZXrstS9rja9qRxXt/jQRf2+tBOj1ulSzqC1WeXcuk0TGjZFsOSdsDw9zHrHVaZlVese9bz0OmmY7TZ1qlW9/IdduyXe9I8RMJ11GLTreLVtIdcTlcSNtAfkmqeGy3GrZSDK/Uu/60s9joA0UeNR/6jb6RbfUh5M0/Slq8QNAqbXjdqGHqStJOHq9VvyhOSjTCbj1VdyrnKMah3crRwKOf+wckfjaeI6SKz2jbxketM0OwqzKq91PuRyOV8hVAuufNSCLgVD/egVZaVS8d0cqBVjEPWYTNN0NzY2vLDV1VXv+PT9QrtgN7WbcNM0OyqpXse/vb0d6cIpN0X9Ctu/3mhSz08PQ0DlG0S9SEilKX/r+w87LlWvvNONvu2wc9DXCTuWMNvb2768JxdT+b/kl7DzDYtvNZ+F7UttROiKxaIv7tSLvEptdEoDJijN9LiLUuaCzlnOTQ+T8G7UsqKeu2VZrqF0bOnbRfv4g85LL4tR0rIfYecqxzSoqMcalAb7Od8Vi0Vfwy+VSnU0sIK2E1bnIOJvHKZpuqZp6sGuqzSaZXuGYXQck06uG5lMJvKNw25Sy1pYWqjUvCc2NjZC42yvDJJWqqCOIDfkhl5stzu/1H3KzVwv+jUwrDwJKddqWjXbN9SmabqG0qndi5RR9dorNzZyfXfbx5ho/zgk59itjtBF+b6Eq5+wOl0/96A47FXmbNsObQPoN5gi6FgGrXe61c96WLfwbmVWBLXbwo45bD+qjY2Njjo6ameN265r9fIS1Pbb3t72jttst+Pddjro1wU57qj3L/2ur8cHAu4VMplM6HbC4jts2/l8PvA7ep7V874ej/r3ZdtheVkEXb/VfKSen6wr9ze9th1k0Psf2lsx91+Z7MCrVqs4fPgwEonErr7vS/+yuLiIG264YWRTnRERUbByuYw777wT29vbQ3nEV66nq6urB+adanmVRtoH2WwWt912245flxgn6XQatm1701qLQqGAhYUFVCqVPR0oWPJVPp8PbCskk0nk8/mh5GGi/aLf+5d+16fR4v3P/jRxY5DQ7nMch1NbERHtkWPHjiGVSnljQ+yUPnbOQXDLLbdga2sLaN9gNNpTch8UjUYD6+vrO5q6ci/JGCLsHCGi/YL3P/sXO0hoJEqlkjco4pNPPol0Oh1pgCsiIhq+l156CbZt73gq43q9jrfffhuJRCJ0Nqj96Dvf+Q7QPr+f//zn3gxhB0Uul0OxWNy3HQzPP//8vu3cIaLJwfufg2FiOkjee+89oD2qsz4yMQ1XtVrF8ePHceedd3ojzz/99NP6akREtEump6exubmJV199teesO0Hi8Tjq9ToWFhbw0ksv4fbbb8fFixfhtGeCGWSb40Rmdbn77rvx6KOPHqgGbTabxY9+9KN9+URMo9HA4uIifvzjH+/bzh2inej3/qXf9Wl4eP9zcExEB0ksFvOmSrNtG6ZpjmTubvqXm266CZZlAQBSqRRqtdrQp00lIqL+TE9Po1Qq4S9/+UtfU/LW63XYto2FhQX87ne/w/T0tPfI8I033ojbbrtt39+8yvEfPXp0X3YkhCkUCjh16lSkczp8+DBisdiuTm8sU/jGYjEcPnxYX4yZmRmcPXt23+cvokH0e//S7/o0XLz/OTgmZpBWIiIioiBra2uo1+sH7tUaIiIi6s9EPEFCREREpIrFYgA7R4iIiEjBDhIiIiKaKPKKUTwexxdffMHOESIiIgL4ig0REREREREREZ8gISIiIiIiIiJiBwkRERERERERETtIiIiIiIiIiGjisYOEiIiIiIiIiCYeO0iIiIiIiIiIaOKxg4SIiIiIiIiIJh47SIiIiIiIiIho4rGDhIiIiIiIiIgmHjtIiIiIiIiIiGjisYOEiIiIiIiIiCYeO0iIiIiIiIiIaOKxg4SIiIiIiIiIJh47SIiIiIiIiIho4rGDhIiIiIiIiIgmHjtIiIiIiIiIiGjisYOEiIiIiIiIiCYeO0iIiIiIiIiIaOKxg4SIiIiIiIiIJh47SIiIiIiIiIho4rGDpIdyuYypqSmk02l9ER0Q+ymNG40GFhcXMTU1hWq1qi/ec41GA4VCYWyPj/5PMpk8EOnkOA4KhQIajYa+aN9xHAdra2uIx+MjSZe1tTWUy2U9eGTGrb5Sj0cXpTxUq1Wk02nEYjHEYjFks1k4jhN5+UEwSB7tdl1oNBqIx+OIx+M7iqtqtYpsNotYLKYvohDlchnJZBLJZFJfNPbGrW6h/+M4DkqlEuLxOAqFgr54ZMY9Pw9Sd9LemYgOkkKh4DVYonwmLeM6joNsNot4PI5YLOZ1FlSrVe/mI4xcpIbVudAtrYKOQ18nbL2DoFqt4sKFC1haWkKr1dIX7zk5voWFhbE8Pjp46vU6fvKTn+CBBx7AzMyMvnjo9dMoVatVPPzww3jooYdg27a+uKt6ve67MQ9rmJ46dQr/+7//i2w2qy8aunGrr0qlElKp1MDHUy6XceLECSwtLaHZbMKyLKysrHiN8V7LD4JB8mi9Xh/5daFUKuHFF1/EysqKvohCrK2t4amnnsLW1pa+aOyNW91C/8dxHFy4cAHZbDZyHTEM456fB6k7aY+5E6LZbLqpVMoF4AaddrPZdFdXV10AbqVS0RcfWM1m0zUMw7Usy93e3vbCisWia5qmC8DN5/P611zbtt18Pu8ahuECcBOJhL7KjuTzeS+tMpmMvtinUqm4ANxUKuU2m0198b6WSqX0INeyrLHOp4lEYqyPb9Ksrq4eyLTY3t52TdMMLPOjrp9Gqd/yI/WfaZpuIpHw6m2pE4NkMpme9eoggvY3bvVVWBugF8Mw3Fwu5/3dbDZdy7K8vNVr+V4ISo9h6DePugN+px/NZnOgtB1VHO0HUnfsZR6NYnt7O7AdOm51C/0facMHpduoDDM/j6peGHU9SMMzEU+QAMD09DTuv/9+PdgzPT2NU6dOIZfL6YsOtCeffBKtVgubm5uYnZ0F2nGRTqdx+fJlmKapfwUAMDMzg9OnT+O3v/2tvmgoHnjgAe//9913n2+Zbn5+HolEAvfffz+mp6f1xftWqVTCP/7xDz34QJ0jjd6zzz6rB+17juPg7rvvxpkzZwLLw6jrp3Hy85//HMViEVevXsXm5iauXr2K1dVVAMD6+jpKpZL+FTz99NO4ePEi1tbW9EUDO8j1VbVaRavVwg033OCFTU9P48qVK9jc3Oy5fC+EpcdBNUg+azQaWF9f14NpzITVU4OkOVEvk1Z3UrCJ6SABgOuvv14P6vDjH/9YDzrQVlZWYJpm4IVmenoaL7zwgh7s881vflMPGoqg4+klSvruF47j4IknntCDifqytrZ2IB/nfP7553Ht2rWer86Mqn4aF/V6HSdPnuyIh1OnTiGTyQAAXnnlFd8ytOvXBx98EI8//vhQxm456PXVe++9pwf59Fq+2w56egzLpP0gth/V63W+OkW7hnUniYnqIIlidnYW8/PzevCBZtt24K+MAHDs2DE9yCfovX/auSeffPJA3tjS7qnX63j88cf14H2v0WhgaWmpo1MgyEGvn2ZnZ3Hq1Ck9GIjw5F0ikUCr1cJvfvMbfVHfWF+NF6ZHb6VSiU+PjDnHcXDy5Ek9mGhkWHeSYAdJW7VaDRyctVQqdR0VuVQqYW5urmOgUHXAUPVvdTv6MnX/5XLZNyL74uJix/cRsP9+R82XXxmPHz8eOKgfAJw+fVoP2jcKhYI3+Gw8Hkc2m+24sQpLYz0NqtWqF9dzc3Oo1+u+9YWeJvonLJ5FMpn0fjHZ2toKzB9CHZwxHo+HdnRVtdkVkslk6PGHWVtb853X3Nxczxkx1DiLx+Ohj8oGDRSczWZ9v25Xq9WOuFTTTF+uxlej0UA2m8XU1JR3LL2OPYietmHlTQY31s+nUCh4+a9b+Q87R7S3vbi46G07FoshnU770rNcLuPIkSPeAHaHDx/2bavXDABR0gPt7cio7IVCwTu2qakpTE1NYXFx0bc+AgYUTSaT3qDQUbzxxhsAgNtuu01fNHRR4ho7qCvK5XKk/LQTt9xyix4EtDtXDMMIrTOiGtf6Clr9PzU1FVr3hpUHKaMLCwsAgIWFBd/59Vqul496vY54PI6pqSmv/omax4ReB+n1cJT06Cd+R51Hqz1mn9HPV/+Epal63HoZLBQKOH78uPd3r20h4PoSa8dpULhaZyeTycDtV6tV3zLJI+rybtvVl6vpu1vXOz1/R6n/EXB8QZ9Go4FDhw6hVqsBWtkKEqVuUfOETEYwNzenr9ZBv1bLMQSFq2mohqvpE9Q+0PNevV731UmlUglTU1OIx+Md7aKoZTmMfjyxkDqo37oqTK/9qeUipqS3nuf1OOumV3nDPqw7acT0QUkOMhnARz9tGcBVHzQnn897A+oEDfqTy+VcAO7q6qrrtgeSkkEB9QHwZABYfTu2bXvfkf1vbGz4BpTN5/NuLpfz1rNt23XbA+1ZluX9LfuwLCtw4MIgMpCc7Ms0TbdYLOqrdRV0XsMgx6SnS5BEItGxXj6fd03T9OKnUql0DJoXlsZ6GhSLRTeRSPjWN03TW1/0kye66TbYlOx/dXXVtSzLzefzbiaT8Y5VzlcUi0XXMAwvfiqVimsYhmsYhjcwby8y4JbkDdu2vcEg9XiX45M8m9AGjlQHMnSVOMpkMr68HHSMcuxB23GVgfrUY5LtS5rYtu3l+X7yetTypg7OqOc9PU2bzWZoPEpe0vNAIpHwxYvkFcMwOsq9pIW67Uql4hsEWd9v1PRoNpu+gVBzuZybSCTcXC7nq6/UOJZBoWXgNtlG0HGE6XdgvqA4jCpKXA9aVxSLRRdKXWHbtm87Uc8vjGy/23bk+DY2NvRFfZF4CYrnvaiv3HZ51bejXutEr/LgRhhwMGi5Xj5kYFyJD7keRMljQuogOUb1+qKmYbf06Cd+h5lHg+qiYrHoywu6fq+nsp2oZTBsv2EkXvX4Vo8rKI9YluVmMhkvPWU7cg7SBtW/L2mDEV3vuuWTXtc7PX9Hqf9dpc2rbrtbfRBUtkQ/dYucq8SVmpejUOsItVxKGVG3LSR9JC0kTM0PzWbTO2bJD9vb217eRztuc7mc11aQOO2nLIeR40mlUl58yTkZhuGLw37qqrB0i7q/7e1t7/z170u669sOy89Ry5u6rr4Nt8/4HmbdSXsjWs1wQEjGD/sEZdiwwmLbtov2xUKlVpaqsO24IQ0HV7l4y4XYtm2vEEpB1SulsIqjG7WykE8ioMMhTNh57VS3dNEFHa9crFWVSqXjWMPSRi5uCLjIy4VKrRT7zRPdhB2Tq6Sx3kCUi6x6rHJMetzIxSto+0GksaMKuwCqx6fmz7CGi2VZgY1XaZDpyyQ+9fN32zererhpmh3HKPEbVIaC9FPeEu0OId3GxkZgnIeV/6A8II2GqNsIC++2rN/0kIacNJyFpJM6GrycU1A86scRBu08pG8jTFB8RdFPXPdbV0g86Pmy2e5A0rc/iEQi0XMk/rBGYr+C8qpQ6wPVKOsrWV/fjhwnAurioHQVYXWd6LZclqnXhUql4jabzb7ymJQn/fik/KnxGJYe/cTvsPNo0DmJoDQZ5Hoq4WFlUL/5DttON0H51u2RB/S6UcqdGhdhaTbK6123ferruiHXu37qf1eJP71TVtJIP/Zu8dpP3ZLP5zvykuTlqMLyUVjetm27I24z7U5SVViZku1KO7bZbHrL+ynL3WTaHcl6WluW5bvx76eucrukW9T9uV3KZ9i2w/JzP+UtLLyf+JZt6McXls40nib2FZt25xBc10Wz2fReNYnqT3/6ExAwmOgdd9zh+3sYZByQmZkZb6aZ5557Dul0umP/t99+OwDg9ddf94V3Mz09jVKphEqlAsuygPbjZYcPH0Y6nd7Xj4StrKz4Hn+bn5+PPC6BGrdp7bWceDwOAPjyyy+9sN3MEwgYY+Ab3/gGAOCzzz7zwi5cuADTNDvG1fn+978PtNM5Svqapunljajuu+8+X1wsLy9725DXJMrlMmq1GlKplLeeOHXqFAzD6Bgj54477oBhGFhZWel45eOFF17wjclQLpdh2zbuuece33oSH61WC5cvX/YtCxK1vFWrVWxtbeFXv/qVbz0MaRDh6667DoZhhL42sVODpIfM3HHvvff64uff//3fASBwNPgnn3zS9/eJEyd8f4dRH3XV02LY+onrfuuKF198EQA68uX09DRuvfVWX9ggqtUq3n//fbz00kv6Ip+bb74ZAPDOO+/oi4ZuN+urc+fOBW5H/3s33Xvvvd7/5+fnMT093Vcee+KJJ2BZVsc5nD17Fq7rduS7IP3E76jzaC87uZ7qcSFl8O9//7svfBCSj/XBjyWezp075wuXx+zV8zBNE4Zh4Gtf+5pv3SDjfL3DAPW/XDv062HQNSeqKHULANRqNd+1a7o9Y2NUDz74IKC0X4Rcv6TMiAsXLviubY7jYGVlpeN6p5apP/7xj75lAPCf//mfQHs9Sct+ynKYRqOBlZUVZDKZjrS+cuUKrl275t1z9FNXhelnf8PUT3kL009873XdScMxsR0kqunp6Y4Kthd1Oj+VXuhHpVarYWVlxfc+Xkx5F1re2+zH/Pw8rly5gmKx6E3vu76+3jEGwn7xyCOPoNVq4bvf/S6y2azXUbK8vKyvOhR7nSeCfPDBB7BtuyOfHD582Fvnk08+8X0nyJUrV3DlyhWg/W5sNpvtaAhGITcJH374IQDgz3/+M9Al7o4ePQoAePfdd72w6elpPPbYYwDgG2BSGo/qBfavf/0r0L5A6nGgr9NN1PImjZtvfetbvu8Py8zMDK5du4azZ88C7QZxOp3G1taWvupABkmPfszPz8OyLKysrHjviTuOg3Q63dHw2GujjGsZHDJqZ20/HMfBiRMn8Pvf/35P655BDKO+qran3JWb4nEWNY85jgPbtnecnv3E7yjzaBRhddBO42Cn5ufnYZomtra2fB0Wb7zxBlKpFFqtlu8mXO/EQLtT69q1a5iZmUGj0UChUOi4aRbjfL0bxNTUlB4EdEnvYbnnnntgGAaOHz+OZDLpjcnST3tQbnhffvllX/jbb7+NRCKB9fV1L10cx8H6+rqvA0bK1vHjxzviVsr8Bx984K3fTT9lOcz//M//ABHjPmpd1U0/+xumfspbmH7ie6/rThoOdpC0zc/P99VAl17A999/39dLK5XjTnrDo8rlcr4nYfTPoNLpNC5fvuw9VaP3uu8Xx44dg23bSCQSWFlZwXe/+10kk8mOX2GGZRzyRBDLsjryhvqJmu+r7YEnFxYWcNttt/X91BUAfPvb3waUX5V6NQbkF249zR544AGg/WuUxPVvfvMbPPLII771RLPZ7Dhv+UQdhDhKeet1PsMiA+P94Q9/wP33349EIqGvMpBexx+WHv24cuUKVldXce3aNRw/fhw33nhj6OC942DYca0+BTMKDz/8MM6cORO5XI+bndZX4zblbhS98livG51+RInfUefRKMb1egrAe0LwwoULQPtm+MMPP8TS0hLQfgID7WN1HCfwV/FGo4F0Oo2jR4/ihhtuwJkzZ/RVPON6vRuEdLLr5fTTTz8F2rNrjcLMzAz+9re/IZfLYWtrC3feeSfi8XhfeX1mZgapVAq2bXsdLNVqFTfffLN3wy154k9/+lNoHt3Y2OiIT/lsbm7qq4eKUpa7idJZputVV3UzyP6GpZ/yFiZKfPeTn2i8sYNkQDMzMygWi2i1WnjyySfhOA4cx0Eul4NhGN6FcpQuXryoB/Ut7MZkenra90qE/qjiuHn//fdx3XXX6cGYmZnB5uYmKpUKEokEtra2YFlWz0cPBzEOeSJIrVbb8flms1kcPnwYv/71r7G5uYl0Oj3QrwD/+7//CyiP6koPuzxREkbWF9PT08hkMmi1Wrhw4QIcx8HFixdDp6WO8lhxL/2Ut88//1wPGgrHcTA3N4dnn30Wb775JpaXl0PPeRCDpke/Tp06hb/97W/I5/MAgIceeqhjRPm9Nuq4HoVsNosf/ehHfT02Pm6GUV/tF1HzmDwaHuWx+V72S/yO6/UUytMIMuPFhQsXcP/992NmZgaJRAK1Wg3VahUXLlzAo48+qn8dpVIJpmnCNE1cvXoVp06d8l5JCTLu17t+PP3007AsC+fOnfNuJqvVKlZWVpDL5QI7k4ZlenoaZ8+ehW3byGQysG0bhw8f7uum9mc/+xkA4NVXXwUAnDlzBg888IDvVSjHcfDcc895HVs6eVJzp3Zalr/+9a8DEV/Jj1pXddPP/oap3/IWZqfxTfsLO0h2IJ1OI5VKodFo4Ktf/Sq++tWvAgAuXbo08kerTNPs+mRH2PRqurfeeqtrgVffm95t0jMd9E6mKuhRU2hxMD8/j83NTa+Rob9DOix7mSeCyD71MR/E2tpaz6cB6vW6995ovxdEnXS0SdrKVK1hjTH5VUne81T98pe/BNrvfD///POBvwjIBfmpp54KzOf1ej20DKmiljfpONDfTx+WN954A7VaDWfOnOnI78Owk/SIolqter+8TU9P4/Tp07h06RIMw4j0ypb6i1ivfLtTo4pr9RzC8tMgstksZmdn++oc+eKLL4AhdHgNyzDqK/Wd8F7r7rWoeWxmZgaGYQAB4x+IKB2MUeN3VHm0X+N2PRXT7bErWq0W1tbW8Prrr3vXRnmS4LXXXut4xUJks1mYpum9rhDFOF7vBjE9PY3z589jamoKJ06cQCwWw4kTJ5DP5/uKj37JNMRol4Pl5WUUi0UgYOyQbuQVq/X1dZRKJczMzGB6etqXJ55//nmYptmRR6WjUx8bTzjt6W+jiFqWu7npppuA9o1/2PHIj6hR66pu+tnfMA1S3nRR43tc6k7auYnqIBn2r7rZbBZHjhzB5uam94hVqVQKrDyk0OiPi5bLZVy9elVZMxoZLOr48eMoFApeRdhozy/fz6/7YQUeyuB9+mBDolcFDKXSlxujqKShsb6+HnixR3vb2Ww28HWPDz74oOOXgX7HmulXP3miH47jBF5QepHzXVlZQVqZZ14uRG+99VbHRVz3l7/8BQhIa7lZFmFpJJz2AGWpVMqLj3Q6DdM00Wq1AhsGFy9eRCKRCHxUVH6ta7VaWFlZCRy8T37VqdVqvveO0S57d999d+D3dFHLm3T8bG1tIZvNKlv4V4M5iNycqo8cO44TuP6lS5cA7Ykup/3Lqvp3GL086HaSHlG98MILvr9nZ2f7GrhMnmqLMuCinmf7sdO47kbqqyeeeCJ0G//85z/1oFCS1/SxDtC+KQpKSyivVMmrb2jfSMRisY7824+9rK/kBgbt1wTChMX7buonj8k4FI8//rivHDvta6DcHAeR9OgnfoedRwcxqutpmF71o0rK2uOPP+57SiSdTntPEgS9YlGv19FqtXDt2jVfvOrtUz3Ox/F6N4h6vY6TJ0/i8uXLuHr1KlzXxdWrVyO/+lOv1zviJip5/UUEdV5FIa9YZbNZr+MKSp5YWlrC/fff74ULNQ2PHDnie2WqXq8jmUxG/vGhn7IcZnZ21muznDx50ne9bDQaSCaTXn7pp64K08/+oLSn1HJZr9f7GlR80PIm9mvdSUOgT2tzUDW1qWzVecm7kSmcTNP0TUslU17J3OvyKRaLbqVS6ZgT21Wmw5LvpFIpt1gs+sLluGRKUARMhyas9tz2+kefbq0b2XcikfDtR52zW5/OTiVTfyJg6jMhcYgBsptM12ZZlu/4ms2mWywWXdM0O6aRE4n2nO1y/JIH9CnGwtJYnU5QTc9ms+lN96ZOIzxIngijzgGfy+XcRCLhNptN17Ztb5owPQ9Lesm6Qqbh0z/6lGph1GNJpVJuvj1dnuzPNE03k8l46a+mmUxlZtu2a1lWx7HJ9vVzajab3nRwYfnKVaZT06dzVqllSf90y9u6qOVNjW/DMNxEIuGVbQRMHyfnIOeRy+XcVCrlO+5cLudub2/7ypusK9uXbatTHkoaWZbl5nI5b9o5dbo5PR/1kx7NZtPbt14O5VjV78i5plKpjjB9Srwwsl39uINEqZ/C9BPX/dYVaryZpunVERLHUOqRXqS8JRKJjo/sI6ycm6bZUR/KeaCP8jFO9ZWr5eFE+9q2sbHhawPI9dftUR7UtNLLeq/lzWbTTSjXWP27/eQxdT+yr0T7GqdPcxqWHm4f8TvMPNotH6j1n7r/fq+nan2pn0dQGXSV6etTqZSbSqX6nnrTCpkSXeI4rM7R40/SWY4/l8sFtvuGfb2T49TbPm7E652aR6LU/65S7uV6JJ9KpeJW2tNfh20n3243uz3yVFDdklemhtXD+k33Zntad73cuV3yhFCPW/+o21PXC0vvqGW5G7WulDiTOkvNL/3WVbINPV9E3Z+rpI+kfSaT8fKNGq7XbXp+7qe8jVvdSXun/zvWfUgKU9CnW8Wor6uurzdWgj4J7UZoe3vbqwhM0/QKZCKR8G6I5O9e2xL5fN67+BuG4eZyuY4LTDdSQDc2NnyFF+2KLSx+1EZNr+OsVCquYRgdFWVUlUrFTbU7NmQ/sj29QlWlUqmOuEwpN2ZulzTWvyfnFpaX3AHzRDdqZb+9vR2677C0UG1sbPiOTY+HXorFohf/8l25gMvx6etLIwXti0G3tLJt25f/TNOMnJcty+p5Ltvb2x3HE5a3u4la3tT1EomEu7297aVTUB7I5/PeuWcyGbfZbLqVSsU1TdPN5/O+85N8oe5fGsXqxdxtn7d+cxCUj/RjipIeYfkuLDzfbgRLA1LCTdPsaOB2Y9u2i5DGqQg7Bv08e4kS14PUFW67vlDjWPJJot1g7FZeRFiDTf1YlqV/zXW7xKMck+S9qMapvnIDyryUK/m/lP+g45R8ErRMPd5uy8POU693ouQx0Ww2fXVFtzTS00MVNX6HkUfD4sENaevI+fRzPQ3aTlgZVOsAua4Zyg8p/SgWi4Hxb9u2bz86tV5Wr0WWZfU8lmFd74LiTD+XfJfrXVi6hoXLtotKZ3LQxzAMX+eQWsdKeQhKV3TZt5xLot2hKOFB8RKVWoeowvKESi9X+jUw7PyCRC3L3cj1Xo2XoA66qHWVftzQ6r2o+5N4kn1KvObbP9IVi0Vvn93yc7/lbVzqTtpbMfdfmZkGkM1m8cMf/hDXX389/vnPf/pGaP7iiy+wsrKC5eXlgR/jo/2HeYLCVKtVHD58GIlEoq+R6qnT4uIiVlZWcO3aNX0RRbS2tobHH38ctVot8FHsQqGAG264IfC1HaLdwOvpwVOv17G2tua9svDxxx97YyGh/Vr31atXB3r1nIhoWNhBMqBCoYAvvvii66A/hUIBX//613nxnhDME9QNO0iGx3EcHDp0CL/61a94Az+geDzeNf6SySSWl5cDO0+IRo3X04PHcRzceOON+Nvf/obp6Wl9sScej7ODhIj21EQN0jos9XodC/9/9u7+RZLq7hv/e/6AaGrm/il3IjI1wi3mYsTUrGJmBQNOd9YQEtR0r7kIC4prz4pgHna1ZxcJcR+6jd4QdB7CLkjIZfd8VZSLqyczG1BId0LWHaUbI7nBrUa8vfNT13RM/oDz/SH9qevU6aruqp6ex36/oGGmqroeznOdrjrnzBm4rmuu8nmeh3fffTfWgFh08DFNEO2eiYkJvPXWW3jxxRe3NRDrqFpZWcHc3Fxk50i5XMaJEyfYOUJ7gvXp4XTq1Cm02+2uATJ15XLZHySWiGiv8AmSATSbTTiOg3a7Ddu2kclkAqN6f/rpp7h+/TouX768Y6Ot0/7CNEH9rKys4Mknn/RnGeDN5/Y1Gg1cvHgRr776as9fJOm/lctl/OEPf8Di4qK5Cui8vvTNb35z21N6Ew2K9enhtLCwgAsXLgAAMpkM7rrrrsD6N954A3Nzcz2fGiIi2g3sIBmQ53m4cuUK3njjDWxubvrLU6kUvv/97+Phhx9mg33EME1QlLGxMXMRCoVC7KkNKZrku4cffpidTn2Uy2XcdNNN7PygfY/16eFUq9Xwyiuv4OrVq2i32wAA27YxNzeHRx99dFtTyBMRDQs7SIiIiIiIiIho5HEMEiIiIiIiIiIaeewgISIiIiIiIqKRxw4SIiIiIiIiIhp57CAhIiIiIiIiopHHDhIiIiIiIiIiGnnsICEiIiIiIiKikccOEiIiIiIiIiIaeewgISIiIiIiIqKRxw4SIiIiIiIiIhp57CAhIiIiIiIiopHHDhIiIiIiIiIiGnnsICEiIiIiIiKikccOEiIiIiIiIiIaeewgISIiIiIiIqKRxw4SIiIiIiIiIhp57CAhIiIiIiIiopHHDhIiIiIiIiIiGnnsICEiIiIiIiKikTeSHSSe56FYLGJqagpjY2OYmprC2tqaudmuq9VqmJ+fx9jYmLnqUGo2m5iamsLU1BQ8zzNXD0W5XEY6nUaxWAwsX1tbw/j4OLLZbGB5Ertx/julXC5jZmYGY2NjGB8f7wofOtikLEmn04HlcdJsv/Kx3/rDZhhlxSDS6TTGx8dRq9XMVaGiyjoK12g0Dl19WywWMTY2hpWVFXPVvjbsPJY07xxWScO12WxiYWEB4+Pj5qp9w/M8rKysYGpqatvxu5/a3J7noVwuY2pqatfLcD1Mh3Hsvch/Scu+g5DWaW+NZAeJ3DTcuHEDpVIJruviwQcf3NNGfrlcxiuvvIKlpSVzFQ2g2Wxifn4e8/Pz2NjYMFePtIWFBbzzzjtYX19HvV4HAJw5cwYLCwvmpj4Jz/Hxcb9TZX5+Hs1m09zUt7a25nfCTE1N9a24km5P4RYWFnDixImBy5J+5WO/9bS7WNYlt7a2hosXLw6cR3aD53mYn5/3OyLlRrdWq/mdlETDUi6XkclkcOHCBbTbbXP1vlCr1XDq1Ck8+eSTcF3XXJ3IfmpzN5tNXLlyBfPz89u+rqTk2M8999yuH3uvHIS0TvuAGjHLy8sKgGq1Wv6yUqmkAKhqtRrYdictLy93Ha/VaikAagSjZccUCgUFQBUKBXPVjguL471Wr9cVAFWpVALLLMuKDCPXdZVlWSqTySjXdf1lmUxGWZblL9NJPlteXlZKKVWtVpVlWSqXy5mbKjXA9odVvV6PjIckqtWqAqBSqZS5qqd+5WO/9QfBfsyXw7BXZV0mkzEXHRj7tb5ttVrKsizlOI6q1+v+slKppGzb3pN43ksHOY0dNPs1T+hSqVTiOiesbt2NNneStLtbZXjYOeXz+V059n6y03Ef5rC2Pw6jkXuC5O233wYATExM+Muy2SyUUpidndW23FkvvviiuShwTnTwhcXxXpNfmG+66SZ/2fT0NLa2tnD69Glty//2y1/+EgDw6quvYnJyEgAwOTmJV199Fe12218varUannzySeRyOZw8eRIAMDs7i2effRZLS0tdTxok3f4w2+unZvqVj/3WHwT7MV8eVM1mE6urq+Zi2qZz586h3W5jfX0d09PTQCfPZbNZXLt2DbZtm185tMrlMv7+97+bi4kSCatbd7rNvR/TbtQ53XzzzeYi2gFsfxwcI9dBsh8eQV5ZWRmZR9lG1X6N43fffddc1Fez2cT4+HhXY0L+N1+zeeGFFwDA7+wQDz/8MADg6aefDixPuv1h1Wg09vxx337lY7/1+91+zZcHVT6fNxfRECwtLcG27a4yF51y91e/+pW5+FDyPA9nz541FxMlshd1635Mu/vxnEYJ2x8Hy8h1kOy1RqOB5557zlxMh8hhjGPXdbue5JBBPr/1rW/5y5rNpn8TLb98isnJSdi2Ddd10Wg0Btr+sPI8D48//ri5mIboMObLvVQul/n0yA5yXRflctlcDAA4duyYuehQOnfuHG8oaFv2qm7dj2l3P57TqGD74wAy37k5rORdM/NjvqNfqVT89xsBKMdxVKlUCmwj2+VyOf/9NXl/z9yfrlKpKMuyep6DLJPtHcfxz0PeRTaVSiV/OwAql8sFxgjopVKpqEwm459DoVDwzzGVSg18TNd11fLysrJtWxUKBVWv15Vt28qyLH/8i2q1GghDU71e98e5AODvK+raZHs9XOV/873KUqmkUqlUZHyZ1+c4TmDcDhVx/r3iWE9X8tHfRdTXR52XKW4YhR1bPv1UKhUFQFmWFcgLeroRMh6F4ziB5ULOQ8YaSbp9FHk/X49TSX8AVCaT6QoTc/tKpeJvr6d9PV31GqslyvLycs+05Lquf1zzE0er1VK5XC6QBqLKo7A0q2KUj+Zyc70w841ZLpjx1Gq1/DjWw7XVaqlCoeCHS1i41+t1lc/nlWVZqlqt+uPioBMGelrtlS/7MdOJMOuAarU6UHltpgfVSRP6tZmSlHWqc27m9ub5JbkeeVfe/IQd21StVv04h1Zm6cz6o9Vq+eFhWZbK5/OB7YXruoG8EPbRhS0TccJMdcJC0qlt2yqXy4W+45+ExEPcMFWdPKOHmRhWWFqdMaHMclQlCKsoYXlMTyP6Jyw/6Hrlnah8Y27Xi3mtZnjrCoVCIK+HHcssE1WMusss8x3HUblcrus8zP2awspYOVdTnDLZTGth7T7ZzqyzzDJQ6O1gdOoU+d8MS1OculX/P06bO075NWjalfAvFAqB+kzyqZkORJx01u+c9GPr6atXGREmKv8lqa91cfJbVNmnC0u7sk9TnLSe5Hq20/6gvdOdMg65qAyhOo0SvSB3XdcvVHLaYJGVTqeC7KtQKPgZBYByQwat1Mk+zQJMaecnFVuhUPC3t23b3NyvLOSYMoii4ziRhalYXl72ryOVSql8Pq9s2w4UpFbIIJz9jimFi4RHLpdTuVwuEJalUinQCDTJjfPy8rK/T7npC7u2emegUWnAyTnI/vXCTQ/TsAJKrk/iR/YNbXDTfucfFseu6/qVmG3bXdegOh1tYdcXJmkYqYjzikO/1lznBiCs0pQwDwtXpR1f4iPp9lH0TohUKuWnOb2S0/OwmQbkmgpaQ8O2bVWv15XjOCqfzwfCIKoxZ5Lrk8pSb7CZcSDb9rtWXavVUo7jBPJjqVTy06serv3SrOpTPqo+6/uVC7IsLJ4kvJV2TXpelm0kDqVxIucj+y0UCoFrNMuupOnfTCfCrAOSlte9ypZqtRoou8xzTVLWKS09yH6qnQGQLcvybwAGvR7ZPq5qZ/BgicdWq+UfV85brkfCJZ/Pq1SnftLrWbNB7XYGk9bTYK+0oHqcf5wwU1qjW/Zd7XQqRZVncUkekPMzG9wm13UDZd12w1LSWEHrbJewdIzO7LhhFSUqjyktvZjLo/TKO63OwLdm2Jjb9SLXKuGlx5NeH+rlsoRBtVr140cP76gyUY9PyS8i1enYkbiR89Lzfq9wVVp7V483Pc3p4pTJZlqT65Bz0Mtuy7LUcudHD71dZKbDktbGkW31cipuvEk86+EjZF9xyrw45Ze5bVjYR5HzlLhJpVKBODHzXpJ0JuuizkmOHbeMCBOV/watr+Pkt6iyTzfstD7o9Ui6iptuaW91twwOubAMobRfyc1CoNVqRRY2si+9QyVOg6BXJpF9mseSc9AznBQeUkkK2X9YQWGSAlOvsJTRcNcr5yTHlIJSL9Sr1Wrgu2HxIQ1d/bhCKiN9XavT8Akr9MPOS/WoKKRCNuNGCkMzXsLOX/WIY7k2GDOBCCfk1+QwScNIRJ1XHHLDK3FqFv4qQYdHpvMLa9Lte5E8bBkNc9d1/eU6Pe3r20t6QqcS1uNJb8DEIfvRyT7MNBm1vJdUKhWaH3uFq8RhmF7rVI/1ScoFPdwlDdXrdf9vaVTr9DjR0640csz4kEaKXqapAdN/VFnR0mZAMMsFKa/1dJW0bAk716RlnaR985hh6SPp9age6SGKlE36+USFr4SLY3T2SjiaZYLEuVl+9mo4h51/kjBLdW4kdNXOL8zb1dJuvuSTSqW6zksXVYYkDUu780OJTuoc/aYxSVj1EpUGopb3E5Z3ZF9hZZR5/mHkWs2wlXpHL4MkvM06st6ZRc5cl7TuQkg6LxQKXecWFX4SP+Z1y/Yw8kSSMln2HdXus0N+5Zfj6nWILDO3jTpuL1H5QiVscycpv6KW96KHnX5cyafmeSZNZ73OST92WBlh1rG9hOU/lbC+TpLfVI843sm0nuR6VI9wof2JY5B0PP/88wCABx54ILB8YmICP/vZzwAgcnAjeR94cnKyaxyFQWWz2cD/U1NTAIC//e1v/rKXXnoJ2Wy2ayA3GRPijTfeCCzv5ciRI4FBMqenp7G4uAh0BowTgxzzkUce8f+enZ3t+q7pypUraLfb+M53vmOu8t/hW1pa8gcHffPNN9Fut3HixAlj6+D4GHGcPXsWjuN0zchx/vx5KKW64iWpyclJPPvss0DnOnW1Wg3tdjvW++VJw2gYPvvsM+TzeViWhc3NTTiOM/DYIOPj4+ainuJsLzPzHDlyJJAPZeadqPnuze0nJiZw5MgRAMC3v/3tQHq99957gZCBaaPYtg3HcczFQ9FoNLCxsRGaH+U8d8sg5cKRI0f8uJmensbk5CQ8z8PS0lJXXtbj5He/+11gOQA8+uij/jIAuPXWWwEAX3zxRWD5MOnXapYLUl7/85//9JcNo2xJWtZduXIFtm13HVPSx8bGhj+WUNLrGYRt27AsC1/5ylfMVV1kVoVHHnkkcG5f/epXAaBrJgYZr0OfoQsAMplM4P9+koQZOuWsXg7Ozs766Xo7JiYmUC6XUa1W/TJkY2MDR48eRTabDZxDP0nCslwuw3XdrsGxJycnsbW1hRs3bvjLkobVfnDu3LnA/2F5KYzM1vbYY48Flh87dgxKKb+95HkeLly4AMdxutLB9PS0nx712d8Gqbuef/75QNjKoOZxXLp0KTTezP/RuZ4kZbIIa/etra3Bdd2uc5XjttttXLt2DQDwyiuvACHXpR93mKLKPL3NnaT82o5HHnkkkHay2aw/IPZrr70GDJjO4ogqI+K2eXpJUl/HzW/97GRaT3I9dPCwg6STKTY3N4GIab/uueceoDNo2jAKiWHZ3NzE0tISxsbGAp8zZ87467dD7yyq1WrALhwTAK5evQqENHTRKfgtywIAvP/++4A2NakU5IPyPA+u64amgWF67LHHYFkWLl26FGjgvP76635nXD9Jw2i7pPFw/vx5fPLJJ3AcB+12G/fff/9AnSRSgcSVdPv94vr167h+/TrQ6dCYn5/HpUuXzM0GIoPb7oewGVa58Ne//hUAcPz48a59yfV+8MEHxrf2v2GVLUnLug8++ACu63aF5dGjR/1tJMx3w/nz57G1tYXJyUk0m00Ui8WuxuigojpRk05fmSTMnn76abTbbdx5552Yn5/3y8K4jfc4Zmdncf36dZRKJX9639XVVaTTaXPTofjoo4+AiLrFlCSs9trs7Cwcx8HS0hKmpqZQLpfheR6y2WzozZJJyvF+eVhu8KO2u//++wGtDh9EPp/H5uYmbrvtNhSLRTSbTUxOTuL06dPmpl3khxjpAOhnmGXyX/7yF6DT0WDuy9xGBoA2b/730k6WX/18+9vfBrQ23W6ks70UN7/1spdpnQ4+dpDEqMD1Hn29N3k/yOfzUP96VSr0sx1RBdNOHhMxbqakJ/ezzz4Dhjj1aL90MCwTExN49tln0W63/V+zms0mlpaWun4tiZI0jLajWCxidXUVP/7xj4HO+a+vr/udJHITjAQ3I7Jd0u0PolqthpmZGZw5cwb33XcfcrmcuclABpmyeScNs1yoVCpd35fP+vq6ufm+N6yyZZCyznGcrjDUP3FuDoep2Wwim81ibm4ON998sz/N93bNzc0BAP70pz8Fln/66acAgFQqFVjeS9wwO3bsGFzXRSqVwtLSEu68806k0+kd+SElm83i2rVrfvmxubkZOcvNdiS9AYgbVvvB9evXsby8jK2tLRw/fhy33XYbVlZWzM1C9atzhdzgR7njjjuAzg9ugzp//jyq1SrGx8dx5swZ2LaNhYWFWE/rmPkjrmGWya1Wq2sf8jl9+rT/g9x+tFPlVz+33347oD1NtBvpbC/FzW+97Ie0TgcXO0iAwONy/X4N30+VPXaxd1gKZ+zCMeVXso8//thcFTDs1wgkHezGY8HyFIm8BvPmm28il8tFdkqZdjOMLl26hFQqFTg36SSxbTtw0yZPW0U9uSLLZbuk2x808/PzOHr0KH7+859jfX0d2Wz2QHf29DLMcuGPf/yjuehA282yxbS5ubnrx4xSLpdh2zZs28aNGzdw8uTJ2E/D9POLX/wCjuPg0qVL/g1WrVbD0tIS8vl8otdfk4TZ5OQk1tfXUa1WkUqlsLGxAcdxYn8/TNRN+8TEBBYXF/1XbobRAW6SX+zDXpsIkySs9oOTJ0/ik08+QaFQAAA8+eSTKBaL5mZdpM41p7s33XLLLUCPOk0k6bALMzs7ixs3bvhPFl24cAE//OEPzc2GZphlsjz9cNDsZPnVz+effw5o6Wa30tleiZvfdsIw0zodXOwg6TQIJDP++c9/Nlf7vwbtt4LGtu2evyItLCyYixKRRo/jOP7N8U4fE9ovge+99565CgBw48YNWJbld9pIvLz++uvGlslMTk76r6a8+eab5mqg8zTFMMhTJOi8a3np0qXAGDD9JA2j7Qh7/xmda3jiiScCy6anp/0nS8zOxmaziXa7Dcdx/JuVpNsfJI1GA0tLS8jlcrHGlUlKxpz49a9/ba7adcMqF6QjwRzXQXieN7Q8uJuGVbYkLevkZtccd0GsrKzsyNMOUebn52HbNs6fP2+u2raJiQlcvnwZ4+PjOHHiBMbGxnDixAkUCoVEx0sSZnq6np2dxfr6OnK5HNrtdmQ8x/H222/37HTQx3cYNilrV1dXQ8+hVqv5HVBJwmqv1Wo1/2ZrYmICp0+fxnvvvee/7tqPdEr95je/MVcBWv6VpzfD6jRoN7phYwbFpac7ebLIcRxsbGyEHlOnjw8TJ26GWSbLTb05fopoNBool8uBHyKj6pS9sJPlVz//7//9PwDA97//fWCX0tleipvfetnLtE4HHztIOuQxueeee66r4JYe2qhBWrdr0McJ5eb0+PHj/nuo6NxYzs/PJ/qlWh94TUgD7yc/+Ym/bJjHjPLTn/4U6DTQzLBpNptwXRfPPvus32kj74BGFWpIMFiSdFo899xzgWN7nof5+Xm/gk/KvA4YT5GYg7P1kzSMtkN+FQ2rYD788EO/c1H87//9v4GQ1wEkPf385z8PLE+6/UEhna1muMkj/8Isb0Sj0YhcB23wOtd1I39x7vX9YRpWuTA5OYlUKuWPbyPjBKATHul0eihPRQkz7+ykYZQtScs6GTxuaWkJ2WzW/47neVhZWcHbb7891Hf8e4Vno9FAu93G1tZWIF1KQ14MmmYbjQYef/xxXLt2DTdu3IBSCjdu3Ig1LoMuSZh98MEHXddsDtiHzq+gxWIx0bVFdTpAe70u7iuZSTz88MOwLAuu6+LcuXOBc67VanjmmWf8G9gkYTUMnudFpvs4fvWrXwX+n56ejj3g51NPPQV06lyzvF1ZWfHL9cnJSf81KP31U/GHP/wBlmV1DT6ZxNLSUiBeJiYmYneazc7O+nW2DPwZRvY/zDL5gQce8Ad5T6fTgacD1tbW8NBDD/lj30kYnj17NjLf/OMf/zAXxdKvbg2z3fJrGGnXtm0/zw8jnW33nHZS3PzWy16m9TjMuoP2GXNam8MsaqosIVMz6VNsVatVZVlW11R+MtUUQqZb60emCnMcR+XzeX9aKn2f5rSjMuWYeR76XN76x5yqK4o+1VWuM++30qbtNKevUjGP2Wq1/CmtUqlU6Lnoxzanj5S4srS5y13XVU5nzneTxJ1lWapQKKhqZz52CTdZLvEqU3/Zth04t5Y2z7pcU6ozlaoZFr3OPyqOTXIeYemxn6RhFDV1cz/yPcdx/OO0Wi1VKBS6piUUOWPe+X5TxSXdPoykATNO9Snv9LwqU+SZ27uuGzk1qJ5uzKn1TPpxM5mMKhQKynEcP23Ytq1yuZy/H5lGWdKqOfVmGL1My+VyqlqtqlKpFEjD+XzeD9deabZf+dhvfZxyQWnhbmnT/OpcbSps86OnB5kGECHT6UkYm2VP3Hypiyor9PCIU14nKVta2rSC5rUlLeskvM2PmXeTXo/SprHOZDIqk8n0nb5QtnccRxUKBZVKpfzrkf1XKpVAWJn5QM8nYVNwSrzKp1qtqqoxvbzqUd+qBGEm8Sf5odWZmtcypryW78dJb0qbDjKVSgXKLNd1/esMy4PyPT3MBglLPS1YnWmlHcfpun6VIKx6icpjehmaz+e78nOYqLwjZV8mkwm075AgXvS0anemQrZtu6uM08M8p7WrJLzNNmPSugudPCT5Teosc3rSXuEqYSRprFKp+GlLwknSWNwyuRWj3afnO/Ojp2k9DG3bVqVSSVWrVb+tAK0c6Seqbo0qA1oRZZ553KjySw2YdiXfmWVKLpdTtm135aek6SzqnPR4i1tGRInKf4PU13Hzm4oo+9QOpvVBrkeWJ2l/0N4ZmQ4SM6HLx0yg5s1FJpPpKmQkI+ofs2LqpV6vdxW+UfuUCs5crjMbx/l8vqvwiCINBMmwUjDYtt2V6XW9jin7ND964znses24qFargULMcZzY52TbtqpUKv6y5eVl//zM45rn1tJu/mVf5rn1O/+wOA4jhfeg4oZR2PkiJC1FcV030DCxOjd1vSrM5eVlPwwcx+nKR6ak2+vM65L4CLvusGWyfVh+Q6cf2VyGGPPZlzodjdAa5lIBmw0evZFiVqy9VCoVv8ySBmBV69iVOAq7bkmz5vKk60WvciFqP+Y+lNYojCqPouKpX9kTN18Kcz+yr7CwjCqvof0OEadsCduHmU/1cO5V1gk9jcC4SVQRaSPO9Uj6trQGfS96+Os3eE7n5ltugszjoUfcSvjpN/VhH8uy/DIl7LrMMO4XZqrT4DXDLmo7S+sA7keuqVKpBPKB7N/cT1TYJF2up0UznWcyma4bNBEnrKKY5yDnJ6QDxiwvw/SK12q1qhzH8dOf7DOsvuylVCoFyjj9xlQned3c1rwG83zRp+5SSim7c5Moy+OWtXq41uv1QNtBrkP+NtNYvzI5Kk2Z+1Ehx9bLAp15zFQqper1ukqlUiqVSsUqc1RE3RoVvr3SUJzyS5ck7Yqq0QkkdURYGlMJ0pkwz6lXvJnLZHmUqLALWx73GP3yW9Q+dGZ6225aH/R6krY/aG+NqX8VpDSiarUajh49ilQqxdGZ98DCwgJuvvnmxI+BExHRf2s0GlhZWfFf+/j4448Drxu9++67uHHjRujrpERERESCHSQjjh0ke8fzPNx2223Y3Nwc6nvaRESjRMrSTz75pOe4S1NTU+wgISIiop44SCvRLiqXy/7AZOfOnUM2m2XnCBHRNpw6dQrtdrtrwERduVzumnWLiIiIyMQnSEZcsVjEmTNnYNs2rl69ypv1HSRP6wjLsvr+4klERL0tLCzgwoULAIBMJoO77rorsP6NN97A3NzcnkzPSURERAcLO0hG2NjYmLkIhUKB42HsEM/zkE6nsbm5iUwmgwsXLrBDiohoCGq1Gl555RVcvXoV7XYbAGDbNubm5vDoo4/6U9MSERER9cIOEiIiIiIiIiIaeRyDhIiIiIiIiIhGHjtIiIiIiIiIiGjksYOEiIiIiIiIiEYeO0iIiIiIiIiIaOSxg4SIiIiIiIiIRh47SIiIiIiIiIho5LGDhIiIiIiIiIhGHjtIiIiIiIiIiGjksYOEiIiIiIiIiEYeO0iIiIiIiIiIaOSxg4SIiIiIiIiIRh47SIiIiIiIiIho5LGDhIiIiIiIiIhGHjtIiIiIiIiIiGjksYOEiIiIiIiIiEYeO0iIiIiIiIiIaOSxg4SIiIiIiIiIRh47SIiIiIiIiIho5LGDhIiIiIiIiIhGHjtIdlCz2cTCwgLGx8fNVYn02k86ncb4+DhqtZq5yler1ZDNZjE2NoaxsTHMz8/D87zY6w8Dz/OwsrKCqampnmGlW1tbQzqdRjqdNlehWCxibGwMKysr5qpEyuVy5DGGpdFoYH5+HmNjY+YqrK2tYXx8HNls1lw1FHHS50GxV9fSK/52wsrKyq5fY5harYZisWgu3jG98vtBsra2hnK5bC7uUqvVdjVd7aSdLseGSa/Ph53Pms0misXijux7NxyWPHhQSFo8SO09aTNtt244TOVfWBv+MF1fr3ugMJ7noVwuY2pqKjSdDKMtt5PlOO0TinZEqVRSjuMoAGo7wdxvP6lUSlmWparVqrlKKaVUpVJRtm0r13VVq9Xy9+U4Tqz1h0G1WlWZTMYPw6iw0i0vL/thkUqlzNWqUCgoAGp5edlcFVuhUOh5jGGoVCqBazdVKhVlWZbKZDLmqqHolz4Pkr24ln7xN0ytVkulUilVr9eV6lyvHNf8mCQ/mB/Ra1/mR88L1WpVpVIp1Wq1/GU7oV9+PyhyuZwqlUrm4i6lUmnX0tVu2OlybFiq1arK5/N+uA+zLKnX6zu2792w13lQyijXdc1V+06hUFC2bftxnclk/HLbVK1W/XC1LEvl8/lAeeq6bqDc369c11W5XE5ZlqUAqEKhYG4S22Eq/6La8PrnIOt3D2RqtVqqUCj0TCfbbcvtZDlO+0f/1EbbEjdT9zPofqRCFFKASgOk3/q9sFONXGkAxS3MqtWqwg431iqVykDHSBpGg6Yf2h92Ov4k35t5o1Qq+Q2NqMaGkPxiWVZXx2EqlVKFQiGyo0MaG5ZldW0jDSRz+bDtRn7fSblcLjJ+lpeXu+K21WrteLoadfV6PTROpMFvxskwJK3n9pO9zIOWZSnLsszF+04ul1PQfpypVqv+uZudHPV6XQFQuVxOVatVvzw32w/1el3Ztt31/f1IOuPD8lWUw1z+9WrD7/b1RZV3w5D0WgZJJ0kNUo6HpUXan/iKzSFWq9XQbrdx8803+8smJiZw/fp1rK+v912/F8rlMv7+97+biw+tm266yVzU16iFEe28U6dOYWZmBrOzs4Hl2WwWi4uL/v+33HJLYL3u9ttvBwD853/+J06ePBlY53keTp8+jYmJicBydB6rv3DhAgDgt7/9bdc22WwWtm3j1KlTgeX031ZWVnD16lWcPn3aXAUAePHFF81FXeFMwxf1CibDfn9pNptot9uYm5szV+0r5XIZS0tLyOfzfhk7OzuLxcVFtNttPPTQQ4HtV1ZWkEqlsLi4iNnZWWSzWfznf/4nVldX0Ww2/e2mp6fxs5/9DA899NCBet0mrsNa/u23NnxUeXdYDZKGwtIi7U/sIDnE/vSnP5mLAvqt322e5+Hs2bPmYtIwjGjY1tbWsLq62tWpIbLZLDKZDAD0HJ/o5ZdfRqFQ6OpkAYBHHnnEXAR00vO///u/AwByuRyOHTtmbgIAeOqpp7C6uoq1tTVz1chrNpt47rnn8LOf/cxcBXQara7rmotphzUaDSwtLZmLaR96//33AQB33XWXuWpfeemllwAAP/jBDwLLZewd13XRaDT85c1mE9/61re0Lf/VoQIAf/vb3wLLH374YWxtbeHll18OLD/oDnP5t5/a8Czv+jvMafEwYgcJ7Rvnzp1j4dEHw4iG7emnn4Zt25ienjZX+V599VXYto12ux36JEetVuv5BEPU8lOnTqHdbsO2bfziF78wV/tmZ2dhWRaefvppc9XI++Uvf4l2u40HHnjAXIVGo4HnnnvOXEw7zPM8PP744+Zi2qc++ugjAMC9995rrto3ms0mNjc3gc4TH6ZUKgUA2NjY8JdNTk7i3Xff1bb6V1kNAF/5ylcCyycmJjA3N4cLFy4Eni45yFj+7Q6Wd/0xLR5A5js3h1m1M+CfvMtm23bX+2mtVkuVSiWVSqX892CXl5f9AbEymUzku/D6wFmWZQUGLkwi7n5c11X5fL5rsCF9e/NTrVb7rndd17/mQqHgv59qWZaqVCpKdcIpn88nGihMHxTLDHs9XszzEeYgXbZt++djqlQqgYGdcrlc4vcFo96HbrVagfAxySBRetiYHzkH8xj698y0FieMosi2JjOt68zrkLQYV1T6NNOXpCV5j1p/n7afpOkwTL1eD6TNVCqlMplM1zkP81rMtBz20YUtE+YgZrlcLrKMMkn6y+Vy5qousi2AwECgrVZL2QO8v768vOzvL04aljiKc5x6ve6Hr9IGskOPcsPMizp9AEl0BrE29zGstBB1fmFarZayLEvZtm2u8gculXOWj359sky2l2t0HCcynLeT3lTMsNTTWtRHT7NR5Zi5XE8HKW1gSr0MMMs5s77U06q+XI7hum5k2S+kLK9Wq4Fj27YdOsiu67oqk8n48WlZVmS46/uOK06c1DuDwEoZKOfU67xVSN1vfvQ465UH1RDSnpDyXN+Xfu3Ly8sD7XcnSdiE5XWljU2ijy+il+9VbQySqLJIymQZ36SfuPXvoGknqm5GjLEl9lv51zLuLVqdQdHNa4nT7jLLJP0TVj6FMfOlXh7qzPOBEcdxyjuV4HgqwT1QL/IdM+yi2nLCPE/zo6efuOV4nLRI+0/81HbA6RWF6mT6sIJWbyikUimVy+VUrjP4nWTYsJsJaeBKhqtqI4cjQaaOu5+q0dERltGjCggRtl4KQ8nMcv1SEMi1pzqjQEsBJ+FrRQyyaFmWX2C0tJG29Ypa9hFWaNTrdWVpgz+6ruvvw6xcS6WSglbJ65VxVFiFCTsf13UDaSEsbB3HCcShnE/YuerHiJPWws4pDjm+rlAo+PFq7k/iSCr/VqvlN8DMcwoTlT7N9JXP51UqlVL5fN6vtMLCKUqSdBim1bnBlHiU89PPedjX4rqusixLOY6j3M6MCRK2iJhFISz+VOd7+n6kgevEHNQ03xkcNSwdh5FwsCzLP2Ymk4n9fSFhMMixoxr3olKp+NcFwG+cSFrRl+ui8pYcV+JRbxBuNy0kKdfCVGIM8ix5PKzck7CQhrteJoTdiG03vcUJS6U1Uk0SR7Zt+8eLKsfM5blczk+rEsZ2p2PPcRyVz+cD+VBPH61OJ6B5nkrLQ2YcyLWGpW85L2lvFAqFyDJAyig9jGXf5jFVn/gOEydO5AZXzi/OeSstfer1iB72pqg8qIaQ9oT+vUqlolzXDexHwiPpfiXck37CrjVMrzhXPdbrN/56XRdGwt+JOYthKkb9O2jakbJRTztyjYjIV2F65QfZ126Uf1H3FvqxJH/o1yzb5ELaXb3KGNWj3SBtcgmTasRAv3I+mUzGv2Zpz+ptANXnXOIeTyW4B+on7HyqEW05kbS8SlKO69ubx6X9KX5qO+DkBllPmFGVsWQSM/NKRWoZI51LhjMTvew/bqYeZD+9MlxYAaHrtV7W6RVltVpVrVZL1Tsjo5vhFnYuEmbmMfSCSETFh1JK2SFPa8j2emUsy8xtW51Gpnl+vfQ6n6iwk8rDvImTQtPcl34NYWnNLJR7nVMviEg/UfvLdTrFdIOEYViaUNpNhdmwkPALuzkyJUmHUeT6zcZNKpXq+n7UfpNei6QF8wa9V6dbWPxJoyPs3KP2Y5JtzXPpRW/kSeM7KdlHku9KY9SM7ygSZnltWsteDZ6ovCBpXheV/5OmhbjlWhQ5D7O80UWlW2XcIOgkLeoNvGGkt7hhWa1Wu85XL3/MRnVU3EWVr/q+9PShtPMxb0iiwjHq2GHXJWRf5jGkbNDjQ9K9uR+ElAmqx3lGiRsnSsu3UectHX1C0pEevlK3hZ1jVFgOI+0pLX+GtTv0PNTrpnSvSJyYYSP6rY9D6lQzPYRJWv8mSTuSP819qwHiPOp81B6Uf3p5JPuu1+v+30nbXVH5VITFpeS/qH3px891OivMa3Y6PwLqZWrUuSQ5niwzt5VwM6+ll6jzUT3SRNLyKkk5rnocl/ankRmDxLZtWJbV9d5lGJlZ5MiRI4F3PScnJwEA7XbbXwYAly5dgm3bXYMTmv/3M6z9DJM+uOLs7CwmJibwpS99CZZl4Rvf+EZg2zC//OUvAQCPPfZYYPmxY8eglArMkBFlbW0Nruvi4YcfDiyXcGm327h27RoA4JVXXgE6A47pJiYmcOTIkcCynfDOO+8AQGBUcQD4zne+E/jfFJXW9mK8Ec/zsLS0hBMnTgSW62H4u9/9LrAuKQmfRx55JDAS+Fe/+lUAiDVLT5J02M+5c+cC/5vX3kvSaymXy0DIDEYyEGpcL730ErLZbNdI6jIo3xtvvBFYHkbeVzfPpZfLly/DsixsbGzg3//933H58mVzk56KxaL/Ln2S795xxx2A8Y59HOfPn/fDaGJiAqurq0Anb8n7+L3Ytg3HcczFoZKkhSTlWhQZX8Asb5KSQR7F1NQUYAzkOIz0FjcsZ2dnu+q9H/7wh2i321heXg4dg6EXs3zVy7Jvf/vbgWuScSh2YxyGRx99NPD/rbfeCgD47LPP/GVf+9rXAABf//rX/WXDFDdOoM3aEHXeX3zxhb+s0Wj49ZcevpOTk7GPJ4aR9mq1Gi5cuADHcQLtDhno8pvf/Ka/TK5PyupRoeeRfmVj0vo3Sdp588030W63Q+thc9DZYdit8k8cOXLEb+NNT09jcnJyV9pdAHDlypXQ+wwp9zY2NuB5HprNJpaWlpDL5bqu+fr169ja2opVDsc9Hvb4Hmg75VVUmtbLcTp4RqaD5Pz589ja2sLk5CSazSaKxWJXQTQImWZLCtRBDWs/u2FychJbW1s4f/480GnoZ7PZ0BuX69evAwNOhyX+8pe/AJ2G3NjYWOBjbiM3P1L57Lbx8XFzEZDwBnSv/fWvfwUAHD9+vCu8JY4/+OAD41u7L0k6jDI7OwvHcbC0tISpqSmUy2V4nodsNrtjlXJUGkl6k7u5uYmlpaWuODpz5oy/fidMT08jl8sBITee/TQaDf/8BrnRHQa9wRNnFoDr16/75Vij0cD8/DwuXbpkbpZYknJtPxhGehs0LIvFIjY2NpDJZCJnWzqs5MeEY8eOwfM8lMtlzMzMmJsNbNA46edLX/qSuciXtD0wjLQnP578/Oc/DyyXTsb/9b/+l79M76SkcMOof6O8/fbbgNaxvB8MIw32slvtrg8++ACu63Yd4+jRo/42f/3rX/F//s//AQZol5jiHm+v74GGWV7R4TAyHSTo/CKUzWYxNzeHm2++GS+88IK5SWJxGthxDGs/u2llZQVTU1P4r//6L/zoRz/yR1HXbbfS0LVaLXReC+v6nD59uu8vHrvhvvvuA7RGl/j8888BAN///vcDy/ezSqXSFc7yWV9fNzffM3HSYS/Xr1/H8vIytra2cPz4cdx2221YWVkxNxuaubk5ICTPf/rpp4A2G0Ec+Xy+K270z04ZpNHkeR4eeughoHONe3mjm7TBU6vVMDMzgzNnzuC+++7zO4iGoV+5tp8MI70lDctarYYzZ87Atm28+uqr5uqR4HkeFhYWcPfdd+Ojjz5K9ORVHEnjJI7JyUnYtg2EPI1w48YNWJaVqBN6u2lPfjy5++67A8s3NjZg23bgRxU5X8uytC33ljxB1K8DIu4THcOy3fo3TL9r3CvbTYNx7Ea7y3Gcrn3rn9nZ2aF2zsc5ntke2m3DLq/o4BuZDpJyuQzbtmHbNm7cuIGTJ0/uq97pg8TzPMzMzODFF1/EW2+9hcXFRRw7dszcDOj8OorOrwvb1e9x8/0gm80il8thY2PDv8luNps4e/YsHMfZ05vCpP74xz+ai/aVJOmwn5MnT+KTTz5BoVAAADz55JMoFovmZkPxi1/8Ao7j4NKlS35FXKvVsLS0hHw+n+ipiqtXr5qL9q2XX34ZruvCsqxYr9bthjivLczPz+Po0aP4+c9/jvX1dWSz2YE6iKIchHJNbDe9JQ1Lz/Pw3e9+FwDw1ltvJe7YOgwajQZuu+02fPDBB7h27RrOnz+fqIzoJ2mcJPHWW2/Bsiw888wz/itLxWIRruvit7/9rbl5T9tNe0JPQ1L+Sqe1+Pjjj0OX95JOp7t+JY/zSafT5q5C/c//+T/NRQHyo8wtt9xirtoRw6x/D4phpcFedqPdtbm56b/WEkXSUZJXh6LEOd5+MMzyig6+kekgmZ+fh23b/uOAw6K/R7edd5aHtZ/d8Oabb2JzcxMvvPBC34aaPMr+m9/8xlwFdAqffqSgfv7550ML2UajgXK5HOjd3ct3h+UG+PLlyxgbG4PjOJibmxta7/9Ok3F6lpaW0Gg0zNXwPC9WvO20JOkwSq1W8zvvJiYmcPr0abz33nuwLGsoj5mHmZiYwOXLlzE+Po4TJ05gbGwMJ06cQKFQSFQ+2baNzc3NyLS+sLBgLuoiv/bJE047ZW1tDRcuXAAA/Pa3v+35Cly5XA5Nd//4xz+AhE/YRJFyxPw12dRoNPz3sIfd+I9brvUi77/L00c7abvpbZCw3M64I4fFxYsX0W63sbi4OPQOokHiJInp6WlcvHgR6LQFxsbG8MYbb6BSqSQ63nbTnk7Pa9IRIk9+yvoXX3wRAPDUU0/5y/tZX1/v+mU8ziduu2B6etp/osX8hRudX7kB4IEHHjBXxaaHTb9fy4dR/0aRMv711183V+2ZYabBMLvV7pK61xx3TaysrKDZbOL2228HOp0bUecT50nbuMfbD/dAwyqv6HAYiQ6SRqOBdruNra2tQAVg3hSENVL7mZ2d9Z+SyOfz5mpfv30Paz+74b333gOMAYg8zwucm/wtDYzV1dWuwnRlZaVnw97zPDQaDTzwwAOwLAubm5tIp9OBp1HW1tbw0EMP+Y0CeTT47NmzkWElN1o7wfM8pNNpXL58GdevX4dSCltbWzvSuIUWRsM0OTmJVCqFdruN+++/3x+XA528lE6n/cpsLyVJh7386le/Cvw/PT29owP6NhoNPP7447h27Rpu3LgBpRRu3LiR+HWKJ554Aui8s1wsFv1GRbPZxPz8fKxfgeVx7J0cTMzzPPz7v/870BmItl9D46WXXgptcMsjv0kfITcbW41GA5ubm6GDz5n+/Oc/AyH7MMutOOnMlKRciyJPwJjn10vYzVUc201vScOy37gjUTcqO0U6o/RHwT3Pi30T12g0Bkon8qu1PmCkGYaD7BcDxElS5XIZ7733nj+oo1IK169f71sGmLab9qANgn3lyhV/mdQhUt57nodTp07BdV3k8/m+nQS77dlnnwVCOg5qtRpc10Uul+vZ+dyPjIPRb1BKDLH+DSPjA0Z1FsAY1DWJvSr/+tmtdpcMKLq0tIRsNuuHr9fp8Hj77bcxOTmJ6elpv6Pq8ccfD5QRzWYT6XS6Z/0k5V3c4+2He6BhlVdxDZoWaZeY09ocVjJNlsxVnerMQy7TN+XzeX+qS1lu23Zguid9CjR9WkyZrx3a1JeVSsWfWhid6R3NKZ9MSfejT/9lTq+nT2dpTjnZb32r1fKno0qlUl3flWkHJdzy+bxKpVKB6T/1aa/0cLZtW6VSKWXbdtdx9fCVfcp6mRY47KOHq35dtm2rUqmkqtWqP12ZXG/Y1F8mmRLQTAdKm67LnLZTwiaTyahCoeB/KpWKqlarXfOiRx2jV1qLCqMoetiZ02PKVGjm8V3X9cPL/JhTmkWJSp96HEWFnz4NXpSk6TCMTB+XyWT848kyPY0M81okP+fz+UAaqXamNjXjs1f8ybHNj5m3okh6Ms+9F9d1/enwzGsLI9drpjFTvV5XmUxGpUKmdlRaORJ3ijw9LPS4dRwnNHzC8qKe3yRPO44TuKZcLqdc1x0oLcQt13qxLEtZxtTzOjlXx3H8NKd6pKtWq+XHrzl98HbSW5KwlG2j0szy8nIgf0aVY2Fxqow0bNYF+r70uJJyQcIln8+rTCYTCMd8Pu+HpR7nhULBTxN62WrW2xIWerkuy2Q/uVxOZTIZfx+5XM6/hl77DpMkTlxtuktz32HnrbS0qZdzy8vLfllnioovtc20p0LivNUp063ONKalUikyTewXehkjceC6rnI6067GCYdeZDryONefpP4dJO1IeS/pp1qtqkKhEKh7CoVC7Ppnr8s/paVvsx4Qev41P2ZbRk8LYcePuj6lnYf5sYype+vaPQk6cSRtX7N+iirv1IDHS8W4B4rS0u5h9POQdVFlZJLyqldZG5Wmo9Ii7U8j00FSr9f9Qs9xHD+xS8UiGc7MwOhUFpLZ9I/ekJfGvazL5XKq1Wr5f5uZK0rc/RQ6jbiw8wlbJ59+6/VGoLlcpxf0+XxetVotv0A2CwXVqXj1ik2uy6Q3kMxC3QwbPR51rVZL5bQOkVQqper1ul+49ytcldYBon+kkjaXQ+tnNCuUsI8UiuZyWRd1bNErjExhcS3pxFwOI57NcLRtu6siiBJ13Kjwi1rerwJJmg5N1c4Ns6RNhFznsK9FGqFRH8uy/E6xqGPrCkajUcIhLtu2lW3b5uJQYWlTPmH6XWvYx2yUiiTnqbT0vby83Dd8wq5Ljy/JA5lOR5o0jiQPRsV51HI9Xcct16LIjURYg1sZdZ+Ebdj1plKpHU9vccJSdeLaPA/z06sc7RXuYdeITvo1l8m+RKFQ8M9f6rBqtaps21YF42ZNb6RLWRR17KjzNfejl01S9kmc9tpHL3HiJOl5S5hJ2oz62FonVFiaNMv/7aQ91QnLQqcTyDyW4zh+Z9B+ZtbLVo/2VFL9yhJTnPp30LSjjPi2bVtVKhV/2fLycqxr3i/ln7lfhKRvFRK/ep4XYecpn6j15nVUKpVAPpC8b3JdN5CPHccJ/Ggnwso7XdzjmfVh1D1QL+a1o5Ou+oVL3PIqbD9yDHMZjPsDMy3S/jWm/pWYiGgI5BFdebXo888/DzyC+umnn2JpaQmu627rUVg6uBqNBlZWVvxHTz/++OPA48Lvvvsubty44b9TvtPW1tbw4IMPol6vh77ash80Gg3ceeedid4FHutMl3vYq7hmswnHcXDx4sXQV1GI9kq5XMZnn33mvxpgzlTx61//GnNzc3syaHO5XMbx48dRKBQSv954WI2PjyOXyyUaC4vosNjP5RXtPnaQEA1ROp3G008/3fMmLp1OY3FxkR0kI8jzPNx222345JNPeo5/MTU1tWsdJOjMvoQ9GNchrvn5eWxtbSU6v1HpIEFnPKcXX3wR165d65muiHZLrVbDM888g+vXr5urfLVaDa+//vqe3HAsLCzgwoULqFar+26skb1QLpdx9uxZliE0kvZ7eUW7byQGaSXaDSsrK9jY2MD//b//11zlazQa+PKXv8zOkRF16tQptNvtrgGideVy2R8Qbre8+uqrcF13KNNxD1uj0cD169fx6quvmquo4+TJk5ibm8PLL79sriLaE9/97nfRbrd7Dqr4+uuv+0/S7TYZ/FZm6xhlnufhpZdeGtmptIn2e3lFu49PkBANibyqgM4o8I888khg/Ycffoi///3v+I//+A82QkaU/GqJzqwKd911V2D9G2+8gbm5uT15xFleD3vuuef2zas2jUYDZ86cSZxnarUajh49CgAj9QvxwsIC/u3f/s1/Iohor8zMzGBzcxOWZSGbzeLWW2/1133xxRe4evUqfvKTn+xZWh0bG4PjOD1/MR4Fnufhhz/8IQqFwr4p94l2234vr2j3sYOEaIiazSZ++ctf4urVq3BdFwBgWRbm5ubwve99j4UroVar4ZVXXsHVq1fRbrcBALZtY25uDo8++uie38yvrKzgjjvu2PPzqNVq+PjjjxOPq5FOp7GxsRFYlkqlsL6+Hlh2WK2treEf//gHyxrac+VyGa+99logPzqOg7m5OTz22GN79iSldKDmcrmRfly+2WzizTffxGOPPZaoA5roMNqv5RXtDXaQEBEREREREdHI4xgkRERERERERDTy2EFCRERERERERCOPHSRERERERERENPLYQUJEREREREREI48dJEREREREREQ08thBQkREREREREQjjx0kRERERERERDTy2EFCRERERERERCOPHSRERERERERENPLYQUJEREREREREI48dJEREREREREQ08thBQkREREREREQjjx0kRERERERERDTy2EFCRERERERERCOPHSRERERERERENPLYQUJEREREREREI48dJEREREREREQ08thBQkREREREREQjjx0kRERERERERDTyRqqDpFgsYmxsDCsrK+aqkZROpzE+Po5arWau2lGe52FlZQVTU1O7fuyk11yr1TA/P4+xsTFzFdG+I+k1nU6bq2iI1tbWkE6nD0w4N5tNLCwsYHx83FxFmkajcaDKez1e49Zph1Wz2cTU1BSmpqbgeZ65eiQ1m03Mz89jfHwcY2NjSKfTaDQa5mb73mFtu5fL5X1Tj/SqI+K0m2u1GrLZLMbGxjA2Nob5+flAPuy3fj9YW1vD+Pg4stmsuYpG0Eh1kNDeq9VqOHXqFJ588km4rmuu3lfK5TJeeeUVLC0tmauI9p2FhQWcOHGC6XWHrays4Pnnn8fGxoa5al8ql8vIZDK4cOEC2u22uZo61tbWcPHixQOTf2q1Gq5cucJ4pVDNZhOO4+DRRx/F1tYWcrkcNjY2cP/996PZbJqb0y4rFot46aWX9kU9st06Ym1tDSdOnMCFCxfQarXgOA6Wlpb8jp9+64n2JUW0B1KplAKgqtWquWrPLC8vd51Pq9VSABSzymAymYy56FDZb9dXrVYVAJVKpcxViYTlhZ2028fbrmGF825iORbPIOFUr9dVoVAwFw9V1DEcx9l3delO22/l7n6UyWSU4ziBZblcTlmWpVqtVmA57bywNFupVPZVPTJI2aeUUpZlqXw+7//farWU4zj+dfVbvxfC4oNIxydIiDpefPFFcxEmJibMRRRTs9nE6uqqufjQOMzXF5YXdtJuH49omHbj0f+oY4xaHVUul/H3v//dXEyG1dXVrrSxuLiIra2truW0s6LaCjfddJO56MCp1Wpot9u4+eab/WUTExO4fv061tfX+67fCyxDKA52kBB1Gp/7/ZWfgyafz5uLDpXDen27nRd2+3hEw9RoNHb8tZzdOMZB4Hkezp49ay4mQ6+xImj3Hda2AgD86U9/MhcF9Fu/21iGUFzsIKGR12g08Nxzz5mLaRvK5XLoLyaHxWG9vt3OC7t9PKJh8jwPjz/+uLl4qHbjGAfFuXPn2JlKB8phbSscVCxDKDbznZvDqtVqqeXlZWXbdtd7vK1Wy383E4ByHEflcrmu7aK4rqsymYz/fcuyVC6Xi3zPs1Qq+e8Ny/EqlYq5mVIh22YyGf86lPYuvHz0c5ZxPsLeK3RdV+XzeWVZVuDd5Xq9HlheKpWUZVnKtm3luq6/XbVaVZlMxt93KpVS9XrdX6+rVCqBa8jlcrHfmy4UCoFrkOsIW65fu75cjhF2zZVKxY83/aO/G6kfV78Wx3EirzlM0nQSRj++ZVld7xm3Wi0/zRQKBT9tyzVEHa/VaqlCoaBs2/b3HZX+zbg381RY3KATP67rBvJhvV5Xtm0ry7ICeUDOWz+fXC4XSIOynZmvC4WCH8b69ephZ9t2ZJ4zr89M272uT7iuGyhTwo4XN69FMcst27ZVPp/3z9nU75zi5AUVUiZFpSnzeGZ6j3u8QqHQVQaa5Yak+1QqpVKplGq1Wn75F5WORb1e989Tdc5L0p0ZRkLKXfNcVWc8lbjle78w0vVLl7qwvCzfi8NMm1J2SZiUSiXzK0p1vqeXcZIvzesx92+mfbOs1ssxuR6hX2tUmCSJk7jh5Lquf1zzo4sbJmHiHEPSebVa9Y8lx4mKpyRpKYq5D/MjeaNfXMu+9PaKhJFOX69/qp2yoFqt+mlEV6lUAsur1WqsOtws58yPeX5h9PhAJ0yk/KoO0HbrV86Z+4zaf5L8kKSMMsMsarskwur4OFoJ2jQ7RS93w+JC4kvyin6+mUwmNOyGdV1h+5Dz05llsf5987rkU61W+66PUy5IvRMn7amQ9GemazNf6ecj35e8FaZSqQT24ThOaBk7aJlD+0v/VsAh4LpuoDAwCxOptCTTSUY1twvTarWUZVnKcRz/+1IwhGWyXKdzQDJkvV73M79ZQeU6N4iyrd5IlYwnZLl5zpXOIFD69mbhpZ+L3GABUPl8XuXzeT/cpCCQ8JHvVatVZVmWsiyrK+OXSiUFQC0vLysVcg16gRtFP1e9YJR9h+2n1RlcVY4bdc1CCj1zudIazFJ4FgoFf3u701HVT9J0EqbaqUzD0oP8rzd8Cp0bS/nIdTjGwG2tzoBZUvG0tJuRXC4X2FbiXtKCfBed9KKT4wmp2CW953I5lcvl/LCUY0meyGkdIsvLy11pzMzX+XxepVIplet0burHkYpTjzvLsvz9iyRp27w+Ieevp3kJIwm3uHktioS74zj+Nci5IyRNxTkn0SsvSPmlxws6aUrPm3K8gnYjKGnKTH9Rx9OvUcK+Wq2GhpGe7iUNyPF65dFKpRKIB+m0SaVSfljKcp3kRTOcJU/LubnaDa55fUnCKEm6zHVuZvRt9fzfj5k2JWwLhYJ/fgBC845sL+WI7EdPH+b+zbQv+dc8vmwny0ulksrlciqTyQTKATPsksSJ6pGvo8j+CyHthbhh0k+vY0j+SRJPZvqISktRpF2R0+oMSWN6fusX16VSyc9LUv63Wq3I9kxUvpO0IMcRlUol0N4oxazD5ZylvJS8qp9nP61OnS/XIPUfjHQXda1hbbe45VxUOKmE+SFJGZWLWTckYdbxZhhFkfSop08577jxN0xmPAo9niQu9es1z3VY15WLWUdU+7SbVZ+ySUWsj1MuSP7R04/sKyxdS/qTc9TzrF5/R+UNvUww1yktzGRfruv62+thP2iZQ/tPd449xMIyquoUXmYDuFAodG0XRioBc1vJHDppLJmFjBQUeoNfztVs3LQiZlWJujYVcS6qx42JLM93bnhbrZa/jeu6od8JK7ikIDLPSQq+sP1EkYLTDI+oa5DCyxS1fdRyZXSQ6KLOKUySdBKl0Onw0ElY6iQubK1zTRkdSvq15DqdFLqwOJK4N69Bbyzroq5Nzk+/lmrnV2LVmZUhrAKRMDTX6fvTG2KS/iytY0BIfOvhkCRtqx7XZ4f80qWfi36OvfJaL6nODby+L9XjXAc5J/M85MbKPKZsr+/ftu2uc3BdV1mdX4h0UceTctHMX/V63Q97fZ1+PbK8Xq93fT+M7C+fz/vX14q46VM9GlmSZ3RRZXPcMEqSLmWZua2cr3luvci1m/laGuR6npLzNrdV2g2gua5f2pf15veiyje9zNLjPEmcqB75OkrUvgYJkyhRx1A9wkniaTtlXBSp+/SyQPYdtv9ecS1hoX8nKn9FLRdhcdfS2kxRdbjeMSTXYda1ev0Zh5xrWHmpX2uvuA07Xpxyrlc4JckPccuoJHXDIKLOL0rcNs1uCYtHZcRlWBo0651hXNcgdYTEo/kdFSNueq3vVS4kaTMnubfqlTei1kkb1yw/Wq2WX4bo65KWObQ/cQySjueffx6e5/n/P/zww4H1Ub72ta8BAL7+9a+bq7qcPXsWjuNgdnY2sPz8+fNQSiGbzQKdd44vXbqETCaDycnJwLa7Ofr4t7/9baBzTDnnK1euwLbtrmu49957AQAbGxt+OL7yyitASFhOTEzgyJEjgWX9PPHEEwCAN998M7D8xIkTgHYsceXKFX/dsEj8iKmpKQDA3/72t8DyMEnSSS+bm5sol8v+/xMTE13nJZ544olAPGWzWeRyOQDAa6+9BnTS2tLSUldY6XH0u9/9DgDwy1/+EgDw2GOPBbY9duwYlFJYXFwMLO/nkUce8f+enZ3FxMQE1tbWsLm5iUwmE9gWAE6ePAnLsuC6biAMxCOPPBLIH3Lt7XYbJ0+e1LYEvvWtbwEAPvvsM39ZkrQdZW1tDa7rdqV5/VyuXbsWWIeIvBal0WhgY2MD2Wy2qzyQc9UNek6ml156KfSYEpZvvPEG0Hnn2nVdPP3004HtJicnsbW1hRs3bgSWh/E8DxcuXIDjOF1l4PT0tJ8+JE3qjhw54n9nenq66/u9nD9/3r++iYkJ/91x13VjDXxo2zYcxzEXd0kSRknS5aVLl0K3Nf+PQ8Lh0UcfDSy/9dZbAQBffPGFv+zKlStot9v4zne+o235LzLGzNLSEprNprm6b9o3jy/XPTU1FdheL7P0MjlunAzbdsJkEGY4STwNu4xrNBr+O/x6WTA5Odk3nMPi2rZtWJaFr3zlK8bWw6Gfo1lXSh3+z3/+01/2+9//Hghpaz3wwAOB/+M6d+5c4H+zrh3UoOVc3PyQpIyKWzfshiRtmv3iyJEjmJ6e9v+XuNTHyhjWdQ2zjhiWsHIhSZs57r3VoJ5//nkgpAyYmJjAz372M6BzDvpyYR47rMyh/YkdJJ0Rpjc3N3HbbbehWCyi2WxicnISp0+fNjftIjeHx44dg+d5KJfLmJmZMTeD53lwXberAglz7do1tNtt3HXXXeaqPffBBx/AdV2MjY0FPkePHvW3+etf/wp0ppmDVthvh9zc/frXvw4sf+edd5BKpbC6uuo3ND3Pw+rqalfBtJfippNeHn74YViWhePHjyOdTmNtbQ3oTN0XlzTWNzY2AC2ujh8/3hWnss0HH3wAALh+/ToQ0nAcpj/+8Y8AEJgSTjc3NwcA+MMf/mCu2rYkaTvKX/7yF6DTCDX3Y24zKIkXuQHqZ1jntLm5iaWlpa59nDlzxl8PAB999BGwzSkMpcMmKq3df//9AICrV6+aq4ZKv+mLMxr/9evX/XzSaDQwPz+PS5cumZslCqO46VKmU5QG2G6SeAi7nunpaViWBQB4//33zdU7Lm6cDNt+DJO4aamXL33pS+YiX1R+7eX8+fPY2trC5OQkms0misVi103gboqqe5Je2+zsLBzHwdLSEqamplAul+F5HrLZbNeN3G6Kmx+SlFFx64bdkKRNc5AM47r2so5IKm6bOcm91SA8z/PTb9gx7rnnHqDTmTWszm7aH9hB0qmgq9UqxsfHcebMGdi2jYWFhb6/pAjP87CwsIC7774bH330ES5fvmxu0rfRoYtzs7KXHMeB+tfrWaGf2dnZWL+2JjE5OYlMJgPXdf2OgVqthrvuustvTF25cgXo/AIU9gTCXouTTnqZnJzEJ598gnw+j42NDTz44IOYmppKFNZRjZ1KpdIVj/KRuep3o5HTr4KXTsOdqojipO04Wq1W13flE6fjtZd3333XXBTLMM4pn893fVf/IEYcxtGvDLzjjjsA4xe2nRLWKOqlVqthZmYGZ86cwX333ec/taVLGkZx0mWcDpyd0q9skF849acZdlOcOBm2/RomcdJSL5OTk7BtGwiZTvbGjRuwLKvvPkzNZhPZbBZzc3O4+eab8cILL5ib7BqJl/fffz/QBpQ6J0nb4vr161heXsbW1haOHz+O2267DSsrK+Zmuy5OfkhaRsWpG3ZTnDbNQbSd69rLOmIQcdrMSe6tBtFv//qTP3GeJqeDgx0kHbOzs7hx4wZKpRJs28aFCxfwwx/+0NysS6PRwG233YYPPvgA165dw/nz5wMZRsjjo3EeYRWffvqpuWhf2NzcjH0Nw/TUU08BAH7zm98AAF544QU89thjeOCBB2BZFpaWluB5Hl566aWu10D2Wtx00s/ExATOnz8P13WRy+Xgui6OHj3a1VDtx3zEVp7c6EUaxdJBtRPkaaMPP/zQXBUgj+4O27DSdpxXVnbbMM4pzhMbEodxHveNcssttwAxfl1PpVLmoh0T51Hf+fl5HD16FD//+c+xvr6ObDYb+ot00jAaVrrcKVI2fPzxx+aqgLBXwHZa3DgZtv0aJsNIS2+99RYsy8IzzzzjdxwUi0W4rovf/va35uY9lctl2LYN27Zx48YNnDx5El/96lfNzXbN5OQkSqUS2u02zp07B8/z4Hke8vk8LMvChQsXzK/0dPLkSXzyyScoFAoAgCeffBLFYtHcbNfEzQ9Jy6g4dcNuitOmOYgO63WZ4raZB7m3SkJ/9a/RaATWmZJ2DNP+xg4SAAsLC/7f2WwW165dg+M42NjY6JshLl68iHa7jcXFxZ6/NE5OTvqP1JrjaAipNKXBJI9k7idSaZrv1YqVlRU0m81AQRE2XsQgZmdnYds2VldXUS6XMTk5iYmJCUx0xuFot9t4+eWXYdv2UF7rGaa46aSXYrHop4fJyUksLi6iVCoBIWOwRPnHP/4BaK+qSOG/tLQUmtY9z/PTpXSqSAeVaRiNvvvuuw/o0diSTsOduKmIm7Z7kRt7c0wj0Wg0tp0fpHPIfN0syrDOybbtrjFwdFKOSiNmdXU19Hi1Wq1vh578ittut0PT5eeffw7sYEeZTq7h7rvvNlcFNBoNLC0tIZfL4dixY+bqgCRhFDdd6uNI9EunwyblyXvvvWeuArQnC26//XZz1Y5KEifDth/DJG5a6md6ehoXL14EOvXC2NgY3njjDVQqlcThPD8/D9u2cf78eXPVnslms8hkMmg2m/gf/+N/4H/8j/8BdOIybtuiVqv5PyZMTEzg9OnTeO+992BZVugrLbshSX5IUkbFrRt2Q5I2zUEyjOvayzoiqbht5iT3VoPQn5j785//bK72w3E3f6yh3cEOkk6Bo1cAExMTgQEke5EbOf3RKrPgkX0/++yzQGeANv0GwfM8zM/P+zcys7OzsCwL7XYb6XQ6cG5RFZAUfObj98N+nFMGgltaWkI2m/ULas/zsLKygrfffttvQMhjm2fPng2tYKHdsMclAyLNz8/jpz/9qb9cBuG8cOECfvSjH/nLB9XvBi6pJOmkF3mNSPQaZyXsCSTp3JAnbCYnJ5FKpdBut3H//fcHOuUajQbS6bSftuQJntXV1a50tbKyEno8XZwwzWazsG0b7XY7tFK7evUqUqnUjvTUJ0nbYWq1mv800+bmZmCcGHSevHnooYe6BvpKSsbjcV23Kx6Enpa2e04SbzJQ8vHjx/2xmtBJx/Pz8/6vkDJWjuu6/i+w+r6eeeaZnvFXq9UwOTnplx/yHrvuD3/4AyzLGvqTYmaebDQa2NzcRC6X69lIg9Z4Mvdh5gvP8xKFUdx0KR3I6DzuHiVOOZOUlMWrq6td+bzZbMJ1XTz77LN9w3DYksTJsDQaDXiet6NhIsdIKm5a6qdcLuO9997D9evXsbW1BaUUrl+/3vem29RoNNBut7G1tRW4HukAFVHX6nle6M3ids3Pz+P+++/H+vq6//pCuVwO/QW7l1/96leB/6enp7sGqN+tthsS5ockZVTcugGdm9WxsTHMz8/7ywbldToF9DotSZtGlhWLxa50lE6nMTY2Ftnm3g6zPIgj6XWF2cs6Iqkkbea491Zh4pQh8srfc8891xU28pSrPkgrHRLmtDaHmUwplclkAsvRmdJNpohyO/PCm1M9hZEp6qzOXPG5XE5lMhl/2q1cZ15zZUwbKcdMdabrNKfok2ml5JNKpZTjOJFTzelTfWUyGVXozLmtT4mZyWT86Yz17cOma4Q29ZZJn79c/5hTlZnTZJZKJVWtVlWuM584OmFgTuPVi0yfZYaX6jE9rIi6ZqXFo+M4Kp/P++ekx4N5bTJdV1Q46ZKkkyj6dGkynV7YlG2yTL/OVqvlLzenHdPj3PyY4SxTR6ITp6lUStm23TXFrtKmE8xkMiqTyahqZypfyYepVKrrO8qYv14/f0k3+nSG+v7MfK1PW6eHT6vV8uMjk8kEziFu2lYR16dC8q7+Mafc7JfXoujlQC6XU9VqVZVKpUD5ks/nE5+T6pEXlDb1q/kx418/P8uy/PIrLByjjqeXH7lczt+/TP9nTs0ucWemkTj065DvVqtV5ThO17Up7Vi2bfvrzLK20JmWW67Ptm2Vy+X8/ScJo7jpUs87qVRKVSoVValU/HOQczPj3KRP2RpVVpr5V67HsqxAXSphqOuX9vX15vGlHLNtOxDPUm9DmxoyaZxElfe9SHq0OmW7Xg4lCZNeoo7RK5yi4iluWurFsiz/XOSzvLysqtVq11Sb/eJa1jmdtkAqlQrUM/l83s/renzm8/nAtenlvX4dej6LU4fLMeR85CPtl7hhJOeTyWQCZQqMqUtbCdtucco5CT8zTs199ssPScooKavNj1l+6uv6lUMiqo6XsgBGe1hPc+bHbNPo7RGhpyWETDWflB6/Ga2tEFaPKCOe9HouyXVFSVpH6OnTLGP0OtqM537r+5ULcj5SzvRqM+vHkWOlIu6tepUhkp7M+FBannKMNoJlWV3nn7TMof1pJDpIzMJOPkJu8GS5JHgzg4RpaTdotm37BYgUfGYmaHVuVCWT27YdqCx1lUrFPy/btv2C0jx/fXvJfFLBqk7hnMvl/P/1SkU+qVQqdHnYcZRxbjAaAbqWdmOrn1cqlVKpVCp2BamTG0JTqVSKDMuwa9MrxHq93lVwSbya3+m3rzBJ00kYaTjpFaSjdezp26FTgeiVXti2wown/RxNpVLJDytJW2F5pVQqKavTkJbGpRluCJm7XnUqT/N8zDzZa39RcRf1HV3ctG1en65er/cM+7A0ZJ5HP/p5SiNCr7DNc+53Tvp2Zl7QFQqFQPyb8SLMeMhkMl2NatXneFJemunN3I8ZjjBuQvqR7ywvL/e9trC0JceSNCHX67qu3xC0bbvrvOOGkUqQLs14lvwpf4fFuS4qbUblHX1/1Wq1K42Z5UjU/uOsN5ehE/Zh35EyOW6c9NpHL3rZngrp9I0TJv2EHSPsfNEjnnRx01IUuVmI+tidzquoc9Tp+V8vk5zOjbhZtkqdqcddVJ4MW56KqMPlvFrGzVbYJ066qHY6WOXa0KNejdt2M88DRjkXFffQ8mnc/KDvM24ZZZbVYeWn1Ot2j7aviLoefb1lWSpjdJyoBG0a6XzU10kasG1bWVrn5qDC2grmNaFHmtXDKe519RK3jgjLJ5L2w9bJp9/6qHU6vczTrzGqzSxloh4uUekrrAwxzwUhbdOS8SNURuu4FGHx16/Mof1pTP0rYdABMtaZnpNRR2GKxSLOnDmDQqEQe3YSolHGMpUovnK5jM8++8x/pN+cHePXv/415ubmEk1Bv5/Mz8/jO9/5Dm666Sb84x//CMyq9cUXX2BpaQmLi4s9X3Gl3orFIm6++Wb/9ej9Kp1Oo1AoJH69iogONnaQHEBszFMv7CAhSoZlKlE8Mv7E9evXzVW+Wq2G119//UB2kBSLRXzxxRc9B40tFou45ZZb2EGyDel0GouLi7HGvNkrnuchnU73TOtEdDhxkFYiIiIi6uu73/0u2u1212CFutdff90fEPYgaTQaOHPmDFzXNVf5PM/Du+++23Nga+qtXC7jxIkT+7pzBABefvllXL582VxMRCOAT5AcMI1GA3feeScADDSlHh1unufh1KlTWF1dRSaTwauvvjrQLAlEo6JWq+Ho0aMAgGq12nOGHaJRNzMzg83NTViWhWw2i1tvvdVf98UXX+Dq1av4yU9+ciCfrmg2m3AcB+12G7ZtI5PJBGZg+fTTT3H9+nVcvnyZr1wMaGFhAd/85jf3ddu12WziypUr+MEPfsB4JhpR7CA5QNLpNDY2NgLLUqkU1tfXA8toNOk3ejre9BGFY5lKlFy5XMZrr70WyDuO42Bubg6PPfbYvn8yoBfP83DlyhW88cYb2Nzc9JenUil8//vfx8MPP8wfHYiIDjl2kBARERERERHRyOMYJEREREREREQ08thBQkREREREREQjjx0kRERERERERDTy2EFCRERERERERCOPHSRERERERERENPLYQUJEREREREREI48dJEREREREREQ08thBQkREREREREQjjx0kRERERERERDTy2EFCRERERERERCOPHSRERERERERENPLYQUJEREREREREI48dJEREREREREQ08thBQkREREREREQjjx0kRERERERERDTy2EFCRERERERERCOPHSRERERERERENPLYQUJEREREREREI48dJEREREREREQ08thBsgeazSaKxSLGx8dRq9XM1UO3srKyK8eheBYWFtBoNMzFRIkVi0WMjY1hZWXFXLUvNBoNFItFc3Ese51PyuUy0uk00um0uWpf8jwPKysrmJqaGjjMt6tcLmNmZgZjY2MYHx/fs/MgIiIiGhQ7SHZZo9HAlStXcObMGbTbbXP1UHmeh3Q6jXvuuQezs7PmaqCzTbFYxNTUlN+onZ+fh+d55qYjbW1tzW/4j42NYWZmBmtra+ZmQKcDLJvN+ttms1k0m01//Y9//GOsrKygXC4HvjcoOY750W/s5EY67MPOM9oJ5XIZKysrOH36tLkKAFCr1TA/Px95Ez3sfJLEysoKXnrpJWxsbJir9qVms4krV67gueeeg+u65updsbCwgHfeeQfr6+uo1+sAgDNnzmBhYcHclIiIiGj/UrQnUqmUAqCq1aq5aiharZZyHKfn/mUby7L87arVqgKg8vm8ufnIKpVKCoDK5XKq1Wop13WV4zgKgCqVSoFtW62Wsm1bpVIpValUVKVSUY7jKNu2VavVCmznOE7X9wcl8QZAZTKZwLFEq9VShULB365QKJib0D61vLzcMy/vN6VSSaVSKXOxUp20ms/nY6XD7eSTer3ec9/9SJ6Kuo69lslkzEV+uG7nugdRr9cVAFWpVALLLMva9XMhIiIi2g4+QXJInTp1CjMzM5FPjgBAOp2G67p47733/O1mZ2fhOA4uXLhgbj6Sms0mjh8/DsdxsLi4iImJCUxOTmJ1dRUAcPz48cDTIb///e+xtbWF//iP/8CxY8dw7NgxrK+vY2trC7///e/97SYmJnD58mUcP358KK8RzM7OIpVKAQDuuusuTExMmJtgYmIC9957r/9/1C/7tP+8+OKL5qJ9q9Fo4Pjx41hcXDRXAZ20ev78eeTzeXNVl+3kk/362tEwlMtl/P3vfzcX4+abbzYX7Qp50uamm27yl01PT2Nra4vlDBERER0o7CA5hNbW1rC6uoqTJ0+aq3zFYhGbm5t49tlnMT09HVgnN9f6jf+ounLlCgDg8ccfDyyfnJz0OyT0jo/PPvsMR44cCXRQTExM4MiRI/jss8/8ZejcQKRSqa59E+lWVlb27LWJQTz++OPIZDKYnJw0VwX827/9m7ko1CD5pNFoYGlpyVx8KHieh7Nnz5qL99S7775rLiIiIiI6kNhBcgg9/fTTsG27q+NDeJ6HS5cuwbIsPPbYY+Zqf/yRv/3tb+aqkSNPitxxxx3mKnzrW98CALz99tv+sltuuQXvv/9+YAwXz/Pw/vvv45ZbbvGXie9///vY3Nzck3EWaP9rNBp47rnnzMX7VrlcxubmJr73ve+Zq7p89atfNRdFSpJPPM9L1Jly0Jw7d+5AdZgRERERHSQj1UFSq9WQTqf9wSnDRvv3PK9r9gKZGUAG3AwbwNQc7DTsE3cwzFqtFhjkM51Ox368vFarwXVdzM3Nmat8b775JtrtNnK5XOirGJubm0DnUfhRJzciX/nKV8xVfofH+++/7y974IEHAAA//OEPsba2hrW1NaTTadi2jWw2628n7rnnHgDAO++8Y67aM/pMFGNjY12D9jabzcBsGZ7nYWFhAePj4xgfH48clLHZbGJ+fh7j4+MY6zMg8HbyQD/9rk+YeVrOt1gs+nFpDn6r53F9uTkTioSZXl5ks9nANa6treH+++/3B3M+evRoYF9en1lLPM/D/Px81/mbT4YNGp9hXnvtNQDAkSNHzFXbEjefNJtN3H333X4ZdubMGT989W2y2WysdGiq1WqBeDXjPCzNhMVNo9HoSt/ZbLZvHZFOp/0nYzY2NkLPQUj894tHM19OTU1FDkBtkvpUXrGRNKqHN7Tr1Y8hac3cTtJerVZDuVzG+Pg4pqam0Gw20Ww2A+vlGsPCWo+HYZYfREREdMiZg5IcVjLgXi6XU6oz+F8mk+ka0G55edkfgDOVSqlcLqdyuZwqFArKtu3APnTmYKcysGfYQJ6qxyCtpVKpa9BUy7KUZVmqXq8Htg0TZ5A+uT7z2EobbO8gJA19wNGknzj0gU/DRK2v1+t+2oI2uGsU2a7XNnFImuoV91HnLHK5nHIcR7muq1QnPwBQjuOoVqvlD/RqWZZCZzDfVCql8vm8yufz/nIzzesDNsp15nI5f9+67eaBXvpdn5DBQVOplL9ttVoNlA36tlI2mHlK8qM50GcqlQpcj8SLZVld6SCsrHBdN1AmmXEu4Z3L5QLXaobjoPEZptVq9UxbJrlm89yjyL7N8AkjZYO571arpSzLCsS3bGvGkZyfuTyXyynbtlWpVApNM5LfW62Wn8b1OkPOQc5N4sCM4yhR56W0a4kbj5JOlpeXleqkq6gBqHsJS6NC6sLl5WU/XCRf6PFQr9cDg/fKuev1rl7mS10t28nyUqmkcrmcymQygTxiljNEREREYeK1ZA8BuWHVG3BRDc1KpaLQuVnRb8hc1/WX66QBmDdmfpHGsbl/FdGglP2bjcyoBnwY2a8+m4BOv4np9YlzrMNO0gcibvj6rY9Lbl7MeE9K4j7uxyQdE+YNqOxXv9kMu8FRWl4wZ9iQmX10rusqy7KUbcBrS+oAAJv5SURBVNuBZWFhkSQPRElyfalUKnBeQsoG8zzC8rOKKGOkEzLuPqKWqx4dAU5n5iSTdAiZ65LGZxi51rg3orK9ee5RkuSTqHCR6zeXIyRPhMVdqTM7j5mGVKe8N+NUOkP085b9mvtIpVKxri3svIRcd1Q8mp37tm13hYXsPyyvRIlKo5LHzeMqrU4218m+pD5ttVqB/cp683ty7bZtB7bX40A6C4mIiIiijMwrNrZtw7Ks0FclTDIS/5EjRwLjeMigg/LIu5DHvs0ZBL7zne8E/u/nypUrsG2769UWmXlkY2Oj65FkU9hsArq//vWvAIBUKoVOB1ngk8lkAADf+MY3jG/STpHXEf70pz+ZqwZSKBS64lU+1WrV3Nz30ksvIZvNdr12JWOtvPHGG/4ySeuPPPJIYHsZV0KfYaNcLsN1XTz99NP+MnTy09bWFm7cuOEvG0YeiBL3+mq1GjY2NvCzn/0ssB165KskvvSlL8GyrB3LY2tra9jc3PTzsu7kyZOwLAuu6wbG80gSn1Ek/ZrhOyzDyCdf+9rXAABf//rXzVV9zc/P46OPPsL6+nrXNXqeh6WlJZw4cSKwXAZoBoDf/e53gXXnzp0L/G9+dzui4lF/vWptbQ2u6+Lhhx/2l0F7tbLdbuPatWuBdUlduXIF7XY7tC6UsXWWlpa6XvsCgG9/+9tAJwzN8gAAHn300cD/UkZMTU0FttfjgONqERERUT8j00Fy/vx5bG1tYXJyEs1mE8VicWgN0vHxcXMRMMDN1AcffADXdbvecT969Ki/jXRwDEpuLuSm0HT16lUAwDe/+U1zFR1ym5ubWFpa6kp/Z86c8dcP4qOPPgJi5oedzANxr09uZMMG5h0G6Rg6f/480LlRzWazfufmdv3xj38EQjpshYxP9Ic//MFcdegdO3YMSikcO3YMXme8qZmZGXOzAM/zMDMzg6tXr/pxZpI0efz48a70JfH6wQcfANpU6ktLS5iamkK5XIbnechms6EdATvlL3/5C9D58cA8Z3ObQUl9Epb3p6enYVkWYIzjRERERLSXRqaDBNrgfHNzc7j55pvxwgsvmJsM5L777gNCpjr8/PPPgc4MDHE5jtP1q7/+GVYDOuzmaW1tDe12G5Zl4dixY+bqkXP77bf7f4cNgigcxzEXHVj5fL4rzemfQciNYVw7mQfiXF/S8x2UDIz6X//1X/jRj37kTxu9Xf3O/6677gJGeBpvGYT27rvvxkcffYTLly+bmwTIkxiu62J+ft5cHVCpVLrSlHzW19f97a5fv47l5WVsbW3h+PHjuO2227CyshLY125ptVpd5yqf06dPm5sn0q9TVZ7sMKdAJyIiItorI9NBUi6XYds2bNvGjRs3cPLkyUTTTPaSzWaRy+WwsbHhN3KbzSbOnj0Lx3Fw8uRJ8yuRNjc3B36FIA7pxAn7dfw3v/kNAODZZ581V+1L5gwiST5xTExM+L9whpGncWzbNlcdWPKL7zDJq2nmKwZRdjIPJLk+6eAcNnki4cUXX8Rbb72FxcXFoXZISnh/+OGH5qqAqKfIDrNGo4HbbrsNH3zwAa5du4bz589HToeuW19fh23bWFpa6tmRIU/vxHHy5El88sknKBQKAIAnn3wydMabnbbd12h6kbLx448/NlcFyOsxRERERHttZDpI5ufnYdt25CPS2/WLX/wCjuPg8uXLGBsbg+M4mJubC/xq2I/c2JjvpouVlZW+v/rKr9BRN3df/vKXzUVAp0NndXUVlmXhscceM1fvS6dPn+76xTPuJy55HSFs3INPP/0UAPC9733PXJWIdAbs9U2CbdvY3NwMjE2hi5omtB+5AV1dXQ3t+KjVav4TOsPIA1HiXp90HMiUtcP25ptvYnNzEy+88EKsm/Ok5Im2qM4gSbfDTm+yP31MmWEaRj65ePEi2u02FhcXu8YR6WViYgJvvfUWLMvCk08+2ZWGZGyrpaWl0Olkvc70v+ikd5lGd2JiAqdPn8Z7770Hy7Jw6dIl45s7R6Ypf/7550PzZaPR6LrOpKT8fO+998xVQCetWJYVeFqPiIiIaC+NRAdJo9FAu93G1tZWoCFodiKENRLj8DwP6XQaly9fxvXr16GUwtbWVuJGuAw6t7S0hGw26ze0Pc/DysoK3n77bf8GMooM/Bj1yLI8Xm9euzw6/tvf/jZwzsViEePj4xgfH0ez2USj0cDMzAzGxsaQTqeBzqs5U1NTGBsbQzab9b9r8jwP8/PzGBsb89/717+7F7+e9vPUU08BAH79618Hlnud8Qts2+55zXHIY+j6TUKj0UCxWAy92YoyaPoVTzzxBNAZR6FYLPodEc1mE/Pz86GvZcXx8MMP+wODnjt3LnCetVoNzzzzjP/aTJI8sLa2hvHxcczMzMS69rjXJ52MGxsbXa9UvP7664H/hXSq6B1pnueFbi83i3oe9TwvcA29rqfX617oPNFm2zba7XZonrp69SpSqdS2XlUKI+nXdV1zVSizDOonLJ/E1Wg04Hme32mkD9ZpdrhFhf309DT+8z//E+iUl3renJycRCqVQrvdxv333++PK4LOsdPpdKBj51e/+pX/Nzr7ltdNkvI8L1E5IR544AFYloXNzU2k02m/0wadvPXQQw/hgQceCHwnqZ/+9KdAp3PUTLfNZhOu6+LZZ59NVE8SERER7ShzWpvDSqb5cxxHFQoFlUql/Gl4ZUpBmRpXltu2HZjmUKbnhDGNrkwdmclkVKFQ8D+VSkVVq9WuqQVl6kMAanl5ObBOpts0P+aUw1HkHKOm5ZRpVGWqylar5U+3WCqVAtuWSiW1vLwcmI4zl8upVqvlT6mYy+VUPp9XrVbLP3fzekU+n1fVatX/ruxfaVM37keSHuTaW62Wv8yc1jIpPT50Eh7m8igSR+ik8ag40NO8Ob2n6kwPK+v1jz5taKvV8rcz05nkBcuyAucg04zKulQqpRzHCU3XcfOAhBFCpvyMEuf6lHEO+vnK9Znxood/Pp9X+XxeZTIZf1pgWV6v1/196NvK/mXf+vVI/nQcR+Xz+UC8SRiY8VCv17vKGEm3ZtwMEp9R5FzNOA2jX1e/6WSj8kkU/bwLhYJ/XXJMWZ7L5VQmk/HDKpfL+eEracCsByQPWZYVqAf0ct386PEpaSWTyfhhqpex/ej1kKQdKZei0kNUPOrp0/yY9UEUPa2F5UPJ+5Zl+eWl67rKcZyuKaH1MJRpfqPWm3WnPs2vfo2u6yrbtmOHLxEREY22/XlHugPq9brfSHIcx2+oyU2aNAbNRqI0qvSbMflIY11vIEZ9pGGm30jpH12lUgncyOkN6Ths21a2bZuLfWH773WjrzfohTS49Qax3FD0Iw1ZvYErNyn7VaFQ8NOPhEWcm8B+5ObBvBmR8DVvAsKYaUk++s2khHnYx4x7/Voty/I7wFSP9Bu1XL8hqVargXzUKwzD0qiZByTsHMeJfeOs+lxf1HapVErV63X/OsOOVygUAjeKrVZLVatVZdu2KhQKgfOXvKIfX25W5YZX6GWX3DRGhbfOdV2/QwSdG0fzWqP2E7W83w1mVHrWRaXFXvuOs1+d3lmgh6e+3LZtP39JfEj4mucm5xcVLvpxzTA383C1WlWO4wTKk7DtetE7b/R0aX56LRf1et3vOIJRP/YTVi8iJH9Uq9WuY5jXG5Uu4qw3l6ETX2HfMc+NiIiISDemkgzIQKE8z8OpU6f81zE+//zzwOPzn376KZaWluC6bt9XZIZhbW0NDz74IOr1+lDGOCgWizhz5kzg/Ofn51Eul/HJJ5/4j0fPzMxgYmKi77gr6XQaN27cCIxVMDU1Bcdxtv3O+0GTzWbhui6uX79urqKYarUaXnnllV1JO7VaDUePHkUqleqbzkfVzMwMbNseanwwnxARERHRbhiJMUh22g9/+EP86Ec/wuzsLGZnZ5HNZnH69Gn/s7i4OLQpPOM4duwYMpkMLl68aK4ayLvvvgvHcQKdO9evX8fc3JzfOeJ5HjY3N2PNjLGxsYFMJuP/32g04Lou7r///sB2h50MjNtvmlHq7U9/+tO2B8ql4bl8+TJWV1cHGhcjDPMJEREREe0WdpBs08rKCjY2NvB//+//NVf5Go0GvvzlL+/K0yPi1Vdfheu6gYH3BrWxseHPRgCtM0QGfAWA3//+90CMGSZkoL5/+7d/85f9+c9/BgDcc889/rJRkM/nUSqVhvKUz6hqNBr44osvtj1QLg3P9PQ0SqUSHn/8cXPVQJhPiIiIiGi3sINkm772ta8BAJ588knMzMygWCwGPtlsFmfOnMGrr75qfnVHyasuv/nNb7b1S25Yh8a1a9cAozNEXim6/fbbsbKy4j9eXywW/dluoM3yoc/Y8MUXXwCdGytzdojDan5+Ht/73vd4Y78N5XIZGxsbOzZ1d5iPP/4YAPD+++93zX5C/y2bzeInP/nJwFNDC+YTIiIiItpN7CDZpmPHjsF1XeRyObTbbZw5cwZnzpzBpUuX8OGHH+J73/se1tfX92Qaw4mJCZTLZfz5z3/ummIxrrAOjT/+8Y8AEJgmNJVKwbIs3HbbbUDnBinMu+++C9u2A0/TfP3rX4dlWZiamsJ3vvOdQ/9LcbFYxMmTJyPDiOKRV9l2y9jYGJ588kkAQLvdhm3bodPo0r9ks1n84Ac/GDiMmE+IiIiIaLdxkFbaUTMzM3j88cdx8uRJcxURERERERHRvsEOEtox5XIZn3322a7+yk9EREREREQ0CHaQEBEREREREdHI4xgkRERERERERDTy2EFCRERERERERCOPHSRERERERERENPLYQUJEREREREREI48dJEREREREREQ08thBQkREREREREQjjx0kRERERERERDTy2EFCRERERERERCOPHSRERERERERENPLYQUJEREREREREI48dJEREREREREQ08thBQkREREREREQjjx0kRERERERERDTy2EFCRERERERERCOPHSRERERERERENPLYQUJEREREREREI48dJEREREREREQ08thBQkREREREREQjjx0kRERERERERDTy2EFCREQHRqPRQDabxdjYGMbGxlAul81NiIiI6IBZWVlBrVYzF/dVq9VQLBbNxUQDYwcJEREdGGfOnMFTTz0FpRQymQyOHz8Oz/PMzQ6FRqOBqakpvzPI/MzMzGBhYeFAXH+5XMbMzIx/7tlsFo1Gw9yMiIhGjOd5SKfTuOeeezA7OxtYVywW/XpwfHw8tM6bnZ3Fvffei3Q63bWOaBDsICEiogNjfX3db0D96Ec/AgD89a9/NbY6HKanp3Ht2jX//2q1CqUUlFKo1+uwbRsXLlzAbbfdhmazGfjuIKQDY5Bf8HqZn5/H8ePH8fjjj0MpBdd1sbm5iccff9zclIiIRoh0jpw9exbT09OBdel0Gu+++y6eeOIJ5HI5AMCFCxdw6tSpwHbodJKcOHGCnSQ0FGNKKWUuJCIi2u8ajQbuvPNOVKvVrl+dDpOxsTGg00FiXufU1BRc10Uul8Pi4mJgXRLNZhO2bcOyLGxtbZmrB7awsIALFy6gVCohm812LQ+7JiIiGg3ZbBbj4+Nd9Ze8PqvXG1LnA4DrupicnPTXCdmer9/SdvAJEiIiOpDMX5tG0RNPPAEAuHr1qrkqkcnJSSilhto5UqvVcOHCBaRSqUAjFwBuvvlmAMDnn38eWE5ERKNhbW0Nq6urOHnypLkKt99+e1e9MT09jVQqBQD45z//GVgnnnrqKayurmJtbc1cRRQbO0iIiOhA4hgW/22YHRvD8sILLwAAzp49a67CF198AQD47LPPzFVERDQCnn76adi2HfpjR9gydF7JcRwncv3s7Cwsy8LTTz9triKKjR0kREQ0VPqAnDMzM/77wCsrK/5ga1NTU34HR61WQzqd9gdhi/toLMew+O+OhiNHjpirsLa25oerPrDr/Py8v02tVgus1zudms0m5ufn/XUSL/ry8fFxrKys+N8RjUYDGxsbcBwn9BWaDz74AABw7733mquIiOiQq9VqcF0Xc3Nz5qpI5XIZruvi8uXL5qqAubk5uK7LH1FoYOwgISKioSkWi/joo4+wvr6OfD6Pzc1N/PWvf8XCwgJuvvlm3LhxA/l8Hq7r4uLFiyiXy3j99dfxH//xH6jX62i324Eb+CjFYhGbm5vm4ljMToO4n3Q6be5qT3meh9XVVQDAiRMnAuvW1tbw4IMPYnJyEq1WC0opVKtVuK4beB1ndnYWlUrF/19+lfM8D5lMBo8++iharRYA4LXXXkOj0cD8/Dx++tOf+suffPLJrkFi/7//7/8DADzyyCOB5eL99983FxER0Yj43e9+BwC49dZbzVVdpN45fvw4Ll68GPn0iLjrrrsArR4iSkwRERHtgHw+rwCoVCqlKpWKv7xarSoAyrIslclkAt8BoPpVTfV6XQFQjuMoAKparZqbHCoSJvp1VqtVlUqlFACVy+UC2yul/HWtViuwPJ/Pd20v8ZFKpQLLRavV8sM7lUoF9inHMeNA4qbfh4iIRo/UHXrbIIzUT/rHrMNMy8vLCj3qNKJ++AQJERHtCHmN4hvf+AaOHTvmL9cH5nz11Vf9v+VVHMuy/GVh5NWafo/ZHjZHjx71n2b57ne/iy9/+csolUpdo//r3nzzzcD/58+f79r+448/BgB861vfCiwXMo3y5uYmFhcXMTEx4a+TJ0Fuv/12fxk62+JfPSBdn+XlZQCA4ziB7xAR0WjY2NgAANx0003mqoDZ2VkopVCpVPwBWpeWllAsFs1NfXfccQegHYMoKXaQEBHRjpDGyY9//OPA8o8++ggAcPHixcDN9rVr14DO+8NRFhYWsLm5iUKhYK7aV8zXc+J+ejX6qtWq38mwtbWFcrncNcq/kAHqnnzySSwsLPidT2Hee+89oMd4IH/6058AALlcLjCtYrPZRLvdhm3bgXis1WoA4DdmTXK8XvFMREQkjh07hvX1deRyOQDAr3/9a3MToqFhBwkREQ2dfpOs3zxDm5L2gQceCCz/4x//CAC4//77A8uFTBtr2zZOnz4dOc3ffmA+NRH3c/r0aXNXAzl27BgqlQosy8KFCxdw2223RU57KE97mE+BiHfffRcA8OijjwaWy9MjUR0dX/7yl81FgXFTfvCDH5iriYiIIv3iF7+AZVlwXddcRTQ07CAhIqKhk6cOzNc2PM/D5uYmLMsKPI0ArePknnvuCSxH53syEOlrr71mrk7ksAzS2s+xY8fwySefoFAooN1u48EHH/Q7rkSz2YTrunAcp6sjS8iTQOZsNO+88w4A4L777gssl7iXgfJ08spPKpXqO9AeERGRbmJiAkeOHOn7Ki7RdrCDhIiIhu7DDz8EQl7bkPEszKcO9I6TsBvnl19+Ga7rIpfLdd2oJ7W+vt715Eacz/r6urmrfW9iYgKnT5/2X0mSzgshT4HMzMwElguZJjHsdZmoJ4FuvvnmwP+6F198EQBw9uxZcxUREY0IqVP0McmSiHq9FAD+8Y9/ABH1FlEc7CAhIqKhk5tn87WNqKcLpOPkyJEjgeXQXq2xLAu/+MUvzNWkaTQamJqaMhfj61//urkIAPDZZ58B2vS+pj//+c9AZ6Bdned5oeOPQBsg79NPPw0sLxaLcF0X+Xx+251cRER0cEmdInVQXI1GA++//z5OnjxprvL95S9/AULqLaK42EFCRERD1Wg00G63Q1/bkPEszCdLhOd58DwPxWIRxWIRnufhu9/9LhAyqOuXvvQloDMLS7PZRDqd7jkY6UGkX4/MNtPLn//8Z7iu64cdOvHx/PPPw7IsPPzww+ZXgM5TH81mE9lsNvAajgyo+s1vflPbGvjiiy8C/6+srPi/6M3OzsK2bZTLZTSbTaDTOXLmzBnkcjmcP38+8F0iIhotMgaVPG1qGh8fx/j4OIrFol+P1Go1PPTQQ1hcXIzs1IfWOf/tb3/bXEUUjznvLxER0XaUSiUFQOVyOXOVsixLAVCtVstcpVKplAKgbNtWhUJBKaVUJpPxl4WR76RSKVWtVs3VB1q9Xle2bSsA/kfCJUqlUlGZTCbwPcuyVC6XU/V63dw8cAzHcVSlUgmsl3Wu6waWK6VULpfz918oFAJxWq/X/biTfZdKpcD3iYhodNm2HVm35/N5v70gdUg+nw+ti0y99ksUx5hSSpmdJkREREREREQ7YW1tDQ8++CDq9XrPJ0KSaDQauPPOO1GpVHDs2DFzNVEs7CAhIiIiIiKiXSWvZpbLZXPVQObn57G1tTW0/dFo4hgkREREREREtKteffVVuK6LtbU1c1VijUYD169fx6uvvmquIkqEHSRERERERES0qyYmJrC+vo7f/OY3/rTyg2g0Gjhz5gzW19e7BocnSoqv2BAREREREdGeWVlZwR133JF4GvharYaPP/6459S/REmwg4SIiIiIiIiIRh5fsSEiIiIiIiKikccOEiIiIiIiIiIaeewgISIiIiIiIqKRxw4SIiIiIiIiIhp57CAhIiIiIiIiopHHDhIiIiIiIiIiGnnsICEiIiIiIiKikccOEiIiIiIiIiIaeewgISIiIiIiIqKRxw4SIiIiIiIiIhp57CAhIiIiIiIiopHHDhIiIiIiIiIiGnnsICEiIiIiIiKikccOEiIiIiIiIiIaeewgISIiIiIiIqKRxw4SIiIiIiIiIhp57CAhIiIiIiIiopHHDhIiIiIiIiIiGnnsINknPM/DysoKpqamUCwWzdX7xtraGtLpNNLptLlqZDWbTSwsLGB8fNxclVivfaXTaYyPj6NWq5mrfLVaDdlsFmNjYxgbG8P8/Dw8z4u9fj9oNpuYmprC1NTUvju3vXRQyoj9rFwuY2ZmBmNjYxgfHx84HGu1Gubn5zE2Nmauom0ol8tIp9MDx8uwrays9CxvD5Narbbj4e55HorFIqampjA2NoapqSmsra2Zm+2qZrO57+tEOlj0unpUyo8went2N8PB8zyUy+XItlKctnQ/e3VttHvYQQJgZmZmTyvEZrOJK1eu4LnnnoPruubqfaNYLOL555/HxsaGuWpklctlZDIZXLhwAe1221ydyHb3tba2hhMnTuDChQtotVpwHAdLS0t+Z1a/9bR/NZtNvPnmm/u+jNjPFhYW8M4772B9fR31eh0AcObMGSwsLJib9lQul/HKK69gaWnJXLWrpJMmrAHYz27cDCfRbDYxPz+P+fn5fVG/eJ6HdDqNe+65B7Ozs+bqA0m/aQszOzuLe++9F+l0esfaQ1LX3LhxA6VSCa7r4sEHH9yzTpK1tTU4joPx8XG0Wi24rotyuYyXX37Z3HTPNBqNvp25a2trfsfv1NQUVlZWzE12nOd5GB8f9zua5JPNZs1NgQTn7HmefyM6NjaGmZmZfX1DWqvVcOrUKTz55JPbrqvlJlzCKayt5nke5ufn/fDJZrNoNpvmZkDn3PQfCBYWFnYsr9dqNVy5cmXg9uygPM/DlStXMD8/v+3wj7JX10a7TI24arWqAKjl5WVz1Y7KZDLmIpXP5xUAVSgUzFX7hoRXKpUyV400AGpY2WnQfVmWpfL5vP9/q9VSjuP4cdVv/V4IywcUrVAo7PsyYj+q1+sKgKpUKoFllmX1Dcvl5WVVrVYDy1qt1sD5dLuq1apfVwyaFmzbHuh7O20/pG8pF804P6harZZaXl5WjuPESrOlUkk5jqNarZa5aluWl5cVgMB+S6WSArAnYS3536yDcrmcsiwrsGwvSbxF5QkJV2nDVqtVZVmWyuVy5qY7SvKu+QmL2yTnnMlkVC6XU67rKqWUqlQqyrKs0P3uJ6lUKvL645DwtG1bLS8vq3q9bm6iWq2Wsm1bOY6jXNdVrVbLT7/m9pLepQ50XVflcrmhtf/q9XpoGpX0O2g4DGo36pJBri2sPUH7U++acgRIIWbbtrlqx5RKpdBCaTcy9HZV2UESShoDwzDIviReotJOv/V7ISofULSDUEbsRxJugzRMbNsO/d4g+XSY4nSo27atAKhSqeTffMh5y0duPPaD/ZC+5YbssEnSqZfJZLo6DrZL2lr7gdxYWpbV1REkadC8wdwL+XxeWZYVmSekXjfTq1yD3iGstO3lUyqVAusHJeFphmWYJOdcr9dD2+alUmno6XPYttNBksvl/DDqFaZyDL0Mb7VayrIs5ThOYNtMJhMa37ZtDyWt53K50DS6nXDYjt2oSwa5tqj2BO0/I/2KTaPRwPvvvw8A/qOVO83zPJw9e9ZcTLQtf/rTn8xFAf3W7zbmA9pN7777rrkolpWVlR17THe7/u3f/s1cFFAsFvHCCy9AKYU//OEP/mPXSinYto1CoQClFCYnJ82vjqy1tTWsrq7i5MmT5qoDb2JiArZtm4tDPfXUU1hdXR3qqy/74dUpceXKFbiui2effRYTExOBdV988QUA4J///Gdg+W5bW1vD1atX8eyzz5qrfC+88AIAdKXXhx9+GADw9NNP+8tqtRqOHj2Kzg+jKJVKOH78+FDavVeuXMETTzzRFZZhkpzzP//5z9BXwr761a/i73//u7n4UJifn8fS0hJyuRwWFxcjw7RWq2FjYwOZTCZQhk9MTCCbzWJzczMQt3//+9/x1a9+1f9fTE1NbTutNxqNPX/l9CDYz+0J6jbSHSQrKyvI5XLI5XIAgNdee83cZOjOnTvHDEIjj/mA9rtGo4HnnnvOXLxvhDV2TcePHwcALC4uYn193VxNhqeffhq2bWN6etpcdSiE3WyGmZ2dhWVZgZvVw8LzPFy6dAmWZeGxxx4zV+ODDz4AAHzpS18yV+0az/Pw9NNPY3V11VzlazabfqeTmV4nJydh2zZc10Wj0QA6HROFQsHfJpvNIpfLbfuHimaziTNnzuDMmTPIZrM9O1ySnvOXvvQl3LhxI7AdAHz++ef48pe/bC4+8FZWVrC0tIRUKoXFxUVzdcDrr78OALjrrrvMVbjvvvsAAO+8846/7Mtf/jI+//xzbat/uXHjxrbSuud5ePzxx83FZNjv7QnqNrIdJM1mE0tLS3jsscfw6KOPAp1fOPoN/qQPLDU+Po5sNouZmRlzs1DpdNrvZd3Y2PAHsQo7pj7wkgymFEYGt5MBmgYdFV5mp5FzmpmZ6VnRIWTwrKjBocxR6+fn50MH7opzLWtra4HZIxYWFvzBq/TzDwtbfb052JU+u8VYn5Hs9evpN3haP3H3FTVidrFYxNjYGM6cOQN0Bp3Ur73f+mazGZgZpdFoYGpqCuPj437YSzzLeY514loaMSYzLGdmZgLx2C8fyOCTYxEzhMRNq2Za0Qcom5mZiTz/MI1Gw0+b6OxbT9NmOhU1Y9agdDodetyVlZWeYdaLxLH+EY1Go+v42Ww2tMyJEufc4qQj2a5fHo9DrkvfT7FY7Mqzkk6kUX706NGuMAqztraG+++/3x+ATb5nlhtCrxd6pS0zb/QqZ7br9OnTAOAfKyyPJBE3zBuNRqCsKpfLGB8fx9TUVKB+CEubH374YWBfujh5yczzev3QT61Wg+u6mJubM1f5Go0GVlZWkM1m/UElpSwwy2aZRWF8fDy0Xtzv5ubmAjergzLzmx5/ukHL9SRxjM7TDu12G9lsNvTXeXmq2LyB300//OEP8cILL/R8ukvO03EccxWgdYb9+c9/Bjo3wqZbb7112z9U/PKXv/T/Xl1dxfHjxzEVMXtL0nOenp6G4ziYn5/385DE/1NPPRX4bi/NzkxFUnaNj4+Hlr1m2orbZtDL/7EBy3XP8/wb6DidVlevXgUAfP3rXzdX+Z3nsg0APPfcc5ifn/frW6mLp6amBk7rzWYTd999NzY3NwGjfRlGL/OnpqZC8zdilvWDimpLC/PY5ieqnOl1bUnbE7RPmO/cjIpCoRB4h1EG2zHfi9TJu5Py/pjruiqTyagkwdhrDA95Zy6fz6tUKqXy+XzgHVTz/UEZdEkGunJd178Oc9teZFAnffAmebfODA/9/B3H8Qf5ROedVsuyAu9DFgoFZdu2v6xarYYODBrnWiqVih/e6LxbqIdPvV73392EMRicyOfzKpPJBNblcjl/kCulDSAWNlCdhJWkAbkeOWYScfdVrVb9tIGI9x37vW8Ztr7VaqlCoeCHXy6X8wftkv9V5z1LfdAvSQNh729LWMo5SrzCeLc4Kh/IWAlmGIi4adVMKzLeSaFQ8LcPe7c5TKVSCQyKKYPESbjoy3WlUqkrfi3LCoSl0uJG0rnruv7YEWZch8Wj6rzXmkqlAucg7yLLthLfYfuNEufc4qajOHk8DhnYcXl5WbVaLdVqtfz4CcuzasB3hVWf70m8x01bScqZOCQPmWkhjBlndsJBWuOGeb1eD+QVqcP0sVBkO6szKKPsT9Ja2DXFyUtmni8Y9UO/sVb6jemyvLzsX4fsr1KpqGq1qiqVigLgtylkUEW5Jknzvch+436izrMXSZ9xyLnntYG9t0POO8yg5XrSOFZaXjDLa6UN5uwY4zeY9LQa9xNXoVAIXLMcy4xvWW7WoULCT74ndYSu0GmfbVer1VLVzuDRverEpOesOvvW96u3L+KQelAvp8LOw0xbcct1vWxUxn0BIuqOMLIf27ZVqTPGiuwjk8l0jRPSa/9SN8BId1WtjWl1Bu0fpO4xRaVRpcXpcmegaEnfcn5mno1T1scRdk7VPm1pKcf1eknCKyzuk15br/YE7T/xS+1DRApMPZFK4RSWqEWhUOiqOGVfcUnBFVZBSMY1G8xybnqlqSIaubJ/K+TmNYwUCOYNSqsz6Ja5Tt+/Hn76jbB+nqlOR4+uWq12XX+Sa5F40htTesEp5x0Wj/oNitIKYzOswipqiR+zcIuqjHoZZF+9CtewykDXa72e7kS1WlWtVstvMJrxFXYukk7N85Mbj7B0ZO5XhIVB0rTa0gYlNL8j2yepcGVfeqMiqgJ1XTc0LCSs9euWfBO2nRlfYctzuVxXHlNaGIelbfO8ogxybmHpSCXM41Fc11VWj9kOEFJOqoj0Gkev70l6iEpbg5YzcUnYRX23UCgEzs3WBoeTuKhWq6HXphskzOW6JF22OjdQ8rfV6WA0hYVHkrykYtQPUeTY5k2dybZtPyxlv3odXalU/OVS9sXpINkNco1xSAeeGb6DkngxJS3X1TbiWOqzfp+w8nQ31Ov1rvZfv/I2Kn4krqXTTtKovh+5GR+mVqvlH9ss85Ke8zBIOjbDT+Jal7TNEFUGSxmHkHIripSlepy0OrPSSFjqdYqcZ9j+5bzM890pUWlUaXFq1hFyXXo4Jy3re4lzTuZxJI71NCvnFLZ9kmtTPY5L+9NIvmLz5ptvYnx8HLOzs/6yBx54AJZlAZ1HMKOYAx/JgEjD9MgjjwQe/ZTH5fTHdNfW1uC6rj+wlZBrarfbuHbtWmBdmOeffx7oXL9uYmICP/vZz4CIx/2OHDkSCL/p6Wn89re/BYCuwZqWlpYCj8fNzs4GHh0d9FqOHTsGdN5d1R8RfOKJJwDj0U90Hp2zbTtw7Jdeein0UdtvfetbAIA33njDX3bp0iXYth24bmjnmcQw9zUsjzzyiP/37OwsJiYm8KUvfQmWZeEb3/hGYNswZ8+eheM4Xddw/vx5KKW2nU+SplU9Ts1jy6O8gwxOdv78eX/fExMT/nviruv6j2xeuXIlNH7vvfdeoPNqkTyCa9t25CPHvXieh3Q6jfvuuw/nz583V/vOnTsX+P/EiROB/3sZ5NzC0tGgedwkj8d/5zvfMVf5jycvLS3t6isNUWnrb3/7m78sSTkzTH/4wx/8R4OfeOIJP7zn5uZw5swZvPDCC11p1LSdMP/2t78NdPKJHOfNN99Eu90OTYcSHrokeUkXVT9EkdewbrrpJnOVr9ls+q/hfP755/5+//CHPwCdevCmm27yl0vZcM8992h7ORjuuOMOYBcGV01aruuSxrG8upHJZND5gTDwyWQyAIAf/OAHxjd3nozlcPny5a5yYjvktdBsNotSqRR4DeKFF17oKr+2a2JiAuvr63AcB+12G2+++aa5SV9yzsPwta99DYh4FcWUtM3wyiuvANoAs2JiYgJHjhwJLOtHXof52c9+5h97YmICi4uLSKVSaLfbyOfzxrf62874IsMkQxmIW2+9FQDw2Wef+csGLeuHodFo+K+b6elgcnKybxsozrXRwTOSHSQvvviiP5K2mJiY8AdrXVpaCs2EDz/8MCzLwvHjx5FOp/13+foNprQT/vKXvwCdGxjzHTlzmyie5/nvDoZVyNKoc103tPFrksYKOoUNOoPetdtt3HnnnZifn/eX62E2jGvRPfbYY7Asq6vR/vrrr3e9t7q5uYmlpaWu48qYHRI+tVoN7XbbryS3Y5j72mmTk5PY2tryb8DX1taQzWa7Gs2e58F13dB0NAzDTqvDpFegMlvQBx98ANd1u9LV0aNH/e/99a9/BQBcv34d169fB7SxTi5duuRvF+bDDz/EbbfdhsnJya6GnJidnYXjOFhaWvLfifU8D9lstqsBEmWQcwszrDwujciwm9jp6Wm/k1vedd8v4pYzw3T69GksLi76N38yJgk65a9SKtbArcMO87fffhuIOcgsEualnfb73/8eAGBZViDflctlWJaFm2++2c9b0uB2HCfWzbt5ff0+UeNVHSS7Xa6/9957AIDvfe975io0m02srq7GGqQ3bNynfp9+Tp06hZ/85Cd9j52U3Kyhc9OvdwhF1R3D8L//9/8GtLZgEvo5b9exY8eglMKxY8fgeZ4/DtQwSAdor7Fi4pLxKaRjUieDJfcatDfKMM5tt+xlWd+rIymsbKLDb+Q6SMrlMlzXxfHjx7sy4YULF4BOQRXW6z05OYlPPvkE+XweGxsbePDBByMHo9otrVar61eQsAZxmH4FjV5R67+G9iI3itLLfuzYMbiui1QqhaWlJdx5551Ip9OhjZ3tXItO7+ySeGw2m7h+/XrojWE+n+86nv7BkKfJHea+dosMwPlf//Vf+NGPfoRUKhVY3y8tbVe//Q+SVocprAJ1HKcrLekfPS3KYHBnzpzBfffd56ffKPIL29LSUuRAZ+h0cCwvL2NrawvHjx/Hbbfd5g8uGVfSc+tlu3m8X0eC/Gq3H3+5iVPO7EfDDnOzczWOJHlpJ12+fBnQnoxBp9O43W7Dtu3AUxDytELcGR7Ma+r3iZNf9rvdLtflF+KwX/elrWD+eBbm9OnTXfHR79NLo9HwBzg126XmAOsysOPNN99s7CVc3O2GbbYzE9LW1pa/LO65xN0uLq8z0Pzdd9+Njz76yM/H27Gb7f67777bXOR3TPcSZ5v9Zq/KeplFCSFxe+PGDViWtWPHpv1p5DpIXnrppZ4NVbnxe/HFF82vAp0bofPnz8N1XeRyObiui6NHj3ZlqN0S57H0KF/5ylf8v/v18sctGKQBom8/OTmJ9fV1VKtVpFIpbGxswHGcrqd0tnMtJpm+79KlS/A8D1euXMFPfvITczPAGOmbgjzPw8zMDF588UW89dZbWFxcDDwpJCQt7dQjkDuRVneC/hjv5uZmrLCYn5/H0aNH8fOf/xzr6+vIZrN9G4i33nqr/2vo8ePHe4bJyZMn8cknn/hTPD755JOxf30e5Nx62W4elwbMxx9/bK4KkEdy95ODWs7shzCPm5d2UrPZxObmJlKpVKCM+eMf/wiEvBorN2HmqyP033a7XN/c3IRlWaG/qstrrzv5VEUvqVQq9CP5z7ZtpFIp/3VXebom6sktWb6Xr3eNj4/j/vvv9//fi3NuNBq47bbb8MEHH+DatWs4f/780J/SGQa59wibijfsBxiZbSusXJZlvWbk2q/2sqx/6623YFkWnnnmGf9H3GKxCNd1/SEEaHSMVAdJrTON349//GNzlU/edXVd13+FRuhTGk5OTmJxcRGlUgnQ3kXcLbfccgvQeX83rDBpNBo9f1mG0WMqv3bppIAwnxaI4nke2u22/x4vOlPwidnZWayvryOXywWe0hnGtZgmJyf947z88su4evVqaMPHtu2ucWV0cv76O5BhT78kMcx97bQ333wTm5ubeOGFF3o2KiYnJ/1fK8KevkIn/wxq2Gl12CTdyi890gA3x/8QKysraDabaDQaWFpaQi6XC+146mV6etovf+6///6uG4xareaXYRMTEzh9+jTee+89WJYV6zWZ7ZybaVh5XBp80jlkkl96br/9dnPVnopbzuxHww5zyaOvv/66uSpU3Ly0Xb1uUKDdvJljp8hj79IpD60zxXGc0Jvxg+Af//gHsMNl6m6X67Zthz49UiwW0W638atf/cpctSump6exvr4e+pEx1Z544gmsr6/7r7tOd6bAbbfbXWV/s9lEu92O/XrXTmg2m9ja2gp0EO7FOV+8eBHtdhuLi4uhHQ2D0jvsosr1JL7//e8D2nhGOqkz9bb1j370IyCiXJawlW0Oit0q66NMT0/j4sWLQOdJlrGxMbzxxhuoVCrbbgPRwTNSHSQvvPACcrlcz0JytvPePrTBw3TmAK5hN91JeJ7XVVHEIYPKbm5uBsZDQeeR34ceeijWL1fyOOlzzz3XdeMiDcKoAdJMEjYycB867xSaT9eYAxoN61pMcpwLFy4EBo7USePj+PHjKBaLfuHb7MwRL7+Wz87O+g25XgNlmWEYZpj72mlS+eqPz3ueFzg3+fvZZ58FOvGvx7nneZifn/dvksPEyQfDTKvbYVbQjUYDm5ubgbJF0t7S0hKy2ax/bZ7nYWVlBW+//TYmJyf9mwJzn59++mngf/N6RTabRaFQQLvdxuOPP961ndngn56eDr1BCLPdc9MNK4//9Kc/BTo3pWa50uwMoPnss8/2LOO3wzxmXHHLmSSibuSHbdhhLh0M5uDdui+++ML/O25e2i75ZT7qVaF33nkHMJ4IaXTGGTHbFTJWyeOPP94VZnvpxo0b5qJIMiaQPkD32toaxsfHMTMzEyvfx7Gb5frc3FzX0wvNZhOXLl0aSkfwbpNxPszX1uRHip///OeB5f2k02mMjY3FvuGXPGjWEei0bS5evNiVN4d9zv3Ik3v6K1rm+ZrpLi553fTs2bOR+5COxn4efvhh2LbdNXYetLDRx9A7duwYUqkUrl692tUeK5fLcBxnoPScNA2EaTQakeHRy26V9VHK5TLee+89XL9+HVtbW1BK4fr16wOFYxz7qW6gEOa0NodRq9Xyp3zqN+93q9UKzD8u82ErY9ooc1ncaZv0aeby+bxKpVKq1ZlvO2qKM5mmzJzmS6bHC/uY00v1IlNS6VPgVjtzj5vT3enT+erhsLy8rCzL6jpuKpUKLJfwNad/i3st+nb9pmNU2rRaveJcpmk1P+Z0e/q1p1IpValUVKVS6Zqv3gyDMEn3pU8bZ04Z2dKmmjXPud96Pd1JWtRJ2kMnvUqalf2lUil/ijP9OHIsiX9zGrSofKD6TFGXJK3KtIbmflra9JHmd3rRr0s/tuM4XeGqtCk+zY9lWf756OGQyWRUoTOVuD7lXy6XU67rBuLKLCPkehzH8fct4ZjJZALni4ip70yDnltYOlIJ8ng/Eq+WNtW467p+PJj0vGamw37kWh3HUfl83g83/Vripi09b+ifsLQTh35ug3w/iSRhLtMCh4WB0KeuLHSmGy4UCn7YyXJJt3HykhqgftBJejfzltKm/zTXSfloHkvyQqlU6iqv94qen+PkN4kjiW+lXRcS5iW9LA47dpJyfRhxLPlY0nCSa9ltvaYrVZ2w0/OlhHXSa5K6QT56WzOK/p18Pq+q1aoqlUrKcZzI81VDPOc4pJyUMiWXy/ltUDmmnGvSNoPe5pHpeavVqn996KTpXmGhk7pKzwelzhTxYfuQ7XOd+xTXdf02l9l2imOQNKCMe5RCoeCXk3pdYJaDEi9meyFuWd9Lr7ZSq0db2rIs/xrks7y8rKrVaqAcVANeW1R7gvankegg0St1+ZiJXYUUDvpHdSoqKXxkueM4ofvqRQoA27ZVvV6PPG6v5aJer/uZbtDzUZ1CWG/AZzKZyMaH67oqn88HGrNyo2TKZDJd4Z/Rbth0/a7F3A9izIteqVRiVbpm4zwf0ZFmnqNUTPJ3krCPuy9pIIVdd9g6+fRbHyd9KS296uEijVSzAmh1OiMlj9i2HVkJmPlARcSx+f04aTVsP6lUKjI84pBtl5eXY6UV1Ul/5rmaaV8aQPp6qXzjlBFh15RKpVS103kj54pOWJuVeS/bPTeTmebNPB5XtVrt2k/YdYWlA8QoN0S9Xu9qGIftMyptmceJW870EnYchOSTYYsT5lHnFkYPC9u2VaVS8ZctLy93hUu/vBQVL0nYtq1s2zYX+zdO5s29nI8p07kBM7ffK2a49IoXERYWEg5Op/M7DvOY8jHT63bK9SQqlYqf7hzH2TdxFEXylBleOr1OchynK9zikJt927aVpXVe9JPP5wP1fVRb0DSMc45Dv1nW6z9pfwxSrkPLO61WK9AhkkqlVL1eV6lUSqVSqcTpK6yO7BU2ruv620tb3Cw74xo0DehhnOq0CaPCLaq9oOtX1vdj7luOG3ZOevmR63TURn1s21au64buR45hLoN2bWHtCdq/xtS/EhMREfUw1pmqkUUm0eG0traGBx98EPV6fajjIBw0jUYDd955Z+S797VaDa+88sq2HsOn/SudTqNQKIx0Hhh1o5gGyuUyPvvsM3+cQHPGyV//+teYm5vD4uJiYDkdTuwgISKKgR0kRIefjCs2yjf/8/Pz2NraigyDYrGIW265ZdtjsNH+43ke0uk0rl+/bq6iETGKaaBWq+GZZ57pec21Wg2vv/46O0hGxEgN0kpEREQU5dVXXw2dxW5UNBoNXL9+Ha+++qq5Cuis/+KLL9g5cki9/PLL/hTVNJpGMQ1897vfRbvd7jm47Ouvv941yQQdXnyChIioj1qthqNHjwIAqtVqYIo/IjpcPM/DqVOn8Nxzz43UI+aNRgNnzpzBf/zHf4TOSiSPoJ8+fdpcRQdcs9nElStX8IMf/GCk0jz9t1FOAzMzM9jc3IRlWchms7j11lv9dV988QWuXr2Kn/zkJ+wYHiHsICEi6iGdTndNSZhKpbC+vh5YRkSHy8rKCu64446R6BCt1Wr4+OOPcfLkSXMVEdGhVy6X8dprrwXae47jYG5uDo899tiOTjFM+w87SIiIiIiIiIho5HEMEiIiIiIiIiIaeewgISIiIiIiIqKRxw4SIiIiIiIiIhp57CAhIiIiIiIiopHHDhIiIiIiIiIiGnnsICEiIiIiIiKikccOEiIiIiIiIiIaeewgISIiIiIiIqKRxw4SIiIiIiIiIhp57CAhIiIiIiIiopHHDhIiIiIiIiIiGnnsICEiIiIiIiKikccOEiIiIiIiIiIaeewgISIiIiIiIqKRxw4SIiIiIiIiIhp57CAhIiIiIiIiopHHDhIiIiIiIiIiGnnsICEiIiIiIiKikccOEiIiIiIiIiIaeSPfQeJ5HlZWVjA1NYVarRZYVywWMTY2hpWVlcByXbPZxPz8PMbHxzE2NoZ0Oo1GoxF7/X7QbDYxNTWFqakpeJ5nrh5ZzWYTCwsLGB8f70obRMPQq/zZS41GA/Pz8xgbGzNXHQqe5yGdTmN8fBxra2vmaqKh2a95nAiAXw7uZtpcW1tDOp1GOp02Vx0qva4zzv3FXimXy0in0ygWi+aqSPv5euLyPA/lchlTU1Oxr73ZbKJYLO56HqKdN9IdJLVaDadOncKTTz4J13XN1X01m004joNHH30UW1tbyOVy2NjYwP33349ms9l3Pe1fjUYDV65cwYULF9But83VRNu23fJnp5TLZVy8eBFLS0vmqkPj5ZdfxuLiIn7729/iN7/5jbl6z0gj0/xEdarrN99J7XQHWK1Ww/z8PKampjA2NhbZ4JSO6Gw2a64K8Dwv8GPD1NTUvm+MDzOPxwnPYrHorx8fH8f8/Hzkjx6NRgPZbNZPY0luCogGtbKygueffx4bGxvmqkPlIF6n/KA7Pz+/7847nU531Yv9Pkk6LJrNJq5cuYL5+fnYZbXcJ5w5c4b3CYeRIpVKpRQAVa1WzVU9ZTIZ5ThOYFkul1OWZalWq9V3/V7IZDLmIuph0LRBh89O5Z1B09hOnY8AoPZ7FbG8vJw43JRSKp/P+3+nUqnAur3SarWUZVl+uMsn7PxarZZaXl5WjuMMFE+VSmWg78UhdZ+ce6lUUq7rmpsp13VVoVDwrznsOoWETS6XU4VCwd8/ALW8vGxuvu8MmsdVgvB0HEc5juMfo1qtKsuylOM4Xe2NarWqACjbtlUqlVK2bfvhudPlCu2NQcvKnSDpr1eePwx2+jp3Kq8WCgUFQBUKBXPVnpHz0csyOU8zfEulkrIsa6D0Psi1b6d8p/1rpJ8g2a7V1VVMTEwEli0uLmJrawsTExN91++2ZrOJ1dVVczER9VEul/H3v//dXLxn9tv57JUXX3zRXBTL+fPnzUV77sqVK3j22WehlAp81tfXzU0xMTGBkydPhq7rp9ls4umnnzYXD4W8urS6uorl5WWsr68jm81icnLS3BSTk5M4ffo0fvvb35qrurz88st47733sLi4iNOnT6NcLmN5eRnYRho4COKGZ7FYxObmJlZXVzE7OwsAmJ2dxeLiIjY3N/HDH/4wsP0zzzyDUqmEGzduYH19HTdu3PDDc3V1FeVyObA9HXyHOZ+MolFrz6dSKZw+fTrWvVM2m8Wzzz5rLiZKhB0kA+r36Fa/9Xshn8+bi4ioD8/zcPbsWXPxntlv57NXVlZWYj8Ku995nodf//rXeOyxx8xVPU1MTMC2bXNxT5lMBr/61a/MxdsmN/Obm5solUo4efKkuUmo//W//pe5qMsPfvADTE9PB5bJ/re2tgLLD4sk4Xnp0iXYtt3VcZLNZmHbNjY2NvzXtBqNBh5//PGuV5pOnjyJXC4HAHjttdcC6+hgO0xlJf3LqLXnv/Wtb5mLerr33nvNRUSJsINkRJTL5ZHqbSYalnPnzu2rxuV+O5+90Gg08Nxzz5mLB2LeVO4FidO7774bCwsLicaoSjL+SLFYxNzcHI4dO2au2rZTp05hc3MThUKh6+a7lzjhb3aOoNOBAMC/qT9s4oZnrVZDu92OTAdzc3MA4I8pMD09HdnZ8uijj5qL6IAbZllJ+8MotudPnz5tLuppdnbWf5qOaBAj10GytraGmZkZfxCfqEHM9MHv9IHLarUaxsbGcPToUaDT6JB9FYvFvutllGQZ2Vp+JZL1YmVlJXCeMzMzkbMt1Gq1noOtFYtFHD9+3P9fPx/5fq8B+2QwN31wPLkWczt91pdms+mf19TUVKLHdtfW1pDNZv3Rv2WU6LE+MwGVy+VY8ZskfE3mYFH6COV6+hofH0c2m8XMzEzg+714noeFhQV/oL2xsTFks9mu611bWwvE2cLCQte5IEF49GLOxNRr8D8ZtV0P17B4N9Nco9Hwvzc1NeXHhWcMzGgeV/LTzMyMnyZlv+b2kjflo+cRM0715TJYqZ6X9SfEzPDRz98Ut/yJEud8JAzMwRqT3HSbpCwc68Rp1BNyZlnUK6+GiZP+19bWcP/99/uDoh09etQ/VlK1Wg233nqruXhXNZtNP05d18WFCxdg2zYWFhYSpY1+arUa3njjDfz4xz82V21brVbD6uoqLMtK/BTMoM6dOwfHcRJfT5w0hpAytlar+Xl3Zmama3ux3TyOAcMz6hiSvt99911zVaRvfOMb5qJQzWYz0E6SsB0fH8f4+DgWFhYC23sh7Sq9btfDSg/HXmVqEmachtWbnuehaAx2q9cVwhzkNp1OI5vN+mVjkrpJF/f4CKl7zLq5X1kpAyRLmw0h9aQZPub6QetCk3nMMaM9qi+PCo844uZ/DKE9FyUsH4h+6apfex4J4yHseB9++KG5WU9R1yN5IK3N5KO3JbLZbGge2Am1Wi3QzjPPNYx+DyPlWdLz3W6biPaQOSjJYVYqlQKDurmuGxjsTQbYkcHjZOCysMF6+g2+FLVeH1gvlUqpXC6ncrmcQmfANKUNElQqlZTqnI+cizkIkAxGJNu2Wi1///pAhCpi0MVSqeQf31wn6yXMWq2WarVaKp/PKwCBwd/q9bq/XLZ3HEcVCoXA/sMGlzMtLy8HBqXL5/P+YHKyH8uyuvaVy+WU4zj+8uXl5a7zVAnDN2zwJdd1FQCVy+VUvV73l0uc6+lIriOuVCqlLMvy9yv71Af2rVQqgXRbKBRUPp/3BzuU648bHr3U63VlWVZgcCyJz6gBiCuVilKd65fwy+Vy/nZmmiuVSn5a0a+rXq/7eUS/PknXrusG8lOhUPAHKpRlYecpxzDzddTAlVF5WWnho5cpcmxJXyJu+dNPnPPJ5XKBeLcsK5Cu4pDz0vOfxAEAP56FOTBatTNIZJLjxkn/+rZJws3UarWUbdtd6aAXvQyK8wmLoyj1el2VSqXAMcy0G0a270WuVY8HOcYwSH7OZDKBPClp0Yw7U5KwqlQq/jXHTVe6OGnMLGMlXgqFgn9sqa91w8rjScJTzh9AaDhHDWQYRs4/znm2Wi1V0AbZzefzKtWpr/XyWq9n9XaVbJ/rDLwr2+dyuUCdIOFthdT5SZhxGlZvSvtJwrjVavlxoddhrc6gwVJ2SFhI2A1aN8U9vkpYN4eVldVq1T/nsHV6vJparVbXd5LUhZJm9TSpHzNq8FEJm+2Ik//15XKNg7Tnwq7TzAd6/dMvXekk3kxJ4kFvL0h609OEfm5Rel1P1P2Ovv124lPOtV/ZJvEgx2ppA1+b1yj7zHXas6lUqmeeVRH5Sw2pTUR7pzt3HVKSQczMIAVSWOKWjGJ+R0UUfLpe6/UCWSr8er3u/y3nows7F7dzo26en9zomQWPZPAwYetc1/ULT5MULuY6KUjM5VJxS6Hdjx5G+nekQDePIQWRXsEpreDSwyhu+KqQgq/VaqlUZyYBU6HTCNJJ+oqjXq8rhKQZ8xyExJneISGFbpLw6EVujHWSLvQbBElzZri0OjdmYevk/M3lco6pVCrQIJY0Yd6YSNzZth0II2nsm8eIimsVkQ965eWwG2w97Ur4D1L+ROl1Po7jdIWP0jrHwtZFkbDQ819L64DV9yVlkXkNEtZh52pKmv6jlsclHbpmnOwHkn/jnJ+EQy+ZTKYrn0n8DoOcayqV8uNDb5ib5aIpLN7DSHrSP+Z19ZIkjclNYNgxpEzTG7nDzONJwzPs5kRI3Rt106lLpVKxttOF/WCitPLX3J/Eobm9Xm6a7QSJHzMeBiFxGlZv5nK5rrQRFn9yrmH1qx7HSeumuMdXCepmFZG++62TczTbcqpT35vL49aF+nLz/KUdYaZvpeVHM8yTSJL////27ve1keveH/jbf0Cyd+w+Kr2laBy4pQWHdrwtvd7ABpJxN+XSkgRpc6EEEnYjpQTSNOusnCWE7m5Wzo9CyPWPUEMJl0hLNuTypXbtLTQQqaHJaoNFWnohO6KkuX2kWTXNH3C+D6rPcOZoRpqRJdtrvV8gkp0Zaeb8PnM8c85u+3OqRzhVTD8kab5SPervpOkgYYm6NokP83d6iQqP0tLUMgYFpM+QJj5NSfsXcr+ix2Fc2uj1k97/jCuzKib/DKNPRPtrbF6xee211wAADzzwQGj71NQUjh49Gtq2V44ePRq8fz0zMxP8v23bcBzHOLrbSy+9BABdj+CeOHECSiksLy+Htqe1vr6OdruNH/zgB+au4J3WlZWV0KP7MsO0+S6zPOb7+eefh7b3c/To0dD70jMzM0G45LF0AHj55ZeRy+W6ZriWiZ3eeuutYFvS+DXJayC93gmv1+uhV0qmpqZijzXddtttsCwr8ePNQuYTyGQywbv6aeIjTqVSged5XSteZDIZ3Lx5Ezdu3Ai2PffccwCAe+65Rzvyn+F/+umnASB2YlEzfuQa77777tD8BPI+adz8G6dOnQq9c5rL5UY66eDm5iY8z+uqU+Qa2u02PvjgA2CP6p/NzU3U63Vks1lzF06fPg3LsuB5XuQrT73o5W9qaipYOcXzvOCx3/X1ddi23fXOr0yUtr293ffR1EHz/yBqtRouXrwI13XNXQdCLpcLVne5dOmSuTuVtbW14PHwUWg0GsEj/KVSKcgDmUwGW1tbsCwL9Xoda2trxjfTO3PmDFqtFsrlcjA57cmTJ0OP+feSJo/pdacZd9Od+T6++OKLYNuwyvgg8SmT7i4sLATlu9lsYmlpKfj3t771reD4KLVaDR9++CH+67/+y9zV05EjRwAADz74YCjOvvKVrwBA7Gpb5vF6vWnOkSJtwqeffhravhtmu+n7PlZWVvDwww+HjtPT7ze/+U1o37lz50L/Nr8rkrRNac6fpm0e1D333APLsrr6eOjkNz2N0rSFvZw4cQKu66Jer3eV6fX1deTz+a4+TRppyj922Z/bjaT5ypQmHa5cuYJ2ux3522knRO3l9ttvBzp9eX0uKenbSV03SrZtw7IsfPnLXzZ3xXrwwQdD/c9cLhdMjJukPzmMPhHtr7EZIJEJjZJMCLffrl27hmvXrgGdzlKhUIjsJMsxu2kwerl69SqgVXC6mZkZWJYFAPjwww/N3SOl34RLI1qv17GyshK85yefhYWFYL9IGr+6N998E3feeSeeeuqpyAkD0ekYW5aFkydPYn5+PnjnM+lAlXRuZAnSzc48LDK5Xhpp4iPOxx9/DMSkv873/eD3ovLid7/7XaBzQ212tEZNBvcGicN+/vjHPwKdxteMZ/OYvah/fv/73wPaDYtJJmt87733zF2pTE1NBQMLf/rTnwAA169fh+d5XfEgczEBwJ///Ofg/6MMM//34vs+Hn74YViWFTtoF0d/hznJZ5B5UYTcLLTb7YHLTaPRwC9/+Uv8/Oc/N3cNjT5IYNaNU1NTwY3gO++8E9o3KLlJ+eCDD4KB7jfffNM8LNIo89iwyvgg8XnixAlUq1U4joOTJ09icnISL730Er75zW8GNyC9BgOlTPy///f/IuvwcSD108mTJ7vKseSP69evA50bTsdxsLKygunO/Gq+7yOXy3XdEMUx26Y050/aNu/G1NRUsFSq/DEOnYE3GHkzTVvYj9TJ58+fD21//fXXuwbO0kpT/nfbnxvEbvNVmnSQ+kMGMg+zCxcu4ObNm8hkMsHAcdTAUD/f//73gYT3PMPoE9H+GosBEnMk+lZQ60wIt7CwgLvuuitypv4kN7m70e/35a8aw/yrThJxHbhisYjOa2ORH12S+NXJYFChUIidYCmTyeCTTz5BsVjE9vY27rvvPkxPT6fOfzKJ1a9//Wv8+Mc/7tmx7SVNfESRzlg//Sp5vSP1t7/9LbRv1EbZgRStVqsrbuVz5syZ1Ok/qH7pJX9BHvRmWyd/gdOfCHMcpyv8+idJBw9DzP9xXnnlFXiehxdeeAHoMaAUZWtrqytcvT7ytM2gfvSjHwHGTXMaL7zwAur1Or70pS91ddSE/HtU+fTf//3fzU1DMTU1hV/84hfAAHl62HlsVHEXJS4+5+bmcO3aNSilcPPmTSwvLwc3Q67rdg226B5//HGcP38+cRk9zDY2NrrKcVR5vnbtGlZXV3Hz5k2cPHkSd9xxR6qnpOLapiTn71fXD4s8nSw36ugMlphProh+bWESc3NzcF0X29vbwdMblUoFlmX1zMNpJCn/w+rPpbXbfIWE6RA1KHSYyYSr9957L44cOdI1AJfE17/+dSDFUy/D6hPR/hiLAZJbTaFQwLFjx/D8889ja2sLuVwushMvjxjHzU69W/L78lfiOPu53rhUWNCeeOknafzqvv/972N1dRXtdhv3339/7KNxU1NTuHDhAjzPQz6fh+d5OHbsWKJG1fd9zM7O4sUXX8Tbb7+N5eXlXS3HmTQ+4shfQs3Hik36Y4txg0divxqEQV6pSirJo8N7QdKr3wz0w3h8Vl5z0st+vV6PLRdJDDv/R9FfrZG/Rn7jG98wDzswjhw5sqsbA9u24bpu5EfIv2+77bbQd5PSy3TUQEXcjeAwyLn/5V/+xdwVaS/y2G4NKz6bzWbwZGSpVDJ3BwqFAn74wx/uyasDtwJ5Ei+J06dP45NPPgni97HHHuu7MobJbJuSnD9p27xb8sRSu93G+vo6fN/H1atXY8vMsNpCeYpE/vurX/0KTz31lHFUemnL/276c7ux23w1rHQ4LCqVCmzbhm3buHHjBk6fPj3QkzOfffYZ0OdpPN1u+0S0v8ZigETvcKR9/36vNRoNrKysIJ/P96y4oTWsb7zxhrkL6CwHthvySP67775r7gIA3LhxA5ZlhQYp9oJUOI7jBE+T2Lbd9b6oTpYbTBO/ptOnTweN5HxniWadLOWHTgdmeXkZ5XIZ0N5P7+XKlSuo1+s4f/78wDdEIml89CLXcPny5a6wonOzWavVkMlkgsG0P/zhD+ZhQSc/aaMyTP/4xz8ALS8P01e/+lWgM/9KVPw0Gg1UKpU9q3/uuusuoMfA2F/+8hdgSAOanufBsqwgbNJhN9+dFmtra5E3e7ph5v8ofuc1Aoz4Melheu+99/o+3dbLhQsXsLW1FfkR8u/dxLnMexP16LGUQXkaZhR++MMfmpsijSqPDbuM7zY+fd9HNptFu93G6upqbFgLhQJmZmY4OKIN9K+srEQO9Pud5XfRafvkD1NTU1M4c+YM3n33XViW1fd1XWG2TWnOn7RtHoaf/exnQGcupFdeeSXyL+9J28Kk5CkSz/OwuLiIDz/8cCh5NE35321/bhC7zVdp0kH6Y0lfT7yVFQoF2LYdvFo1qP/7v/8D+tS9Yhh9ItpfYzFAAiDoZD777LORFQe0Bms/yQ2mWXDk5kb4vo+f/OQnQKeRNB/BW1tb6/qOqV8DKg3j5cuXu45tNpvwPA/PPPNM7CsvwxA12diVK1cAIPQXhVOnTgGd93eXlpaC+Gt21oOXJ0TSxG+U5eVluJ1JxKIqvvX19dC/0zTqMhClv7Lk+37oWuKuy5Q0PnqRd3A9z8O5c+dC567VanjyySeDGwPpNJ09e7brGqWTn3a+h7TMNIQ2eKhPZCwDBL/73e+CbeiUmSR830ej0QgmsavX66F3lNF5quv+++8P5ssZZf0j15PL5WDbNtrtduTg6NWrV+G67q6f4qnVaqjX68ErKtAmZV5ZWUEulws6+L7vY21tDe+8807fuRl2m//NOsokr9aUSqXQtcgTcsO8qUijVqtF3jw0Gg1cvXoVP/3pT81dIVF15G5sbm5icnISs7OzPeNbJ5N2R5XxN954A5ZldU0cKMy6OI21tTU4jtM1OXSc3eaxXoZZxncTn77vY35+HvV6HaVSKXbehkKhABiTMItGoxFZhxwkzWYT09PTmJycjBxQSCuTycDtzPlz/Pjx0Gsljc4E7frgskyMK2ZmZmIn403SNqU5f5q2OUqaek6/rpWVlciylqYtTEry/sWLF4O5UExLS0uYmJgI8nI/acv/bvpzg0qTr3S1Wi1VOsgfC+IG5DDAogoHUaMz6fXNmzdDaStPg4i4Olv36quvwrbt2LpXN4w+Ee0zc1mbw8pcnrJcLqtqtRqsdS3LOulLVMnSTeYydUpbOs9cuirJflkWz9KW+RWyDJmcV5Yak2WqbNtW+Xw++J6cR/a5rqts2+5aQk9pSwdms1mVzWaD5adkuSsYyxYqbWkrS1vLW5YbNJdAk2WtELGcr1y/67pd1xVFv6Z8Z412pS1/aS4xp7Qlhs2PHhdp4leWzDPDo4czm80Gv60vc2ZuM5f6iiJLsQJQxWJRFYtF5WprsLuddeSVtnQatOUKTUniox99aTNZEs5xnMh8LXlRXx6t2ln3vVgsho7Vr1//nZa2Pr0et8rIE3p8ShxDS6dWqxVsN5dkk+Xt5BylUkm5rtuVNyRe9e2SJnJdejjMj37eQeqfOL2uZ0dbBluPCzmPWd/0IkuHZrPZvumptHrN/ETllShp8r/S6hTHcVSxWOwZd5J3zDqrWq0Gy+2Z+W2vSDvjOE6QL4rFonIcp2+86XnBzOf9yPdMcj2IWeIzjr4saKvVCpXBXvWfnu5R+VPCKOVG0mh1dVXZtt03jnRp8phe95l1lJQNvRwMs4yrAeJzZ2dHlUolZVmWsiwrtl1QWl3tum7XR8KQJF71MJv9JIlrvd5ptVpB/jKPj6vfWzFtgl7vm8vaxunXbuptvvnRy4Jcq1k3wljmNG3blPT8KmXbHFdXtrS20Oyz6SRsUfW+SNoWKq2tsG27Z50reSWqXlBaHRZ1jihpyr+kUWnA/pzqE86ocpA0X6ke/fk06SD1gGVZqlQqqWq1qkqlUlC/yfa4+NdFhUdp5zDjQG+7ospiP57nha7TzPM6s/6VdJbzF4vF4BqkXFmWFcRXq9OHimpv4u4T1BD6RLS/untHh5hkcsnMbuemSDoGUhj0hlr/9NqHTqXZb7+5DREVX7kzCACtopRCGFVAy+VyqKKQDpVJflcv+FKp9bqearUaNLDoVDJmRaB3BPRPXJj7NTDyPWnQJT5s2+46t86s3IvFYldcJInfuPCoHnEmFa/8tlx/v7DqpELVr10aPLdzIxx1fjdmTfUk8dFPtXMTKefKZrNdeVCUy+WgsyHHmo1f3PX3yitR35F8KmmVz+e78mlc3G9sbATxIvWA6jSk+Xy+K3x6R8fct7Ozk+i8SeufJHpdj+d5ofPYtj1QurdaLbW6utqVnlFhExsbG13HJ+lciST5X+zs7ARpWOzRcW9pN7RmXCktP6aJ/2Ha2dkJxVnSvCDHm5+k4o6XDqLjOLH1Spyo9I+Kc9WjLTXP2dJukPVjVldXU+dplTCPRdU3ruv2bBfUkMu4ShGfaeIlrtOufxxjIDFKXPrFbddvSMzj4+I77reUNhgs8dNP3DlMZhpG9Tmq1apyHCeoV+KOG6RtSnJ+YcZdXP6Iqiuj8nJUfAhH+8NHnCRtYVQ6mH1Osbq62nXDrZN4sm079jdMScq/6sSPu4v+XFw4e+XppPlKxfTnRZJ0EHof0bZttbGxEWzrV5eoHvWAimmjJF7N7b3yninq+/p5TXr+1+PC6QwomvFXNQa2JX+ZcdEr7CKqDu9XjuhgmFD/zMREB0qtVsOxY8fguu6uV4Kgw21paQkLCwsolUqJZ8onot5qtRpee+21yNd/iA6SyclJ3Lx509y879g27c7s7Cx+8Ytf9HxdCJ14PnLkSOTrYkREgxibOUiIiIgomffffz/x5KdE+6VWq+3J3BC0t2q1Gtrtdt/BEXTmE0s7xwkRUS8cICEiIqJAo9HA559/zhtPOtB838ebb76Jn//85+YuusXI5JWNRgO+7+PJJ5+MXDHHVKlU8PDDD3PCSyIaKg6Q0IH0/vvvA50VGnazygEdbr7v46OPPgIAfPTRR4lmIieieJVKBdvb27teEpFolGq1Gl555RX8/Oc/H+lKeoNi25TO+vo6HnvsMdx555340pe+hKmpqb4DtIuLi7j99tv7HkdElBbnIKEDZ2JiwtzEd3ipi8xTY6pWq4keyyUiIho2tk3pNRoNHD9+HOgsmf3Tn/70QA58EdF44AAJEREREREREY09vmJDRERERERERGOPAyRERERERERENPY4QEJEREREREREY48DJEREREREREQ09jhAQkRERERERERjjwMkRERERERERDT2OEBCRERERERERGOPAyRERERERERENPY4QEJEREREREREY48DJEREREREREQ09jhAQkRERERERERjjwMkRERERERERDT2OEBCRERERERERGOPAyRERERERERENPY4QEJEREREREREY48DJEREREREREQ09jhAQkRERERERERjjwMkRERERERERDT2OEAyJubn5zE5OYlarWbuol1YWlrCxMQE1tbWzF17olaroVAoYGJiwty1b+Sa5ufnQ9ubzSamp6cxPT0N3/dD+3SVSgWzs7OYmJjA5OQklpaWUu0/CPY7Xxx2UfVZs9nE0tJS1/a9srm5icnJSeRyOXMXdWxubmJ+fr6rbojTbDaxuLiIyclJc1es/c4Ho5K0/tRVKhXMz88fyDpyGAYJX9o8uFf0vH5Q8u0g5e8wGqTsUbdByutu+L6PpaUlTE9PY2JiAtPT09jc3DQPS+Qglk8arbEcIPF9H2tra5ienjZ3jUyz2TxwDTLd2iqVCl577TWsrKyYu/bN4uIiHn744YGvaXFxEf/zP/+Dra0t7OzsAAAWFhawuLiYaD+Np1qthvX1dSwsLKDdbpu76QBYW1vDc889h+3tbXNXpEqlgmw2i4sXLyZOU+aDf2o2mygUCigUConj+1YyaPiWlpZS5cG9Ivk2TV4ftUHKH1GUQcvrbsk9140bN1Aul+F5Hu67777UgyQHsXzSHlBjpNVqqdXVVeU4jgKg9jL4pVJJAVA7OzvmLqJEdnZ2VKlUCm1rtVp7npf7qVarCoByXdfc1dPOzo4CoDY2NkLbLMtSpVKp7/79EJUmlNzq6qqqVqvm5oG5rqsADPU3TUzzwQ1SNwxSv+1FPrgVSL/jsObXQcI3SB4ctrg6RPqmBynfDlL+aG9ls1lz04E0SHkd1OrqqgKgWq1WsK1cLicuX1FxehDLJ43OWD1BMjU1hdOnT2Nra8vcNVK+7+PSpUtA569oRIOIyjtTU1PmpluW/GXh9ttvD7bNzMzg5s2bOHPmTN/9+yEqTSi5F1980dx04DHNiWg34uqQw9Se095oNpu4fPmyuXnsvfPOO4BRpnK5HJRSmJub047sVqlU8Pe//93czPI5ZsZqgERMTU3Btm1z88hcuXIl+P+VlRU0m83QfqJ+Go3GwK+t3Cp+97vfmZtC+u3fa+OQJqO0trYGz/PMzQca05yIdoN1CA1TsVg0N5H2B7e0fN/Hs88+a26mMTSWAyQA9nT+kRdffBH//d//HQzK6AMmRP34vo9HH33U3Ez7iGmyO41GA2fPnjU3H2hMcyLaDdYhNEyVSoVPjwzZuXPnbrk/3NBojO0AyV6pVCoAgBMnTuDUqVMAgEuXLvWcCXtzczO0MkmtVgtW7ZidnUWj0TC/0lPc7MvNZjOYrHZpaQm+7wfHTU5Oxk58KRMuTU5OBiuJFAqFUJjMMCwuLmJiYqJrolp9RZKJiYmu3xFra2uh42ZnZyMnWtrc3AytcJLL5TA7O2se1jW79SCroeiT/erf9X0/mK1bwivHTUxMIJfLRYYxSrPZxHe+8x3U63WgMyGpxEEUPfy98krSeO/H9/1QXpiensZvfvMb8zCgx4o78/PzmJiYCEb8jx07Fgpjv/2NRiOUvyuVCiYnJzE9PR08rdVsNpHL5XrmWWHmDUkzict+aRKXL3RLS0uh+M/lcl0zow8zH+mSlF/RaDRC8abXFeZxehpIfMt3pB5EJ48eP348mOxM0nN+fr4rzL7vB+kvcRlXn5n0enN6ejr0WPtSZ5Uh+ei/o2+XeO+X5tBm6DfrOHGY0lzSxIyDWq0W2h6X/+Pstk6O0isf6Mw4mt7Fige96lczjiaMdtHcL3kkrv4Ukm76b3700UfmYYFardZ1vNlemO24Hpdp2pe49jpNnKcNXxK+1ueZ6JQv/QlfM59PGHWFvj+u3IskdYhOD69Zh+qSpGNSacqf2U72Ot68xqi20cxru+kzSrrGteG6JH3GuLKXpt3TmfFhfswwR1laWsLJkyeDf8t3l5aWuvr2jUYD09PTmJycDJWvJOVv0DAOu7xudlafkt+bnZ2NPLfsN/+dJE7n5+eDp7u2t7eD75rtNPapfNIeMyclGRcyiduoua6rVldXlTIm1CyXy+ahSimlNjY2VDabDR3nuq4qlUrBNdu2bX4tVrVaDSZG0icXarVaqlQqKcuyFABVLBaV67qqWCyqYrEYbDevU58UUyY/yufzCoByHEepiDCUSqXQb3qeF3zPcZzg3zKpkuM4oYmV5PrlWjzPU7Zth8KjtMnXZJvnecF16FqtlnIcR+XzedVqtVSr1QrCkM/nQ8fG8TxPlUql4Dr0Saf0iYBd11X5fF7l8/nQ8UnPI3pNbiXxnDSvJI33fiQe9d8ql8tBOuuT4JXL5SCOzfQQ/SZWjNq/s7OjisVi8LuSfyWey+WyarVayrKsUPgkPs2J+iRM2Ww2FCYAyrKsYJuKSZNe+UIZcSYTNler1dD1ilHkoyTlV0i4V1dXg3Iica3HpZkGct2lUimU5nrcqZj0jAszOnk5rj4zf1PqG9d1g7iS7aLVakXWI0qpIDxm/ohKc9ku5za/cxjTXGmTKiOifpW4MONJ6mgzjlTnmizLCtKiWq0GcWGeo580+UBpcSRtted5wbnNNrCfJPVrtVoNtb2mVqevIHHRr/6U689rbZpeTsx0kHpaj2vLspRlWUEeNdvxtO2L/LZcG2Im2E4S52nD14ueB6VcSnhg1PP6Ndm2Hcr/olgsdpWNXuLqEKXl26R1aJJ0TCpN+ZM6TU8PuU6zfpJrlDSV70LL+2ZeK+2yz+i6bigOJM0tywodJ9slzFF9xriyN2i7t7GxEcSTxJ2ex9Iyr0vKhsRdvtOGSN6S9ElS/gYN4zDLq9LyptQfnud1hcdkxktSev1g2s/ySXsvfe45JCSjj5IUBr1ClsLUqyJs9RhIkU5e2sIl4ZWCKuI6v9JRNmdytm27q+LwPE9ZltUVJgmDXqnJdUvFYXYq5Dr1ClQqel1UJ6NUKinH6PC3OjfHOmksdHJcVBz1EnUdSmsEzYrQ87xgexpx51HGAIlO8opeaaeJ936kE2L+llyrGceqT6MVl0dFr/2yTzpcrVYrOE46UWbYoq5FGmIzTI7jdKVlrzSJ2yflzWxId7SbTX3fsPNR0vIr26I6H9KBNPdJ58rcLnWedMREXHpKB8XSblR2dnZC8RL3XdkuHTMR14mJ+524TlJcuqoe3znMaS7Xb4qLp7g4kuPj0iHqHL2kzQe2bcdea1R9ECdN/SptrBmnqpMHorZHxYW0XWacqpjzSj4y4zqq3k7bF5Ewmb8tZUD/jaRxnjZ8/ejn0K9TburMNJFyAWNFDOE4Tmjgp5+4sqGMfKuTfKvHX5p07Cdt+csn7EPJNZph1QcJdHKu3fQZpV41r0+O08NYSthnVDFlTw3Q7km50cMh8WReXxJx1yVpqoevWq0G501a/lTKMA67vEpeMeuflvYHDnOf6hEv/Ugc9Lr+uHgYVfmk/cFXbEbotddeQy6XC818/NBDDwEAPM/repRNmLMu66Y7c6d88cUXoe2DOnLkCADgwQcfDJ33K1/5CgCEZnKuVCrwPA9PPPFEsA0AMpkMbt68iRs3boS2ixMnTgCd42ZmZgAAL7/8clfcAMDdd98NAHjrrbeCbbZtw3Ec7ah49Xo99Kjb1NRUKA5938fKygoefvjhYJscd/ToUQCIfUUkDVlp5ejRo0GY0YkDACNZSz0ur/ztb38LtqWJ914ajQa2t7cjf+t73/te6N976fvf/z7QSU+Zqfxf//VfAQDf/OY3Q8eams0mVlZWkM/nu8J07do13Lx5M5SWafm+j4sXL8JxnCAfiJmZGWSzWQDASy+9FGwfZj5KU37X19fRbrfxgx/8IHQsgGDuEHPCaYkzqePE1772NQDA559/Htrez9GjR4NwzszMdMVZLw899FAoDZeXl4M6ZC/ngDrsaT4sly5dgm3bXasLmP9OK0k+2NzchOd5eOCBB4LjoJ273W7jgw8+CO2Lk6Z+veeee2BZVmScvvrqqzh9+nRoW5wrV66g3W53tWnQzqtbX1+PjGupt7e3t4NXFtL2RZ599lk4jtP12xcuXIBSKviNNHGeNnxJHT16NHSdMzMz+O///m+gk89FJpPBM888A3TiTler1dBut4M+zrDE1aGffvppsC1NOvaTpvyl6UNJvfbII4+Ejj1x4gSUUlheXg5tF7vpM952222wLAvf/va3Q8fF6ddn7CdNu9doNIL5LfRwZDKZxH3ctB588MHg/+fm5jA1NZWq/CFlGIddXp977jmgU1/qpqam8PTTTwOdemcvxcXDqMon7Q8OkIxIs7P01s9+9rPQ9rm5uaAifPXVV0P7DrqPP/4YMJZZHVS9XsfKykrwXp58FhYWgv3i2rVruHbtGtBpYAqFQrBssu6BBx6AZVk4efIk5ufngwEovRH+85//DAA4efJk17lljovr168Hxx82aeK9F4kraRgOMumMnThxIpjjwXzHGAD+93//F9AGDYdNOhxmB08cP34cAHD16lVz11CkKb9yDVHHzszMwLIsAMCHH35o7j6wpKO4m/eg02Ka9yc3mXLDPWpmPvjjH/8IdAbizXpRyDH9pKlfp6amghtvfYBMBkuSDsbKcpbyR41+rl+/Ds/zuq7x2LFjwTHSTqbh+z48z4vN67o0cZ42fLuhD3To8wQ88sgjsCyra/64N998M7hJ22vDSse05S9NH0r6bUnyRD9Jy5YM/l64cAHoDMblcrnIVU2S9BmH6bbbbjM3BYYRR0mlKX9pDbO8+r4fpGtU/Hz3u98FOn9wNgeZ99uwyiftHw6QjIh0eKIqICnw29vbt9RkPcMeOCgWi+i85hX50cnkcAsLC7jrrruQz+dD+9FpGD/55BMUi0Vsb2/jvvvuw/T0dOQESxsbG13nk8/W1pZ5+KGSJt7jHLQld/uRSdu+853v4OOPP8Yvf/lL85CBOwRJ9fv9b3zjG0CnsR+FNOW330CZ/KVQ/4vJQSdPEOlPxY0a07y/999/39w0UnH5oNVqddWF8jlz5kzo2F7S1K/yl/VKpRLceL/00ktdT/z0EnXj14/jOF3XpX/Mv3omMUhnP0mcDxK+3ZA/YOlPxshgVrvdxrlz5wDtiUPzr/B7aRjpOGj5S9KH6lenpJWmbMkkpb/+9a/x4x//GK7rhvYjZZ9xGDKZTLCapXmOGzduwLKsRGk2LEnKX1rDLK/96hR9EFl/UvqgGEb5pP3DAZIRkEcQ4xqQVqsV/DUubkb9g0ge8R7GKyhI8VfTQqGAY8eO4fnnn8fW1hZyuVzsX/mnpqZw4cIFeJ6HfD4Pz/Nw7Nixrsbo97//fejf4yRpvB8WjUYDd9xxB65fv44PPvgAFy5ciPzr7Fe/+lUgxWtGacnv9/sLfFRHbhjSlF/pxP3pT38yd4Xs5+tUaf31r38FBnzMd1BM84MnLh8kfY2mnzT169TUFPL5PNrtNtbX1+H7Pq5evTr0VzZM9Xp96I93f/nLXwZSPjo+rDgfJhmsNG9e5CkSeSXqypUrka9j7qVRpGNSSfpQUqfEvU6eVpKy5fs+Zmdn8eKLL+Ltt9/G8vJyz/KUtM84LG+//TYsy8KTTz4ZPPWwtLQEz/OCV7z2ykEsfzqpU2A80RXFLK8HwX6WT9o9DpCMwPr6OlzXja2U9UdrV1ZWbpkCJDeVly9fjrzmWq2WuFGxbRt1491PnSwx3Gg0gnkh4uJT6EtRZjIZLC8vo1wuA535YKBVuCsrK5EVrt9Zuu6wShrv/cjNxeuvv27uOnBeeOEFtNttLC8v9+zMfv3rXwc6jVpc3tjNgKb8Bb7dbkf+/meffQZE3LgNS5rye++99wIA3n33XeOof5K/dkmc3QrkyYdRDUZEYZr3p7+TvRePSZv5QAaxnnvuucg4ajQasfWlaZD6VV7DvXTpEl555RWcP3/ePKQnCcebb75p7ookg2byJIRpbW1toHTIZDLBH37i5vmRtjVNnKcN3274vo92ux3MDaQzX4m6dOlS4nliRmFY6Zi2/KXpQ8nTOG+88YZx1D+l6WslLVtXrlxBvV7H+fPnI/8QokvSZxy2mZkZvPDCC0AnfiYmJvDWW29hY2Ojbx93WNKUv7SGWV71J27+8Ic/mLuD/LqXbXpSwyqftH/GdoAkbkJR3draWuobIt/3cenSpb6PyOqTVr3yyiuhfQeVvK/peR7OnTsXqlhrtRqefPLJxKO4p06dAjrvscq67dDWZZcnRKRSNCuSv/zlL6F/y7WYk6iZk21lMhm4rot2u43jx4+HHm1uNBqYn5+/Jf5C2mg0Ihu2fpLGez/yWLHnebFlZJDrGwX5q5P+CKaZn3zfx8zMTNDQPvroo6Fjms0m5ufnuyYK0/VLk0wmE7waJu9N69577z1YltU1od2wpCm/ctN2+fLlrkHPZrMJz/PwzDPP9BxwSss8zzD5naf6stlsqNMsAxP6Y+a+7yfu3I17mkt50Y9vNBqpXsGbm5sLOsHFYtHcHegVz0lF5QOZLLVer4fmIUDnL9/3339/z3KvG6R+1duklZWVxOcSMhli3A0rjEkUZYLBlZUV5HK54Dt+ZwD4nXfeCTr3ackAwtmzZ0N5wvd9FAqF4MYsTZynDd9uSP9BJiU26U+RmJMoD6pfHRJnWOmYtvyl6UP95Cc/ATp1itlPWFtb6+rH9ZK0bMkAr/4qoO/7oTjW/79fn3HYKpUK3n333WDid6UUrl27NrTBEbPujpKm/KU17PIqA8Znz57tKifyZOYoJ2n1fT82HL0Mq3zSPjKXtRkH+vKKUctDKWN5M3OZpjietoZ63O8Kz/OCJapgLJMlS+XBWEJPX9ZKljNNQl9+zVyOS5bvMpfzlaVRLW2pTWVcmyzlFbUEqizNBW3JNpOc2/zoSw7raZXNZoNl2SSebdtW+XxeeZ4XWj5Pvh+1fJ2+bJ/5MZfv6keW/TLjT5b9sm07tFyaHp64eImip0epVArOp8dz0rySJN6T0PNCPp9X1WpVlcvl0O8Xi8Ug7vUypV+r6rHEYpL9enqaYVXaEqUSd/l8XmWz2dDv6UsE6nnDdd0gjc0yHZcmqke+0MtcXluCVH7LzBPDzkdJy69+rKUth+l5nnIcp2tpRH2ZQnNZQ4l/13VDYZDtjuOoYrEYpIEsCWrWPSKuPlNafDmO03XN5vmVkSeLxaIqFosqm82GylWxWAzipleaS11jptVhTXOlhVkvW5KW+nYJh6RtVNgkTV3XVRsbG2pjYyPII+iUJbMMxkmbD/T0Nj9JzykGqV8lH0bVX6JX/SnhlfiuVquqVCoFbYBsl/Ik6WB+zDyRti+i53UJs9tZDt6st9PEedrw9aLnNT1vrq6uKsuyus5tkrzd77g4cXWI3o6Z9VpcHZo0HftJW/7S9KEk7dAp967rKtu2u8rDsPqMEr/Q6nSp89AJn1yjpKWeD2Sb1BuqR9kbpN2zLCtIe/msrq6qarUaOmdSkg7ZbFZls1lV7SzlK30Q8/wiafkbJIzDLK/KqM/lO9VqVVmWFVln6vVW2nKqt7OSd1qt1r6WT9ofYzdAYmZU+ZikA2B25HoxfzPqd5VWAZsfV7sZM7fHfaefqO+5rhuq8PVP3PaStm55tVoNXWc2mw0V9rgwRDErzWKx2BXf5XI51Ah4nhdUVrZtB+culUrK7XTG5Lx6B1nXarVUPp8PjrVtu6vS6yUunlRMPpBrM7fHxYspqsGL+724NNclifckNjY2go6H3hjKb0pjFnWtkqei9unX3Gt/VFhhlAs9rvR0lsbLbGA9zwt16hzHieywRaVJr3yhf8+M/3w+39Vgmr+BIeQjlaD86qrVaqiT7DhOVzmJS4O4uJDyuLOz03WTZR4Lo+6JOpcZ9nK53HXNvTpJpVIpqAdkAKNarSrbtlXJ6MRFpbmKuW693jlsaS6kHpUwSVqVOgPZ5XI5iKOoMOhpu7OzEzqvpIX8f1Q93kvafGCeP67tSMJM6yT1q975N/WLO2Wc07ZttbGxEWxbXV3tOr9ed0NrW0XUOZPUuZLX9bbVvFaRJs7Thq8Xz/NUsVjsKo9x8a+TwYRBRdUhcXEaV4fq+qVjUmZa9Ct/UvaT9KHK5XJXXOvpFZfXoiQpW9K26/tlQECvt6VulTAgIg9GXVupM7BhbkePNJPf1PsWUR/btlOln/SPrc7gXr/z68w0N8M+aBjlu8Mqr6oTTjOfR/XLzGuST1wdFEXyj925v0gbD7phlU/aexPqnxmKiIiIiIhiLC4u4siRIwOv8kHjrVKp4NNPPw1eQzJXEXr99ddx7733jmypYSJKhgMkREREREQ9+L6PO+64A/V6nfMHUGoy79O1a9fMXYFarYY333yTAyRE+2xsJ2klIiIiIopTqVSCSSzPnTuHXC7HwREayH/8x3+g3W53TTaqe/PNN4MJPolo//AJEiIiIiIiTa1Ww7Fjx4J/W5aFTz75ZKird9H4mJ2dRb1eh2VZyOVy+NrXvhbs+/zzz3H16lU89dRTI19Jh4j64wAJEREREZHG933Mz8+jXq8jm83i4sWLfHqEdqVSqeBXv/oVtre3g22O4+Dee+/FI488wvxFdEBwgISIiIiIiIiIxh7nICEiIiIiIiKisccBEiIiIiIiIiIaexwgISIiIiIiIqKxxwESIiIiIiIiIhp7HCAhIiIiIiIiorHHARIiIiIiIiIiGnscICEiIiIiIiKisccBEiIiIiIiIiIaexwgISIiIiIiIqKxxwESIiIiIiIiIhp7HCAhIiIiIiIiorHHARIiIiIiIiIiGnscICEiIiIiIiKisccBEiIiIiIiIiIaexwgISIiIiIiIqKxxwESIiIiIiIiIhp7HCAhIiIiIiIiorHHARIiIiIiIiIiGnscICEiIiIiIiKisTf2AyS+72NtbQ3T09Oo1WqhfUtLS5iYmMDa2lpou67ZbKJQKGBychITExOYn59Ho9FIvJ/CfN9HpVLB9PQ0lpaWzN20B2q1GgqFAiYmJsxdtAvNZhPT09OYnp6G7/vm7rFwK5bvZrOJxcVFTE5Omrv2TbPZxNLSEiYnJ7varVG5FdLuIKYVHT6HvY1M0vc1bW5uYnJyErlcztx1S/J9H0tLS5iensbExASmp6exublpHrav9Ppur9qBg+pWaJ9wi+Qr+qexHiCp1Wp4/PHH8dhjj8HzPHN3X81mE47j4KGHHsLNmzeRz+exvb2N48ePo9ls9t1PYc1mE+vr6ygUCgOlB+1epVLBa6+9hpWVFXMX0a74vn/Lle9KpYJsNouLFy+i3W6bu/dFo9HA+vo6FhYW9uyaboW0O4hpRYfP5uYm28gxMD8/DwC4ceMGyuUyPM/Dfffdd2BuZmu1GtbX11nf3SLtkzjo+Yo0ipTrugqAqlar5q6estmschwntC2fzyvLslSr1eq7n6KVSiUFQJVKJXPXUOzs7Izst281UXHRarUUAMXqgUxR+SWtUZfvUTiI5WHQdms3hpV2q6urI7vug5hWdPiMcz7LZrPmpkNldXVVAQj108vl8p7Xt7q4ttdxnH29roNkWO3TqBzEfEXxxvoJkt26fPkypqamQtuWl5dx8+ZNTE1N9d1P+yPNY6OHXVRcMG9SnKj8QpTWiy++aG4ioltApVLB3//+d3PzofLOO+8ARl8ol8tBKYW5uTntyL0T1/ayv3brOIj5iuJxgGRA/d7367ef9kej0eCjsR2MC0qD+YWGYW1t7cA/Bk1E3Xzfx7PPPmtuPnS2t7fNTfuKbe/hcNDyFfXGARIaG77v49FHHzU3jyXGBaXB/ELD0Gg0cPbsWXMzEd0Czp07x8HNPca2l2h/jN0AyebmJmZnZzExMYGJiQkUCoXIFSV8bXUbfUbkWq2GiYkJHDt2DOiMCMpvLS0t9d2v/74+k/Hk5GTXzMuNRiM0Q3WlUsHk5CSmp6dDk7zWajXkcrngPFEr5WxuboZmXa/VakE8zM7Odh0vKpVKKL5mZ2cjJxMyV+sZ1szMzWYzCNvk5CQWFxdj06tXfDabTXznO99BvV4HACwsLITSRf5fPtBmctc/+m/q2/UnhtLERb+0k5m55+fng8mdJF9OTEwgl8tFxkcvveIiil5m0uSVuLKVVL+4mZ+fD6XBhJY+UdvQCUsulwvicqmzEkjU7+v6ha3ZbIbqi0ajgenpaUxOTgZpH7fygTkTve/7wXFmPtbz+DCv1/f94BqknOnH9ssvUk4lLicnJ7vOOSxJzrWbctOrHhmUWSdEXTM6eUTP12b7k1S/88nvSz4SZp2X5knItbW1nm3F5uYmjh8/HkwoeOzYsa7zI0He1Q0zrYbZ3sK4tunpaRQKhcgVPhqNRig/62XSPE6/Pr1tnJ6eRqVSCR2PhGUFt1D/QMr17OxsEEdy3b3yit+nf6Aft7i4GBw30akr4sJvku/IJ+occQYNGzp5TU+HXC4XWXblNyUdZmdnUSgUQtfpx/R95+fng6cY9H6tnMesb02bm5uhum12djYyzw6SF5OWtX7k2sx/m2EaNCyLi4uRvxcnSdurk7pE4iHqmpCiDksiaZkx4yJJuiKijjE/SctY0jogjaT5QPab/06aD2ifmJOSHGYyGc7q6qpSSinP81Q2mw0m25JJcjzPU6VSSdm2HTvhT7VaVQCU67rmLqX67G+1WspxHJXP51Wr1VKtVkvl83kFQOXzeaU6EzIVi8Xg2orFoioWi8E1lctlpTphsiwruPZqtaosy1KWZamdnR2llFIbGxuhcJbLZeW6riqVSsFEf7Zta1f4T/l8XjmOE/z2zs6OsixLAVAbGxvBcbJdj1eZOEquMw2ZaEkmtHVdN/g9AF0T3yaJTxE3iZNsR8wESoiYREkmM5Vwq5RxkSTtVldXg++7rqvy+bzK5/Oh/GmGMam4uFDaBHRp84rneUppk1E5jjPQhMRJ4kZ18rbkST0e5Pt6nK+urgblwHXdoDxJuAAoy7KCMIh+YWu1WqpUKoWuI5/PB7+bz+dVuVwO8iS0ardarYbynqS3lHc9HfL5vMpms6G0N8uCGuB6i8ViEB/FYjHYbubXuPzSarWUZVmhtJZjo+q/uN9JIum5Bi03+U6do+c7ve4ZhNQJpVIpuGbJC3r6VTtthlxXqzPRd1xcxU3SmvR8ki/MNPI8L8gD5m/HpZ1slzzjeV4Qz+ZvxF23SpB3zWOHlVbDbG9VJz5s2w7CIddmxrW0L6urq0HZlOvQw2xen+TvUqkUqlf0uitpWblV+gee54XKdalUUo7jBB+5fj2Pq5T9A9d1Q2kpZdKKmFhfzqeT/FEqlbrakV52GzbHcULXbOZb4bquymazQVj061UJ+r4SH2Y+1vOKuU9pZVXyhed5wfF6GgySF5OWtTSi0lYMGpZSqRRqX9PkDym3ZnoorT5NUieoFHVYUknKjBkXSdJVKRXUeVJ36HWMWXZVj3hKUwcklTQf6CT8dGsYm5SSQhtVcKTASYUh4gqb6tFQiF77852bJ13cdUiBKxaLwXGy3/O8ruNVTCeopa1MYjaa0hjqlaN03MzflgpL/w3btrviKKqSTEqu39E6ysoYrNDPnyY+e6WpxIPZoEgamHEhFaIuaVykSbuNjY3g+3oayW9YlhVsS6NXXETFs4qJI2lwzXSWeIv6/V7SxI3S8oXEjzSGeidd6Gkhja7q0fCmCZueb0W1Wg19V+LVFNewym/ath2KDz1/D5oWUTdiSotPc6WCuPwiN7Hm9riwxv1OEmnOlbbcyHWZ+U7yjPn7SdmdQTid1xmE0DuF0oHUzy/nNr+vetRLSc83yG/HpZ3kRV3csXG/nSbvjiqt5Fy7bW/dzoCjrlqtho6RNDHLvNLygrlPbpbN7dLZ1+u0NGXlVuwfmHXibvsHOzs7ChHlIS6/mvG4s7MTGqgYRNqwSXybfRYJi7kPxuCV6pzTTJ+4sivpZsZRr31SD5v5qtVqBXlL35c2LyYpa2nJ+U1pw6K039JvpNPmkbj0UD36DlIn6NeTpg5LIk2ZSZuucq3moKBeFkxx8ZS0DkhqkHygeuQrOpjG5hWb1157DQDwwAMPhLZPTU3h6NGjoW2j5Ps+VlZW8PDDD4e269fxm9/8JrQPAL7//e8DneNktuP19XXYtt01+/H3vvc9oPMYpDySac6arJuengYAfPHFF8G2Z599Fo7jdP32hQsXoJQKfmNzcxOe53XFq3yv3W7jgw8+CO1L6sEHH0Qmkwn+ncvlUCwWAQC/+tWvgF3EZ5RTp04BAK5cuRLaLr8teUisr6+HzpsmLtKk3e233w4AOHr0KGZmZoJjJW7kkfVRiMsrf/vb34JtL7/8MnK5XNds6nfffTcA4K233gpt7ydN3EDLF+12G48++igef/xxPPXUUzhx4oT27bCjR4/i9OnTwb9nZmawvLwMAKHJ0AYJ24MPPhj8/9zcXNd3e3nooYdC/5YwT09Ph+JDz9+DpsWRI0eAzvXqx3/lK18BgMQrFfzrv/4rAOCb3/ymuWvo0pwrbbm5dOlSZL4z/51GpVKB53l44oknQtszmQxu3ryJGzduBNts24ZlWfjyl78cOjaNNOcbJtu24TiOuTmVNHl3FGml2217i049oj82Pjc3F2rP1tfX0W638YMf/CDYJmSelpWVldDrPRI3Zj3xta99DQDw+eefB9vSlJVbsX9w6tSp0PlzuRzy+TwwYP/gtttug2VZ+Pa3vx06NolKpYKFhQVsbW2F6ppBJQ3bxYsX4ThOKF+h055ls1kAwEsvvRTa99xzz4XyqZk2w/bcc88BAO65557Q9qmpKTz99NNAJz/p20WSvIgEZW1Y0oZFJ/2RTCYzlDxiiqsTPv3002Bb2jqsnzRlJm26/va3vwUiVukx476fNHVAUrvJB3TrGJsBksuXLwNa53i//PnPfwYAnDx5sutdOpnh+Pr168a3ol2/fh2e53X9jsx/Au18afi+D8/zuiqmKH/84x+BTgfZvA7zmGGQjuuHH34IDDk+paPw+uuvh7b/z//8D1zXxeXLl4POqu/7uHz5cqiiTxMXo0q7/VCv17GystIVloWFhWB/GoPEzYULF+A4Dur1Ov7+9793NcBJ6I2dvFc97LCN2n5c74kTJ6CUwokTJ+Br79GPwqjOVavV0G63g47asHz88ceANljTy4ULF3Dz5k1kMhk0m00sLS11der6SXO+Ybp27RquXbsGdN6DLxQKuHTpknlYT0nz7qjSqp809dITTzyBdruNO++8E4VCIbh5k0FYALh69SoQk1YzMzOwLAvQ2rq0RlVWDnL/QAabpO1P0z+QQcQLFy4A2nxV/VaeKBQKOHnyJJaXlxPFyaDMsMnAUtw5jx8/Dmj5DACKxSLq9TruuOMOLC0todlsIpPJ4MyZM9o3h8f3/aDcRl3nd7/7XQCA53mhgcA0kpS1YdiLsIxamjosiUHLTBLyBxxTVNz3kqYOSOIw5ANKZiwGSKImq9pvGxsb6Lzi1PXZ2toyD4/lOE7X9/WPOVKcRJoKUrRara5zy2eYje/Xv/51IOKvv8OIz0wmg2w2C8/zggnkarUavvWtbwU3Kuvr60BndFv+QmNKGhejSLv9UiwWu65f/6Q1SNw8//zzQKcDOUiZj2rsMIKwjdp+XK/fmajtO9/5Dj7++GP88pe/NA8ZmlGc6/333zc3DUWajhe0STXvvfdeHDlyBOfPnzcP6Snt+YZJJt1bWFjAXXfdFfzFO40keXdUaZVE0nrpxIkT8DwPrutiZWUFd955J+bn50Md5n6DlfLXTf0vwGmNoqwc5P5B1GATUvYPZILSX//61/jxj38M13VD+00ykJXNZlP99T0tM2z9Bpa+8Y1vAJ0bNXHhwgVUq1VMTk5iYWEBtm3HTnw/DP3yiv4khf4kZBpJytow7EVY9kLSOiyNtGUmCan/Pvzww1D+lHSN63/HSVMH9HJY8gH1NxYDJAfR73//e3PTQOr1+tAbN3nEO83jdoM+JpvWZ599BgBdFfCw4vMnP/kJAOCNN94AAJw/fx6PPPII7rnnHliWhZWVFfi+j5dffhmPPPKI8e1/ShoXo0i7/aL/lWoY0saN7/t44oknUCqVAAD/8R//ker7JhmIwwjCNmp7fb2NRgN33HEHrl+/jg8++AAXLlwYySPE2ONzDYM8sZjkEd5KpQLbtmHbNm7cuIHTp08HrzslleZ8w1QoFHDs2DE8//zz2NraQi6Xi/0LYC97nXfTSlMvZTIZbG1toVqtwnVdbG9vw3Gc4Pu2bQMA/vSnPxnfDJPH39MaVVk5yP0DYb7ulaR/4Ps+Zmdn8eKLL+Ltt9/G8vJyz9c0xYULF5DNZlGv1/H444+bu4dOwvbVr34VSPCEkdlXmpubw40bN1Aul2HbNi5evIj//M//DB0zLPrrgnGrlIhBbsxFv7I2DHsVllFLU4f1M2iZSSKTyaBcLqPdbuPcuXPwfR++76NYLMKyLFy8eNH8Sk9J6oAkDks+oP7GYoBEz6RRSzDtJSlc5juTwu8sRZWEdIbPnTtn7gI6o7qDjKJnMpngryLmfBxCrlEaafO9VtFoNIYa5//3f/8HAPjRj34EDDk+0ckrtm3j8uXLqFQqyGQymJqawtTUFHK5HNrtNl555RXYtt31ulaauBhV2u0H27ZRr9dj01lfMjaJtHHj+z7m5+fx9ttv48yZM8F8JGk7fZJmjuMET5MMO2yjth/X+8ILL6Ddbo/8EXOM8Fz6O9jDLHdyQ3r58uXIOqFWqwVPOxUKBdi2HTyuPIg05xuWRqOBlZUV5PP5XXWOk+bdUaVVP2nqJb2czc3NYWtrC/l8Hu12O2hT7733XgDAu+++Gxyru3HjBizLCg3WpjGqsnKQ+wf/+Mc/AC1u0/QPrly5gnq9jvPnz6ceSPqv//ovOI6Dy5cvo1AomLuHwgyb/IW93W5Hhk3+mCRz+MDIl7lcDh988AEcx8H29nbkb+xWJpMJBgL/8Ic/mLuD8mIO4qSRpKwNw16EZdTS1GFJ7KbMJJHL5ZDNZtFsNvGlL30JX/rSl4BOnWn2v+OkqQOSOAz5gJIZiwESAMHjvs8++2xkQw2tARqlTCYD13XRbrdx/PhxVCqV4HoajQbm5+cT/8VIJmVaWVlBTlt33O+sY//OO+8krkRMzzzzDNCZLE7vUPu+j0KhEHR85MmKer2O+fn54NUUdN5HvP/++7smMtqNV199FbZtB/OF7DY+G41GV36QSZYKhQJ+9rOfBdtlUs+LFy/ixz/+cbBdpImLUabdoKLiIgmZ3PbkyZPBe83oNBSFQiH1X5LTxs25c+fw1FNPBQ20zEeyvb0d2/BFTVYpnamnnnoq2DbssI3aXl6v5Bf5q7/+OKnZyRokX0UZ1blkYBSd1zzipP3tBx54AJZlwfO84K9golar4cknn8Tc3BwajQba7TZu3rwZOkZuckS/8yc9H7Q/HJiPMG9ubkaWjzjSSTTT4S9/+Uvo33HXLu1L0rw7qrTqJ029dP369a6BKHMSRWlbLl++3HVss9mE53l45plnBh7cGFVZwQHpH5j5C9qTn/J0Z5r+gQxU6a80+Z2/Wuv/jjI1NYWtra3gKdPdDvokDZv0a2WeHt17770Hy7JCT7rKE7BiamoqNKl4Wr7vR9506uQ1wbNnz3bFnzz9spsJLZOUtWEZdViSGrSvlqYOS2I3ZSaJQqGA48ePY2trK3gdplKppBqMSVMHJHVQ8gGNmLmszWHV6iz9ic4SauVyWVWr1WAta1lOSl8eSpaqMpe7VNoSWuYSkkn2y/J+suST/tGX6tKPM5cxE7LMm/kxz6svjaVv15el0s+hxxc6ceN21js3lxOTJa+iPlFLXfUj12pZVvD9Vmfdctu2B45PpS19aFmWKpVKkWkry5GZ31WdZRb1pTJNaeIiadpJXrJtO7Qkor6Un7l0XxJxcaGHIUleUdryk+bHXEI2qTRxE7VUpIQNxtKXshQhOukr3yt3lhiNS3PzOsywtVqtoL5wXbfrepRxbnM5O8m/+rUqY9lHfblGz/OCtDCXtEt6vXKcWQb0fKGfMy6/yJKksj2fz6tsNhuEKZ/PB9eox5N53iTSnCttudnRlnp2XVdtbGyojY2N4JxyzWY57kevey3LUq7rKsdxuvKynFvaIdd1gzCgU+b0pSLj8kzS8ymtjZNzSvj07fL7cWmnx2c2m1WlUkk5jhPEm23bKp/PB3lJtjuOo4rFYij/Jsm7cs5hp9Uw21tpK/X2S/KpHg69rZOlJj3PU47jKMdY3lKWvUREmku49bonTVm5lfoHUifq8dBqtYLt5m8m7R/obUaxWFTFYjEoO+jErRwf10bq8WjWy0mkDZueDnp7JmEx+wXopJWe1+yIZcGjyrkyyrrEj5xTrtGsb5VWFzuOE9QD1WpVWZbVVdbS5sWkZS0p/fxmfKuUYdHziZkWacS1vb3agag6QaWow5JIU2bSpqvkNWmb5FPu3LuZ19qKaZ9UijogjTT5QCXIV3TwjM0AieoUoLw2IOK6rtrZ2VGu6yrXdYNMq9/I6J9e+9BZS7vf/rhrsW07VMHpDaX+ibKxsRHqrGSz2dCNjVQa+sd13b7nkIZZv8a4Rn9nZyfUOdUb4UFUjcErOXdcg9cvPvXjJD7MhkOXz+cjr79cLsfGgUgTF/3SzkwbdDpecWmaRlRcxP1uVF4xz1cqlYKGThqJuPhNol/cmNckosqgXKvsczo3Z/3yi+gVtqjzwSjvUfEqDb65HZ2wmNt6fSdNWvS6XnObnFPF5Bdzux6P0hHTOwvmb8t5k0p6LvMcEo6odNDjziy7ctMh/5/mWnXVajV07mw229XB29nZCdJMrzOczuBGkvZJJDmf6pxTj0/pxLuuq7LZbKhTb54PWtqVOwOMci7P84JOqW0MauvhjOpI9sq7umGmVVSZwoDtrercnJh5Leo41Ukrs70w66K464vLC9VqNXFZMa8TPep8HID+gVxXvjPgk+Q3Wwn7BxI3er6Tm1yp8+LiS/UpI0kMGjazzOTz+cjybtt2KO+a5SsuP+kkjvRybR6PiHCXy+WucmMOGsTFba+8mKas9WP+vnzMfL2bsAwiqu2Ni5MkaZikDktqN2UmLgyqE2b9GqM+enya+5DynmsQSfKBirk2ROQrOlgm1D8Tj4jo0KvVajh27Bhc1001czkREe2/paUlLCwsoFQqDXUFnIPgMIeNKK1CoYAf/OAHuP322/GPf/wjtHLT559/jpWVFSwvLyOXy4W+RzQMYzMHCRERERERER1cS0tLsCwLJ06cwNzcHE6cOIEzZ84EnwsXLgRzIRGNAgdIiIiIiIiIaF81Gg0sLCzA8zxzV8D3ffzud78beJJnon44QEJEY+P9998HOqvYmCs6EBHRweX7Pj766CMAwEcffdS1gsSt7DCHjSiN2267DZZl4fLly5iensbi4iKWlpaCT6FQwPz8PEql0sCrfBH1wzlIiGgsTExMmJv4rjcR0S1A5o8yVavVYMnqW9VhDhvRIHzfx/r6Ot566y3U6/Vgu+u6+NGPfoQHHniAgyM0UhwgISIiIiIiIqKxx1dsiIiIiIiIiGjscYCEiIiIiIiIiMYeB0iIiIiIiIiIaOxxgISIiIiIiIiIxh4HSIiIiIiIiIho7HGAhIiIiIiIiIjGHgdIiIiIiIiIiGjscYCEiIiIiIiIiMYeB0iIiIiIiIiIaOxxgISIiIiIiIiIxh4HSIiIiIiIiIho7HGAhIiIiIiIiIjGHgdIiIiIiIiIiGjscYCEiIiIiIiIiMYeB0iIiIiIiIiIaOxxgISIiIiIiIiIxh4HSIiIiIiIiIho7HGAhIiIiIiIiIjG3lgNkCwtLWFiYgJra2vmrpHZ3NzE5OQkcrmcuSuS7/tYW1vD9PQ0arWauftQ8X0fS0tLmJ6exsTEBKanp7G5uWkeRjRUjUYDS0tL5uax0mw2sbS0hMnJycT1TKPRQKFQwMTEhLlrT62trbGeICIiIqKRGKsBkoOuVqvh8ccfx2OPPQbP88zdh878/DwA4MaNGyiXy/A8D/fdd9+huPlpNBqYnJzseSO+ubmJ2dnZYHAobuDO930sLi5icnISExMTmJ2dTXxTu19qtRoKhUIw+BUVD41GA7lcDhMTE5icnMTi4iJ83zcPAzo3xfpAWlxc9VOpVLC2toYzZ86Yuw6MiYmJ1J80arUa1tfXsbCwgHa7be6OtLm5iRdeeAErKyvmrqFrNptYXFyMHVQ+ffo0/vrXv6JQKJi7iIiIiIh2R9GB47quAqCq1aq569BYXV1VAFSr1Qq2lcvlQxNux3EUAFUqlcxdSmnhX11dVUopVa1WlWVZKp/Pm4eqbDar8vm88jxPKaXUxsaGsiwrVTytrq6mOn5QrVZLZbNZBUC5rqvK5XJw3To9vK1WS3mepxzHUY7jhPKE6ly74zhqZ2dHKaXUzs6OchwnNm7jlMtl5bquuflAkXgpl8uh7VIn6GFutVqqVCqpQavxQeoZAAOfrx/P81SpVFKWZQX5p5d8Ph9ZXoiIiIiIBjWani7tyiA3LrcaCeNhVCwWg5u8qJv4arWqAHTd3MnN7sbGRrBtZ2dH2bYdOk51bvaz2ay5OZZt2yPPT61WKxgYkoGfKK1WS1mW1RUuiZdisRjabllW1yCL53nKsqzQtl52dnYUgK7fOWiq1WpknokaINH3DWKQemaUAyRiY2Mj0QBJq9VStm33zGtERERERGnwFRvaF9vb2+amQ2FzcxNXr17FM888Y+4KnD9/Hui8KqB74IEHAABPPPFEsO2LL77A9PS0dtQ/feUrX8Hf//53c3OktbW1kb+y5fs+5ufnUa/XUS6Xu8KmW19fR7vdxtNPPx3aPjc3B9u2cfHiRTSbzWB7u91GJpMJHZvJZBK/HgIAjz76KLLZbNfvHETf+973zE093X333eamW9q//du/mZsiTU1N4dSpUzh79mwovxARERERDYoDJERD4vs+nnjiCVy+fNncFWg2m8Hg0MzMTGhfJpOBbdvwPA+NRgMAcNttt+HGjRuh4wDgs88+w7/8y7+Ym7s0Gg2cPXvW3Dx0jz/+OOr1OkqlUuzcEeL1118HAHzjG98wd+Hee+8FAPz2t78NtlmW1XUD3Gw2YVlWaFucSqWCer2OH/7wh+auA2dubg5zc3Pm5p4O8nwqg0gziOW6LtrtNl566SVzFxERERFRamMzQKKvDqNPGOn7PiqVCubn54NJQ/UJIXO5XOTEkeYKLHKs3NgK87dN+kSdExMTKBQKkecTlUql5/GjDg86kzzK5JoTExOYn5+PPC6KOamk/hvoxIe+Usbi4mJov9jc3MT8/Hzw/dnZWVQqldAx0CYLld9rNBrB9/RVc3zfR6FQCCZCNeM1if/8z//E+fPne97gffjhhwAAx3HMXQAQPC3yhz/8AegMojiOg0KhEAwSSBz95Cc/CX3XtLm5iePHjwdPWhw7diwyLpeWlkJ5KpfLpZoEtlar4fLly7AsC4888oi5O6TZbAZPs3z96183d+NrX/saAODdd98Ntr3wwgvIZrNBHms0Gshmsz2f0tH96le/AgAcPXrU3AUYk8VK/ETFgVlGek3C22w2Q/lpL1doWltbC6Xn7Oxs33PXarVEEwb30q9uGoWZmRlYlhVZ9omIiIiIUjPfuTmMZPI/27a73uOXCSDlnXeZ+E8/3pwrQuZayGazwZwGMsGoPl9CqVQK3vOPep9eviPv0HueF0xwGTU3QD6fV47jBL8vE33qE1uOMjyyXZ8gVCaVtCwrmEQziai5DDY2NkLhL5VKofk85Dry+byyLCuYq8PzvCCe9bCVy2WVz+eD3yuXy8Hknvp5dnZ2grjSz2fOhdFLqVQKnVvmEzHnjJDtUflBxcw10Wq1QtflOE5X3uglbq4JSXd9AtRqtRrkE3Oi0DgSx9lsNpT/9ElYhcwzgpiqJy5+VldXg+tKM+9Eq9XqeT6ZD0XiW5/4VI8viSsJT6vVCsJtlqednR1lWVaoXEucJI1TU1S+iCLXLufxPC+INzP95Tclb7muGxwr201xcZmkbkojKg/EkXDoc/cQEREREQ2iu6d7iMXdtMqkgOZNvud5wXad3KCbHX/Hcbp+Q24Izc6+bDevRW7YzBsaGZgwzxl14zSq8Mj3zRutuJvaXuJutJS2Tx8AkWuQsJk3mq3OhI1R++T3zO0Sd67rhgaBJG3MSUTjyKoqevzF5bV+cSXXlGYC1n7iBkiKxaJCxMSlMqFp1L4okl9d1w3OoQ8KOI4THJt0gMTMo4OS8+nXoJP9Zt7Xw6I6ZcRMs7iyatt2V7rLeaLKWRJR5TyKXI8uLi/Kb5qDWPqgopn+UWmXpm5KCj3KiEkGOwc5DxERERGRbmxesenl9ttvBzqP4OvzQsirEvpkkM1mEysrK8jn85iamgq2A8C1a9dw8+bNrrklorz22muANjGnmJqainwV4OWXX0Yul+s6p0zQ+NZbbwXbRhWe9fV12LbdNUeCTCq5vb091EfqT5w4AXSuW67hueeeAwDcc889oWOnpqaCST+fffbZ0D5hzo0hcXf33XeHXouR8CWZ2NT3fTz66KP45S9/2RV/uzE5OWluGirf93Hx4kU4jtP1StDMzAyy2SwA9J3bodFoBPmpVCoFcZfJZLC1tQXLslCv11O/sjGs8L///vtAJ3/0cu7cudC/H3744eD/fd/HyspKaBuMsvqb3/wG6LzW5HleV7mWeGm32/jggw9C+4bJtu3Y17fiPPTQQ6H4WV5eDn7jypUr2pHR0tRNo/Ctb30LAPC73/3O3EVERERElAoHSFL63//9XwDAkSNHzF2pyESe5s1pnHq9jpWVleD9fvksLCwE+weRJjzXr1+H53ld13Ds2LHgmD//+c+h7wyT7/tBOM2bMQD47ne/C3QGNsxJPUfl8ccfx1NPPZVoUCwNmYtjVOQmPSoeAeD48eMAgKtXr5q7Qr744ovg/804mJqaQj6fBwC88847oX39RK3cMwpzc3NwHAcrKyuYnp5GpVKB7/vI5XLBoIbk6ZMnT3blfZlw9/r16wCAP/7xj0BnoMI8Vsgxo3Dt2jVcu3YN6AxeFQoFXLp0yTysrwcffBAA8NFHH5m7uoyqbiIiIiIi2mscIElpGDc35uSPSRWLRXRei4r8DCJteBzH6Tqv/jGfLhmmfoMv+g363/72t9C+UWg0Grh8+XLkjbPcHC4sLGBCmxg1yUAUUhw3qH7pLivMJHmKppd///d/D/37tttuC/07TpIVeobl2rVrWF1dxc2bN3Hy5EnccccdkU+8bGxsdOV3+WxtbYWObbVaXcfIZ9SrzsiEqwsLC7jrrruCQao0vvnNbwJA4qWkR1E3ERERERHtNQ6QpPTVr34V2IPHxqP0+2v+INKGp16vD/U1mjS+/OUvB//fb9WcUQ7U6FzXjfzYtg10niRwXRff/va3Ae0pF1nNxiTb5bhRkXSPuw7huq65KUSP56induR1LyGrjiAmDeWJBXmCZa+cPn0an3zyCUqlEgDgscce61qh5ve//33o372M8jWaXgqFAo4dO4bnn38eW1tbyOVyAw22/fWvfwW012T6GUXdRERERES01zhAkpIsTVqv1yNv8PzOcsK96DeVSZentG0b9Xo99vjFxUVzUyJpwiOvA5nzNYi1tbXIm+RhyWQywcCDLIOrk3P3u6kflpmZGWxtbUV+Tp06BQA4deoUtra2cOHCheA7juOg3W53xXez2US73YbjOF2vqwybzJ0RdR0A8NlnnwEJb5BlvpKowZZ//OMfAIAf/ehHwTZ5oiEqDeV1DHMOj0HJ/Dg3btwwdwGdpy1kCdypqSmcOXMG7777LizLCl5NkYG5lZWVyLiS5X+hDTw999xzkQOJjUYjtgzvVqPRCOYTkvl7BvXpp58CCcvSqOqmpD7//HMgYV4lIiIiIuqFAyQpzczMBDcNjz76aGhAoNlsYn5+vmsC0Shyk/jss89G3khBu7lE50YbnXkQlpaWgvM2m00UCoWB/kqMlOF56KGHgM6NYi6XC24WZRDlnXfeSTynyqDOnz8PADh79mxXvMkNetwkrQfFL37xC6Azqa1OJsR8/vnnQ9uHrVarIZPJBHlQXgfSvffee7AsC4888oi5q8vZs2eBmHh/4403YFlWaMDjpz/9KSzL6pqXpFarwfM8FIvF2LlR0pIBwF6vCr366quhf8/MzIQmSs5kMnBdF+12G8ePHw/mKUFnUGJ+fj4YiLnnnnuCiWnn5+eDwRd0JnC9//77E9UPg5ABJ3OQ8i9/+Uvo32a5McmktNlsNtFA3bDrJvP6+5H5X+S1IGiDVnr8ExERERH1ZS5rc5jFLaEqy1rath1aqlJf7lSWnJXtspymLEcpv20uJStLbJq/3Wq1gmVQbdtW5XJZVavVYMlddJYm1ZeulOPNj7nE7CjDI0vDmh9zSeFeyuVy8D3z92UZX/MadRI+x3GCZUir1aqyLEsVi8XQsfrv6dfXarWC5UGz2WwonvSlaM2lcZOKW1pVSDrL70uc5PN589Bdk3A6jqOKxWJwTXoe1Jd6XV1d7Rn/UfTrb7VaqtVqBXEQFYdy/OrqqlKdOLdtuysvD4OEPyp/Slpns9lQXjLTzvO8UBnRP2aa6XnO/Jj5PQk9P/aKH718Z7NZVSqVlOM4Qfht21b5fD4Ip16OJI1keWbXdbvOE1eWVIq6KQnJf4hYZjiKbdtdywxL3sN4NXFEREREtEtj0XvUbzD0j/rn7IFdn1KpFAwQ6B/XdYPf9DwvuMFA50bAvKE0vw/jZrHVaoUGRFzXVTs7O8EARdTNVKlUUrZtK3QGJYrFYujGwDwfhhgesbGxEboh0m8u+zGvIc016srlctc1mNcb93tx+aFarUZ+J26Qo5d+AySqcyMoadkrvndrZ2cnOI85gCQDGXqeyufzXTfASUTli16/U61Wg+Nt2+4ZV7shgzFR5UmuQcIv1yIDNzqzvMYdpzpxLgMTkr5RA0X96PlQ//QqF3J9Ui5lcMe27a70KJfLXdcZFU/6gEPcNZj5yKyb+okrl+Z5dJ7nKUQMUlU7A6bmYDgRERERUS8TiksMENEhNzs7C9u2Y+fJoFvT2toazp49i3q9PvLX+4iIiIjo8OMACREdeo1GA3feeSd2dnYSzatBt4bp6Wk8/fTTOH36tLmLiIiIiCg1TtJKRIfezMwMyuUyHn30UXMX3aLW1tZw7733cnCEiIiIiIaGT5AQ0dioVCr4+OOPg2WX6dZUqVTw3nvvYXl52dxFRERERDQwDpAQ0VhpNBrY3t7GmTNnzF10C6hUKrj99ttx4sQJcxcRERER0a5wgISIiIiIiIiIxh7nICEiIiIiIiKisccBEiIiIiIiIiIaexwgISIiIiIiIqKxxwESIiIiIiIiIhp7HCAhIiIiIiIiorHHARIiIiIiIiIiGnscICEiIiIiIiKisccBEiIiIiIiIiIaexwgISIiIiIiIqKxxwESIiIiIiIiIhp7HCAhIiIiIiIiorHHARIiIiIiIiIiGnscICEiIiIiIiKisccBEiIiIiIiIiIaexwgISIiIiIiIqKxxwESIiIiIiIiIhp7HCAhIiIiIiIiorH3/wE4iiETPKc2zwAAAABJRU5ErkJggg==\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eTable 1: Comparison of the reflectance peak positions derived from the experiment and computer simulations. Diffraction and Mie models were considered in the simulations, where the nanovoid diameter (D), depth (d) and periodicity (P) were considered to be 254, 80 and 800 nm, respectively. The data for various incident angles\u0026nbsp;\u0026theta;\u0026nbsp;= 40\u0026deg; to 60\u0026deg; are listed.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"623\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eIncident angle\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003cem\u003e\u0026theta;\u003c/em\u003e in deg.)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 505px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReflectance peak position (in nm)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eExperimentally measured\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003eMathematical calculation:\u003c/p\u003e\n \u003cp\u003eDiffraction model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eComputer simulation:\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eMie-resonance model\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e40\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e514\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e541\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e50\u0026deg;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e650\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e613\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e591\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 118px;\"\u003e\n \u003cp\u003e60\u0026deg;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e692\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003e651\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eIn order to get a deeper insight into the reflectance spectrum peak positions, the possible contribution from Mie resonance was investigated using the FEM computation in COMSOL. An earlier report on this topic revealed that the light-matter interaction of the tapered array of conical nanovoids, acting as nanoresonators, filled with a LRI medium (air with \u003cem\u003en\u003c/em\u003e = 1) fabricated on a HRI medium (Si with \u003cem\u003en\u003c/em\u003e \u0026gt; 1) could show higher monochromaticity, compared with the nanoresonators (e.g. Si nanocylinders) made of the HRI medium surrounded by LRI air medium [32]. It is also observed that the constricted nanoresonator shapes such as conical nanovoids showing higher monochromaticity (i.e., spectral purity), in contrast to the less- constricted cylindrical, square or sphere-shaped nanovoids at the normal light incidence [31],[32],[48],[49]. However, it should be noted that the reflectance spectra reported hitherto, for the arrays of both conical and non-conical shapes, were measured for the normal incidence of broadband light source [31], [32].\u003c/p\u003e\n\u003cp\u003eComputational FEM simulation of this work has given focus on the evaluation of different light scattering parameters, including scattering cross section and scattered electromagnetic field distribution as a function of incident angle and periodicity of the conical nanovoid array. Fig. 5 (a) shows a schematic of trapped meta-atoms (conical nanovoids) and the relevant details considered for the computational model. The nanovoids were modelled as conical holes on a Si substrate (\u003cem\u003en\u003c/em\u003e = 3.88 at \u003cem\u003e\u0026lambda;\u003c/em\u003e = 632.8 nm) [31], [32] with a finite layer of air covering the entire nanostructures (\u003cem\u003en\u003c/em\u003e = 1 at \u003cem\u003e\u0026lambda;\u003c/em\u003e = 590 nm). In computational simulations of an array of conical nanovoids, the excitation wave was considered to be a plane wave propagating along the Z-axis. Figure 5(b) shows the influence of the incident light angles (varied from 40\u0026deg; to 60\u0026deg;) on the reflectance spectrum of the meta-atoms with an array periodicity of 800 nm. Figure 5(c) shows the simulation results of the electric field distributions over the nanovoid resonator of diameter \u003cem\u003eD\u003c/em\u003e = 254 nm and depth \u003cem\u003ed\u003c/em\u003e = 80 nm, respectively. The effect of incident angle and nanovoid periodicities were investigated numerically. In the computational simulation, broader scattering cross-section resonance reflectance spectra (large full-width half maximum) were observed (Figure 5(b)), as compared to the experimental reflectance peak width (Figure 3(g)), with an approximate error in matching the spectral peak position of about 55 nm. The resonant reflectance peak positions derived from the Mie resonance model are also listed in Table 1 for various incident angles in order to compare with the experimentally measured values.\u003c/p\u003e\n\u003cp\u003eThe observed small difference between the experimental and calculated peak position using the diffraction model at higher \u003cem\u003e\u0026theta;\u003c/em\u003e (Table 1), it could be perceived that for a higher angle of incidence (\u003cem\u003e\u0026theta;\u003c/em\u003e = 60\u0026deg;) diffraction dominates over the Mie contribution. In this case, light diffraction, i.e., the interaction of light with structural periodicity (array of nanoholes), plays a dominant role in determining the reflectance peak wavelength position. It is important to consider that at high incident angles, only a small fraction of incident light can enter into the individual nanoholes resonators to excite the Mie resonances efficiently. In other words, the nanoresonator depth contribution to the Mie-excitation becomes less effective, and the incident light only detects the structural periodicity. Therefore, the diffraction involvement becomes dominant in deciding the reflectance spectra peak position. An average value of about 55\u0026deg; peak shift between the experimental and simulated Mie-resonance could be attributed to the possible deviations in refractive index values of the nanovoid boundaries from the crystalline Si matrix considered for simulation. The inner wall of the nanovoid resonator is not essentially composed of crystalline Si but is a mixture of amorphous Si, Ga inclusions and their oxides[39]. This modified inner wall layer is because of the Ga ion bombardment on the dielectric surface during the creation of nanovoids, as reported previously[40]. \u0026nbsp;\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn this work, we have demonstrated the incident angle-dependent dynamic tuning of visible structural colors with an array of nanovoids fabricated on the surface of silicon using a focused ion beam nanolithography technique. In addition to the high precision in fabricating the nanostructures by this method, prudently designing the nanostructure geometry and their spatial arrangement resulted in sharp peaks in the experimental reflectance spectra. The potential for effective tuning of structural color using either material or instrumental parameters, or both, is suggested by the observed linear relationship between the reflected wavelength and changes in periodicity or incident angle. The origin of the reflectance peaks and their shifts instigated by the incident angle or array periodicity were explained by harnessing two different physical phenomena, the Mie resonance and light diffraction, indicating that the nanovoids, building block of the array, not only perform as Mie-voids, but also simultaneously as an element of a crossed-diffraction. We further demonstrate that the Mie resonance associated with the individual nanovoids dominates for smaller incident angles (\u0026lt;\u0026thinsp;45\u0026ordm;), while for the larger angles (\u0026gt;\u0026thinsp;45\u0026ordm;), void array periodicity, the grating constant dependent light diffraction dominates structural color wavelength.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eOne of the authors, HR acknowledges the Department of Atomic Energy, India for the financial support needed to conduct the study. The authors TKB and JML acknowledge the High Performance Computing Center and Center of Excellence for Electronic Cooling and CFD Simulation of SRM Institute of Science and Technology, Kattankulathur, India for providing computational resources and financial support needed to conduct the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eZ. Xuan, J. Li, Q. Liu, F. Yi, S. Wang, and W. Lu, \u0026ldquo;Artificial Structural Colors and Applications,\u0026rdquo; \u003cem\u003eInnov.\u003c/em\u003e, vol. 2, no. 1, p. 100081, 2021, doi: 10.1016/j.xinn.2021.100081.\u003c/li\u003e\n \u003cli\u003eY. Yu, L. Wen, S. Song, and Q. Chen, \u0026ldquo;Transmissive/Reflective structural color filters: Theory and applications,\u0026rdquo; \u003cem\u003eJ. Nanomater.\u003c/em\u003e, vol. 2014, pp. 1\u0026ndash;18, 2014, doi: 10.1155/2014/212637.\u003c/li\u003e\n \u003cli\u003eB. Yang, H. Cheng, S. Chen, and J. 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Li \u003cem\u003eet al.\u003c/em\u003e, \u0026ldquo;Recent advances in focused ion beam nanofabrication for nanostructures and devices: Fundamentals and applications,\u0026rdquo; \u003cem\u003eNanoscale\u003c/em\u003e, vol. 13, no. 3, pp. 1529\u0026ndash;1565, 2021, doi: 10.1039/d0nr07539f.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"e6371b8a-2a71-4b49-8e28-6055d6515617","identifier":"10.13039/501100001502","name":"Department of Atomic Energy, Government of India","awardNumber":"NIL","order_by":0}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"Indira Gandhi Centre for Atomic Research","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"structural colors, nanolithography, subwavelength nanostructures, high-index material, focused ion beam, air-filled nanovoids","lastPublishedDoi":"10.21203/rs.3.rs-5606019/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5606019/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWe demonstrate incident angle-dependent dynamic tuning of visible structural colors with an array of nanovoids fabricated on the surface of silicon using focused ion beam nanolithography. Enhanced structural purity and resolution achieved by this method are manifested as sharp peaks in the experimental reflectance spectra. The linear correlation observed between reflected wavelength and changes in periodicity or incident angle demonstrates the potential for efficient tuning of structural color through manipulation of material or instrumental factors, or a combination of both. Two distinct physical phenomena, Mie resonance and light diffraction, were employed to elucidate the source of reflectance peaks and their shifts induced by incident angle or array periodicity. This analysis demonstrated that nanovoids, the fundamental components of the array, serve a dual purpose: they act as Mie-voids while simultaneously functioning as elements in a crossed-diffraction system. Our findings also show that for smaller angles of incidence (below 45°), the Mie resonance linked to individual nanovoids is the primary factor. However, when the angles exceed 45°, the structural color wavelength is predominantly influenced by the periodic arrangement of the void array and the diffraction of light, which depends on the grating constant.\u003c/p\u003e","manuscriptTitle":"Incident angle-dependent dynamic tuning of high-purity structural colors with an array of nanovoids on a dielectric surface","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-11 06:26:38","doi":"10.21203/rs.3.rs-5606019/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"63717ebe-c775-477f-bef1-de5645000c21","owner":[],"postedDate":"December 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":41322556,"name":"Nanoscience"}],"tags":[],"updatedAt":"2025-08-08T13:58:03+00:00","versionOfRecord":{"articleIdentity":"rs-5606019","link":"https://doi.org/10.1021/acsphotonics.5c00885","journal":{"identity":"acs-photonics","isVorOnly":true,"title":"ACS Photonics"},"publishedOn":"2025-08-07 00:00:00","publishedOnDateReadable":"August 7th, 2025"},"versionCreatedAt":"2024-12-11 06:26:38","video":"","vorDoi":"10.1021/acsphotonics.5c00885","vorDoiUrl":"https://doi.org/10.1021/acsphotonics.5c00885","workflowStages":[]},"version":"v1","identity":"rs-5606019","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5606019","identity":"rs-5606019","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}