Exchange Rate Volatility, Inflation Rate and Foreign Direct Investment in Nigeria

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Annual time series data were obtained from the Central Bank of Nigeria and the World Bank. Exchange rate volatility was measured using a five-year rolling standard deviation of the naira–dollar exchange rate. The Vector Error Correction Model (VECM) was employed in obtaining the effects, while the VEC Granger Causality/Block Exogeneity Wald test was used in investigating their causal influences. To allow for residual diagnostics, the short-run equations of the VECM were re-estimated using Ordinary Least Squares (OLS). The result showed exchange rate volatility has a negative effect on the foreign direct investment in the short run but positive effects in the long run, while inflation has a positive effect on exchange rate volatility both in the long run and in the short run. The result further showed that inflation Granger-causes FDI and there is weak evidence that inflation Granger-causes exchange rate volatility (10% test). Based on the findings, the study concluded that monetary authorities should exercise caution in their reliance on these results by identifying the threshold for inflation targeting policies in Nigeria. Macroeconomics Exchanger rate volatility inflation FDI VECM Co-integration 1. Introduction Foreign Direct Investment plays an imperative role in country's economy, particularly emerging countries where resources, technology, and managerial expertise, may be lacking (Nguyen 2022). It entails an investment by an individual or firm in one country into business interests located in another usually in the form of purchasing significant ownership stakes or establishing business operations like subsidiaries or branches. The economic policies developed with aim to stabilize the macro economy of Nigeria, such as interest rate policies, fiscal policies, and exchange rate policies, creates mixed results. While a few of the policies have observed an ability to induce foreign investments in some of business sectors, influences have been restricted with enduring macroeconomic instability (Nikolenko, et al 2022). For instance, Nigerian inflation rates relatively remained high, often over 10% per annum, which significantly impacts the cost of doing business (Okeke & Nwafor, 2022 ). This circumstance makes foreign investors concerned about investing due to perceptions of risky and unexpected business environments. As one of Africa’s main drivers of its economy, Nigeria offers an ideal example for exploring the interrelationship between exchange rate volatility, inflation rate and FDI. Nigeria’s economic history has been characterized by several periods of instability, particularly after the 1986 Structural Adjustment Programme (SAP), with a propensity aimed at charting a path towards a market-led economy. Although SAP helped towards liberalizing Nigerian economy and promoted private sector initiative, its implementation was accompanied with high rates of inflation and exchange rate volatility (Kombo and Isah, 2024 ). Despite these challenges, Nigeria remains a target for FDI, especially in oil and gas, telecommunication, and agricultural sectors. The Nigerian government has made efforts to create an enabling environment for foreign investors through various incentives, tax exemptions, and investment-friendly policies. However, the success of these initiatives in attracting stable and long-term foreign investments continues to be undermined by the unpredictable economic environment. Devaluation of Nigerian Naira, as well as constant movement of exchange rate regime, did tend towards creating an environment of uncertainty repeatedly discouraging foreign investors (Bamidele, 2024 ). This volatility, combined with ongoing inflationary pressures, remain an empirical among scholars and policy makers as to implications on FDI inflows. This is not to concludes that studies have not been done in this respect, but, however produced contradicting outcomes which makes open to further empirical work. For instance, studies like (Ramzen (2021), Warren, et al ( 2023 ). Akinlo and Onatunji (2021) and Hniya et al ( 2021 )) have provided a negative effects of exchange rate volatility on FDI at one hand and studies like (Agudze and Ibhagui ( 2021 ) and Sayek ( 2009 ) also produced a negative relationship between inflation and FDI, except for the work of Tsaurai ( 2018 ) whose result showed a positive relationship between inflation and FDI. More importantly, is that the effects of these variables on FDI at a given point in time may not inform the adequate needed direction in assisting policy makers towards formulating policies that could attract FDI to this country. To this effect, the study will go beyond effects and look empirically to the causal influence among exchange rate volatility, inflation rate and FDI in Nigeria. This is because exchange rate and inflation rate and their collective impact on FDI inflows, alongside their causal relationship in Nigeria could offer insights that could inform policy decisions and attract more stable and sustained foreign investment in the country. Based on the above issues raised, the following questions emerged. What is the effect of exchange rate volatility and inflation rate on foreign direct investment in Nigeria? Is there any causal relationship among exchange rate volatility, inflation rate, and foreign direct investment in Nigeria? To attend to these questions, the following objectives are achieved. Examine the effect of exchange rate volatility and inflation rate on foreign direct investment in Nigeria. Investigate the causal influences among exchange rate volatility, inflation rate, and foreign direct investment in Nigeria. 2. Literature Review The interconnectedness between FDI, exchange rate volatility, and inflation calls for good economic policies to be enacted to pull foreign investment into Nigeria and sustain them. This is supported by many theories but more specifically is the Purchasing Power Parity theory, first propounded by Gustav Cassel in 1918. The theory posits that exchange rates between two currencies in the long run would shift to counter changes in the price levels of nations. Essentially, if a country has a higher inflation rate than another country, its currency will depreciate so that the purchasing power of both currencies will be the same. This adjustment preserves the relative price of a similar basket of goods and services equal when defined in different currencies. According to the theory, if Nigeria experiences higher inflation compared to its trading partners (such as the U.S.), domestic goods become more expensive relative to foreign goods. The exchange value of the Naira should fall to bring back parity in the relative purchasing power of both nations. This depreciation is needed in order to influence the exchange rate adjustment so the relative prices of goods and services in Nigeria is equal to that of its trading partners. If Nigeria's inflation is constantly higher than its trading partners, the market would anticipate the Naira deprecating further. Anticipations of future devaluation therefore make exchange rate volatility high. Exchange rate volatility results when the market reacts to these anticipations, reacting to anticipated changes in the value of the Naira in the future. 2.2 Empirical Studies The effects of exchange rate volatility and inflation rate continues to generate arguments in the literature. Studies has looked into the collective effects of these two variables on FDI while some studies looked at it differently. For instance, Agudze and Ibhagui ( 2021 ) explored the nonlinear relationship between inflation and foreign direct investment (FDI) in industrialized and developing economies. Their study revealed that inflation has threshold effects, with the threshold being five times higher in developing economies compared to industrialized ones. Inflation negatively affects FDI in industrialized countries only when it surpasses the threshold, while in developing economies, the impact is negative even before exceeding the threshold. The authors highlighted that the mixed findings on the relationship between inflation and FDI in prior studies could be attributed to these threshold effects. Tsaurai ( 2018 ) examined the influence of inflation on FDI in Southern Africa and explored whether financial development moderates this impact. Using panel data analysis, the study found mixed results: inflation had an insignificant positive, negative, or significant negative influence on FDI depending on the model applied. The findings emphasized the need for Southern African countries to implement policies that lower inflation and develop the financial sector to attract sustainable FDI inflows. Vasileva ( 2018 ) investigated the effect of inflation targeting (IT) on FDI inflows to developing countries using a difference-in-differences approach. The study concluded that IT adoption increases FDI inflows, particularly during times of economic instability. This highlighted the role of credible monetary policies in creating a stable macroeconomic environment that fosters FDI in developing economies. Valli and Masih ( 2014 ) analyzed the long-term relationship between inflation and FDI in South Africa under an inflation-targeting regime. Their findings revealed an inverse relationship between inflation and FDI, indicating that higher inflation negatively affects FDI inflows. The study also demonstrated causality between stable inflation levels and improved FDI, emphasizing the importance of consistently applied inflation-targeting policies in enhancing FDI inflows. Hong and Ali (2020) assessed the impact of inflation on FDI in Malaysia and Iran over the period 1986–2016. Their results showed a short-run relationship between FDI and gross domestic product (GDP) in Malaysia, while no causality was observed in Iran. The study employed advanced econometric techniques to explore these dynamics, highlighting the variations in inflation-FDI relationships across countries. Udoh and Egwaikhide ( 2008 ) investigated the effects of exchange rate volatility and inflation uncertainty on FDI in Nigeria using data from 1970 to 2005. The study employed the GARCH model to estimate exchange rate volatility and inflation uncertainty. The findings revealed that both variables had significant negative effects on FDI. Additionally, factors such as infrastructural development, government sector size, and international competitiveness were identified as crucial determinants of FDI inflows, emphasizing the need for policymakers to ensure exchange rate and macroeconomic stability. Asmae and Ahmed ( 2019 ) examined the impact of exchange rate and price volatility on FDI inflows over a 27-year period. Their findings indicated that real exchange rate volatility had a significant negative effect on FDI in one case, while price volatility showed a positive effect, suggesting that higher inflation volatility may lead to increased marginal profitability and investment. The study also identified factors such as potential market size, institutional quality, and infrastructure as key in attracting foreign capital. Dal Bianco and Loan ( 2017 ) explored the effects of exchange rate and price volatility on FDI inflows across selected countries over 22 years, using GARCH models to estimate volatility. Their results showed that exchange rate volatility had a significant negative impact on FDI, supporting the theory of hysteresis and option value. However, price volatility was found to have an insignificant positive effect. The study also highlighted the importance of trade openness and human capital development in attracting foreign investment, alongside the need for stabilization policies. Mostafa ( 2020 ) investigated the impact of inflation and exchange rate on FDI using time series data spanning 37 years. Employing econometric techniques, the study revealed that inflation had a significant negative effect on FDI in the long run, while exchange rate depreciation positively influenced FDI both in the short and long run. The findings underscored the importance of maintaining low inflation levels and ensuring currency stability to attract higher FDI inflows. These empirical studies collectively underscore the importance of macroeconomic stability, particularly in terms of exchange rate and inflation management, as key determinants of FDI inflows. The literature has revealed the existence of the effects of exchange rate and inflation rate on foreign direct investment, however, most investors are sometimes not particular about exchange rate phenomenon but exchange rate volatility whose determine their investment future stability, more also, is that, the causal influence among these variables seems missing in the literature when considering studies in Nigeria. 3. Methodology The Mundell-Fleming model offers a useful framework for explaining how macroeconomic instability influences capital flows in an open economy. Within the model, inflation and exchange rate uncertainty can influence foreign investment decisions through their impact on investor optimism and anticipated returns (Rahimian, et al 2022 ). Along this line of reasoning, chronic inflation or exchange rate volatility can make a nation unattractive to foreign direct investment (FDI), especially in countries that are strongly dependent on foreign capital (Adewale, et al 2024 ). 3.1 Model Specification In obtaining the existing relationship among exchange rate volatility, inflation and foreign direct investment, a linear model is specified as thus: Each equation of the VECM system illustrates the short-run relationship between the variables and permits the long-run equilibrium relationship through the error correction term (ECMₜ₋₁). The ECMₜ₋₁ is derived from the residuals of the co-integrating equation and illustrates how far from equilibrium the system was last period. The coefficient on the ECM term in each of the equations (λ₁, λ₂, λ₃) controls the speed of adjustment, and it specifies how quickly the respective dependent variable responds to eliminate disequilibrium from long-run equilibrium. The existence of a negative and statistically significant coefficient confirms that the variable adjusts to return towards equilibrium after a shock. The specification of this single ECM term is consistent with the Johansen test outcome of a single stable co-integrating relation among the variables. 4. Result and Discussion To analyses the existing relationship among exchange rate volatility, inflation rate, and foreign direct investment (FDI) in Nigeria, Vector Error Correction Model (VECM), was used. The unit root and co-integration tests to establish the time-series properties and long-run equilibrium among the variables was conducted. Table 4.1 Unit root result- Trend and Intercept Variables Criteria Value At Level I(0) At 1st Difference Remark -3.548490 -1.889753 -8.843145 I(1) -3.540328 -2.617217 -6.01577 I(1) -3.557759 -2.617217 -6.015777 I(1) Source: Author’s Computation From Table 4.1 the finding shows that the variables are integrated of order one, I (1), based on this, the Johansen cointegration test was conducted. It therefore important to determine the lag length as given below in Table 4.2 Table 4.2 Lag length selection LagL LR AIC SC HQ 0 -355.430144 NA 21.72304 21.85909 21.76881 1 -316.589180 68.26594 19.91450 20.45868* 20.09760 2 -304.411109 19.18969* 19.72189* 20.67421 20.04231* 3 -296.822315 10.57832 19.80741 21.16787 20.26517 Source: Author’s Computation The lags' structure is central to the identification of the dynamics of the underlying system and the assurance that the error terms of the model are adequately behaved (Udo, & Idochi, 2024 ). The results of the lag length selection including the Akaike Information Criterion (AIC) and the Hannan-Quinn Criterion (HQ), both of which selected the optimal lag length at lag 2 of the VAR system. Having obtain the Lag length, we proceeded to test for the existence of a long-run equilibrium relationship among the variables. The Johansen cointegration test was applied, using the trace statistic and maximum eigenvalue statistic, with a lag length of two as determined, but however, reported the trace statistics since there is not contradition in their outcome. From the Table below, the Johansen trace test discovers the presence of one cointegrating relationship at the 5 percent significance level Table 4.3 Johansen Cointegration Test Result Hypothesized No. of CE(s) 5% Criteria Value Prob. None * 29.797073 0.002145 At most 1 15.494712 0.210115 At most 2 3.8414654 0.174683 Note: Trace test indicates 1 cointegrating equation(s) at the 0.05 level * denotes rejection of the hypothesis at the 0.05 level **MacKinnon-Haug-Michelis (1999) p-values Source: Author’s Computation Table 4.4 Long- and Short-run Effects of Exchange Rate Volatility and Inflation Rate, (FDI) Variables Coefficient Std. Error t-Statistic LFDI(–1) 1.000000 Nil Nil EXR(–1) 0.010092 0.003338 3. 02289 INFR(–1) 0.061279 0.009564 6.40711 C -22.984526 Nil Nil Error Correction D(LFDI) Coefficient Std. Error t-Statistic ECM(-1) –0.503048 0.129619 –3.880970 D(LFDI(–1)) –0.218719 0.161947 –1.350570 D(LFDI(–2)) 0.035566 0.148400 0.239670 D(EXR(–1)) –0.000630 0.002560 –0.247950 D(EXR(–2)) –0.001480 0.002560 –0.578170 D(INFR(–1)) 0.027200 0.006780 4.013880 D(INFR(–2)) 0.016070 0.008260 1.946220 C 0.065760 0.088770 0.740760 Statistic Value R-squared 0.278711 Adjusted R-squared 0.076750 F-statistic 1.380028 S.E. of regression 0.630351 Log likelihood -27.01527 Source: Author’s Computation The result from Table 4.4 confirms that in long-run a one percent increase in exchange rate volatility and inflation increases foreign direct investment by 0.01 and 0.06 percent respectively, while in the short-run a one percent increase in exchange rate volatility and inflation rate reduces and increases foreign direct investment by 0.001 and 0.03 percent respectively. These effects are significant both in the short run and long run except that of the exchange rate volatility that is not significant in the short run. The error correction term (ECM(-1)) is negative at the 1 percent level, and the coefficient value is − 0.503048. This is evidence that approximately 50 percent of any long run disequilibrium in FDI is corrected within one period. In other words, foreign investment flows in Nigeria exhibit a strong tendency to revert toward equilibrium following macroeconomic disturbances. This is consistent with the work of Akinlo ( 2004 ), which cited that FDI in the country is sector-specific and profitability-based rather than macroeconomic stability-based. Investor response to volatility might be dampened with adequate promised payoffs as the finding in the work of Iseolorunkanmi et al., ( 2023 ) shows. Same finding was also seen in the work of Warren, Seetanah, and Sookia ( 2023 ), in which exchange rate volatility propelled FDI inflows positively according to their gravity model estimation, which espouses the view that foreign investors perceive volatility as an indicator of market activity or speculation, and hence, take FDI inflows positively. Additionally, inflation rate has a positive effect on FDI, this means that higher FDI inflows are followed by higher inflation. This is an unexpected finding, as the hypothesis according to economic principles is that higher inflation leads to reduced real returns and hence decreases FDI inflows. But the result may indicate the capability of the investors in the Nigerian experience to hedge the price or terms of contract of the inflationary risks. Otherwise, the result may indicate periods of moderate inflation that coincide with economic growth periods, which attracts capital flows. There is an argument used in some parts of the recent literature that in developing countries, inflation may indicate domestic demand expansion or price mark-ups that attract foreign investors. For example, Agudze and Ibhagui ( 2021 ) observed that inflation was positively related to FDI in the select developing economies, and the suggestion is that foreign investors may accommodate inflationary sentiments if the prospects of profitability remain strong. While the relationship direction is the reverse of ex ante expectation, statistical significance, with OLS-based re-estimation diagnostic help, is strong. They emphasize the need for the FDI behaviour explanation to be in the structural realities of the country, and not an application of large macroeconomic models strictly. The intercept is captured negatively, with the constant term. 4.2 The Causality Test To assess the direction of causality among the variables, the VEC Granger Causality/Block Exogeneity Wald test was employed. This test helps determine whether lagged values of one variable provide statistically significant information in forecasting another variable, within the context of the Vector Error Correction Model. Table 4.5 Granger Causality Test Dependent Variable Excluded Variable Chi-square df Prob. Conclusion D(LFDI) D(EXR) 0.3954 2 0.8206 No causality D(INFR) 16.5659 2 0.0003 INFR → LFDI (Significant) D(EXR) D(LFDI) 0.0112 2 0.9944 No causality D(INFR) 5.2207 2 0.0735 INFR → EXR (Weak significance) D(INFR) D(LFDI) 3.1050 2 0.2117 No causality D(EXR) 0.9649 2 0.6172 No causality Source: Author’s Computation From the result in table 4. 5, Inflation Granger-causes FDI at 1% significance value. It signifies there is presence of relevance of past values of inflation in FDI inflows in Nigeria. It confirms earlier discovery in VECM estimation of inflation as significantly determining FDI in long-run as well as in short-run. There is weak evidence (10% test) that inflation Granger-causes exchange rate volatility, thus some impact of change in domestic price on change in exchange rate but not particularly large. The result did not reveal any causal influence between exchange rate volatility FDI, nor FDI Granger-causing exchange rate volatility or inflation. 5. Conclusion and Recommendations The study investigated the short-run and long-run effects of exchange rate volatility and inflation on foreign direct investment (FDI) in Nigeria from 1986 to 2023. Employing the Vector Error Correction Model (VECM). This study concludes that, the long-run estimates exhibited a statistically significant and positive connection between exchange rate volatility and FDI. Conversely, the short-run exchange rate volatility coefficients were insignificant. Correspondingly, inflation registered a positive and statistically significant relationship with FDI both in the long- and short-run, this was also complimented by the causal influence result. Although, this result is contrary to the hypothesis that it decreases the volatility of real pay and investment but aligns with the result of Omolade and Ngalawa (2018), which is that inflation is always non-deterrent to FDI, especially with the efficacy of liberalises policy or growth prospects. Iseolorunkanmi et al. ( 2023 ) further hold that investor decision in Nigeria is rather guided more with the aid of structural possibilities and hypothesized profitability rather than macro volatilities. Based on the findings of the study, it's recommended that the exchange rate should be kept stable in Nigeria to motivate foreign investors’ confidence even if the result shows its positive response by FDI. More importantly, the results indicated that foreign direct investment (FDI) responded positively despite the increase in Nigeria's inflation rate over the years. The monetary authorities should be cautious in relying on this by knowing the threshold through inflation targeting policies in Nigeria. Based on this, the study recommended that the exchange rate should be kept stable in Nigeria in order to motivate foreign investors’ confidence even if the result shows its positive response by FDI. More importantly, the result showed a positive response by the FDI in light of the increase in inflation rate in Nigeria over the years. The monetary authorities should be very careful in relying on this by knowing the threshold through inflation targeting policies in Nigeria. References Adewale, A. M., Olopade, B. C., & Ogbaro, E. O. (2024). Effect of exchange rate on foreign direct investment in Nigeria. ABUAD Journal of Social and Management Sciences, 5(2), 302-318. Agudze, K., & Ibhagui, O. 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Investigating the impact of inflation on foreign direct investment in Southern Africa. *Acta Universitatis Danubius. Œconomica, 14*(4), 597-611. Udo, O. C., & Idochi, O. (2024). SIMPLE REGRESSION MODELS: A COMPARISON USING CRITERIA MEASURES. Udoh, E., & Egwaikhide, F. O. (2008). Exchange rate volatility, inflation uncertainty and foreign direct investment in Nigeria. Botswana Journal of Economics, 5 (7), 14-31. Valli, M., & Masih, M. (2014). Is there any causality between inflation and FDI in an ‘inflation targeting’ regime? Evidence from South Africa. Vasileva, I. (2018). The effect of inflation targeting on foreign direct investment flows to developing countries. *Atlantic Economic Journal, 46*, 459-470. Warren, M., Seetanah, B., & Sookia, N. (2023). An investigation of exchange rate, exchange rate volatility and FDI nexus in a gravity model approach. International Review of Applied Economics, 37 (4), 482-502. Additional Declarations The authors declare no competing interests. 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09:39:20","extension":"html","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":75019,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7963423/v1/82d1c1d30a88ae1aa687866e.html"},{"id":95230441,"identity":"8047bab5-9293-4576-965f-e687024956b9","added_by":"auto","created_at":"2025-11-05 16:37:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":804641,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7963423/v1/8f067faf-d867-4ede-a4a6-a27e12e5e6bb.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eExchange Rate Volatility, Inflation Rate and Foreign Direct Investment in Nigeria\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eForeign Direct Investment plays an imperative role in country's economy, particularly emerging countries where resources, technology, and managerial expertise, may be lacking (Nguyen 2022). It entails an investment by an individual or firm in one country into business interests located in another usually in the form of purchasing significant ownership stakes or establishing business operations like subsidiaries or branches.\u003c/p\u003e\u003cp\u003eThe economic policies developed with aim to stabilize the macro economy of Nigeria, such as interest rate policies, fiscal policies, and exchange rate policies, creates mixed results. While a few of the policies have observed an ability to induce foreign investments in some of business sectors, influences have been restricted with enduring macroeconomic instability (Nikolenko, et al 2022). For instance, Nigerian inflation rates relatively remained high, often over 10% per annum, which significantly impacts the cost of doing business (Okeke \u0026amp; Nwafor, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This circumstance makes foreign investors concerned about investing due to perceptions of risky and unexpected business environments.\u003c/p\u003e\u003cp\u003eAs one of Africa\u0026rsquo;s main drivers of its economy, Nigeria offers an ideal example for exploring the interrelationship between exchange rate volatility, inflation rate and FDI. Nigeria\u0026rsquo;s economic history has been characterized by several periods of instability, particularly after the 1986 Structural Adjustment Programme (SAP), with a propensity aimed at charting a path towards a market-led economy. Although SAP helped towards liberalizing Nigerian economy and promoted private sector initiative, its implementation was accompanied with high rates of inflation and exchange rate volatility (Kombo and Isah, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Despite these challenges, Nigeria remains a target for FDI, especially in oil and gas, telecommunication, and agricultural sectors. The Nigerian government has made efforts to create an enabling environment for foreign investors through various incentives, tax exemptions, and investment-friendly policies. However, the success of these initiatives in attracting stable and long-term foreign investments continues to be undermined by the unpredictable economic environment.\u003c/p\u003e\u003cp\u003eDevaluation of Nigerian Naira, as well as constant movement of exchange rate regime, did tend towards creating an environment of uncertainty repeatedly discouraging foreign investors (Bamidele, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This volatility, combined with ongoing inflationary pressures, remain an empirical among scholars and policy makers as to implications on FDI inflows. This is not to concludes that studies have not been done in this respect, but, however produced contradicting outcomes which makes open to further empirical work.\u003c/p\u003e\u003cp\u003eFor instance, studies like (Ramzen (2021), Warren, et al (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Akinlo and Onatunji (2021) and Hniya et al (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)) have provided a negative effects of exchange rate volatility on FDI at one hand and studies like (Agudze and Ibhagui (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Sayek (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) also produced a negative relationship between inflation and FDI, except for the work of Tsaurai (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) whose result showed a positive relationship between inflation and FDI. More importantly, is that the effects of these variables on FDI at a given point in time may not inform the adequate needed direction in assisting policy makers towards formulating policies that could attract FDI to this country.\u003c/p\u003e\u003cp\u003eTo this effect, the study will go beyond effects and look empirically to the causal influence among exchange rate volatility, inflation rate and FDI in Nigeria. This is because exchange rate and inflation rate and their collective impact on FDI inflows, alongside their causal relationship in Nigeria could offer insights that could inform policy decisions and attract more stable and sustained foreign investment in the country.\u003c/p\u003e\u003cp\u003eBased on the above issues raised, the following questions emerged. What is the effect of exchange rate volatility and inflation rate on foreign direct investment in Nigeria? Is there any causal relationship among exchange rate volatility, inflation rate, and foreign direct investment in Nigeria? To attend to these questions, the following objectives are achieved. Examine the effect of exchange rate volatility and inflation rate on foreign direct investment in Nigeria. Investigate the causal influences among exchange rate volatility, inflation rate, and foreign direct investment in Nigeria.\u003c/p\u003e"},{"header":"2. Literature Review","content":"\u003cp\u003eThe interconnectedness between FDI, exchange rate volatility, and inflation calls for good economic policies to be enacted to pull foreign investment into Nigeria and sustain them. This is supported by many theories but more specifically is the Purchasing Power Parity theory, first propounded by Gustav Cassel in 1918. The theory posits that exchange rates between two currencies in the long run would shift to counter changes in the price levels of nations. Essentially, if a country has a higher inflation rate than another country, its currency will depreciate so that the purchasing power of both currencies will be the same. This adjustment preserves the relative price of a similar basket of goods and services equal when defined in different currencies. According to the theory, if Nigeria experiences higher inflation compared to its trading partners (such as the U.S.), domestic goods become more expensive relative to foreign goods. The exchange value of the Naira should fall to bring back parity in the relative purchasing power of both nations. This depreciation is needed in order to influence the exchange rate adjustment so the relative prices of goods and services in Nigeria is equal to that of its trading partners.\u003c/p\u003e\u003cp\u003eIf Nigeria's inflation is constantly higher than its trading partners, the market would anticipate the Naira deprecating further. Anticipations of future devaluation therefore make exchange rate volatility high. Exchange rate volatility results when the market reacts to these anticipations, reacting to anticipated changes in the value of the Naira in the future.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Empirical Studies\u003c/h2\u003e\u003cp\u003eThe effects of exchange rate volatility and inflation rate continues to generate arguments in the literature. Studies has looked into the collective effects of these two variables on FDI while some studies looked at it differently.\u003c/p\u003e\u003cp\u003eFor instance, Agudze and Ibhagui (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) explored the nonlinear relationship between inflation and foreign direct investment (FDI) in industrialized and developing economies. Their study revealed that inflation has threshold effects, with the threshold being five times higher in developing economies compared to industrialized ones. Inflation negatively affects FDI in industrialized countries only when it surpasses the threshold, while in developing economies, the impact is negative even before exceeding the threshold. The authors highlighted that the mixed findings on the relationship between inflation and FDI in prior studies could be attributed to these threshold effects.\u003c/p\u003e\u003cp\u003eTsaurai (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) examined the influence of inflation on FDI in Southern Africa and explored whether financial development moderates this impact. Using panel data analysis, the study found mixed results: inflation had an insignificant positive, negative, or significant negative influence on FDI depending on the model applied. The findings emphasized the need for Southern African countries to implement policies that lower inflation and develop the financial sector to attract sustainable FDI inflows.\u003c/p\u003e\u003cp\u003eVasileva (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) investigated the effect of inflation targeting (IT) on FDI inflows to developing countries using a difference-in-differences approach. The study concluded that IT adoption increases FDI inflows, particularly during times of economic instability. This highlighted the role of credible monetary policies in creating a stable macroeconomic environment that fosters FDI in developing economies.\u003c/p\u003e\u003cp\u003eValli and Masih (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) analyzed the long-term relationship between inflation and FDI in South Africa under an inflation-targeting regime. Their findings revealed an inverse relationship between inflation and FDI, indicating that higher inflation negatively affects FDI inflows. The study also demonstrated causality between stable inflation levels and improved FDI, emphasizing the importance of consistently applied inflation-targeting policies in enhancing FDI inflows.\u003c/p\u003e\u003cp\u003eHong and Ali (2020) assessed the impact of inflation on FDI in Malaysia and Iran over the period 1986\u0026ndash;2016. Their results showed a short-run relationship between FDI and gross domestic product (GDP) in Malaysia, while no causality was observed in Iran. The study employed advanced econometric techniques to explore these dynamics, highlighting the variations in inflation-FDI relationships across countries.\u003c/p\u003e\u003cp\u003eUdoh and Egwaikhide (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) investigated the effects of exchange rate volatility and inflation uncertainty on FDI in Nigeria using data from 1970 to 2005. The study employed the GARCH model to estimate exchange rate volatility and inflation uncertainty. The findings revealed that both variables had significant negative effects on FDI. Additionally, factors such as infrastructural development, government sector size, and international competitiveness were identified as crucial determinants of FDI inflows, emphasizing the need for policymakers to ensure exchange rate and macroeconomic stability.\u003c/p\u003e\u003cp\u003eAsmae and Ahmed (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) examined the impact of exchange rate and price volatility on FDI inflows over a 27-year period. Their findings indicated that real exchange rate volatility had a significant negative effect on FDI in one case, while price volatility showed a positive effect, suggesting that higher inflation volatility may lead to increased marginal profitability and investment. The study also identified factors such as potential market size, institutional quality, and infrastructure as key in attracting foreign capital.\u003c/p\u003e\u003cp\u003eDal Bianco and Loan (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) explored the effects of exchange rate and price volatility on FDI inflows across selected countries over 22 years, using GARCH models to estimate volatility. Their results showed that exchange rate volatility had a significant negative impact on FDI, supporting the theory of hysteresis and option value. However, price volatility was found to have an insignificant positive effect. The study also highlighted the importance of trade openness and human capital development in attracting foreign investment, alongside the need for stabilization policies.\u003c/p\u003e\u003cp\u003eMostafa (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) investigated the impact of inflation and exchange rate on FDI using time series data spanning 37 years. Employing econometric techniques, the study revealed that inflation had a significant negative effect on FDI in the long run, while exchange rate depreciation positively influenced FDI both in the short and long run. The findings underscored the importance of maintaining low inflation levels and ensuring currency stability to attract higher FDI inflows.\u003c/p\u003e\u003cp\u003eThese empirical studies collectively underscore the importance of macroeconomic stability, particularly in terms of exchange rate and inflation management, as key determinants of FDI inflows. The literature has revealed the existence of the effects of exchange rate and inflation rate on foreign direct investment, however, most investors are sometimes not particular about exchange rate phenomenon but exchange rate volatility whose determine their investment future stability, more also, is that, the causal influence among these variables seems missing in the literature when considering studies in Nigeria.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Methodology","content":"\u003cp\u003eThe Mundell-Fleming model offers a useful framework for explaining how macroeconomic instability influences capital flows in an open economy. Within the model, inflation and exchange rate uncertainty can influence foreign investment decisions through their impact on investor optimism and anticipated returns (Rahimian, et al \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Along this line of reasoning, chronic inflation or exchange rate volatility can make a nation unattractive to foreign direct investment (FDI), especially in countries that are strongly dependent on foreign capital (Adewale, et al \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Model Specification\u003c/h2\u003e\u003cp\u003eIn obtaining the existing relationship among exchange rate volatility, inflation and foreign direct investment, a linear model is specified as thus:\u003c/p\u003e\u003cp\u003e\u003cimg 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EOhqBILod3X3ROUCgUAgEAgEegeBqGkgEAgEAt2FQBD97uqPqE0gEAgEAoFAIBAIBAKBwEhBYAa3I4j+DO6AKD4QCAQCgUAgEAgEAoFAIBDoBAJB9DuBauQZCAwNgUgdCAQCgUAgEAgEAoHAkBEIoj9kCCODQCAQCAQCgUCg0whE/oFAIBAIDByBIPoDxyxSBAKBQCAQCAQCgUAgEAgEAjMWgRZKD6LfAkgRJRAIBAKBQCAQCAQCgUAgEOg1BILo91qPRX0DgaEhEKkDgUAgEAgEAoFAYJQgEER/lHR0NDMQCAQCgUAgEKiPQPgGAoHASEUgiP5I7dloVyAQCAQCgUAgEAgEAoHAqEZg0ER/VKMWjQ8EAoFAIBAIBAKBQCAQCAS6HIEg+l3eQVG9QKCHEIiqBgKBQCAQCAQCgUAXIRBEv4s6I6oSCAQCgUAgEAiMLASiNYFAIDAjEQiiPyPRj7IDgUAgEAgEAoFAIBAIBAKBDiHQlUS/Q22NbAOBQCAQCAQCgUAgEAgEAoFRg0AQ/VHT1dHQQKCnRb7+LAAAEABJREFUEYjKBwKBQCAQCAQCgcAAEQiiP0DAInogEAgEAoFAIBAIdAMCUYdAIBBohkAQ/WYIRXggEAgEAoFAIBAIBAKBQCDQgwiMOqLfg30UVQ4EAoFAIBAIBAKBQCAQCAQGjEAQ/QFDFgkCgUBghCEQzQkEAoFAIBAIBEYkAkH0R2S3RqMCgUAgEAgEAoFAYPAIRMpAYGQgEER/ZPRjtCIQCAQCgUAgEAgEAoFAIBCYBoEg+tPAMbQfkToQCAQCgUAgEAgEAoFAIBDoFgSC6HdLT0Q9AoFAYCQiEG0KBAKBQCAQCARmGAJB9GcY9FFwIBAIBAKBQCAQCIw+BKLFgcDwIRBEf/iwjpICgUAgEAgEAoFAIBAIBAKBYUMgiP6wQT20giJ1IBAIBAKBQCAQCAQCgUAgMBAEep7ov/zyy+mee+5JjzzySHrllVcG0va2xn3xxRfLOtx+++0N81XHBx98MD3wwANJ3RtG7rLAl156qWyjug+kak888US677770gsvvNAw2VNPPZWmTJmSnnnmmYbxWg00JvTH888/32qSqfGee+65dNdddyV1n+rZAy+wu/POOxMsh7O6xvLjjz+e7rjjjgTzxx57rOfG93Di1aayIptAIBAIBAKBQKAhAkMm+pdcckmaNGnSdO7ggw9OF1xwQccJB0KxyiqrpN/97ndtI4gNEasTiFSdfPLJ6bvf/W5aYokl6sT4nxfS+ZOf/CT98Ic/LEnz/0K6++3hhx9Ohx12WPrmN7+Z1ltvvZYre+2116af/exnafXVV0833nhjw3RHHHFEWnjhhdMpp5zSMF6rgb/85S/L/rj++utbTTI13kUXXZQ+8YlPpH333XeqXy+8nHHGGWn55ZdPsByu+iL55vo//vGP9Nvf/jZ99rOfLcfI1VdfPUOF7+Fqf5QTCAQCgUD3IBA1CQSmRWDIRJ+G+sorr0xbbLFFWmedddLTTz+daEOPP/749P3vfz9ttdVW6aGHHpq21BZ+3XDDDemaa66ZLubee+89jd/rXve6tO2226Yvf/nL6TWvec00YZ38gbRW6zf33HMnQk+zMmeZZZaSBP3gBz9Ic845Z7PoXRX+hje8IR177LFl/7ZasaIoSk1+K6cASy+9dPrXv/6Vxo0b12r2DeN97WtfS7vttlt629veNk28c845p+mYfPe7312S1hVWWGGatK3+uPjiixPNeqvx2xXv/e9/f9p5550TLNuVZ7N89O3uu++eFlpoofSnP/0p7bTTTomAZ11oljbCA4FAIBAIBAKBQKBzCAyZ6H/4wx9OG264YUIwVHODDTYoiewuu+yS3vWud6U99tgj7bjjjgMih/I56KCD0nXXXed1qmOis/3220/97QW5/8IXvpA+9KEPJSSa33A42u2rrrqqLIqwgVi9/vWvL383+jPzzDOn5ZZbLo0fPz7NNttsjaIOW1grBb3xjW9Mn/rUp1qJOk2cRRZZJHHTePbz453vfGdae+21pyPm/URv6r3kkkumr3/964mAUo38xz/+selJ03zzzVeeQrRa92r+Tj+OOuqoxESr6j8c7wsssED6yle+kmA5HOUpw7w877zz0lve8pZUFEVywnbSSSelL33pS+VvccIFAoFAIBAIBAKBwPAjMGSir8qI7hxzzOE1zTTTTKWba665SvMUpioXXnhhabtbRmjyxwnBFVdckY488sj07LPPTo3tlGDixInlicFUzxn0wiSBaUS1fkVRBKmZQf3RarHuUfz6179uakLUan79xWM+g+gby/3FGUn+TrLcvyiKomwWgXv++edP1oXSI/70IgJR50AgEAgEAoERgEBbiH5/OGTyjxAjA/vss0+aNGlSQoSkYdLjN3faaaeVWv+bbrqpND0QX7z//Oc/6ayzzkrsfw888MDSDr8a/9FHH02nn356aTaDyLEXdiHwuOOOS7feemtpB8/c5L///W9pTqDcqrv77rtLc5RJffWqusMPPzw9+eST1ajl+y233FLeByC8nHnmmenf//53uvzyy8uw/MeFyPPPPz9pLxOmaj7C2H9LCxdp1Pnmm29OhxxySJnfiSeeWLYnh4tTdYQephHahExqpzsRTkG0R37qmfNjYuQibTWPe++9NylHm+EqP2StGsc7oUu4trDD5lfraLAnT56c9JU6TZkypTZK09/67rbbbkuHHnpoeSFXAvXRDtphT/2qTQcccEDyWzvFq+cImNq0//77l2PARVFtcLpk3MHr6KOPrpe0vETq8vAJJ5yQsvmJ+sFWXfS9PIQzJTNWhcvMXY0ddtihFGyRffi6FCzMWDWm+WlHFSeXfi+77LIkP+32vt9++yV5qLv02Slfu/TLueeemy699NIcVGKnjkzLeJ566qnlnFMmR/vOX9n6ip+xyo/TB8Y+f20xXvnXc9oD07PPPrucK8ccc0xZljmc4xt7OT9zMpcvXDuVp77iaYf5JL02a5sw8ZhCuS8Bc/dyzA0YGXNO16r56nt1sqbkflFeuEAgEAgEAoGhIBBpexGBjhJ9ttBAmWeeedK8885bfh2HHT9zHv7c/fffn7bZZpvSltqlVqYt73jHO5ITAeHZsf+dffbZ88/yiawghhMmTEjInw0eAfzzn/9c3hdAMFzI9Nx6661LPwStTNz3xz2A9ddfPyFDyPhf/vKXtO6665YEvS+47v9OLN7+9rdPV78cGbEgWCBA8vvOd75TknfhCJ+Tih/96EeJ+Qgywx+xUWdfK5EeCWXzjNAIrzqE3WVVmMESoZEXEuSCr/Ygbn//+98T4s/PPQltlQ/BAHnfbrvtSoLot/zEQyrFyU47Ntlkk/LrM8xQ2LvnsPxE9tiEI2IwRBBdNs5mTTleo6d+Q9rYdsNL/cVHoNWTadjf/va3Ekd12nTTTRMTLmNHvFrnnghTknxvJNvKM8cxjmrj1/42hv76178mWCpPOEIKZ5jrK4TUqc6WW26Z1Ef9xeMWW2wxj2kcIYGQwRwNSdVf2kVIU1/lGBfyR7ARfm2Gh3GUM0N0d91119L0yFeB5Ckv4QSAP/zhD8n9D4IkP30ivXwJavqbP2fsKCOTefMArsYpoeoXv/hFef9F/cQfiEPO1Uv/ESqNE2Nae7LwZIzoc3d5hMHURW91MH823njj8p6EMeU3+3/z04VfQqr7HIi++Q+TPF8InhMnTizrnts2kLpH3EAgEAgEAoFAYKQgMFO7G4LQIG5Ioy/hjBkzJv34xz9OvmCCNFbLIwB873vfS0sttdRUb7bFbMEd+3/84x9P3/rWt0qb9s9//vPJhdfXvva1ycbukiTSJi4/BFgmCy64YHkREWGmIUQ6EYPNN9+8tPlHasXjkGVaw80226wkR3vuuWepzUXmP/axj9W9LDt27Ni04oorlmYJvm7y7W9/Oy2++OKyKx0tszYjOEg9MwaaThpbwot6s6OGUZmg74+vwghnn46QIT6Enb6g6f5XN+UirQgjTaav2qg7jBBBmmq4IqsIvxOPTJ7hgrC6HyCO8pAighgSheApVHxEGdlCSDnhwqruN7/5TZKnOssP0URUkTAksxq3v/dZZ501ve997yvvWcAhx/vABz6QPv3pT6cpU6YkeMHa3Y+f/vSn5ReAkO8ct/okELo7QiCTThjsP/e5zyXYG3fs2N3tEFbr8hiCdQ7jZ6wZ3wSHlVdeOREiaZNhNXny5DKq+ub7Gl/84heTsepki3DrroDxTIBAxpF+Qpj6jh8/PhnDiDhHMKX1N5Y8s1Cjn909QJj1Cdzhr3AYrrTSSuWnW/3mtPH3v/99eU/hIx/5SGlHz39s3zhWL/1lnjlRMl/VC84EGHdJCHfGrzS1Tt18hWnZZZct54rxp73u5jjlIgAaE8bNRhttlMwJp3PqTJhYdNFF06qrrpr0ozaYq8Yuwck8MS4IpePGjUuEDicQ+oQQRPgwDpxsfPWrX000//JJff+5K6MNhFfY9nnF/4FAIBAIBAKBwKhEYKZ2txqpd4ERQUR6kASf27NB27hry6PBd6G21r+V39IhcJ45PgKLyCExymUrjJAQIIRlwkQbyoRG+eKo3wc/+MGSbNJGIl05z4E81QUhdHkVefb1FoQXgVVWFlaqeSqbNhUJEk8awo/41Xjei6JIiAzhxm8kB+lXHnIkLxeTtRexdDHSyYEvo4iPDDkFQRbhws8lSl8tIpTQEBNWCGq0oYiYfhNGWBM/O6cjSKS84OpEQlxCCmydAuS4jZ5FUST9pS+r8fgh69oLD2QbfgitNjFhqsbP7zAgKEqf/QbyNE6UWcVfv8KpKIpyjCCpY8aMScsss0xpcqY+/ZVBGIOHecEkCE7q56tLzG+Q3je/+c2l8CgPAokxbPwoh0CH2AqDL005AmycIvLvfe97BZXp4VP++P8/sJCHsUErrk8FOUnQTmNFHCcA8tZuwh6BxqdOzQOChjStOvUy75Wl3+QLS2URdJhUMWkzho1bT2Te15EI0T5Rqx3SueRPQBGPYP/Rj360vMQuX/0BJ4KKsZj7ALbK8dUlebRa74g3bAhEQYFAIBAIBALDhEDbiT6tGxLB0erSjA9TWwZUDCLBIbX5yF8GCC0Chnz4PRwOsUHYnXj4ahHTHdpsJKbd5bMRR35qNZ1IKDycCCDtbKYJEI3Kp9lGBBFI2lqOKQZtun5HjhulHy1hSDryzAQFRhwNv36fMGHCgC6YOwF405velGisf/7znyf9hdQ2wtI4om1nCuV0R58RPJBlY0FagiDhgaCnfpyTirXWWisRFMRp1RFsmaMh3EVRTJMMkUfIja9pAuJHIBAIBAKBwChGIJreKQTaTvQ7VdF254vMI9bMJBBV2kdaTQLKmmuumWhr211mf/m99a1vLU0TmNogR0yKmCUg3P2lGax/1g6zma7mgeQj5sg9YkrLXA3v752mlmnGXnvtlarO1220q790o9GfqU0Vo/zupKJVPAiA0rHnR8xhz3wqmyjVy0cf0eg7KWJuRFvvROs973lP+YWsnMapAgFE/lU3ceLEHKWlJ+GZVt/phfdqIlp4wrSTg6p/vAcCgUAgEAgEAoFA+xEYtUQflAg9EyN2z8x22CW71Ee7Lny4HO2ny7JMjdig+2oLm2P3B9pdB/bjiLzyCDc5f1pW5Gy11VYr70Igfe440ETnOLVP5hRsq12IZDqRw+Xj5ADRy36dePZKngQozmVT2vRqvZ2ADQQnNvXIsvsczH5oyNmpu9hazbf2nTmVce1CLoGyKIrENCfHYzbFpIbJVvbLT/2b31t5ElaZ2TBZkmc1jbYSoqv3Wqrh8R4IBAKBQCAQCAQC7UOgLUTf13KQR9WiMfbszyGzbJQRAF/H8GWeTDqRTRrAonj1uJ9JDa12JjFsiYUzM+CHqCJOiKVnLtNvBNQz+/lNe69+8uDPRAbJ9hk+pgzMIFZfffWm38MviqKMo37s0GlWlZXzVZb8/faubp781EFcft75uYzr4q720xW6ugAAABAASURBVHSyea+SMHGqTlp58MuaXHnld2F+C8927MpXHzbPbJd9iUi9+Qnz1RhluyjJ1IPdMxtupx5IPKz1lzz1N8LmYusaa6yRXKBkcoTcOxGhFfZFF4RPPdRBOeotfX9OPGHq48kpK6eVF78cnuPzq3XiwoF/ju/dGOLvxIJpCr96ThrlZkzFMXbkK8yTXw6Xp/j8lCGO/tS35oYL1L6C5B+RcnHXRdx//vOf5b8XQaiSPuPjXT7yk09+8jNWXSjn5w4GYZV/djBRN+k8s786uW/h3oLPdjLboenP4QRAl2j1p9MY48FXfPRrrZlXTpOfxoa6ZyzEz3cH3NlxeqQu4rHdZ9plfEnPT5i0nvw49dfG/OSnDNiI58mPk1bc7KdvXd4lNMNenHCjBoFoaCAQCAQCgUAFgSETfZ9V9GUOxFu+2267bfkFDBu437XOv1TqKyq+PMIe2KbMHAF5R4Ckcwlx7NixCeGgfbTZy8dXQBA/aX0CkUOWfDHE5xR9olB92ELTJvr8IW2nL4Ag9WyHaUFpLZXjUiriIT/OVzpo02n12RAjD8qtdYgwjaWvivjUIlMInwf0GUH5+tINEkmDKx/18/lPF2F9MYRw4x/dYjIkb8TFBUtfWlF37wi5i57Cqw4WtMCINH9fSlGWL91oDzKEULrYy8FQPOFMk9hkO7lwgsEOG77q6fRAf9C2is82G8mj1feFGpiob1EUCUF0eRiJomFG6pD88ePHJ5cqvfviDPMon0EkVMBGu7Q71fyHqKkrjGChHYQQ313XPn1OmICb/LRfFvpeu7xXnfj6FSGWn/jGiji+EKO/EMHsx7/qkHBkmJCpXBdHjSEYiAd7/uzdfdGJHwJubCnP2NUmn4mELZMZ48sXavQVMxp9S7hjSoMIGzMEXnmZT/pDvZULO+HMbZwMbLXVVom5DoHKeDKnjBdY8DMGYQdD9ZEnl+uBaHP8sqNh9/Upl13NAcImIYKmn31/jld9qrcxoQ7q6GSMyQ+BkCDhS1fGqy/uCFM3QiMC7g6MMaStxpG56rfxK71/N4MQbv7A0Ppi/BiPwuVnPpnf5rZ89RklAiHUpzjdFzFmqnWO90AgEAgEAoHRhsDobu+QiX5RFAlRR3hs8vkLIP3B6usuCJrP7n3jG99IfiOUiAzTAlpghER+CAcNO/IoP7brCACtM7KE9Mw///zJt8DlJy3Npa/9qAvtqXQcjSoy7vOBNI78fJHG5whpMtmo04YiF8xmkDpERrxa54s2CDQiof6+JkK7jfgrw2VJaWhP+f3qV79KyuBHS87mmSMw8JPe12uQo6Ioyi+5IKLs5YXXOuQr23v7UolwWNDGwhbJRuj5+6Y7LFzY1O6iKBKS7xObBBtknAkOkveZz3xGktKNGTMmuezpQjUzEWkQVYIIbGAnLTMS+CtDGKctiKeM9If+ReiaXepELJWn/tJyLp0aGz5nScAoiqL8VKvy+IlTz8HD5xrFy+NHPGOHcONZLUdY1SHi6ixe9mcmo35wkz9/9vXK0EZ48COQ8jMmabSRWm03FuAjjIMboUAa9xkIBvxp+PlJRxBAjPUjP7b5xo5y9ScBguCW6+PEDKE29uElTdUxVZM+x6+GERi0r1pHwqBxXI1X+25OKdOcLIqiDDb+zG/5GSvGvTGhL90NKCP1/dEHSLvxWa2TEy3zBma5fHNUfYw/X17qS17+b9yYd4Q4481chOOECRMSoa6MFH8CgUAgEAgEAoFRiMCQiT6SakOtOoQISamHJzKEUCKNtIou5tEiygdRl8aGz5QAySNE8OOQWmREemYmBIJquYhf/pJJ9heftjL/9kSGaGtpPZEtpBqZQlY4pAGZZ6qh3FqnfuqMnCDACDmtt7w5pjHCEW+/Obbv7KS9V528kTzEDCZINfLDryheJU3iZAcv4TkPGCnLpy+znyf8EE7v2Yknn0yGaGqVx6QDsZK38OwIFOP7tPTSi0sgUB48c1+J6wTGJyGFaad+4s/pK+mzy4RVWHbwrK0rXPVnTuepTcaW9+wIdTmf/FS3arnGgP4Urg36Rd7GIr9ah5Tn/D0Jg9rsPTtjCObwy35ONoqiKL8pL41ysjCnDAIgHMWHuT7mT6gi0PLnnKYQNGDpd3YILIE158Ff/2QiDAt+2SHWRTHtGJJHdU4pv+oQaAK3sc28pr95LI16G7O5vPyEsXBkv5qfz87CQBj3yU9+MuU0ntpGOJHe7+zgqC3mSPbzNJ/0rffsjD1rAzzh4tOcygoXCAQCgUAgEAiMRgSGTPR7FTRknrmIo36mDkwGtIW5js9G+n47G2h+4QKBQKB3EDCXmW0R7giwvVPzqGmXIxDVCwQCgUCg5xAYtUSfNpZmk/aSBpUJxBZbbJGYCriISPvYSJvZcz0dFQ4ERgkCbP7NXXPbadEoaXY0MxAIBAKBQGDYEej+Akct0WdqwkyHvS9TG6Yc/Lyzrc520t3fhVHDQCAQqCLAdMc/2NafaVY1brwHAoFAIBAIBAIjGYFRS/R1KntlttbZvpcNMFts2kDh4QKBTiAQeQYCgUAgEAgEAoFAIDAcCIxqoj8cAEcZgUAgEAgEAoFAEwQiOBAIBAKBjiAQRL8jsEamgUAgEAgEAoFAIBAIBAKBwGARaE+6IPrtwTFyCQQCgUAgEAgEAoFAIBAIBLoKgSD6XdUdUZlAYGgIROpAIBAIBAKBQCAQCAQyAkH0MxLxDAQCgUAgEAgERh4C0aJAIBAYxQgE0R/FnR9NDwQCgUAgEAgEAoFAIBAYuQjUJ/ojt73RskAgEAgEAoFAIBAIBAKBQGBUIBBEf1R0czQyEBg6ApFDIBAIBAKBQCAQCPQWAkH0e6u/oraBQCAQCAQCgUC3IBD1CAQCgS5HIIh+l3dQVC8QCAQCgUAgEAgEAoFAIBAYDALDT/QHU8tIEwgEAoFAIBAIBAKBQCAQCAQCA0IgiP6A4IrIgUAg0AkEIs9AIBAIBAKBQCAQaD8CQfTbj2nkGAgEAoFAIBAIBAJDQyBSBwKBQBsQCKLfBhAji0AgEAgEAoFAIBAIBAKBQKDbEBhZRL/b0I36BAKBQCAQCAQCgUAgEAgEAjMIgSD6Mwj4KDYQCASGB4EoJRAIBAKBQCAQGK0IBNEfrT0f7Q4EAoFAIBAIBEYnAtHqQGDUIBBEf9R0dTQ0EAgEAoFAIBAIBAKBQGA0IRBEv9XejniBQCAQCAQCgUAgEAgEAoFADyEQRL+HOiuqGggEAt2FQNQmEAgEAoFAIBDoZgSC6Hdz70TdAoFAIBAIBAKBQKCXEIi6BgJdhUAQ/a7qjqhMIBAIBAKBQCAQCAQCgUAg0B4Egui3B8eh5RKpA4FAIBAIBAKBQCAQCAQCgTYjEES/zYBGdoFAIBAItAOByCMQCAQCgUAgEBgqAkH0h4pgpA8EAoFAIBAIBAKBQKDzCEQJgcCAEQiiP2DIIkEgEAgEAoFAIBAIBAKBQCDQ/Qi0leg/+OCD6R//+Ef617/+lZ588smOt/75559PJ554Yrr22mtbLuvxxx9Pu+22W1p//fXTX/7yl/Tcc89NTSu/Sy65JO2xxx7p3HPPTS+99NLUsEYv2n3KKaekhx56qFG0GRPWg6VeffXVaeedd07nn39+x2v/7LPPppNOOilNmTKlY2VNnjw5XXfddenll1/uWBmdyPjRRx9N//nPf9Lvf//79Mgjj3SiiKl5mmsXX3xxOv3006f6tfpy//33pz/84Q9pvfXWK9cf8/juu+9OJ5988rCsQ63WM+IFAoFAIBAIBALDjUDbiL6Ndc0110ybbbZZSZyqBLoTjXriiSfShhtuWBLyt771rS0VcdNNN6Xll18+nXbaaelb3/pWOuKII9IBBxxQpr3nnnvS6quvnlZeeeWS2BAIZpqpNXhe//rXpwceeCD9+Mc/Tk8//XSZX/wZHAJXXHFFWnXVVdOvfvWrdOONNw4ukxZTIbJrrLFGScLf9KY3tZhq4NHmnnvu9Mc//jERIgeeesakILT+6Ec/KufYoYce2tFx/eKLL5bzcM8990xjx44dUIMJUJ/61KfS5ZdfntZee+0kD/N6zJgxpfC2wQYbpGeeeWZAeY6GyNHGQCAQCAQCgekReOyxx9Imm2yS3ve+96XFFlssbbHFFgkfnD5m7/i0xmRbaA+yfeSRR6Zx48Z1XHMJdETwPe95T9p2220TItWsioj8OuusU9YN6ZpvvvnSzDPPnBZaaKEy6Vve8pZ09NFHl5r+N7/5zWnRRRdNRVGk7bffPinnrLPOKuPV+zPbbLMlQs4qq6ySVu0jqXfccUe9aOHXAgIf/OAH06RJk5L+eOWVV1pIMbgoWTD74he/mDbaaKM055xzDi6jFlItscQS6Xvf+176zW9+k6688soWUsz4KPPMM0/6+9//XgrGnT6JOPXUUxPh24L6jne8Y5rGO3Wbd9550+GHHz6Nvx933nln+spXvpLe8IY3lIKhdWCWWWZJb3/729Mcc8yRvvvd76bPfvaz6dvf/na69957JQkXCAQCgUAgUB+BUe973333pRVWWCGdffbZCRcpiqI8Lf785z9fKnN7FaCZeq3ijviZ69DoI+6t1J+WnTkO7d/GG2+c3va2t6VFFlkkHXfccSWRyXkw42Au8q53vSuNGTOm9F588cVLTT/BoPRo8OfLX/5y+vjHP57+/Oc/97zJwAsvvJDOPPPM9PDDDzdocW8GOW3673//mxBI5h7D0YpxfQIwUrrpppsmpibNyqTlZj7GLKxZ3F4Ov+uuu9Luu+9eCspjx46drikE7jX7TgqR92og08BddtklSU+IIhh+4AMfSATyj370o1OjOrmTB3PCVjT74jDDe+qpp6bmES+BQCAQCAQCIx8Byt5f/OIXpQkpjsCsF69zGr/vvvv2LAA9R/TZCh911FFp2WWXnUrGG6GPsB544IFp7733TuPHj0/f/OY3+41+/fXXp8suu6wk/8xxRPzSl76Ufv3rX5dafb+bua9+9avp0ksvTeedd17qpEa6WT2GGk7oodFteDox1EJmUPqbb765lNi/8IUvDGsNPv3pT5dHgPvss09C5BsVDn8nG7feemujaD0dZm7+6U9/Sm984xvTMsssU7ctzHIIzh/60IemhhPczWdmd05kLMRTA+u80MbQ0Fx11VVN56TTQnUaiQJuHWjCKxAIBAKBQOD/EaCoxQucCPOiQPrtb39bmq7ih/x60Q0b0aeZZMO+0EILldr0n/zkJ8kxSRU02rSf/exnpTkNW3q2wdVw7474r7nmmjIPpjf86jmd8rGPfSy9+93vTuytXLYknakDja40F1xwQUICmOYw5znooIPKI39CBCLGXpzWkK1yq/biCy64YJp//vkTYaTTWkFCz8SJE9P73//+0p7s3//+t2al22+/vdSQ0mKWHsP0h807UyeaVfZtuXwmFt/4xjfKS85DqQrzK3bYxtB73/vetMMOO5TYyXixAAAQAElEQVQTsJonzH/4wx+WYwixnjx5cjW4fD/hhBOSutaaiZSB///nhhtuSLks+Lpk7pInkx9mY06G3EsR3digrf/BD35Qmobxq+cQ2lVXXTXRDNx22231ogzZzzwzt+CvH44//vgyT2MZHk6xSo8h/IHDfvvtl5ZccskSZ+YxNOlO23K2SPz+++9fzlN1mdg3TtUth3uax8aI+ZYXVv6c9E7g/vrXv6Z11123vN/A7Elf6Puf/vSnyXgwz5jvqZN09dw73/nO9JrXvCYde+yxSb714gzFz+nCL3/5y3IeGptOGJw4DiXPXk4bdQ8EAoFAoBcRwBdnnXXWaaruNJl59gILLDCNfy/9mKnTlaXVRppcinOkfssttySE2uU52jgkUB1cgGBLSxN+zjnnJGY5bGzZTiMUCAsi4TiFHxti6fpzTHPkQ4u30korlZswYo842OxpCRFCggUNPGJPg0o4QNR9aYQ2f8stt0zse5G0/sqq+hskNntlu9BYDfMOD4RnypQpaUoDx7xDe6WpdfwR2M985jMlqWdqcPDBByeaYvg6wSAErLjiirVJO/Jbfc4444wEZ9pyXzs55JBDyn5WH3XTnsHWh434RRddlNZaa61yXLhU7bSBIIhkZoER3n7Tyupr2mCO7TZJ/bK+0xp5IbvMdoyjWkAQRtpipJ1wQqPOdhwhhbM2EgoRXWPV+DW2fTEGuSNo1OaZfxdFkT784Q+X5ibiZ/92PI3fww47LC211FLJGKTB/uc//5m22mqrhDCrvzEMj6GUBx9zg1mXOekLSe4gmK/u6MDX/DKXxNNH6kW4slBaNNWJsM02H0ledNFFp6mSthCG3HkhUKk/zQrBxXzWt/qTll+Yuw+I/DSZVH4QIpSt/ygTKkFDelVPY+Bzn/tccnGf2R/BAy7G/JAyj8SBQCAQCIwcBHq2JfYYH+ugfO7VRnSc6NtYkWvk2YZYFEV5ycHnE5FR2nabPU29jR+5t6mLS7paeumly6/4rNRH1pEo2moXf+eaa66WMGd6giQiQC7ZygNRsyEjQrSJr3vd66aa5jADkDeNIQ25d3HGjBnTUnk2fFp95gUIfW0ipNhXQbbbbrvUyNGGqmtteoICksiODGlD4LSL1lTd2TsThghNcKpN3+7f6oNAb7PNNqXJE5KsPrSu6vO3v/2tFECYTMFlMOUTEnw+8ZOf/GRpfuUkB9HTjwRG2lTjDKEkYK255pql/T2iri6rrbZaOuaYY9K4ceMSgVJ+7mnMPvvs01RH36g/DPUNDbgIBDKCAYxhz47P2Dz88MPLT8kqn0DgU5TZ5Eu6em7s2LHpta99bXIagBDXizNQP4TTaZUxQXhlauaCKsHaSQPskGPCCyFgoPlX42szQdLdBosfEo2465sdd9yxbJdxT5g3d+Hk5MRx6MILL5yQbfWTp7lMYK8dpy7UTpgwIRnHyhg/fnzZn9JwhEmE/xOf+EQaM2YMr4ZOm/W3UxxrTsPILQYSaCZPnlxe9LVm+dqYdYRSg/bHGtZiVhEtEAgEAoFAoAsRsEf7HDsuYT/rwiq2VKWOE32bK6LNPKZKrGjcaehcOGTGYANGWPKlVwQbMUQGkDOtoQVkO2tDbaTBEze7008/vbSL1knSIdm0jcgg4iaeTVs5tH5IPT91oflFmGiJkUv+zVxRFAnZY2ON7NfGR2KYIuy1116pkWMuBIPa9DSqyLM6f+c735kmWHt8XhC2SGqrdZYJUycmH+uss06pNf/+979ffroUgc9+nuosfnbIsfroG+HZ3xPZdwkawYOhtvNvyVUi0ZojUMZLxTvRJCuDVpVWH4EXjjx66jtjiLCXhSb9QvNOm19bH2R44sSJ5ddaCIbGALJpzBgvmZAqk6DBHMapD0KtvFacPiUMGtP6MKdx8kG4hCHnlACRZArld3bwzGnyU7sJJwg1Ap79PZ0g0Kovt9xyJV5FUfAelLPoOamBr7JyJsY7vPTTZZddloxR8x7+2opow04fOB2TDrbmPFIsPb+qM66cEknv3ku1r5gJKYNdv7yr6eq9mwfKUD6BsBqHciFj62neOeGrzgUCkjKr6Ywpp4JOHXyitSiK8iIwczJjope1P9V2xnsgEAgEAqMVAQo0PM6pvr2qV3HoONFnToGEIflF8T+SQavJxAXxsmkjcYg4jR8wEQFkCDHi+A3U2dRpeWl1szaXNpGpgBOCTBLYXTtRIAyIqxzkCdGiTaSV5NcNDrlkGsDEiGCS6wRD2la4GpRZYMrhzZ6Imy/CsHfmaGl9Xgrh9Ds75lbVvNhN05bDDqnOYerDlINAJq+Maw4fyFNfII7GUDUdsu4LScYQEqoOwhF/T37S0frSPPPrz4mL0COUhD2mJggbAu3kwOlEHi/y+shHPlIS2v7yG6i/vvTvQmScmZQh6Yh79vP0bz3U5q29F154YTKmYZLDCV9OKMwz/0AcE6YcNpgnokzg0qcZC/kg0jTY/C2K5ithiIAPV6c+0sLWyYg0zZx+Y360dN+JnrUhx5c/W3vj1TeOCQI5bDBP/QjX7GjmCcq1c8H6kfMnoBFonPS4c2EOMDHafPPNE2FNXtayHD+e7UMgcgoEAoFAYDgQcPeOIpqyjXJrOMrsVBkdJ/o2YqTdZ/A8c0OKoii/Y4+QApEdPi0y7SMiy7SGpt+Gy7Y49f1XFEVCFmy0yEOfV8P/He8jGwirC3k0dey7mRHQMEpMc4io0uayIS+KV4URhFr5TE60QdxWnfpJw9WmUW+mDUhCI4fcqlttep8WlT+CgtQL95tdPHMf5hs+CVoUr7ZDHsxE4I98i1/PIdHMG5iWcIgUsgInv7NjSlFNrz76VX3EF6Y+NKXs2J0I0LwXxav1Ec5UC5GDhd/NHByRVhrjatyiKMoxRIhALpmP0L6yj3aSQxtPa+zkQ3jq+09eiKk6Vssn7LGxdmLkMiWSSTtLq0wbXpXm1YVmWhpjpy/blv9XrsjqUBT/w0T+yH7GmS07LTQCnf08a/GXl7Yi+GzWtY+ffvdVGvOJdppAxJ9ThzwGtYFfK64oihJvaeGUKv8plyCh3jT5TG+MYeZMzKuMT4KTeShZUbw6l/WBuvKrOuY5TpkcmcIqh5nD5jUhCF7Zv9FTGdqsjlw1Lozhmh1hlSBXnQvaBN+czjxSD+ZaxptTNCdW2ki7X42b08QzEAgEAoFAoCMItD1TH3qwt1vP7QVtL2CYM+w40bdJOmJHmGz8uX02S4TBho280PjZbGlOaaZd9vOP5djocxpkjXYSyWJ+kf3rPeXvwiZShmAQFhBFpKFKEBB/dte0eExM5EVDzNbbpo+kOhngnx3i4JRC3tkvPxEK5SAQ2pX98xOpoTnebpA2+vKRL8KEtKiLr5e4b4AsMt+hRUXgPB090Q7//Oc/T043pG+3gy0iqT7ydnkF+SGU+UqKeuT6EJ4QT3c0aGfFb+ZohznCX7Uv4C9fgg2S6RKueIg5IQMhlMaXlXIZ4rkvQvjRz9lfXsYgrbiTHF/WIXwKp8VmqgFrv40/7WKeYVxLS3AhwAj3dJLlvdZpv/gWD/jUhg/2t3lGKJPeGKOJcH9DOca1tpp/2oCgmlu010ySmA1J18zBznwkNMpfOdIY807f1IGASPAjOLobQdvtVIQQTQil9ZfGWBWXIGZR5Zed8YJIE2SZBOkXYeb0rrvuWgob7vBYD/hrE8ED7n7XOvmpM4WCsVobPtDf2qssY8AJJNM1JjwEXSaAlASw4VrFdqB1iPiBQCAQCAQC7UfAGo47OknmlGCPsYf0t6+L082urUQfceeAkYm4zY92jx/yhJghHci8Td7mT4OG2NOg2hgRIQ5Zcxx+7bXXlhgiCWyjERZpS89+/iDbyAhST9AQDTmWBwKIFNqk1deG7GQBmRNP/sg/O3ebtjrzzw6pYLObCUj295TXlClTkrIQC35Vh9wNxUaf2RGSgdwjMOq59dZbl/8aKPJjQCLaBBiElB2xLwexPadlR8iq9Rnqu/og7DBVHwSNUIFMOzlRH5pZZFlZRVEkBA0Oftc68eGPOJtYwhFYl4v1hTGi72HALKUoiuQCKmLpkqx2mqhIIaEACXP0hmDLS7wlllii/PKNevPj1JeZCE0+4QhZVY77HDS1TGNcapUPsw3ac+PDGDOOnAYY1/LiZwx4r3X6BsmFWxaMauMM9Dcir69pweGnvi7GuqxNGNEv/sEPwqm84QtP9y2khaP2Cqs67Tc/9IUxL8xcJgC5YO8UTHnmJ9M3YU5XzHVY8bMOIMZO1gic6iYfAjchXz+Z8/yy07fwZC5j3GRBgIBCAF9ooYXK+wY5vn7Wb7XzNIdbS8xtpj7t0LbrPxjAxKVjbVAH5l5O1fxWtjlIEPQeLhAIBAKBQKC7EbBmO6W1btuzfDmO88EN/NXe2d0tqF+7thF9GlKX2WzMSDBQkGlkhp27f4QGiAiSDR6IyABNuqohPjZw5gbIVXY0eGy8M+lzMc9mrRwEQtp6DlFAEJBqZF8chJ8trbowz0DukAnad2SANlw8hA0hRoyRdUSTP4fA0YKyXWeDzq/qECYEAMllG14Na8c7jTNCtdNOO5X/RoB/FwBpQ4CRD6ZGhCaSKHKjTJpTJiBFUSS482uX84lPduQ+ceguAztzWl/1Y87jnYac+RS7bqckTGwIXPXqQAOsTYir+xROBqTz9Rj9hijKi9YesfNlJCdB8jK29BWylcePp0mqfgireDTNSD5h0G+O9piAQvuvzrS1NN6eMCWw0kyrj7IJK8a1ujGPQSKNdX0hPY2AcSDvqkOOV1hhhfLLU1X/obybEzTmxjQB01cCnJpwxoGvwhgL+qcoivITnzAz7t25IAAQUKt1QNYJiAQ385YJFgGKWY5+gLV/dVZ5cPva176W2KvDQL5Owow1QoQ+4FwkFg8GyoIjZ55lcszfHCJkmMNwN375M1FSLxgTKPgRRL7+9a8n5ln6nVDDv+qQcPOb1h1Jr4YN5p2QYn5bAwiR1i5HvAR/9XDCROjULxQVBL/BlBNphheBKC0QCARGLwI4pj3TR1golFhdUERz+BVOmPeiXkOpbUQfwaLZtNEiyogOMgQQZAgpoilFOHx72782hmwIpxWk4aWBRMD8zo4AQYtv4xcX0DSpNJTK4VfraARp+ORv40U+xFEPF+XkiRQgZ4gEMxJ23cwcxPOFIMKKzkb+1Y0/Jw6igfB58qs6pBap0JZqumqcobyrL601LTmhg+TpgiZyRdBCXkmkhCGaUvV1YpLLrBKq7FfvKT/f5Uda6oVnPwTZRMj1gTtSru/hA2vkX345TaMnEk9zi3gi5gQ18RE0pBRJNIZo1RFMZkzCjRf9y0wLsfM7OycBTIsQMXG1iYmP0xC/s0Me/cNYyCTNuz4mPGkLG2yEF7HLZRobiCazKTgzC4E9ws00xu+ct6d60Pq6i1LtE2G1Tv+ZQ4Sl2rDa34Q4F4Zp9GHHXAnxVwZhgmTWEwAAEABJREFUxXxDsJ1mSEvIKoqi/Me9CMzaBl9h2RFwCVHGsjnN7ItpjnBzkAAOD+U5nSO8yFc4Zw4h5oTx3A/mNoFBPcWBqz4kTBAi+HEu7CpPH/uikX41FuRH8CJo5zmtLwgyhDmCibjyqDpzEp4E/ZyuGl59NwaY1hFIq/617/LbZJNNEoHUPIO5eaju6uB0iEDpfoJya9PH70AgEAgEAoHuQYBC2NqPe+CW9qunn346efrtvpk9tXtq3HpN2kb0Wy9y+piIOS0hAoE4VmMgA8iODZg/MkF7RrpiTsHPOyGDhhepsLnSDJPCEAFx2uUQZeRIfWpJAwLDHALxaEYU2lWfRvkgIwapgdso3kgIIwgikQhnJrS5XcgXW29jiR+tNCEE0UeC+bXL+SIMARPZq+ZpbCLOyKETrWrYjHrXdoKjU4x21oGw51SJ8FMU0144JmRxuTxCvJMAwoITwOxP2HLR29wmLPiyEEJNwKgVoGj+LdI07Tl9fhLYXKpyCsY8L/t3+klwsRa1KuB2uj6RfyAQCAQCgcDoRKAriD5piSaalj3bnusO9r02cUSNhpEfx1zAxs0+luaPdp9WnqkO8i8fl3qdIojfTsccAyHJ2k15IyLKZWpCCKFN5T+jHVMomNBkE6Y8CVMzul6dKF/7jCHadZpm5h/KQRTdH0A6CT78OGR77bXXTk6WmAPl+MIG6+B7wQUXJEJFNQ+nGsx+1IEQWA2bUe808Yg+MyPCczvrQcuN6NPAEzTl7WSAAO6Ui7afX3ZObQjNhGRzHkF2cqNv9J/TNZoWp3M0/Dmdp7noZIv5jN/ZEW6ddjEhc5rhk6k5rNNP64G7HE45a09KOl125B8IBAKBQCAQCFQR6Aqij8TbkBEAx91siWnx2fQyseCPCOSKe6cVZMLCvpg2lzDAtEM+SL7vhtNW5jTtetIC09bSHtrQ5cu2iz0ykwxlt5s4KWMwjmkJsw4aVqY1sMx3IgaTXzenodFl6oLMu5TMVMe/NeDOBxMtgllR/E+7bAwhf2z3kV4XSofaPtpjAoOTA+YuOT8ma2zWkfxOjMlcTqtP5JiGfNy4ceU/7uY0jHDUavpm8djCb7TRRskdHGPQmHOSgcATgpD9ah409Mydxo4dm5jAFEWRmOg4JnWZmBmUexJOYcy9alpCflEUySkOcp/DnK451fNdeycWtelyvE48mY4ZU7T5BJxOlBF59hYCUdtAIBAIBGYUAl1B9JEu2mcaPISUho6G3MUIBB6prgWoKIrELMeFOLax7Kdo0Wj+6plv1KYf7G+kXlomPOrtnZkOku+CYr26ijMjHHLDdtuXd5w2uDw5o+vHTt0/6EXz7g5Au3DRLlpdZJ9plTHkjgWBD5HMfVUtryiK5EK2y8QurVbDBvNO6CRoMDuBfc7DyQHyKyz7zcgn8xdfwFl55ZWTebfvvvuWOLSrTj7D6cSNJl4/mNO+0kOw6E8IJgC5X7HWWmuV1TCnXHY3pwlrhLJ62nH3NeTpNMUYKBP3/aEc8DUmgkbVvy+o4/8T9ghTTifUreMFRgGBQCAQCAQCvYbAsNW3K4j+sLW2DQW5bPm73/0uMcNoQ3YdzwLJZTeONCFPHS+wSQFOYmhaaTxpcZtE76lgJwlszQl83Vxxdxngn53v7XeLEDJQ3AivLk07BRxo2k7FJ+i4H0QJUU846VS5kW8gEAgEAoFAIFCLQBD9WkTidyDQrQhEvQKBQCAQCAQCgUAgEBgAAkH0BwBWRA0EAoFAIBAIBLoJgahLIBAIBAKNEAii3widCAsEAoFAIBAIBAKBQCAQCAR6B4FpahpEfxo44kcgEAgEAoFAIBAIBAKBQCAwMhAIoj8y+jFaEQgMDYFIHQgEAoFAIBAIBAIjDoEg+iOuS6NBgUAgEAgEAoHA0BGIHAKBQKD3EQii3/t9GC0IBAKBQCAQCAQCgUAgEAgEpkOgzUR/uvzDIxAIBAKBQCAQCAQCgUAgEAgEZgACQfRnAOhRZCAwqhCIxgYCgUAgEAgEAoHADEEgiP4MgT0KDQQCgUAgEAgERi8C0fJAIBAYHgSC6A8PzlFKIBAIBAKBQCAQCAQCgUAgMKwI9BDRH1ZcorBAIBAIBAKBQCAQCAQCgUCgpxEIot/T3ReVDwRGOQLR/EAgEAgEAoFAIBDoF4Eg+v1CEwGBQCAQCAQCgUAg0GsIRH0DgUDgfwgE0f8fFvEWCAQCgUAgEAgEAoFAIBAIjBgEguiXXRl/AoFAIBAIBAKBQCAQCAQCgZGFQBD9kdWf0ZpAIBBoFwKRTyAQCAQCgUAg0OMIBNHv8Q6M6gcCgUAgEAgEAoHA8CAQpQQCvYZAEP1e67GobyAQCAQCgUAgEAgEAoFAINACAkH0WwBpaFEidSAQCAQCgUAgEAgEAoFAIDD8CATRH37Mo8RAIBAY7QhE+wOBQCAQCAQCgWFAIIj+MIAcRQQCgUAgEAgEAoFAINAIgQgLBDqBQBD9TqAaeQYCgUAgEAgEAoFAIBAIBAIzGIEg+jO4A4ZWfKQOBAKBQCAQCAQCgUAgEAgE6iMQRL8+LuEbCAQCgUBvIhC1DgQCgUAgEAgE/h+BIPr/D0Q8AoFAIBAIBAKBQCAQGIkIRJtGLwJB9Edv30fLA4FAIBAIBAKBQCAQCARGMAJB9Edw5w6taZE6EAgEAoFAIBAIBAKBQKCXEQii38u9F3UPBAKBQGA4EYiyAoFAIBAIBHoKgSD6PdVdUdlAIBAIBAKBQCAQCAS6B4GoSXcjMGSi/8gjj6QpU6ZM4+6+++70/PPPd7TlzzzzTDryyCPT+PHj069+9auOlHXmmWemN7/5zekPf/jDgPM/5ZRT0lvf+tY0adKkAacdaQleeeWV9PDDD6f99tsvvfOd70wHHnhgwyZeeuml6f3vf3/aY489GsZrV+Auu+ySPvKRj6Srr766XVkOKJ9HH3007b333um9731vmjx58oDSdmPkl156KV155ZVpyy23TCuvvHLLVTSnDzrooLTCCiukv/71rw3TXXLJJekDH/hA0ncNI3ZhoHXlXe96VzkfXn755SHXcNKkSSUWZ5xxxpDzGi0ZPP744+U69IUvfKFc4z/3uc+lK664IrWjP0Y6hi+88EI677zz0mqrrZZ+/OMfj/TmRvsCgZ5HYMhE/9RTT02bbrppSZQWWmih9PWvfz39/e9/T/fdd19Hwbn55pvTWWedVS44rRR04403pqeffrqVqFPjIPlrrrlmet/73jfVr9WXt7zlLWmNNdZINvRW04zUeDaG2267LR199NHp9ttvTyk1bukb3/jGtOqqq6b3vOc9jSMOIpTAceutt06TcrHFFks2/DFjxkzj36kfL774YonDk08+WRYxZcqUhPwZ04Si0rOH/zzxxBPp+OOPT/vvv3/S9602RfvPPvvsdPHFFzdNMs8886QvfelLSd81jTyMEc4999ympVlXVl999WS9LIqiafxmEawxsJBvNe51112Xnn322apXV7/bM+65556O15EgStlwwQUXlMKWcWp9+sc//jHgPaLjla0U8MADDyRKtIrXsL1aN/Pa7f3CCy9M3HPPPTdsdYiCAoFAYHAIDJnof/nLX05//OMf0+KLL17WYNttt03bbbddWnDBBcvfnfpD4/u1r32tpewtRrTDA10kEU1t++xnP9tSOdVIhINdd901LbfcclXvUfn+mte8Ji2xxBLp85//fEvtf8c73pF23HHH8rSmpQQDiPSf//xnOuFQ/xq3CyywwAByGnzU+++/P9FcP/jgg2Um48aNK7XYc845Z/m71/8QmL7xjW8k/TiQtpjTBOtW0sjbGNF3rcQfjji0xBtvvHHToqwrv/3tb9MyyyyTimLoRN8aA4tFFllkatkI/m677ZYeeuihqX7d/nLIIYeU5LHT9aTwOeCAA8o96vWvf336xCc+kfbaa6/07W9/O80+++ydLn7Q+VOUtCJIDrqAfhI65SC4I/aiECidgCy88MJ+hgsEAoEuR2DIRF/7LI6cd5o2z25yV111VTruuOM6bk7UTW2OukyPwG19pwq/+MUvpg8YZh/ae6Zd1WJnnnnmNNNMM1W94r3HECC8XXPNNV1Ra+ZvJ510UnJ61BUValKJKVOmpMMOOyw99dRTTWIOPZjih5nTLLPMUgpa5t5SSy1VnkrzG3oJ7c/hrrvuSoceemh67LHH2p95kxwpJAiNTkJyVGsV3PLveAYCnUIg8h06Ah1lFrRKFgnOEb6jWWTL0R8tQbPqS3/vvfcmm8Cdd96ZmATUS8PcwQYhjvwthjl/Zf7lL38p7a9p9B0/0ujIRxp+Of9sSiGMYzMsvfz85qTlR3vnHoL08vRbPcTxVHfH0PyzX86PTbbNRniurzTicd7FFa5uVSc+LMWr56SF7x133FHilrEXV31zXtpg4RZfG7K/ePzUT1raZ22BrXyF9+eqeMrT73px5a8v1ZHzzi/HVbZj6tr+UH/+6mrj0xc5TX4qU1iOA0d5G0dbbLFFOYa0S7h2SaeP4CF/v2txz/75Por+rtZNeu2QJw1qHnvyqjp4uwfw85//vNywYSpNNY53dYafPLWHX9Vpt3Bp1bvReJBOfG2Sr7Z414Y8rvnBx9iqV3/hyhEunfFb20YYZxzEg7H2Kr/qEE99KI72qVs1vNV3Y0Sd1CWnkbdy4QJbY1ebc3jtU7vE12bvcJGWX667OvKTXx4veRzwV39Y0Ha6V+A3f3n11y/qBO/ct7CTThpPbfOubHOjtt61v8WBRa6f8W/Nu+GGG5J66zNlwkdb1U/ejfCRl7TicvLPmKg7P2Mw+8kbbvpVeeqkXbmuMOKX85RWnYTrw3/9618J+c5jI49N4XASP5cJI/7Z+a1+8jcG1aGaPsfzhI366W/rmTyVKYzT7tw+dZUf/+yEa2fGDo7Sa5+4fourztJz2gkLa4bf6icuP3E5fa4NwjiYZGy1a++9904EN2XncOnqOfG1U9s8lV+Np+25jcaZPPsbqzDaZJNNEjMw7ZSnulbzU094wFVewoyHXIb65vyVJw84wUhcTh+qqzA4mGPyEMYJ41fFjH+4QCAQaI5Ax4i+SenyJdvR9dZbr9Sob7755mnZZZdNjvWbab5uueWW9Pvf/z79+te/TltvvXX6zne+k370ox/Vtd+1aPzmN78p7azf/e53J+Wx87X4nnPOOSnbZNv8fvnLX6brr7++tHXcZptt0s9+9rMy/7XWWiv95Cc/SRYzsNlY2Gx+5jOfSX/+8595lfcObOaf/vSny0uA//3vf9MPf/jD0jxH3WyiFiJp//nPf5amJy7KSWyBV778Jk6cWJpuSMNsw0KqDeJx0rtgvNVWWyUmJV/84hdLe15mUuqf6yhu1VnAjzjiiKRdjvLlD2ubqI3Pwits6aWXLvGUj0X6T3/6U1nXhRZaqMzOJuRomx0x3PWjNq+zzjpleO0fODs1UTf9AFNxPS3ctfEREPhgQA0AABAASURBVPUYP358ef8B7tdee20ZzSKvPGY+bGdLz74/xpN2wBBR1l+w4d8XXP6PRP/6179OO+ywQ4Id3Iwdm4vLYzYtEQ8++ODSvEzd1JuWX1tzHYw5l3Ph8dOf/jTZxKQ7+eSTS7tw5iUug/KTrzZL893vfjd99atfTbT11U1KPM4GvM8++6RZZ521HJPMwpi5CctOP+2+++7lGGba4bKbTTCHq/POO++cfve73yXjBk7yrN3Mq/H/9re/peWXXz4Zr0wUNtpoo3Ierr/++uWYhvOGG25YajSNscsvvzwnT/A15tVz++23T9r4ve99r2xj3ryNefMZjvrGUx+o69SM+l4QHXPKBVpz4Ctf+Up5Ydcm3hfc8v/IhLYwH4ChhMaxy/nqaVzoN2MfeRRe6xCpww8/PGmvO0byUx/27u6HMFXQh3B26fBjH/tYOv/888tshOlnpgvIF+yF5fGlDua/+VUmqPxBhvbcc8/SVEv5gsx3GlMmOE4FjPMf/OAHSZn6qkqIxK86a9lOO+1Ujkt3loRZ8zL2zAeZCSFqTjX1Iezh861vfaskj6nOf+40bbDBBuU9GfcgrGO5HswgYS8Pa0Ved2Alf/e0Nttss2SeGxvWBycM+t24MCfNN/PGnDDvjDnz4pBDDinN9nJbLrvssnI+W1uUZ95Lr36qbb0wXz71qU8l7TRWmU0aA3l8ipeduOaP38cee2y5DsDcb/uEOprLyrD2WUMvuugiwcmYyeuiscXO3xxdZZVVEsytd8rWbrjDwTqizTfddFPSx8yDxNEW/S5j9YQpzPQN3CdMmJDcIYCfPrafwccYh/HkyZMlnc6552LMmIfqY+xO7Ntv1F1kfaWN/MxT66Q46iy81hnrxrU1CE7GdnWvMkeMYxfv9YE5ZOwpzzhmFmVP1gZ584MXU86jjjqKVzJ/9Im81VteTOCs2yJYEz/60Y8mYcYLv3CBQCDQOgIdI/qq8Pa3v71cAG3MjvqQFosM7ZcN0iIhXq2zSPjSjQXDpLfJ2MwsuDZAi2ZOIw8ag2z3qgy2jBZaC4RF7Pvf/34ZXR5Ij0XGgu3doil/i7qFDJkrI/f9mWuuuUpNRt/r1P/ZcSOHypxvvvnKjcLCjGDblETMx7/a7Tc322yzpde+9rVJWu1i52jhQngtlHljQ1gQ0RNPPDFZ7BAzdXTnAQlx0dnXfORZ61yMJnjYhBEgaT/5yU+WC6Q8pUNAkL6cVl0t+tJU/eaee+6kjTY/bVbXFVdcMUeZ5mmzha2NSF7wRN5tSoihfsgJ8sblqJwAZeMWX73yIq5OMLIBSmdzQmZtRvpfu9Zdd93ysidhUByClI3NRV5CkjgrrbRS+cUk42XVVVcthRtx9ZfwRRdd1M/SZEYbyh99f/SJjdzdAmTkbW97W59vKkm8rwYRopAwBMWmajMzrrXDpii9upaJKn/YrqvbCiusUH5hx+amHpUoJZn84Ac/WJIbF4ThQoARB46EWGPHmFCeL8/YIPsjtNIpFwGw2RoDSAxBDPGDn7sB5pk82QArUzpOfZkMIMPGHkHLnHM6gtyLAztkxpgx7qQ372qP9mklESL4y0uZSC88a7WE8u3PWUvkDWvjSTxrhnJhBhekkx1/Dhen1ulfBBQuyjfG1YUfXIxB7SEQVdO6G0TI0l7+r3vd6xJBiQDttz5FomDtd63Tf4h39jdviqIoBUqEjoBpDBEmCCCEyRy33nOOOeYoNfc5TDrzw284IJhjx44tv+xk7Kmf9RUB6w8fZFQcc+QNb3hDKXhaD+VpDrobYRwZW9YdaxgSS5BTJmEXeSUcEAYQ9Te96U2l8kY/je8T8pE+yhFkGZ7KIUTKgwBrTlvP9bWxqd7mOMHUepMFcOuiOUJgNBeFyVNdp7r/fxFGseHnN7/5zdI2X3vMLX1tnhjbxpA6E0CM1yxY2GeY3olvXbDerdq3tphDBDvCrPGjfDi4uwZHc8i+Y85b1+01uV+tT/YrdYcNYcQXgKyfThCWXHLJREkGP/PWnFGmNtQ665W8PeEFR+2yd4qLpJvT8BZunCLxwuo56zM83GWAkzTwznGtgfrHOmg+W/es1eoqnXGS43qaY+J5z878s98RzuBurdHuHF4URfmFH+uiuZ/94xkIBAKtIdAxom/RRjJVw4KIdI0bNy7xm3/++UtNIsIgvNbRlrLXpHHy9RrEz2JngbSI2iByGosM0kh7QltuI7AYWljzRpDjVp+0CBYswoj8kVkbfybnNmkLSzWNDZrWgp+Lg8oT5+Mf/3iy0NPQFEVRfq7NpxKRe3E5QoHF30JFQwYHm4A22jRyXZFamg4LJdzERyDEtUjLq57THpsYgcDi6s4E0kvIoXncd999E41+URTJol3NQ9yqH+KiPG2SH22+Bd8mXE3nHVGgeUIQaWr0OxzhRFtK80RLJy5XFEUiMCBLhAsbn08wWuht1DCGbbU+cD3ttNNK7Ssc5U/7qX02SJvrMcccUwomNiN1IFTRmjkZMj6UXc8pCz7VMPdMnEQZAzbdHGZDMlZsyJ7GIUIEH32tv2i0bH7wyOkG8nTiBZ8PfehDCRnS/4iAPGjXtIdQqm+QLOTKuCCgZsFI3OzGjh1bfqrUbzg45TAPzUdzC5ZIA80jcug3sik+soGs6VekUJs9CXE2dP1qDmsr4goz2MtD/5hb8uGQNhpQ/YOAi6MucFN3QqV4rTj9DncY5PiIujkAo6J4dQ5aE4yDHKf6hB0Sq00usZqHxqO2cQRv7ZcmE1zvnD6RXt39HoiDCfyraYxp49CYp7nUN0ih/jc3CdvV+NV3ddeOql+9d+sKQkfBUhRFmnfeeUvBtbZtOa11VV9bSwng+iiHwcW4Mm+KoiiFaePWmgcb65v1g8KFAEYJYl3VLn2mTQgfoc+cyfnWPiknnJQQovS5dOYa5YE1EuG2XlhXpYUr/MS39hCg+LfitMmeYZ0z742LD3/4wwmBRfYJH/o8lyWOdQA+hBFlm0/KMq6t7+pC4OVnzJvX8kSy4WFOCDN24UKIgLs2Kcu6RvEjTquOYEX4l4fxSWi0Rttj5KEvzRO4aqM9kHJI2GCcMWJ9sF5Z8/VTFirkr121+dprq37qZo23pugz9Xfik+MYowSXCRMmJHtT9o9nIDBUBEZL+o4RfQBa9D1NeM57URTJYmbx4VLNf455EapM+nJwURTlcTcyY1G2OAgriiJZ0OTpt0WB1ko8Wh5+9RyBwMkCksRUhJaDhrBe3KpfbhOikt+Loii1wvXakyr/FcWrX9iQNtcXLtJxohZFUS5mFvjsJz7CYqMTp56jiXLUabPJeYsnnc3JaUMr7ZOm6pQtP84iXA3zro4EM/GUxY8Tf3yf1k5/Iun8shMvY4fc2LzVHynIcapP/vrS50ptXJxNxaaFJCFCNgnjgMtp5Y2QNMItx619woxwaYNBrrWDho2WStvEJ3QiMQiPOnG0bciuOoszUFfdyHI5xoJ8fJteHyN3yuKQfuTReEfkxOvPVXEw7vQBv1xO7t9cng1bnkhhNU8kB6lDFhB9Qpp5lzXc4ub8vXOETNrbah8iNggNcoD4iDdYp06IJA04oYUQgnASwpvlCQNOPBjQgsLT6Zsn/067oijKi6G087ks/VMURVu+7Y74UQDQvCOltL7wR1ZzefWehD/ziJaWGZf+NuaRO/WThhDgBMJplzGJ5FsTCBfiEwTNy+rYlieSb5zIo9bR6MrD+LOm5XBlUrBYy6wJyshh+q4oiiRPLvs3e5rb9hx7AZxy/KIoyi/yaIM9pzqnzRlleCo3p/Gs9qF2F8Wre5S6C+dn3VSu3/qDcG1OOWWjnNE2YQN1FDqUK04gnL45aazmoSz40aqvvfba5SeqzUlzpRqv1XfzJrerKIoyGbzKlxb/ZKWAExbKGfOO8oGSKWcBU2UVxatlZP94BgKBQHMEZmoeZXhjIBk2FKVmMu+dQ6g8mzkbio3E4tBfXOTQIuh41mZOo4d09Bd/uPxtGggLW17k3IbAhIDG30LYXz1gpR21hMkijATBVV79pR+svzwROBty7QKPgMpX2Z79ORp0goK69hdHfyIn+q3qkHBkHunXdtqx/vIYiL9NheawKIpk87RxPvjggwn5r+ZjQ6rWJ7/TClfjtesd6UFKcjn56WSjSrTbUZ4xp3+rBEe+sHEqp1+F03jyb8XRmuY65yeBgSlUK+kbxUFeaIEJQgiD0w7CSqM09cIILfytH0UxcogFe3MCkFNIZjfWEyRcW/tzsGBKgXgi3rTwyC1Cn9MQ3Jk85f6sPs1NmmtaZGtETtPsKT7ttHi1448WmX+7HMKd9xxmRtV8CS/V3514185///vf5d0q2NGwD5Z4UwYwc3ISaa2gBa+tM0GNaRpTI2Ze+ncgJ2q1+Q31t/FEAGWeZDxS1LknYf0Zat6RPhAIBFLqOqJPS2JzsHkwCal2Ei2OcMf2/ZEaxAPxRB77O9K24VgIXcaiiaLZoF1qRDSr9ejku0WP+YejcHcIaGwtyha/fAxcr3zaD8TEhmwBz3Hg4QiYlo2mOfu361kURbLx0tjapKr52jRh2kyrSkvNVKGqTavmQ/ihubMZVP29014JQzxtVn7zrzpEsvq71Xf1dgRPwLARO0UoimJqcoIhk6Fsq54DjD/9kH+362nMayOtXzVPONOCwaHqP9R388x4ZMZSzQvBR05ozvUN0ofMaXc1XvXdfCbMsRc3/6phhDXtqvoN9B0ZhDlzCXObEI+8MZMYaF7qR7Bk1qD9A03fjfGNEfgwsYAPu21a81YEUmYU1hZClLsViGG1jRQrTIKq645wWmprD1MM5mcEQqRaGOduh5M477UO/tY0+BMuquHGmblgfTemqmGDeVdGoz1HuLlgvtfNf4ieTsRo3ykNmEcy4xpMluYAkygKIk/95rSsmhcFEtNCZm3MkdwxcF/NmKjGG853Y8BcZXLljoJLyUwGmeENZz2irEBgpCLQdUS/KIry6x80p76iQFOdwbdx2ADWXHPN7DXd0+aF7LEXZtZRG4HWm9aAdgoJpfUQxyIpzLtnuzTD8huIQ8wdEyPPLnG5oORSF21HI6JOUCEg0Gy70JTLRMos7EgqMqzNCAxiZRMWj31kLVnl34qTH0Js00XiqmlgrM6NBBQbv42O/ar6VdPnd/7Igs3QPQ2bFY2fjcCFXhuwOrD9pA2j8ZYWFi6befpddUgJolH1q31HTuEOP5phfVKNw8QD6SAounxo7Dn+d9mPfzVuf+9s2+vVr158QgfSwSbYpTj9Z9wSQswNpLteusH6OeKn0WTiZs7kfMxJZTMFIXiba8YTImju5Hie6ufJRhmZQips6Igff0IEUoK4+T1Yh5w7eTEuaKHZ27v74SSmWZ7GfzUOUxSE2JgriqK846A/mRMar8qCt2c1XfXd+KKYqPrNqHdrmTHsjoS+Yzetb11cdlrYrF7WSKeMLlMz40LAq2msx+zx9aOzo/AWAAAQAElEQVTxbM1xQZdAajywlzfGmbXl8mBj7ho/1by8S2OOI6ruKrlsTrAUxhHcKS4IdX4P1RVFkdjOu8NCqQKjnCfzPEKOy/nZr91P80Yfwdb8Rnpze+FWWx58641rfjT6BC+4SVfVipsbxiVtuXXbekmRRMmS+0WaRk599HGjONUwQos5k+e79O5XVONQEpm7xoK9iXBuP8t1tycyr7UO1Z4aV/OJ90CgmxDoproMmehblGhqEBwNQ9psnMwokBF+NkjaJJs+bYNwk7a/BQOhItUzEbDY21QRDQu+C6c2YfmOGTOm/Oyki7vZJMDmYQN2icoCnfr+s7GJy88iQsvBDIimSP40VI4zi6JIPs+m3hYf5M3Cou60ztpEC9KXZbJxWhy1HzG3cSGeNigbhS8q0KKdffbZ5dc0hFusLHpItXgWXaRCfk4vLNQ2OQuhTRVhpEFTH9psm6c8xa91Fm724+zdxXdRlKYU+bbAuzRG+yWeTRLJtcjT6GgzMm2DQJRtpL7igtxohz6zEdWWmX9bzGGLYDN3gdcJJ5yQ2PXaxLKmHtmzmekj7Yah/kAAabLYruY8q0+nM+xWCRPwkI/+RBiZDNgc2Xk6hoYzTTMbexu3fGDiKR/k3RhyCRiW+tDY0rf6EVkXNztklh2zvGoJDkzZKtNIIU7wQw5tZuqQ86h9EkD1ty/VwAJpNk6MG8TX/IC9OWK80JbyQ0Zs0uL5+g6h14YIS6S2KP532pDLtFkiYX4TVoxj81D5sDIHzEN5Gl/GuzGtbBuvuUWAcPIlrpMDAjginYkWjIwb44gJnD4nlBnPnDGoLPMXhuzozXH5Ek591UR/qpe0xppytNkmr+5VBy9CpDmq78QTrs40lfyEG8c+HyiskYMLjaa6mjfqR9NtjZAOacrmLvJzv8dcso4QxjO+xrk2WVPMX2lrnTlvneBv3fRbH7nHoh3mm9MRfaANsDCXnJYheNJVnbjS6j8kDzbCCTuEJ+OESRM/pFX/6EdzGk7mn7BGzjpMKDBPjfnauIRptt/mO823+PrUuqAOnsoxtpFK88l8MQ+MX/mZO+IyOzEvtJfwzgTLWmmNNiasydZFArh1wDzRX/LQHnd9vPfn7EW0xsJPP/30BDPrAIHWnqMeBFdjQl+oC/NOc8+8Nj6lJdgaX+aLOaovrevC7IHGuzjmtTjqZu5ZZ+w14kmj/wjw1iEYGV/WceuUeW+uieu3OeLOkDW7XjvhAU93ifSztVid1M84VS9jyF5JWWC9M3asX/VMfJTLWTftIXA3z/UTbJB3bdBOGHqHkTDv2m0dNha1zZwiDDqdJsj4ehJ8zHGn1xRa9hACon0KLsq3n6iftsOVX7hAIBBoHYEhE33kAIFFvk1Gkx8Zs5iZ8PwsQOLQtNsMbBr8LBz9VRWBYjLBhAVRsEjRtiB8OY2NGMmxoHkib/K1aNiUcjxfrdluu+0Souhymc3GZm2zsIhZUCyEyCqyaKP2RQeLJDtfG5e6Iz0WIm2y8NFC2CyQJlor8VzqRZLhIC/CBi2mzd0iLz9+8qJhY/ohP2nFQ66QRJpwZdmUxWWKoH6csnPbqk/Ez6ZncyQcwWP++ecvPyGX7eWLoii/qS6MLbPNg5acdpqftDYVGwDyyF+9bJDVsqrvyA0CAI9MfpAKpMmmnuMi43B0+UvbHc8ijOzLkakcr95TWmn0G7z0nQ3NBTbx4WdTNr5o32zMyCk/4ZzPivrtkrB22dyNC6TNqYOxjFSIW3XIh/7VN1V/7wQw4824RKqQCIIEDIXXc2yjbZj6xHgxdp988snEn3CGdCKPSKDxYtMzDuSF8CAb+gwONj+CHdIkvNbZTAnh4iJP8LEJGx+wR06dCMhfW2hn4aRONlVjhImbExf9icDCVz/kNtr4kT1j1NhGUOGLsOhj8bWVEGRc6QP1QTYQtzxGzCVk35dPCOvmBrJQ2yb1RxCsI+6fEDCUi+SzbVamuhqT5ktt+trfBBblwJLwaf3y5ZQcD7b6yZqENOlrcwNxQU7UQ1x9ql+sM8aLucC/6pAs+Gi//rVWmBPIPj9POMJff/k6FaJkPUWOqnl5t24RTglMiBuhjT+SbPwTqORrnliPEHLKCs48RMDEb+YIOkinOVMb19w1Jo17ygOYO1U0Boxdc5OwYW4YX8aUuolr7smPMGC8mOf6wwkkf/cKrD/WKeu/vreXZMytAYQWbSTwiytdf87cysQWqYe19Vt8eVpjjEeCqjVbv1MoCCdI6hdlGcv6hEDGZE6/0pALk4e05rBxZfzra+uLOaa/xSuKovxHwsxxY08fGTvGs5Nca5L2K9vFafiom9NuJyz8q844ldZ+qE+UIV9KFHPKPmc/0BfGsbGjnjAznqt5Vd/1jb3B2NG35qj9WB8ZX+YzQUbblGHuwAb51ybri/rqQ3NGGu2TjgJFnezLxjtFhv4wh3EK9TCnrffGjn2RX7hAIBBoHYEhE30bGqJRdciTiWvDzP42ATaI+Xd+NqoqzTOSJa6FwQZQG9/i6jvXFnAub4zVeDZcG7DFOy8eBAF1suFZmGialaHuFkmkS7nZIRGIXP7tSTtR2yYLrfyEZ2dxtNDm354WcMTAe3YuyNHoI9W0SNnfpsn5bSOnvau2r/qOdNHmaKu62GS0rRoHcbAJaLuNXrh2IDA0QjZ1ZWVns6u3wVfztGHbpJEBGzrNlA2iGse7TR4eFnIbjQ0mE0bhVacfqr8JdvpIvWjyaQ+r4fJBXrWbcKjPasNtNMJsmIiBvKrOhlpN491FUZuc93pOOfJE+BEu9agXL/s5nrahaYu+0F/VOmgbc6Cqn3xz+vHjx5f/YJtwY6jR5meciZedDVPb829PY00/ELz95gh8iIMy1RfJ0K82fKS/9vTFGDIPEWz5wQyRNx+r9TO+9IEykBCbuDI4mlRlCOPMN0KksKoj/AvPDmFAIhBHefK3FiAG9dJX8/JO2LE+KFv7kA/+2ckD5gRSxN4YtjYhgEhXjgcn4drv3kL2rz6RLvXLzvqJcOffnsgnUu49O/PUWKnm5R35zXE8c330B/ytA8autMaZcSeeOWKNQ8Ll08zpQ0SYMqFeXOswIRSG6q//4ZbjSmcM2xPMfUKTk9YcTlBDeKUnIGR/T0KLdUW9tak67wlz/LMjgErTn7Pm57j5mU/8pLH22QOE0ZzTSPPnkFhzXBinn+EMw5yGvzZY781Nv7OzFiPh+beneHASFzbWZX2F5Ft3x44dq+jy32CxzlizzZPSs84fa64+t7Zaj9XP2uSztvqAwG3dMZaVr6/gWyerqV7WSXuDfCihkHdps9Nep3r5tydBzr4rE+MGbpQBFHHmj/0B1trut31evaU1Rs0vabmiKJJ+M37E5xcuEAgEWkdgyES/9aIiZisI0Lj6MoaNFQFBsC3enEWbxsezlbx6OQ5BzAbQy22IugcCgUAgEAgEAoFAINBOBAaaVxD9gSLW4fguvrF5pLWh5aFZpR2hLaM18rUMGpYOV2PYs6dNprFnAsDsiQbVEe+wVyQKHBUIsCVmM84Gnu03Mz2naaOi8dHIQCAQCAQCgVGDQBD9LutqJhTsQB3xs/104RABcWzsaJOJQpdVuS3VYRfO5IldtgyZnDjO9x5uqAhE+loE2Fuz82c24+SIjbU7NLXx4ncgEAgEAoFAINDLCATR77LeK4pXP+fHJpo9JptFtppIsMtjXVbdtlXHBelsN8o+mZ1q2zKPjAKBGgQIzuZWdu7HOE2riRY/A4GRi0C0LBAIBEYFAkH0R0U3RyMDgUAgEAgEAoFAIBAIBEYbAgMh+qMNm2hvIBAIBAKBQCAQCAQCgUAg0LMIBNHv2a6LigcC3YBA1CEQCAQCgUAgEAgEuhWBIPrd2jNRr0AgEAgEAoFAoBcRiDoHAoFA1yAQRL9ruiIqEggEAoFAIBAIBAKBQCAQCLQPgW4h+u1rUeQUCAQCgUAgEAgEAoFAIBAIBAIpiH4MgkAgEOhSBKJagUAgEAgEAoFAIDAUBILoDwW9SBsIBAKBQCAQCAQCw4dAlBQIBAIDQiCI/oDgisiBQCAQCAQCgUAgEAgEAoFAbyAwGoh+b/RE1DIQCAQCgUAgEAgEAoFAIBBoIwJB9NsIZmQVCAQCvYJA1DMQCAQCgUAgEBj5CATRH/l9HC0MBAKBQCAQCAQCgWYIRHggMAIRCKI/Ajs1mhQIBAKBQCAQCAQCgUAgEAgE0R/aGIjUgUAgEAgEAoFAIBAIBAKBQFciEES/K7slKhUIBAK9i0DUPBAIBAKBQCAQ6A4Eguh3Rz9ELQKBQCAQCAQCgUBgpCIQ7QoEZhACQfRnEPBRbCAQCAQCgUAgEAgEAoFAINBJBILodxLdoeUdqQOBQCAQCAQCgUAgEAgEAoFBIxBEf9DQRcJAIBAIBIYbgSgvEAgEAoFAIBBoHYEg+q1jFTEDgUAgEAgEAoFAIBDoLgSiNoFAAwSC6DcAJ4ICgUAgEAgEAoFAIBAIBAKBXkUgiH6v9tzQ6h2pA4FAIBAIBAKBQCAQCARGOAJB9Ed4B0fzAoFAIBBoDYGIFQgEAoFAIDDSEAiiP9J6NNoTCAQCgUAgEAgEAoFAOxCIPHoegSD6Pd+F0YBAIBAIBAKBQCAQCAQCgUBgegSC6E+PSfgMDYGmqR999NE0ZcqUIbv77ruvaVkRYWQj8Mwzzwx5HE3pG4t33XVXeu6550Y2WD3euueffz7deeedQ+7v2267LT3xxBM9jkZUPxAIBAKB1hAIot8aThGrTQi88sor6bjjjksf+9jH0kILLVS6L3zhC2mbbbZJ2223XVM3ceLEtPbaa6fFFlssrbnmmunFF19sU80im15E4Oabb07GTx5LSy+9dPrFL37RdBzlsbbJJpukD33oQ+kTn/hEuvDCC3sRgh6p89Cref/996cf/OAH5Zqhv8eNG5d+/OMft9zXW2yxRdnPiyyySPr73/+eXn755aFXKnIIBAKBQKDLEQii3+UdNNKqVxRF+uIXv5h++MMfprnmmqts3ute97q07rrrpj333DPttddeDd2kSZPSv/71r5Lsv/TSS+nZZ58t84g/oxOB97///WmXXXZJ73znO6cCsPzyy6d//OMfDcdRdZzttNNO6Q1veEN66qmnEkF0akbx0lUIvO1tbyv7+iMf+cjUei288MLpb3/7W8t9jeC/+93vTo8//niyfkzNKF4CgUBg+BGIEocFga4h+g899FD69a9/ncaPH5+uvvrqjjf+yiuvTL/73e9aKseGcMwxx5Sav+WWWy5JW5vw4YcfTkcddVTaaKONyo3nhRdeKKMwB/jvf/9bHjmXHvEnzTnnnCXR//KXv1yicdFFF6Vtt902OVIvPZr8sbn/5Cc/STR6TaIOezAzkA022CBtvvnmyZjodAWMS6S1lXKMxd/85jfpXe96V9p0002TOVeb7vbbby8FLuP44osvnhp81VVXJWWZC1M9u+Rl2ENLdgAAEABJREFUhRVWSFtttVWaZ555EnMu2vojjzyypdoh+N/61rcSN+uss7aUZkZE0i9/+ctfSoLa6fKffPLJdOCBB6Z77rmn00UNOH9j95///Gd6z3vekx577LH05z//ORHUWsmIQuGzn/1sss9Yg1pJMyPiOKXcd9990/nnn9/W4pk+wY5QvNZaa5XrrXlyxhlntLWcyCwQCAS6C4GZOl0dGtfJkyc3JD0W7B133DHtsMMOJYm2IHWqXhbRE044odT4ESqalYOw0zRzBx10UPrgBz+YDjnkkGlMRjK5QxZomxdccMGUSYPna1/72rT11lsnhLZZeaMlfMyYMen3v/99YmpRFEU6/fTT08SJExOb6wYYTA16+9vfnj784Q9P/d3plxtvvDFdcMEFDYshqKy22mrJZnrHHXd01DTgkUceSX/4wx9KM6iVVlqpYb0EMnuYMGFCuvvuu9PRRx+dHnjggekEavNixRVXLIXVa665Jr3xjW+UtHTG9Nlnn51+9KMfdR0BNMe++c1vJu2bffbZyzb+6le/SpdccklqRUM/xxxzJFpipL9s7DD9ueyyy8o6NipO/S+99NJyrjBXUddG8dsRBkP5/OxnP0tXXHGF165yTnH071vf+tZkr3Cigxhb25tVtCiK9NGPfrQ0/2kWt13h9pBTTz01Pfjggw2z1NfuIGy22WbJfH3ve9/bMP5AAp1g2IPOOeecRIDXx2eddVapvLIOW0vEGUiewxn33HPPTZ/5zGfKNYlCDVYDLd+aR8Cxrs0000zlKd7YsWPLsTC270lRYC059thjp8la/91yyy1p9913T5/73OfK+AROeRGSxP/rX/9apjFXCVLmqT3usMMOa7gGGbP//ve/S74w//zzp5/+9Kdx0lQiOWP/2F/t4RQsFHa9bubXcaIPLIuICdDf5Jx77rlLkj9+/PiO966Fbv/990/rr79+WnLJJZuWl+NvuOGGaYEFFihNBGj1Z5lllqlpLRLyZH5iclsEBDqZIBQstdRS6atf/WqyOV133XWCwvUhgFjBh5Zt5plnThY8wl4rG44FmUbfsy+rjv5vMT7ttNPSn/70p9K8o7/C3vGOd6STTjqp3Aj6i9MOfyYmBEoC8h//+Mf0lre8pWG24jNvsLkRqG1CxiTiWE2oH4xZ41tbjGXhCIH5u+WWW5ZzgA38vffeK6hrXBam11tvvfSa17ymFKqNJZdsm1USLtr75je/uVnUtoU7XTn88MPTbrvt1tD8zEkKAZgAiWRU1522VaYmI2U4bVtllVXKuzM33HBDTYwZ+1N/wcIp4LzzzpueeuqpZFxTFrRy4mS/QaLlMxwtMVd23XXX8g5II8JgrBKuPvCBD5Qnbtm0MdfRXoo43nbbbdmrpacyDz744HT99dcn+VszlcExhyIkITTW31YVLS0V3KZI6r333nun+eabL9lrrcMUiAPN3ljZb7/90m9/+9v0+te/vuQcN910U7r11luTMa79n/zkJ8vTopz3lClTSoXKd77znVJQM1/FpwhhfmqNMVfynr/EEkuka6+9tjRPJYQiiTmv2qd+oVzZeOONyztnBAanU/bC2rjxe/gQOL1P6Ugo/vrXv14qIgl0Z5555vBVoAMldZzos6lGfoBnc+uvDRYfEnV/4e3wp8385S9/mVZdddX0vve9r2mWvswgvnotvvjiiRaEtuXTn/70dGlJgDblfMlUhOOPPz4xMbGI0kZYWP2mWRAeLiVaOYsl4gkPGyLtSCsLuT6ZbbbZJOuoY8JweB8p4y6//PKGZRkjiETDSEMMdKRvo6HFbmVTIFweccQRySbGfMFpiM2Flr62KsiE9tJwZ6LhhGKPPfYoT1s22WSTUotq4+02UkAw2W677UozHO1iarTVVlu19IUV45ArikLSjjt9YmN3SogY1CuQBnhi3ynX5z//+eTeQb04nfIzrpSLECOH9cy8OlV2K/maZ9/4xjeS9Vh8RE3fu5ztdyNnr3EqoI2N4rUrjFB+8sknJ8qC/uYM/3322SeZmz42UK9swrbxXM90tF787Ge/cSLtNJqyitkS0z2/xfHbWuLU4bzzzuPVNY4ZGUWDfmai2A6zK2uctcLYJtRqLOWAC/lIHaGfn7FEuUFJ4snR1gsTf9lll00UgAQQH4fgz+U9CdF/9NFHedV11vCdd965NMdTNn4wXMJn3QqNNM9BtIfgZ3/9yle+MtUskLLXOowPDiLLrkjSUaJvc2CuglAwF0C0Z1SrTTqSvEX+U5/6VGplQvk6jIWPNt5xX6O626w5C4VFQFzaRYOElK9cWjnHpoiT40BxRppDCLmBtAthpyU2Tmx4ToBoXroFoyl9Wh2Ch03Bwux9IO1rZ9ynn366PFmwKSAFreRNm4fg09Q3G/eEcu0jsGYi5C6LkwMaMZpz5j3unbRqGtNKHRvFoRUzd1shOE6JjCWnE8bPAQccUJLBblqkaZ1pKfWJdcnFYc8qBk6R/vOf/5Qmj9af3BfVOJ1+t44p2xqoLurU6TLlT9BHer03cvBzl4Q5Ge2otfZ73/teqXltlG44w4xdZic00bS3lD615Tvpti9Mnjw5felLX0rWmdo4flMwIeP2L79bdeaAepgTBKR66RBY8xuRtsbUi9NuP9yA5rRRvk4fv/a1r5X3iuyhCy20UMpEulG6/sKsbcYzMu+eRzWesox35SDo1j3roQvcsKtXLmHBV7+Y3eS8mF1R/DktYfKjf3NYfjqNpfzMYU7PlJvDO/FkhucUrHat6URZvZqn/dEa4t4X3sYc23xzitaKpUG3trtjRN/C60KXicORlGgkBgqEQUkTQsJyCdPksbgjX3mSOCmgPWfvbUHVQTYKk0wH2eTZPsrHhHJs11895EmTZoJP7NOm0c4iVBaInEbb5GnRlr9JbTGnJaB5s5FbLBENm2VeuC0sNEmOgZSR8xuup7Y5HnZKASNY+VydhUl7JkyYUJ50aNdg62QycANJj8SsvPLK5QVWG1G+UGnjG0g+1bjaanOjeaZ50VZjSH8ZU4irRZqpyv+nq/vQlzYGF2x9ls/ibCzXjdyPp7oQemmkfMrRJmMc0LIxq8nJLP4uXPoqiDHHPMHibKwTktUb2TWuadyNrZy29mlO6GvH0TYqZcJZXXJcbVMv+dPiG8eEAnWz8Ru/NGrS2OQsgtKOGzeuvH/gc5TmAr9OOvVUN21qpRxtRSBo2aS1FrDjNidbSV8vjrQnnnhieSSPbBCaKALkj6TpVwS1FTKsLbSKTlWQK3a+flfLNXZpMp3CEF6qYbXv5q70+tE4USdYmdf6V3x9qC/NbePMb/2L0Jhv3tXdOw2wcOnMEeNRXdSJX6ed9UObWinHeuFE0Je8xLdm0IgPZX2Fn5M72lpzXvvZsasTbAjBNODN8DA3Dj300LT66qsnCiAmH4Rj9aw68cwl/Tx27NhqUPku3P6jT+0l5j2FiL7lRFJn9bG+6UNrBZMhppH2MeZ99jLxxK91Tu/sCbTM1pja8E781iZ1bpS3NceJgzja73TE+C2KwZ280dLDmtluJufWU+NGWci+sghUBCR7IgFLGP9aZ138+Mc/Po3i0B5BEWMddbcrz6Wc1m91sPbr20UXXbS8K5HDO/WEn/Gi/FbKMIZwNiZK2mJPcnoBE+tGK3n0Whz7nnmS622+WI+Qfadh2b/Xnh0j+ogDEoXk0wCaVIi/yT0QkCyUNOC0dAiWo26LsMHnt45gluAbyY7WTGRHzd5JZWzeHMXYjG18Nq5G5dvw2EEiXDZPWiOLpcVAOvUnBNB8+Pb79ttvX9rZ8rP5k8oROHWwwPvOs0VZWtpQm4ZjZkf3rU44GwxBZtKkSWlSE+dUQVm1TrtOOeWUUmNkgWE2oB6ED23VN3CyoZnQtemH4zdJ+uc//3l54QohYeZk4xlo2RZPBJldJXJm/BgrNEOOgLUTof3ud79b2kY2yh+eCBLSzeTLAud0Cp6N0lXDEDu42uhdaNUmJMLYsQlbSDgXsZguMRFiBsbu0+ZrHLkIhsQZizYd86laRu27uPqVJhZJNZbNJfPFuEMCCEFsm80twh/NsnnCzExdCUNMdZTvDgoiqBwCrcWQ4JzHNv9ucssss0yCLVKu/YQdfZ7bMJC6InfWEbbB5rO1wNdeXAqkmbcWmEeUCIhYs7z1v7WAlpDwqW+QA30jrf4xXpEERJNfPQd7647y9aMxNX78+KSdTp7kj5Aas/obHkgFTaU2sDeeMGFCEoeQoD36ngCCFChTPW1+6mxtVTf+3eQQQe0nFMEfJsh/MxJZrw3Wd6eJMGDacumll5b3PZBL8x52xoN50eyUF+G2B1p37IGUVOavfquWbXwS9gh9BJdqWK6PvtNP7oGpB82svVV9rHcECEI9cyZrlfXP/LYXqbs1zPy3FlXzz++UAIiM+aGOeSzm8Bn9NB6tZdrjLk0tTq3UD07WLBgg4vZqPIVpDuxzHvqHUsbe74SlKPoXKigV9G9Oq57ws1cYH/qvdq9wCd+HHcxt6zRBgpCX8+iGJ5KPa7FKMA8ou4wpH37AHezP3VDPTtXB+M97oHFir+5UWcORb0eIPpAco/oqCkLAHp4GElm18LXaMJOAGYcNy8Qsile/mODThfJhImJAsn+0SCHaFixPX1ZgW28hpGU3SEnfzEMalU9bYnATHNQdMZQH7aCyaO2QNvWxUSIQ4smfpkfeBobJbPG1UFgw+HM0fzYKJBtO/DrtLHBIviNu5bPzpOHRVv/olCNUi52Nw4bU6fr0l7/6wN0mSrNCs4SsIxj9pannjyQRtOCLkBHuEACLlEXepWj22GussUa95FP99DeCazwhE7SGNBo+SYc4TY3Y5IX2BlGCNeJkPNA6usSFjMsP8UL2ED9jjYbNsaGxRYNOQ23jsFEh+c02BgQXebfxi+8dtnCg6UccJk+enITb1IwJm49NycmYecQhBwiT+Wtca6r6EwaNeWH8us2pO1M5cxVuNnSLtQ1rIHW1cSP51i52zWxpi6IoT76QAwSTUOZkzJxqlrf8aAutjcY4/I17+Rub0puvxjACCGd+tQ5xM2cJgE6sCIjWKWNeXvrfCajTQ785BMl4M47hgyyZ+9phPMMIydHG3NfKZVon3DxUN37d5IqiSDSO+slcN4ad4iC+iFardUVyaYzNBev2t7/97aSPzEVrO+JDIUIwJoA3yhdO5pN6mcMUPIRP67DxUk1rDhEY7WHGQjXMu33LXkgY0NcEbWNDPuYlf5papwZORpEw9abs8tEJc55SinCgr+VZzxFEzG3rAmVQvTgzyk8bCdrGcLM9vL86Eni1TThheJ111kkcxU91njkVcUKv78wh8Vt1lIn2DcKxcWPeKDenN4cocuy1wvQjop/Du+VJ8USB6uTDHmz/0x57s/2CYqNb6tqJeuh/ShBrirllLk9TTo/96AjRR2QtNgg6PN70pjclx1u0QTYmmx3/Zs6kNDEs3rSY4o8YNuMAABAASURBVHvaeCycNO8mls2J1ttCLY4NzOJq4xRmsbeJFUVRXqgVp5GzWSLpFj0arhyXhhNhQsAQMoNffZA/i7SFQbk0KoiYyVBLnE0W7VcfG1LOu9GTqRGSauA1c7CqzctGQhsCD4u//HIcmwZ8kCET2qaQw2bE00bHTAYpVhdExHhqtS7GGI2XxRtW2pXT6i+kl5BFmNNnOaze00ZqwxvfpyUVTmBdYYUVyi80INzGCf9mjoZRu8yDHBfhRyaMAURfHxm/tIA5jrrb5C004nkaN/KqErEcv/ZpnMGCFrc6LpwcOKkgxFrI4WwcqJO55SSBsGHO2rRclK6mzyTReEJAasvtlt/qidSy70d8rCU28YHUzziiRUTSKA/Md+n1AdIEX+MVEcxhwvtzNgz1QvTFIXjDlzDomNz4Na70M+z1iXhVJw5TGl9LsfEid+LJwxhSH6TPiRh/CgnjhZYasVEeExECrLwcS5tj1jXCpnmjjrlM64V1VF+rW/bvpifsYWp/sQabT+Y5PFqtp/GBTFIQwc8+Im1RFOUpo1NY67C1qYqPOLWO6ZBTEtgKsx9QOKmnfcTc5M/BFRk014Xzy04dCKwIJ5JrP5EPRZN5iiwS+qxLxrj1khCCuBo/9lB9rc9znv09laVd6mOt6S/ecPtro3FuP9VOWA6mDsYEAdoJJYGXMsieTXCwN+Q89Rs+AV/7dfZv5WkOW1ONIcok+cBTWnsJYdEJgLXDfPW0tgjvJmfdcFphPFgj1M3YtF65pG+s8BupzhyiEDT3KLSspZQmvdrethN9g8ICa9FBHgBTFEVJ9A1qkjkhgH8zB2Cakdp4Nh4kzaaDpNBykIwdgYtvEeUQM3HVSdzafPr7bdG1IdNwmLDiWUAtDi7e0AQrl7/FVFyChwWDnyMfRIqgkzHgn91A65PTDeapLIuPQWojt2FU89EftEmOGmFaDWv2TuKnOaw6ghBX9XOk7oSjWX45HCH2aSt1dWJCw5zDmj2RT0fWFk+uGp/Jl2NHBFaYhasaXn03XmhBLWpIkjDxmfsgPTTDNlj+zdzVV19d91vK8Da+jFWbsc1bXyBdxrFNQt7GMRLAj+PXinNKwFQISSe0GgvsTtmWI3PIfM4HATZmLWx5zjgpI2AQXC38OW5+qguc8u92PWlRquMHgXOSxjSm6k9QgV2jcm1U+hBBYu7nFKVR/GqYjZmW3GZPA1clA4g4szBkgElFXg+q6WvfkU4bPfKX46ufjR8xtPHDWz81wtUYZ2YlHxuS8eLkBcl1f4lAUhRFaZZmY1YugmoM5Topw5qgHoiUNPrdqUS9TVx8dfLMebTjSUNe7VPv/lE3WnPv2elD47NRmeaneU2IJ8QwZar2WaO0cKdpddqFVFII5PjCnMLAkaBEyMth/T3tAepjLROnKIpEGET+CFPIJH+uGa4UMU4CnOwhX/Ycgp49j7Mn6VuCCuVEVkIZozST1hXCj7JacfrY3G4lbqtx3JEzT3J/eppTTl68Vx3BOudL8WHOah9iDk8mLzm81ac2Ud4Z6/Yj6609Wx2cqhXF/8xzmMyJb24Wxf/8m5Wln5g+6g97hrlkrOgvzvgiWFiP9Y357vSMQqdZ3gMNtyYw86riSrHklAt+VX/rRm3+RVGUnwQnpIjPIb7GW23ckfjbfmm+MpWeOHFi+Q+e4gO92ta2E32DnebDolQlBzZEE9YAz4tmK6BZZC2a9eISJpSBACAt7FJtgAi5ieVza+KYsBYKC7X61cur6mcxsKkghNJLw37VBugIVF45PpKPOOWN0qKNWCODtA85XvVpA5BXUbS2iCB8BplB18ypd7UsCzYTGPXKmukcbhE1iE1ii4DFKYe18pRG31SdxZir+ulv46GVPMUxRpzWIEAWK36tOiZdNhVH2lXNj6NI48IYIJ2byI3yJKwWRTHdZw0RCOMC0a9u1o3yEqZN6uC91qkLbR2TNCdUxq1xzOwEQWVyZcPIztg2L2rzqf1tI6GZ0+/SIohMPAhO5ox5IY3Fm12pcZZPsKRjfkcziDyJV+uQRPOv1n+ov93TqI4fm+f3v//95OSj6o+EV+divXL1t7bBmOmNeVcvXj0/48hcdiJC2Mpx5OkLKoRXtuCEtRzW6IloGJM0ftV4+ocdrJMfuBfFqyeP5q51pBrXOwwQOnEJbsyHzDEnF9ooDqet1iACH/LCLztCqvpTRCif0JnD6j3zmuVZL3ywfpQm2lN1Th3hWvXzqVQEqVE51jjCFxJMUKj2WaN0wsxNigDKKESQX3a0wE5PaIIRtezf39P8tOY6HTPucjzmHARpc1w9X3zxxTLIHIIroVWfl56VP8z+kHh7DKGTMGL9cZJsTxVV281XfW7N4GcvoPxCPJvNE/Gzsw9YL/LvdjwpzZD6ap8SepH/qp/3vObDyVighLBPwd59A3vyQOtkjbMeSkvozekJXrXjRDnWRnOvXn/ktLVP5FoaXKcoXp3DfttLjC0KRH1YFEUyH81fv/V9bV5D/W0cE5jgmR3FHHM0yqTs58nssFqekw97EIUdc0/rhzROguFXjTsa3p2EEtqMvV5tb9uJPpKMQNoci+J/RNbi4cjTooYYG0zNQKOJsGjabD1r4yMsFj5hCBjp3IImnQtqtFnS8LPQWAwt6Pz6cyR5g9+kzOmlsWjSpmStvfQGv3sCNn5xtVFdHJcithYM8aoONjCwwIhfDevEu4UKIaUJsdHkMpA+mlPkDpGDIyIiXBrEwQLgayWtkErp2uGUjZAjkcjdQPPUT9ISXmx60hPUXLAzjmhQjAUbZ564Nk02m+KJrz+RS/2X8+DPGUs2V5jaWI0X/o0cgiK+TbdePIu9MYF80ciqo3IIOu4YZO0ikmj80TTnutbLjx/S4BSKtkg7+CkfaSAUy4sfhxgRZNWTpoefsQ1Ldwly+fw548GcsJkQUPgNxBln+sPmO5B0g4nLZI3QiABXx38reSFU2mk9gWNOYxzRjDlxQhKsFTZu4QRNWl923sYYP8664PQMyaglUQgbAQvx1mfGr43F+qB86auOIsUYMI4JYkx1KDmYdCAoOa4+lLfN2emo9S+HISXq57TG+Mv+9Z7iIqzWrGr+9eLW+tEIIu1OLGrD2v3b6ZXTANg77RhI/nC2dyFpcM1pCejIjvlpjS+KIpn3wo0PwrkTBKdf/DhtdWptnhXF//ZA/UrbTrtOcIGr+OaQ8WUttv7xqzqnNQQyCgZjJ/c/TbT1QFz1R2TtO/zMUWNRma2Y7chD+dIZU9X1QVgjZw20htBYW3caxW01TF2c4lmHPZ3oWJete7DwdBpEeKjmaX9FSD2r/rCGj9NB7cthsLKvW3vhZU2yd/CHcyOeYn7hCjkvhNhaac9A3s1hJ0rmtfFBoLYPi8/PnLKGFMX/xoiwVhycEXencvBvJU0rcfQ/ZRBc7T/GTlEU5Wd+KZ4oHI1R/eL+GkGmlXx7OY5+Mia4YWlHBwppO9FH4hELk7G2vjQcSKWN3qQzYGrjVH/bhKRhD02rksMspDZX2gB5GHAmmfhMEmiJLNgmmzQ2TBNcXBOeX3/OYqJu6m+DF88GaUAjQhZOfjYAk9fEMABoxMSzsZnEFuWiKJLFQvzsLMgWAwQhb5rSKRP5zvGqT0fqK620UtK2Zk4dq2mLoij/FUAY2CSEIR0mss3fJoxUIhiZ+FrAHBWz2UcoXL6RbjgcTTZtqbJtgAMt00Kq37WpKF5dQNlZI/LytPDaoC3qRVEk7aSps3nre+XRJHE2ar9rnTGsv5FV+NSG1/6mxYM/jbQxmMORbvUhOCAGhCqbDoFVP9PEIQU5vgXHhmfzsRFm/3pP41OfEoAzebc5cMYIjKRD5m3SxjXtrw0PDuaoJ2ICCyRIfM54tdE6Nalqs+WNlIjTn0N2tYv5grnTX7x2+JufNn3CUyZpA8nXvIMTkpfnqrXHxWhrA4IMI/0KPycAhAplFkVR/nsHiIMykWobMuz9rjrEgPmhvnaMDkeKEmSrlrBIp17Iu02YgGAtUUcKBsfr4lgfjRFrItKin/Utgc6YtS7RKDqVU3dp+nPyQX6tc/AQT7uZhcjT73pOmfra+twoXr20A/Wz/lNcaK8yc3+1mo+1UT/AMeOh3U5wrZfmo7bra2uLPkJ2kG32/C7xEqSVh4DZA5F3v6vOuDEnrb3WHOuBOWSfM7Zq54S5rkzh+pF2GKGWP2Em19XYgzdtPu2xcWNPMY70W7UO/b2b0+Y2DK014vGzdnrvzzmdsOdSmBgX/cVr1d88cfeFMO10L/enummXcedLar7SVku0c1/YZ6vlwc16C0drcTXMu9MFpzDCEHRaXPu4C+/qI07VGW9wNmf56zfCvrlonPCTDwWaPc1aae4XRZGsCTATN6/N4nPwVhfvjRxsCPj6vF79GqVtFGZtMN7MA2MszyOnok4OrWPWGXefrOXmRs4PBsOxrufyhuupX81Nd6GGq8x2l9NWoo+o6nxaJMdttJhVZyGkrcyT1WKpQRY75NKgNXBMSE8bHY2cwUdzYoKbsI6kkBI2VBYW+fo6jw2wKIpUFK86k9ACbIEwwceOHVt+eq7RxEDotcFijDSqn0WP4GACkKAdmyNHCCLBwcRGhtQFuZKHsk3YqvZAO/IEl5+8pbFgKLN2cRI+VGeiwsmmhdxboBBKGnukAmElwZvEtAv6gjkSf5jZ4PRLFgKGWp/+0usjWi7aM19HUXZRFP1F79cfYSIg2Jws1NpMy0frZhNE7BFvm7VF2GbJpp9glzO1eegL/Vgdv/ndgqb/5G8zzen40yradDlCnzAnT9plPDAbQrIsiE6DLKBIlLljXqy66qpTx29RFOU7LORr3FpgYUWrLO+UUt2HTQvZp102PkUiYLJLtUkgGgRoT+PYfEPGjGPjlL8xwE+/VEmLdpnf5jKCpF7i2ZwtijYr5dVzBGB9U82vXryh+KmPOer4mXYXmc0YDCRfBAmZ137zlgAKT2QNmTdOKBAIjjZs6xmhwqVBBBDZtkHoL4IlEuF3HkfVJ+KOGFjj9J21iqCJNGpPtd7GuDKseYRY+Rhb+tNcNUZsxsa0PjfukTDkSBnIIZLq3Xio5l37rl+tFdpMCBVunEuPqFpX+NVziA3MjO964e3yM1etYU4cfGXGmjfQvK31BHjzypphHWeCKG/jVR9YQyiy9Ln8jX8mV8i0tZOfPidgwtYc0TdVZ69iGmQc6GukzxwyL/Qd4Us+2dkLrdnGlzVDuPyt6dY58dTN/mkO20/8No/lZ61rBQ/p7EPiGj/y1Xbrk/ob2/zqOcKmsWXPqxc+ED91Vw/YMzNhYlgURZkFQQzO5ph11BoOlzKw748TO1p+c6fvZ/m/tQyGyLaxKg/t4axV2kfTzgJAenO0KIpEKYRz4B9ONc0tafSF9YDwKh2OYt3WJ7gGIowTKNw8M6+Z1PmyjnWRwpJZmXkLawoU2Gq3+hHElcFPHv25CRMmJAriMD4IAAAQAElEQVQHhLy/OIPxt2ZQKsKN0kJ79K0TQzjQ8hu/cNb2XIb6WmPsh9Jm/157utdD8KY0MA5xIX7ab8/vtfbk+raV6Bu0Bp6BYZOt52zApG4TzsKkIgiVgW8zoUFE5k0eYTY0A84ibLI6PkLyLegmuvJsqvK0MJgA2VmAfHHCxkn4oCm1+OW85V/rkBh+LtIi+N4RQnbSymEjbzOgWTUglGESW/C1yeZmcbJwqpOJLg/OwoIU0FCYUPws3DZsi4fFml87XVEUycRkb4d8IvTqieRnjYK2sXe2ISP6FiptsxDBwAJkY2qlXsgJ10rcHMciZ2NVB4sijVIOG+jT5ucCL7MSX7dAsIwZC5TN19iAN4LfX942a5u0+tQbw/LVf8aqhTvng6zrR5I/AmWcaJvNA0lAsJE+ggfy5GncSA8zl6XVUx2rDoFhI2ysWGyMf3MESZC21plXSKiLmghEDid02owQE0+nCTRxSLc6Iw+0OOYVfAgYCIMFHhnJ+cAUzjTKCLQxg7TAlfDjdCLHbcfTeEWukLFW8jNWjW9aNFqvVtLUi2PeW8vMZxs7kucCsHFhfsCM0Ix0SI+EZLKjzsYbLK0FNnkbhw2k3piytukXxAyhULb8rUe1eOov5cLfWGfeZdMlfDjlpPm13hFU1IvwSHEBD2NCf8HSekk5Ik5/zppk3KmLOolnnUesHeMbh/za6YzBXPdm+cLWWEaO9I152SxNvXD95LK2PCgD9Lv54DTTPHGvAkEzZ6UXn79x799WgDfc7S1wUqd6/cyPkGQvgT2CZJ0lUOrX6nqiHHn6AIB9Tv+JY78xJq0r4nCEcv7Iqrlyxx13JOu5tV94M2eNp4Aw760x1ilrlDltz7ZvNctjoOHWEEqQajpCJKHaWmjuVvdP7fWRBiadBHhjvbouVfPJ79YqJE1fMR32Wx9w9kTKCcICYl8dc8pVhtMT2Fq7paFkNPcJAfpcfQkDiK/09jF8RfnmGJNBa7nf5gqzVKc06q7/zV9z3JykzDGvKVlq57z0Q3XqA2/jrVFe2umkX5/jC3gL3mPdk0e9tNYsY8WY0c56cXrBz7izLpqH+trYN5ftub1Q//7q2Faij+RaGFtxpNG8KSKTiBBApTXQLHAqXRRFsvCIL9zEQMItfMIJCTrDYittrUO2SZikawvm2LFjEzJmIZO+1tHYm8hITlG8qkkQRzqDX+cbDBYCi4zFwDGfSSse4ka4sEjJhx+nnupOu8ZUI082GzSzAmRBmLjtdrBSpvJhuMkmmyQkRDkmruNptp1IGz9aPAtj/s2vVYcQcK3GF8+C4oiUAJQvYvFvxVkQEdtqXJumRcdYYMpgXArXpixIGA/86jlCnLStOOM252Hh93m+nA5BLopXx5DybLo53BhH7ovi1XBj2JgyvnL6/JSGEIzUIBiEXEKbxSiXXX3atOVn0za3qmHIAhKMqHkviiIRAIxti1lRvHqJzKZoHBO6jPOch5Md2mMbbsbVWDZfEU+nFITzHL8dT3OLUGUOtpKfOiBQBFiEu5U04hAQaoUnZMlmpy9gRosrLkxs4NYU7/yys2nT3MIDMdNnNnZ5tOIIXzBF5uRhk0Uocv5FUSQYExrkR5BF8rSV4kH/IqnykMaaZJMm9PGzHiBL+rC27uJnBwtjgIaPlldaYdY1axbBQp782unMP3OllTxp25EsGuA8HltJp20Ec4J4jq+vrOUwtR7Bx5wsilf//RZ7DHKa4+cnAY+iinIA2ZO+Fee79rCUj7rDGLE0dvlxTlH0gf3PPkgYJBTCXzhXFEWiCCOEjB8/PtnbEE79jqSK08jBgBBKweNelvFqvTLfEENCDwGiUR6DCaMMQaqqaY1Hp59OdethbZ+CB5OevIdV09e+mz+t9IVLv5mP5DxgIL09JOdhzsFEPcXzJBzmcE/rszD5US6ab36re96XxOPcPyBomFvWUHsXvGEjTTudcqxD2tUoX/1vXcMX1NG4sp40SmfvI2C6NA2zRvl3cxj8cx/ZdwmArcyhbm6Tuk0l+n70oqNlc/xmUtUSU5PHRETatU0cmzapkzbKhuy4yWR0vEfSRoQd1TjylqYdzsLrSI7Ui+AhLjlf5M0Ca2IXxaukL4fNiGdRFInwQasNn07XQRm0HDBBnBotJrV1sVGbjPCtDeul38izzds4yJtCtf7GtUU6kwIbOKHQcbO0hEiLMY2j8URrZfNGFKWt5jWUdwSEFgwhIjiaWzk/xBYZQDYJbsxl1LnqECd1zWk68aRdM9cIzgSYVstQL5o45gqtpukvnj4hNBC0aCH7i9fMn2BKAKMhMz70bbM07QpXlnVVXyLR6pLzdjpBmEQEi6JIyGG1n70TAJDfnKYTT+aTBHdjEvlqdaxbc2jV84nbYOtmf2FGRbvr1K0/wbuV/M0lSinrIDzNtVbSiaM9TvycSBh3+swaIL9aQV/8Wme80lgbr05TcjizDXunNZm2n4JN31YdU7YcP55DQ4DSigCPaMvJyZJxXcXbu1MC4d3krAfG4Uggxd2Ea7vq0vNEnzYFQbcZZTs6pMPCZPEjmVo8M2AWZAszrSS7OnbMFlVHrrTzFllakaJoD+lGQn0Cz6ZES1SrpUD+1X+wR865Xe16FkWRCDk2DJpymmH4taI9GWgdaClpDAhbtGWZyLaSj0UFkVDPeuS4lTy6Jc7ss8+eaPTYBtNkMX8xLoxNhIR2joYTGVBnBIM5Bm07Ux9CKnMKZIxNIQ2wkwYaIvGH4KYmZcJDkEAcaKGYJ+RA4wQZ5VcURbLYsy1nPlR1zF861VfmmY2Rpo9pFbO0omhtDhOK4K0NNLi5XYN5EhisO05gtJXmeDD55DTmHtMDfUyIMWdyWKee+tNYdCHb/RXaumpZ+hQ5pDjh7wSBX9W5c0Q7JrzdTn8xJyDoOp20XrdK8tVFH1k75DOQdNLWc4gZzbt5WS+8VT/rAI0oAdVeRPBvJa12WCsQcqap9jcXVY3Bomg8B5hmOUVF8mkvs2AKI2FMIOXvJMF9i2ofe7d+t1LHiNMYARzE+oMHwFtsfWJvhHPV0TgL7ybHdI4CwP7QTfWKuryKQM8TfRoHmjiSrw2WxtxRtoGXTWxebeqrf4uiSI7QHMFZmG0S8mDO4xhRmldjtucvAoKAEURsBrW52nDUgwYtT/DaOMP528bnGJhm0+kGYchx31AJUG0bEBbCFpMCR6O0g7Vx+vtNMHIiw+TI6UN/8Vrxl5eLi8i1TbKVNO2OgygQMJEqJAtRNY6ZoBgbyHwm+blsG7J+QQKlYdrCnMe32I21dh+fwolJFiKNkOR6eDL1Ilx7VxfP/pxTGGPKvRlCJIGtv7it+suDQAQLbiAE0+ZEkJKOBrMoGhOjRnWCvxNDmmIbNFMfglejNK2EUU4QACk1rCetpBlKHHOTSZ9xVE/AhzVSKV6jNYvJJHLIBpmiw++h1CunNRZh62TLRfLs3+ypvgQECpf//ve/ybxrlqa/cOuj02RCta9vEciYLvQXv1V/c4uZjtOvVoVEawSzR2tCXhdp31spk7kRocKdAelzGvOU8kD/Tj+nc6xXn5QtLgoTDAkHr/p29q/93TxTrnmnNMKJtZyA5KmP+PeCoxHP7WiGt/ZQTFi3mBo7CeA3XM7YoFSxhjs5sv66V2AcmmPDVY8op3UEep7oF0WRaC7dxGfbRsNgE6DtbLSQ0zqSmBFFx+MIpwtrrUPXWkwEjQkFLXm9FC55sYfO2tB6cYbbD57MmcaMGZPY57ZjA6u2wcLg9AV5sRgz3XEEPBDHxhjhYGdezXsw72zl9VGj8TKYfAeSBnHSFmYIxjDHhpdQ2igfWjuCGRMClzKlYcvbKM1gwmj02PBbzGvTEwLhZywjKrXhtb/Vj2AiXW3YYH4jknBDNHzecyDjiLmYUz/acvb4VbIzmLo4SfA9e2kJ9pQI3ofqmEsxh2kF36GWRSuHONLm1suLIMV0C7ktisaCkXWNDTPBoV5eA/VDgpipOR1yEZaZZav9ra/FJayab7UnFQOtS46vjQQOeGS/oTzNMYK68dNqPuanPYwCq2p+0yy9Ox3Wndp42mQPsDY2WxeLokjGubsVzeLWljPY3/rP3lRbd0o1CqB29e1g6zfQdNZCp7Quy7cyx7Uff2E7XxSN5+BA69JKfKbG1gCnluJb8/Q//P0O110IDAvR764md1dtEDWTpJsmSFEUycbBxtNC0m7E2LLSWNOuIWnMBGjGWnU+c0qLgZCwaRxK/RAo7UQCaAiHktdoTWtjMk6QXCdCjXAgWGe8bWrN4jfKK4chbscee2yiyXMxs9VxJB6zuqyNQqyQrJzvQJ8EBZpRY4lzEqO9A82n2+Mjdfrb/GtUV+EEQFggZX43it9KmK+SEGhpFWltnYLpx1YczbsvmxAWmFBSZLRSZr04iLATLm0jtHbT+l2vvgP10x77UivrKyEuz2mCwUDLGkx8ygInmvA37+SBdDrJ4OeOkD7i3wsO0aesYcJZFM2JO1v93H7r1nC20ZqW+zuv4Z4UAPpgOOsSZbWGQBD91nCKWG1CgDY/H+ezRWWyM1hngYuFpU0dM/zZtKVEtuCcE7rBjqOczgZWFM032bZUPDIZMALMQtz9mH/++VPus8E+mSTRig64EpEgEAgEAoEeQyCIfo91WK9XlwaXmVX1ctFg39kIDpcGqddxH6n1Z84y2PFTTefyvsuIQf66d6T4dCVznWq/DeadfTc7fad53dva0VqzaHcgEAi0G4Eg+u1GNPILBAKBQCAQCAQCgUAgEAgEugCBnif6XYBhVCEQCAQCgUAgEAgEAoFAIBDoOgSC6Hddl0SFAoFAYIgIRPJAIBAIBAKBQCAQ6EMgiH4fCPF/IBAIBAKBQCAQCIxkBKJtgcDoRCCI/ujs92h1IBAIBAKBQCAQCAQCgcAIRyCIfoMOjqBAIBAIBAKBQCAQCAQCgUCgVxEIot+rPRf1DgQCgRmBQJQZCAQCgUAgEAj0DAJB9Humq6KigUAgEAgEAoFAINB9CESNAoHuRSCIfvf2TdQsEAgEAoFAIBAIBAKBQCAQGDQCQfQHDd3QEkbqQCAQCAQCgUAgEAgEAoFAoJMIBNHvJLqRdyAQCAQCrSMQMQOBQCAQCAQCgbYiEES/rXBGZoFAIBAIBAKBQCAQCLQLgcgnEBgaAkH0h4ZfpA4EAoFAIBAIBAKBQCAQCAS6EoEg+l3ZLUOrVKQOBAKBQCAQCAQCgUAgEAgEgujHGAgEAoFAYOQjEC0MBAKBQCAQGIUIBNEfhZ0eTQ4EAoFAIBAIBAKB0Y5AtH80IBBEfzT0crQxEAgEAoFAIBAIBAKBQGDUIRBEf9R1+dAaHKkDgUAgEAgEAoFAIBAIBHoDgSD6vdFPUctAIBAIBLoVgahXIBAIBAKBQJciEES/SzsmqhUIBAKBQCAQCAQCgUBvIhC17hYEguh3S09EPQKBQCAQCAQCgUAgEAgEAoE2SHF4FwAAEABJREFUIhBEv41gRlZDQyBSBwKBQCAQCAQCgUAgEAi0D4Eg+u3DMnIKBAKBQCAQaC8CkVsgEAgEAoHAEBAIoj8E8CJpIBAIBAKBQCAQCAQCgcBwIhBlDQSBIPoDQSviBgKBQCAQCAQCgUAgEAgEAj2CQBD9HumoqObQEIjUgUAgEAgEAoFAIBAIjDYEguiPth6P9gYCgUAgEAhAIFwgEAgEAiMegSD6I76Lo4GBQCAQCAQCgUAgEAgEAs0RGHkxguiPvD6NFgUCgUAgEAgEAoFAIBAIBAIpiH4MgqkIXHTRRWmhhRYaslt66aXTKaecMjXfkf7Sa+3bc889h9zHxslaa62Vnn322V5rftS3Awjce++96dvf/nZbxtV2223XgRpGloFAIBAIjE4EguiPzn6v2+oll1wybb755smmPWXKlDTXXHOlU089Nd1yyy3p1ltvberEXWyxxdLtt9+e7rzzzvTSSy/VLSc8ZywCq6yySlpmmWXSHXfckab09fNyyy2XCHmt9LE4f//738uxcd1116XHH398xjYmSu8KBOaff/603nrrlXUxpp566qm0zTbbpOuvv77pumFMXXbZZWnddddNTzzxRLrqqqtGggBZYhF/AoFAIBCY0Qh0HdG/+eabS2I5HMAo65577hmOonqmjPXXXz/94Ac/SHPOOWe64oor0mqrrZZswq00gJb3gAMOSKuvvnqaeeaZW0ky7HGQCgR1OAq+7bbbSoFnOMoaSBnzzjtv2mKLLdKyyy6biqJIhxxySJo4cWJ68MEHW8pmxRVXTLvuumtaZJFFyvQtJRrGSC+//HIpwBx55JElyRyOohFU8+WFF15oWtwrr7xSCtOHH3542n///cv3aiL1v++++9IFF1yQTj/99PTiiy9Wg5Px+8gjj0zj1w0/ll9++bTTTjul+eabLz3wwANp6623LsdWK3Wbe+6505Zbbpm22mqrNNtss7WSZIbEueuuu9Kll17a9rKNiSl9Qrf186CDDirHLQVLK+Op7ZWJDAOBQKBDCMyYbDtO9G1SyNUzzzzTsIUWtKOPPjrttdde6bHHHmsYt12BiM2OO+6YzjzzzK7TPjOJOPbYY9OGG26Y1llnnfS9730vHXHEEe1qer/5zDLLLGnTTTdNtL6zzjprSfa33XbbcuPpN1ElYI455khMOuaZZ56Kb/NX7T3hhBOmae+hhx7aPGFfDAIbDWLfa7//G4cnn3xy2n333dNwkSTl7LDDDunEE0+cjqz1W9FhCvjgBz+Y1G2BBRZI5uY+++yTJk2a1NI8KIoifeQjH0mI3UwzDWwJcQLAdMh4Nq6N74svvrjlVt90003poYceahhffvKfMGFCOu+88xrGbUegdWTvvfcuT0WQ9GZ5Wg8R4muvvTYh+3vssUey/uV0Bx98cDnn4VNvDtxwww2loHXjjTcmBDGn64bnGmusUY4rp4F33313SdwnT57cUtWsN8x/Fl544Zbi50j3339/2m233coTBZhtttlm6ZprrsnBTZ/wfPTRRxvG068EL6dZymsYeYCB+lDeO++8c4LZfvvtl/bd9//Yuxf439KpfuDPo5pGmjqkDLnMCA2RQY1JxRnEuGUKGSFDKnKb6OKSmlG5hQnJFGmQSBeVRKnMyKVJaSTdLzPdr1JJqPif9z7WnH32f9++t9/v+/udNa95zv7uZz/X9axnrc9az9r796qCDy666KLykY98ZMEWd674Rz/60fLGN76xkdvGTZYs27s1eOYzn3kl71vLvvSe97ynt4sPfvCDhXHPWFSPDDAmuuW9731vc1Kk4mWHTo88l84999yiX/ljiS5WXjLfsbL5LCmwbRRYTEsvMXqb76UvfekoUATCKH+CDcgEQpboauEqt7nNbRrlQEm8853vXLj+pirwGgFAQIDjbJ6xU045pRBKAMWm+o12gT8gUEgHJfSmN72pXHDBBbPCNGqt5XrXu165xjWuEc1NXoUKWffXvva15WEPe1jjCbzFLW7ReJ3xxVgDxgcoAU1D5YQQ8ZIBszzZp5122lDRtebHHIADYH+tja/YGIBufXkQhV1Qdueff36x1nOavtrVrlZueMMbFu3MKa/M2972tnLnO9+5OEV73OMeVyhkwB8gn7v/rDWDTXtDyUmDuQFI+GOo3DryARtzAVLPPvvsSW+08jzXDGGnZ+pxbDCwYzxOTB7ykIcUsvPmN795aT9TxvMb3/jGBSiybvK2JRnrgx/84PLkJz+5ORUUxiek533ve9+sITptutGNbjSrrEJA1z3ucY8CiD/hCU9oZAZjkPycC/Zf9KIXlUsvvVRzvQkPvf3tb2+Mifvd737lTne6U2+5ZTMZrtbylre8ZQNygefjjz++4IF3vetdzWnbsm1vut6LX/zi8sAHPrC4mgOjadk+TzjhhEIWXPva1y6vec1rmpMhfMTRZM/QS29+85uPMoqjL/L17ne/e3nd615X7EN1nEwzhskDetQ+U/4mN7lJsY7WnD518ip/KOHdRz7ykYWO4cS63e1uN1Q08/chBZ71rGc1emsrprbkIK6yZL3Z1cRtv+QlL2livdteq2iAEHXkTaA99alPLRTgToV9UEqMCpseGAOwY1y7df3Qhz7UKCvXpz/96eVWt7pV4eHiKQPInv/858/yQKwy/lprA+IYaISidfP7la985SyPL6B/29vedlb4DqX2xEPH9Y76eTlvfetbN/O9z33uU6573euW5z73uaMe+EsuuaS87GUvK294wxsG43p5/JV7zGMeUwCJneIv/Vg7oINnTsjFKuuy7rpAOqV14YUXNnQBLB/0oAcVoBtwGuuv1lrOPPPMcvWrX32sWPPMHn/HO97RhIQBBQzXm93sZk3oD++rtXeaB5g3FQb+oXABAON9//vfP1CqNACTchd+NlhoDQ84KF74wheWAwcONADNadZYs2jqRIn31n4m6xifeLzWemVVYSy11kYWepfCA6DEniKnrnrVq5b73ve+jTFNRtifymxLMr5HPOIRDVA97rjjmlBMexzonxpjrbUwFADdsbJ46vWvf33jqHnsYx9bpFMOOUNuetObNr/ttbe+9a2TJ2neTbEGPOjCr/r6ZIwKbxOS6B0keqNdjqymQ4DBRQ0vTgjr71Torne9a8FLZJl9ca1rXasAz8CtMSrb7nc3f6M/PiZDvOvjFA1t7Illx0Ve0nEcJBxFTgwZtCeddFKxtsC+dSY7og8nuU95ylMaXgPwGRynnnpqOemkkwrDCeBnCNpTYUDapwxohoPx0kHRXvdKNuFl63PWWWeVO9zhDkVb3XJ5v/8oQF6TIc94xjPKNmDDVSi8UaDvyIzFTBFdfPHFpU8IEq6EGMVs460ymWXqElQ8vECOsCEbf5l21lWH54jhAxABAtEuZUOoGStvauTPvYr5BeDmlleOx9baAPs8kQwxXvcpQKbu3CS0gsIwX7G9UQ9fmO/pp59ehuZrHLxxlA4g6WQg6scV7zFQKA7ziPydvFIqlAv+GlMq6xwTxXTppZc2ns6pdnmIAQsgwx5lmABA6wIWgJAjdftbaEZ7PPgScLL/ebfbz9q/7UvGQK21AHHGZ93bZXbyNyVApomxB/AA2qn+eZoZzE41Tj755MHi5KY9AZgwmhVkoAIseMk9IAx4OvUDQte1VtoeSzykxjZWxjNgCDDDW2jlFObZz352E7vv+aqJF5wsIh8YTe328JT+0Rh4bD9r/yYbyDdrd9lllzUvDnd5Ct/RYfYTo5i+aLfhN/49ePBgcYq06PsFQko4Ac4444xy4oknau6oRG7xTDPwlO2O76jCa7qxXujhgwpDTeI34VlOHchnuoIhihZDdebkaxc/M3KA9XYd8sFpClkqn07kHHre855XnnjIWeQ0+PhDJyGetROj+JRDRiCeiHz8Q8eQx0OnENq39l4ov+Y1r1noXrwSbWziesUVVxQnn5toO9tcjAL4gnyFMxaruX2lNwr0WUPA1ZmHPH/i4B19dUlAaXu5yYuBiwrJblvL3lOiFCihPybclm1/bj1Ch9AnVHgtaj3s5aOQfK6SYDrnnHMKgTe3zShHWL3iFa+I29lX4U1Pe9rTCpAm5jxCbCjA2Y0MFDRfwIdX2MlKKFFt88Dz2j784Q8vQ8KVlxMQ4v3nUeqL3SQ4gQzeoU17eAem2XiAeJmAXfHZQ+XWma8fBg5aTrVLcVKSPGKAEUOT193enKo757m4Y/sfKGuvAUNOKM51rnOdyXh/62guQA8+dFTPgJjTf7sMoS1EkJdOvC3wSem3yzBq0U7IiTLi5PXdLsMxIOyJxx2IaD/r+42XzRUIZezweveVk2c8ZCJgaW3kAVK+YkNOupd4r+U7JVBH3qYTmc64mdOPvSnkz/scjBegyQmENZhTf6gMsIs37Xde8LbeICMZ1NaER7fWwzK0ry2hPfhRLLf9AmCRte2ywsys2x3veMdCLrefxW/y6VGPelQTwjK2rlE+rvYFbz5gfe9733sw7Ov2t799894azz6ZGfWXv47XNB4AB32HSgL0aAzsK4P/rAmg7n7ZxFlD/pCXN7jBDZpmOB+0DcTTRzLtR/KU/iC37FPPPesm+oUR1n7O6KbzGRSiCbp1tI8fzBOPMLqdWHTLrfueA8OcFmnXOyMcXvgYHThqvO9mDou0k2WPUIB8hxs4KoSUHXmyN39tDOgTuOJ9ebtY1ACEMJ4umRCT4AYka+0Xyo5Nzj333MJocJTnBVrKmPLE4A94wAMKoKdtR23i8YQgOFLkIffJSB4RdXijAEMv1xBo6hDOQixsmL4xKrMTydE2gOszl8BP9AmkE/KhNCN/J67Atxdzhb1geEAF/Y1z1f4ZVQwYwtv6R3u+NmF9HJnxEkV++wokWivAj6DnVeobE4EHEPLu1drPX5SU41/ASTn8on0KRlgQz2m0rS20kEf5UBLiSClsHiDgwTMvgYXSAwR4pzw3nvY8tuU3EHP++ecXR9MUxFve8pbm84irgjLzE3IDnFtLilOeJAwHzwOAodTld5PxAB2AG4OEEWy/AwXdsmP3YnTVp0zFc5NLlKrYXnss6lpfYFZZvEX2UPR4A6BTjmwxJnu1PSfPukmMp7ED5MZAIXtnJMpp5/73v3/zDXq8xCGCXsL2AE+g/wUveEETpsLLFPV4KIEtY/dJysjfpit5DSiT3ZSn0ArhKKuM0b7ica61FsZjuy3vW+EX+xGIaz9r/8bXThOdkjC8hAm6N8Z2OfqDnALyyML2M6DbCYewH3ouDELryYAkR8hL48FnDB5fMaPPPOMhdipBj6nPiGq3H7/pAqe7HBtkSORvy9V60MPvfve7m7C5VcZljowufANga4susB/8joSuaAdXkN1hcMTz9tXa0WHtPGPlgLSHum0rZw/SQ9oloxgKHIKebVOCschVBql3hQB9fIgm6LhNY91LY6HvneIxsvHYXhp731hnAf2+imN5gLuNgkA8TnYAQEwAABAASURBVLy1Nq5YfUIz6hKqNrEjSxsq8uNKyYlXFLNJSAIMjuh4bABfSpfSEKvpJRwg//GPf3zzx5psXgo6lDlQ7+jTUSNFT/hGP66AGM8QTwaDQN6cJEYXAJhKXrwj0IfaRDPgCrh0jEu5U2Ji1ikBQklC06E2NpXPEOLJ5ykAaoANR6a8Isv2ab4UmzUTygCo2FTmy1ADOO91r3sNxvmLu8cfABgQAUgBZzy/MSagHKCi8Hl1Ij+u6hsDw4+hgebPec5zmi9e4CfC0mkGcE6pEKZiRPEbhcvDetZZZxU8wGNJ6TM6gQNtRz+u2mcoOZY2LnnbloROmdtd7nKXJuSHwhCuZW7LjtU626vAivAcnnJrBuQ4vfKyNbDaBVHt/jgNrCsPMWV7z3ves/nEITrb1+2yQ7+BEfJHW+J2ySMgz3zJJEYOXiSPrJGX7njreYzPOXSKxlgzdoBGn2SR/Uy+DfUZ+UJYnGgwCjggGIjkEkWCvowJChr/MGKcNpCJ+Fb5u93tbs2XsAAO8492a62F5xMvCl3r8lyU2+2rvQngozlwDITbq10ZPHec5DNvKwAHoMenXslLL+fSD+Rxrf2GvX4ARQY+uY83yRtOJyDdcwnfa48RbD3kRWIoCBmxVxgK6gqz8Q4VviI7jFN5fIN3fQhA+CTd6As72iYXGJYcUOSf8t1E5qId4wavdp/v5j2eQ2+GqJPmVfQTejmps7/IBHueEcV4c9+eJ0PfngJyyZP2s+5ve5cOi3w0JIPVQ1v9uI/nxkFmaVtZ+fbZmIxSZqcTPYzPeJ0538gOY4YTGCZeat7pMe2H/hh4nBPkMAfifpjTRoA+AE+gUZaIxFsnto5idNxG6coHximvAwcOlPaxmmfKAFvAuvhhypAgoSgw8PWvf/3mG9TAmbAMFhiBoE8Kk4FAYfOkEPo2NC8cRc6b4li8vXEJcwLBIlOcxjAnEdIs56mEcSiCoTYpHbQh0IFdSouHiVGC4QhScxyqv+l8tOFtBDysA6Nklc994gUx14QtACQB3QQ4z4QTGMK2b14EMU86EOY5QEThEtYAOd6Rz2hiEPDadDcsZcIbgq8YjAwxPEi5aw8AAOp4SwEta+EeyCRgKXZ9MSQABYYEhcEowK/G1lZ6eJyywV/GZXzbmISKAGIUhv0BkKB1z1hnZdkXeMWpDUMCKGIgWlsgmSc7lOlQg4AR2tkbyjgxQW9r4ORF3lTSh7URgqGtKM/4EDbBaADyfMucrGg7HoydTPMM3+AvYReu5Ea0NXRl7PDiMjK8tKmc+kC+MTGoKGf94uNaa/NCOhDoGbmmHwYpY1H9SOQgwEy2AZ+Rv03XWmsTv07u8kyjg/2NBsuMk6FkrRhi9jUdYZ8y2sgmOgCQH2rbuqnPQYCuHDz2tbraQE91Y83xgiQvkjqcTtaH5xmwcgLjpIjuoXPIEGCUbOPMcGKsP6fHeIKeciWDot2+q31IJtERY/Pqq7vJPCCf/DNnThk6tb23Fu2boc2YIRfoQo4UsojcsM7t9oLf7ed2/pzfQoNgEsYbLEFHhEy2hzgEGBbKkAvGwzExp+2dLINP8Qa6R7/40ik04xdfRn5e51GATOLs89VB/DGv1vaX2gjQp9wJMAINCYBEYJyS4t3gyZJP4ANWfncTjxlvvRhtQlJ7gCHvKW+YMAt1AChH7wwGoBEoI7A9ky6++OLm83TGwNgggHmmCVzPuwmIBBi7+Zu+B+gl3sOu144wMiZerDnjIDDRjpcwkjAYgCvu4wpwzWlTGYJDu7xfTmkYI/KXSQQ6L5bwCEos2qi1FvPFF4Rs5LevPOtCIChq+QCSEx8KgWEXyhAItJ7KdBOwSYngrzjWBRzPO++85g9+AXfqEJyAJSVtXEAhXvJM4oEC6JUjcAkHgMbV824yHgCim7/KPVoI64o1dXUSISzK/NxHAkKm+qLkKG8GDHAZdJ6q1/dceI7x8ToxIqKM37yxjKYpQ0KIFq+wOurzjgJP1ss6yptKgAFDrL23og7ZZF3wDWOC8iRPAMIowwjE/+7lk12u7qcShcwhoRzaAhPoQjaJWQ9Z5rlxeo6XAtwwgPE2GuA15dqJbMTrnCDt/FV/O2UjK4N3XIEIPO93JIYy8DTWnz0DgDtRBQbJaaB/rM7QM7SL/daW9cA43jBu+mOoPtniOQ+o+rXWYg3wOeDOKFRXOXLX76HEoYXueIh+U45cs+acGdr1FRl7QD65YozaFaaCBvpVbyrpZxEn1FR78ZxMiLV0daLKiQMsuo9ExgQgZvDSJ07CgHx8wqFy3HHHRbMLXxk+ZLtTUacETvzCY41/okH8DmPUWpuvFEX+nCsamq/9BTuQQfa+/WPNnOjLhxWEYZJPTmiG5PmcPofKcPo86UlPar7YFTRm1NN7cR9XjqZuO7CM94hgKuXsQ+XQp1s276cpQC+jJdkE30zX2Dsl1g70Wfk2CCs4FBVyAGIAoo0zpRRsOEIE4QkRYFRsI5DJMy7GlaDXLpCnXRvRJpYXiaC1qSl3R28EUTzbpivFTmEAE+bZVeaEK2BBAM0ZN28ng0GIQiT3wFHcx5Xndk6bUcb6Eoq8WcsCfetE6ZknD6drtO9qvhRa33oRYvgL8KEklZcoUyFPhOcUcATQ0Bt4500T9kC58CDhL+FfwIh2JZ5DyphCcB/JOJ0aGQvQ4BrPdvIKgAJRsaauAD4vFK+x+0g8j3PGBvR6WU1cedsQm1M3ygA3FCew45Sq1iOhFPhIHwDDGF/z3jr5awtefMEDS06QDdHf2NUew3fAfrectSZH5ANsHAle2MVneB1P2Cf4nRGg3CJJG/gND+ER3n3tO81or4cxCnExP2unL15cXn9hKmRqrUdouMgYlinLUSPcJHjHlVGMDn5HEprEQJrqw1o7ncGrQuDa+mGqbjwn053K8p6jZ61H6IF+PHLoFqA76rWv1rXW2nxCOPIBPqdw6M2wjPyxK/0k/IZ+8ZK0fskIMsGaOy0yRm0w4Jw6OLHBa2SP00t8Zb2V2a2EB2MtXclBOtU6uY/kPuhKjwP56EZGAOLkaleWz52TvUknMK447tRDTzyPRu7biVHXvp/7297jaLSftI8HyXF85ZSHgW9fesbxZj3Jg2XnNTYuJ3YMpKCvqy9IMej9bif6rd2WcTGERD0whpS1D5Wr9cieaNfJ3+MUsB8ZmEKlGVGROE6d+rgXmkd3jbe0fU/XDvQBNMqU56K9OYARnlEC0NcqCElKj5CzyXg4gjzaANZY9wAqz6RwCOCfUKKYoyzhYnNqVww+IBjP5BPcYh9t7FqHN4B21AUeAeVoY+rqhAEDTCWhIebZ1x7BQ6gwhhzFt8sAM6x0cwY4jZMyI7AIx3bZ+E2RMHwcHUfijSak4z6uiwhMLz96X4KHYxXhB7hZX8ra8WiM29UamC/FwTAxz/bGQg8bkkeGN04dibfXuPwmAAlvaymhO37zTMJrXsbiufNZT4oZMKbgGQuEv3KR8DNDC0gxvsi3DnjUuhgr5RDPulcgR13hW0OnSd06ca+e+bTnEM9c7TNgPNbUlTfeeqOv+0j2mzpjiUeJgUzh26NjZcee2Y88p47XzbtdFu0Z/AwkgFJYDP4y1yiHZgQvXmuvCf4mX8zN/rMOUWfoqo4ETNhD3XLGZ89wIOAF4I3xx9hhqPC0ea6edtBbO4wVeWPJujl5cOKofXTBkwCze3XxtRNLoRB4m9dXPiPUHsBjfXJJPXxnvGSEOnOTumje3l/tutojj4J3XPEumeF3JGWUbdft/iafnaDZp9Zsqny3ftzzgpPr9AD+jnxXHmEgHlDCt3gKoPYskjWjf4RKcaxEvnWgJ/ABTzblbq+Yr70nRdm46g8PA8VoIZ+jAY+RI4xRMgofW/Naa/N3UZQzLnw7F5gZtz0QPKiNuYkBZD7a6KtjnsYfyb5ifKNh5LniebKGLBTaoF20wg+11ubvPpDb+sDf6N/dH3gNP+M95SLRCXSgPdI26ukIshUNgVvXWg8bafieZz/a6Lvae+15GxOdgHeMFdj2nCHuhJAhhhf0hc/gFmPqa3ssjxzDM/ofKqcf/aNtJDTXZ9zH1dpHO9r2BT0v+TMU8Jpy6nKuGLuyaEw/mbOxyMs0TAH7wPo7zSELIuETcss9uVzrMI4cbn13n6wd6ANhmJLi6U6N4KM4gSxC0mbj6WPFY8ooTxhQDIQ5ReelJ8KU0HQsy7qKsgSmfN4YZTE6pibYeFtsJl5yyjnq9F2Bbf0C28YfZQgzmyXuu9dVY/RtWrTgIRHe0G2fl4GBA5CinWNzsfKseN7SbvlN3RPYQlIwuphYNF+2L8I5AGC3DQqRB9PxGT6xuQDtKEfR6xuQjby42qCUgjYk6whMWUNrG+UIdgJYWUoZiMM/FL9x8SJHWQoLL/JkUup4S130sC7ajfcWok7fVT0C2HgI8iiD73n74r7vKuzDcbp3Aii6vjLrymPM8NQJ2UGfZds1L7xaay1dvrbfvR/B4PKSNz52hC1+n7IvpTTd2hPohu+bjNY/PMgHDx4sgKq2rGnr8f/3E1gHGih069guwBnAESCsxl4HXhg5ZA1eFbMJHEQdYIdiBXDMIfKHrtrRB9mCd/EO5UFG1lqbP0KnjHdwaq2FnKy1FoY8UAoMAKb4sLv+9ga+NT9tGgM+04ffQ0lb+ElYJDoPlVtHvj1iHvazUKVlQT56MMrR3T5qj43cF3ZjbzktYDCRkUIaAOooa+3xH/6JvLgyHhlZwLowSboDz5AfUpRzxW/KyKcDzFG75A6ZziscPOOZsvjLGqkjdFE7eMJ1LFlzfA6At4G+fOs/Vhcf+HCC97zw4FjZOc844YQFmqd9Yd+YLzkJGJurMfEuWweykfGlbWvk5XsyHfiUF8k+o+vofKAq8uMKV3D4obE8awU7WHMyW147GZN1hwEYJp4ZG5nNWeVesm9qrc0f9CRnzEc+epNF+AGAlheJbOOoiPu+K14ns53cGUtfmWXz0JGxbOyMoloPywphJ04k6UhjNH7vWHnnjZzFC9Gn/Q/zxH1eSxH14V1IX4FrJwYAR6k8zuopLLmNtFwr0CeIKXfMRqB1JwzYA928W0A5ixyAolxZ+VGe58pxHdABBNigBAzh7ajKEagjFMqRF9Yxt/I2J0UuppXQYaHzhFHK0XbflcBU3niMjzKOcrzLIagib51XCoMQI4zMxeY0XwLNEbW4O8rYZrU5vRBKiIolNz+bfp3j6WsL7fUL4FLUAHRfuTl5hJ75AnDWCdCO+QL4vKmMOuEzjoXboAB/ic9FD+Cm2x8l73gZPxHo1pXCpYTaxqHxU7DWXHvaRVsvgLmXT5A6dRCrClQAvehAiKI7ZSbGGn9NeXyMg9IhfIUqtfeG+YfS784n7gFLewd/Rt4mrpStkydKlEBr74NF+2NooxWwQxkDT+iAhkJhvPQoLISyovh57hlbjC7rYV+gr2N8c+/2D4Q5KXBOseLiAAAQAElEQVS1ZjyCUQadOQAAKlf5PLMMVGsPAFLE+nC1xpQyEIVvjE3IE5AYSSwssIpXa60FaOPJBs61P5Z46k888cTi9MIaHjhwoPkrzsACmpAxlDD+RS9jBMrwIXlGvuFhctP+ib6MhYxkMOBRfOKZ9shIv8cSQKWvsTLreOaEyN8oEZ/v5HPZNtELPfCDNaIz0MMaM84YxD5rSRf4GpaTPQ6BAIL4wlp4Zu7dcZA19BHZq30GE4cDfgRC2+XJXXtXaA59RZaRj+rx0pNhUR6gMjZzJwesGz7D+3goyg1dGZPmTmbxqkc5MsjLvnE/dGUY2SdDz+fmows6A5QMYaAcP9dam49p2AvCau0Vp3ToL6TJSY456wePo7PfkdCZrrMH1It868UJpr6vyhx//PEl6pK59rEy9qg9bE3UNU50IafJbfvNPrNekr2onOQEx9WawS1AHLkBZzCAA/grE4lcmyOzzRV9ot66rtbSHiBjyQXtOoEVQkVW4Cs0MGdyjGy1T9BDnvL2EZnsd6b9T4G1An3AyNcUeKQItb5EUBCIlD+wR0HZELyawYSAEMBx9tlnN9+Ottl4JChr3hMA0OfZLrzwwsKLS9Da0K7yWOYABc8s4Ke9saUkyClGHhPCVFnAW7gQYOYlJIJW/roTAWgDmgcBCUjzNvEk2Iw2r83KqweI6Z/hQljVWq/8+wHyN5GsCQBMiIsDRPtV+gGueGCBO0qBYjZfgFkf5suIsYaULN6I/njjKA8gtI+35FEIFAdPDiCgXR4ZtNO3tgBYYRnCwhx9AmC8yYQ8z4fxUByMG0d5wJfxsOp5SJQnOAEI4IXg1e5Q0i9DAyAzHuUYFjxj5uLdE8/l9yWCG/g2vr7n68gDRvyRLHsM/SnHVdoFQClKp0+UDzqJtxVehf5i0e1NXjmeFIYb4GAclDdAxBvWjZe0xpGAc2tN6TIKYrwMZi+fkwFOJ7RD4aK9mH4eGicWQAWjw/5iNADKjEjlrD9ei8QTiTcABf0AXGQOnjQGeX3JM3TAR+SLMo7a8b+5kZVoDhABMRQ0PpFHNhg3kMmQYVwYozYkAJDRjDcAH/MlHxm3PFMMXuX6EoDvRMTe6Hu+rjxAzZgYbN63WoWHASx8gT+NG2DHU7zGZCLZj55kI3pYK/3hK/NhKPn7FngxeKh75WCwX3ng8ZUwIPsdP+NL7Ujkoqt9C1QyLvAuRw1jgS7yXJIPkOEFbbnKsxfa5ZTtS+pyYtlH5CHZw1AQz40nyc2+evLwKV7HW+6XTWjiBIhMJAPRHm2jPfTWl/3lgwXWHIjG6+Qw2tl3ZDqQGvUYRviajiUTgfdYE23aJ/Yn3lau1sNhE2QInQngchA4EQTW1SVX7A30tee0a0048dANoKdnjMEYlbPuDCJyybsV9Ai6C48ho+gP7ZAnZLb8MaBsne3LNo30t45kLUU5GK89Zc5433tz1sc6MGRhGfxljmQaGSL5AAYaqYMP1zGmbGO7KbBWoE9ZAchAu43Rl1ihhKRjOArNRiSweETUDXJhTgAIY1KUBDShAYA4ruK14v0j1NUh8ClECtpvZQkYQsfzsUQZUdgECmGkLGHkiI+AcFy8KsDVZl8iLBgZaEeoMYAca/I0ioMkLGxadSkV47DRaz0s8Bgpnk0lbRNiU+W6z42PB4fgRvfu86F7ikHqPjc3AJngMSYgTB6PFyMHeAJCuvXce8ZIZHT18ZY8XiH8xUiiKAg6RqITpLZQs86ALS8QAGCNgRF8R3AyvoA8Bpa+0R2YBCJ58Sh2Jz0MBs/HEj40HjRkNChrjmLPKSt7AeiUv65EyNsfU0au/vCQdaAcAVpjkz8nqQt4tMvKA0D1DeBSsMCQdXYFcK0NJchIqrUWbVhX+w2/CxGzBoCdde1LnuExHl20jDEIc0FzfEB+xDOgGZ05CbRnPJQdWhmL+sC1NQEsjCkSPjFu66iccbvXvnEqJ7+b8Ah5CFSr4zm5h87Gz5MJWABw5I9xA5fGw8AL2YQ32+uiP3zDWSI0A80oft5N8tT3xxmm+ltnYlwBZXPadCphjwHaeB8/zKlnbtbBNcoDWWhP3uMpYIVjyTo6RQbeecetsYTPgGC0BzK1AygC7GisXl9iHOmXzuGVR1Ogjjwmf7UjMcTIRW0Zi32tfbKcg6jWw/JZWetpHRmf6tFT5keeWWdlhhL+xiucXUAdQ6/WWhjHnFBAvnEO1V8m35gYUwBw1NcvZwj5Si8qE89cGVocQsCxU2i8av85lbL/6CzlusmcnEzQ/crDB7Eu9qf1IJcAdDK4Xd+Y9EtP2mf6UpcOJQOsCV4wFic55ARvPTnjDy1qy95jbCjr3p7Wb4zHfOgmOkE7aM4pwKCBM9RZZ2KU0TtTbdKfdFHM2Wk4A5/+Ute8GUN+4yHzIefMk4PNPib78KMymYYpgAfJjeES2/9krUB/mekSGLwDlABBEUJ5mbaWqUOI8Aqw2imkdhuEKO9uKOj2s3X9pujNXSwoWoy1CwwYr407Vm5dz4B8IFmMNYFMeMxp2/h4wwCZbnm0rrUWSi4EUbfMuu8BAyAgwsDW3f5Ye/jZnCkp46j1CADgcQR4ebMBEh4zQr6dAJax9tfxDGAEloTSMIzmtklp2rM8lO06QDFDHE/PBZt4RTtzDKd2X0v8HqwCmFKCZAFDv12QkmeYtmWENXUiZd2AN0AF8Ac0zIfBw6jgcaRk2+2t8hsQBY7Q3pqRUdEe5Y+nQmYBw21+8psRAMhGnU1cGSAMArwNKMd45vSlLlBv70R59AS4gKwpcFJrLdbKyeGBAwcKgzfaWebK2QI4Wlfru2gbwDE5j7+c2AgBY7gBmWNt4SdhTwxJHmcgLcprE3gzP/IW0LO27QTcKhN1dvqKR42NYbDTfW+qP3KNowdf76bMXmR+nFwcqvhYPfuC4QJ3uM+0/ymw60AfiYEBHhnHnl7wARTkbzoRvI7AeFd4wgDp6BPooLx54iJv3VeWIqUrTIf3bqp9m1Md3i2ebQmAnaq3zHP9OA4VWgX8LKKoKRcKilHS7tvxs3hBbTpmbT/b5G9eDi8z8/YIl1lGWS8zPv3gZ7QUitYGKBS+d0x4j5dpe1114qU64Q+Mr1qPGCJTfaAnz1ZXYZgXDybjsPusr038IizDKUkXYPeV31QeueN0x0tXDFVyQV+uPLoANu+svEhODp1Y8LriefQU4sZr6JTEHnWkPuTRjHYWuRqjvxdhH7VPLO0342wbI4u0u66y6AXM8jaK5eYVX6Rtc3Dqx2OrHrCIPxgAPKry5iT7XvgnI2FO+aEyHBK80rXWwmjhGR4q25fPoPdOmXHgEyCRR3VMpjKiAXWx4viJ8Rlt40MnCU4lF6VttLHpq9NTp3rk29g8Nz2O+e1PlwyZLbxvuvR2lLAG5LSTUo5E2AHOImu3Y4Q5ip2gwFYAfRN17AmEObLHiPI2nbzEByg74nUMV+sRkMMbQUnzohC6mxiLT2TxmosVJ7Sn+nB86+iahe79A/dTXqGpNvuemzfFZO5iJhcBX5QQrwcPUyjq6EP4lSMwSo4nKvJ34spIEi/OoNoJL7k5xZEwr6uYzVqP8BfwzxAQxkGB4HshF3ihncSTamsTCRAD8MWcAuUAzdx+gEqeUlcKpF1P3Lv58KrOOQUStofH7EFrAxi129up37xePK/4nmHIU45v/PEwc2SQ9wF2StRL5Lzk5sBh4J4MIdPs2XXOAYgWrsE5gW7RNlnCQQHghsxyktDmJ7/NjVcy6q37yhsvFM5pIHos0j7ni3AfdYJ3gBMOEeDEKZFnc5ITFWNZxymRdwKEHwmxxCNz+o8yQh4BX3Kv1lqEKLaN/ijXvgofESqkT3HtbVnK8BEiJFzLqYdnTo2sbTt5X6HNH+32N/nbSYR3HPC90EcnhgznTfa5E20z1BibeGG3ZPYi8yR/GM0iJsgD6wA72Bfwhusi7WXZvUuBrQH6tdaC+SghXoCdIKlYQnGHFHOtR0CYvsXmAT680H0eCWVWTb6eIxYYIKr16P772jYeLzN70Y5nydgJ+b6yy+ZRIr5uRJmJ0XRETOnMSYQ5w4DXjZIW7tAeh+NnAsfxe63j8+U1sz7695k2/bfbWvR3rbXwfnkJCTBbtP4y5a2PF6z1W+vR8+U9rrUWyoOHb6x9LxZ7v0IMNw/6WNm5z9CXgWuN7DceQjSek4QSiAcF6PtOZoSrCFcC9qfGw9j1QrQTDyEn+Md1qt4mnttLYvidwvAoowVvmP0mJnrodIIRwNMPyAnnAS698+NEDChY91gBYeF0XbkETMqztq5j/QIsPMVim52muo6Vn/OMkQ+AApv4wtyBDXScSuo5pWCYGAsDK/q0f+wBz+mIyB+6kpHqMwoYRAy0obKL5NsrDGLzW6QeA5JnlQErNnwO+ObAsT8ZSrUeLTvQmX5i1OHZsbEw/hjyQrrwNX0zVn4dz8gFYxeyYz8xbMTS40vzp1N9RQ5PrKO/nWojZDZZOSWzyT8x8OTZumT2IvP0rgMnA9qTTfYV/Yxn4B0G9ZA8W6SfLLs3KLA1QH/byEU5+CTcbh+Dd+nC2wiEi88FKrrPV73nifcilhAEHiEKc26iWL1wxsvLk8PjtOx4gAQnLoCW+VIUy7a1jfUAR8AFyJ4an/AM4ActeO6myk89p+yBIXH5QKlTjrlrrByQKaxAP04qXJdNjCHzisSjzyO9bHu7XG9XuxdmaM8I6ZkaiBM1p3a8xk5QV11H/TllZLBZSyGRcSKCZ6aSE11GsboA9RwjUZ99yWdUtcNY815MX5m9nMfhw9hz0jRlNDAUvNuAHt4nYTRteu5OcvQXiScZv5HpTqPkA8J7TabTb0KvOKqmaCicL2T2bvCgk2JjRWuJIY1fOLmctkW8/tQ88vn+oEAC/f2xjmuZhbhqR8VCOlZpkJeJ542nc5V2su5mKMDDxOsmRGuVHni1Fnl5d5W+su52U0AYGsOB4bjqSHkcgf1V28n6SYHtoECOIimwuxRIoL+79N+q3nnReF94AFZJDAYvIK7i0d8qwuyzwfDI8+KussbqeunWC7z7jDw5nSUowFPsG+PeU8Abq6S+TykuMaSskhRICiQFkgKHKJBA/xARtu3/3RoPD63j1FWTmFSe3lqPji3drXllv0dTAChbdY3V9yL7VCz40T3n3X6lgFM8f6gHX6yahP3laeB+5ZScV1IgKbDTFEigv9MUz/6SAkmBpMDiFMgaSYGkQFIgKZAUWJgCCfQXJllWSAokBZICSYGkQFIgKbDbFMj+kwLTFEigP02jLJEUSAokBZICSYGkQFIgKZAU2HMUSKC/55ZstQFn7aRAUiApkBRICiQFkgJJgWODAgn0j411zlkmBZICSYEhCmR+UiApkBRICuxTCiTQ36cLm9NKCiQFkgJJgaRAUiApsBwFstZ+oUAC/f2ykjmPpEBSICmQFEgKJAWSAkmBpECLAgn0W8TIn6tRIGsnn/hLNAAAEABJREFUBZICSYGkQFIgKZAUSApsDwUS6G/PWuRIkgJJgaTAfqNAzicpkBRICiQFdpECCfR3kfjZdVIgKZAUSAokBZICSYFjiwI5252kQAL9naR29pUUSAokBZICSYGkQFIgKZAU2CEKJNDfIUJnN6tRIGsnBZICSYGkQFIgKZAUSAosRoEE+ovRK0snBZICSYGkwHZQIEeRFEgKJAWSAhMUSKA/QaB8nBRICiQFkgJJgaRAUiApsBcokGPsUiCBfpcieZ8USAokBZICSYGkQFIgKZAU2AcUSKC/DxYxp7AaBbJ2UiApkBRICiQFkgJJgf1IgQT6+3FVc05JgaRAUiApsAoFsm5SICmQFNgXFEigvy+WMSeRFEgKJAWSAkmBpEBSICmwOQrszZYT6O/NdctRJwWSAkmBpEBSICmQFEgKJAVGKZBAf5Q8+TApsBoFsnZSICmQFEgKJAWSAkmB3aJAAv3donz2mxRICiQFkgLHIgVyzkmBpEBSYMcokEB/x0idHSUFkgJJgaRAUiApkBRICiQFuhTY3H0C/c3RNltOCiQFkgJJgaRAUiApkBRICuwaBRLo7xrps+OkwGoUyNpJgaRAUiApkBRICiQFxiiQQH+MOvksKZAUSAokBZICe4cCOdKkQFIgKXAUBRLoH0WOvEkKJAWSAkmBpEBSICmQFEgK7A8KXKXsj3nkLJICSYGkQFIgKZAUSAokBZICSYEWBdKj3yJG/kwKJAUOUyD/TQokBZICSYGkQFJg71Mggf7eX8OFZvDxj3+8XHbZZeWiiy5aOf3qr/7qQn1n4fVS4F/+5V/KK17xipXX8TWveU35y7/8y/UOLlvbUxT4r//6r/Irv/IrK/PSRYfkym/91m/tqbnnYGdTIAsmBZICe5ACCfT34KKtOuR//ud/Ls961rPKQx/60PL1X//15ad+6qfK//3f/81qlqHwzne+s3zLt3xLOf/888tHPvKRWfWy0GYo8OY3v7lZR2v53d/93QVgm9sTPnj6059eHvnIR5Zf+7VfKx/72MfmVs1y+5AC733ve8ujH/3ohp/OPffc8ru/+7vFfp8zVXz36le/unzjN35jefGLX1z+53/+Z061LJMUSAokBZICG6bAZoH+hgefzS9OgVprOeOMM8oTnvCEcvWrX70Bd3/wB3/Q/P66r/u6cs4554wmgPL7v//7y7d/+7eXT/mUT0mFvvgSrK3GNa95zfKiF72oWU+N/sM//EN561vfWs4+++zRNTznE2vMWHvTm95Ubn7zm5cPf/jDDS9oJ9OxR4GrXe1q5Zu/+ZvLgx70oGbyH/zgB8tv//Zvlzve8Y6zeImx+PKXv7zc8573LB/60IdmOw6azvKfpEBSICmQFNgYBTYO9HmEeH2nvIXK/fu//3t5yUteUn7mZ36m8RQ/5CEPKTe60Y3Ku9/97qUIoM0//MM/LI95zGOadj71Uz+1UVof+MAHZnuqlup4gUo86Tyrf/VXf1Uuv/zycsUVV5R/+7d/2yjo+uRP/uQC1H/TN31T8fvyQ/3yBv/e7/3erJF/xmd8RuP1++Iv/uJZ5T/60Y+Wf/zHf2zmpq+//uu/Lv/5n/85aw0AUDSa6gi4+Pmf//nmlEF5fHTSSSeVX/zFX5yq2vsc7/zd3/1dec5znlNudrOblU//9E9vvJV4tLfCLmVaixe84AXlVre6VWN0vfa1ry1PfepTG+A+NSRrf8Mb3rB813d9V9HOVHnP0UXIkDW0ltK//uu/LgTsyANrpL2+pA/74SlPeUq51rWu1RgvfeXWlfe///u/5Xd+53fKs5/97ALgTrX73//93+V1r3td+dIv/dKCx17/+tcfxctk3V/8xV+UH/3RHy33uc99yrd+67cWeyDa/ZEf+ZHyG7/xG42Mi7xtuF71qlctF1xwQbnXve7VDOcd73hHISPs1SZj5J+rXOUq5cQTTyzPfOYzy+d8zueMlDzyyDrbT3/zN39TLj8kgyTGqvU4Umr4l1MDabjE4Sd4zWmFvfxP//RPhzM3+C/+tvZORObOZYPDGWwa/Z3E2Gvk8ypjxSN0lzUcSuSGvdE3IHvKGKKNv//7v29kmPWlD9Xx+2//9m8bXlEO75iDZ0PJWsR4tL/KHIf6yPykwLZTYONAHwD7uZ/7uUKADxHD5hc3/n3f930N8Lzzne9cPumTPql82Zd9Wfnqr/7q8lmf9VlDVUfzeaof/vCHl7vf/e5FuAlvtDAVx9MExmjlHXgIxIqLfdnLXtaE0vCo3fSmNy0MHMYNumxqGMcdd1wBpPRFwf/+7/9+46WfSxfe5Fvc4haTw6NIgG3A2/oKFbrlLW/ZhP4Q1lMNvOpVrypTBggBfuGFF5Y//dM/LY94xCNKrbXc5CY3Kfe9733L9a53vakuep/jVwANbd7+9rcXhtBP//RPl/POO6+3/G5m4hnju/GNb9wM48d+7MfKyw95V/FXkzHxz+d//ueX61znOhOlSgNMf/3Xf71cdNFFxakOA/oLvuALyv3ud7/ytre9bTbYZ4wAwkMdUuiXXnpp+dmf/dnCCB4qt458it94yKg73elO5dM+7dNGm1Xe/NX54R/+4XLWWWeVN7zhDUfNHWh54xvfWF760peWX/iFXyi3ve1ti/0WDd/hDndoDIVXvvKVDU0jfxuu+J3hiBZO7H75l3+5kQvvf//7Zw2P4YMnpgoH+P6Jn/iJor/v+I7vKAcPHmwSurQNo6G2vAsg5GzouXzrxSgTVsQwu8Y1riF7owndOAfIdX1vtLMVGv+zP/uz8uQnP7lYr3vc4x4LhWq1uwW26avHPvaxhU4g37UrtFNycsgpRN8wCNp1Qz9ccMEF5Xu/93vL93zP9zTOGnLWaSXjjPGpDofCC1/4wgIfkFnPe97zRvePfWgPnnzyyc1JFZn4H//xH5rKlBQYpQAD8S1veUsh6yNdfPHFRzlsRhvYsocbB/p//Md/XJ7//OcXinsIuLLebcIv+qIvajzFn/mZn9kA/m/4hm9ovGw3uMENFiYbAU9hAIGnnHJK+ezP/uxy3nnnNScGvIQWb473buGOF6jAY8bbwGtGqBkToPq+972v8Jgu0NRSRXmpeTGBfcpJvDehPMfrxRsMsBx//PGjfQMKgJt2eTKB0Lvd7W7NKQ2PzFhla/eDP/iDxcuiQ6CVkgEIKRBGnbXlXTQ2SoLSGeuj7xk+tTa8vF/yJV/ShDVZI2Ox+fFyX73dymMUoylFeeDAgUIhPve5zy3Gij5T4+KB/cIv/MLGuB4rS5kznh/2sIc14Ay/CgGzx4GGsbrxDF8DdkKG8EXkt69A8Vd+5VcWczK39rN1/2a4AOMPfOADy21uc5uCd8b6QFN71Z4BNs4666xCTtkPUU8YjH38VV/1Vc2JRPAgZwN6ASBCXRiQ+o5623K9/vWvX57xjGeU008/vaEH2Szufo68tHZ3uctdmrC+sfk4LXvXu95VvuIrvqKR8eQCkAf42Xtl4j/lnKQAe2PgjQHqhfUHPOABxV5ur9NEF0s/xkNod8455xQ6aMoYWbqjFSoy3IzLiZ5TGAau02+yb9Fma62FvAXqr33ta5fb3/72xXq2E+BvfzEko32OmW/7tm9rwD1Hg9+hIzgurCvsYN3UcWLEWXT/+9+/OfHGj/S8Z91kHpdccklzQkX3MxA4bnbC0OuOJe/3HgU4ouj8hz70oQ0mJc/38sdHNg70bTCeFwK3D6zZqJQd4XjXu951PkdMlHSSAJgISZAUJyi+9mu/thDAlKzjc/m7lXjPjSOEH8BF2RkXkIMmmx4bwcebxkuiLx6opz3taU2crfuxxFs+pThtGOAQANAWEPFDP/RDhceTJ0neUOLt480HxgCDvnKMIkDfyQ+Q21dm0Tw8Cbi6OrlQHw+dffbZBXijbOYYQ+rtVEJfYwOi9Wn8j3/844uwiDLxH2MN79VaR0syvLwDABQo6KTtSU96UrG/Aak5oJw8ENJACceRvLa6Ce/rp9bxMXXrLXKPNk984hPLgx/84AK0T9UFPABg77bwUDKODx482BgI3bqM2Pe85z1Fuc/7vM9rHtsLThSBLCGJvKj2GsDTFNiSf9D+1FNPbTys1phhgq/IaZ74qWECj1O8AKgzpGs9vL7WGoBjRDstws9j/fzRH/1R+aVf+qXGmMVPfWU5kM475Nwh772H0ldmU3m11iacjhzn5GDgbqqvRdtl/JOnt771rZv3MgAaThJyYNG22uWvuOKKYo98+Zd/eREmG8847rzrob9YV7qP7GA4O+21B+kGvKce4O+k0MmIUwJ5Er4ih8hmoUBDJz/CkRiBviZ2xhlnFMZ2tK2dTEmBMQpwegppxT/Sn/zJnzQnm8G/Y3W38dlGgb6NT6mJH+Z94b3uEkEZIREU5gknnHDlYwoFEKCM25sZgLfRP/CBDzQxyTa7doVa2PyEGGFjo7P4eQ0JFclvHRAo0vnnn18oZHm7kYSWGLMvVQCsxscbSMgtK3QpyTjqnDunk046qVCIhKrx8IDxpFDGc9sYKmduwLpNY62tD8HP8z5mJPBKW9d73/veBWi18Yyt3Q8vvnAnJ0FObeKZPqy9NQdSIt9xnHbxClrjIX1QwvhKObzmHl/pD1jAS/qiKMRcWyuAzXN1Np0Yf/qb6gc9Kczv/M7vbDyqwBAwiX5oMlV/6jnQYo8C9cAVWjFSP/dzP3cy5EXbaIkHDh48WH7zN3+zOdVZZlzoLqRHW9bPWpEX+ohkfckJz60ffohnrniBwWmvASG1HgacnvUlfQrRAU554wHgvnKRp18eUuAVOJHv1MBYoj8hPbXW5p2K4D/lNpmAKqcKU33gdZ5ZhhkQzrBlFAFmy6xZtz+GjlMkINzetj4MJ+sxZbBba0YTAwr/Ob3qyiq8edFFFxXy9Mwzz2zC+bpj2PQ9GjqxoAMZSnhu031qf0oH1FqbF/BPO+20Rk4Yp3qrJPvNfsQrZI62eNXJ31prA7TJafnKogdeItvwQewRzyPZY9q67nWvG1mF7IYJnJgwVrrrriD+EBJr7ckr4aLrmKO2hxJdw2FGNwyV6eajD/xB35AX6Eeuye+Wzfudo4C1EJop1A9OgY/gRc6+nRvFenvaGNAnaBHLJqPsKGPKvTt8eZSomOrYjOoK+QBaHNuJH1fPC1UAI8HNE+bo8Sd/8ifLox71qOIIncFgk2hT2IYFAy4cTQq7sIm0I2SFcPHc8bG83UiUFEWKNmjkmBctdmMshD6aOvUAan/gB36gCZlZdSw2h5dDeeUBRGCJIB5r1xry7DnqJTxZ0daJAdeuR6h6t8O7HEBCPAOwHNNSLHhEPkGMBwB1BhZwwfgEioWJ4BGGJX4RzmS87nmFfIrU6ZBxiYOneIyHkNb2tiXvoHzN13xN41WzZ8TOAvurjpOXDr+itfa9F0GRz2kXX9vTaM+D6HTPGsufUz/K6E8olzXBr9o6+9BJi7X0TDmg2V5CB0/4uowAABAASURBVCEA5IOwADHTwJ+1BBh8VUYsun2o3lBSDjDRJx4AMNr0lHf55Zc37xRonxGEL9HJvgLw1HHy4fjX3PVlr/FyMh7+/M//XNbWJXLJ/gW+ARJGjlPIVQfKKHUsztuKJ3h3ec7mGBGAM1D0uMc9rng/xXryuLXHxKC3bvQH8Nl+1v5NLjgRtG70Bx1hDGQyIBphRPKsMd6zvniMIQ1QMoLoLOuIx9s8DSDQNZ6RLe2+t+W3kydhNuZY67jBOzRmspBMNF9GnHJ4PuSv+0hC2LysTO5a/8jvXu1Lsr2dbz0YyLe73e2KNbIO7ed0i3fC6DDOMmG/p512WrvIVvw2bjKLfOJwtMecSnNsdXl5KwZ8jAyCbHYSTjfhT+sDT9rfe5kEGwP6lALByKPBM8Trx1PcBmuI5ziYh5ciaROSIuC16VrslKN2CXJ1eIzFzAo9ANCUFyPKI83Lyxrz3JE7b5E+eA8IJAraS3g8DPLnJOOloKYSYEDYDLVJCIpHtNkBMd4pLyuJhx2qs+l8QgYYRhvKi5cfIF62X2AIUBbDzRtovQEFYTtjbaIbYXfqqaeWUw8lR8HCmdohDpQp0KQdwtw1EoMRSMcjkefKOhdGRClRajYyBQdoeOkXKNYWMMsgENtp/PhHDKp2gd2TDp2AUPZ4XLvbluwFBoyX0I2Z0cLrCcQsO1Z17V/hVOIVASh7ygupc9pU337mzaaohVLgfflz6kcZAN7XlTgQvGhn/RzLA4p41Z4GLhiq1hW4B9CtF/lAkCsDpFk/DoZoe+yKXxgSgGXIEeWB+B//8R9vXiAEVOWRKcZpjsAKD3rIC7ykjMQQcIpmr1EmQIr8bUsMJaD6wIEDzemaUBSndMuOk7wFkIE9hhZedWKFn+zNqXb1jXbAnnA1gA+4I1/UtVZ4jfwhV+V1Ez7wdTcgC/0ZD/YIvQGQm681M3ceZGuLx+SR7RwQfgMFTgbJIrqI8Yknoj9OCmtsLGSPscWzbbiSqcJ2XDnAyItlxuWkisHAOUNGWkeGk3Vqt+fkxjrLIwuEwfndl/AbWRHPrBkjQUiPkFP7EWCO564Amr3EgLBmZIN2PNumRAeiA/2Gn+wFX8Kjs8xrm8Z6rI2FE8s7JQxWGM07aW25vRfpsRGgD4Txhjjqp+goR5a5TcjTFYQC+t0D747YIp9wZBwI+Yk8V7F62iSQgC2bhCABbAh04JlQVnYqAbMsfl4IxsFR5UdujIuVN5V4Gfs8SQQ9RQXUG7eTCMrOPQHp2JXQHBnCxh4xrowHwOeJR0vCxxot0inAQpED99Yd4PTJPkqQBw1AGwN4vJuMMaAbL9h4yvPmxDgIfYoFGAfgI9/VBiXo2/RnaOIdfOZIGO8wMPEPZUA5MyDVn0riuc0Dv02V3Y3ntdbmq0OAi31hbgxIydosOiYKk8cJ7+IPe8DfUfDinZMz6zXWJmDN6wpUo7n1shYMQDJhrG77GWAOwHufhBFfa22+FiR8y1rHCQM+ISOsKz4iK+wxQBC4sPbm5J4caPfR99vJEOeBNoEi7/ngMXT1B8e8BG2f+AqRUBS8BzjhE0AGMCa7AEinlORO9MPbi5cZHgBw5G/T1Z7hjGD8khHWkvxbhv+BGOEa5IOTWSEYjH+AHfCe4gf1eeCtB9lgLbxHc/HFFzef8EU3fIpXyHXvEclrJ/qJYU+JWy9r6oo/gXEyxXs41gpA59xhlDrdcIrIcMRz5JPEMYEWQC6vLF5s94ffOB4YH8vsv3Zb6/wttI2h4nTEviAXl2kfvek0e4rh7Ss3+B14xf/tNvXppIWxjF6LGBYMKrLEnqU7rS+9EO2jr3eIGGTyrQn9E8+36eqdRfLTHsAveJnzAh+j3TaN9VgaC9kMuwH6eJnOhFOFQ3M27lVabAToA0Esel4/hKEobDhAFsFsUPk8KQSgzV7r0UeGtdbmyzvKdVOtRz+rtTZfhyAE5grS6JM3yBjKzP94BwCHqUQQARndZgk6AJg3yh+X4ZmgPBlDPICEkzF16/Xd844Ap+1kLrxT7TzrAZT0tdHNM2YeEyER1qv7fM49ZU0ZAgdCF4A7c6TUASTjsXn62qI0eF8JO/VqrQUY8oKf43XCXj3KFZ2soyQvUq21+YJMrUfzVPnEf+bYruPeI/zjOpWU50kS/mG8U+UXeY4u7bXz25wpLr8j6RtgGWq71looXN5vRs5Qual847GOlCsBCARZS20DMPhZGmuHLDBuYSrq4isvqWqLYauPsfrxjFGunQD5kW+v4S18A+BZH/tAv8pYa4rUWknoRvYA1soqM5bIFOGD6pFjyvrNEycBrsC9PjzTprmhj7kanzmSGfaDMpHQQ/vGg6cifx1XoJjTAM0i8RgaS9y7KqPsWJ/kFEO9O/6xOt1n+nC6IYRJCKY9jT6ATtDV+nXrte8BIeCdvJSPLxl+TuOAJ7S0j+0PMs9aKNdODFPOBsDdfGqtzd9RYGz5ghLj31p5p4ITyheHAFNGrjFbTzqNDCLHeZkZBQwH86v1aLmjPUalfYLn2mNZ9feyOgAPkNG8307p6DXjXGY89hTD1prYowA/ueMklhHWbpPsJ7fRFU+1n0395hhgWHFChUyzzuqhA95gsHjO2OdkJHM8X3eyj+ydSJxi5A39HXmuyvX1jTby8aJyeMM+AP7JBM8y7R4FyCV7QpSD8HDryBGB13dvVMv3vHagT8gSmLwDPGAxNIIcyOMNIhQi/1i68twB+WgE5Lc3tN+ALW8nRTKHLrwojp7bSfiCONF2npcOCaA5bSpDQPK2OHIWrgGwyJ+TKD9HkoB690SGIuHhIcxsor72KAHCjzc0nlOyBCPPE6Ua+fvxSvG2185vp2NCG/yOZF0YAFM0AFjsPZ+DlPqAz1AbgBLPBt4Begi/KKsdChWvWp/I77sCb3i/Xc4Xl/AVAI2P++p184AEe4dSbz+zdwAK/CXfCZK9xHOoXzwJzAJ1ALgyiyQAFTjVh0TYO03yDpK/JMsbHe0xAHh/0YWHuNZagHjGr3VYFNxEu8tceaOBueAZV2Ozh/yOpIyyU32Yu9Mc4End9npO1QXAxbcLa+ItxzvtOkCO9gG5dn77NweREBmnQe18a+DeGlkrv4eS9XEqRA6Zi3UU3iU5OSRnoq6xOAnSZjuExPrTYcAdecUAaO+NqL8TV3vHWrRTnw4QemAfG5O14DTxvpTTKC8dMoaHZLI6Y8l+tC7eX7LvlGWAOd2AA9xHAobj9yJXsgiPkhvqGauXbcM4BvLpLU4heXQg/WMcyq87+eLTJ2jehO0J8fTuCl3bzhdShl/a/XPE4UNGo5fjlWdsGXe7XP7eDgrYH/AaYwyvb8eoFhvF2oE+ZiUEKYPwcBmSFxhtfErPJuHh4BUhIAlw98rtdKJgpLn9OsYVmzmVePoAjHa74s55OiiNLuAgxAhtSgxIaNcb+s2b5HipnSgrL7228yhWHtihdrr5PCfGyZPrHYvu87F7XlXKU7gDQdwuy8jTtnj3rqKPcsATI4PBE3n4hNeO4UiQ2myO2KwbfsM/UXanrkClOdR6tPdu1f6FJLTXzm9AUqiA35GEzgBGY/3xHjpBo1R4Grs8N1bXM54568Fb3gV1wLu1xh+8c8oPJUee1jRAgHLG4osa9r0wCmBK/pwkfKKvnPWg7Cl4+0CIh+NwfMwwYWQDCEANXgJ4eDb72mrn4S97k+GrD/TkMQQ+vK/QlnOMMoDWfIOH0YlHyAkneddu2+9aazGedjvyV02MbQAveMZViIrPGPsdSRllx/pDK8CQwYKnAKqx8t1nTlj87QTGT4C1KIMHGB90BLAY+d0rww347tZHaydEAC6DrtZayAxGYXd9hU8ph7e9iyOOnDF47rnnFqFX1qHdL88xrzHZHfnaJa/RxH417ng2dMV/xuQ6VGaZ/Lk6QIhZ6ADr6F0s+piuwMf2BJm6zBiEdnLCMKTtD22Yq9C5rg6wfmhMN6K7snMSOY+HQtaQ/cYsXEf/dI6veZmDsZBPeC3GM6ePRco4wYn94wroczAwnNxH4lyp9YiOgH+8/xEnSq7KCu9Dl0XGkGV3jgLwDP3VJ793bhTL97R2oM/LQamxVms9wuAEHK8gC5/1LRSBV4XFTdBQnstPY/GaPDEUjHEuIgx4gcSnTiVhDoRRe2S8lx/+8IebUBReyHhm/r5fb6PzoFJorEieIgIuyu3EFU0oBcewQngW7dPYCVux4QRx1AeWvLjJi6tdgpF3MZ67EuTAAM9nu26ttfnjPeqK7WUsoC2lYbyS+juVeMbwbiidRfoVAywmmMBfpN4yZXntvCjqi0JO0xZtg8EOKBFyDJuob6/y4OFbIRivfvWrmzAh8dJd5W2fA8mAYa1H5IH1pRjxiZeFAbRof+jKeWAc4nABhW45gI/xwxBUDo8xcnmshQgBHvq19xgu+HSOgWFsgAMDQrv4DW0Ifu3EOBggYjq1af9q3zMGhxMqBhM5KC8SUKJN4SiLKhEnHOLmjSXa29SVscIgEP9sbov2QyegIV4KukQbQDce4DyhPwBSnnXgP8rgKx57ThLrF/mu5DdjWF11rLFTQyDTWigTCb3tX7zqhVoGs3cEtNs1tKwnmcPx4qQN32uHAU3OmYs1lTeWhGYYC17prv9YPc+cbtoneND9qklojZcLGejmj3b2i/2EruaF/ubFaI3+lHFSy0iIvLgy1AF79AgaujLmtWltyWzltY2m1srJv7y+ZL76R2vPyUsGlrVwz2C3xnif0QJbhDzWn7KM10X3lLatuxer9el+XclchIFxBHBEoBf6aN+7EvaWEw/zRifx+2M0Ui/TzlCAzGiHZ+5Mr+vrZa1A3xGVo1mKAGjtDhMwcxTK+hZPCazx6vGYYPB2ed6SEKx+xzO/bWLKVn/yXSPfZpKnrkTBSPIiKU9xuBeDxQvotyM1QsvvoUTACIeYSgRSV6hT6LXWQujFOAFgJxxowrKnBAEnAsGRNOvffIfGs858NPHSpfXwciHltGj7BLw5EdQxbiEmjiith6NMPOLEA4iM9q0J4E+phSc0nrkyEG00dEMn5SkrbVMaykTyTF+uyke+8UieSZHvN/7BU/KU8dv4+tpmfPEq4gHlJXN2CqKu+74ELOF3Xij99ZVZR54x+PKM0w8v5AL5tR4B2XP7oIQkBip6qAc48dAzuABpNDIXAAG9gQFXZV2FGNnzfSErFDVlBrA6KeuulXXRhqv2KEYK0smQ/mNMjlQBOGDPXhZT6TlDRD30YERaS4AGEPQ+DGONZ1aZsWS++Jqx0t7TASy0D8Qalz3Ow4s30EqfvP+MFOXQMvoyNwAK2OLtV9ezoOfY2HimndJou0039dedyAPGEvDHCK91cV5Cc/Mzf/vHGK0fEOzTpzyk9j7ZCNz62g25iD7KysOLvLTu28maMMLQndzEk8oB1vZau6w1I5vJDeAUD1gX/MvBwXMP4OEpfEeXeSfEuCh7Dhlf9uMuAAAQAElEQVS8Rl6jhzba7Xd/W2M8Z2yAp7HKY/yiRbd8+x6IdQID7BlL+9miv/WpHXQluxjAdJl2PNMXmWHv2GfWA6hHJ/TxYi1AjbbqSOqR874goy37Wb5kvOrSZb5ARffLRy8Go7X0FSzvVuADz7RnzzL8OBLsUTyjfw4S+ohxrazf1tGYGW32m3wOPGEwdAjDvtYjvEpG0z3KDSUyGh8ag304VG6ZfPPEj9rl4Ky1FjqXjPR+R621+bs+aIIPyUZrYP76s2/oSPXdZ1o/BchwetP+R297l2OJjvJBkfX3uDMtrhXox6YnBHkT+xKFCVDz6tt4QjIwO6Vmo5u2DeF41beHPRNvR1G7B8QBd55f3kobUp4jZWV4jfXrWJYgtWDuWcmEiPYpRm0RTl7esXFsLsqMR0j7yq072biOSnn4ADACSSKAvejG62dchJsjbLSh0IGIdY+l2x6mRjuCBB1CMHfLTd2bHwXoSNKGCUFfay1iYxmAXvQ999BRedvbgiesOQ+w9epL1hePWGv84qiY5wMvhTA0PvTEH+Yk9ASYwJvGQhF4TnHx3HjBxvG9/ilx/TJKgAxl3StD+Wub8iIMKEPGhzxASHtoN7ZWwAhgRgmpt6lEKVLKDEWhBcv24/SK9w8tnQrYZ/gV8PWVKOtsPRmFaMEjy+sK4OoTXdCEckPHvlRrLcoz/JVXz360xvrxmwFlH+AXxgVjiaEIKGjTuuIFcwUolTMOXlr8Ecn+Aio5FXjQAQHrDJToty95Bkxo3+mfMmSYe3yEpwEdQElIGmAKxFAQeBWf6s9vchHg04aEPxkkgCRQI4+8M1+KH7g0f/ndBFT5yhADovtsnff4HQA2Z2FKDKll2idPhDGQ1zyXwJ91ExvvhEtoGscP0GYvoyGwThZaA3uOPLcXrXk34RUg2t/QABIBerQh99WPMTN6hXJR3sIs8DQeJXedoJIX+Et7TocYqPIBQHIbD1lHusR+Ns5ou++KD8g1RiIwan2BN2DXPqWL+urJowPIpDbPyF8mASp0DKOS3qT7oh1zRHt7Hb2sByCKL627PWXt0c3eUg+f2ztOtsk88+LEiXWxP8kF6ypUjANLPYnBoxzZ4USFbHHPyLCX0EdMNJlCDtgLXni3rpI2rLUTA3Oiw/EpWjmlIGPtLc4D+0958oNOMkbjldeXrKnTG0ZE3/NV8hgnTrPtdeFvdIaTRqeAjHahY+bsNAFfnHDCCQW/1lqbL0rZK2QDXbbKOLLuMAUYWPgR9mIM4xn4wmd37ZHhmtv9ZK1An1Cg7DHr0LR5SAAp1hEhSZjwEoXwjHraoBCARQo58oWU8NrwTNg48gkv4NHG4RmTR6gCBerbLPIiAZOAPSAUQhTQMwbH/1Fu3VfeDJ8jJBwpIu3rzybnZam1FoxGyBCo6EnpBchUfiqJ8SdYp8q1n+sDmOHtoICMqf18kd/WDfihGAjyWmuxaawXD9tQW3hBGAIFM1TGOvLmA2s8O2joD2NZtwCJ6lIqBCoFwbiSJwHYDECGjLbkSU4KGDm+wuHeOlFQ+gIW5UWy6YEPYEA/8il9oE88b61HPEierSP53r8Y5DltGYs1BG4BKwpxTr2+MvYXYUcZxbpQUpQpQwcAQEd8GvXxcdyjE9BgneJ596o9+5bcaAtSa4CHKDcyI+pZd/vayRPwKB+/AylRn+KnLK2/NYxEgOMVRoX2hdcBngC1dvoSjzyQgI8CHJmXk0DjAP6BX7HS1h+fGxswg37oQQYxQsQQRxv6AkoZQUJHgC15kjExfgBN9+tMjBHzntMmsGFfANhCCkNWzqnbLYMngHiKE5jyXHtCFgBpNEVH/MqwYMR4Tg7WWps/jCWch5xQt5vQVZwz3lcPLzjhYawbf7u8vY0X6JJaa2H0AaXewSA3nKLSOdZWPfvvvPPOK3iAvgL27Qtr6/lYclJA35g7nlPWiQB9w1hzv+7UpwPQTUw+AG6+7T7JaYDZPrHejBq8bXzo2C7b/q1N/KQeHUYPx3P8rD/rgfcj37XWWjgR7E+0DtmiPcaNfU8HKiuRs4wMew6fyDNm+8bJg3tJfTxiPPi1LXfIRTIabyi77uRkyGkjGTDWtrUh04zbePGTNSEz0JvMqLUW68EBhQdrrYXz0/iVIXfH+shny1OAgQmf4mchZrALpxa6L9/q7tdcK9BHDEeNc5LjMYKd8AO4KVteByShFIB/QEVbjAIbCQB1H4nwBGgAtMgbugJzlAZQy2vvt7I2G+VSay2Agzxg1Tg2kczDfPRj/LxO5ht98QChy1Kb+VAjgBOFdejn7P/RHhjhUQBGZlc8VJBXijfn0M8r/6dIgHZzBCooVHS+skDPDwCOwldnKhGo+rBueIQw5IkK7yfwiae04zmjjzJp84nnFHWMU9mhpAzFw2vEs+QFT7xY62FQb/0ADSBBPz3TWykL6DCHOY2ImeexYgwtAhQBIqnbh/1pr6KNOFiGj73TLceDRhE9+tGPvvKzuPpHZ3WnkrWPfWddgUHKUD3rTbZEn8ZEAMdzewgYiOcUPZDHyFA/krExDJW1v8gEJ1BAJUUa9dtXfKU/+0KdeCZP6Bj+Ylho07iVAwwpbGV5HfUB7AA/8iRA3ukIWQAQqStfO67acWoQ+fLWkXjJ5xqNvOfiicmGRWQKAwGYbXvSjd3cADHrYe2EdNk3nkUC5Bh95D/vutMQNGBYqjcn4VFrxemD9hwPgF70YRz61hYZjM5krudAPJ4FOLUhD2D0x9eAMnn2oz0BbHo+lHi9nazhQ/2pq29yivFqjuY7VH/Z/D4dEHPoW8daa0FftLKX8DRACmgOOZnMnYGNhmMJfdt8H3OqtRZjYjxFfTQmk0NXoJe1jOeu9pw20I1eCZmBj+w7ZSJZR7ogytO9ZAndIW+diUFEJxjHWLvBy+hinHRGe87q0ic+82rsTpzwizw6Eo3gFOUyrZ8Cbb62Nhw21mz9Pe1si2sF+ssMvdZaCBdCgxXFm4Wxl2lrqg7FI1zDUS3QF+DBsbojPoq/1sPgbaqtTT2naHinAQ90MDZCbVP9ibl0ykDpEO61zp8/TydFtqmxzWkX6OQBEl7iWBfImFNvkTLWQDgXzwtlD6S0N7+QIt6s4CcCnAHaThSa05pF+l2kLN4GcB1NG2eMZU4beA3t7L055btl8CnPJa/2bishL+IJTRAWaF4xVmNkqPGuGqd8gMLpBOPfHgAqfcEDgADwhXwJKXACxNBTZx0JyBf2YCw8mu39bZz4BMCptRaGZZuP/AbkhDnMHcui5fC7kAlzF2KI52udLxcYfPbjov0qX+thDzsgBDwxIOUvk6wvT7C9yUPKi25uy7S1aB1yVXgSA0KYorFow/oKQ+LRrvUwTY3RurYTHr3kkktU2dFUay1kB/2I5zmednQAG+qMjAaUGRe6YMy06e034w0O8Hw3U621+EiBMZJj5BPZxXkwdWKwm+POvreXArsO9IM04YHjfeFhjvx1Xh3ZOzrmYQG8eAy0Tyh72YvnAWCSt1sJ0OcJ4l0VZkDY8i5tYjyADSBB+fEgUEpz+wGoxQsCU8cff/zcahspRygyEoUfWeN1d0JJeGHKWjh27c4XMCOMQ5kDSEBzOwE+vKnrHpv28Kw4YOBP30445M9NwlPEpbYB59y6yjnV8S6M+Xlh0W/5u5F4YBisYmCFHDF+eMXEXPviiFOJLp8Ly2AwCl3D17w6wJi6+Or0009f61TEDnM4COHrhrMBGryoQAmecqTf5iO/haIAYmsdVKsxBo7wSKcNHACtR5M/ne6JvVcw9oPfiyaAGOC0LovW7ZYXiy9sj4d6FcOh2+7QPR5yGqEvfMhgibLWz8k1XWN95TPM5beTOHNhMZ7vRiJTyLvuXtmNsayjTzKangueFBffprffjG9e9HX0t2obxmoPOCGu9fAHPNzH+Fdtv5SSTRxDFNgaoA9kiI9ytE7JbWINhBJQ3I6P2x5Znh7gZBu8FwSNEw4xhoCbb3+z5NdNDwqZUQUA6YtQn9uHY3kvp4hzXTTmkQCjxLw4JX6TMTO336FyDDbxdMJVKPShcsvm402hFzwsXZCvTaANPSlH90MJgAPueEuFbayL3wBttHT07vh4qP9uPm8RT749wZO9jFJXn0eSAcQ7bQ3WNa/ueOfcC5XhnTcnXrpaD3tNgXfASchNtx11nArxojIUAH987eiWTOqWX/We4S5O3F6v9fD4ok0GBgDI6x95fVfOAGDFu0ZeShau1Vdu0TxODzxK5gi7EzIwpw3gVmy3ExLGJiA7p167jH2El4TuMM6Eu6xDF/Doc2QIsdoJoFRrLcKj9NmVq762QwYyAtpz7/vNwUBGA6nCy5wA9ZVbV55+7Bv05xCjJ43feP0xKI4dJ7jmsK4+d6odMnKOjIYDGNccHwxW+2ynxqgfJ6NCQyUv6jO2YRV7Y874tZEpKdClwNYA/RiY+LlNHU858mYhR19xpdR9FlD40E4ogui376p/gI0XisARRtBXbpU8ngGxt8AhoS3eGSgaTSef3HwrXRmACBjw9j+jZJGx1FqbeFBClMeUF3iR+mNlAba+GNSxOnOeAYfiKIeAMNDmRUAxoGPtAT/WVHiJl//anr6xemPPAAbgmkefUeh0wxrNSWjFM8zDbOzLgCrxzdaRBxhPAJ36Hhvzpp8BqWKgee+FUbmKQR5aP+NRBwBnyHnRGl3IC0ak5+tM9gynQ1+bDAsvKXonY6xvvCO8xddjnMqtw8AVx+7FM7KBIcpotJZzEto5JcUHTvnU6ZvfWJ6TKLyMjxiNYuGBnLE6c59Ze4bVOk4Ipvokw42dgdEty2EgtMxYxtZXPfW93A10zpEv6qyS6Eb9oL9wI+tvLrXWxnAhsxn01nqVfnajLjriqQMHDox2T0abv9NhIZr22WiFNT8kk71nZQzGTD/WWgtHBCOMnF5zl9ncMUCBrQP6u0FzHlsgkddvN/rv9glsMD54U7rP1nHv04MMGx4inkMeesf1c5PwDACTIlomJhtwVg+YoYDXMafdbIPwlaYUN6XJkDVv/LYqiAHMfG2G5we48m7H3DVUjqHmNMu4xa4usxZ4wHwi4dtV57Wba7nbfdsbQPuUJ92a4SF0x1NT5afm5TSK15jRxjsvJniOXMBHkrJOrNRlxBjbVJ/d5/jPXMxJfXPsltnr93SMvTZnvewj4Uvo4Up+bHL+oXf0hwf1H/3hy70ss8lnaYqnYIHd5EGGBTpLjI4Yr7G7b69JrE1ekwJTFEigP0WhffZcWIDjSV553s5VEo8iAbTPSLRnpiPWF3BYZQ3VdbrgCyVzwMeeIU4OdCEKCNlhLApXwhOrJO9bOSFZaABZOCmQFNgvFMh5bBkFEuhv2YJsejg8BD5lyHO3avLZPce9mx5ztt9PAaEOYmlXXUffsQf2eVT7e8rc/U4B3kJhM6vykvpOC3n19zvNcn5JgaRAUmAvUCCB/l5Ypf0+xpxffEEwqgAAAc9JREFUUiApkBRICiQFkgJJgaTA2imQQH/tJM0GkwJJgaRAUmBVCmT9pEBSICmQFFidAgn0V6dhtpAUSAokBZICSYGkQFIgKbBZCmTrS1Aggf4SRMsqSYGkQFIgKZAUSAokBZICSYFtp0AC/W1foRzfahTI2kmBpEBSICmQFEgKJAWOUQok0D9GFz6nnRRICiQFjlUK5LyTAkmBpMCxQoEE+sfKSuc8kwJJgaRAUiApkBRICiQF+iiwb/MS6O/bpc2JJQWSAkmBpEBSICmQFEgKHMsUSKB/LK9+zn01CmTtpEBSICmQFEgKJAWSAltMgQT6W7w4ObSkQFIgKZAU2FsUyNEmBZICSYFtokAC/W1ajRxLUiApkBRICiQFkgJJgaTAfqLArs4lgf6ukj87TwokBZICSYGkQFIgKZAUSApshgIJ9DdD12w1KbAaBbJ2UiApkBRICiQFkgJJgRUpkEB/RQJm9aRAUiApkBRICuwEBbKPpEBSICmwKAUS6C9KsSyfFEgKJAWSAkmBpEBSICmQFNh9CkyOIIH+JImyQFIgKZAUSAokBZICSYGkQFJg71Eggf7eW7MccVJgNQpk7aRAUiApkBRICiQFjgkK/D8AAAD//xVtn2cAAAAGSURBVAMAV3TZfc0O7y4AAAAASUVORK5CYII=\" width=\"724\" height=\"356\"\u003e\u003c/p\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003c/span\u003eEach equation of the VECM system illustrates the short-run relationship between the variables and permits the long-run equilibrium relationship through the error correction term (ECMₜ₋₁). The ECMₜ₋₁ is derived from the residuals of the co-integrating equation and illustrates how far from equilibrium the system was last period. The coefficient on the ECM term in each of the equations (λ₁, λ₂, λ₃) controls the speed of adjustment, and it specifies how quickly the respective dependent variable responds to eliminate disequilibrium from long-run equilibrium. The existence of a negative and statistically significant coefficient confirms that the variable adjusts to return towards equilibrium after a shock. The specification of this single ECM term is consistent with the Johansen test outcome of a single stable co-integrating relation among the variables.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Result and Discussion","content":"\u003cp\u003eTo analyses the existing relationship among exchange rate volatility, inflation rate, and foreign direct investment (FDI) in Nigeria, Vector Error Correction Model (VECM), was used. The unit root and co-integration tests to establish the time-series properties and long-run equilibrium among the variables was conducted.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4.1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eUnit root result- Trend and Intercept\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCriteria Value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAt Level I(0)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAt 1st Difference\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRemark\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-3.548490\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-1.889753\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-8.843145\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eI(1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-3.540328\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.617217\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-6.01577\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eI(1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-3.557759\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-2.617217\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-6.015777\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eI(1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003eSource: Author\u0026rsquo;s Computation\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFrom Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e4.1\u003c/span\u003e the finding shows that the variables are integrated of order one, I (1), based on this, the Johansen cointegration test was conducted. It therefore important to determine the lag length as given below in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e4.2\u003c/span\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4.2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eLag length selection\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLagL\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAIC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSC\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHQ\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-355.430144\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e21.72304\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e21.85909\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e21.76881\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-316.589180\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68.26594\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19.91450\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e20.45868*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e20.09760\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-304.411109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19.18969*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19.72189*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e20.67421\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e20.04231*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-296.822315\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.57832\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e19.80741\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e21.16787\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e20.26517\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003eSource: Author\u0026rsquo;s Computation\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe lags' structure is central to the identification of the dynamics of the underlying system and the assurance that the error terms of the model are adequately behaved (Udo, \u0026amp; Idochi, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The results of the lag length selection including the Akaike Information Criterion (AIC) and the Hannan-Quinn Criterion (HQ), both of which selected the optimal lag length at lag 2 of the VAR system. Having obtain the Lag length, we proceeded to test for the existence of a long-run equilibrium relationship among the variables.\u003c/p\u003e\u003cp\u003eThe Johansen cointegration test was applied, using the trace statistic and maximum eigenvalue statistic, with a lag length of two as determined, but however, reported the trace statistics since there is not contradition in their outcome.\u003c/p\u003e\u003cp\u003eFrom the Table below, the Johansen trace test discovers the presence of one cointegrating relationship at the 5 percent significance level\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4.3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eJohansen Cointegration Test Result\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypothesized No. of CE(s)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5% Criteria Value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eProb.\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNone *\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e29.797073\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.002145\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAt most 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15.494712\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.210115\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAt most 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.8414654\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.174683\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cem\u003eNote: Trace test indicates 1 cointegrating equation(s) at the 0.05 level\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cem\u003e* denotes rejection of the hypothesis at the 0.05 level\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cem\u003e**MacKinnon-Haug-Michelis (1999) p-values\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cem\u003eSource: Author\u0026rsquo;s Computation\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4.4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eLong- and Short-run Effects of Exchange Rate Volatility and Inflation Rate, (FDI)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e\u003cp\u003eCoefficient\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eStd. Error\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003et-Statistic\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eLFDI(\u0026ndash;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e\u003cp\u003e1.000000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eNil\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eNil\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eEXR(\u0026ndash;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e\u003cp\u003e0.010092\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e0.003338\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e3. 02289\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eINFR(\u0026ndash;1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e\u003cp\u003e0.061279\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e0.009564\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e6.40711\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e\u003cp\u003e-22.984526\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eNil\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eNil\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eError Correction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e\u003cp\u003eD(LFDI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eCoefficient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eStd. Error\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003et-Statistic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eECM(-1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e\u0026ndash;0.503048\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e0.129619\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e\u0026ndash;3.880970\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eD(LFDI(\u0026ndash;1))\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e\u0026ndash;0.218719\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e0.161947\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e\u0026ndash;1.350570\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eD(LFDI(\u0026ndash;2))\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e0.035566\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e0.148400\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e0.239670\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eD(EXR(\u0026ndash;1))\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e\u0026ndash;0.000630\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e0.002560\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e\u0026ndash;0.247950\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eD(EXR(\u0026ndash;2))\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e\u0026ndash;0.001480\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e0.002560\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e\u0026ndash;0.578170\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eD(INFR(\u0026ndash;1))\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e0.027200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e0.006780\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e4.013880\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eD(INFR(\u0026ndash;2))\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e0.016070\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e0.008260\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e1.946220\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e0.065760\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e0.088770\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003e0.740760\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eStatistic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eValue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c10\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eR-squared\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0.278711\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c10\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eAdjusted R-squared\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0.076750\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c10\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eF-statistic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e1.380028\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c10\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eS.E. of regression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0.630351\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c10\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e\u003cp\u003eLog likelihood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e-27.01527\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c10\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003cem\u003eSource: Author\u0026rsquo;s Computation\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe result from Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4.4\u003c/span\u003e confirms that in long-run a one percent increase in exchange rate volatility and inflation increases foreign direct investment by 0.01 and 0.06 percent respectively, while in the short-run a one percent increase in exchange rate volatility and inflation rate reduces and increases foreign direct investment by 0.001 and 0.03 percent respectively. These effects are significant both in the short run and long run except that of the exchange rate volatility that is not significant in the short run. The error correction term (ECM(-1)) is negative at the 1 percent level, and the coefficient value is \u0026minus;\u0026thinsp;0.503048. This is evidence that approximately 50 percent of any long run disequilibrium in FDI is corrected within one period. In other words, foreign investment flows in Nigeria exhibit a strong tendency to revert toward equilibrium following macroeconomic disturbances.\u003c/p\u003e\u003cp\u003eThis is consistent with the work of Akinlo (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), which cited that FDI in the country is sector-specific and profitability-based rather than macroeconomic stability-based. Investor response to volatility might be dampened with adequate promised payoffs as the finding in the work of Iseolorunkanmi et al., (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) shows. Same finding was also seen in the work of Warren, Seetanah, and Sookia (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), in which exchange rate volatility propelled FDI inflows positively according to their gravity model estimation, which espouses the view that foreign investors perceive volatility as an indicator of market activity or speculation, and hence, take FDI inflows positively.\u003c/p\u003e\u003cp\u003eAdditionally, inflation rate has a positive effect on FDI, this means that higher FDI inflows are followed by higher inflation. This is an unexpected finding, as the hypothesis according to economic principles is that higher inflation leads to reduced real returns and hence decreases FDI inflows. But the result may indicate the capability of the investors in the Nigerian experience to hedge the price or terms of contract of the inflationary risks. Otherwise, the result may indicate periods of moderate inflation that coincide with economic growth periods, which attracts capital flows. There is an argument used in some parts of the recent literature that in developing countries, inflation may indicate domestic demand expansion or price mark-ups that attract foreign investors. For example, Agudze and Ibhagui (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) observed that inflation was positively related to FDI in the select developing economies, and the suggestion is that foreign investors may accommodate inflationary sentiments if the prospects of profitability remain strong.\u003c/p\u003e\u003cp\u003eWhile the relationship direction is the reverse of ex ante expectation, statistical significance, with OLS-based re-estimation diagnostic help, is strong. They emphasize the need for the FDI behaviour explanation to be in the structural realities of the country, and not an application of large macroeconomic models strictly. The intercept is captured negatively, with the constant term.\u003c/p\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e4.2 The Causality Test\u003c/h2\u003e\u003cp\u003eTo assess the direction of causality among the variables, the VEC Granger Causality/Block Exogeneity Wald test was employed. This test helps determine whether lagged values of one variable provide statistically significant information in forecasting another variable, within the context of the Vector Error Correction Model.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4.5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eGranger Causality Test\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDependent Variable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExcluded Variable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eChi-square\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003edf\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eProb.\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eConclusion\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eD(LFDI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eD(EXR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.3954\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.8206\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNo causality\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eD(INFR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.5659\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eINFR \u0026rarr; LFDI (Significant)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eD(EXR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eD(LFDI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0112\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.9944\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNo causality\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eD(INFR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.2207\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0735\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eINFR \u0026rarr; EXR (Weak significance)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eD(INFR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eD(LFDI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.1050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.2117\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNo causality\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eD(EXR)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.9649\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.6172\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNo causality\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003eSource: Author\u0026rsquo;s Computation\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eFrom the result in table 4. 5, Inflation Granger-causes FDI at 1% significance value. It signifies there is presence of relevance of past values of inflation in FDI inflows in Nigeria. It confirms earlier discovery in VECM estimation of inflation as significantly determining FDI in long-run as well as in short-run. There is weak evidence (10% test) that inflation Granger-causes exchange rate volatility, thus some impact of change in domestic price on change in exchange rate but not particularly large. The result did not reveal any causal influence between exchange rate volatility FDI, nor FDI Granger-causing exchange rate volatility or inflation.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusion and Recommendations","content":"\u003cp\u003eThe study investigated the short-run and long-run effects of exchange rate volatility and inflation on foreign direct investment (FDI) in Nigeria from 1986 to 2023. Employing the Vector Error Correction Model (VECM). This study concludes that, the long-run estimates exhibited a statistically significant and positive connection between exchange rate volatility and FDI. Conversely, the short-run exchange rate volatility coefficients were insignificant. Correspondingly, inflation registered a positive and statistically significant relationship with FDI both in the long- and short-run, this was also complimented by the causal influence result. Although, this result is contrary to the hypothesis that it decreases the volatility of real pay and investment but aligns with the result of Omolade and Ngalawa (2018), which is that inflation is always non-deterrent to FDI, especially with the efficacy of liberalises policy or growth prospects. Iseolorunkanmi et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) further hold that investor decision in Nigeria is rather guided more with the aid of structural possibilities and hypothesized profitability rather than macro volatilities.\u003c/p\u003e\u003cp\u003eBased on the findings of the study, it's recommended that the exchange rate should be kept stable in Nigeria to motivate foreign investors\u0026rsquo; confidence even if the result shows its positive response by FDI. More importantly, the results indicated that foreign direct investment (FDI) responded positively despite the increase in Nigeria's inflation rate over the years. The monetary authorities should be cautious in relying on this by knowing the threshold through inflation targeting policies in Nigeria. Based on this, the study recommended that the exchange rate should be kept stable in Nigeria in order to motivate foreign investors\u0026rsquo; confidence even if the result shows its positive response by FDI. More importantly, the result showed a positive response by the FDI in light of the increase in inflation rate in Nigeria over the years. The monetary authorities should be very careful in relying on this by knowing the threshold through inflation targeting policies in Nigeria.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAdewale, A. M., Olopade, B. C., \u0026amp; Ogbaro, E. O. (2024). Effect of exchange rate on foreign direct investment in Nigeria. ABUAD Journal of Social and Management Sciences, 5(2), 302-318.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eAgudze, K., \u0026amp; Ibhagui, O. (2021). Inflation and FDI in industrialized and developing economies. International Review of Applied Economics, 35(5), 749-764.\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eAkinlo, A. E. (2004). Foreign direct investment and growth in Nigeria: An empirical investigation. Journal of Policy Modeling, 26(5), 627\u0026ndash;639. \u003c/strong\u003ehttps://doi.org/10.1016/j.jpolmod.2004.04.011Akinlo, A. E., \u0026amp; Gbenga Onatunji, O. (2021). Exchange rate volatility and foreign direct investment in selected West African countries. \u003cem\u003eThe International Journal of Business and Finance Research, 15\u003c/em\u003e(1), 77-88.\u003c/li\u003e\n\u003cli\u003eAsmae, A., \u0026amp; Ahmed, B. (2019). Impact of the exchange rate and price volatility on FDI inflows: Case of Morocco and Turkey. \u003cem\u003eApplied Economics and Finance, 6\u003c/em\u003e(3), 87-104.\u003c/li\u003e\n\u003cli\u003eBamidele, K. (2024). Impact of Exchange Rate Volatility on Foreign Portfolio Investment in Nigeria (1986-2023). \u003cem\u003eAvailable at SSRN 4954853\u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eDal Bianco, S., \u0026amp; Loan, N. C. T. (2017). FDI inflows, price and exchange rate volatility: New empirical evidence from Latin America. \u003cem\u003eInternational Journal of Financial Studies, 5\u003c/em\u003e(1), 6.\u003c/li\u003e\n\u003cli\u003eHniya, S., Boubker, A., Mrad, F., \u0026amp; Nafti, S. (2021). The impact of real exchange rate volatility on foreign direct investment inflows in Tunisia. \u003cem\u003eInternational Journal of Economics and Financial Issues, 11\u003c/em\u003e(5), 52.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eIseolorunkanmi, O. J., Rotimi, E. M., Babatunde, O. O., Ake, M. B., Umar, A. P., Ahmed, A. V., \u0026amp; Akinojo, I. C. (2023). An Assessment of the Impact of Foreign Direct Investment on Industrial Performance in Nigeria. Journal of Management and Corporate Governance, 15(1), 63-84.\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003eKombo, I. S., \u0026amp; Isah, N. S. A. (2024). STRUCTURAL ADJUSTMENT PROGRAMME AND REVAMPING OF NIGERIA\u0026rsquo;S ECONOMY TOWARDS SELF-RELIANCE AND GROWTH\u003c/li\u003e\n\u003cli\u003eMostafa, M. M. (2020). Impacts of inflation and exchange rate on foreign direct investment in Bangladesh. \u003cem\u003eInternational Journal of Science and Business, 4\u003c/em\u003e(11), 53-69.\u003c/li\u003e\n\u003cli\u003eNikonenko, U., Shtets, T., Kalinin, A., Dorosh, I., \u0026amp; Sokolik, L. (2022). Assessing the Policy of Attracting Investments in the Main Sectors of the Economy in the Context of Introducing Aspects of Industry 4.0. \u003cem\u003eInternational Journal of Sustainable Development \u0026amp; Planning\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(2).\u003c/li\u003e\n\u003cli\u003eOkeke, D. C., \u0026amp; Nwafor, C. J. (2022). Economic impact of inflation and interest rate on life annuity business in Nigeria. \u003cem\u003eBritish International Journal of Applied Economics, Finance and Accounting\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e(3)\u003c/li\u003e\n\u003cli\u003eRahimian, F., Renani, H. S., \u0026amp; Ghobadi, S. (2022). The Impact of Exchange Rate and Investor Confidence Uncertainty on Monetary and Economic Uncertainty in Iran. \u003cem\u003eJournal of Money and Economy\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(1), 115-136.\u003c/li\u003e\n\u003cli\u003eRamzan, M. (2021). Symmetric impact of exchange rate volatility on foreign direct investment in Pakistan: Do the global financial crises and political regimes matter? \u003cem\u003eAnnals of Financial Economics, 16\u003c/em\u003e(04), 2250007\u003c/li\u003e\n\u003cli\u003eSayek, S. (2009). Foreign direct investment and inflation. *Southern Economic Journal, 76*(2), 419-443. \u003c/li\u003e\n\u003cli\u003eTsaurai, K. (2018). Investigating the impact of inflation on foreign direct investment in Southern Africa. *Acta Universitatis Danubius. \u0026OElig;conomica, 14*(4), 597-611. \u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eUdo, O. C., \u0026amp; Idochi, O. (2024). SIMPLE REGRESSION MODELS: A COMPARISON USING CRITERIA MEASURES.\u003c/strong\u003e\u003c/li\u003e\n\u003cli\u003eUdoh, E., \u0026amp; Egwaikhide, F. O. (2008). Exchange rate volatility, inflation uncertainty and foreign direct investment in Nigeria. \u003cem\u003eBotswana Journal of Economics, 5\u003c/em\u003e(7), 14-31.\u003c/li\u003e\n\u003cli\u003eValli, M., \u0026amp; Masih, M. (2014). Is there any causality between inflation and FDI in an \u0026lsquo;inflation targeting\u0026rsquo; regime? Evidence from South Africa. \u003c/li\u003e\n\u003cli\u003eVasileva, I. (2018). The effect of inflation targeting on foreign direct investment flows to developing countries. *Atlantic Economic Journal, 46*, 459-470. \u003c/li\u003e\n\u003cli\u003eWarren, M., Seetanah, B., \u0026amp; Sookia, N. (2023). An investigation of exchange rate, exchange rate volatility and FDI nexus in a gravity model approach. \u003cem\u003eInternational Review of Applied Economics, 37\u003c/em\u003e(4), 482-502.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"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":"Exchanger rate volatility, inflation, FDI, VECM, Co-integration","lastPublishedDoi":"10.21203/rs.3.rs-7963423/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7963423/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigated how exchange rate volatility and inflation rates affect foreign direct investment in Nigeria, as well as the causal relationships among these factors from 1986 to 2023. Annual time series data were obtained from the Central Bank of Nigeria and the World Bank. Exchange rate volatility was measured using a five-year rolling standard deviation of the naira\u0026ndash;dollar exchange rate. The Vector Error Correction Model (VECM) was employed in obtaining the effects, while the VEC Granger Causality/Block Exogeneity Wald test was used in investigating their causal influences. To allow for residual diagnostics, the short-run equations of the VECM were re-estimated using Ordinary Least Squares (OLS). The result showed exchange rate volatility has a negative effect on the foreign direct investment in the short run but positive effects in the long run, while inflation has a positive effect on exchange rate volatility both in the long run and in the short run. The result further showed that inflation Granger-causes FDI and there is weak evidence that inflation Granger-causes exchange rate volatility (10% test). Based on the findings, the study concluded that monetary authorities should exercise caution in their reliance on these results by identifying the threshold for inflation targeting policies in Nigeria.\u003c/p\u003e","manuscriptTitle":"Exchange Rate Volatility, Inflation Rate and Foreign Direct Investment in Nigeria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-04 09:38:50","doi":"10.21203/rs.3.rs-7963423/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":"c475e576-88c7-4e54-92fd-b45c3af237bb","owner":[],"postedDate":"November 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56977828,"name":"Macroeconomics"}],"tags":[],"updatedAt":"2025-11-04T09:38:50+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-04 09:38:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7963423","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7963423","identity":"rs-7963423","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}