ĐĎॹá>ţ˙ ĚÎţ˙˙˙ĘË˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙ěĽÁM đż°<bjbjâ=â= "ž€W€Wb8M˙˙˙˙˙˙lppppppp„ô5ô5ô58,64`6L„łÍ<¸7¸7:ň7ň7ň7Í8Í8Í82Í4Í4Í4Í4Í4Í4Í$ďÎ ŃXÍpÍ8Í8Í8Í8Í8XÍCppň7ň7ŰmÍCCCÍ8Śpň7pň72ÍCÍ82ÍCzC‘Jć2šđppĆň7Ź7 °Žîć"„p4ô5s9J"ž„Ć$ƒÍ0łÍŚžhŇ˝AZŇĆC„„ppppŮMidterm—Sample Economics 173 Name_____________ Fall 2001 Instructor: Petry SSN______________ 1. Given the following t-statistics (23 degrees of freedom) and p-values (1 tailed); t-statistic: 1.7 ( p-value .05 t-statistic: 1.2 ( p-value .121 t-statistic: 2.1 ( p-value .023 What is the p-value for the t-statistic 1.3? .141 .103 .042 .013 .461 2. When comparing the proportions of two populations, what type of test statistic is used? z t F all of the above none of the above 3. Given a population standard deviation of 13, a sample mean of 40, and a confidence interval width of 10, and a critical value of 1.645, what is the sample size? 4 5 6 7 8 4. If the p-value for a test is .4 then your decision is: there is sufficient evidence to conclude the alternative is correct. there is sufficient evidence to conclude the null is correct. there is insufficient evidence to conclude the alternative is correct. there is insufficient evidence to conclude neither is correct. none of the above 5. Which of the following statements are equivalent? Alpha Beta Probability of a Type I error Probability of a Type II error Probability of Rejecting a true null I and IV I and III I and III and V II and V II and IV and V 6. The 95% confidence interval for the population average final exam score is [126.4, 195.5]. To test the claim that the average final exam score of the population is 180 at a 3% level of significance, what will be your decision? reject the null – conclude it is not 180 fail to reject the null – insufficient evidence to conclude it is not 180 reject the null – conclude it is 180 fail to reject the null – sufficient evidence to conclude it is not 180 cannot decide based on the given information 7. When doing a matched pairs test with differences distributed normally and unknown population standard deviation, which is the correct test statistic? equal variances pooled t test for means unequal variances pooled t test for means single population means test on the difference none of the above any of the above will work 8. If you wish to know if more than 45% of the class scored above 70% on the exam, what is your null hypothosis? H0: p=0.7 H0: p=0.45 H0: p>0.7 H0: p>0.45 any of the above will work 9. Suppose we are interested in whether the mean scores on the midterm for Economics 173 is below 80%. Given a p-value of .11 what is your conclusion? fail to reject the null at any reasonable level of significance cannot determine based on the given information reject the null at any reasonable level of significance fail to reject the null only if the significance level is .01 reject the null only if the significance level is .01 Given the following list of observations: 1, 10, 34, 15, 8, 40, 90, 41, 5, 16. What proportion is above 8? .4 .5 .6 .7 .8 11. Before running an equal variances pooled t-test, what test should you run to formally decide if the needed assumptions are correct? F-test for variances t-test for variances z-test for variances no need to run a test eyeball test A pharmaceutical company currently produces an anesthetic whose effective time is normally distributed with mean 7.4 and standard deviation 1.2. It is considering the launch of a new drug that they believe has a lower mean effective time but the same standard deviation. In a clinical study meant to test their belief, what would be the appropriate null and alternative hypothesis? Ho: ( > = 7.4, H1: ( < 7.4 Ho: ( > 7.4, H1: ( < =7.4 Ho: ( = 7.4, H1: ( ( 7.4 Ho: ( < = 7.4, H1: ( > 7.4 Irrespective of your answer in the last question suppose that you intend to do a two-sided test. You collect a sample and compute the sample mean. In order to reject the null hypothesis at a 10% level of significance, using a Z statistic of 1.645, and a sample size of 25, you need the sample mean to be smaller than 7.01 you need the sample mean to be greater than 7.79 both of the above none of the above The mean of a sample is computed to be –0.301. It has been found out that the p-value is 0.275 when testing Ho: ( = 0 against the two sided alternative H1: ( ( 0. To test Ho: ( = 0 against the one sided alternative H1: ( < 0 at a significance level of 0.5, we will have: a p-value of 0.275 and therefore reject the null hypothesis a p-value of 0.138 and therefore reject the null hypothesis a p-value of 0.862 and therefore accept the null hypothesis a p-value of 0.5 and therefore the test results will be inconclusive. The following table presents the summary statistics from a sample of 24 exam scores, expressed in percentages. ScoreMean75.66667Standard Error1.782226Median73Mode73Standard Deviation8.731087Sample Variance76.23188Kurtosis0.646501Skewness1.303676Range30Minimum66Maximum96Sum1816Count24Confidence Level(95.0%)3.68681 In order to do a test where the null hypothesis specifies the population mean to be equal to 70, the t-distribution should be used to get a test statistic equal to 3.18 the z-distribution should be used to get a test statistic equal to 3.18 not enough information is given to calculate the test statistic a pooled variance t-test should be used Based on a 95 % confidence interval, if you tested Ho: ( = 70, H1: ( ( 70, you would: not be able construct the confidence interval due to lack of information. Accept the null hypothesis Reject the null hypothesis Reformulate a one sided hypothesis instead. The pooled variance t-test is based on the following assumption(s): that the two populations be independent that the two populations have approximately equal variances that both populations be normal all of the above A truck manufacturer has two plants, one in Champaign and one in Urbana. The CEO of this company suspects that the Urbana plant is more efficient (in terms of number of trucks produced each month) than the Champaign one. Let Champaign be plant 1 and Urbana be plant 2 . Then the test should be specified as: H0: (1-(2 = 0, H1: (1-(2 ( 0 H0: (1-(2 = 0, H1: (1-(2 < 0 H0: (1-(2 = 0, H1: (1-(2 > 0 H0: (1-(2 < 0, H1: (1-(2 > 0 For the scenario described above, monthly production data was collected from both plants for a year and a pooled variance t-test was performed at the 5% significance level. The results of the test are presented below.  CHAMPAIGNURBANAMean57.7555.66667Variance5.84090909113.15152Observations1212Pooled Variance9.496212121Hypothesized Mean Difference0df22t Stat1.655995622P(T<=t) one-tail0.055959227t Critical one-tail1.717144187P(T<=t) two-tail0.111918455t Critical two-tail2.073875294  Based on the correct answer to the last question, The p-value is 0.056 so we do not reject the null hypothesis The p-value is 0.112 so we do not reject the null hypothesis The p-value is 0.888 so we do not reject the null hypothesis The p-value is 0.944 so we do not reject the null hypothesis. The test for difference in proportions between two populations uses the z-distribution the f-distribution the t-distribution both a and b Suppose a record store chain (Badidea cd’s) is running a promotion for the new Grand Funk Railroad anthology that was released last summer. Badidea cd’s would like to know whether or not the promotion that it ran was successful or not based on it’s own sales (23 stores) of the anthology before and after the promotion. In order to test this hypothesis which of the following tests should be used? pooled variance t-test assuming equal variances pooled variance t-test assuming unequal variances paired sample t-test z test for difference in means z test for difference in proportions Suppose two record store chains are both running a promotion for the re-release of Mike and the Mechanics Reggae Christmas album that was released last August. Badidea cd’s (23 stores) would like to know if it’s store sold a significant amount more than its competition Dave’s Unbelievable Music Bin (DUMB) (18 stores). In order to test this which of the following tests would be the most appropriate? pooled variance t-test assuming equal variances F test for difference in variance z test for difference in proportions t-test for population mean paired sample t-test A poll was taken recently on the UI campus asking students whether or not they support military action to solve world conflict. Suppose you believe that men and women answer this question differently. In order to test your hypothesis that men would answer “Yes, I support military action” more often that women, which of the following tests could you perform? pooled variance t-test assuming equal variances pooled variance t-test assuming unequal variances paired sample t-test z test for difference in means z test for difference in proportions A poll was taken recently on the UI campus asking students whether or not they support military action to solve world conflict. Suppose you believe that the percentage of students who support military action is more than half. In order to test this hypothesis which of the following tests could you perform? z test for difference in proportions t-test for population mean F test for difference in variance z test for population proportion pooled variance t-test assuming equal variances A professor studying “grade inflation” (the upward trend in letter grades in most college courses) believes that the upward trend in grades is accompanied by a greater uncertainty (ie wider dispersion or spread) of letter grades. To test whether or not there is more uncertainty in letter grades, which of the following tests could be performed? z test for difference in proportions t-test for population mean F test for difference in variance z test for population proportion pooled variance t-test assuming equal variances In the simple linear regression model, the intercept and slope coefficients are computed by minimizing, SSE the sum of the squared discrepancies between the observed values and its conditional mean the sum of the squared discrepancies between the predicted values and the conditional means both a and b both b and c Use the following Excel output to answer the following questions. (Note: some parts left blank) SUMMARY OUTPUTRegression StatisticsMultiple R0.164737873R Square0.027138567Adjusted R Square0.017109068Standard Error6.982167345Observations99ANOVA dfSSMSFSignificance FRegression1131.9131721131.91317212.7058745430.103216227Residual97Total4860.727273    CoefficientsStandard Errort StatP-valueLower 95%Intercept10.003685570.87224302511.468920129.40437E-208.272525588X Variable 1-0.2317716260.140898523-1.6449542680.103216227-0.511416034 Based on the Excel output what is the value for the total degrees of freedom? 99 98 1 97 0 Based on the Excel output what is the value of MSE? 4728.81 4992.64 48.75 356.94 not enough information to answer Based on the Excel output what is the correct interpretation for the slope coefficient? For every 1-unit change in X, the expected average change in Y is –0.23 units. For every 1-unit increase in X, the expected average change in Y is –0.23 units. For every 1-unit increase in X, the expected average change in Y is 10.00 units. For every –0.23 unit decrease in X, the expected average change in Y is 1 unit. For every 1-unit increase in Y, the expected average change in X is –0.23 units. Based on the Excel output what is the value of the appropriate test statistic for testing whether or not X has a significant effect on Y? 11.47 –1.64 0.027 0.103 none of the above Calculate the mean of the following array: 20 24 29 54 65 78 40 45 50 55 65 What is the median salary of the following array: 20 24 29 54 65 78 29 38 41.5 46.7 66 If the distribution is symmetrical, which of the following are equivalent? the mean and median the mode and the median the mean and the mode the mean, the mode, and the median none of the above The range of the measurements is: the difference between the smallest and largest measurements the test statistic as measured in Excel the average of all measurements the number of measurements the difference between the mean and the test statistic The variance is: 2 times the standard deviation the square root of the standard deviation the absolute value of the standard deviation the standard deviation squared none of the above Find the variance (in years) of the following array: 3.4, 2.5, 4.1, 1.2, 2.8, 3.7 1 1.05 1.275 2.95 1.075 Which of the following are true regarding the standard deviation: can be used to compare the variability of several distributions make a statement about the shape of the distribution contains 68% of the measurements within 1 and –1 standard deviations contains 95% of the measurements within 2 and –2 standard deviations all of the above Covariance determines: the strength of the linear relationship between two variables if there is any pattern to the way the two variables move together the shape of the distribution the size of the population being measured both a and b. If two variables are strongly and positively correlated, the coefficient value will be close to: 0 .5 –1 1 .2 What is the 95% confidence interval (Z= 1.96), for a mean of 7.8, a population standard deviation of 3, and a sample of 85: 7.0651, 8.5554 7.1622, 8.4377 6.9749, 7.8846 7.2432, 8.5094 7.2321, 8.6858 The width of the interval estimator is a function of: the population standard deviation the sample size the confidence level all of the above none of the above Increasing the sample size: decreases the width of the interval estimator increases the width of the interval estimator changes the confidence interval leads to exactly the same standard deviation none of the above What sample size is required for a machine to be precise within 1 inch with 95% confidence (Z = 1.96)? 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Ć„Đ„Đ^„Đ & F& Ć  ŕŔ!Đ„„^„`„ & F- Ć„Đ„Đ^„Đ,,,,,,,,oiiiiii$If$$If”˙ֈ¸đ  Řü˜"'¨˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙'(˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙' ˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙'(˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙'˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙'Œ˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙ö8"6Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙4Öaö,,2,3,4,5,6,olf````$If $$Ifa$$$If”ֈ¸đ  Řü˜"#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙ö8"6Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙4Öaö6,7,B,N,O,P,Q,R,‚p|s|||| $$Ifa$$If}$$If”˙Örđ  Řü˜"#˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙ö8"6Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙4ÖaöR,S,\,h,i,j,k,l,m,,‹,Œ,ohi`iiiioŒi`i $$Ifa$$If$$If”˙ֈ¸đ  Řü˜"#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙ö8"6Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙4Öaö Œ,,Ž,,,Ÿ,Ť,Ź,­,Ž,Ż,°,ůůůi€ů`ůůůůiT $$Ifa$$$If”˙ֈ¸đ  Řü˜"#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙ö8"6Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙4Öaö$If °,˝,Ŕ,Á,Â,Ă,Ä,Ĺ,Ć,Ç,Č,É,ůđůůůů`ůůůů$$If”ֈ¸đ  Řü˜"#˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙ö8"6Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙4Öaö $$Ifa$$If ż,Ä,Ĺ,Ë,Ě,Ń,×,Ř,Ů,Ú,Ü,Ý,ß,ŕ,â,ă,ä,ĺ,ó,ô,ő,˙,--- ----%-&-1-2-3-;-<->-C-D-I-K-V-W-X-Y-Z-[-\-]-^-d-e-f-g-s-t-‚-ƒ-‰-Š-‘-’-›-œ--Ś-§-˛-ł-ž-ż-Ę-Ë-Ö-×-â-ă-ä-đ-óîóîăóîŐĹŐĹŐĹŐĹŐĹŐĹîăóăóăóăóăóăóîăóăóîăóăóăóăóăóîóîŐĹŐĹŐĹŐĹŐĹŐĹîăóăóăóăóăóăóîă6CJOJPJQJ]^JaJ6CJOJQJ]^JaJCJOJQJ^JaJCJaJCJOJPJQJ^JaJNÉ,Ę,Ë,Ě,Ň,Ó,Ô,Ő,Ö,×,ůůi0ůůůůůů$$If”˙ֈ¸đ  Řü˜"#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙ö8"6Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙4Öaö$If ×,Ř,Ú,Ý,ŕ,ă,ĺ,ô,otffffff $$Ifa$$$If”ֈ¸đ  Řü˜"#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙ö8"6Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙4Öaöô,ő,----&-2-oři````` $$Ifa$$If$$If”˙ֈ¸đ  Řü˜"#˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙ö8"6Ö˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙4Öaö2-3-<-?-@-A-B-C-D-J-K-oDi``Wiiohi` $$Ifa$ $$Ifa$$If$$If”˙ֈ¸đ  Řü˜"#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙ö8"6Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙4Öaö K-W-Y-[-]-^-_-`-a-b-c-d-öđđđ`đđđđđđ$$If”ֈ¸đ  Řü˜"#˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙ö8"6Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙4Öaö$If $$Ifa$ d-e-g-t-ƒ-Š-’-œ-oŕffffff $$Ifa$$$If”ֈ¸đ  Řü˜"#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙ö8"6Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙4Öaöœ--§-ł-ż-Ë-×-ă-oi````` $$Ifa$$If$$If”˙ֈ¸đ  Řü˜"#˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙ö8"6Ö˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙4Öaöă-ä-ń-ţ- ..#.0.o4i````` $$Ifa$$If$$If”˙ֈ¸đ  Řü˜"#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙ö8"6Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙4Öaöđ-ń-ý-ţ- . ...".#./.0.1.;;b<c<m<n<‡<ˆ<<<–<—<˜<™<<ž<¨<Š<Ť<Ź<°<óčóčóčóčóčóăŢŮŮÓŮŮŮÓŮŮŮÓŮ mHnHu jU 5>*\CJaJCJOJQJ^JaJCJOJPJQJ^JaJ!0.1.2.3..‚.….‰.ommXRDD & F/ Ć„Đ„Đ^„Đ ĆŕŔ! & F& Ć ŕŔ!Đ„„^„`„$$If”ֈ¸đ  Řü˜"#˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙#˙˙˙˙˙˙˙˙˙˙˙˙ö8"6Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙Ö˙˙˙˙˙˙Ö˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙˙4Öaö‰.‹.Ž..‘.’.“.Ç.Č.Đ.Ř.ß.ć.//`/a/°/0S0Ł0ô0ńńńëëë×ŐÇÇÇÇÇŐ×Őššššš & F1 Ć„Đ„Đ^„Đ & F0 Ć„Đ„Đ^„Đ & F& Ć  ŕŔ!Đ„„^„`„„ź^„ź & F/ Ć„Đ„Đ^„Đô0ő01€1†11“1™1Ť1Ź1é1ę1í1ń1ô1÷1ú1ű1?2@2C2ýéáÓÓÓÓÓýéÍżżżżżýéý˛ & F4 Ć„„Đ^„Đ & F3 Ć„Đ„Đ^„Đ ĆŕŔ! & F2 Ć„Đ„Đ^„Đ Ć ŕŔ! & F& Ć  ŕŔ!Đ„„^„`„C2F2L2Q2T2U2 2Ą2ś2Î2ä2333=3>3|3¤3Ä3ß344ňňňňěŘÖČČČČČÖŘÖşşşşşÖ & F6 Ć„Đ„Đ^„Đ & F5 Ć„Đ„Đ^„Đ & F& Ć  ŕŔ!Đ„„^„`„ ĆŕŔ! & F4 Ć„„Đ^„Đ4(4)4H4r4Ÿ4ż4Ń4Ň4$5%5'5,52575>5?55‚5Ă5ř5=6ëĺ×××××ŐëŐÇÇÇÇÇŐëĺššš & F9 Ć„Đ„Đ^„Đ & F8 Ć„Đ„Đ^„Đ & F7 Ć„Đ„Đ^„Đ ĆŕŔ! & F& Ć  ŕŔ!Đ„„^„`„=6‚6“6”6•6Ź6­6ë6/7M7w7…7†7ç7č7ę7í7đ7ň7ő7ö7r8ńńďďŰŐÇÇÇÇÇďŰďšššššŐŰ & F; Ć„Đ„Đ^„Đ & F: Ć„Đ„Đ^„Đ ĆŕŔ! & F& Ć  ŕŔ!Đ„„^„`„ & F9 Ć„Đ„Đ^„Đr8s8‚8’8Ą8°8ż8Ŕ8ö8÷89)9>9P9b9c99€9Ż9Ý9ý9*:<:ýďďďďďýŰýÍÍÍÍÍýŰýżżżżż & F> Ć„Đ„Đ^„Đ & F= Ć„Đ„Đ^„Đ & F& Ć  ŕŔ!Đ„„^„`„ & F< Ć„Đ„Đ^„Đ<:=:ű:ü:;;; ; ;;;;+;:;I;X;g;v;…;”;Ł;ł;Ă;Ó;ă;ó;ýéýŰŰŰŰŰýýýýýýýýýýýýýýýýý & F? 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`„˜ţ.h„Ä„˜ţĆÄ^„Ä`„˜ţ.’h„”„L˙Ć”^„”`„L˙.h„d„˜ţĆd^„d`„˜ţ.h„4„˜ţĆ4^„4`„˜ţ.’h„„L˙Ć^„`„L˙.„Đ„˜ţĆĐ^„Đ`„˜ţo()€„ „˜ţĆ ^„ `„˜ţ.‚„p„L˙Ćp^„p`„L˙.€„@ „˜ţĆ@ ^„@ `„˜ţ.€„„˜ţĆ^„`„˜ţ.‚„ŕ„L˙Ćŕ^„ŕ`„L˙.€„°„˜ţĆ°^„°`„˜ţ.€„€„˜ţĆ€^„€`„˜ţ.‚„P„L˙ĆP^„P`„L˙.„Đ„0ýĆĐ^„Đ`„0ýo()„Đ„˜ţĆĐ^„Đ`„˜ţo(.€„ „˜ţĆ ^„ `„˜ţ.‚„p„L˙Ćp^„p`„L˙.€„@ „˜ţĆ@ ^„@ `„˜ţ.€„„˜ţĆ^„`„˜ţ.‚„ŕ„L˙Ćŕ^„ŕ`„L˙.€„°„˜ţĆ°^„°`„˜ţ.€„€„˜ţĆ€^„€`„˜ţ.‚„P„L˙ĆP^„P`„L˙.„Đ„˜ţĆĐ^„Đ`„˜ţo(.€„ „˜ţĆ ^„ `„˜ţ.‚„p„L˙Ćp^„p`„L˙.€„@ „˜ţĆ@ ^„@ `„˜ţ.€„„˜ţĆ^„`„˜ţ.‚„ŕ„L˙Ćŕ^„ŕ`„L˙.€„°„˜ţĆ°^„°`„˜ţ.€„€„˜ţĆ€^„€`„˜ţ.‚„P„L˙ĆP^„P`„L˙.„Đ„˜ţĆĐ^„Đ`„˜ţo(.€„ „˜ţĆ ^„ `„˜ţ.‚„p„L˙Ćp^„p`„L˙.€„@ „˜ţĆ@ ^„@ `„˜ţ.€„„˜ţĆ^„`„˜ţ.‚„ŕ„L˙Ćŕ^„ŕ`„L˙.€„°„˜ţĆ°^„°`„˜ţ.€„€„˜ţĆ€^„€`„˜ţ.‚„P„L˙ĆP^„P`„L˙.h„„„˜ţĆ„^„„`„˜ţ.h„T„˜ţĆT^„T`„˜ţ.’h„$ „L˙Ć$ ^„$ `„L˙.h„ô „˜ţĆô ^„ô `„˜ţ.h„Ä„˜ţĆÄ^„Ä`„˜ţ.’h„”„L˙Ć”^„”`„L˙.h„d„˜ţĆd^„d`„˜ţ.h„4„˜ţĆ4^„4`„˜ţ.’h„„L˙Ć^„`„L˙.„Đ„˜ţĆĐ^„Đ`„˜ţo()„„0ýĆ^„`„0ýo()‚„p„L˙Ćp^„p`„L˙.€„@ „˜ţĆ@ ^„@ 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`„˜ţ.€„„˜ţĆ^„`„˜ţ.‚„ŕ„L˙Ćŕ^„ŕ`„L˙.€„°„˜ţĆ°^„°`„˜ţ.€„€„˜ţĆ€^„€`„˜ţ.‚„P„L˙ĆP^„P`„L˙.„„„˜ţĆ„^„„`„˜ţo(.„T„˜ţĆT^„T`„˜ţ.„$ „L˙Ć$ ^„$ `„L˙.€„ô „˜ţĆô ^„ô `„˜ţ.€„Ä„˜ţĆÄ^„Ä`„˜ţ.‚„”„L˙Ć”^„”`„L˙.€„d„˜ţĆd^„d`„˜ţ.€„4„˜ţĆ4^„4`„˜ţ.‚„„L˙Ć^„`„L˙.h„„„˜ţĆ„^„„`„˜ţ.h„T„˜ţĆT^„T`„˜ţ.’h„$ „L˙Ć$ ^„$ `„L˙.h„ô „˜ţĆô ^„ô `„˜ţ.h„Ä„˜ţĆÄ^„Ä`„˜ţ.’h„”„L˙Ć”^„”`„L˙.h„d„˜ţĆd^„d`„˜ţ.h„4„˜ţĆ4^„4`„˜ţ.’h„„L˙Ć^„`„L˙.„Đ„0ýĆĐ^„Đ`„0ýo()h„„„˜ţĆ„^„„`„˜ţ.h„T„˜ţĆT^„T`„˜ţ.’h„$ „L˙Ć$ ^„$ `„L˙.h„ô „˜ţĆô ^„ô `„˜ţ.h„Ä„˜ţĆÄ^„Ä`„˜ţ.’h„”„L˙Ć”^„”`„L˙.h„d„˜ţĆd^„d`„˜ţ.h„4„˜ţĆ4^„4`„˜ţ.’h„„L˙Ć^„`„L˙.„Đ„˜ţĆĐ^„Đ`„˜ţo()€„ „˜ţĆ ^„ `„˜ţ.‚„p„L˙Ćp^„p`„L˙.€„@ „˜ţĆ@ ^„@ `„˜ţ.€„„˜ţĆ^„`„˜ţ.‚„ŕ„L˙Ćŕ^„ŕ`„L˙.€„°„˜ţĆ°^„°`„˜ţ.€„€„˜ţĆ€^„€`„˜ţ.‚„P„L˙ĆP^„P`„L˙.h„„„˜ţĆ„^„„`„˜ţ.h„T„˜ţĆT^„T`„˜ţ.’h„$ „L˙Ć$ ^„$ `„L˙.h„ô „˜ţĆô ^„ô `„˜ţ.h„Ä„˜ţĆÄ^„Ä`„˜ţ.’h„”„L˙Ć”^„”`„L˙.h„d„˜ţĆd^„d`„˜ţ.h„4„˜ţĆ4^„4`„˜ţ.’h„„L˙Ć^„`„L˙.„Đ„˜ţĆĐ^„Đ`„˜ţo(.„ „˜ţĆ ^„ `„˜ţ. „$ „˜ţĆ$ ^„$ `„˜ţo(.€„@ „˜ţĆ@ ^„@ `„˜ţ.€„„˜ţĆ^„`„˜ţ.‚„ŕ„L˙Ćŕ^„ŕ`„L˙.€„°„˜ţĆ°^„°`„˜ţ.€„€„˜ţĆ€^„€`„˜ţ.‚„P„L˙ĆP^„P`„L˙.h„„„˜ţĆ„^„„`„˜ţ.h„T„˜ţĆT^„T`„˜ţ.’h„$ „L˙Ć$ ^„$ `„L˙.h„ô „˜ţĆô ^„ô `„˜ţ.h„Ä„˜ţĆÄ^„Ä`„˜ţ.’h„”„L˙Ć”^„”`„L˙.h„d„˜ţĆd^„d`„˜ţ.h„4„˜ţĆ4^„4`„˜ţ.’h„„L˙Ć^„`„L˙.h„„„˜ţĆ„^„„`„˜ţ.h„T„˜ţĆT^„T`„˜ţ.’h„$ „L˙Ć$ ^„$ `„L˙.h„ô „˜ţĆô ^„ô `„˜ţ.h„Ä„˜ţĆÄ^„Ä`„˜ţ.’h„”„L˙Ć”^„”`„L˙.h„d„˜ţĆd^„d`„˜ţ.h„4„˜ţĆ4^„4`„˜ţ.’h„„L˙Ć^„`„L˙.„Đ„˜ţĆĐ^„Đ`„˜ţo(.„ „˜ţĆ ^„ `„˜ţo(.„p„L˙Ćp^„p`„L˙.€„@ „˜ţĆ@ ^„@ `„˜ţ.€„„˜ţĆ^„`„˜ţ.‚„ŕ„L˙Ćŕ^„ŕ`„L˙.€„°„˜ţĆ°^„°`„˜ţ.€„€„˜ţĆ€^„€`„˜ţ.‚„P„L˙ĆP^„P`„L˙.„Đ„0ýĆĐ^„Đ`„0ýo()h„„„˜ţĆ„^„„`„˜ţ.h„T„˜ţĆT^„T`„˜ţ.’h„$ „L˙Ć$ ^„$ `„L˙.h„ô „˜ţĆô ^„ô `„˜ţ.h„Ä„˜ţĆÄ^„Ä`„˜ţ.’h„”„L˙Ć”^„”`„L˙.h„d„˜ţĆd^„d`„˜ţ.h„4„˜ţĆ4^„4`„˜ţ.’h„„L˙Ć^„`„L˙.„Đ„˜ţĆĐ^„Đ`„˜ţo()„ „˜ţĆ ^„ `„˜ţo()‚„p„L˙Ćp^„p`„L˙.€„@ „˜ţĆ@ ^„@ `„˜ţ.€„„˜ţĆ^„`„˜ţ.‚„ŕ„L˙Ćŕ^„ŕ`„L˙.€„°„˜ţĆ°^„°`„˜ţ.€„€„˜ţĆ€^„€`„˜ţ.‚„P„L˙ĆP^„P`„L˙.„Ŕ„˜ţĆŔ^„Ŕ`„˜ţo()€„„˜ţƐ^„`„˜ţ.‚„` „L˙Ć` ^„` `„L˙.€„0 „˜ţĆ0 ^„0 `„˜ţ.€„„˜ţĆ^„`„˜ţ.‚„Đ„L˙ĆĐ^„Đ`„L˙.€„ „˜ţĆ ^„ `„˜ţ.€„p„˜ţĆp^„p`„˜ţ.‚„@„L˙Ć@^„@`„L˙.„Đ„˜ţĆĐ^„Đ`„˜ţo(.„ „˜ţĆ ^„ `„˜ţo(.‚„p„L˙Ćp^„p`„L˙.€„@ „˜ţĆ@ ^„@ `„˜ţ.€„„˜ţĆ^„`„˜ţ.‚„ŕ„L˙Ćŕ^„ŕ`„L˙.€„°„˜ţĆ°^„°`„˜ţ.€„€„˜ţĆ€^„€`„˜ţ.‚„P„L˙ĆP^„P`„L˙.„Đ„˜ţĆĐ^„Đ`„˜ţo(.€„ „˜ţĆ ^„ `„˜ţ.‚„p„L˙Ćp^„p`„L˙.€„@ „˜ţĆ@ ^„@ `„˜ţ.€„„˜ţĆ^„`„˜ţ.‚„ŕ„L˙Ćŕ^„ŕ`„L˙.€„°„˜ţĆ°^„°`„˜ţ.€„€„˜ţĆ€^„€`„˜ţ.‚„P„L˙ĆP^„P`„L˙.„Đ„0ýĆĐ^„Đ`„0ýo()h„„„˜ţĆ„^„„`„˜ţ.h„T„˜ţĆT^„T`„˜ţ.’h„$ „L˙Ć$ ^„$ `„L˙.h„ô „˜ţĆô ^„ô `„˜ţ.h„Ä„˜ţĆÄ^„Ä`„˜ţ.’h„”„L˙Ć”^„”`„L˙.h„d„˜ţĆd^„d`„˜ţ.h„4„˜ţĆ4^„4`„˜ţ.’h„„L˙Ć^„`„L˙.h„„„˜ţĆ„^„„`„˜ţ.h„T„˜ţĆT^„T`„˜ţ.’h„$ „L˙Ć$ ^„$ `„L˙.h„ô „˜ţĆô ^„ô `„˜ţ.h„Ä„˜ţĆÄ^„Ä`„˜ţ.’h„”„L˙Ć”^„”`„L˙.h„d„˜ţĆd^„d`„˜ţ.h„4„˜ţĆ4^„4`„˜ţ.’h„„L˙Ć^„`„L˙.„„„˜ţĆ„^„„`„˜ţo(.„T„˜ţĆT^„T`„˜ţ.„$ „L˙Ć$ ^„$ `„L˙.€„ô „˜ţĆô ^„ô `„˜ţ.€„Ä„˜ţĆÄ^„Ä`„˜ţ.‚„”„L˙Ć”^„”`„L˙.€„d„˜ţĆd^„d`„˜ţ.€„4„˜ţĆ4^„4`„˜ţ.‚„„L˙Ć^„`„L˙.„Đ„˜ţĆĐ^„Đ`„˜ţo()€„ „˜ţĆ ^„ `„˜ţ.‚„p„L˙Ćp^„p`„L˙.€„@ „˜ţĆ@ ^„@ `„˜ţ.€„„˜ţĆ^„`„˜ţ.‚„ŕ„L˙Ćŕ^„ŕ`„L˙.€„°„˜ţĆ°^„°`„˜ţ.€„€„˜ţĆ€^„€`„˜ţ.‚„P„L˙ĆP^„P`„L˙.h„„„˜ţĆ„^„„`„˜ţ.h„T„˜ţĆT^„T`„˜ţ.’h„$ „L˙Ć$ ^„$ `„L˙.h„ô „˜ţĆô ^„ô `„˜ţ.h„Ä„˜ţĆÄ^„Ä`„˜ţ.’h„”„L˙Ć”^„”`„L˙.h„d„˜ţĆd^„d`„˜ţ.h„4„˜ţĆ4^„4`„˜ţ.’h„„L˙Ć^„`„L˙.„8„˜ţĆ8^„8`„˜ţo()€„„˜ţĆ^„`„˜ţ.‚„Ř „L˙ĆŘ ^„Ř `„L˙.€„¨ „˜ţƨ ^„¨ `„˜ţ.€„x„˜ţĆx^„x`„˜ţ.‚„H„L˙ĆH^„H`„L˙.€„„˜ţĆ^„`„˜ţ.€„č„˜ţĆč^„č`„˜ţ.‚„¸„L˙Ƹ^„¸`„L˙.h„„„˜ţĆ„^„„`„˜ţ.h„T„˜ţĆT^„T`„˜ţ.’h„$ „L˙Ć$ ^„$ `„L˙.h„ô „˜ţĆô ^„ô `„˜ţ.h„Ä„˜ţĆÄ^„Ä`„˜ţ.’h„”„L˙Ć”^„”`„L˙.h„d„˜ţĆd^„d`„˜ţ.h„4„˜ţĆ4^„4`„˜ţ.’h„„L˙Ć^„`„L˙.h„„„˜ţĆ„^„„`„˜ţ.h„T„˜ţĆT^„T`„˜ţ.’h„$ „L˙Ć$ ^„$ `„L˙.h„ô „˜ţĆô ^„ô `„˜ţ.h„Ä„˜ţĆÄ^„Ä`„˜ţ.’h„”„L˙Ć”^„”`„L˙.h„d„˜ţĆd^„d`„˜ţ.h„4„˜ţĆ4^„4`„˜ţ.’h„„L˙Ć^„`„L˙.h„„„˜ţĆ„^„„`„˜ţ.h„T„˜ţĆT^„T`„˜ţ.’h„$ „L˙Ć$ ^„$ `„L˙.h„ô „˜ţĆô ^„ô `„˜ţ.h„Ä„˜ţĆÄ^„Ä`„˜ţ.’h„”„L˙Ć”^„”`„L˙.h„d„˜ţĆd^„d`„˜ţ.h„4„˜ţĆ4^„4`„˜ţ.’h„„L˙Ć^„`„L˙.„8„0ýĆ8^„8`„0ýo(.„ „˜ţĆ ^„ `„˜ţo(.‚„p„L˙Ćp^„p`„L˙.€„@ „˜ţĆ@ ^„@ `„˜ţ.€„„˜ţĆ^„`„˜ţ.‚„ŕ„L˙Ćŕ^„ŕ`„L˙.€„°„˜ţĆ°^„°`„˜ţ.€„€„˜ţĆ€^„€`„˜ţ.‚„P„L˙ĆP^„P`„L˙.h„„„˜ţĆ„^„„`„˜ţ.h„T„˜ţĆT^„T`„˜ţ.’h„$ „L˙Ć$ ^„$ `„L˙.h„ô „˜ţĆô ^„ô `„˜ţ.h„Ä„˜ţĆÄ^„Ä`„˜ţ.’h„”„L˙Ć”^„”`„L˙.h„d„˜ţĆd^„d`„˜ţ.h„4„˜ţĆ4^„4`„˜ţ.’h„„L˙Ć^„`„L˙.„Đ„˜ţĆĐ^„Đ`„˜ţo(.„ „˜ţĆ ^„ `„˜ţo(.„$ „˜ţĆ$ ^„$ `„˜ţo()€„@ „˜ţĆ@ ^„@ `„˜ţ.€„„˜ţĆ^„`„˜ţ.‚„ŕ„L˙Ćŕ^„ŕ`„L˙.€„°„˜ţĆ°^„°`„˜ţ.€„€„˜ţĆ€^„€`„˜ţ.‚„P„L˙ĆP^„P`„L˙.„„„˜ţĆ„^„„`„˜ţo(.„T„˜ţĆT^„T`„˜ţ.„$ „L˙Ć$ ^„$ `„L˙.€„ô „˜ţĆô ^„ô `„˜ţ.€„Ä„˜ţĆÄ^„Ä`„˜ţ.‚„”„L˙Ć”^„”`„L˙.€„d„˜ţĆd^„d`„˜ţ.€„4„˜ţĆ4^„4`„˜ţ.‚„„L˙Ć^„`„L˙.„Đ„0ýĆĐ^„Đ`„0ýo()„Đ„˜ţĆĐ^„Đ`„˜ţo(.€„ „˜ţĆ ^„ `„˜ţ.‚„p„L˙Ćp^„p`„L˙.€„@ „˜ţĆ@ ^„@ `„˜ţ.€„„˜ţĆ^„`„˜ţ.‚„ŕ„L˙Ćŕ^„ŕ`„L˙.€„°„˜ţĆ°^„°`„˜ţ.€„€„˜ţĆ€^„€`„˜ţ.‚„P„L˙ĆP^„P`„L˙.„Đ„˜ţĆĐ^„Đ`„˜ţo() „ „˜ţĆ ^„ `„˜ţo(.„$ „˜ţĆ$ ^„$ `„˜ţo(.€„@ „˜ţĆ@ ^„@ `„˜ţ.€„„˜ţĆ^„`„˜ţ.‚„ŕ„L˙Ćŕ^„ŕ`„L˙.€„°„˜ţĆ°^„°`„˜ţ.€„€„˜ţĆ€^„€`„˜ţ.‚„P„L˙ĆP^„P`„L˙.„Đ„˜ţĆĐ^„Đ`„˜ţo(. „ „˜ţĆ ^„ `„˜ţo(.„p„L˙Ćp^„p`„L˙.€„@ „˜ţĆ@ ^„@ `„˜ţ.€„„˜ţĆ^„`„˜ţ.‚„ŕ„L˙Ćŕ^„ŕ`„L˙.€„°„˜ţĆ°^„°`„˜ţ.€„€„˜ţĆ€^„€`„˜ţ.‚„P„L˙ĆP^„P`„L˙.„„„˜ţĆ„^„„`„˜ţo(.„T„˜ţĆT^„T`„˜ţ.„$ „L˙Ć$ ^„$ `„L˙.€„ô „˜ţĆô ^„ô `„˜ţ.€„Ä„˜ţĆÄ^„Ä`„˜ţ.‚„”„L˙Ć”^„”`„L˙.€„d„˜ţĆd^„d`„˜ţ.€„4„˜ţĆ4^„4`„˜ţ.‚„„L˙Ć^„`„L˙.h„„„˜ţĆ„^„„`„˜ţ.h„T„˜ţĆT^„T`„˜ţ.’h„$ „L˙Ć$ ^„$ `„L˙.h„ô „˜ţĆô ^„ô `„˜ţ.h„Ä„˜ţĆÄ^„Ä`„˜ţ.’h„”„L˙Ć”^„”`„L˙.h„d„˜ţĆd^„d`„˜ţ.h„4„˜ţĆ4^„4`„˜ţ.’h„„L˙Ć^„`„L˙.„Đ„0ýĆĐ^„Đ`„0ýo()„Đ„0ýĆĐ^„Đ`„0ýo()h„„„˜ţĆ„^„„`„˜ţ.h„T„˜ţĆT^„T`„˜ţ.’h„$ „L˙Ć$ ^„$ `„L˙.h„ô „˜ţĆô ^„ô `„˜ţ.h„Ä„˜ţĆÄ^„Ä`„˜ţ.’h„”„L˙Ć”^„”`„L˙.h„d„˜ţĆd^„d`„˜ţ.h„4„˜ţĆ4^„4`„˜ţ.’h„„L˙Ć^„`„L˙.h„„„˜ţĆ„^„„`„˜ţ.h„T„˜ţĆT^„T`„˜ţ.’h„$ „L˙Ć$ ^„$ `„L˙.h„ô „˜ţĆô ^„ô `„˜ţ.h„Ä„˜ţĆÄ^„Ä`„˜ţ.’h„”„L˙Ć”^„”`„L˙.h„d„˜ţĆd^„d`„˜ţ.h„4„˜ţĆ4^„4`„˜ţ.’h„„L˙Ć^„`„L˙.„Đ„0ýĆĐ^„Đ`„0ýo()?y D3cEJ`ËV@PĎÖQH U>ZŐbébj,8œ) ^ă Ţq8=—`Ljűf„vHŰnh$ĂqÜĐ}Ď@w4Ň3=É•]^&ƒh>{Îzîl:Br˙$0$p+]Ew%kNš Ü+?KőI ˝/9Ű-7kţw•KZ 7Čf‘4ş=˙sčy÷tWzVćüfáh *#rĆuľ! bí]\ukčUŰHŢZ ž4Œ^ě˝OÓ $5_ˆc03ô,Ź|íE2+Ô# 7@O 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