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Malaria persists in 13 of Bangladesh's 64 districts, notably in the Chittagong Hill Tract (CHT) districts consisting of Bandarban, Rangamati, and Khagrachhari. While prior studies have explored malaria in Bangladesh, none have delved into the behavioral and climatic factors that simultaneously contribute to its persistence in the CHT districts. This study aims to fill this gap by investigating behaviors influencing malaria persistence in Bangladesh's endemic region, focusing on the Lama, Alikodom, and Naikhongchhari subdistricts of Bandarban district. Data were collected through surveys and key informant interviews (KIIs) in Lama and Alikodom, revealing tribal villages as having the highest concentration of cases, with inhabitants lacking essential knowledge about malaria and prevention methods. Socio-economic dynamics between tribal and Bengali communities emerged as a barrier to accepting information provided by NGOs. Additionally, occupation (employment) was found to be closely linked to malarial sickness. These findings can inform policies to eradicate malaria and protect tribal minorities. Meanwhile, in Naikhongchhari, this study analyzes the relationship between malaria incidence and climatic variables such as rainfall and temperature from 2013 to 2022. Utilizing NGO malaria registry data and meteorological data, significant correlations between rainfall, temperature, and malaria incidence were identified, with temperature and rainfall spikes preceding increases in cases. Despite limitations such as retrospective data collection inaccuracies and omitted determinants, these findings underscore the importance of considering climatic factors in malaria control efforts, necessitating further research for a comprehensive understanding of malaria dynamics. Combined, the overall findings suggest the need for greater education measures using improved communication devoted to preventative efforts among the ethnic minority residents of the CHTs, particularly during the time periods immediately after high rainfall and temperature. Such efforts could contribute greatly to Bangladesh's attempt to eliminate malaria within its borders. / Master of Science / Malaria remains a persistent issue in 13 out of Bangladesh's 64 districts, particularly prevalent in the Chittagong Hill Tract (CHT) districts like Khagrachhari, Bandarban, and Rangamati. Previous studies have overlooked the behavioral and climatic factors contributing to malaria's endurance in the CHT districts. This study fills this gap by investigating behavioral influences on malaria persistence, focusing on subdistricts like Lama, Alikodom, and Naikhongchhari in Bandarban district. Surveys and key informant interviews in Lama and Alikodom revealed tribal villages as hotspots for malaria, with inhabitants lacking crucial knowledge about prevention methods. Socio-economic disparities between tribal and Bengali communities hinder the acceptance of information provided by NGOs. Occupation was identified as closely linked to malarial sickness. In Naikhongchhari, the study explores the correlation between climatic variables and malaria incidence from 2013 to 2022, finding significant relationships between rainfall, temperature, and malaria cases. Temperature and rainfall spikes preceded increases in malaria cases. Despite limitations like retrospective data collection issues, the findings stress the importance of considering climatic factors in malaria control strategies. Enhanced education and communication efforts, particularly targeting ethnic minority residents of the CHTs, could significantly aid Bangladesh's malaria elimination efforts.

Yes / A key prediction of the Capital Asset Pricing Model (CAPM) is that idiosyncratic risk is not priced by investors because in the absence of frictions it can be fully diversified away. In the presence of constraints on diversification, refinements of the CAPM conclude that the part of idiosyncratic risk that is not diversified should be priced. Recent empirical studies yielded mixed evidence with some studies finding positive correlation between idiosyncratic risk and stock returns, while other studies reported none or even negative correlation. We revisit the problem whether idiosyncratic risk is priced by the stock market and what are the probable causes for the mixed evidence produced by other studies, using monthly data for the US market covering the period from 1980 until 2013. We find that one-period volatility forecasts are not significantly correlated with stock returns. The mean-reverting unconditional volatility, however, is a robust predictor of returns. Consistent with economic theory, the size of the premium depends on the degree of 'knowledge' of the security among market participants. In particular, the premium for Nasdaq-traded stocks is higher than that for NYSE and Amex stocks. We also find stronger correlation between idiosyncratic risk and returns during recessions, which may suggest interaction of risk premium with decreased risk tolerance or other investment considerations like flight to safety or liquidity requirements. The difference between the correlations of the idiosyncratic volatility estimators used by other studies and the true risk metric the mean-reverting volatility is the likely cause for the mixed evidence produced by other studies. Our results are robust with respect to liquidity, momentum, return reversals, unadjusted price, liquidity, credit quality, omitted factors, and hold at daily frequency. / National Research Foundation of Korea (2016S1A2A2912265)

By leveraging historical data together with machine learning algorithms, marketers can predict how new campaigns are likely to perform before launch. This approach can save time and resources and can help marketers optimize campaigns in current time through adjustments to increase return on investment (ROI) and reach the right target group. The objective of this thesis is to develop a predictive model through the application of feature selection techniques to assess the likability of a campaign. This study aims to identify the key features that significantly influence campaign likability and to quantify their impact. The task has been approached as a regression problem, with the objective of examine what predictors drives the liking of a campaign. The study implemented four methods for feature selection, recursive feature elimination with cross validation conjucted with random forest, lasso regression, ridge regression and decision trees. Further, to model, the following machine learning algorithms were employed: linear regression, ridge regression with cross validation, lasso regression with cross validation, elastic net with cross validation, kernel ridge regression and support vector regression. Based on the machine learning algorithm and the available data, the results indicate that the set of features generated by recursive feature elimination with cross validation combined with random forest was the most prominent and the algorithm support vector regression generated the best models. / Genom att använda historisk data tillsammans med maskininlärningsalgoritmer kan marknadsförare prediktera hur nya kampanjer sannolikt kommer att prestera innan de lanseras. Denna strategi kan spara tid och resurser och hjälpa marknadsförare att optimera kampanjer i realtid genom justeringar för att öka avkastningen på investeringen och nå rätt målgrupp. Målet med denna avhandling är att utveckla en prediktiv modell genom tillämpning av metodiker för variabelselektion för att bedöma sannolikheten för att en kampanj kommer att vara omtyckt. Denna studie syftar till att identifiera de nyckelvariabler som signifikant påverkar kampanjens popularitet och kvantifiera deras påverkan. Uppgiften behandlas som ett regressionsproblem för att identifiera vilka prediktorer som bidrar till ett positivt helhetsintryck av en kampanj. Studien implementerade fyra metoder för urval av variableselektion: rekursiv variabelselektion med korsvalidering kombinerad med random forest, lasso-regression, ridge-regression och beslutsträd. Dessutom användes följande maskininlärningsalgoritmer för modellering: linjär regression, ridge regression med korsvalidering, lasso regression med korsvalidering, elastiskt nät med korsvalidering, kernel ridge regression och stödvektorsregression. Baserat på maskininlärningsalgoritmerna och det tillgängliga datat indikerar resultaten att uppsättningen av funktioner genererad av rekursiv variabelselektion med korsvalidering kombinerad med random forest var mest framträdande och att algoritmen stödvektorregression genererade de bästa modellerna.

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Submitted by Deyse Queiroz (deysequeirozz@hotmail.com) on 2018-05-28T18:07:04Z No. of bitstreams: 1 EDILENE SANTOS DA SILVA - DISSERTAÇÃO PPGSA PROFISSIONAL 2017..pdf: 2158872 bytes, checksum: 418ea38c71e65c65b9193ce57c792957 (MD5) / Made available in DSpace on 2018-05-28T18:07:04Z (GMT). No. of bitstreams: 1 EDILENE SANTOS DA SILVA - DISSERTAÇÃO PPGSA PROFISSIONAL 2017..pdf: 2158872 bytes, checksum: 418ea38c71e65c65b9193ce57c792957 (MD5) Previous issue date: 2017 / A jaca (Artocarpus heterophyllus. Lam) pertence à família das Moraceae, ao gênero Artocarpus e é originária da Ásia. O tamanho dos frutos associado à exsudação do látex e o seu aroma característico acentuado, tem sido fatores limitantes quanto ao seu consumo. O objetivo do presente estudo foi avaliar a qualidade da jaca minimamente processada e acondicionar em diferentes tipos de embalagens, sob temperatura de 3°C durante 12 dias. O experimento foi desenvolvido no Laboratório de Tecnologia de Produtos de Origem Vegetal do Centro de Ciências e Tecnologia Agroalimentar da Universidade Federal de Campina Grande, utilizando um delineamento experimental inteiramente casualizado em esquema fatorial 4 x 7 (4 tipos de embalagens e 7 intervalos de tempo), com 3 repetições totalizando 84 tratamentos. As embalagens usadas foram: polipropileno (PP), politereftalato de etileno (PET), poliestireno expandido recobertas com filme de cloreto de polivinila (PVC) e saco plástico de polipropileno biorientado (BOOP). Foram realizadas analises físico-química e de compostos bioativos da polpa. Os dados foram submetidos a análise de variância e regressões polinomiais. Foi significativo do tempo de armazenamento e dos tipos de embalagens. Houve acréscimos significativo em relação tempo e entre tipos de embalagem para as variáveis físico-químicas: Perda de Massa, Sólidos Solúveis, Acidez Titulável e pH. Os compostos bioativos: Clorofila, Carotenoides, Flavonoides e Antocianinas aumentaram com o tempo de armazenamento e diferiram com o tipo de embalagem. Os níveis de Ácido ascórbico foram reduzidos de forma significativa e os Compostos fenólicos totais sofreram também reduções com a evolução da maturação dos frutos. / The jaca (Artocarpus heterophyllus, Lam) and originated from Asia belongs to the Moraceae family, and Artocarpus genre. The size of the fruits associated to the latex exudation and its marked aroma characteristic has been limiting factors in its consumption. The had as of the objective to evaluate the quality of the processed jackfruit and to pack in different types of packages under temperature of 3° during 12 days. The experiment was developed in the Laboratory of Technology of Vegetable Sources at the Center of Sciences and Agrifood Technology of the Federal University of Campina Grande, using a completely randomized experimental design in a factorial scheme 4 x 7 (4 storage bags nature and 7 time intervals) with 3 replicates totalizing 84 treatments. Polypropylene (PP), polyethylene terephthalate (PET), expanded polystyrene coated with polyvinyl chloride film (PVC) and bioriented polypropylene plastic bag (BOOP) were used as packing materials during seven processing periods. Physical and chemical analyzes of the bioactive pulp compounds were performed. Data was submitted to analysis of variance and regressions. Was significant effect of the storage time and types of packages. The physic chemical variables mass loss, soluble solids, titratable acidity and pH were significantly influenced by the processing time and types of packaging increasing these with the time of processing. The bioactive compounds Chlorophyll, Carotenoids, Flavonoids and Anthocyanins also were affected significantly with the time of storage and type of packaging, increasing these with the time of processing. Ascorbic acid levels and total phenolic compounds were reduced with the evolution of fruit maturation.

Este estudo têm como objetivo identificar qual o comportamento de empresas brasileiras de capital aberto com relação à aplicação dos recursos financeiros de seus fluxos de caixa (recursos internos) em investimentos e não investimentos (em fins que não se configuram como um projeto real de investimento) no curto e longo prazo e mostrar como essa questão está relacionado com o grau de restrições financeiras enfrentado pelas empresas. Para alcançar esse objetivo foram estimadas quatro regressões pelo método OLS (Ordinary Least Square / Mínimos Quadrados Ordinários), cada uma delas com uma das variáveis resposta correspondentes aos principais usos de caixa, ou seja, retenção de caixa, investimentos, dividendos e redução do financiamento externo e com as variáveis explicativas dadas pelo fluxo de caixa nos períodos t, t-1 e t-2 e algumas variáveis de controle específicas da firma. Os resultados sugerem que empresas brasileiras restritas e irrestritas se comportam de forma diferente ao receberem um choque positivo em seus fluxos de caixa e que o comportamento das mesmas também difere no curto e no longo prazo. Empresas restritas e irrestritas ao receberem um choque positivo em seus fluxos de caixa, retêm caixa no período contemporâneo e alocam tais recursos intertemporalmente. Empresas restritas investem mais no curto prazo enquanto as irrestritas investem mais no longo prazo. No curto prazo, empresas irrestritas distribuem mais dividendos do que empresas irrestritas e no longo prazo, os coeficientes dos fluxos de caixa não são significativos para nenhum dos grupos. No curto prazo empresas irrestritas reduzem o financiamento externo, enquanto empresas restritas levantam mais financiamentos externos e no longo prazo, esse comportamento se inverte. Dessa forma, fica clara a importância de se considerar o longo prazo bem como as restrições financeiras enfrentadas pelas empresas. / This study aim to identify what is the behaviour of Brazilian public companies regarding the use of financial resources of cash flows (internal resources) in investments and not investments (for purposes that are not configured as a real investment project) in the short and long term and show how this is related to the degree of financial constraints faced by firms. To achieve this aim, four regressions were estimated by OLS ( Ordinary Least Square), each with one of the response variables corresponding to the main uses of cash, ie , cash holding, investments, dividends and external finance reduction and the explanatory variables given by the cash flow in periods t , t - 1 and t - 2 and some control variables specific of the firm. The results suggest that restricted and unrestricted Brazilian companies behave differently when they receive a positive shock on cash flows and their behavior also differs in the short and long term. When constrained and unconstrained firms receive a positive impact on cash flows, they retain cash in the contemporary period and intertemporally allocate such resources. Constrained firms invest more in the short term while the unrestricted invest more in the long run. In the short term, unconstrained firms distribute more dividends than unconstrained firms and in the long run, the coefficients of cash flows are not significant for either groups. In the short term unconstrained firms reduce external finance, while constrained firms raise more external finance and in the long term, this behavior is reversed. Thus, it is clear that it matters to consider the long term as well as financial constraints faced by firms.

自從Cross在1973年提出股票市場具有星期效應(Day-of-the-week-effect)之後，開啟了學者在這個研究領域一連串的研究及探討，過程中金融市場經歷了國際化、法規制度的鬆綁與解禁、交易技術複雜化、交易電子化及衍生性商品的推出等事件，使得整個市場結構產生了極大的變化。正因如此，星期效應也有了轉變，根據Kamara(1997)及Hiraki,Maberly, and Taube(1998)的研究發現，股價指數期貨於市場交易後，原先存在的星期效應開始產生轉變，這樣有趣的發現激發出本研究的研究動機。基於研究動機，本研究主要目的為探討，在股價指數期貨推出後，股票市場的報酬型態是否產生變化。本研究以歐洲五國(英、德、法、瑞士、荷蘭)及台灣市場為研究對象。 本研究以敘述統計、虛擬變數所建立的星期效應模型及SUR(Seemingly Unrelated Regressions)來驗證股價指數期貨對市場星期效應的影響。研究期間在歐洲市場部分乃自1980年1月1日至2000年12月21日止；在台灣市場部分則是從1993年1月1日到2000年12月31日，選取每天收盤時的指數作為樣本資料，資料來源為教育部aremos資料庫及台灣經濟新報。 本研究驗證結果發現： 1. 歐洲五國有相對應股價指數期貨於市場上交易的指數，在期貨交易後原先存在於市場上的週一效應消失。至於無相對應股價指數期貨於市場上交易的指數，在期貨交易後除了英國之外，其餘四國的週一、週二效應皆於市場上消失。由此可知，期貨交易促使市場的報酬型態產生變化。 2. 使用SUR來考量歐洲各國股市相互影響下的星期效應發現，結果除了係數略為不同外，星期各日所呈現的型態基本上與沒有考量相互關係前的結果大同小異。 3. 台灣市場在摩根台股指數期貨交易前存在的週二效應，於交易後的期間轉變為週一、週二效應同時存在；而在台灣期交所推出台股指數期貨之後，台灣市場的週二效應正式消失，取而代之的是週一效應。期貨交易對市場星期效應的影響再度獲得證明。

This thesis contains two parts: the detectability of convex sets and the study on regression models In the first part of this dissertation, we investigate the problem of the detectability of an inhomogeneous convex region in a Gaussian random field. The first proposed detection method relies on checking a constructed statistic on each convex set within an nn image, which is proven to be un-applicable. We then consider using h(v)-parallelograms as the surrogate, which leads to a multiscale strategy. We prove that 2/9 is the minimum proportion of the maximally embedded h(v)-parallelogram in a convex set. Such a constant indicates the effectiveness of the above mentioned multiscale detection method. In the second part, we study the robustness, the optimality, and the computing for regression models. Firstly, for robustness, M-estimators in a regression model where the residuals are of unknown but stochastically bounded distribution are analyzed. An asymptotic minimax M-estimator (RSBN) is derived. Simulations demonstrate the robustness and advantages. Secondly, for optimality, the analysis on the least angle regressions inspired us to consider the conditions under which a vector is the solution of two optimization problems. For these two problems, one can be solved by certain stepwise algorithms, the other is the objective function in many existing subset selection criteria (including Cp, AIC, BIC, MDL, RIC, etc). The latter is proven to be NP-hard. Several conditions are derived. They tell us when a vector is the common optimizer. At last, extending the above idea about finding conditions into exhaustive subset selection in regression, we improve the widely used leaps-and-bounds algorithm (Furnival and Wilson). The proposed method further reduces the number of subsets needed to be considered in the exhaustive subset search by considering not only the residuals, but also the model matrix, and the current coefficients.

International Fisher Effect (IFE) is a theory in international finance which asserts that the spot exchange rate between countries should move in opposite direction with the interest rate differential between these countries. The aim of this thesis is to analyze whether differences in nominal interest rates between countries and the movement of spot exchange rates between their currencies tend to move together over the long run. The presence of IFE is tested among the G-5 countries and Turkey for the period from 1985:1 to 2007:12. The long run relationship is estimated with the Johansen co-integration method and supportive evidence is found for all country pairs. Individually modeled equations are further tested with the Dynamic SUR method. Those DSUR equations that include the Turkish currency provide supportive evidence for IFE that higher interest rates in favor of Turkey would cause depreciation of the Turkish Lira. The magnitude of the effect is found to be lower than expected which indicates that there might be other factors in economy, such as inflation rates, that affect the exchange rate movements.