Bakgrund: Främre korsbandsskador (ACL-skador) är allvarliga och vanligt förkommande inom idrott, speciellt hos ungdomar i åldrarna 14-19 år. En förhöjd risk för ACL-skador har påvisats för individer aktiva inom fotboll och handboll, vilka är mycket populära sporter världen över. Inom dessa sporter har även kvinnor påvisats ha två till åtta gånger högre risk att drabbas än män. Syfte: Syftet var att undersöka om det fanns någon skillnad i knästabilitet vid en hopp-landningsrörelse mellan tjejer och killar i åldrarna 16-19 år, aktiva inom fotboll och handboll samt att undersöka om det fanns någon skillnad mellan fotbollsspelarna och handbollsspelarna, oavsett kön. Metod: Ett drop jump-test utfördes av 20 ungdomar, aktiva inom fotboll och handboll, medelålder ±SD 17,0 ± 0,9 år. Testerna filmades i frontal- och sagittalplanet och analyserades sedan med hjälp av Landning Error Scoring System (LESS). Post hoc-analyser genomfördes för att kontrollera skillnader i 1) graden av valgusställning i knäleden mellan tjejerna och killarna och 2) graden av knäflexion mellan fotbolls- och handbollsspelarna i landningsmomentet. Ett oberoende student’s t-test användes till de statistiska analyserna och signifikansnivån sattes till p ≤ 0,05. Resultat: Det fanns ingen signifikant skillnad i LESS-poäng mellan tjejerna och killarna (p = 0,694). Fotbollsspelarna hade signifikant lägre LESS-poäng än handbollsspelarna (p = 0,002). Andelen tjejer som uppvisade valgusställning i knäleden under testutförandet var högre än hos killarna. Fotbollsspelarna uppvisade enligt LESS tillräcklig knäflexion i landningsmomentet i högre utsträckning än handbollsspelarna under testutförandet. Slutsats: Ingen signifikant skillnad i knästabilitet och hopp-landningsteknik fanns mellan tjejerna och killarna. Fotbollsspelarna hade signifikant bättre knästabilitet och hopp-landningsteknik än handbollsspelarna. Tjejerna hade en större grad av valgusställning i knäleden vid testutförandet än killarna och handbollsspelarna uppvisade inte lika stor knäflexion som fotbollsspelarna vid testutförandet. Mer forskning krävs inom området för att resultaten ska kunna generaliseras. / Background: Anterior cruciate ligament injuries (ACL-injuries) are serious and common in sports, especially in adolescents between the ages of 14 and 19. An increased risk for ACL-injury has been shown in individuals active in soccer and team handball, which both are popular sports worldwide. Within these sports, women have been proven to have two to eight times greater risk for ACL-injury than men. Aim: The aim was to investigate whether there was any difference in knee stability during a jump-landing movement between girls and boys aged 16-19 years, active in soccer and team handball and also to investigate whether there was any difference between the soccer players and team handball players, regardless of gender. Method: A drop jump test was performed by 20 adolescents, active in soccer and team handball, mean ± SD age 17.0 ± 0.9 years old. The tests were recorded in the frontal and sagittal plane and were then analyzed using the Landing Error Scoring System (LESS). Post hoc analyzes were used to examine differences in 1) the degree of knee valgus alignment between the girls and the boys and 2) the degree of knee flexion between the soccer- and the team handball players in the landing movement. An independent student’s t-test was used in the statistical analysis and the level of significance was set at p ≤ 0.05. Results: There was no significant difference in LESS-score between the girls and the boys (p = 0.694). The soccer players had significantly lower LESS-score (p = 0.002). A higher frequency of the girls displayed a knee valgus alignment during the test compared to the boys. The soccer players displayed according to LESS adequate knee flexion to greater extent than the team handball players did during the test. Conclusion: No significant difference in knee stability and jump-landing technique was found between the girls and the boys. The soccer players displayed significantly better knee stability and jump-landing technique than the team handball players. The girls displayed a greater degree of knee valgus during the test than the boys did and the team handball players displayed a smaller degree of knee flexion then the soccer players did. More research is required within the area to be able to generalize the results.

Praticamente todas as grandes instituições brasileiras que trabalham com concessão de crédito utilizam-se de modelos para avaliar o risco de inadimplência dos potenciais contratantes de produtos de crédito. Qualquer avanço nas técnicas, que resulte no aumento da precisão de um modelo de previsão, acarreta ganhos financeiros para a instituição. Neste trabalho são apresentados, em um primeiro momento, conceitos de crédito e risco. Posteriormente, a partir de uma amostra de dados, fornecida por uma grande instituição financeira brasileira, estão desenvolvidos três modelos, aplicando-se três técnicas para a classificação de clientes: Regressão Logística, Redes Neurais e Algoritmos Genéticos. Em uma etapa final, são avaliadas e comparadas a qualidade e performance dos modelos desenvolvidos, onde é apontado qual o modelo que melhor se ajusta aos dados. Os resultados obtidos pelos modelos de regressão logística e rede neural são satisfatórios e bastante próximos, sendo o primeiro ligeiramente superior. O modelo embasado por algoritmos genéticos apresenta também bons resultados embora num patamar inferior aos dois já citados. Este trabalho ilustra os procedimentos a serem adotados por uma empresa para identificar o melhor modelo de concessão de crédito que tenha boa aderência aos seus dados. A adoção do melhor modelo detectado permite o direcionamento da estratégia da instituição, podendo aumentar a eficiência do seu negócio. / Most of the large Brazilian institutions which work with credit concession use credit models to evaluate the risk of consumer loans. Any improvement in techniques that results in the precision increase of a prediction model, will provide financial gains to the institution. The first phase of this study introduces concepts of credit and risk. Subsequently, with a sample set of applicants from a large Brazilian financial institution, three credit scoring models are built applying three different techniques: Logistic Regression, Neural Networks and Genetic Algorithms. Finally, the quality and the performance of these models are evaluated and compared, and the best one is identified. The results obtained by the logistic regression model and neural network model are good and very similar, but the first one is slightly better. The results obtained with the genetic algorithm model are also good, but a little bit inferior. This study shows proceedings to be adopted by a financial institution in order to identify the best credit model to evaluate the risk of consumer loans. The use of the proper model will help the definition of an adequate business strategy and increase profits.

Made available in DSpace on 2015-03-05T19:13:44Z (GMT). No. of bitstreams: 0 Previous issue date: 26 / Nenhuma / As facilidades na concessão de crédito a pessoas físicas têm aumentado no decorrer dos últimos três anos. Variáveis como redução das taxas de juros, aumento de prazos de pagamentos e empréstimos consignados à folha de pagamento possibilitaram à população em geral acesso a aquisição de bens móveis, imóveis entre outros. Neste contexto, a procura por mecanismos mais robustos de análise de risco de crédito, no sentido de evitar ou reduzir os níveis de inadimplência do setor se tornaram necessários. Este estudo objetiva construir um modelo econométrico para estimar a probabilidade do risco de inadimplência em uma Instituição Privada de Ensino Superior. Utilizando a técnica estatística de regressão logística, o modelo de risco de crédito foi construído com base em uma amostra de alunos (pessoas físicas) matriculados na Universidade Católica de Pelotas, situada em Pelotas/RS. As variáveis explicativas do modelo foram obtidas a partir da aplicação de um questionário socioeconômico, que gerou um rol de 59 variáveis d / The facilitation in the credit concession to individuals has increased over the last three years. Variables such as the reduction in the interest taxes, increase in maturity, payroll-attached loans, have provided the population in general, with access to consumption property, buildings among others. In this scenario, the search for stronger tools of credit risk analysis, trying to avoid or at least reduce the default rates in the field, has become necessary. This study aims at elaborating an econometric model to predict the probability of default risk in a Private University. By using the statistical technique of logistical regression, the credit risk model has been built based on a sample of students (individuals) enrolled at “Universidade Católica de Pelotas”, located in Pelotas/RS. The explaining variables of the model have been obtained from a socio-economical questionnaire, which has generated 59 variables from which, only 3 were really relevant: existence of previously negotiated debts, possession of a

Made available in DSpace on 2016-04-25T18:39:35Z (GMT). No. of bitstreams: 1 Wagner Schmidt.pdf: 8727051 bytes, checksum: 9669cd75306633dfdd1a2d712ce4d2a3 (MD5) Previous issue date: 2010-10-28 / This study is the result of the present observation of the movement of civil lawsuits that are growing every day on the market of financial institutions. Nowadays, especially in financial institutions, significant civil lawsuits has been a concern of executives. The main objective of this study is to propose a model of risk management for contingent liabilities in financial institutions, since the difficulty of managing such numbers in the deal result. This is an adaptation of the instruments used in the management of credit risk for the legal area. The models used are the Behaviour Scoring and Credit Scoring. The first model is based on the curve behavioral processes, in this work are denominated like variables. These variables are known industry products offered by financial institutions. On a second level is taken into account the reasons, known as triggering events that led to the civil suits. The second model, Credit Scoring, based on a statistical study of values, which serve as the basis in determining the historical losses. The proposed study is to assist the risk management of these liabilities, eliminating the subjectivity of analysis and allowing greater speed in information. The present results prove that it is possible to use the instruments in question to the risk management of contingent liabilities, reducing the subjectivity of analysis, as greater adherence to criteria and faster responses for managers. The top ten products analyzed shows the results of Credit Scores, for the respective taxable events, termed here as Behaviour Scores. This work, in addition to demonstrating the applicability of the models Credit Scoring and Behavior Scoring also allows us to expand this study to other fields of activities, such as telecommunications, energy, companies that handle large volumes of civil lawsuits, as well as expanded discussion of risk allocation of contingent liability for the product / Este estudo é o resultado da observação atual do movimento de ações cíveis que vem crescendo a cada dia no mercado de instituições financeiras. Nos dias atuais, principalmente nas instituições financeiras, volumes significativos de ações judiciais cíveis tem sido motivo de preocupação dos executivos. O principal objetivo deste estudo é propor um modelo de gestão de risco para passivos contingentes nas instituições financeiras, visto a dificuldade de gestão desses números dentro do resultado do negócio. Trata-se de uma adaptação dos instrumentos utilizados na área de gestão de risco de crédito para a área jurídica. Os modelos utilizados em questão são o Behaviour Scoring e o Credit Scoring. O primeiro modelo baseia-se na curva comportamental dos processos, que neste trabalho denominam-se como variáveis. Estas variáveis são os conhecidos produtos ofertados pela indústria das instituições financeiras. Em um segundo nível é levado em consideração os motivos, ou seja, fatos geradores que geraram as ações cíveis. O segundo modelo, o Credit Scoring, baseia-se em um estudo estatístico de valores, os quais servirão de base na apuração das perdas históricas. A proposta do estudo é auxiliar a gestão do risco desses passivos, eliminando a subjetividade de análise e permitindo maior velocidade nas informações. Os resultados obtidos neste trabalho provam que é possível utilizar os instrumentos em questão para a gestão do risco do passivo contingente, diminuindo a subjetividade de análise, visto maior aderência nos critérios e respostas mais rápidas para os gestores. O top ten de produtos analisados mostra os resultados dos Credit Scores, para os respectivos fatos geradores, denominado neste trabalho como Behaviour Scores. Este trabalho, além de evidenciar a aplicabilidade dos modelos Credit Scoring e Behaviour Scoring, também permite expandir este estudo para outros ramos de atividades, como telefonia, energia, empresas que operam com grandes volumes de ações cíveis, além de expandir discussões como alocação de risco de passivo contingente por produto

Une grande partie de l’impulsion de diverses technologies d’Internet par les systèmes Pair-à-Pair (Peer-to-Peer ou P2P) peut être vue comme une réaction au détriment du centrage de contenu sur les serveurs devant des clients passifs. Une des caractéristiques distinctives de tout système P2P est ce que nous appelons souvent connectivité directe de bout en bout entre pairs égaux. Le Pair-à-Pair a augmenté les débits des échanges entre des communautés dynamiques des utilisateurs qui tendent à augmenter rapidement. Nous parlons donc de systèmes distribués à large échelle dans lesquels l’information échangée, partagée et recherchée atteint des volumes de plus en plus impressionnants. Dans le cadre de cette thèse, nous nous intéressons essentiellement à la Recherche d'Information dans les systèmes de Recherche d’Information P2P (RIP2P) et plus précisément au problème d'agrégation des résultats dans de tels systèmes. Résoudre le problème d'agrégation en RIP2P de la même manière que sa résolution dans un cadre de Recherche d’Information Distribuée (RID) va manquer beaucoup d’intelligibilité. En effet, ça fait perdre de vue tout un contexte qui a changé en RIP2P, vu le facteur d'échelle et l’absence d’une vision globale sur le système, dans ces réseaux qui s'étendent naturellement à des milliers voire des millions de pairs. Ceci va impliquer notamment la suppression d'un serveur courtier inadéquat dans ce contexte et va soulever le problème de retrouver de nouvelles politiques pour agréger des résultats provenant de pairs hétérogènes dans une liste unique tout en reflétant les attentes de l'utilisateur. Toutes ces raisons nous ont incités à explorer un mécanisme d’agrégation basé sur les profils des utilisateurs déduits de leurs comportements passés suite à leurs interactions avec les résultats d’une requête. Dans cette thèse nos contributions portent sur deux axes complémentaires. D’abord, nous proposons une nouvelle vision d'agrégation de résultats dans un contexte large échelle. Dans ce cadre un modèle de profils et une approche de score hybride à base de profils sont proposés. Ensuite nous avons mis l’accent sur la mise en place d’un cadre d'évaluation de notre approche dans les systèmes à large échelle / A huge part of the impetus of various internet technologies through the Peer-to-Peer (Peer-to-Peer or P2P) system can be seen as a reaction to the content centering detriment on the servers in front of passive clients. One of the distinctive features of any P2P system is what we often call direct connectivity between equal peers. The Peer-to-Peer increased the exchange flows between dynamic communities of users which tend to grow rapidly. We talk, therefore, about large-scale distributed systems in which the exchanged, shared and sought information reaches a more and more impressive volumes. Solving the aggregation problem in P2PIR systems the same way as its resolution in Distributed Information Retrieval (DIR) will miss a lot of intelligibility. In fact, the context has changed in RIP2P, given the scale factor and the lack of a global vision of the system in these networks that extend naturally to thousands or even millions peers. This will involve the removal of a broker server that is inadequate in this context and will raise the problem of finding new policies to aggregate results coming from heterogeneous peers in a single list while reflecting the user’s expectations. All these reasons prompted us to explore an aggregation mechanism based on user profiles deduced from their past behavior due to their interaction with query results. Our contributions, in this thesis, focus on two complementary axes. First, we propose a new vision of results aggregation in a large scale system. In this context, a profiles model and a hybrid score profiles-based approach are proposed. Second, we focused on the development of an evaluation framework of our approach in large-scale systems. In this thesis, we are mainly interested in the Information Retrieval problem in P2P systems (P2PIR) and focusing more specifically on the problem of results’ aggregation in such systems

La drépanocytose est une maladie génétique qui se caractérise par des globules rouges en forme de faucille. Chez les personnes atteintes de drépanocytose, ces globules rouges (GR) adhèrent à l’endothélium vasculaire et provoquent ainsi une vaso-occlusion. Ce phénomène s’explique par la surexpression de la protéine Lutheran (Lu) à la surface des globules rouges falciformes qui se lie fortement à la Laminine (Ln) 511/521 exprimée par l’endothélium vasculaire enflammé. Le but de cette étude est d’identifier un inhibiteur d’interaction protéine-protéine (PPI) qui possède une forte probabilité de liaison à Lu afin d’inhiber l’interaction Lu-Ln 511/521. Un criblage virtuel de 1 295 678 composés ciblant la protéine Lu a été réalisé. La validation préalable d’un protocole de scoring a été envisagée sur la protéine CD80 qui présente un site de liaison avec des caractéristiquestopologiques et physico-chimiques similaires au site de liaison prédit sur Lu ainsi que plusieurs ligands avec des constantes d’affinité connues. Ce protocole contient différentes étapes de sélection basées sur les affinités calculées (scores), des simulations de dynamique moléculaire et les propriétés moléculaires. Un protocole de scoring fiable a été validé sur CD80 avec le programme de docking DOCK6 et les fonctions de scoring XSCORE et MM-PBSA ainsi qu’avec la méthode decalcul FMO. L’application de ce protocole sur Lu a permis d’obtenir deux ligands validés par des tests in vitro qui font l’objet d’un dépôt de brevet. La fonction de scoring XSCORE a permis d’identifier neuf autres ligands qui semblent aussi être des candidats prometteurs pour inhiber l’interaction Lu-Ln 511/521. / Drepanocytosis is a genetic blood disorder characterized by red blood cells that assume an abnormal sickle shape. In the pathogenesis of vaso-occlusive crises of sickle cell disease, red blood cells bind to the vascular endothelium and promote vaso-occlusion. At the surface of these sickle red blood cells, the overexpressed protein Lutheran (Lu) strongly interacts with the Laminin (Ln) 511/521.The aim of this study was to identify a protein-protein interaction (PPI) inhibitor with a highprobability of binding to Lu for the inhibition of the Lu-Ln 511/521 interaction. A virtual screening was performed with 1 295 678 compounds that target Lu. Prior validation of a robust scoring protocol was considered on the protein CD80 because this protein has a binding site with similar topological and physico-chemical characteristics and it also has a series of ligands with known affinity constants. This protocol consisted of multiple filtering steps based on calculated affinities (scores), molecular dynamics simulations and molecular properties. A robust scoring protocol was validated on the protein CD80 with the docking program DOCK6 and the scoring functions XSCORE and MM-PBSA and also with the FMO method. This protocol was applied to the protein Lu and we found two compounds that were validated by in vitro studies. The protection of these ligands by a patent is under process. Nine other compounds were identified by the scoring functionXSCORE and seem to be promising candidates for inhibiting the Lu-Ln 511/521 interaction.

Previous research has found that civil resistance has a positive impact on democratic development. Still, despite increased academic attention to how civil resistance affects democratization and democracy, no systematic study has yet examined how the nature of inclusion in a civil resistance impacts various elements of democracy. This study addresses this research gap by comparing how inclusive civil resistance and non-fully inclusive civil resistance uprisings between 1943-2013 affected the development of liberal, egalitarian, participatory, and deliberative democracy. Two theoretical arguments are presented for how the nature of inclusion in civil resistance affect its impact on democracy: one arguing that inclusion should generate higher levels of participatory democracy and another underlining how the nature of inclusion in civil resistance generates higher levels of deliberative democracy. The arguments are tested with a quasi-experimental difference-in-difference measure combined with a nearest neighbour matching propensity score method. The results give tentative support for that inclusive civil resistance compared to non-fully inclusive civil resistance increase democracy in general and deliberative democracy in particular up to five years after civil resistance ended. The impact of inclusion in civil resistance does however vary considerably, and further research is needed to strengthen the theory and generate more statistically significant results.

The growth of micro-credit along with the excellent conditions to carry out microfinance activity in the economy and financial system of the Republic of Peru are pushing for Microfinance Institutions (IMF) increased competition with banks in this segment business. Like in commercial banks, in microfinance questions such as: is this customer profitable?, What is the credit limit that I must accept to his/her application?, What interest rate should I charge to him/ her?, How I can reduce the risk default?, etc., are matters to be assessed properly. We propose a method that could facilitate improvement in customer qualification between failed and not failed. To this end, we propose a methodology that analyzes credit risk in the provision of microcredit through the design of a credit scoring model that we apply to a Development Agency for Small and Micro Enterprise (EDPYME), which is an IMF under the supervision by the Banking and Insurance Superintendency (SBS). / El crecimiento del número de microcréditos junto con las excelentes condiciones para llevar a cabo la actividad microfinanciera en la economía y sistema financiero de la República de Perú están impulsando a las instituciones de microfinanzas (IMF) a una mayor competencia con las entidades bancarias por este segmento de negocio. Al igual que en la banca comercial, en microfinanzas preguntas tales como: ¿conviene este cliente?, ¿cuál es el límite de crédito que debo aceptar a su solicitud?, ¿qué tasa de interés debo cobrar?, ¿cómo puedo reducir el riesgo de impago?, etc., son cuestiones que deben valorarse de forma adecuada. Este trabajo plantea un método que podría facilitar una mejora en la calificación de los clientes fallidos y no fallidos. Para ello, se propone una metodología que analiza el riesgo de crédito en la concesión de microcréditos mediante el diseño de un modelo de credit scoring aplicado a una entidad de desarrollo de la pequeña y micro empresa (EDPYME), IMF sometida a supervisión por la Superintendencia en Bancay Seguros (SBS).

Alors que les modèles de credit scoring sont largement utilisés depuis plus de cinquante ans et sont considérés comme un outil indispensable dans la prise de décision dans d'innombrables institutions financières du monde entier, la littérature et les empiriques disponibles sur ce sujet restent encore très limitées. Notre objectif est de combler cette lacune en présentant une analyse approfondie sur les modèles de credit scoring et le processus de prise de décision d’octroi de crédit, avec diverses applications sur des données réelles et extensives provenant de différents pays. Notre thèse comporte trois chapitres. Chapitre 1 commence par présenter le processus de développement d’un modèle de credit scoring, et fournit une application sur des données réelles d'une banque de détail basée en France. Visant à donner de nouvelles perspectives sur les pays émergents, Chapitre 2 analyse le marché du crédit à la consommation en Chine et enquête sur l'utilisation des modèles de credit scoring dans un tel marché prometteur. Chapitre 3 va plus loin que la littérature méthodologique précédente et se concentre sur les différentes techniques d'inférence des refusés qui peuvent corriger le biais de sélection lors de la construction d'un modèle de crédit scoring basé uniquement sur les dossiers acceptés. Ces chapitres présentent les différents aspects du crédit scoring, pour lesquels les principales problématiques de credit scoring seront traitées. / While credit scoring has been broadly used for more than fifty years and continued to be a great support on decision-making in countless businesses around the world, the amount of literature, especially empirical studies, available on this subject is still limited. Our aim in this thesis is to fill this gap by providing a profound analysis on credit scoring and credit decision processes, with various applications using real and extensive sets of data coming from different countries. The thesis is organized in three chapters. Chapter 1 starts by presenting the credit scoring development process, and provides an application to real data from a France-based retail bank. Aiming at providing new insights regarding emerging countries, Chapter 2 analyzes the Chinese consumer lending market and investigates the use of credit scoring in such a promising market. Chapter 3 goes further than the previous methodological literature and focuses on reject inference techniques which can be a way to address the bias when developing a credit-scoring model based solely on accepted applicants. These chapters provide a round tour on credit scoring, after which major issues in credit scoring are treated.

Praticamente todas as grandes instituições brasileiras que trabalham com concessão de crédito utilizam-se de modelos para avaliar o risco de inadimplência dos potenciais contratantes de produtos de crédito. Qualquer avanço nas técnicas, que resulte no aumento da precisão de um modelo de previsão, acarreta ganhos financeiros para a instituição. Neste trabalho são apresentados, em um primeiro momento, conceitos de crédito e risco. Posteriormente, a partir de uma amostra de dados, fornecida por uma grande instituição financeira brasileira, estão desenvolvidos três modelos, aplicando-se três técnicas para a classificação de clientes: Regressão Logística, Redes Neurais e Algoritmos Genéticos. Em uma etapa final, são avaliadas e comparadas a qualidade e performance dos modelos desenvolvidos, onde é apontado qual o modelo que melhor se ajusta aos dados. Os resultados obtidos pelos modelos de regressão logística e rede neural são satisfatórios e bastante próximos, sendo o primeiro ligeiramente superior. O modelo embasado por algoritmos genéticos apresenta também bons resultados embora num patamar inferior aos dois já citados. Este trabalho ilustra os procedimentos a serem adotados por uma empresa para identificar o melhor modelo de concessão de crédito que tenha boa aderência aos seus dados. A adoção do melhor modelo detectado permite o direcionamento da estratégia da instituição, podendo aumentar a eficiência do seu negócio. / Most of the large Brazilian institutions which work with credit concession use credit models to evaluate the risk of consumer loans. Any improvement in techniques that results in the precision increase of a prediction model, will provide financial gains to the institution. The first phase of this study introduces concepts of credit and risk. Subsequently, with a sample set of applicants from a large Brazilian financial institution, three credit scoring models are built applying three different techniques: Logistic Regression, Neural Networks and Genetic Algorithms. Finally, the quality and the performance of these models are evaluated and compared, and the best one is identified. The results obtained by the logistic regression model and neural network model are good and very similar, but the first one is slightly better. The results obtained with the genetic algorithm model are also good, but a little bit inferior. This study shows proceedings to be adopted by a financial institution in order to identify the best credit model to evaluate the risk of consumer loans. The use of the proper model will help the definition of an adequate business strategy and increase profits.