The purpose of this master thesis is to determine internal and external balance of the Italian economy and its development during the economic crisis after 2008. The theoretical part focuses on the definition of indicators of internal and external balance based on magic quadrangle. It also describes the main problems of the Italian economy, their interaction and the effect on the macroeconomic equilibrium. The practical part analyzes the development of the Italian economy during the crisis in terms of economic growth, unemployment, inflation and balance of payments, followed by the list of anti-crisis measures of the Italian government.

Algoritmos de aprendizado de máquina são frequentemente os mais indicados em uma grande variedade de aplicações de mineração dados. Entretanto, a maioria das pesquisas em aprendizado de máquina refere-se ao problema bem definido de encontrar um modelo (geralmente de classificação) de um conjunto de dados pequeno, relativamente bem preparado para o aprendizado, no formato atributo-valor, no qual os atributos foram previamente selecionados para facilitar o aprendizado. Além disso, o objetivo a ser alcançado é simples e bem definido (modelos de classificação precisos, no caso de problemas de classificação). Mineração de dados propicia novas direções para pesquisas em aprendizado de máquina e impõe novas necessidades para outras. Com a mineração de dados, algoritmos de aprendizado estão quebrando as restrições descritas anteriormente. Dessa maneira, a grande contribuição da área de aprendizado de máquina para a mineração de dados é retribuída pelo efeito inovador que a mineração de dados provoca em aprendizado de máquina. Nesta tese, exploramos alguns desses problemas que surgiram (ou reaparecem) com o uso de algoritmos de aprendizado de máquina para mineração de dados. Mais especificamente, nos concentramos seguintes problemas: Novas abordagens para a geração de regras. Dentro dessa categoria, propomos dois novos métodos para o aprendizado de regras. No primeiro, propomos um novo método para gerar regras de exceção a partir de regras gerais. No segundo, propomos um algoritmo para a seleção de regras denominado Roccer. Esse algoritmo é baseado na análise ROC. Regras provêm de um grande conjunto externo de regras e o algoritmo proposto seleciona regras baseado na região convexa do gráfico ROC. Proporção de exemplos entre as classes. Investigamos vários aspectos relacionados a esse tópico. Primeiramente, realizamos uma série de experimentos em conjuntos de dados artificiais com o objetivo de testar nossa hipótese de que o grau de sobreposição entre as classes é um fator complicante em conjuntos de dados muito desbalanceados. Também executamos uma extensa análise experimental com vários métodos (alguns deles propostos neste trabalho) para balancear artificialmente conjuntos de dados desbalanceados. Finalmente, investigamos o relacionamento entre classes desbalanceadas e pequenos disjuntos, e a influência da proporção de classes no processo de rotulação de exemplos no algoritmo de aprendizado de máquina semi-supervisionado Co-training. Novo método para a combinação de rankings. Propomos um novo método, chamado BordaRank, para construir ensembles de rankings baseado no método de votação borda count. BordaRank pode ser aplicado em qualquer problema de ordenação binária no qual vários rankings estejam disponíveis. Resultados experimentais mostram uma melhora no desempenho com relação aos rankings individuais, alem de um desempenho comparável com algoritmos mais sofisticados que utilizam a predição numérica, e não rankings, para a criação de ensembles para o problema de ordenação binária. / Machine learning algorithms are often the most appropriate algorithms for a great variety of data mining applications. However, most machine learning research to date has mainly dealt with the well-circumscribed problem of finding a model (generally a classifier) given a single, small and relatively clean dataset in the attribute-value form, where the attributes have previously been chosen to facilitate learning. Furthermore, the end-goal is simple and well-defined, such as accurate classifiers in the classification problem. Data mining opens up new directions for machine learning research, and lends new urgency to others. With data mining, machine learning is now removing each one of these constraints. Therefore, machine learning's many valuable contributions to data mining are reciprocated by the latter's invigorating effect on it. In this thesis, we explore this interaction by proposing new solutions to some problems due to the application of machine learning algorithms to data mining applications. More specifically, we contribute to the following problems. New approaches to rule learning. In this category, we propose two new methods for rule learning. In the first one, we propose a new method for finding exceptions to general rules. The second one is a rule selection algorithm based on the ROC graph. Rules come from an external larger set of rules and the algorithm performs a selection step based on the current convex hull in the ROC graph. Proportion of examples among classes. We investigated several aspects related to this issue. Firstly, we carried out a series of experiments on artificial data sets in order to verify our hypothesis that overlapping among classes is a complicating factor in highly skewed data sets. We also carried out a broadly experimental analysis with several methods (some of them proposed by us) that artificially balance skewed datasets. Our experiments show that, in general, over-sampling methods perform better than under-sampling methods. Finally, we investigated the relationship between class imbalance and small disjuncts, as well as the influence of the proportion of examples among classes in the process of labelling unlabelled cases in the semi-supervised learning algorithm Co-training. New method for combining rankings. We propose a new method called BordaRanking to construct ensembles of rankings based on borda count voting, which could be applied whenever only the rankings are available. Results show an improvement upon the base-rankings constructed by taking into account the ordering given by classifiers which output continuous-valued scores, as well as a comparable performance with the fusion of such scores.

Os recentes avanços da ciência e tecnologia viabilizaram o crescimento de dados em quantidade e disponibilidade. Junto com essa explosão de informações geradas, surge a necessidade de analisar dados para descobrir conhecimento novo e útil. Desse modo, áreas que visam extrair conhecimento e informações úteis de grandes conjuntos de dados se tornaram grandes oportunidades para o avanço de pesquisas, tal como o Aprendizado de Máquina (AM) e a Mineração de Dados (MD). Porém, existem algumas limitações que podem prejudicar a acurácia de alguns algoritmos tradicionais dessas áreas, por exemplo o desbalanceamento das amostras das classes de um conjunto de dados. Para mitigar tal problema, algumas alternativas têm sido alvos de pesquisas nos últimos anos, tal como o desenvolvimento de técnicas para o balanceamento artificial de dados, a modificação dos algoritmos e propostas de abordagens para dados desbalanceados. Uma área pouco explorada sob a visão do desbalanceamento de dados são os problemas de classificação hierárquica, em que as classes são organizadas em hierarquias, normalmente na forma de árvore ou DAG (Direct Acyclic Graph). O objetivo deste trabalho foi investigar as limitações e maneiras de minimizar os efeitos de dados desbalanceados em problemas de classificação hierárquica. Os experimentos realizados mostram que é necessário levar em consideração as características das classes hierárquicas para a aplicação (ou não) de técnicas para tratar problemas dados desbalanceados em classificação hierárquica. / Recent advances in science and technology have made possible the data growth in quantity and availability. Along with this explosion of generated information, there is a need to analyze data to discover new and useful knowledge. Thus, areas for extracting knowledge and useful information in large datasets have become great opportunities for the advancement of research, such as Machine Learning (ML) and Data Mining (DM). However, there are some limitations that may reduce the accuracy of some traditional algorithms of these areas, for example the imbalance of classes samples in a dataset. To mitigate this drawback, some solutions have been the target of research in recent years, such as the development of techniques for artificial balancing data, algorithm modification and new approaches for imbalanced data. An area little explored in the data imbalance vision are the problems of hierarchical classification, in which the classes are organized into hierarchies, commonly in the form of tree or DAG (Direct Acyclic Graph). The goal of this work aims at investigating the limitations and approaches to minimize the effects of imbalanced data with hierarchical classification problems. The experimental results show the need to take into account the features of hierarchical classes when deciding the application of techniques for imbalanced data in hierarchical classification.

Les maladies chroniques de l’adulte (maladies cardiovasculaires, cancers, maladies respiratoires et diabète) tuent chaque année dans le monde 38 millions de personnes dont 16 millions avant l’âge de 70 ans. Jusqu’aux années 1990, l’origine de ces pathologies étaient associée au style de vie de l’individu : consommation de tabac, d’alcool, l’inactivité physique et un régime alimentaire déséquilibré. Depuis l’élaboration du concept de DOHaD, identifiant les origines développementales de la santé et des maladies, de nombreuses données montrent que les maladies chroniques de l’adulte ont, en partie, une origine très précoce pendant la période péri conceptionnelle (in utero, premières années de la vie). L’exposition, à cette période, à des déséquilibres alimentaires, des toxiques, des produits chimiques synthétiques perturbant les hormones endogènes (perturbateurs endocriniens, PEs) pourra impacter l’organisme en développement via des modifications épigénétiques qui retiennent la mémoire des facteurs environnementaux auxquels sont soumis les individus. Toutefois, les phénotypes et les mécanismes impliqués sont encore loin d’être décryptés. Au cours de ce travail de thèse, nous nous sommes intéressée aux effets développementaux sur la prostate. En effet, le cancer de la prostate (CaP) est la deuxième cause de cancer et la 5° cause de mort par cancer dans le monde. Les données de la littérature montrent que les déséquilibres alimentaires (régime riche en graisse, HFD) et les PEs œstrogèno-mimétiques sont des facteurs de risque pour ce cancer. Nous avons développé un modèle expérimental de rats (jeunes adultes, 90 jours post-natal) exposés pendant la gestation jusqu’au sevrage à un HFD (60% de graisses), ou à un estrogène (estradiol benzoate, EB) pendant la période néonatale, ou bien à la combinaison des deux, pour explorer les effets sur la prostate (lobe ventral). L’exposition péri natale à l’EB ou à la combinaison EB+HFD diminue le poids de la prostate adulte. Cette anomalie est associée à une inflammation de la prostate modérée (HFD), importante (EB) ou massive (EB+HFD). L’infiltrat est composé essentiellement de macrophages et de lymphocytes T. Cette inflammation est associée à une augmentation dans la prostate du taux de cytokines pro-inflammatoires TNFa, CCL2/MCP1 (EB) mais aussi IL-6 (EB+HFD) ainsi qu’à une dérégulation de l’inflammasome NLRP3. NLRP3 est activé de façon chronique puisque l’on observe une sur expression de ses substrats IL-1b et IL-18. En conclusion, nous montrons que l’exposition péri conception à un estrogène ou à la combinaison RRG+EB programme des lésions prostatiques chez l’animal adulte. Chez l’homme, il est suggéré que des lésions inflammatoires chroniques (atrophie proliférative inflammatoire) seraient, comme pour d’autres organes, une première étape vers le début de la carcinogenèse. Ainsi, notre modèle expérimental permettrait l’étude des étapes précoces de la tumorigenèse prostatique. / Non-communicable diseases (NCDs) including cardiovascular diseases, cancers, respiratory diseases and diabetes kill 38 million people worldwide every year, 16 million of them before the age of 70. Until the 1990s, the origin of these pathologies was associated with the lifestyle of the individual: consumption of tobacco, alcohol, physical inactivity and an unbalanced diet. Since the development of the concept of DOHaD, identifying the developmental origins of health and disease, number of evidence showed that NCDs have, in part, an early origin during the peri-conception period (in utero, first years of life). Exposure during this period to food imbalances, toxic chemicals, synthetic chemicals disrupting endogenous hormones (endocrine disruptors, EDCs) may impact the developing body through epigenetic changes imprinted by the environmental factors to which individuals are exposed. However, the phenotypes and mechanisms involved are still far from being decrypted. During this thesis, we focused on developmental effects on the prostate. In fact, prostate cancer (PCa) is the second leading cause of cancer and the fifth leading cause of death by cancer in the world. Data from the literature shows that dietary imbalances (High Fat Diet, HFD) and estrogen-like EDCs are risk factors for this cancer. We developed an experimental model of rats (young adults, 90 days postnatal) exposed during pregnancy until weaning to HFD (60% fat), or estrogen (estradiol benzoate, EB) during the neonatal period, or a combination of both, to explore the effects on the prostate (ventral lobe). Peri-natal exposure to EB or EB + HFD reduces the weight of the adult prostate. This abnormality is associated with low (HFD), moderate (EB) or massive (EB + HFD) prostate inflammation. The infiltrate is composed mainly of macrophages and T lymphocytes. This inflammation is associated with an increase in the prostate of pro-inflammatory cytokine TNFa, CCL2 / MCP1 (EB) but also IL-6 (EB + HFD) as well as a deregulation of the NLRP3 inflammasome. NLRP3 is chronically activated since its substrates IL1b and IL-18 were over expressed. In conclusion, we show that peri-conception exposure to an estrogen or HFD + EB combination programs prostatic lesions in adult animals. In men, it is suggested that chronic inflammatory lesions (proliferative inflammatory atrophy) would, as for other organs, be a first step towards the onset of carcinogenesis. Thus, our experimental model is relevant for the study of the early stages of prostatic tumorigenesis.

Title: Compensation of muscle asymmetries in cross-country skiers Objectives: The goal was to assemble methodological material, that is focused on muscle imbalances in cross-country skiers. Which is based on review of found materials and results gained from author's bachleor's thesis. Tasks: The task was a review of Czech and foreign literature followed by explanation of terms compensation exercise and muscle imbalances. Next task was assembling of methodological material, that is focused on muscle imbalances in cross-country skiers. Methods: Method used was comparative analysis of found materials reffering to the topic of muscle imbalances in cross-country skiers. Results: On the basis of review of found literature and results gained from author's bachleor's thesis was made a methodological tool - stack of compensation exercises for cross-country skiers. Keywords: cross-country skiing, muscle imbalance, compensatory exercise

This document deals with devices which are used for the automatic Gram staining. The document starts by a research with the aim to discover existing devices and to compare them to the concept of the device developed by company Biovendor. There is theoretically and then practically dealed with the methods of the rotor imbalance detection and measurement of water-level. The Practical part of this document describes the development of the control unit with the microcontroller ARM Cortex-M3 which will be used for the prototype development of Biovendor’s device. The Last part describes measurement of imbalance of three different rotors with the aid of the control unit.

Master’s thesis deals with the influence simulated unbalance vibration level asynchronous motor. First is focused introduction to the problem of vibration. Another part is introduction with machine construction and vibrations in machines. Introduction with methods of measurement. The last part is vibration measurements with simulated imbalances.

Title: Assessment of muscle imbalances in handball players Objectives: The main aim of this work was to evaluate the occurrence of muscle imbalances in the handball players of the first - league team of woman by means of the kinesiological analysis and segmental analysis from the BIA method. Methods: In modified kinesiological analysis, we focused on assessing posture and examining shortened muscles. To segmental analysis by the BIA method, we used the Tanita MC - 980 apparatus, where we first assessed the asymmetry in the distribution of muscle mass on individual body segments. Results: In 80 % of the total, the upper cross syndrome was recorded. Lower cross syndrome was found in 67 % of the players. The results of segmental muscle mass analysis using BIA showed a statistically insignificant difference (p > 0.05) in the distribution of muscle mass in the upper limbs (average difference of 0.05 kg) and a statistically significant difference (p < 0.05) in the distribution of muscle mass at the lower of the limbs (average difference of 0.11 kg). The following significant correlations were found for the whole population (n = 15): m. Iliopsoas right and the amount of muscle mass (BIA) on right upper limb (r = 0.549), iliopsoas on the right and the amount of muscle mass (BIA) on left upper limb (r =...

Title: Muscle imbalances in white water canoeing measured by TMG Aims: The aim of this paper was to select the endangered muscle groups, to identify possible imbalances using tensiomyograph (TMG 100) and to define hypotheses about the influence of training load in water slalom on the development of imbalances in the selected specific muscle groups. Methods: This work has a character of a qualitative research. Specifically, 6 case studies were carried out, appended by control measurements after one year, in which emphasis was placed on the detection of characteristic muscle imbalances that could arise as a result of specific training activities in water slalom. To measure these muscle imbalances, we used tensiomyograph (TMG 100). Results: Among the measured participants, we found that during a one-year training cycle, significant changes in the functionality of individual muscle groups have occurred. The most endangered groups, ie the groups with the most significant changes, included BB, DEL, LD and TRM. There have been also notable changes in the functional symmetry of the elbow joint, where 4 out of 5 participants have deteriorated during the year. It was also found, that women might be more prone to imbalances as an effect of the specific activity compared to men. Key words: white water...

This study examines how effort-reward reciprocity at work impacts the job satisfaction of the self-employed. The self-employed regularly show higher job satisfaction than the wage-employed. Theories point toward effort-reward reciprocity, the balance between what one gives and what one receives at work, as a predictor of higher job satisfaction. No earlier research has explored the mediating effect of effort-reward reciprocity in order to explain the higher job satisfaction for the self-employed. This model was explored among employed individuals in the Nordic Region (N = 3,916). Job satisfaction was measured via an index of nine items. The effort-reward reciprocity measure followed the theoretical model of effort-reward imbalance. A causal mediation analysis showed that effort-reward reciprocity fully mediated the impact that employment form had on job satisfaction. The results suggest that this effect is not part of some elusive feature of self-employment. Further research should expand on the model by introducing rewards more attuned to self-employment, such as autonomy and flexibility.