Structured and long-term planning is an important part of the work with the renewal of water supply networks. This requires well-founded assessments and methods for evaluating the annual need for renewal for a sustainable and healthy future. Evaluating the condition of a management object has been a complex task. This is due to limited accessto the various parts of the water supply network and the fact that physical, operational and environmental factors affect pipelines in different ways. Since experience and knowledge have been developed about, for example, joint methods or the durability of pipe material, this has meant that several different pipe materials are underground. There are various useful methods for evaluation of the condition of the water supply network. Recently, mathematical models have begun to be used to analyse the status and estimated lifespan of lines through data on pipes and external factors. In this study, an ANN model from Svenskt Vatten was used to evaluate the organization’s geodata for the model and to study the relationship between risk management that models calculate and reported operational disruptions. The use of the model requires that large amounts of data need to be compiled and adapted to valid values.The results show that most of the water supply network in the study area can be used to set prediction values with the model by compiling and adapting attribute values. Several objects were excluded due to deficiencies in management attributes. Some comparisons can be made between estimated risk water pipes and reported operational disruptions. The conclusion of the study is that the model could be an important complement to future renewal planning. Assessed risk water pipes can provide a good indication of which parts of the pipeline network need to be evaluated in more depth for possible renewal.

Failure to Yield is a collection of creative nonfiction that explores themes of presence and emotional connection and expression. The seven essays, which include three flash essays, explore the themes by reflecting on such topics as marriage, parent-child relationships and addiction. The collection is woven together by the author's relationships with her parents and children and by her experiences growing up in a small town in Iowa.

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This dissertation proposes that the work produced by black writers between the end of the Depression and the end ofWorld War II, specifically that ofEllison, Himes and Petry--and to the degree that it influenced the others, that ofWright--comprises a distinct period in African American literature. Their work is characterized by a concern with the implications of the war for the self-determination of African Americans within the United States and for people of colour worldwide. In addition, these writers explored the effects of the war effort, particularly ofthe second Great Migration ofblack Americans from South to North, on the cultural and political strategies of African Americans as a whole. These migrants, the majority of whom had been employed as agricultural or domestic labourers in the South, entered into industrial occupations and left service work in private homes in unprecedented numbers. In their prewar role within a neo-feudal southern economy characterized by white power over the labouring black body, these workers were seen by many contemporary commentators, and particularly those aligned with the American Left, as conforming to a socio-economic category of the "folk." In the South, the black folk had developed strategies for survival and resistance, many of which were contained in their folklore. As these migrants entered into industrial relations of production and a concomitant working-class consciousness in a war-driven economy, African American writers, intellectuals, and workers were faced with the question of the degree to which this folk "past" was usable in the present. In the work ofEllison, Himes and Petry, the figure of the black folk in the urban-industrial environment, as it e/merged with the working class, became the embodied site for an examination of the massive cultural and political shifts engendered by World War II. In addition, each ofthese writers employed black folklore as a strategy in the struggle for Mrican American selfdetermination within the United States during the war. / This dissertation proposes that the work produced by black writers between the end of the Depression and the end ofWorld War II, specifically that ofEllison, Himes and Petry--and to the degree that it influenced the others, that ofWright--comprises a distinct period in African American literature. Their work is characterized by a concern with the implications of the war for the self-determination of African Americans within the United States and for people of colour worldwide. In addition, these writers explored the effects of the war effort, particularly ofthe second Great Migration ofblack Americans from South to North, on the cultural and political strategies of African Americans as a whole. These migrants, the majority of whom had been employed as agricultural or domestic labourers in the South, entered into industrial occupations and left service work in private homes in unprecedented numbers. In their prewar role within a neo-feudal southern economy characterized by white power over the labouring black body, these workers were seen by many contemporary commentators, and particularly those aligned with the American Left, as conforming to a socio-economic category of the "folk." In the South, the black folk had developed strategies for survival and resistance, many of which were contained in their folklore. As these migrants entered into industrial relations of production and a concomitant working-class consciousness in a war-driven economy, African American writers, intellectuals, and workers were faced with the question of the degree to which this folk "past" was usable in the present. In the work ofEllison, Himes and Petry, the figure of the black folk in the urban-industrial environment, as it e/merged with the working class, became the embodied site for an examination of the massive cultural and political shifts engendered by World War II. In addition, each ofthese writers employed black folklore as a strategy in the struggle for Mrican American selfdetermination within the United States during the war. / Thesis / Doctor of Philosophy (PhD)

LD2668 .T4 1962 S78

The purpose of this paper is to determine why Mrs. Radcliffe's gothic novels were popular with contemporary readers. Sources include reviews from eighteenth century periodicals, essays of early nineteenth century critics such as William Hazlitt and studies of her work by twentieth century critics. The thesis is organized in four chapters each of which discusses one aspect of her work which particularly pleased her contemporary reviewers and critics: her invention, her attitude toward superstition, her use of poetic justice, and her outlook on nature. These aspects of her work alone did not secure for her the popularity she enjoyed, but, when combined with her ability to create suspense, helped her become one of the most popular writers of her era.

A depressão, também conhecida como distúrbio depressivo maior, é uma doença extremamente séria caracterizada por distúrbios afetivos que apresenta sintomas como tristeza, pessimismo, baixa autoestima, alterações nas funções vegetativas como sono e apetite e cognitivas como concentração, memória e atenção. A depressão afeta hoje cerca de 300 milhões de pessoas sendo essa a doença mais incapacitante do mundo, segundo dados da Organização Mundial da Saúde. O receptor humano 5-HT2a tem sido associado a inúmeras condições neurológicas e moléculas ligantes seletivas a esse receptor podem apresentar potencial terapêutico no tratamento de distúrbios de comportamento, tais como a depressão. Com o propósito de contribuir para o planejamento de novos fármacos mais eficazes no tratamento da depressão realizou-se um estudo de QSAR (do inglês Quantitative structure-activity Relationship) com um conjunto de 106 compostos arilpiperazínicos utilizando os métodos de Mínimos Quadrados Parciais (PLS) e Redes Neurais Artificias (ANN). O modelo de PLS foi obtido com 76 compostos no conjunto de treinamento e 11 compostos no conjunto teste (r2 = 0,749 e q2 = 0,696). Os testes de validação leave-N-out, randomização e detecção de outliers confirmaram a robustez e estabilidade dos modelos e demonstraram que os mesmos não foram gerados através de correlações ao acaso. O modelos de Redes Neurais Artificiais de Perceptron de Multicamadas (MLP-ANN) foi gerado utilizando funções de transferência tansig-tansig. O treinamento das redes demonstrou que o melhor modelo apresentava arquitetura 7-10-1. Tal modelo apresentou valores de erro quadrático médio (EQM) igual a 0,00964, desvio médio absoluto (DMA) igual a 0,0775 e r2treinamento, r2validação e r2teste iguais a 0,794, 0,795 e 0,788, respectivamente. Os descritores dos modelos matemáticos gerados mostraram concordância com as propriedades moleculares dos compostos e os valores de atividade biológica preditos pelos modelos de PLS e ANN demonstraram que a interação dos descritores é satisfatoriamente relacionada tanto por aproximações lineares quanto não-lineares. / Depression, major depressive disorder or clinical depression, is a serious mood disorder characterized by severe symptoms like emotional suffering and feeling miserable that affects vegetative functions as sleeping and eating and cognitive functions like concentration, memory and attention. The world mental health estimates that depression affects more than 300 million people worldwide and is the leading cause of world disability. The human receptor 5-HT2a has been associated to many neurological dysfunctions. Molecules that selectively bind to this receptor present the potential to be used as an effective treatment of mental health disorders, such as depression. Our primary aim in this work is to contribute to the development of new drugs for the treatment of depression. Quantitative Structure-Activity Relationships (QSAR) studies with a series of 106 arylpiperazines that interact with the neuroreceptor 5-HT2a were conducted employing the methods Partial Least Squares (PLS) and Artificial Neural Networks (ANN). The PLS model was obtained with a training set of 76 compounds and a 19 compounds test set (r² = 0. 749, q² = 0.696). Leave-N-out analysis, biological activity randomization and outliers detection confirmed the robustness and stability of the models and showed that they were not obtained by chance correlations. Predictive models were also generated by Multilayer Perceptron Artificial Neural Network (MLP-ANN) trained with tansig-tansig transfer functions showed that the best results were obtained for a 7-10-1 architecture (r²training = 0. 794, r²validation = 0.795 and r²test = 0.788). The descriptors used to construct the predictive models showed good agreement with the arylpiperazines molecular properties, and the biological activity predicted by the PLS and ANN methods suggested that the descriptor interactions can be described by a linear or a nonlinear approach as well.

A combretastatina A4 é um promissor agente anticâncer. Na célula, inibe a polimerização dos microtúbulos, os quais são fundamentais nos processos de motilidade, manutenção estrutural e mitose. Essa inibição se dá a partir do sítio de interação da αβ-tubulina bloqueando o fluxo do sangue que alimenta os tumores, o que resulta na morte dos mesmos. Com estrutura semelhante às combretastatinas, as chalconas constituem uma classe de compostos que atuam no mesmo sítio de interação na tubulina. Baseando-se nos trabalhos experimentais de Ducki e colaboradores, estudou-se a estrutura molecular de 87 chalconas análogas à combretastatina A4 por meio do método quântico DFT com o propósito de desenvolver modelos de Relações Quantitativas Estrutura-Atividade (QSAR) aplicados a tais antagonistas. A partir dos métodos dos Mínimos Quadrados Parciais (PLS) e de Redes Neurais Artificiais (ANN), foram gerados modelos que conduzem à elucidação da relação dos compostos estudados com suas respectivas atividades biológicas. Os descritores eletrônicos e moleculares selecionados apresentam alta concordância com as características das moléculas, havendo predominância de comportamento linear com a atividade biológica, podendo, eventualmente, apresentar comportamento não-linear, o que torna o modelo gerado altamente consistente. / Combretastatin A4 is a promising anticancer agent. It inhibits the polymerization of microtubules in the cell, which are essential in the process of motility, structural maintenance and mitosis. This inhibition is given from the interaction site of αβ-tubulin blocking the blood flow that feeds the tumor, what results in its death. The chalcones, sharing a similar structure of the combretastatin, are also a class of compounds that act in the same site of interaction in the tubulin. Based on the experimental work of Ducki and co-workers, we proposed a molecular structure study of 87 chalcones similar to combretastatin A4 using the DFT method in order to develop Quantitative Structure-Activity Relationships (QSAR) applied to the given antagonists. Through Partial Least Squares (PLS) and Artificial Neural Network (ANN) methods, some models has been generated to lead the understanding on the relationship between the compounds studied and their respective biological activities. The electronic and molecular descriptors selected have high correlation with the molecule features, being linear most of the time, although with eventual non-linear behavior, which makes the generated model highly consistent.

金融市場瞬息萬變，幾乎所有商品價格都是非線性的動態過程，如何預測價格一直都是倍受討論和研究的議題。隨著電腦科技的不斷進步,許多財務學者以市場上的歷史交易資料作為研究對象，希望能夠預測出有效的結果。本研究利用 EEMD 法拆解原始加權指數訊號，建立類神經網路模型，並預測出未來市場之價格後，利用 FK 值當作交易門檻，帶回台指選擇權做交易測試並計算報酬。由於不同神經元個數會配適出不同的預測結果，本研究希望能夠找到較適合使用在指數預測的網路架構。 / The financial market forecasting is characterized by data intensity, noise, non-stationary, high degree of uncertainty, and hidden relationships. Investors are concerned about the forecasting market price. Throughout the development of computational technology, researchers have been involved in data mining on historical trading enabling them to have a more accurate data. This research uses Ensemble Empirical Mode Decomposition-based Artificial Neural Networks (ANNs) learning paradigm to provide different ways to analyze the stock market. In our research, we used the ANN method to obtain our prediction of the stock price. First, the previous day’s stock price needs to be decomposed in order to see the various variables, that is, the numerous IMFs seen on the graphs. Acquiring the information, it is inserted into the ANN method to get a prediction. Following that, the prediction can then be transformed into a simpler result via the Forward Calculator % K indicator. As a result, the FK value can display a signal if to buy or sell, and confirm trading time, and make buy or sell Call-Put decisions on TAIEX options. In summary,we found different neuron numbers in the hidden layers that may affect the result of prediction.