Abstract Malignancy Associated Changes are subtle alterations in the morphology and nuclear texture of cells in the vicinity of a malignant lesion. The phenomenon was first described in 1959, and has been the subject of considerable research in the four intervening decades, due to its potential utility to cancer screening programs. In this thesis the history of research into malignancy associated changes is reviewed, and the major findings of previous workers summarized. Original work aimed at improving the accuracy of classification of Pap smear slides is described in detail. A novel algorithm, which incorporates a genetic algorithm for feature selection and training of a neural network, is described. The algorithm was tested upon a large artificial dataset consisting of points from nested spheres in multiple dimensions. It was able to select the most discriminatory features and classify data with 99% accuracy on 80% of runs for two dimensional data, and on 90% of runs for three-dimensional data. The algorithm was also tested on two real data sets from the UCI Machine Learning Repository, the “sonar” data and the “ionosphere” data. On both of these datasets the algorithm produced a classifier using a subset of features which performed as well as previously reported classifiers using the full feature set. This algorithm was then tested on a large dataset of cell images, and its performance compared with that of the standard stepwise linear discriminant analysis approach. Both of these approaches produced similar results, which are comparable to those of previous workers in this field. Interestingly, runs of the genetic algorithm with different random number seeds tended to select different feature subsets, which produced approximately equivalent performance. This finding indicates that amongst the features used, which were selected from those previously identified in the literature as useful for MACs detection, many subsets exist which are equally discriminatory.

Typ- 1 diabetes (T1D) är en autoimmun sjukdom med insulinbrist orsakad av nedbrytning av insulinproducerande betaceller i pankreas. Fyra olika antikroppar har identifierats som är riktade mot betacellsspecifika antigen; insulinautoantikroppar (IAA), glutamic acid decarboxylase antibodies (GADA), islet antigen2-antikroppar (IA-2A) och antikroppar riktade mot zinktransportören 8 (ZnT8A). I denna studie gjordes en jämförelse av metoderna 2screen islet cell autoantibody ELISA-kit (RSR, Cardiff, UK) och 3screen islet cell autoantibody ELISA- kit (RSR, Cardiff, UK), vars brunnar är coatade med GAD65/IA-2 antigen respektive GAD65/IA-2/ZnT8 antigen, för att undersöka ifall dessa båda kit ger jämförbar sensitivitet och specificitet i en adult population av nydebuterade patienter med T1D och friska vuxna blodgivare. RSR 2screen erhöll 1 % högre specificitet (98 %) jämfört med RSR 3screen (97 %) vid samma sensitivitet (92 %) och rekommenderas i första hand för screening av autoantikroppar i en population av vuxna patienter med ökad risk för T1D och friska vuxna blodgivare. / Type- 1 diabetes (T1D) is an autoimmune disease with insulin deficiency caused by degradation of insulin- producing betacells in pancreas. Four different autoantibodies that target beta- cell specific antigenes have been identified: insulinautoantibodies (IAA), glutamic acid decarboxylase antibodies (GADA), islet antigen2-antibodies (IA-2A) and antibodies against zinktransporter 8 (ZnT8A). In this study, a comparison between 2screen islet cell autoantibody ELISA-kit (RSR, Cardiff, UK) coated with GAD65/IA-2 and 3screen islet cell autoantibody ELISA- kit (RSR, Cardiff, UK) coated with GAD65/IA-2/ZnT8, was performed to investigate whether results from these two kits provide comparable sensitivity and specificity in an adult population of new onset patients with T1D and healthy adults. RSR 2screen obtained 1 % higher specificity (98 %) in comparison to RSR 3screen (97 %) on the same sensitivity (92 %) and is recommended primarily for screening of autoantibodies in a population of adult patients at increased risk for T1D and healthy adults blood donors.

A modelagem em radiobiologia possibilita prever a eficácia de tratamentos radioterápicos, especificando protocolos e estratégias para se tratar pacientes com câncer. Muitos modelos matemáticos têm sido propostos para a avaliação da Probabilidade de Controle Tumoral (TCP). Nesta tese, inicialmente apresenta-se um estudo desenvolvido em colaboração com pesquisadores da Universidade de Alberta, no Canadá, em que são comparadas as TCP\'s obtidas através de simulações Monte Carlo e dos modelos Poissoniano, de Zaider-Minerbo (ZM) e de Dawson-Hillen (DH). Os resultados mostram que, para tumores de baixa proliferação celular, o uso do modelo Poissoniano para indicação de protocolos de tratamento é tão eficaz quanto o método Monte Carlo ou o uso de modelos mais sofisticados (ZM e DH). Na segunda parte da tese, propõe-se um teste estatístico, baseado em simulações Monte Carlo do modelo de TCP de DH, para se determinar a capacidade de previsão de erradicação de tumor (cura). Obtem-se a curva ROC do teste a partir das distribuições de probabilidade da fração de células tumorais remanescentes, nas condições de cura ou não-cura. Os resultados mostram que o método pode ser também aplicado a dados clínicos, sugerindo que a avaliação do tamanho do tumor no início da radioterapia permite a prognose do tratamento a curto prazo. Na terceira parte da tese, aborda-se o estudo da fração de sobrevivência (FS) de células tumorais em função da dose de radiação a que são submetidas. Na literatura, esta fração de sobrevivência tem sido formulada através do modelo Linear-Quadrático (LQ) e, mais recentemente, da estatística não-extensiva de Tsallis. Avalia-se o comportamento dessas duas formulações em termos dos ajustes da FS a dados experimentais da literatura (referentes a células cultivadas in vitro para vários tecidos tumorais) estendendo-se assim estudos prévios da literatura. Os parâmetros da FS para ambas formulações são obtidos e a qualidade dos ajustes da FS a dados experimentais é comparada utilizando-se o qui-quadrado reduzido. Os resultados mostram que, em geral, as duas formulações permitem bons ajustes das curvas de FS. Além deste estudo, utilizamos a estatística não-extensiva de Tsallis para obtenção da TCP de ZM em função da dose, expressando-a analiticamente em termos da função Gama (para um perfil de dose típico de radiação de feixe externo) e da função Hipergeométrica (para um perfil de dose típico de braquiterapia). Finalmente, as curvas das correspondentes TCP\'s são levantadas com o uso de dados experimentais e comparadas com a TCP\'s obtidas através do modelo LQ. / Radiobiological modeling allows one to predict the efficacy of radiotherapeutic treatments, specifying protocols and strategies to treat patients with cancer. Many mathematical models have been proposed to evaluate the Tumor Control Probability (TCP). In this thesis we first present a study in colaboration with researchers at the University of Alberta, Canada, in which we compare the TCPs obtained by Monte Carlo simulations and from the Poissonian, Zaider-Minerbo (ZM) and Dawson-Hillen (DH) models. Results show that, for low proliferation tumors, the use of the Poissonian model for indicating the treatment protocol is as effective as the Monte Carlo method or more sofisticated models (ZM and DH). in the second part of the thesis, we propose a statistical test based on Monte Carlo simulations of the DH TCP model to determine the prediction capacity of tumor eradication (cure). We obtain the ROC curve of the test from the probability distributions of the remaining tumor cells for conditions of cure and non-cure. Results show that the method can also be applied to clinical data suggesting that the evaluation of the tumor size at the beginning of the radiotherapy leads to a short-term prognosis of the treatment. In the third part of the thesis, we study the surviving fraction (FS) of tumor cells as function of the radiation dose to which they are subjected. In the literature, this surviving fraction has been formulated by the Linear-Quadratic (LQ) model and, more recently, from the Tsallis non-extensive statistics. We evaluate the behaviour of both formulations in terms of the FS fittings to experimental data in the literature (related to cells cultivated for several tumoral tissues) so that we extend previous studies in the literature. The FS parameters for both formulations are obtained and the quality of the FS fittings to experimental data is compared using the reduced chi-square. Results show that in general both formulations lead to very good FS-curve fittings. Furthermore, we use the Tsallis non-extensive statistics to obtain the ZM TCP as function of the dose, expressing it analitically in terms of the Gamma function (for a dose profile typical of external beam radiation) and the Hipergeometric function (for a dose profile typical of brachitherapy). Finally, the curves of the corresponding TCPs are plotted using experimental data and then compared with TCPs obtained from the LQ model.

This master’s thesis is focused on problematic within the prediction of bankruptcy of companies operating in the field of agriculture in Czech republic. First part consists of introduction to companies that do business in field of agriculture and it describes bankruptcy models that are used in academicals sphere. Other part of thesis is divided into two sub-parts. First part is dedicated to an application of data into models of bankruptcy and their evaluation. Second part is focused on improvement of the best model and its main goal is to maximize the precision of the bankruptcy.

This diploma thesis deals with the creation of a bankruptcy model for the manufacturing industry in the Czech Republic using logit analysis. The theoretical part defines the concept of bankruptcy model, financial distress and financial health of the company. This section is focused on the influence of macroeconomics on the accuracy of these models, a look into their history and description of selected models. The practical part of the thesis is initially focused on determining the reliability of selected bankruptcy models, and then a new bankruptcy model is compiled.

The diploma thesis is aimed at the problematic within the prediction of bankruptcy of companies operating in manufacturing industry in Czech Republic. There are defined terms related to the topic, methods of creating bankruptcy models and selected bankruptcy models in the theoretical part. Analytical part includes testing of the selected bankruptcy models. Thereafter a new bankruptcy model is created, which is subsequently tested and its accuraccy is compared to models from other authors.

This diploma thesis deals with the issue of bankruptcy prediction of small and medium-sized enterprises operating in the manufacturing industry in selected Central European countries. The theoretical part of the thesis defines the concepts related to the prediction of bankruptcy and methods of model creation. The analytical part of the work includes testing the accuracy of selected bankruptcy model by other authors and creating a new bankruptcy model. The accuracy of the newly created model is then compared with the accuracy of selected models by other authors.

The ROC (Receiver Operating Characteristic) curve is a projection of two different cumulative distribution functions F0 and F1. On axis are values 1-F0(c) and 1-F1(c). The c-parameter is a real number. This curve is useful to check quality of discriminant rule which classify an object to one of two classes. The criterion is a size of an area under the curve. To solve real problems we use point and interval estimation of ROC curves and statistical hypothesis tests about ROC curves.

Orientador: Francisco José Teixeira Neto / Resumo: Objetivo: Comparar a acurácia diagnóstica da variação da pressão de pulso (VPP), variação do volume sistólico mensurada através do análise de contorno de pulso (VVSACP), índice de variabilidade pletismográfica (IVP), pressão venosa central (PVC) e índice do volume diastólico final global mensurado pela técnica de termodiluição transpulmonar (GEDVITDTP) para predizer a fluido-responsividade em cães. Animais: Quarenta cadelas saudáveis (13,8–26,8 kg) submetidas a ovário-salpingo-histerectomia. Métodos: A anestesia foi mantida com isoflurano sob ventilação mecânica com volume controlado (volume corrente 12 mL/kg, pausa inspiratória 40%, relação inspiração/expiração: 1:1,5). O débito cardíaco e o volume sistólico foram obtidos pela técnica de termodiluição transpulmonar através de um cateter inserido na artéria femoral. A fluido-responsividade (FR) foi avaliada por uma prova de carga (solução de Ringer com lactato, 20 mL/kg durante 15 minutos), administrada uma vez (n = 21) ou duas vezes (n = 18) antes da cirurgia. Respondedores a volume foram definidos como indivíduos onde o VS mensurado pela técnica de termodiluição transpulmonar, elevou-se acima de 15% após a última prova de carga. Resultados: Dos 39 animais incluídos no estudo, 21 cães foram classificados como respondedores e 18 não respondedores ao último desafio volêmico. As áreas sob as curvas de características de operação do receptor (AUROC) foram de 0,976, 0,906, 0,868 e 0,821 para VPP, IVP, PVC e VVSACP, respectivament... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Objective: To compare the diagnostic accuracy of pulse pressure variation (PPV), stroke volume variation from pulse contour analysis (SVVPCA), plethysmographic variability index (PVI), central venous pressure (CVP) and global end-diastolic volume index measured by transpulmonary thermodilution (GEDVITPTD) to predict fluid responsiveness (FR) in dogs. Animals: A group of 40 bitches (13.8–26.8 kg) undergoing ovariohysterectomy. Methods: Anesthesia was maintained with isoflurane under volume-controlled ventilation (tidal volume 12 mL/kg; inspiratory pause during 40% of inspiratory time; inspiration: expiration ratio 1:1.5). Transpulmonary thermodilution cardiac output was recorded through a femoral artery catheter. FR was evaluated by a fluid challenge (lactated Ringer's, 20 mL kg over 15 minutes) administered once (n = 21) or twice (n = 18) before surgery. Individuals were responders if stroke volume index measured by transpulmonary thermodilution increased >15% after the last fluid challenge. Results: Of the 39 animals studied, 21 were responders and 18 were nonresponders. Area under the receiver operating characteristics curve (AUROC) was 0.976, 0.906, 0.868 and 0.821 for PPV, PVI, CVP and SVVPCA, respectively (p < 0.0001 from AUROC = 0.5). GEDVITPTD failed to predict FR (AUROC: 0.660, p = 0.078). Best cut-off thresholds discriminating responders and nonresponders, with respective zones of diagnostic uncertainty (gray zones) were: PPV >16% (15–16%), PVI >11% (10–13%), SVVPCA ... (Complete abstract click electronic access below) / Doutor

Debris-slides are fast-moving landslides that occur in the Appalachian region including the Great Smoky Mountains National Park (GRSM). Various knowledge and data-driven approaches using spatial distribution of the past slides and associated factors could be used to estimate the region’s debris-slide susceptibility. This study developed two debris-slide susceptibility models for GRSM using knowledge-driven and data-driven methods in GIS. Six debris-slide causing factors (slope curvature, elevation, soil texture, land cover, annual rainfall, and bedrock discontinuity), and 256 known debris-slide locations were used in the analysis. Knowledge-driven weighted overlay and data-driven bivariate frequency ratio analyses were performed. Both models are helpful; however, each come with a set of advantages and disadvantages regarding degree of complexity, time-dependency, and experience of the analyst. The susceptibility maps are useful to the planners, developers, and engineers for maintaining the park’s infrastructures and delineating zones for further detailed geotechnical investigation.