Attention deficit hyperactivity disorder is one of the most common neurodevelopmental disorders, affecting around 7% of the worldwide population in their everyday life. It has been suggested that individuals with ADHD differ in gray matter volume from typically developing controls. However, findings on in which brain areas these differences are located, as well as how gray matter volume is affected by stimulant medication, remain inconclusive. Therefore, this systematic review aimed to investigate any potential differences in gray matter volume in medication-naïve individuals with ADHD compared to controls, focusing on studies using voxel-based morphometry applied to MRI-imaging data A keyword search in the databases Web of Science, Scopus and Medline EBSCO resulted in 349 studies, of which seven met the inclusion criteria and were included in the review. The results included a total of 169 participants diagnosed with ADHD and 148 typically developing controls. Findings suggested decreased cerebellar gray matter volume, potential gender-wise volume differences in the anterior cingulate cortex, and a decrease in caudate gray matter volume, specifically in adults with ADHD. Some limitations include small sample sizes, possible effects of age on gray matter volume, and the overall heterogeneous nature of the disorder. The present review agrees that individuals with ADHD exhibit differences in gray matter volume, but also highlights the importance of expanding research on medication-naïve subjects, to be able to draw more robust scientific conclusions about the neural correlates of ADHD in the future.

Genom litteratursökning och manuell datakompilering av sexualbrott mot barn, besvaras frågan “Vilka ord och fraser som förbrytare använder i konversationer är vanligt förekommande och kan användas som identifierande markörer av grooming?” och resulterade i en ordlista av könsord, sexuellt nedvärderande skällsord, och interjektioner som utrop, uppmaningar, och svordomar, som förekommer i högre utsträckning än i vardagliga konversationer. Denna lista användes för träning och test av en språkmodell som flaggar för skadlig data som kan indikera på grooming. Med en semistrukturerad intervju, kompletterat med litteratursökningen av sexualbrottmål besvarades frågan “Vilka sociala plattformar används av förbrytare för att kontakta barn med syfte att utsätta dem för sexualbrott, och varför är dessa plattformar mer använda än andra?”. Dessa metoder påvisade att Snapchat hade en överväldigande majoritet och var den mest använda plattformen, följt av Instagram på en andraplats, samt Tiktok och Kik på en gemensam tredjeplats. För att besvara den tredje frågeställningen “Kan identifiering av grooming underlättas genom Djupinlärning och Naturlig språkbehandling?" utfördes ett flertal experiment på den skapade detekteringsmodell med Naïve Bayes algoritmen som gav positiva utslag. Motiveringen till användandet av AI var att underlätta för IT-forensiker och utredare i deras arbete genom att snabbt identifiera förekomsten av grooming. Eftersom mängden data som extraheras är väldigt omfattande och innehållsklassificering har stor potential för automatisering, kan AI-modeller avsevärt minska arbetsbördan och öka effektiviteten. / By investigating and analyzing court cases, the question of which are the most commonly used words and phrases during grooming attempts that could be used as grooming indicators. A list was compiled and utilized as “harmful” and “harmless” for a training- and test dataset for an AI-model. The list contained snippets of conversations where genital, sexually derogatory terms, commands, and swear words averaged higher than in daily conversation. Through the methods of a semistructured interview and analyzing court cases, results of which social platforms perpetrators use to contact children could be compiled. This showed that Snapchat was by far the most prevalent platform used, followed by Instagram and in third place Tiktok and Kik Messaging. To answer this question, “harmless” data from the same platforms were used in the experiments. The third and final question, pertaining to the possibility of using an AI in grooming detection, was answered through multiple experiments. In an effort to determine if the conversations contained grooming or not, similar in fashion to e-mail spam classification problems, a script with Naïve Bayes as the classifier produced positive results. The goal of this study was to compile a list of words and phrases that, once used to train the model, could detect usage of these words and phrases. And notify the user if the current conversation has been flagged for suspected grooming attempts.

Introduction Prostate cancer (PCa) is the most common cancer among men in Sweden. The clinical course varies considerably, which makes it difficult to predict the prognosis in the individual case. In order to explore the early as well as the late course of the disease, large study groups and population-based cohorts are necessary. Aims To explore factors that influence the long-term outcome of men with low-risk tumours in a population-based register, to predict the long-term course, and to assess the mortality rate for men with prostate cancer (Paper I) To analyse long-term outcome and to investigate factors associated with long-term survival in patients with metastases to the skeleton (Paper II) To analyse early androgen deprivation treatment (ADT) failure and to define clinical predictors associated with short survival due to early ADT failure in prostate cancer patients with bone metastases (Paper III) To analyse the prognostic significance of the extent of bone metastases in relation to other pretreatment variables in prostate cancer patients, and to explore the impact of bone metastases on quality-of-life (Paper IV) Material and methods The study groups were assembled from The South East Region Prostate Cancer Register (SERPCR), and The Scandinavian Prostate Cancer Group (SPCG) Trial No. 5. In the first study, prognostic factors and long-term disease-specific mortality rates of low-risk prostate cancer patients from the early PSA era were analysed. In the second study, patient-related factors, quality-of-life (QoL) and long-term survival in 915 PCa patients with bone metastases (M1b) under ADT, were analysed. In Study III factors predicting primary failure to respond to ADT were identified. Study IV explored the impact of the extent of bone metastases on survival and QoL for these men. Result and conclusions The long-term disease-specific mortality of low-risk localised PCa is low, but the annual mortality rate gradually increases. This indicates that some tumours slowly develop into lethal cancer, particularly in men 70 years or older and with a PSA level ≥ 4 μg/L. From the SPCG Trial No. 5, a subgroup of patients with M1b disease and favourable set of predictive factors survived more than 10 years under ADT with an acceptable QoL. Independent predictors of long-term survival were identified as performance status (PS) < 2, limited extent of bone metastases, and a PSA level < 231 μg/L at the time of enrolment in the trial. However, four independent clinical predictors of early ADT failure could be defined. Men exhibiting these features should be considered for an alternative treatment. Patient grouping based on three categories of extent of bone metastases related to PS, haemoglobin, and QoL at presentation, as independent predictors of mortality, may provide improved accuracy of prognosis.

This study investigates E-banking Operational Risk Assessment (ORA) to enable the development of a new ORA framework and methodology. The general view is that E-banking systems have modified some of the traditional banking risks, particularly Operational Risk (OR) as suggested by the Basel Committee on Banking Supervision in 2003. In addition, recent E-banking financial losses together with risk management principles and standards raise the need for an effective ORA methodology and framework in the context of E-banking. Moreover, evaluation tools and / or methods for ORA are highly subjective, are still in their infant stages, and have not yet reached a consensus. Therefore, it is essential to develop valid and reliable methods for effective ORA and evaluations. The main contribution of this thesis is to apply Fuzzy Inference System (FIS) and Tree Augmented Naïve Bayes (TAN) classifier as standard tools for identifying OR, and measuring OR exposure level. In addition, a new ORA methodology is proposed which consists of four major steps: a risk model, assessment approach, analysis approach and a risk assessment process. Further, a new ORA framework and measurement metrics are proposed with six factors: frequency of triggering event, effectiveness of avoidance barriers, frequency of undesirable operational state, effectiveness of recovery barriers before the risk outcome, approximate cost for Undesirable Operational State (UOS) occurrence, and severity of the risk outcome. The study results were reported based on surveys conducted with Nigerian senior banking officers and banking customers. The study revealed that the framework and assessment tools gave good predictions for risk learning and inference in such systems. Thus, results obtained can be considered promising and useful for both E-banking system adopters and future researchers in this area.

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Cortical and subcortical microcircuits are continuously modified throughout life. Despite ongoing changes these networks stubbornly maintain their functions, which persist although destabilizing synaptic and nonsynaptic mechanisms should ostensibly propel them towards runaway excitation or quiescence. What dynamical phenomena exist to act together to balance such learning with information processing? What types of activity patterns do they underpin, and how do these patterns relate to our perceptual experiences? What enables learning and memory operations to occur despite such massive and constant neural reorganization? Progress towards answering many of these questions can be pursued through large-scale neuronal simulations.    In this thesis, a Hebbian learning rule for spiking neurons inspired by statistical inference is introduced. The spike-based version of the Bayesian Confidence Propagation Neural Network (BCPNN) learning rule involves changes in both synaptic strengths and intrinsic neuronal currents. The model is motivated by molecular cascades whose functional outcomes are mapped onto biological mechanisms such as Hebbian and homeostatic plasticity, neuromodulation, and intrinsic excitability. Temporally interacting memory traces enable spike-timing dependence, a stable learning regime that remains competitive, postsynaptic activity regulation, spike-based reinforcement learning and intrinsic graded persistent firing levels.    The thesis seeks to demonstrate how multiple interacting plasticity mechanisms can coordinate reinforcement, auto- and hetero-associative learning within large-scale, spiking, plastic neuronal networks. Spiking neural networks can represent information in the form of probability distributions, and a biophysical realization of Bayesian computation can help reconcile disparate experimental observations. / <p>QC 20170421</p>

Os linfócitos T regulatórios (Tregs) desempenham um papel essencial no controle da tolerância periférica, regulando a homeostase do sistema imune, e, por este motivo, são consideradas a população celular - com fenótipo regulatório - mais importante do sistema imune. Sob estímulos específicos, as Tregs podem ser geradas naturalmente no timo (nTregs), ou serem induzidas na periferia (pTreg) a partir de células T naive. É possível gerar Tregs in vitro (iTreg) a partir de células T CD4+ naive isoladas de sangue de cordão umbilical, suplementando a cultura com TGF-?, atRA e IL-2. Haja vista o grande potencial terapêutico das iTregs, a comunidade científica apresenta grande interesse no entendimento dos mecanismos envolvidos em sua geração. Os mais recentes trabalhos indicam um importante papel da via NF-?B na geração destas células, especialmente no que tange o componente c-Rel. Entretanto, na literatura, não existem dados suficientes sobre a avaliação dos genes potencialmente orquestrados por este fator. Permeado por todo este questionamento, o presente trabalho avalia a interação de c-Rel com as regiões promotoras do genoma, em células T naive e nas células iTregs geradas in vitro. Em adição, também avalia o efeito do silenciamento da proteína c-Rel no perfil de geração das iTregs. Para isso, foi utilizada a metodologia de imunoprecipitação de cromatina atrelada à técnica de PCR em tempo real com primers, que cobrem as regiões promotoras de alguns genes com papel importante na biologia de células T naive e de iTreg. Também foi avaliado a eficiência de transfecção de siRNA contra c-Rel e também do siRNA marcado com molécula fluorescente FITC em conjunto com diferentes concentrações e diferentes reagentes de transfecção, utilizando células Jurkat e T naive. Nossos resultados mostraram uma melhor eficiência de transfecção do siRNA FITC, considerando as células viáveis transfectadas, com os agentes DharmaFECT®1 (22,14%), DharmaFECT®4 (43,14%) e DMRIE-C (27,59%) em células Jurkat e DharmaFECT®1 (16,35%) e DMRIE-C (25,94%) em células T naive, nas maiores concentrações, entretanto não é muito eficiente para a avaliação do silenciamento proteico por qPCR. Além disso demonstramos que em uma pureza média de 80,46% de células Tnaive isoladas obtivemos a geração das iTregs (CD4+CD25+CD127-FOXP3+) com 98,42%, em média, na expressão do marcador FOXP3, e essas células iTregs apresentam maior ligação de cRel aos promotores de genes como IL2RA (CD25) (média de 8,26 vezes), CD69 (3,71 vezes), regiões do gene FOXP3 (região promotora (20,15 vezes), região CNS - kb1 (16,9 vezes), kb2 (17,2 vezes) e kb3 (23,29 vezes)) e do próprio Rel (8,12 vezes). Estes resultados evidenciam os potenciais mecanismos de regulação exercidos por c-Rel, durante o processo de geração das iTregs. / Regulatory T lymphocytes (Tregs) play an essential role in the control of peripheral tolerance, regulating the homeostasis of the immune system, and are considered the cellular population - with regulatory phenotype - most important of the immune system. Tregs can be generated naturally in the thymus (nTregs), or be induced at the periphery (pTreg) from naive T cells, in dependence of specifcs stimuli. In cell culture, supplemented with factors such as IL-2, TGF-? and atRA, it is possible to generate in vitro Tregs (iTreg) from naive CD4 + T cells isolated from umbilical cord blood. Knowing the great therapeutic potential of iTregs, the scientific community has shown great interest in understanding the mechanisms involved in this process. Recent works indicate an important role of the NF-?B pathway in the generation of these cells, especially relating the involvement of the c-Rel componente, however, in the literature, there are not enough data on the evaluation of genes potentially orchestrated by this factor. With all this questioning, this thesis aimed to evaluate the interaction of c-Rel with the some promoter regions of the genome, naive T cells and in vitro generated iTregs cells, in addition, we have also attempted to evaluate the effect of c-Rel protein silencing on the generation profile of iTregs. For this, the methodology of chromatin immunoprecipitation coupled to the real-time PCR technique with primers was used, which cover the promoter regions of some genes with important role in the biology of naive and iTreg T cells, The efficiency of siRNA transfection against c-Rel and also the siRNA labeled with FITC fluorescence molecule in conjunction with different concentrations and different transfection reagentes, using Jurkat and naive T cells, was also evaluated. Our results showed a better transfection efficiency of the FITC siRNA, considering the viable cells transfected with the highest concentrations of the reagents DharmaFECT®1 (22,14%), DharmaFECT®4 (43,14%) e DMRIE-C (27,59%) with Jurkat cells and DharmaFECT®1 (16,35%) e DMRIE-C (25,94%) with naive T cells, however, was not very efficient for the evaluation by qPCR of silencing, that is, the reduction of c-Rel mRNA and RNA of other genes. In addition, we demonstrated that in an average purity of 80.46% of isolated naive T cells we obtained the generation of iTregs (CD4 + CD25 + CD127-FOXP3 +) with 98.42%, on average, in the expression of the FOXP3 marker, and in these iTregs cells, when compared to naive T cells, c-Rel subunit has bound to the promoters of the genes as IL2RA (CD25) (average de 8,26 folds), CD69 (3,71 folds), regions of the FOXP3 gene (promoter region (20,15 folds), CNS regions - kb1 (16,9 folds), kb2 (17,2 folds) and kb3 (23,29 folds)) and c-Rel promoter - Rel (8,12 folds). Our results demonstrate the possible regulatory mechanisms, such as some of the main roles of the c-Rel subunit during the generation process of iTregs.

Em anos recentes, muitos algoritmos bio-inspirados têm surgido para resolver problemas de classificação. Em confirmação a isso, a revista Nature, em 2002, publicou um artigo que já apontava para o ano de 2003 o uso comercial de Sistemas Imunológicos Artificiais para detecção de fraude em instituições financeiras por uma empresa britânica. Apesar disso, não observamos, a luz de nosso conhecimento, nenhuma publicação científica com resultados promissores desde então. Nosso trabalho tratou de aplicar Sistemas Imunológicos Artificiais (AIS) para detecção de fraude em cartões de crédito. Comparamos AIS com os métodos de Árvore de Decisão (DT), Redes Neurais (NN), Redes Bayesianas (BN) e Naive Bayes (NB). Para uma comparação mais justa entre os métodos, busca exaustiva e algoritmo genético (GA) foram utilizados para selecionar um conjunto paramétrico otimizado, no sentido de minimizar o custo de fraude na base de dados de cartões de crédito cedida por um emissor de cartões de crédito brasileiro. Em adição à essa otimização, fizemos também uma análise e busca por parâmetros mais robustos via multi-resolução, estes parâmetros são apresentados neste trabalho. Especificidades de bases de fraude como desbalanceamento de dados e o diferente custo entre falso positivo e negativo foram levadas em conta. Todas as execuções foram realizadas no Weka, um software público e Open Source, e sempre foram utilizadas bases de teste para validação dos classificadores. Os resultados obtidos são consistentes com Maes et al. que mostra que BN são melhores que NN e, embora NN seja um dos métodos mais utilizados hoje, para nossa base de dados e nossas implementações, encontra-se entre os piores métodos. Apesar do resultado pobre usando parâmetros default, AIS obteve o melhor resultado com os parâmetros otimizados pelo GA, o que levou DT e AIS a apresentarem os melhores e mais robustos resultados entre todos os métodos testados. / In 2002, January the 31st, the famous journal Nature, with a strong impact in the scientific environment, published some news about immune based systems. Among the different considered applications, we can find detection of fraudulent financial transactions. One can find there the possibility of a commercial use of such system as close as 2003, in a British company. In spite of that, we do not know of any scientific publication that uses Artificial Immune Systems in financial fraud detection. This work reports results very satisfactory on the application of Artificial Immune Systems (AIS) to credit card fraud detection. In fact, scientific financial fraud detection publications are quite rare, as point out Phua et al. [PLSG05], in particular for credit card transactions. Phua et al. points out the fact that no public database of financial fraud transactions is available for public tests as the main cause of such a small number of publications. Two of the most important publications in this subject that report results about their implementations are the prized Maes (2000), that compares Neural Networks and Bayesian Networks in credit card fraud detection, with a favored result for Bayesian Networks and Stolfo et al. (1997), that proposed the method AdaCost. This thesis joins both these works and publishes results in credit card fraud detection. Moreover, in spite the non availability of Maes data and implementations, we reproduce the results of their and amplify the set of comparisons in such a way to compare the methods Neural Networks, Bayesian Networks, and also Artificial Immune Systems, Decision Trees, and even the simple Naïve Bayes. We reproduce in certain way the results of Stolfo et al. (1997) when we verify that the usage of a cost sensitive meta-heuristics, in fact generalized from the generalization done from the AdaBoost to the AdaCost, applied to several tested methods substantially improves it performance for all methods, but Naive Bayes. Our analysis took into account the skewed nature of the dataset, as well as the need of a parametric adjustment, sometimes through the usage of genetic algorithms, in order to obtain the best results from each compared method.

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O uso de sistemas denominados Brain Computer Interface, ou simplesmente BCI, para controle de dispositivos tem gerado cada vez mais trabalhos de análise de sinais de EEG, principalmente devido ao fato do desenvolvimento tecnológico dos sistemas de processamento de dados, trazendo novas perspectiva de desenvolvimento de equipamentos que auxiliem pessoas com debilidades motoras. Neste trabalho é abordado o comportamento dos classificadores LDA (Discriminante Linear de Fisher) e o classificador Naive Bayes para classificação de movimento de mão direita e mão esquerda a partir da aquisição de sinais eletroencefalográficos. Para análise destes classificadores foram utilizadas como características de entrada a energia de trechos do sinal filtrados por um passa banda com frequências dentro dos ritmos sensório-motor e também foram utilizadas componentes de energia espectral através do periodograma modificado de Welch. Como forma de pré-processamento também é apresentado o filtro espacial Common Spatial Pattern (CSP) de forma a aumentar a atividade discriminativa entre as classes de movimento. Foram obtidas taxas de acerto de até 70% para a base de dados geradas neste trabalho e de até 88% utilizando a base de dados do BCI Competition II, taxas de acertos compatíveis com outros trabalhos na área. / Brain Computer Interface (BCI) systems usage for controlling devices has increasingly generated research on EEG signals analysis, mainly because the technological development of data processing systems has been offering a new perspective on developing equipment to assist people with motor disability. This study aims to examine the behavior of both Fisher's Linear Discriminant (LDA) and Naive Bayes classifiers in determining both the right and left hand movement through electroencephalographic signals. To accomplish this, we considered as input feature the energy of the signal trials filtered by a band pass with sensorimotor rhythm frequencies; spectral power components from the Welch modified periodogram were also used. As a preprocessing form, the Common Spatial Pattern (CSP) filter was used to increase the discriminative activity between classes of movement. The database created from this study reached hit rates of up to 70% while the BCI Competition II reached hit rates up to 88%, which is consistent with the literature.