Overexpressing BDNF in Neural Stem Cells using non-viral gene delivery strategies

Dissertação para obtenção do Grau de Mestre em Biotecnologia

Personalization platform for multimodal ubiquitous computing applications

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Narrative Bifurcation, Cloud Computing Interfaces and Hitchcok

From a narratological perspective, this paper aims to address the theoretical issues concerning the functioning of the so called «narrative bifurcation» in data presentation and information retrieval. Its use in cyberspace calls for a reassessment as a storytelling device. Films have shown its fundamental role for the creation of suspense. Interactive fiction and games have unveiled the possibility of plots with multiple choices, giving continuity to cinema split-screen experiences. Using practical examples, this paper will show how this storytelling tool returns to its primitive form and ends up by conditioning cloud computing interface design.

Tbx1 and Bmp2 in the development of the ear, neural crest and pharyngeal system in mice

Dissertation presented to obtain the Ph.D degree in Biology

Uncertainty, generalization, and neural representation of relevant variables for decision making

Dissertation presented to obtain the Ph.D degree in Biology, Computational Biology.

Heterogeneous computing with an algorithmic skeleton framework

The Graphics Processing Unit (GPU) is present in almost every modern day personal computer. Despite its specific purpose design, they have been increasingly used for general computations with very good results. Hence, there is a growing effort from the community to seamlessly integrate this kind of devices in everyday computing. However, to fully exploit the potential of a system comprising GPUs and CPUs, these devices should be presented to the programmer as a single platform. The efficient combination of the power of CPU and GPU devices is highly dependent on each device’s characteristics, resulting in platform specific applications that cannot be ported to different systems. Also, the most efficient work balance among devices is highly dependable on the computations to be performed and respective data sizes. In this work, we propose a solution for heterogeneous environments based on the abstraction level provided by algorithmic skeletons. Our goal is to take full advantage of the power of all CPU and GPU devices present in a system, without the need for different kernel implementations nor explicit work-distribution.To that end, we extended Marrow, an algorithmic skeleton framework for multi-GPUs, to support CPU computations and efficiently balance the work-load between devices. Our approach is based on an offline training execution that identifies the ideal work balance and platform configurations for a given application and input data size. The evaluation of this work shows that the combination of CPU and GPU devices can significantly boost the performance of our benchmarks in the tested environments, when compared to GPU-only executions.

Optimization of breast tomosynthesis image reconstruction using parallel computing

Breast cancer is the most common cancer among women, being a major public health problem. Worldwide, X-ray mammography is the current gold-standard for medical imaging of breast cancer. However, it has associated some well-known limitations. The false-negative rates, up to 66% in symptomatic women, and the false-positive rates, up to 60%, are a continued source of concern and debate. These drawbacks prompt the development of other imaging techniques for breast cancer detection, in which Digital Breast Tomosynthesis (DBT) is included. DBT is a 3D radiographic technique that reduces the obscuring effect of tissue overlap and appears to address both issues of false-negative and false-positive rates. The 3D images in DBT are only achieved through image reconstruction methods. These methods play an important role in a clinical setting since there is a need to implement a reconstruction process that is both accurate and fast. This dissertation deals with the optimization of iterative algorithms, with parallel computing through an implementation on Graphics Processing Units (GPUs) to make the 3D reconstruction faster using Compute Unified Device Architecture (CUDA). Iterative algorithms have shown to produce the highest quality DBT images, but since they are computationally intensive, their clinical use is currently rejected. These algorithms have the potential to reduce patient dose in DBT scans. A method of integrating CUDA in Interactive Data Language (IDL) is proposed in order to accelerate the DBT image reconstructions. This method has never been attempted before for DBT. In this work the system matrix calculation, the most computationally expensive part of iterative algorithms, is accelerated. A speedup of 1.6 is achieved proving the fact that GPUs can accelerate the IDL implementation.

A utilização de uma rede neural artificial para previsão da incidência da malária no município de Cantá, estado de Roraima

INTRODUÇÃO: A malária é uma doença endêmica na Amazônia Legal Brasileira, apresentando riscos diferentes para cada região. O Município de Cantá, no Estado de Roraima, apresentou para todo o período estudado, um dos maiores índices parasitários anuais do Brasil, com valor sempre maior que 50. O presente estudo visa à utilização de uma rede neural artificial para previsão da incidência da malária nesse município, a fim de auxiliar os coordenadores de saúde no planejamento e gestão dos recursos. MÉTODOS: Os dados foram coletados no site do Ministério da Saúde, SIVEP - Malária entre 2003 e 2009. Estruturou-se uma rede neural artificial com três neurônios na camada de entrada, duas camadas intermediárias e uma camada de saída com um neurônio. A função de ativação foi à sigmoide. No treinamento, utilizou-se o método backpropagation, com taxa de aprendizado de 0,05 e momentum 0,01. O critério de parada foi atingir 20.000 ciclos ou uma meta de 0,001. Os dados de 2003 a 2008 foram utilizados para treinamento e validação. Comparam-se os resultados com os de um modelo de regressão logística. RESULTADOS: Os resultados para todos os períodos previstos mostraram-se que as redes neurais artificiais obtiveram um menor erro quadrático médio e erro absoluto quando comparado com o modelo de regressão para o ano de 2009. CONCLUSÕES: A rede neural artificial se mostrou adequada para um sistema de previsão de malária no município estudado, determinando com pequenos erros absolutos os valores preditivos, quando comparados ao modelo de regressão logística e aos valores reais.

Nanostructuring silicon probes via electrodeposition: characterization of electrode coatings for acute in vivo neural recordings

Understanding how the brain works will require tools capable of measuring neuron elec-trical activity at a network scale. However, considerable progress is still necessary to reliably increase the number of neurons that are recorded and identified simultaneously with existing mi-croelectrode arrays. This project aims to evaluate how different materials can modify the effi-ciency of signal transfer from the neural tissue to the electrode. Therefore, various coating materials (gold, PEDOT, tungsten oxide and carbon nano-tubes) are characterized in terms of their underlying electrochemical processes and recording ef-ficacy. Iridium electrodes (177-706 μm2) are coated using galvanostatic deposition under different charge densities. By performing electrochemical impedance spectroscopy in phosphate buffered saline it is determined that the impedance modulus at 1 kHz depends on the coating material and decreased up to a maximum of two orders of magnitude for PEDOT (from 1 MΩ to 25 kΩ). The electrodes are furthermore characterized by cyclic voltammetry showing that charge storage capacity is im-proved by one order of magnitude reaching a maximum of 84.1 mC/cm2 for the PEDOT: gold nanoparticles composite (38 times the capacity of the pristine). Neural recording of spontaneous activity within the cortex was performed in anesthetized rodents to evaluate electrode coating performance.

Identificação das práticas de inovação aberta nas parcerias estratégicas: avaliação realizada com prestadores de cloud computing

No atual contexto da inovação, um grande número de estudos tem analisado o potencial do modelo de Inovação Aberta. Neste sentido, o autor Henry Chesbrough (2003) considerado o pai da Inovação Aberta, afirma que as empresas estão vivenciando uma “mudança de paradigma” na maneira como desenvolvem os seus processos de inovação e na comercialização de tecnologia e conhecimento. Desta forma, o modelo de Inovação Aberta defende que as empresas podem e devem utilizar os recursos disponíveis fora das suas fronteiras sendo esta combinação de ideias e tecnologias internas e externas crucial para atingir uma posição de liderança no mercado. Já afirmava Chesbrough (2003) que não se faz inovação isoladamente e o próprio dinamismo do cenário atual reforça esta ideia. Assim, os riscos inerentes ao processo de inovação podem ser atenuados através da realização de parcerias entre empresas e instituições. A adoção do modelo de Inovação Aberta é percebida com base na abundância de conhecimento disponível, que poderá proporcionar valor também à empresa que o criou, como é o caso do licenciamento de patentes. O presente estudo teve como objetivo identificar as práticas de Inovação Aberta entre as parcerias mencionadas pelas empresas prestadoras de Cloud Computing. Através da Análise de Redes Sociais foram construídas matrizes referentes às parcerias mencionadas pelas empresas e informações obtidas em fontes secundárias (Sousa, 2012). Essas matrizes de relacionamento (redes) foram analisadas e representadas através de diagramas. Desta forma, foi possível traçar um panorama das parcerias consideradas estratégicas pelas empresas entrevistadas e identificar quais delas constituem, de fato, práticas de Inovação Aberta. Do total de 26 parcerias estratégicas mencionadas nas entrevistas, apenas 11 foram caracterizadas como práticas do modelo aberto. A análise das práticas conduzidas pelas empresas entrevistadas permite verificar algumas limitações no aproveitamento do modelo de Inovação Aberta. Por fim, são feitas algumas recomendações sobre a implementação deste modelo pelas pequenas e médias empresas baseadas em tecnologias emergentes, como é o caso do conceito de cloud computing.

Electromyography function, disability degree, and pain in leprosy patients undergoing neural mobilization treatment

INTRODUCTION: This study aimed to evaluate the effect of the neural mobilization technique on electromyography function, disability degree, and pain in patients with leprosy. METHODS: A sample of 56 individuals with leprosy was randomized into an experimental group, composed of 29 individuals undergoing treatment with neural mobilization, and a control group of 27 individuals who underwent conventional treatment. In both groups, the lesions in the lower limbs were treated. In the treatment with neural mobilization, the procedure used was mobilization of the lumbosacral roots and sciatic nerve biased to the peroneal nerve that innervates the anterior tibial muscle, which was evaluated in the electromyography. RESULTS: Analysis of the electromyography function showed a significant increase (p<0.05) in the experimental group in both the right (Δ%=22.1, p=0.013) and the left anterior tibial muscles (Δ%=27.7, p=0.009), compared with the control group pre- and post-test. Analysis of the strength both in the movement of horizontal extension (Δ%right=11.7, p=0.003/Δ%left=27.4, p=0.002) and in the movement of back flexion (Δ%right=31.1; p=0.000/Δ%left=34.7, p=0.000) showed a significant increase (p<0.05) in both the right and the left segments when comparing the experimental group pre- and post-test. The experimental group showed a significant reduction (p=0.000) in pain perception and disability degree when the pre- and post-test were compared and when compared with the control group in the post-test. CONCLUSIONS: Leprosy patients undergoing the technique of neural mobilization had an improvement in electromyography function and muscle strength, reducing disability degree and pain.

Posicionamento do Brasil face aos países mais avançados em cloud computing

This study discusses some fundamental issues so that the development and diffusion of services based in cloud computing happen positively in several countries. For exposure of this subject is discusses public initiatives by the most advanced countries in terms of cloud computing application and the brazilin position in this context. Based on presented evidences here it appears that the essential elements for the development and diffusion of cloud computing in Brazil made important steps and show evidence of maturity, as the cybercrime legislation. However, other elements still require analysis and specifically adaptations for the cloud computing case, such as the Intellectual Property Rights. Despite showing broadband services still lacking, one cannot disregard the government effort to facilitate access for all society. In contrast, the large volume of the Brazilian IT market is an interest factor for companies seeking to invest in the country.

Factors associated with neural alterations and physical disabilities in patients with leprosy in São Luis, State of Maranhão, Brazil

Introduction Leprosy is a chronic infectious disease that is caused by Mycobacterium leprae. The objective of this study was to evaluate the risk factors that are associated with neural alterations and physical disabilities in leprosy patients at the time of diagnosis. Methods A prospective cross-sectional study was conducted on 155 leprosy patients who participated in a program that aimed to eliminate leprosy from São Luis, State of Maranhão. Results Patients who were 31-45 years of age, were older than 60 years of age or had a partner were more likely to have a disability. Patients with partners were 1.14 times more likely (p = 0.025) to have disabilities of the hands. The frequency of disabilities in the feet among the patients with different clinical forms of leprosy was statistically significant. Conclusions The identification of risk factors that are associated with neural alterations and physical disabilities in leprosy patients is important for diagnosing the disease because this approach enables physicians to plan and prioritize actions for the treatment and monitoring of patients.

From "Humanities and Computing" to "Digital Humanities": Digital Humanities in Portugal with a focus on Historical Research

In the following text I will develop three major aspects. The first is to draw attention to those who seem to have been the disciplinary fields where, despite everything, the Digital Humanities (in the broad perspective as will be regarded here) have asserted themselves in a more comprehensive manner. I think it is here that I run into greater risks, not only for what I have mentioned above, but certainly because a significant part, perhaps, of the achievements and of the researchers might have escaped the look that I sought to cast upon the past few decades, always influenced by my own experience and the work carried out in the field of History. But this can be considered as a work in progress and it is open to criticism and suggestions. A second point to note is that emphasis will be given to the main lines of development in the relationship between historical research and digital methodologies, resources and tools. Finally, I will try to make a brief analysis of what has been the Digital Humanities discourse appropriation in recent years, with very debatable data and methods for sure, because studies are still scarce and little systematic information is available that would allow to go beyond an introductory reflection.

Predicting market movement with Artificial Neural Networks

This paper presents an application of an Artificial Neural Network (ANN) to the prediction of stock market direction in the US. Using a multilayer perceptron neural network and a backpropagation algorithm for the training process, the model aims at learning the hidden patterns in the daily movement of the S&P500 to correctly identify if the market will be in a Trend Following or Mean Reversion behavior. The ANN is able to produce a successful investment strategy which outperforms the buy and hold strategy, but presents instability in its overall results which compromises its practical application in real life investment decisions.