Gold nanoprobes for the detection of mutations associated with antibiotic resistance in Mycobacterium tuberculosis complex

Dissertação para obtenção do Grau de Mestre em Genética Molecular e Biomedicina

High or low initial setting price?: Initial setting price as prediction of intention to bid in on line auctions

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Livros on-line da área médica

O trabalho indica alguns sites a serem considerados como alternativa para acesso gratuito a livros on-line disponíveis na Internet e destinados à área médica.

A system’s approach to cache hierarchy-aware decomposition of data-parallel computations

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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.

Produção e facilitação da visualização on-line de uma carta de desporto de natureza

Os Sistemas de Informação Geográfica detêm um papel de crescente importância para a tomada de decisão ao nível do ordenamento do território, conforme o que a própria legislação evidencia. Existe uma carência de uniformização da informação para que possa existir um cruzamento eficiente e uma disponibilização mais facilitada à população e às diversas entidades. As instituições públicas, como é o caso do Instituto de Conservação e Florestas (ICNF I.P.), reconhecem esta necessidade, pelo que se propôs uma série de tarefas, para a concretização deste estágio, no sentido de a colmatar. Este instituto detém um papel de especial relevo na conservação do património natural assim como no ordenamento das áreas protegidas para que se possa usufruir das mesmas, sob um ponto de vista cada vez mais ecológico e promotor de desenvolvimento sustentável. A elaboração de um instrumento de gestão territorial, como se pode classificar a Carta de Desporto de Natureza (CDN), acarreta grande responsabilidade e exige um forte empenho, não apenas no envolvimento da população e das entidades que dele fruirão, mas no cumprimento da legislação existente quer para as atividades quer para o próprio território, no sentido da sua proteção, preservação e promoção de usos adequados. Neste trabalho procurou-se cumprir todas estas disposições sempre com o objetivo de, ao se construir normas de uniformização e ao se elaborar um exemplo de CDN para um território com tanto valor como é a Reserva Natural do Estuário do Tejo, tornar acessível a informação sobre esta área protegida. A intensão é também promover a motivação para a prática de um desporto natureza, saudável e em equilíbrio com o ambiente. O desafio não se ficou por aqui, havendo também a procura de utilização de Free Open Source Software, para que o processo de utilização e disponibilização informação SIG seja cada vez mais acessível e direta.

Avaliação da sustentabilidade corporativa: estudo das relações híbridas pelo modelo do Hybrid Bottom Line

A presente tese reflete sobre os temas do desenvolvimento sustentável, da sustentabilidade corporativa, da responsabilidade social corporativa e das dimensões do Triple Bottom Line. O principal objetivo do nosso trabalho é contribuir para o conhecimento das relações que se estabelecem nas interseções entre a dimensão económica, social e ambiental da sustentabilidade corporativa, aqui designadas de relações híbridas. Neste sentido, desenvolveu-se um enquadramento teórico que fundamenta o modelo proposto, designado por Hybrid Bottom Line. De acordo com este enquadramento procurou-se conceber uma metodologia que permitisse analisar como é que estas relações de interseção entre economia-ambiente e economia-social se verificam e de que forma os seus resultados podem beneficiar a compreensão, avaliação e melhorias no entendimento da sustentabilidade corporativa, bem como possibilitar uma análise dirigida a fatores recombinantes específicos. Em complemento, foi desenvolvida uma proposta que permite posicionar o esforço desenvolvido pela empresa no âmbito da sustentabilidade e desta forma tipificar as suas ações. Nesta tese a abordagem empírica recaiu na análise dos relatórios de sustentabilidade publicados pelas empresas e baseados nas diretivas de relato propostas pelo Global Reporting Initiative. A amostra para o estudo abrangeu um total de 85 empresas de diferentes dimensões de 36 sectores económicos e representando 36 países de 5 continentes. A análise dos resultados foi feita utilizando diversos métodos de análise de dados (de frequência e de conteúdo) e análises estatísticas (análise de contingência, variância e de correspondências múltiplas) que permitiram observar as relações entre as dimensões do Triple Bottom Line, dando lugar à construção de uma matriz de relações híbridas. Seguidamente foi realizada uma análise longitudinal de uma das empresas da amostra tendo como referência a matriz híbrida obtida, assim como a tipificação da empresa no âmbito da sustentabilidade. Os resultados alcançados nas diferentes fases indicam que o enquadramento teórico que foi utilizado é útil para a análise das interseções entre as dimensões e permite uma avaliação dirigida a fatos ocorridos entre pares dimensionais, bem como projetar análises e posicionamentos futuros. Os resultados obtidos sugerem que a proposta apresentada é útil e deverá ser utilizada e desenvolvida noutros contextos. Esta tese contribui para a ideia de que a responsabilidade corporativa não deve ser só vista e operacionalizada como uma realidade de dimensões segmentadas mas também deve ser observada como um conjunto possível de interações que se manifestam nas interseções das suas diferentes dimensões.

In-line rheo-optical characterization during small-scale polymer processing and compounding

As increasingly more sophisticated materials and products are being developed and times-to-market need to be minimized, it is important to make available fast response characterization tools using small amounts of sample, capable of conveying data on the relationships between rheological response, process-induced material structure and product characteristics. For this purpose, a single / twin-screw mini-extrusion system of modular construction, with well-controlled outputs in the range 30-300 g/h, was coupled to a in- house developed rheo-optical slit die able to measure shear viscosity and normal-stress differences, as well as performing rheo-optical experiments, namely small angle light scattering (SALS) and polarized optical microscopy (POM). In addition, the mini-extruder is equipped with ports that allow sample collection, and the extrudate can be further processed into products to be tested later. Here, we present the concept and experimental set-up [1, 2]. As a typical application, we report on the characterization of the processing of a polymer blend and of the properties of extruded sheets. The morphological evolution of a PS/PMMA industrial blend along the extruder, the flow-induced structures developed and the corresponding rheological characteristics are presented, together with the mechanical and structural characteristics of produced sheets. The application of this experimental tool to other material systems will also be discussed.

Implementation of a lean six sigma project in a production line

Companies from the motorcycles components branch are dealing with a dynamic environment, resulting from the introduction of new products and the increase of market demand. This dynamic environment requires frequent changes in production lines and requires flexibility in the processes, which can cause reductions in the level of quality and productivity. This paper presents a Lean Six Sigma improvement project performed in a production line of the company's machining sector, in order to eliminate losses that cause low productivity, affecting the fulfillment of the production plan and customer satisfaction. The use of Lean methodology following the DMAIC stages allowed analyzing the factors that influence the line productivity loss. The major problems and causes that contribute to a reduction on productivity and that were identified in this study are the lack of standardization in the setup activities and the excessive stoppages for adjustment of the processes that caused an increase of defects. Control charts, Pareto analysis and cause-and-effect diagrams were used to analyze the problem. On the improvement stage, the changes were based on the reconfiguration of the line layout as well as the modernization of the process. Overall, the project justified an investment in new equipment, the defective product units were reduced by 84% and an increase of 29% of line capacity was noticed.

Parallel improved Schnorr-Euchner enumeration SE++ for the CVP and SVP

The Closest Vector Problem (CVP) and the Shortest Vector Problem (SVP) are prime problems in lattice-based cryptanalysis, since they underpin the security of many lattice-based cryptosystems. Despite the importance of these problems, there are only a few CVP-solvers publicly available, and their scalability was never studied. This paper presents a scalable implementation of an enumeration-based CVP-solver for multi-cores, which can be easily adapted to solve the SVP. In particular, it achieves super-linear speedups in some instances on up to 8 cores and almost linear speedups on 16 cores when solving the CVP on a 50-dimensional lattice. Our results show that enumeration-based CVP-solvers can be parallelized as effectively as enumeration-based solvers for the SVP, based on a comparison with a state of the art SVP-solver. In addition, we show that we can optimize the SVP variant of our solver in such a way that it becomes 35%-60% faster than the fastest enumeration-based SVP-solver to date.

On line pre-concentration for simultaneous determination of low molecular weight organic acids and inorganic anions in Amazonian river water samples employing ion chromatography with conductivity detection

An ion chromatography procedure, employing an IonPac AC15 concentrator column was used to investigate on line preconcentration for the simultaneous determination of inorganic anions and organic acids in river water. Twelve organic acids and nine inorganic anions were separated without any interference from other compounds and carry-over problems between samples. The injection loop was replaced by a Dionex AC15 concentrator column. The proposed procedure employed an auto-sampler that injected 1.5 ml of sample into a KOH mobile phase, generated by an Eluent Generator, at 1.5 mL min-1, which carried the sample to the chromatographic columns (one guard column, model AG-15, and one analytical column, model AS15, with 250 x 4mm i.d.). The gradient elution concentrations consisted of a 10.0 mmol l-1 KOH solution from 0 to 6.5 min, gradually increased to 45.0 mmol l-1 KOH at 21 min., and immediatelly returned and maintained at the initial concentrations until 24 min. of total run. The compounds were eluted and transported to an electro-conductivity detection cell that was attached to an electrochemical detector. The advantage of using concentrator column was the capability of performing routine simultaneous determinations for ions from 0.01 to 1.0 mg l-1 organic acids (acetate, propionic acid, formic acid, butyric acid, glycolic acid, pyruvate, tartaric acid, phthalic acid, methanesulfonic acid, valeric acid, maleic acid, oxalic acid, chlorate and citric acid) and 0.01 to 5.0 mg l-1 inorganic anions (fluoride, chloride, nitrite, nitrate, bromide, sulfate and phosphate), without extensive sample pretreatment and with an analysis time of only 24 minutes.

Off-line simulation inspires insight: a neurodynamics approach to efficient robot task learning

There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner.

Numerical simulation of the reflow soldering process

Dissertação de mestrado integrado em Mechanical Engineering