Innovative manufacturing process for hybrid pultruded products based on cork and polymeric pre-shapes

Pultruded products are being targeted by a growing demand due to its excellent mechanical properties and low chemical reactivity, ensuring a low level of maintenance operations and allowing an easier assembly operation process than equivalent steel bars. In order to improve the mechanical drawing process and solve some acoustic and thermal insulation problems, pultruded pipes of glass fibre reinforced plastics (GFRF) can be filled with special products that increase their performance regarding the issues previously referred. The great challenge of this work was drawing a new equipment able to produce pultruded pipes filled with cork or polymeric pre-shaped bars as a continuous process. The project was carried out successfully and the new equipment was built and integrated in the pultrusion equipment already existing, allowing to obtain news products with higher added-value in the market, covering some needs previously identified in the field of civil construction.

Including context in a routing algorithm for the internet of things

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Informática

Contribuições da inovação e do empreendedorismo para o desempenho das PME angolanas: evidência empírica da cidade de N’Dalatando - KwanzaNorte (ANGOLA)

Dissertação apresentada ao Instituto Politécnico do Porto-Instituto Superior de Contabilidade e Administração do Porto, para obtenção do Grau de Mestre em Empreendedorismo e Internacionalização, sob orientação de Orlando Manuel Martins Marques de Lima Rua, PhD

GPU implementation of a hyperspectral coded aperture algorithm for compressive sensing

This paper presents a new parallel implementation of a previously hyperspectral coded aperture (HYCA) algorithm for compressive sensing on graphics processing units (GPUs). HYCA method combines the ideas of spectral unmixing and compressive sensing exploiting the high spatial correlation that can be observed in the data and the generally low number of endmembers needed in order to explain the data. The proposed implementation exploits the GPU architecture at low level, thus taking full advantage of the computational power of GPUs using shared memory and coalesced accesses to memory. The proposed algorithm is evaluated not only in terms of reconstruction error but also in terms of computational performance using two different GPU architectures by NVIDIA: GeForce GTX 590 and GeForce GTX TITAN. Experimental results using real data reveals signficant speedups up with regards to serial implementation.

GPU implementation of the simplex identification via split augmented Lagrangian

Hyperspectral imaging can be used for object detection and for discriminating between different objects based on their spectral characteristics. One of the main problems of hyperspectral data analysis is the presence of mixed pixels, due to the low spatial resolution of such images. This means that several spectrally pure signatures (endmembers) are combined into the same mixed pixel. Linear spectral unmixing follows an unsupervised approach which aims at inferring pure spectral signatures and their material fractions at each pixel of the scene. The huge data volumes acquired by such sensors put stringent requirements on processing and unmixing methods. This paper proposes an efficient implementation of a unsupervised linear unmixing method on GPUs using CUDA. The method finds the smallest simplex by solving a sequence of nonsmooth convex subproblems using variable splitting to obtain a constraint formulation, and then applying an augmented Lagrangian technique. The parallel implementation of SISAL presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory. The results herein presented indicate that the GPU implementation can significantly accelerate the method's execution over big datasets while maintaining the methods accuracy.

Parallel GPU architecture for hyperspectral unmixing based on augmented Lagrangian method

Hyperspectral imaging has become one of the main topics in remote sensing applications, which comprise hundreds of spectral bands at different (almost contiguous) wavelength channels over the same area generating large data volumes comprising several GBs per flight. This high spectral resolution can be used for object detection and for discriminate between different objects based on their spectral characteristics. One of the main problems involved in hyperspectral analysis is the presence of mixed pixels, which arise when the spacial resolution of the sensor is not able to separate spectrally distinct materials. Spectral unmixing is one of the most important task for hyperspectral data exploitation. However, the unmixing algorithms can be computationally very expensive, and even high power consuming, which compromises the use in applications under on-board constraints. In recent years, graphics processing units (GPUs) have evolved into highly parallel and programmable systems. Specifically, several hyperspectral imaging algorithms have shown to be able to benefit from this hardware taking advantage of the extremely high floating-point processing performance, compact size, huge memory bandwidth, and relatively low cost of these units, which make them appealing for onboard data processing. In this paper, we propose a parallel implementation of an augmented Lagragian based method for unsupervised hyperspectral linear unmixing on GPUs using CUDA. The method called simplex identification via split augmented Lagrangian (SISAL) aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The efficient implementation of SISAL method presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory.

Static detection of anomalies in transactional memory programs

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática

Parallel hyperspectral unmixing method via split augmented lagrangian on GPU

One of the main problems of hyperspectral data analysis is the presence of mixed pixels due to the low spatial resolution of such images. Linear spectral unmixing aims at inferring pure spectral signatures and their fractions at each pixel of the scene. The huge data volumes acquired by hyperspectral sensors put stringent requirements on processing and unmixing methods. This letter proposes an efficient implementation of the method called simplex identification via split augmented Lagrangian (SISAL) which exploits the graphics processing unit (GPU) architecture at low level using Compute Unified Device Architecture. SISAL aims to identify the endmembers of a scene, i.e., is able to unmix hyperspectral data sets in which the pure pixel assumption is violated. The proposed implementation is performed in a pixel-by-pixel fashion using coalesced accesses to memory and exploiting shared memory to store temporary data. Furthermore, the kernels have been optimized to minimize the threads divergence, therefore achieving high GPU occupancy. The experimental results obtained for the simulated and real hyperspectral data sets reveal speedups up to 49 times, which demonstrates that the GPU implementation can significantly accelerate the method's execution over big data sets while maintaining the methods accuracy.

Parallel method for sparse semisupervised hyperspectral unmixing

Parallel hyperspectral unmixing problem is considered in this paper. A semisupervised approach is developed under the linear mixture model, where the abundance's physical constraints are taken into account. The proposed approach relies on the increasing availability of spectral libraries of materials measured on the ground instead of resorting to endmember extraction methods. Since Libraries are potentially very large and hyperspectral datasets are of high dimensionality a parallel implementation in a pixel-by-pixel fashion is derived to properly exploits the graphics processing units (GPU) architecture at low level, thus taking full advantage of the computational power of GPUs. Experimental results obtained for real hyperspectral datasets reveal significant speedup factors, up to 164 times, with regards to optimized serial implementation.

Parallel sparse unmixing of hyperspectral data

In this paper, a new parallel method for sparse spectral unmixing of remotely sensed hyperspectral data on commodity graphics processing units (GPUs) is presented. A semi-supervised approach is adopted, which relies on the increasing availability of spectral libraries of materials measured on the ground instead of resorting to endmember extraction methods. This method is based on the spectral unmixing by splitting and augmented Lagrangian (SUNSAL) that estimates the material's abundance fractions. The parallel method is performed in a pixel-by-pixel fashion and its implementation properly exploits the GPU architecture at low level, thus taking full advantage of the computational power of GPUs. Experimental results obtained for simulated and real hyperspectral datasets reveal significant speedup factors, up to 1 64 times, with regards to optimized serial implementation.

Incapacidade auto-reportada e retorno à actividade profissional em utentes com dor crónica lombar

RESUMO: O absentismo à actividade profissional devido à condição de Dor Lombar apresenta-se como um problema de saúde pública com elevados custos económicos nas sociedades ocidentais. É estimado que cerca de 20% a 47% dos utentes com Dor Lombar não retornam à sua actividade profissional no período de 3 meses, sendo responsáveis por 75% a 90% de todos os custos e baixas médicas associadas à condição. Objectivo: O objectivo deste estudo foi analisar a capacidade de retorno à actividade profissional em utentes com Dor Crónica Lombar (DCL), que procuraram a Fisioterapia em situação de agudização dos seus sintomas, e averiguar a sua relação com os níveis de Incapacidade auto-reportados. Secundariamente pretendemos avaliar a influência das Crenças de medo-evitamento, nos níveis de Incapacidade auto-reportados. Metodologia: Foi efectuado um estudo correlacional prospectivo no qual se observou uma amostra de 56 utentes com DCL que tivessem apresentado novos episódios de agudização dos seus sintomas. Após 3 meses de follow-up (n=42) foi avaliado o “regresso ao trabalho em boas condições” e a sua relação com os níveis de Incapacidade iniciais, bem como o contributo das Crenças de medo-evitamento para essa Incapacidade funcional. Resultados: Foi verificada uma correlação negativa entre os níveis de Incapacidade funcional e o Sucesso no “regresso ao trabalho em boas condições” (ρ = -0.369; p =0.016), sendo que os scores mais elevados da Incapacidade correspondem à Falha nesse regresso. Verificámos também uma correlação positiva entre a existência das Crenças de medo-evitamento relativas ao Trabalho e a Incapacidade (r =0.511; p =0,001), apresentando estas Crenças um valor preditivo (β= 0.533; p =0.001) na Incapacidade auto-reportada. Conclusões: A capacidade de retorno à actividade profissional nos utentes com DCL, após um novo episódio de agudização dos seus sintomas, está relacionada com níveis de Incapacidade funcional. Os factores psicossociais, nomeadamente as Crenças de medo-evitamento relativas ao Trabalho apresentam um valor preditivo para essa Incapacidade auto-reportada.------------------------------ABSTRACT:Work-absenteeism due to the condition of Low Back Pain (LBP) presents itself as a public health problem with high economic costs in Western societies. It is estimated that 20% to 47% of patients with LBP not returned to their work-activity in period of 3 months, accounting for 75% to 90% of all medical costs and sickness compensation associated. Objective: The aim of the present study was to assess the ability to return to work on patients with chronic LBP, who searched for physical therapy in a situation of worsening of their symptoms, and examine their relationship with levels of self-reported disability. Secondly we intend to evaluate the influence of fear-avoidance beliefs to the levels of self-reported disability. Methods: We conducted a prospective cross-sectional study in which we observed 56 patients chronic LBP with new episodes of exacerbation of their symptoms. After a 3 months follow-up (n = 42) we evaluated the “return to work in good health” and its relationship with initial levels of disability and the contribution of fear-avoidance beliefs for that disability. Results: There was a negative correlation between levels of disability and “return to work in good health” success (ρ = -0.369, p = 0.016), with the highest scores correspond to the failure in the work-return. We also found a positive correlation between the existence of fear-avoidance beliefs for work and disability (r = 0.511; p = 0.001), with a predictive value of these fear-avoidance beliefs (β = 0.533; p = 0.001) in self-reported disability. Conclusions: The ability to return to work in chronic LBP patients, after a new episode of exacerbation of symptoms is related to the levels of functional disability. Psychosocial factors, including fear-avoidance beliefs for work showed a predictive value for the self-reported disability.

Dor crónica lombar : incapacidada auto-reportada em trabalhadores de saúde e sua relação com variáveis psicossociais e intensidade da dor

RESUMO: A dor crónica lombar, é uma condição de saúde cuja prevalência tem aumentado nas últimas décadas. É uma condição que pode ser bastante incapacitante para o indivíduo e por consequência, ter importante impacto social e económico na sociedade. É um fenómeno complexo, multifactorial e pouco estudado na população portuguesa. Objectivo: Estudar a associação entre a catastrofização da dor, crenças de medo evitamento da dor, intensidade da dor e a incapacidade funcional auto reportada em indivíduos com dor crónica lombar. Metodologia: Estudo observacional analítico de corte transversal, com uma amostra de 38 indivíduos com dor crónica lombar, seleccionados a partir de uma população de 186 trabalhadores de uma unidade local de saúde. A recolha de dados foi realizada através de 4 instrumentos de avaliação: Questionário de caracterização e levantamento de factores de risco e impacto associados à dor crónica lombar; Questionário de incapacidade de Roland e Morris; Escala de catastrofização da dor; e Questionário de crenças de medo evitamento da dor. A análise dos dados foi feita através de estatística descritiva pela distribuição de frequências e medidas de tendência central para análise da prevalência e caracterização da amostra e por estatística inferencial para estudar as relações entre variáveis através do teste de correlação não paramétrico de Spearman. Resultados: A variável catastrofização da dor obteve um valor de correlação com a incapacidade auto-reportada de rs=0,473, para p<0,01; a variável crença de medo evitamento da dor relacionada com o trabalho obteve um valor de correlação com a incapacidade auto-reportada de rs=0,462 para p<0,01, a percepção da intensidade actual de dor e a intensidade percepcionada no ano anterior, obtiveram valores de correlação com a incapacidade auto-reportada de rs=0,327 e rs= 0,359 respectivamente para valor de p<0,05. Conclusão: As variáveis psicossociais catastrofização da dor e crença de medo evitamento da dor relacionada com o trabalho, influenciam de forma moderada a incapacidade em indivíduos com dor crónica lombar. A associação entre a intensidade da dor e a incapacidade parece ter um papel menos importante demonstrando associações baixas.--------------------------ABSTRACT: Chronic low back pain is a health condition whose prevalence has increased in recent decades. It is a condition that can be quite disabling for the individual and therefore have important social and economic impact on society. It is a complex phenomenon, multifactorial and poorly studied in the Portuguese population. Objective: To study the association between pain catastrophizing, fear avoidance beliefs, pain, pain intensity and self-reported functional disability in individuals with chronic low back pain. Methods: Observational analytical cross sectional study of a sample of 38 individuals with chronic low back pain, selected from a population of 186 workers at a local health unit. Data collection was performed through four assessment instruments: questionnaire characterization, evaluation of risk factors and impact associated to chronic low back pain, questionnaire Roland and Morris disability, pain catastrophizing scale and fear avoidance beliefs questionnaire. Data analysis was performed using descriptive statistics for the distribution of frequencies and measures of central tendency to analyze the prevalence and characteristics of the sample and inferential statistics to study the relationships between variables by testing for Spearman nonparametric correlation. Results: The pain catastrophizing variable had a correlation value rs= 0,473, p<0,01 with the self-reported disability, the variable of fear avoidance belief of pain related to the work achived a correlation value with the self-reported disability, rs = 0.462 p <0.01, current pain intensity and in the previous year obtained values of correlation with self-reported disability rs = 0.327 and rs = 0.359 respectively for values of p <0.05 .Conclusion: The psychosocial variables of pain catastrophizing and fear avoidance belief of pain related to the work had a moderate association with disability in individuals with chronic low back pain. The association between pain intensity and disability seems to have a less important role demonstrating low associations.

Orientação Internacional das Intenções Empreendedoras dos Estudantes do Ensino Superior Politécnico

Dissertação de Mestrado em Gestão e Internacionalização de Empresas

Seroprevalence of antibodies to Venezuelan equine encephalitis complex (subtypes IAB and VI) in humans from General Belgrano Island, Formosa, Argentina

This work presents the results of the detection of antibodies (immunoglobulin G) for subtypes I and VI of VEE viruses complex (Togaviridae family) in people from the General Belgrano island, Formosa province (Argentina). The prevalence of neutralizing (NT) antibodies for subtype VI was from 30% to 70% and the prevalence of antibodies inhibitory of hemagglutination (HI) was of 0% in the first and second inquiry respectively. For the subtype IAB the prevalence of NT antibodies was from 13% to 3.6%, similar to the prevalence total for both subtypes. HI antibodies were not detected in any inquiries for any subtype. It was observed that both subtypes circulate simultaneously, while subtype VI remains constant with some peaks, subtype I was found in low level.

Evolution of genotypes of Group A streptococci from colonization and infection

Dissertação para obtenção do Grau de Doutor em Biologia