Incorporating sustainability into a chemical company’s modus operandi

The intent of this dissertation is to review relevant existing management systems and chemical industry initiatives to identify synergies, overlaps and gaps with Sustainability best practices, to map the barriers to the incorporation of Sustainability and formulate recommendations to facilitate execution of Sustainability practices within existing management systems. A chemical industry Sustainability survey was conducted through APEQ, the Portuguese association of chemical companies, which constitutes the first baseline on the topic for this national industry association. The commonly used international standards and the Responsible Care® (RC) initiative were cross-referenced against the United Nations Global Compact Assessment Tool. Guidance on how to incorporate Sustainability into a company‘s modus operandi was collapsed into Sustainability Playbooks. The survey revealed that 73% of the APEQ member companies that participated in the survey have a Sustainability Plan. Both large and small/medium APEQ member companies see the market not willing to pay extra for ‗greener‘ products as one of the main barriers. APEQ large enterprise see complexity of implementation and low return on investment as the other most significant barriers while small/medium enterprise respond that the difficulty to predict customer sustainability needs is the other most significant barrier. Amongst many other insights from this survey reported to APEQ, Life Cycle Assessment practices were found to have a low level of implementation and were also considered of low importance, thus identifying a very important opportunity in Sustainability practices to be addressed by APEQ. Two hundred and seventy three assessment points from United Nations Global Compact Assessment Tool plus five additional items were cross-referenced with international standard requirements. With the authorization of the intellectual property owners, the United Nations Global Compact Assessment Tool was modified to introduce actionable recommendations for each gap identified by management standard. This tool was automated to output specific recommendations for 63 possible combinations after simply selecting from a list of commonly used management standards and the RC initiative. Finally this modified tool was introduced into Playbooks for Incorporation of Sustainability at two levels: a ―Get Started Playbook‖ for beginners or small/medium size enterprise and an ―Advanced Playbook‖ as a second advancement stage or for large enterprise.

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.

Serodiagnosis of strongyloidiasis. The application and significance

Parasitological diagnosis based on the faecal examination is frequently difficult in cases of chronic, low-level S. stercoralis infection. Even when a newly developed sensitive method (an agar plate culture) is applied, it is essential to examine faecal samples repeatedly to achieve a correct diagnosis. Additionally, it is important to note that a negative result does not necessarily indicate the unequivocal absence of the infection. On the other hand, several serological tests which have recently been developed for strongyloidiasis have proven reliable when used to complement parasitological examination. We have developed two serological tests, ELISA and GPAT, to demonstrate Strongyloides infection and possible applications of the serological tests for diagnosis, mass-screening, epidemiological study and postchemotherapy evaluation of strongyloidiasis were reviewed based on our recent studies.

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