899 resultados para Isotropic and Anisotropic models


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Apesar das recentes inovações tecnológicas, o setor dos transportes continua a exercer impactes significativos sobre a economia e o ambiente. Com efeito, o sucesso na redução das emissões neste setor tem sido inferior ao desejável. Isto deve-se a diferentes fatores como a dispersão urbana e a existência de diversos obstáculos à penetração no mercado de tecnologias mais limpas. Consequentemente, a estratégia “Europa 2020” evidencia a necessidade de melhorar a eficiência no uso das atuais infraestruturas rodoviárias. Neste contexto, surge como principal objetivo deste trabalho, a melhoria da compreensão de como uma escolha de rota adequada pode contribuir para a redução de emissões sob diferentes circunstâncias espaciais e temporais. Simultaneamente, pretende-se avaliar diferentes estratégias de gestão de tráfego, nomeadamente o seu potencial ao nível do desempenho e da eficiência energética e ambiental. A integração de métodos empíricos e analíticos para avaliação do impacto de diferentes estratégias de otimização de tráfego nas emissões de CO2 e de poluentes locais constitui uma das principais contribuições deste trabalho. Esta tese divide-se em duas componentes principais. A primeira, predominantemente empírica, baseou-se na utilização de veículos equipados com um dispositivo GPS data logger para recolha de dados de dinâmica de circulação necessários ao cálculo de emissões. Foram percorridos aproximadamente 13200 km em várias rotas com escalas e características distintas: área urbana (Aveiro), área metropolitana (Hampton Roads, VA) e um corredor interurbano (Porto-Aveiro). A segunda parte, predominantemente analítica, baseou-se na aplicação de uma plataforma integrada de simulação de tráfego e emissões. Com base nesta plataforma, foram desenvolvidas funções de desempenho associadas a vários segmentos das redes estudadas, que por sua vez foram aplicadas em modelos de alocação de tráfego. Os resultados de ambas as perspetivas demonstraram que o consumo de combustível e emissões podem ser significativamente minimizados através de escolhas apropriadas de rota e sistemas avançados de gestão de tráfego. Empiricamente demonstrou-se que a seleção de uma rota adequada pode contribuir para uma redução significativa de emissões. Foram identificadas reduções potenciais de emissões de CO2 até 25% e de poluentes locais até 60%. Através da aplicação de modelos de tráfego demonstrou-se que é possível reduzir significativamente os custos ambientais relacionados com o tráfego (até 30%), através da alteração da distribuição dos fluxos ao longo de um corredor com quatro rotas alternativas. Contudo, apesar dos resultados positivos relativamente ao potencial para a redução de emissões com base em seleções de rotas adequadas, foram identificadas algumas situações de compromisso e/ou condicionantes que devem ser consideradas em futuros sistemas de eco navegação. Entre essas condicionantes importa salientar que: i) a minimização de diferentes poluentes pode implicar diferentes estratégias de navegação, ii) a minimização da emissão de poluentes, frequentemente envolve a escolha de rotas urbanas (em áreas densamente povoadas), iii) para níveis mais elevados de penetração de dispositivos de eco-navegação, os impactos ambientais em todo o sistema podem ser maiores do que se os condutores fossem orientados por dispositivos tradicionais focados na minimização do tempo de viagem. Com este trabalho demonstrou-se que as estratégias de gestão de tráfego com o intuito da minimização das emissões de CO2 são compatíveis com a minimização do tempo de viagem. Por outro lado, a minimização de poluentes locais pode levar a um aumento considerável do tempo de viagem. No entanto, dada a tendência de redução nos fatores de emissão dos poluentes locais, é expectável que estes objetivos contraditórios tendam a ser minimizados a médio prazo. Afigura-se um elevado potencial de aplicação da metodologia desenvolvida, seja através da utilização de dispositivos móveis, sistemas de comunicação entre infraestruturas e veículos e outros sistemas avançados de gestão de tráfego.

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Os coeficientes de difusão (D 12) são propriedades fundamentais na investigação e na indústria, mas a falta de dados experimentais e a inexistência de equações que os estimem com precisão e confiança em fases comprimidas ou condensadas constituem limitações importantes. Os objetivos principais deste trabalho compreendem: i) a compilação de uma grande base de dados para valores de D 12 de sistemas gasosos, líquidos e supercríticos; ii) o desenvolvimento e validação de novos modelos de coeficientes de difusão a diluição infinita, aplicáveis em amplas gamas de temperatura e densidade, para sistemas contendo componentes muito distintos em termos de polaridade, tamanho e simetria; iii) a montagem e teste de uma instalação experimental para medir coeficientes de difusão em líquidos e fluidos supercríticos. Relativamente à modelação, uma nova expressão para coeficientes de difusão a diluição infinita de esferas rígidas foi desenvolvida e validada usando dados de dinâmica molecular (desvio relativo absoluto médio, AARD = 4.44%) Foram também estudados os coeficientes de difusão binários de sistemas reais. Para tal, foi compilada uma extensa base de dados de difusividades de sistemas reais em gases e solventes densos (622 sistemas binários num total de 9407 pontos experimentais e 358 moléculas) e a mesma foi usada na validação dos novos modelos desenvolvidos nesta tese. Um conjunto de novos modelos foi proposto para o cálculo de coeficientes de difusão a diluição infinita usando diferentes abordagens: i) dois modelos de base molecular com um parâmetro específico para cada sistema, aplicáveis em sistemas gasosos, líquidos e supercríticos, em que natureza do solvente se encontra limitada a apolar ou fracamente polar (AARDs globais na gama 4.26-4.40%); ii) dois modelos de base molecular biparamétricos, aplicáveis em todos os estados físicos, para qualquer tipo de soluto diluído em qualquer solvente (apolar, fracamente polar e polar). Ambos os modelos dão origem a erros globais entre 2.74% e 3.65%; iii) uma correlação com um parâmetro, específica para coeficientes de difusão em dióxido de carbono supercrítico (SC-CO2) e água líquida (AARD = 3.56%); iv) nove correlações empíricas e semi-empíricas que envolvem dois parâmetros, dependentes apenas da temperatura e/ou densidade do solvente e/ou viscosidade do solvente. Estes últimos modelos são muito simples e exibem excelentes resultados (AARDs entre 2.78% e 4.44%) em sistemas líquidos e supercríticos; e v) duas equações preditivas para difusividades de solutos em SC-CO2, em que os erros globais de ambas são inferiores a 6.80%. No global, deve realçar-se o facto de os novos modelos abrangerem a grande variedade de sistemas e moléculas geralmente encontrados. Os resultados obtidos são consistentemente melhores do que os obtidos com os modelos e abordagens encontrados na literatura. No caso das correlações com um ou dois parâmetros, mostrou-se que estes mesmos parâmetros podem ser ajustados usando um conjunto muito pequeno de dados, e posteriormente serem utilizados na previsão de valores de D 12 longe do conjunto original de pontos. Uma nova instalação experimental para medir coeficientes de difusão binários por técnicas cromatográficas foi montada e testada. O equipamento, o procedimento experimental e os cálculos analíticos necessários à obtenção dos valores de D 12 pelo método de abertura do pico cromatográfico, foram avaliados através da medição de difusividades de tolueno e acetona em SC-CO2. Seguidamente, foram medidos coeficientes de difusão de eucaliptol em SC-CO2 nas gamas de 202 – 252 bar e 313.15 – 333.15 K. Os resultados experimentais foram analisados através de correlações e modelos preditivos para D12.

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This Ph.D. research focuses on asymmetric rolling (ASR), as an alternative method for improving mechanical responses of aluminium-magnesium alloy and interstitial free (IF) steel regarding industrial requirements. Aluminium alloys are attractive materials in various industries due to their appropriate properties such as low density and corrosion resistance; however, their low formability has limited their applications. As formability of aluminium alloys can be improved through texture development, part of this dissertation is dedicated to producing the desired crystallographic texture with the ASR process. Two types of ASR (i.e. reverse and continuous asymmetric rolling) were investigated. The impact of shear deformation imposed by ASR processes on developing the desirable texture and consequently on mechanical behaviours was observed. The developed shear texture increased the normal and also planar anisotropy. Texture evolution during plastic deformation as well as induced mechanical behaviour were simulated using the “self-consistent” and Taylor models. Interstitial free (IF) steel was the second material selected in this dissertation. Since IF steel is one of the most often used materials in automotive industries it was chosen to investigate the effect of shear deformation through ASR on its properties. Two types of reverse and continuous asymmetric rolling were carried out to deform IF steel sheets. The results of optical microscopy and atomic force microscopy observations showed no significant difference between the grains’ morphology of asymmetric and conventionally rolled samples, whereas the obtained results of transmission electron microscopy indicated that fine and equiaxed dislocation cells were formed through the asymmetric rolling process. This structure is due to imposed shear deformation during the ASR process. Furthermore, the mechanical behaviour of deformed and annealed sheets was evaluated through uniaxial tensile tests. Results showed that at low thickness reductions (18%) the asymmetric rolled sample presented higher stress than that of the conventionally rolled sheet; while for higher thickness reductions (60%) the trend was reversed. The texture analyses indicated that intense rolling texture components which developed through 60% thickness reduction of conventional rolling cause a relatively higher stress; on the contrary the fine structure resulting from ASR appears to be the source of higher stress observed after pre-deformation of 18%.

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Background In recent years, an abstinence-focused, ‘recovery’ agenda has emerged in UK drug policy, largely in response to the perception that many opioid users had been ‘parked indefinitely’ on Opioid Substitution Therapy (OST). The introduction of ten pilot ‘Drug Recovery Wings’ (DRWs) in 2011 represents the application of this recovery agenda to prisons. This paper describes the DRWs’ operational models, the place of opiate dependent prisoners within them, and the challenges of delivering ‘recovery’ in prison. Methods In 2013, the implementation and operational models of all ten pilot DRWs were rapidly assessed. Up to three days were spent in each DRW, undertaking semi-structured interviews with a sample of 94 DRW staff and 102 DRW residents. Interviews were fully transcribed, and coded using grounded theory. Findings from the nine adult prisons are presented here. Results Four types of DRW were identified, distinguished by their size and selection criteria. Strikingly, no mid- or large-sized units regularly supported OST recipients through detoxification. Type A were large units whose residents were mostly on OST with long criminal records and few social or personal resources. Detoxification was rare, and medication reduction slow. Type B's mid-sized DRW was developed as a psychosocial support service for OST clients seeking detoxification. However, staff struggled to find such prisoners, and detoxification again proved rare. Type C DRWs focused on abstinence from all drugs, including OST. Though OST clients were not intentionally excluded, very few applied to these wings. Only Type D DRWs, offering intensive treatment on very small wings, regularly recruited OST recipients into abstinence-focused interventions. Conclusion Prison units wishing to support OST recipients in making greater progress towards abstinence may need to be small, intensive and take a stepped approach based on preparatory motivational work and extensive preparation for release. However, concerns about post-release deaths will remain.

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Tese de dout., Ciências e Tecnologias das Pescas, Faculdade de Ciências do Mar e do Ambiente, Univ. do Algarve, 2003

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The North Atlantic intertidal community provides a rich set of organismal and environmental material for the study of ecological genetics. Clearly defined environmental gradients exist at multiple spatial scales: there are broad latitudinal trends in temperature, meso-scale changes in salinity along estuaries, and smaller scale gradients in desiccation and temperature spanning the intertidal range. The geology and geography of the American and European coasts provide natural replication of these gradients, allowing for population genetic analyses of parallel adaptation to environmental stress and heterogeneity. Statistical methods have been developed that provide genomic neutrality tests of population differentiation and aid in the process of candidate gene identification. In this paper, we review studies of marine organisms that illustrate associations between an environmental gradient and specific genetic markers. Such highly differentiated markers become candidate genes for adaptation to the environmental factors in question, but the functional significance of genetic variants must be comprehensively evaluated. We present a set of predictions about locus-specific selection across latitudinal, estuarine, and intertidal gradients that are likely to exist in the North Atlantic. We further present new data and analyses that support and contradict these simple selection models. Some taxa show pronounced clinal variation at certain loci against a background of mild clinal variation at many loci. These cases illustrate the procedures necessary for distinguishing selection driven by internal genomic vs. external environmental factors. We suggest that the North Atlantic intertidal community provides a model system for identifying genes that matter in ecology due to the clarity of the environmental stresses and an extensive experimental literature on ecological function. While these organisms are typically poor genetic and genomic models, advances in comparative genomics have provided access to molecular tools that can now be applied to taxa with well-defined ecologies. As many of the organisms we discuss have tight physiological limits driven by climatic factors, this synthesis of molecular population genetics with marine ecology could provide a sensitive means of assessing evolutionary responses to climate change.

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Ecological studies that examine species-environment relationships are often limited to several meteorological parameters, i.e. mean air temperature, relative humidity, precipitation, vapour pressure deficit and solar radiation. The impact of local wind, its speed and direction are less commonly investigated in aerobiological surveys mainly due to difficulties related to the employment of specific analytical tools and interpretation of their outputs. Identification of inoculum sources of economically important plant pathogens, as well as highly allergenic bioaerosols like Cladosporium species, has not been yet explored with remote sensing data and atmospheric models such as Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT). We, therefore, performed an analysis of 24 h intra-diurnal cycle of Cladosporium spp. spores from an urban site in connection with both the local wind direction and overall air mass direction computed by HYSPLIT. The observational method was a volumetric air sampler of the Hirst design with 1 h time resolution and corresponding optical detection of fungal spores with light microscopy. The atmospheric modelling was done using the on-line data set from GDAS with 1° resolution and circular statistical methods. Our results showed stronger, statistically significant correlation (p ≤ 0.05) between high Cladosporium spp. spore concentration and air mass direction compared to the local wind direction. This suggested that a large fraction of the investigated fungal spores had a regional origin and must be located more than a few kilometers away from the sampling point.

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Aims: The study examines the relationship between private and public investment in Zimbabwe utilizing yearly time series data for the period 1967 to 2004. Study Design: Time Series Study. Place and Duration of Study: Zimbabwe, May 2011 to July 2011. Methodology: Emphasis is placed on the direction of causality and the long run and short run effect of the two types of investment on each other. The paper constructs empirical models for both private and public investment, based on the flexible accelerator theory. Private investment is found to be cointegrated with public investment. A cointergration and VEC models are employed to assess the long and short run relationship existing between public and private investment. Conclusion: The relationship between private and public investment is found to be insignificant and the direction of causality found to be unidirectional. The results support the notion that private investment precedes public investment.

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Studies were undertaken to determine the adsorption behavior of α-cypermethrin [R)-α-cyano-3-phenoxybenzyl(1S)-cis- 3-(2,2-dichlorovinyl)-2,2-dimethylcyclopropanecarboxylate, and (S)-α-cyano-3-phenoxybenzyl (1R)-cis-3-(2,2-dichlorovinyl)-2,2- dimethylcyclopropanecarboxylate] in solutions on granules of cork and activated carbon (GAC). The adsorption studies were carried out using a batch equilibrium technique. A gas chromatograph with an electron capture detector (GC-ECD) was used to analyze α-cypermethrin after solid phase extraction with C18 disks. Physical properties including real density, pore volume, surface area and pore diameter of cork were evaluated by mercury porosimetry. Characterization of cork particles showed variations thereby indicating the highly heterogeneous structure of the material. The average surface area of cork particles was lower than that of GAC. Kinetics adsorption studies allowed the determination of the equilibrium time—24 hours for both cork (1–2 mm and 3–4 mm) and GAC. For the studied α-cypermethrin concentration range, GAC revealed to be a better sorbent. However, adsorption parameters for equilibrium concentrations, obtained through the Langmuir and Freundlich models, showed that granulated cork 1–2 mm have the maximum amount of adsorbed α-cypermethrin (qm) (303 μg/g); followed by GAC (186 μg/g) and cork 3-4 mm (136 μg/g). The standard deviation (SD) values, demonstrate that Freundlich model better describes the α-cypermethrin adsorption phenomena on GAC, while α-cypermethrin adsorption on cork (1-2 mm and 3-4 mm) is better described by the Langmuir. In view of the adsorption results obtained in this study it appears that granulated cork may be a better and a cheaper alternative to GAC for removing α-cypermethrin from water.

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This paper presents a novel approach to WLAN propagation models for use in indoor localization. The major goal of this work is to eliminate the need for in situ data collection to generate the Fingerprinting map, instead, it is generated by using analytical propagation models such as: COST Multi-Wall, COST 231 average wall and Motley- Keenan. As Location Estimation Algorithms kNN (K-Nearest Neighbour) and WkNN (Weighted K-Nearest Neighbour) were used to determine the accuracy of the proposed technique. This work is based on analytical and measurement tools to determine which path loss propagation models are better for location estimation applications, based on Receive Signal Strength Indicator (RSSI).This study presents different proposals for choosing the most appropriate values for the models parameters, like obstacles attenuation and coefficients. Some adjustments to these models, particularly to Motley-Keenan, considering the thickness of walls, are proposed. The best found solution is based on the adjusted Motley-Keenan and COST models that allows to obtain the propagation loss estimation for several environments.Results obtained from two testing scenarios showed the reliability of the adjustments, providing smaller errors in the measured values values in comparison with the predicted values.

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The GxE interaction only became widely discussed from evolutionary studies and evaluations of the causes of behavioral changes of species cultivated in environments. In the last 60 years, several methodologies for the study of adaptability and stability of genotypes in multiple environments trials were developed in order to assist the breeder's choice regarding which genotypes are more stable and which are the most suitable for the crops in the most diverse environments. The methods that use linear regression analysis were the first to be used in a general way by breeders, followed by multivariate analysis methods and mixed models. The need to identify the genetic and environmental causes that are behind the GxE interaction led to the development of new models that include the use of covariates and which can also include both multivariate methods and mixed modeling. However, further studies are needed to identify the causes of GxE interaction as well as for the more accurate measurement of its effects on phenotypic expression of varieties in competition trials carried out in genetic breeding programs.

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Transport is an essential sector in modern societies. It connects economic sectors and industries. Next to its contribution to economic development and social interconnection, it also causes adverse impacts on the environment and results in health hazards. Transport is a major source of ground air pollution, especially in urban areas, and therefore contributing to the health problems, such as cardiovascular and respiratory diseases, cancer, and physical injuries. This thesis presents the results of a health risk assessment that quantifies the mortality and the diseases associated with particulate matter pollution resulting from urban road transport in Hai Phong City, Vietnam. The focus is on the integration of modelling and GIS approaches in the exposure analysis to increase the accuracy of the assessment and to produce timely and consistent assessment results. The modelling was done to estimate traffic conditions and concentrations of particulate matters based on geo-references data. A simplified health risk assessment was also done for Ha Noi based on monitoring data that allows a comparison of the results between the two cases. The results of the case studies show that health risk assessment based on modelling data can provide a much more detail results and allows assessing health impacts of different mobility development options at micro level. The use of modeling and GIS as a common platform for the integration of different assessments (environmental, health, socio-economic, etc.) provides various strengths, especially in capitalising on the available data stored in different units and forms and allows handling large amount of data. The use of models and GIS in a health risk assessment, from a decision making point of view, can reduce the processing/waiting time while providing a view at different scales: from micro scale (sections of a city) to a macro scale. It also helps visualising the links between air quality and health outcomes which is useful discussing different development options. However, a number of improvements can be made to further advance the integration. An improved integration programme of the data will facilitate the application of integrated models in policy-making. Data on mobility survey, environmental monitoring and measuring must be standardised and legalised. Various traffic models, together with emission and dispersion models, should be tested and more attention should be given to their uncertainty and sensitivity

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This research is titled “The Future of Airline Business Models: Which Will Win?” and it is part of the requirements for the award of a Masters in Management from NOVA BSE and another from Luiss Guido Carlo University. The purpose is to elaborate a complete market analysis of the European Air Transportation Industry in order to predict which Airlines, strategies and business models may be successful in the next years. First, an extensive literature review of the business model concept has been done. Then, a detailed overview of the main European Airlines and the strategies that they have been implementing so far has been developed. Finally, the research is illustrated with three case studies

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Neurological disorders are a major concern in modern societies, with increasing prevalence mainly related with the higher life expectancy. Most of the current available therapeutic options can only control and ameliorate the patients’ symptoms, often be-coming refractory over time. Therapeutic breakthroughs and advances have been hampered by the lack of accurate central nervous system (CNS) models. The develop-ment of these models allows the study of the disease onset/progression mechanisms and the preclinical evaluation of novel therapeutics. This has traditionally relied on genetically engineered animal models that often diverge considerably from the human phenotype (developmentally, anatomically and physiologically) and 2D in vitro cell models, which fail to recapitulate the characteristics of the target tissue (cell-cell and cell-matrix interactions, cell polarity). The in vitro recapitulation of CNS phenotypic and functional features requires the implementation of advanced culture strategies that enable to mimic the in vivo struc-tural and molecular complexity. Models based on differentiation of human neural stem cells (hNSC) in 3D cultures have great potential as complementary tools in preclinical research, bridging the gap between human clinical studies and animal models. This thesis aimed at the development of novel human 3D in vitro CNS models by integrat-ing agitation-based culture systems and a wide array of characterization tools. Neural differentiation of hNSC as 3D neurospheres was explored in Chapter 2. Here, it was demonstrated that human midbrain-derived neural progenitor cells from fetal origin (hmNPC) can generate complex tissue-like structures containing functional dopaminergic neurons, as well as astrocytes and oligodendrocytes. Chapter 3 focused on the development of cellular characterization assays for cell aggregates based on light-sheet fluorescence imaging systems, which resulted in increased spatial resolu-tion both for fixed samples or live imaging. The applicability of the developed human 3D cell model for preclinical research was explored in Chapter 4, evaluating the poten-tial of a viral vector candidate for gene therapy. The efficacy and safety of helper-dependent CAV-2 (hd-CAV-2) for gene delivery in human neurons was evaluated, demonstrating increased neuronal tropism, efficient transgene expression and minimal toxicity. The potential of human 3D in vitro CNS models to mimic brain functions was further addressed in Chapter 5. Exploring the use of 13C-labeled substrates and Nucle-ar Magnetic Resonance (NMR) spectroscopy tools, neural metabolic signatures were evaluated showing lineage-specific metabolic specialization and establishment of neu-ron-astrocytic shuttles upon differentiation. Chapter 6 focused on transferring the knowledge and strategies described in the previous chapters for the implementation of a scalable and robust process for the 3D differentiation of hNSC derived from human induced pluripotent stem cells (hiPSC). Here, software-controlled perfusion stirred-tank bioreactors were used as technological system to sustain cell aggregation and dif-ferentiation. The work developed in this thesis provides practical and versatile new in vitro ap-proaches to model the human brain. Furthermore, the culture strategies described herein can be further extended to other sources of neural phenotypes, including pa-tient-derived hiPSC. The combination of this 3D culture strategy with the implemented characterization methods represents a powerful complementary tool applicable in the drug discovery, toxicology and disease modeling.