Ageing on commercial automotive catalysts, a structure reactivity study

Increasingly stringed regulations for diesel engine emissions have a significant impact on the required efficiency of DOC. Lowered DOC oxidation efficiency due to thermal aging effects influences the efficiency of the exhaust aftertreatment systems downstream of the DOC. In this work carried out in the Jean Le Rond d’Alembert Institute the effect of hydrothermal aging on the reactivity and structure of a commercial DOC was investigated. The characterization of the catalytic performance was carried out on a synthetic gas bench using carrots catalyst under conditions close to the realistic conditions i.e. using a synthetic gas mixture, representative of the exhaust gases from diesel engines. Different structural characterization techniques were performed: textural and morphological proprieties were analyzed by BET and TEM, the characterization of the presented crystallographic phases was performed by DRX and the determination of the number of reducible species was possible by TPR. TEM results shown, an increase of the metal particle size with the aging caused by the agglomeration of metal particles, revealing the presence of metal sintering. DRX results also suggest the presence of support sintering. Furthermore, DRX and BET results unexpectedly reveal that the most drastic aging conditions used actually activated the catalyst surface. As expected, the aging affected negatively the catalyst performance on the oxidation of methane and CO, however an improvement of the NO oxidation performance with the aging was observed. Nevertheless, for the aging conditions used, catalytic activity results show that the influence of aging in DOC performance was not significant, and therefore, more drastic aging conditions must be used.

Influence of Lean and Green on supply chain performance: an interpretive structural modelling model

This work aims to identify and rank a set of Lean and Green practices and supply chain performance measures on which managers should focus to achieve competitiveness and improve the performance of automotive supply chains. The identification of the contextual relationships among the suggested practices and measures, was performed through literature review. Their ranking was done by interviews with professionals from the automotive industry and academics with wide knowledge on the subject. The methodology of interpretive structural modelling (ISM) is a useful methodology to identify inter relationships among Lean and Green practices and supply chain performance measures and to support the evaluation of automotive supply chain performance. Using the ISM methodology, the variables under study were clustered according to their driving power and dependence power. The ISM methodology was proposed to be used in this work. The model intends to provide a better understanding of the variables that have more influence (driving variables), the others and those which are most influenced (dependent variables) by others. The information provided by this model is strategic for managers who can use it to identify which variables they should focus on in order to have competitive supply chains.

Land cover mapping analysis and urban growth modeling using remote sensing techniques

The rapid growth of big cities has been noticed since 1950s when the majority of world population turned to live in urban areas rather than villages, seeking better job opportunities and higher quality of services and lifestyle circumstances. This demographic transition from rural to urban is expected to have a continuous increase. Governments, especially in less developed countries, are going to face more challenges in different sectors, raising the essence of understanding the spatial pattern of the growth for an effective urban planning. The study aimed to detect, analyse and model the urban growth in Greater Cairo Region (GCR) as one of the fast growing mega cities in the world using remote sensing data. Knowing the current and estimated urbanization situation in GCR will help decision makers in Egypt to adjust their plans and develop new ones. These plans should focus on resources reallocation to overcome the problems arising in the future and to achieve a sustainable development of urban areas, especially after the high percentage of illegal settlements which took place in the last decades. The study focused on a period of 30 years; from 1984 to 2014, and the major transitions to urban were modelled to predict the future scenarios in 2025. Three satellite images of different time stamps (1984, 2003 and 2014) were classified using Support Vector Machines (SVM) classifier, then the land cover changes were detected by applying a high level mapping technique. Later the results were analyzed for higher accurate estimations of the urban growth in the future in 2025 using Land Change Modeler (LCM) embedded in IDRISI software. Moreover, the spatial and temporal urban growth patterns were analyzed using statistical metrics developed in FRAGSTATS software. The study resulted in an overall classification accuracy of 96%, 97.3% and 96.3% for 1984, 2003 and 2014’s map, respectively. Between 1984 and 2003, 19 179 hectares of vegetation and 21 417 hectares of desert changed to urban, while from 2003 to 2014, the transitions to urban from both land cover classes were found to be 16 486 and 31 045 hectares, respectively. The model results indicated that 14% of the vegetation and 4% of the desert in 2014 will turn into urban in 2025, representing 16 512 and 24 687 hectares, respectively.

Enhancement of an implemented rating model and impact on existing risk management processes: A hands-on approach from financial supplier risk management within the automotive industry

The purpose of this paper is to conduct a methodical drawback analysis of a financial supplier risk management approach which is currently implemented in the automotive industry. Based on identified methodical flaws, the risk assessment model is further developed by introducing a malus system which incorporates hidden risks into the model and by revising the derivation of the most central risk measure in the current model. Both methodical changes lead to significant enhancements in terms of risk assessment accuracy, supplier identification and workload efficiency.

Flexible multivariate GARCH modeling with an application to international stock markets

This paper offers a new approach to estimating time-varying covariance matrices in the framework of the diagonal-vech version of the multivariate GARCH(1,1) model. Our method is numerically feasible for large-scale problems, produces positive semidefinite conditional covariance matrices, and does not impose unrealistic a priori restrictions. We provide an empirical application in the context of international stock markets, comparing the nev^ estimator with a number of existing ones.

Produção de matrizes porosas 3D baseadas em réplicas invertidas de cristais coloidais

A Engenharia de Tecidos surge da necessidade recorrente de regenerar ou recriar órgãos e tecidos danificados devido a vários tipos de trauma. A carência de funcionalidades resultante pode ser resolvida através da implantação de substitutos bio-sintéticos. O presente trabalho consiste na produção de matrizes porosas 3D baseadas em réplicas invertidas de cristais coloidais com futura aplicação em substituintes ósseos sintéticos para fraturas de não-união. O substituinte ósseo consiste numa estrutura denominada Inverse colloidal crystal (ICC), em que a sua organização singular resulta numa homogénea proliferação celular e num aumento das propriedades mecânicas, quando comparada com outros substituintes. O primeiro passo para a obtenção desta estrutura é a produção de microesferas de poliestireno, por uma técnica baseada em microfluídica. Posteriormente as microesferas são empacotadas resultando numa estrutura coesa com ligações entre microesferas vizinhas. O preenchimento dos espaços vazios entre microesferas pelo biomaterial pretendido e posterior remoção das microesferas dá origem à estrutura porosa do ICC. ICCs poliméricos (ϕCs = 1,00) e compósitos (ϕCs = 0,86 e ϕHA = 0,14; ϕCs = 0,67 e ϕHA = 0,33; ϕCs = ϕHA = 0,50) são produzidos e as suas propriedades mecânicas são testadas através de ensaios de compressão e comparadas com outros substituintes sintéticos. Para avaliação do comportamento dos materiais em contacto com meio biológico, foram realizados testes de citotoxicidade que revelaram uma viabilidade celular acima dos 80% em todos os ICCs.

Development of 3D in vitro models for prediction of hepatic metabolism and toxicity

The development of human cell models that recapitulate hepatic functionality allows the study of metabolic pathways involved in toxicity and disease. The increased biological relevance, cost-effectiveness and high-throughput of cell models can contribute to increase the efficiency of drug development in the pharmaceutical industry. Recapitulation of liver functionality in vitro requires the development of advanced culture strategies to mimic in vivo complexity, such as 3D culture, co-cultures or biomaterials. However, complex 3D models are typically associated with poor robustness, limited scalability and compatibility with screening methods. In this work, several strategies were used to develop highly functional and reproducible spheroid-based in vitro models of human hepatocytes and HepaRG cells using stirred culture systems. In chapter 2, the isolation of human hepatocytes from resected liver tissue was implemented and a liver tissue perfusion method was optimized towards the improvement of hepatocyte isolation and aggregation efficiency, resulting in an isolation protocol compatible with 3D culture. In chapter 3, human hepatocytes were co-cultivated with mesenchymal stem cells (MSC) and the phenotype of both cell types was characterized, showing that MSC acquire a supportive stromal function and hepatocytes retain differentiated hepatic functions, stability of drug metabolism enzymes and higher viability in co-cultures. In chapter 4, a 3D alginate microencapsulation strategy for the differentiation of HepaRG cells was evaluated and compared with the standard 2D DMSO-dependent differentiation, yielding higher differentiation efficiency, comparable levels of drug metabolism activity and significantly improved biosynthetic activity. The work developed in this thesis provides novel strategies for 3D culture of human hepatic cell models, which are reproducible, scalable and compatible with screening platforms. The phenotypic and functional characterization of the in vitro systems performed contributes to the state of the art of human hepatic cell models and can be applied to the improvement of pre-clinical drug development efficiency of the process, model disease and ultimately, development of cell-based therapeutic strategies for liver failure.

Experimental and modeling studies on reverse electrodialysis for sustainable power generation

A potentially renewable and sustainable source of energy is the chemical energy associated with solvation of salts. Mixing of two aqueous streams with different saline concentrations is spontaneous and releases energy. The global theoretically obtainable power from salinity gradient energy due to World’s rivers discharge into the oceans has been estimated to be within the range of 1.4-2.6 TW. Reverse electrodialysis (RED) is one of the emerging, membrane-based, technologies for harvesting the salinity gradient energy. A common RED stack is composed by alternately-arranged cation- and anion-exchange membranes, stacked between two electrodes. The compartments between the membranes are alternately fed with concentrated (e.g., sea water) and dilute (e.g., river water) saline solutions. Migration of the respective counter-ions through the membranes leads to ionic current between the electrodes, where an appropriate redox pair converts the chemical salinity gradient energy into electrical energy. Given the importance of the need for new sources of energy for power generation, the present study aims at better understanding and solving current challenges, associated with the RED stack design, fluid dynamics, ionic mass transfer and long-term RED stack performance with natural saline solutions as feedwaters. Chronopotentiometry was used to determinate diffusion boundary layer (DBL) thickness from diffusion relaxation data and the flow entrance effects on mass transfer were found to avail a power generation increase in RED stacks. Increasing the linear flow velocity also leads to a decrease of DBL thickness but on the cost of a higher pressure drop. Pressure drop inside RED stacks was successfully simulated by the developed mathematical model, in which contribution of several pressure drops, that until now have not been considered, was included. The effect of each pressure drop on the RED stack performance was identified and rationalized and guidelines for planning and/or optimization of RED stacks were derived. The design of new profiled membranes, with a chevron corrugation structure, was proposed using computational fluid dynamics (CFD) modeling. The performance of the suggested corrugation geometry was compared with the already existing ones, as well as with the use of conductive and non-conductive spacers. According to the estimations, use of chevron structures grants the highest net power density values, at the best compromise between the mass transfer coefficient and the pressure drop values. Finally, long-term experiments with natural waters were performed, during which fouling was experienced. For the first time, 2D fluorescence spectroscopy was used to monitor RED stack performance, with a dedicated focus on following fouling on ion-exchange membrane surfaces. To extract relevant information from fluorescence spectra, parallel factor analysis (PARAFAC) was performed. Moreover, the information obtained was then used to predict net power density, stack electric resistance and pressure drop by multivariate statistical models based on projection to latent structures (PLS) modeling. The use in such models of 2D fluorescence data, containing hidden, but extractable by PARAFAC, information about fouling on membrane surfaces, considerably improved the models fitting to the experimental data.

Modeling and forecasting value-at-risk for the Portuguese stock market

The aim of this work project is to find a model that is able to accurately forecast the daily Value-at-Risk for PSI-20 Index, independently of the market conditions, in order to expand empirical literature for the Portuguese stock market. Hence, two subsamples, representing more and less volatile periods, were modeled through unconditional and conditional volatility models (because it is what drives returns). All models were evaluated through Kupiec’s and Christoffersen’s tests, by comparing forecasts with actual results. Using an out-of-sample of 204 observations, it was found that a GARCH(1,1) is an accurate model for our purposes.

The impact of talent management practices on employee retention: The moderator effect of leader-member exchange and role modeling

Organizations are undergoing serious difficulties to retain talent. Authors argue that Talent Management (TM) practices create beneficial outcomes for individuals and organizations. However, there is no research on the leaders’ role in the functioning of these practices. This study examines how LMX and role modeling influence the impact that TM practices have on employees’ trust in their organizations and retention. The analysis of two questionnaires (Nt1=175; Nt2=107) indicated that TM only reduced turnover intentions, via an increase in trust in the organization, when role modeling was high and not when it was low. Therefore, we can say that leaders are crucial in the TM context, and in sustaining a competitive advantage for organizations.

Produção e caracterização de espumas 3D obtidas por electrofiação para aplicação em engenharia de tecidos

A produção de estruturas tridimensionais poliméricas tem sido foco de estudo por parte da Engenharia de Células e Tecidos, pelo que mimetizam melhor as condições in vivo dos tecidos. A conjugação das propriedades eléctricas com arquitectura 3D permite uma regeneração tecidual mais eficaz. Desta forma este estudo incidiu na construção de scaffolds, que conjugasse as propriedades mecânicas, eléctricas e biológicas num só suporte. O processo utilizado para produção de scaffolds baseou-se na electrofiação de soluções poliméricas de PCL (8% m/m) com incorporação de óxido de grafeno em diferentes concentrações: 0.01%, 0.1% e 0.25% (m/V). Foram avaliados os parâmetros de electrofiação que permitiram a organização tridimensional. A composição química e a morfologia das membranas foram avaliadas por FTIR-ATR e por microscopia electrónica de varrimento (MEV), respectivamente. Através de ensaios de tracção e de permeabilidade estudou-se a influência de óido de grafeno na matriz polimérica. Foram feitas experiências de redução de óxido de grafeno nas fibras electrofiadas, tanto nas membranas como das espumas, através do uso de vapores de hidrazina. Este mecanismo mostrou-se ineficaz, uma vez que afectou a sua morfologia. As espumas foram avaliadas quanto à sua bioactividade e propriedades mecânicas (ensaios de compressão). Também foram realizados testes de viabilidade celular nas membranas e de adesão celular nas espumas, de forma a avaliar o seu potencial para aplicação biomédica. Os resultados destes ensaios revelaram que óxido de grafeno não apresenta efeitos citotóxicos para o organismo e a sua presença promove a adesão celular ao scaffold.

Jogo 3D online para reabilitação de pacientes afásicos

Esta plataforma foi projetada como auxílio complementar ao processo de reabilitação de doentes afásicos lusófonos. Uma gama de exercícios são disponibilizados de forma a induzir diferentes estímulos (compreensão escrita e auditiva e expressão escrita) sendo a grande maioria destes realizados dentro de um ambiente virtual em três dimensões onde o utilizador (dependendo da tarefa) pode interagir com objetos presentes dentro de uma casa. A principal particularidade desta plataforma reside no facto desta estar alojada online, dispensando instalações e permitindo um acompanhamento mais próximo por parte do terapeuta da fala do progresso feito pelo paciente. A ferramenta desenvolvida está disponível para visualização e teste no endereço www.weblisling.net.

Building 3D City Models: Testing and Comparing Laser Scanning and Low-Cost UAV Data Using FOSS Technologies

Contém resumo

Modeling and optimization of extracellular polysaccharides production by Enterobacter A47

Polysaccharides are gaining increasing attention as potential environmental friendly and sustainable building blocks in many fields of the (bio)chemical industry. The microbial production of polysaccharides is envisioned as a promising path, since higher biomass growth rates are possible and therefore higher productivities may be achieved compared to vegetable or animal polysaccharides sources. This Ph.D. thesis focuses on the modeling and optimization of a particular microbial polysaccharide, namely the production of extracellular polysaccharides (EPS) by the bacterial strain Enterobacter A47. Enterobacter A47 was found to be a metabolically versatile organism in terms of its adaptability to complex media, notably capable of achieving high growth rates in media containing glycerol byproduct from the biodiesel industry. However, the industrial implementation of this production process is still hampered due to a largely unoptimized process. Kinetic rates from the bioreactor operation are heavily dependent on operational parameters such as temperature, pH, stirring and aeration rate. The increase of culture broth viscosity is a common feature of this culture and has a major impact on the overall performance. This fact complicates the mathematical modeling of the process, limiting the possibility to understand, control and optimize productivity. In order to tackle this difficulty, data-driven mathematical methodologies such as Artificial Neural Networks can be employed to incorporate additional process data to complement the known mathematical description of the fermentation kinetics. In this Ph.D. thesis, we have adopted such an hybrid modeling framework that enabled the incorporation of temperature, pH and viscosity effects on the fermentation kinetics in order to improve the dynamical modeling and optimization of the process. A model-based optimization method was implemented that enabled to design bioreactor optimal control strategies in the sense of EPS productivity maximization. It is also critical to understand EPS synthesis at the level of the bacterial metabolism, since the production of EPS is a tightly regulated process. Methods of pathway analysis provide a means to unravel the fundamental pathways and their controls in bioprocesses. In the present Ph.D. thesis, a novel methodology called Principal Elementary Mode Analysis (PEMA) was developed and implemented that enabled to identify which cellular fluxes are activated under different conditions of temperature and pH. It is shown that differences in these two parameters affect the chemical composition of EPS, hence they are critical for the regulation of the product synthesis. In future studies, the knowledge provided by PEMA could foster the development of metabolically meaningful control strategies that target the EPS sugar content and oder product quality parameters.