959 resultados para disinfection by-product
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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
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Dissertation presented to Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa for obtaining the master degree in Membrane Engineering
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Dissertation presented to Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa for obtaining the master degree in Membrane Engineering
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Platelet function and plasma fibrinogen levels were evaluated in 14 patients, 10 males and 4females, aged 13-59years bitten by Bothrops genus snakes. There was a statistical difference (p < 0.05) among plasma fibrinogen levels evaluated 24 and 48 hours after envenomation. There was a tendency towards normalization after 48 hours of treatment. The low platelet number was clear in 24-48 hour evaluations with a tendency towards normalization after 48 hours of treatment (p<0.05). Fibrinogen levels and fibrin degradation product (FDP) levels appeared to be altered in 83.33% of patients evaluated. The authors suggest that platelet hypoaggregation is related to decreased fibrinogen and increased FDP levels.
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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
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Dissertação para obtenção do Grau de Doutor em Engenharia do Ambiente
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Este trabalho foi efectuado com o apoio da Universidade de Lisboa, Instituto Superior de Agronomia com o Centro de Engenharia dos Biossistemas (CEER
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Field Lab in Entrepreneurial Innovative Ventures
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This work project (WP) is a study about a clustering strategy for Sport Zone. The general cluster study’s objective is to create groups such that within each group the individuals are similar to each other, but should be different among groups. The clusters creation is a mix of common sense, trial and error and some statistical supporting techniques. Our particular objective is to support category managers to better define the product type to be displayed in the stores’ shelves by doing store clusters. This research was carried out for Sport Zone, and comprises an objective definition, a literature review, the clustering activity itself, some factor analysis and a discriminant analysis to better frame our work. Together with this quantitative part, a survey addressed to category managers to better understand their key drivers, for choosing the type of product of each store, was carried out. Based in a non-random sample of 65 stores with data referring to 2013, the final result was the choice of 6 store clusters (Figure 1) which were individually characterized as the main outcome of this work. In what relates to our selected variables, all were important for the distinction between clusters, which proves the adequacy of their choice. The interpretation of the results gives category managers a tool to understand which products best fit the clustered stores. Furthermore, as a side finding thanks to the clusterization, a STP (Segmentation, Targeting and Positioning) was initiated, being this WP the first steps of a continuous process.
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This thesis aims to study how product relatedness to the current pattern of specialization influences the success of industrial policies in underdeveloped sectors. Drawing from Hausmann and Klinger (2006), this work extends the existing literature on the importance of proximity spillovers to explain economic development by focusing on underdeveloped sectors. We find that investment's success in an underdeveloped sector is more likely if it is highly related to the current pattern of specialization. However, heterogeneity amongst sectors is remarkable. Moreover, industrial policy cases are sometimes successful despite the bad odds provided by this criterion, suggesting further factors should be considered.
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Product fundamentals are essential in explaining heterogeneity in the product space. The scope for adapting and transferring capabilities into the production of different goods determines the speed and intensity of the structural transformation process and entails dissimilar development opportunities for nations. Future specialization patterns become then partly determined by the current network of products’ relatedness. Building on previous literature, this paper explicitly compares methodological concepts of product connectivity to conclude in favor of the density measure we propose combined with the Revealed Relatedness Index (RRI) approach presented by Freitas and Salvado (2011). Overall, RRI specifications displayed more consistent behavior when different time horizons are equated.
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Due to the progresses made in the branch of embedded technologies, manufacturers are becoming able to pack their shop floor level manufacturing resources with even more complex functionalities. This technological progression is radically changing the way production systems are designed and deployed, as well as, monitored and controlled. The dissemination of smart devices inside production processes confers new visibility on the production system while enabling for a more efficient and effective management of the operations. By turning the current manufacturing resources functionalities into services based on a Service Oriented Architecture (SOA), in order to expose them as a service to the user, the binomial manufacturing resource/service will push the entire manufacturing enterprise visibility to another level while enabling the global optimization of the operations and processes of a production system while, at the same time, supporting its accommodation to the operational spike easily and with reduced impact on production. The present work implements a Cloud Manufacturing infrastructure for achieving the resource/service value-added i.e. to facilitate the creation of services that are the composition of currently available atomic services. In this context, manufacturing resource virtualization (i.e. formalization of resources capabilities into services accessible inside and outside the enterprise) and semantic representation/description are the pillars for achieving resource service composition. In conclusion, the present work aims to act on the manufacturing resource layer where physical resources and shop floor capabilities are going to be provided to the user as a SaaS (Software as a Service) and/or IaaS (Infrastructure as a Service).
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Software Product Line (SPL) engineering aims at achieving efficient development of software products in a specific domain. New products are obtained via a process which entails creating a new configuration specifying the desired product’s features. This configuration must necessarily conform to a variability model, that describes the scope of the SPL, or else it is not viable. To ensure this, configuration tools are used that do not allow invalid configurations to be expressed. A different concern, however, is making sure that a product addresses the stakeholders’ needs as best as possible. The stakeholders may not be experts on the domain, so they may have unrealistic expectations. Also, the scope of the SPL is determined not only by the domain but also by limitations of the development platforms. It is therefore possible that the desired set of features goes beyond what is possible to currently create with the SPL. This means that configuration tools should provide support not only for creating valid products, but also for improving satisfaction of user concerns. We address this goal by providing a user-centric configuration process that offers suggestions during the configuration process, based on the use of soft constraints, and identifying and explaining potential conflicts that may arise. Suggestions help mitigating stakeholder uncertainty and poor domain knowledge, by helping them address well known and desirable domain-related concerns. On the other hand, automated conflict identification and explanation helps the stakeholders to understand the trade-offs required for realizing their vision, allowing informed resolution of conflicts. Additionally, we propose a prototype-based approach to configuration, that addresses the order-dependency issues by allowing the complete (or partial) specification of the features in a single step. A subsequent resolution process will then identify possible repairs, or trade-offs, that may be required for viabilization.
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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.
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Chesney’s: Growing Through Product Expansion The purpose of this work project is to have a better understanding about how to proceed when a company is challenged by new options to grow and thrive. It aims to decode the next direction of Chesney’s Ltd, a United Kingdom leading company in luxurious replicas of antique fireplaces, wood burning stoves and other architectural pieces. The work project relies on the concepts of strategy, innovation and design thinking in order to encourage dynamic activities within the company. Chesney’s continuously tries to improve and innovate and this work project will assess whether the possible options have strategic fit with the purpose of the company and consequently, create an introduction plan for the opportunity that shows higher probabilities of becoming successful.