84 resultados para model substances
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The reported productivity gains while using models and model transformations to develop entire systems, after almost a decade of experience applying model-driven approaches for system development, are already undeniable benefits of this approach. However, the slowness of higher-level, rule based model transformation languages hinders the applicability of this approach to industrial scales. Lower-level, and efficient, languages can be used but productivity and easy maintenance seize to exist. The abstraction penalty problem is not new, it also exists for high-level, object oriented languages but everyone is using them now. Why is not everyone using rule based model transformation languages then? In this thesis, we propose a framework, comprised of a language and its respective environment, designed to tackle the most performance critical operation of high-level model transformation languages: the pattern matching. This framework shows that it is possible to mitigate the performance penalty while still using high-level model transformation languages.
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The work presented in this thesis was developed in collaboration with a Portuguese company, BeyonDevices, devoted to pharmaceutical packaging, medical technology and device industry. Specifically, the composition impact and surface modification of two polymeric medical devices from the company were studied: inhalers and vaginal applicators. The polyethylene-based vaginal applicator was modified using supercritical fluid technology to acquire self-cleaning properties and prevent the transport of bacteria and yeasts to vaginal flora. For that, in-situ polymerization of 2-substituted oxazolines was performed within the polyethylene matrix using supercritical carbon dioxide. The cationic ring-opening polymerization process was followed by end-capping with N,N-dimethyldodecylamine. Furthermore, for the same propose, the polyethylene matrix was impregnated with lavender oil in supercritical medium. The obtained materials were characterized physical and morphologically and the antimicrobial activity against bacteria and yeasts was accessed. Materials modified using 2-substituted oxazolines showed an effective killing ability for all the tested microorganisms, while the materials modified with lavender oil did not show antimicrobial activity. Only materials modified with oligo(2-ethyl-2-oxazoline) maintain the activity during the long term stability. Furthermore, the cytotoxicity of the materials was tested, confirming their biocompatibilty. Regarding the inhaler, its surface was modified in order to improve powder flowability and consequently, to reduce powder retention in the inhaler´s nozzle. New dry powder inhalers (DPIs), with different needle’s diameters, were evaluated in terms of internal resistance and uniformity of the emitted dose. It was observed that they present a mean resistance of 0.06 cmH2O0.5/(L/min) and the maximum emitted dose obtained was 68.9% for the inhaler with higher needle´s diameter (2 mm). Thus, this inhaler was used as a test and modified by the coating with a commonly-used force control agent, magnesium stearate, dried with supercritical carbon dioxide (scCO2) and the uniformity of delivered dose tests were repeated. The modified inhaler showed an increase in emitted dose from 68.9% to 71.3% for lactose and from 30.0% to 33.7% for Foradil.
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The future of health care delivery is becoming more citizen-centred, as today’s user is more active, better informed and more demanding. The European Commission is promoting online health services and, therefore, member states will need to boost deployment and use of online services. This makes e-health adoption an important field to be studied and understood. This study applied the extended unified theory of acceptance and usage technology (UTAUT2) to explain patients’ individual adoption of e-health. An online questionnaire was administrated Portugal using mostly the same instrument used in UTAUT2 adapted to e-health context. We collected 386 valid answers. Performance expectancy, effort expectancy, social influence, and habit had the most significant explanatory power over behavioural intention and habit and behavioural intention over technology use. The model explained 52% of the variance in behavioural intention and 32% of the variance in technology use. Our research helps to understand the desired technology characteristics of ehealth. By testing an information technology acceptance model, we are able to determine what is more valued by patients when it comes to deciding whether to adopt e-health systems or not.
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Benefits of long-term monitoring have drawn considerable attention in healthcare. Since the acquired data provides an important source of information to clinicians and researchers, the choice for long-term monitoring studies has become frequent. However, long-term monitoring can result in massive datasets, which makes the analysis of the acquired biosignals a challenge. In this case, visualization, which is a key point in signal analysis, presents several limitations and the annotations handling in which some machine learning algorithms depend on, turn out to be a complex task. In order to overcome these problems a novel web-based application for biosignals visualization and annotation in a fast and user friendly way was developed. This was possible through the study and implementation of a visualization model. The main process of this model, the visualization process, comprised the constitution of the domain problem, the abstraction design, the development of a multilevel visualization and the study and choice of the visualization techniques that better communicate the information carried by the data. In a second process, the visual encoding variables were the study target. Finally, the improved interaction exploration techniques were implemented where the annotation handling stands out. Three case studies are presented and discussed and a usability study supports the reliability of the implemented work.
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Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by the pro-gressive loss of motoneurons (MN). Increasing evidence points glial cells as key players for ALS onset and progression. Indeed, MN-glia signalling pathways involving either neuroprotection or inflammation are likely to be altered in ALS. We aimed to study the molecules related with glial function and/or reactivity by evaluating glial markers and hemichannels, mainly present in astrocytes. We also studied molecules involved in mi-croglia-MN dialogue (CXCR3/CCL21; CX3CR1/CX3CL1; MFG-E8), as well as proliferation (Ki-67) and inflammatory-related molecules (TLR2/4, NLRP3; IL-18) and alarming/calming signals (HMGB1/autotaxin). We used lumbar spinal cord (SC) homogenates from mice expressing a mutant human-SOD1 protein (mSOD1) at presymptomatic and late-symptomatic ALS stages. SJL (WT) mice at same ages were used as controls. We observed decreased expression of genes associated with astrocytic (GFAP and S100B) and microglial (CD11b) markers in mSOD1 at the presymptomatic phase, as well as diminished levels of gap junction components pannexin1 and connexin43 and expression of Ki-67 and decreased autotax-in. In addition, microglial-MN communication was negatively affected in mSOD1 mice as well as in-flammatory response. Interestingly, we observed astrocytic (S100B) and microglial (CD11b) reactivity, increased proliferation (Ki-67) and increased autotaxin expression in symptomatic mSOD1 mice. In-creased MN-microglial dialogue (CXCR3/CCL21; CX3CR1/CX3CL1; MFG-E8) and hemichannel activ-ity, namely connexin43 and pannexin1, were also observed in mSOD1 at the symptomatic phase, along with an elevated inflammatory response as indicated by increased levels of HMGB1 and NLRP3. Our results suggest that decreased autotaxin expression is a feature of the presymptomatic stage, and precede the network of pro-inflammatory-related symptomatic determinants, including HMGB1, CCL21, CX3CL1, and NLRP3. The identification of the molecules and signaling pathways that are dif-ferentially activated along ALS progression will contribute for a better design of therapeutic strategies for disease onset and progression.
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RESUMO - A exposição contínua a substâncias químicas tem consequências para a saúde humana, algumas das quais não estão ainda totalmente estabelecidas. A toxicologia ocupacional é uma área interdisciplinar que envolve conhecimentos de higiene e de medicina ocupacional, de epidemiologia e de toxicologia e que tem por principal objectivo prevenir a ocorrência de efeitos adversos decorrentes do ambiente ocupacional sendo um dos seus principais papéis fornecer o máximo de dados que possam contribuir para o conhecimento dos potenciais efeitos na saúde. O chumbo é um tóxico de características cumulativas que provoca na saúde efeitos principalmente sistémicos, ou seja, o efeito tóxico manifesta-se em locais afastados do contacto inicial que resultam essencialmente de exposições crónicas, resultantes de períodos de exposição mais ou menos longos ao metal (entre meses e anos). Pode interagir com diferentes órgãos e tecidos, ligando-se a moléculas e constituintes celulares. Uma vez que não possui qualquer função fisiológica, a presença do chumbo no organismo humano resulta numa série de efeitos prejudiciais que afectam diversos órgãos e sistemas. A toxicidade do chumbo manifesta-se em diversos órgãos e tecidos, nomeadamente no sistema hematopoiético, no sistema nervoso, no rim, no aparelho reprodutor, no sistema cardiovascular, no sistema endócrino e no sistema imunitário. Da interferência do chumbo com o funcionamento de alguns sistemas biológicos resultam um conjunto de alterações fundamentais ao nível dos processos de transporte através das membranas, da integridade estrutural e funcional das enzimas e de várias vias metabólicas, em especial da fosforilação oxidativa e da síntese do heme sendo os primeiros efeitos bioquímicos do chumbo detectados a partir de valores de plumbémia inferiores a 10 μg/dL. As medidas de higiene e segurança actualmente em vigor nos países desenvolvidos asseguram que os casos de intoxicação grave são cada vez menos frequentes. No entanto, o risco de exposição a nível ocupacional existe em todas as actividades que envolvem materiais que o contenham como as explorações mineiras, as fundições primária e secundária, a produção de baterias de chumbo ácido, a produção de vidro com pigmentos de chumbo, as soldaduras de reparação automóvel e a instrução de tiro. Desde 2006 o chumbo é considerado pela International Agency for Research on Cancer (IARC) uma substância carcinogénica do grupo 2A (provável carcinogénio para o ser humano). Considera-se, assim, que o chumbo tem, inequivocamente, capacidade de induzir cancro em animais experimentais mas que, embora haja fortes indícios de que os mecanismos que medeiam a carcinogénese desses compostos ocorrem no ser humano, os dados disponíveis ainda não podem assegurar essa relação. Com este estudo pretendeu-se contribuir para o conhecimento da toxicidade do chumbo através do estudo da exposição ao chumbo e da influência da susceptibilidade individual (em industrias sem co-exposição significativa a outros agentes conhecidos ou suspeitos de serem carcinogénicos). Pretendeu-se estudar o caso através de uma abordagem múltipla que permitisse relacionar diferentes tipos de marcadores biológicos uma vez que a monitorização biológica integra todas as possíveis vias de entrada no organismo (para além da via respiratória), eventuais exposições fora do contexto estritamente profissional assim como uma série de factores intrínsecos individuais (relacionados com modos de via, de natureza fisiológica e comportamentais). Sendo a co-exposição a outros compostos com propriedades genotóxicas e carcinogénicas uma questão difícil de tornear quando se quer avaliar o potencial genotóxico do chumbo em populações expostas, ocupacional ou ambientalmente este estudo tem a vantagem de ter sido efectuado em populações sem co-exposição conhecida a outras substâncias deste tipo, permitindo concluir sobre os efeitos resultantes apenas da exposição a chumbo na população humana, contribuindo para explicar algumas das aparentes inconsistências e contradições entre diferentes estudos sobre este tema. Os indicadores de exposição usados foram: indicadores de dose interna (doseamento de chumbo e de PPZ no sangue), indicadores de efeitos adversos no heme e genotóxicos (actividade da ALAD, teste do cometa e mutação em TCR) e indicadores de susceptibilidade (polimorfismos genéticos de ALAD e VDR) através de uma abordagem estatística de comparação directa de sub-grupos previamente definidos na população e da aplicação de um modelo de regressão múltipla. Este estudo revelou que os níveis de plumbémia na população portuguesa baixaram significativamente nos últimos 10 anos, tanto na população ocupacionalmente exposta como na população em geral e que a presença do genótipo B-B (do gene VDR) é preditiva das variações de plumbémia, quando comparada com o genótipo mais frequente na população, B-b; ao contrário, o genótipo b-b não aparenta ter influência em nenhum dos marcadores estudados. No que diz respeito a efeitos genotóxicos concluiu-se que estes não se manifestaram na população estudada, levando a concluir que nos níveis de exposição estudados, o chumbo não tem capacidade de induzir este tipo de efeitos per si levando ao reforço da hipótese, já levantada por outros autores, de que o mecanismo de genotoxicidade do chumbo seja essencialmente de promoção de processos de genotoxicidade desencadeados por outros agentes. A realização de estudos de efeitos genotóxicos e de stress oxidativo desenhados de forma a comparar grupos de trabalhadores expostos apenas a chumbo com grupos de trabalhadores com o mesmo nível de exposição a chumbo, mas com co-exposição a outros agentes reconhecidamente carcinogénicos poderá ajudar a aumentar o conhecimento deste efeito do chumbo na saúde humana.
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Research on Parkinson’s disease (PD) has mainly focused on the degeneration of the dopaminergic neurons of nigro-striatal (NS) pathway; also, post-mortem studies have demonstrated that the noradrenergic and the serotonergic transmitter systems are also affected (Jellinger, 1999). Degeneration of these neuronal cell bodies is generally thought to start prior to the loss of dopaminergic neurons in the NS pathway and precedes the appearance of the motor symptoms that are the “hallmark” of PD. Gastrointestinal (GI) motility is often disturbed in PD, manifesting chiefly as impaired gastric emptying and constipation. These GI dysfunction symptoms may be the result of a loss in noradrenergic and serotonergic innervation. GI deficits were evaluated using an organ bath technique. Groups treated with different combinations of neurotoxins (6-OHDA alone, 6-OHDA + pCA or 6-OHDA + DSP-4) presented significant differences in gut contractility compared to control groups. Since a substantial body of literature suggests the presence of an inflammatory process in parkinsonian state (Whitton, 2007), changes in pro-inflammatory cytokines in the gut were assessed using a cytokine microarray. It has been found in this work that groups with a combined dopaminergic and noradrenergic lesion have a significant increase in both expressions of IL-13 and VEGF. IL-6 also shows a decrease in treatment groups; however this decrease did not reach statistical significance. The therapeutic value of Exendin-4 (EX-4) was evaluated. It has been previously demonstrated that EX-4, a glucagon-like peptide-1 receptor (GLP-1R) agonist, is neuroprotective in rodent models of PD (Harkavyi et al., 2008). In this thesis it has been found that EX-4 was able to reverse a decrease in gut contractility obtained through intracerebral bilateral 6-OHDA injection. Although more studies are required, EX-4 could be used as a possible therapy for the GI symptoms prominent in the early stages of PD.
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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.
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Companies are increasingly more and more dependent on distributed web-based software systems to support their businesses. This increases the need to maintain and extend software systems with up-to-date new features. Thus, the development process to introduce new features usually needs to be swift and agile, and the supporting software evolution process needs to be safe, fast, and efficient. However, this is usually a difficult and challenging task for a developer due to the lack of support offered by programming environments, frameworks, and database management systems. Changes needed at the code level, database model, and the actual data contained in the database must be planned and developed together and executed in a synchronized way. Even under a careful development discipline, the impact of changing an application data model is hard to predict. The lifetime of an application comprises changes and updates designed and tested using data, which is usually far from the real, production, data. So, coding DDL and DML SQL scripts to update database schema and data, is the usual (and hard) approach taken by developers. Such manual approach is error prone and disconnected from the real data in production, because developers may not know the exact impact of their changes. This work aims to improve the maintenance process in the context of Agile Platform by Outsystems. Our goal is to design and implement new data-model evolution features that ensure a safe support for change and a sound migration process. Our solution includes impact analysis mechanisms targeting the data model and the data itself. This provides, to developers, a safe, simple, and guided evolution process.
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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.
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Field Lab Entrepreneurial Innovative Ventures
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Field Lab in Entrepreneurial Innovative Ventures
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Programmes supporting micro and small enterprises in developing countries have been showing that capital is not enough to allow business success: survival and growth. Literature does not provide comprehensive and practical tool to support business development in this context, but allowed the collection of forty-nine success variables that were studied in a sample of successful and unsuccessful businesses in the Island of Mozambique to discover what were the key factors affecting those businesses’ performance. Empirical data gave the insights for the development of a model to screen and improve business potential of micro and small enterprises in this context.
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Ion Mobility Spectrometry coupled with Multi Capillary Columns (MCC -IMS) is a fast analytical technique working at atmospheric pressure with high sensitivity and selectivity making it suitable for the analysis of complex biological matrices. MCC-IMS analysis generates its information through a 3D spectrum with peaks, corresponding to each of the substances detected, providing quantitative and qualitative information. Sometimes peaks of different substances overlap, making the quantification of substances present in the biological matrices a difficult process. In the present work we use peaks of isoprene and acetone as a model for this problem. These two volatile organic compounds (VOCs) that when detected by MCC-IMS produce two overlapping peaks. In this work it’s proposed an algorithm to identify and quantify these two peaks. This algorithm uses image processing techniques to treat the spectra and to detect the position of the peaks, and then fits the data to a custom model in order to separate the peaks. Once the peaks are separated it calculates the contribution of each peak to the data.
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NSBE - UNL