759 resultados para “omics” approaches
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ABSTRACT OBJECTIVE To describe different approaches to promote adverse drug reaction reporting among health care professionals, determining their cost-effectiveness. METHODS We analyzed and compared several approaches taken by the Northern Pharmacovigilance Centre (Portugal) to promote adverse drug reaction reporting. Approaches were compared regarding the number and relevance of adverse drug reaction reports obtained and costs involved. Costs by report were estimated by adding the initial costs and the running costs of each intervention. These costs were divided by the number of reports obtained with each intervention, to assess its cost-effectiveness. RESULTS All the approaches seem to have increased the number of adverse drug reaction reports. We noted the biggest increase with protocols (321 reports, costing 1.96 € each), followed by first educational approach (265 reports, 20.31 €/report) and by the hyperlink approach (136 reports, 15.59 €/report). Regarding the severity of adverse drug reactions, protocols were the most efficient approach, costing 2.29 €/report, followed by hyperlinks (30.28 €/report, having no running costs). Concerning unexpected adverse drug reactions, the best result was obtained with protocols (5.12 €/report), followed by first educational approach (38.79 €/report). CONCLUSIONS We recommend implementing protocols in other pharmacovigilance centers. They seem to be the most efficient intervention, allowing receiving adverse drug reactions reports at lower costs. The increase applied not only to the total number of reports, but also to the severity, unexpectedness and high degree of causality attributed to the adverse drug reactions. Still, hyperlinks have the advantage of not involving running costs, showing the second best performance in cost per adverse drug reactions report.
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Recent studies of mobile Web trends show a continuous explosion of mobile-friendly content. However, the increasing number and heterogeneity of mobile devices poses several challenges for Web programmers who want to automatically get the delivery context and adapt the content to mobile devices. In this process, the devices detection phase assumes an important role where an inaccurate detection could result in a poor mobile experience for the enduser. In this paper we compare the most promising approaches for mobile device detection. Based on this study, we present an architecture for a system to detect and deliver uniform m-Learning content to students in a Higher School. We focus mainly on the devices capabilities repository manageable and accessible through an API. We detail the structure of the capabilities XML Schema that formalizes the data within the devices capabilities XML repository and the REST Web Service API for selecting the correspondent devices capabilities data according to a specific request. Finally, we validate our approach by presenting the access and usage statistics of the mobile web interface of the proposed system such as hits and new visitors, mobile platforms, average time on site and rejection rate.
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Next-generation vaccines for tuberculosis should be designed to prevent the infection and to achieve sterile eradication of Mycobacterium tuberculosis. Mucosal vaccination is a needle-free vaccine strategy that provides protective immunity against pathogenic bacteria and viruses in both mucosal and systemic compartments, being a promising alternative to current tuberculosis vaccines. Micro and nanoparticles have shown great potential as delivery systems for mucosal vaccines. In this review, the immunological principles underlying mucosal vaccine development will be discussed, and the application of mucosal adjuvants and delivery systems to the enhancement of protective immune responses at mucosal surfaces will be reviewed, in particular those envisioned for oral and nasal routes of administration. An overview of the essential vaccine candidates for tuberculosis in clinical trials will be provided, with special emphasis on the potential different antigens and immunization regimens.
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In this study, a new waste management solution for thermoset glass fibre reinforced polymer (GFRP) based products was assessed. Mechanical recycling approach, with reduction of GFRP waste to powdered and fibrous materials was applied, and the prospective added-value of obtained recyclates was experimentally investigated as raw material for polyester based mortars. Different GFRP waste admixed mortar formulations were analyzed varying the content, between 4% up to 12% in weight, of GFRP powder and fibre mix waste. The effect of incorporation of a silane coupling agent was also assessed. Design of experiments and data treatment was accomplished through implementation of full factorial design and analysis of variance ANOVA. Added value of potential recycling solution was assessed by means of flexural and compressive loading capacity of GFRP waste admixed mortars with regard to unmodified polymer mortars. The key findings of this study showed a viable technological option for improving the quality of polyester based mortars and highlight a potential cost-effective waste management solution for thermoset composite materials in the production of sustainable concrete-polymer based products.
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In this study the potential eco-efficiency performance of a pultrusion manufacturing company was assessed. Indicators values and eco-efficiency ratios were estimated taking into account the implementation of new proceedings and procedures in the production process of glass fibre reinforced polymers (GFRP) pultrusion profiles. Two different approaches were foreseen: 1)Adoption of a new heating system for pultrusion die in the manufacturing process, more effective and with minor heat losses; and 2) Recycling approach, with partial waste reuse of scrap material derived from manufacturing, cutting and assembly processes of GFRP profiles. These features lead to significant improvements on the sequent assessed eco-efficiency ratios of the present case study, yielding to a more sustainable product and manufacturing process of pultruded GFRP profiles.
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In the last decade, local image features have been widely used in robot visual localization. In order to assess image similarity, a strategy exploiting these features compares raw descriptors extracted from the current image with those in the models of places. This paper addresses the ensuing step in this process, where a combining function must be used to aggregate results and assign each place a score. Casting the problem in the multiple classifier systems framework, in this paper we compare several candidate combiners with respect to their performance in the visual localization task. For this evaluation, we selected the most popular methods in the class of non-trained combiners, namely the sum rule and product rule. A deeper insight into the potential of these combiners is provided through a discriminativity analysis involving the algebraic rules and two extensions of these methods: the threshold, as well as the weighted modifications. In addition, a voting method, previously used in robot visual localization, is assessed. Furthermore, we address the process of constructing a model of the environment by describing how the model granularity impacts upon performance. All combiners are tested on a visual localization task, carried out on a public dataset. It is experimentally demonstrated that the sum rule extensions globally achieve the best performance, confirming the general agreement on the robustness of this rule in other classification problems. The voting method, whilst competitive with the product rule in its standard form, is shown to be outperformed by its modified versions.
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The use of renewables have been increased I several countries around the world, namely in Europe. The wind power is generally the larger renewable resource with very specific characteristics in what concerns its variability and the inherent impacts in the power systems and electricity markets operation. This paper focuses on the Portuguese context of renewables use, including wind power. The work here presented includes the use of a real time pricing methodology developed by the authors aiming the reduction of electricity consumption in the moments of unexpected low wind power. A more specific example of application of real time pricing is demonstrated for the minimization of the operation costs in a distribution network. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs.
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Thesis submitted to the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia for the degree of Doctor of Philosophy in Environmental Sciences
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Dissertation presented to obtain the Ph.D degree in Biochemistry, Plant Physiology
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Neuroschistosomiasis (NS) is the second most common form of presentation of infection by the trematode, Schistosoma mansoni. Granulomatous inflammatory reaction occurs as a result of schistosome eggs being transmitted to spinal cord or brain via the vascular system, or by inadvertent adult worm migration to these organs. The two main clinical syndromes are spinal cord neuroschistosomiasis (acute or subacute myelopathy) and localized cerebral or cerebellar neuroschistosomiasis (focal CNS impairment, seizures, increased intracranial pressure). Presumptive diagnosis of NS requires confirming the presence of S. mansoni infection by stool microscopy or rectal biopsy for trematode eggs, and serologic testing of blood and spinal fluid. The localized lesions are identified by signs and symptoms, and confirmed by imaging techniques (contrast myelography, CT and MRI). Algorithms are presented to allow a stepwise approach to diagnosis.
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Recent Advances in Mechanics and Materials in Design
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Dissertação apresentada para a obtenção do Grau de Doutor em Química Sustentável pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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Dissertação para obtenção do Grau de Mestre em Genética Molecular e Biomedicina