21 resultados para resource-use efficiency


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Due to the importance and wide applications of the DNA analysis, there is a need to make genetic analysis more available and more affordable. As such, the aim of this PhD thesis is to optimize a colorimetric DNA biosensor based on gold nanoprobes developed in CEMOP by reducing its price and the needed volume of solution without compromising the device sensitivity and reliability, towards the point of care use. Firstly, the price of the biosensor was decreased by replacing the silicon photodetector by a low cost, solution processed TiO2 photodetector. To further reduce the photodetector price, a novel fabrication method was developed: a cost-effective inkjet printing technology that enabled to increase TiO2 surface area. Secondly, the DNA biosensor was optimized by means of microfluidics that offer advantages of miniaturization, much lower sample/reagents consumption, enhanced system performance and functionality by integrating different components. In the developed microfluidic platform, the optical path length was extended by detecting along the channel and the light was transmitted by optical fibres enabling to guide the light very close to the analysed solution. Microfluidic chip of high aspect ratio (~13), smooth and nearly vertical sidewalls was fabricated in PDMS using a SU-8 mould for patterning. The platform coupled to the gold nanoprobe assay enabled detection of Mycobacterium tuberculosis using 3 8l on DNA solution, i.e. 20 times less than in the previous state-of-the-art. Subsequently, the bio-microfluidic platform was optimized in terms of cost, electrical signal processing and sensitivity to colour variation, yielding 160% improvement of colorimetric AuNPs analysis. Planar microlenses were incorporated to converge light into the sample and then to the output fibre core increasing 6 times the signal-to-losses ratio. The optimized platform enabled detection of single nucleotide polymorphism related with obesity risk (FTO) using target DNA concentration below the limit of detection of the conventionally used microplate reader (i.e. 15 ng/μl) with 10 times lower solution volume (3 μl). The combination of the unique optical properties of gold nanoprobes with microfluidic platform resulted in sensitive and accurate sensor for single nucleotide polymorphism detection operating using small volumes of solutions and without the need for substrate functionalization or sophisticated instrumentation. Simultaneously, to enable on chip reagents mixing, a PDMS micromixer was developed and optimized for the highest efficiency, low pressure drop and short mixing length. The optimized device shows 80% of mixing efficiency at Re = 0.1 in 2.5 mm long mixer with the pressure drop of 6 Pa, satisfying requirements for the application in the microfluidic platform for DNA analysis.

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Enterprise Resource Planning (ERP) system literature reports very little research on post-adoption stages, that is, actual usage and value. Even fewer studies focus on the specificities of an industry analysis. Based on the Technology-Organizational-Environment (TOE) framework and the Resource-Based View (RBV) theory, we develop a research model to measure and examine determinants of ERP use and value and their impact in the Iberian region (Portugal and Spain) across Manufacturing and Services industries in Small and Medium Enterprises (SMEs). The empirical test was conducted through structural equation modelling, using data from 261 firms in the peninsula in the Manufacturing and Service industries. Results show that amongst ERP use determinants, Training is the most important determinant for Service firms and Compatibility for Manufacturing firms. Firm size, Analytics, and Collaboration contribute to ERP Value in both industries, with Analytics being more important for the Service industry. The paper provides insight into which determinants contribute to ERP use and ERP value in Iberian Manufacturing and Services SMEs, offering managerial and academic implications.

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The reduction of greenhouse gas emissions is one of the big global challenges for the next decades due to its severe impact on the atmosphere that leads to a change in the climate and other environmental factors. One of the main sources of greenhouse gas is energy consumption, therefore a number of initiatives and calls for awareness and sustainability in energy use are issued among different types of institutional and organizations. The European Council adopted in 2007 energy and climate change objectives for 20% improvement until 2020. All European countries are required to use energy with more efficiency. Several steps could be conducted for energy reduction: understanding the buildings behavior through time, revealing the factors that influence the consumption, applying the right measurement for reduction and sustainability, visualizing the hidden connection between our daily habits impacts on the natural world and promoting to more sustainable life. Researchers have suggested that feedback visualization can effectively encourage conservation with energy reduction rate of 18%. Furthermore, researchers have contributed to the identification process of a set of factors which are very likely to influence consumption. Such as occupancy level, occupants behavior, environmental conditions, building thermal envelope, climate zones, etc. Nowadays, the amount of energy consumption at the university campuses are huge and it needs great effort to meet the reduction requested by European Council as well as the cost reduction. Thus, the present study was performed on the university buildings as a use case to: a. Investigate the most dynamic influence factors on energy consumption in campus; b. Implement prediction model for electricity consumption using different techniques, such as the traditional regression way and the alternative machine learning techniques; and c. Assist energy management by providing a real time energy feedback and visualization in campus for more awareness and better decision making. This methodology is implemented to the use case of University Jaume I (UJI), located in Castellon, Spain.

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RESUMO - As organizações de saúde, em geral, e os hospitais, em particular, são frequentemente reconhecidos por terem particularidades e especificidades que conferem uma especial complexidade ao seu processo produtivo e à sua gestão (Jacobs, 1974; Butler, 1995). Neste sentido, na literatura hospitalar emergem alguns temas como prioritários tanto na investigação como na avaliação do seu funcionamento, nomeadamente os relacionados com a produção, com o financiamento, com a qualidade, com a eficiência e com a avaliação do seu desempenho. O estado da arte da avaliação do desempenho das organizações de saúde parece seguir a trilogia definida por Donabedian (1985) — Estrutura, Processo e Resultados. Existem diversas perspectivas para a avaliação do desempenho na óptica dos Resultados — efectividade, eficiência ou desempenho financeiro. No entanto, qualquer que seja a utilizada, o ajustamento pelo risco é necessário para se avaliar a actividade das organizações de saúde, como forma de medir as características dos doentes que podem influenciar os resultados de saúde. Como possíveis indicadores de resultados, existem a mortalidade (resultados finais), as complicações e as readmissões (resultados intermédios). Com excepção dos estudos realizados por Thomas (1996) e Thomas e Hofer (1998 e 1999), praticamente ninguém contesta a relação entre estes indicadores e a efectividade dos cuidados. Chamando, no entanto, a atenção para a necessidade de se definirem modelos de ajustamento pelo risco e ainda para algumas dificuldades conceptuais e operacionais para se atingir este objectivo. Em relação à eficiência técnica dos hospitais, os indicadores tradicionalmente mais utilizados para a sua avaliação são os custos médios e a demora média. Também neste domínio, a grande maioria dos estudos aponta para que a gravidade aumenta o poder justificativo do consumo de recursos e que o ajustamento pelo risco é útil para avaliar a eficiência dos hospitais. Em relação aos sistemas usados para medir a severidade e, consequentemente, ajustar pelo risco, o seu desenvolvimento apresenta, na generalidade, dois tipos de preocupações: a definição dos suportes de recolha da informação e a definição dos momentos de medição. Em última instância, o dilema que se coloca reside na definição de prioridades e daquilo que se pretende sacrificar. Quando se entende que os aspectos financeiros são determinantes, então será natural que se privilegie o recurso quase exclusivo a elementos dos resumos de alta como suporte de recolha da informação. Quando se defende que a validade de construção e de conteúdo é um aspecto a preservar, então o recurso aos elementos dos processos clínicos é inevitável. A definição dos momentos de medição dos dados tem repercussões em dois níveis de análise: na neutralidade económica do sistema e na prospectividade do sistema. O impacto destas questões na avaliação da efectividade e da eficiência dos hospitais não é uma questão pacífica, visto que existem autores que defendem a utilização de modelos baseados nos resumos de alta, enquanto outros defendem a supremacia dos modelos baseados nos dados dos processos clínicos, para finalmente outros argumentarem que a utilização de uns ou outros é indiferente, pelo que o processo de escolha deve obedecer a critérios mais pragmáticos, como a sua exequibilidade e os respectivos custos de implementação e de exploração. Em relação às possibilidades que neste momento se colocam em Portugal para a utilização e aplicação de sistemas de ajustamento pelo risco, verifica-se que é praticamente impossível a curto prazo aplicar modelos com base em dados clínicos. Esta opção não deve impedir que a médio prazo se altere o sistema de informação dos hospitais, de forma a considerar a eventualidade de se utilizarem estes modelos. Existem diversos problemas quando se pretendem aplicar sistemas de ajustamento de risco a populações diferentes ou a subgrupos distintos das populações donde o sistema foi originalmente construído, existindo a necessidade de verificar o ajustamento do modelo à população em questão, em função da sua calibração e discriminação.

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Field lab: Business project

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The interest in using information to improve the quality of living in large urban areas and its governance efficiency has been around for decades. Nevertheless, the improvements in Information and Communications Technology has sparked a new dynamic in academic research, usually under the umbrella term of Smart Cities. This concept of Smart City can probably be translated, in a simplified version, into cities that are lived, managed and developed in an information-saturated environment. While it makes perfect sense and we can easily foresee the benefits of such a concept, presently there are still several significant challenges that need to be tackled before we can materialize this vision. In this work we aim at providing a small contribution in this direction, which maximizes the relevancy of the available information resources. One of the most detailed and geographically relevant information resource available, for the study of cities, is the census, more specifically the data available at block level (Subsecção Estatística). In this work, we use Self-Organizing Maps (SOM) and the variant Geo-SOM to explore the block level data from the Portuguese census of Lisbon city, for the years of 2001 and 2011. We focus on gauging change, proposing ways that allow the comparison of the two time periods, which have two different underlying geographical bases. We proceed with the analysis of the data using different SOM variants, aiming at producing a two-fold portrait: one, of the evolution of Lisbon during the first decade of the XXI century, another, of how the census dataset and SOM’s can be used to produce an informational framework for the study of cities.