Avaliação da qualidade de sítios web institucionais: aplicação de métrica às faculdades de medicina do espaço ibérico

Este trabalho visou o desenvolvimento de uma métrica e a sua aplicação na avaliação da qualidade dos sítios web das Faculdades de Medicina Ibéricas, estruturada nas características de alto nível da norma ISO-9126 que interessam aos utilizadores. A aplicação da métrica mostrou-se um processo simples, e a análise comparativa entre as Faculdades Portuguesas e Espanholas, mostrou que, globalmente, não existem diferenças significativas na qualidade dos seus sítios web. This study aimed to develop a metric and its application in assessing the quality of the websites from Iberian medicine schools, structured on the characteristics of high-level ISO-9126 standard that interest to the users. The metric implementation proved to be a simple process, and comparative analysis between the Portuguese and Spanish Schools, showed that, overall, there are no significant differences in the quality of their websites

The relationship between liquidity and profitability in the food & beverage industry evidence from Europe and United States

This Work Project clarifies the relationship between liquidity and profitability based on a sample in the Food & Beverage (F&B) industry, and comparing the largest European and United States companies. The research concludes that liquidity, proxied by current ratio or quick ratio, correlates with return on assets taken as the measure of profitability, and so does the cash conversion cycle and its components. Moreover, company size correlates with liquidity, and indirectly affects ROA. This research contributes and addresses to managers in the F&B industry and recommends how they should act in order to improve profitability in the industry

Digital item processing

Estágio realizado no INESC e orientado pelo Eng.º Pedro CarvalhoTese de mestrado integrado. Engenharia Electrotécnica e de Computadores - Major Telecomunicações. Faculdade de Engenharia. Universidade do Porto. 200

In silico optimization of the production of amino-acids in Escherichia coli

The increasing need to replace chemical synthesis of compounds of interest by more environmentally friendly biological processes is driving the research for microbial cell factories. The industrial production of amino and organic acids includes several examples of success stories using microorganisms to convert inexpensive substrates into added value products. Traditionally, the design of such microbes relied on cycles of random mutagenesis followed by phenotypic selection [1], but a deeper knowledge of the microbial physiology allowed a more rational approach to this optimization problem [2,3]. However, this task is not straightforward, since the cell metabolism has proved to be highly complex and hard to predict. One of the approaches to tackle this problem is to use Systems Biology simulation tools to predict the microorganism behavior when subjected to genetic modifications. Using genome scale stoichiometric models, such as the latest iAF1260 for Escherichia coli [4] one can simulate a great diversity of possible metabolic phenotypes under steady state conditions by imposing flux-balance constrains. The use of flux balanced analysis (FBA) allows the determination of flux values through all the reactions in the network under a set of environmental conditions and genetic manipulations, by using an objective function, such as the maximization of growth [5]. In this work, we used genetic algorithms, such as OptGene [6] to search for sets of gene knockouts that result in the overproduction in silico of amino-acids in Escherichia coli. From all the proteinogenic amino-acids, glycine yielded the best results in the optimizations. A careful analysis of the in silico flux distribution in some of the mutants revealed an interesting and non-intuitive mechanism behind glycine accumulation. Furthermore, in these mutants the growth is coupled to the production of glycine, which makes them excellent candidates for in vivo implementation. We are reaching a point where bioinformatics tools are advanced enough to aid in complex tasks, such as the optimization of microbial cell factories. Here we described an effort to optimize in silico the production of amino-acids in Escherichia coli, which resulted in the discovery of a potential set of knock-outs that leads to glycine overproduction. This serves to show the increasing importance of in silico optimizations to aid in the metabolic engineering projects, especially to search for non-intuitive beneficial genome modifications

Generic Real-Time Motion Controller for Differential Mobile Robots

Non

Optimization approaches for the in silico discovery of optimal targets for gene over/underexpression

Metabolic engineering (ME) efforts have been recently boosted by the increase in the number of annotated genomes and by the development of several genome-scale metabolic models for microbes of interest in industrial biotechnology. Based on these efforts, strain optimization methods have been proposed to reach the best set of genetic changes to apply to selected host microbes, in order to create strains that are able to overproduce metabolites of industrial interest. Previous work in strain optimization has been mostly based in finding sets of gene (or reaction) deletions that lead to desired phenotypes in computational simulations. In this work, we focus on enlarging the set of possible genetic changes, considering gene over and underexpression. A gene is considered under (over) expressed if its expression value is constrained to be significantly lower (higher) than the one in the wild-type strain, used as a reference. A method is proposed to propagate relative gene expression values to flux constraints over related reactions, making use of the available transcriptional/ translational information. The algorithms chosen for the optimization tasks are metaheuristics such as eolutionary agorithm (EA) and smulated anealing (SA), based on previous successful work on gene knockout optimization. These methods were modified appropriately to accommodate the novel optimization tasks and were applied to study the optimization of succinic and lactic acid production using Escherichia coli as the host. The results are compared with previous ones obtained in gene knockout optimization, thus showing the usefulness of the approach. The methods proposed in this work were implemented in a novel plug-in for OptFlux, an open-source software framework for ME. Supplementary Material is available at www.liebertonline.com/cmb

Optimization of fed-batch fermentation processes with bio-inspired algorithms

The optimization of the feeding trajectories in fed-batch fermentation processes is a complex problem that has gained attention given its significant economical impact. A number of bio-inspired algorithms have approached this task with considerable success, but systematic and statistically significant comparisons of the different alternatives are still lacking. In this paper, the performance of different metaheuristics, such as Evolutionary Algorithms (EAs), Differential Evolution (DE) and Particle Swarm Optimization (PSO) is compared, resorting to several case studies taken from literature and conducting a thorough statistical validation of the results. DE obtains the best overall performance, showing a consistent ability to find good solutions and presenting a good convergence speed, with the DE/rand variants being the ones with the best performance. A freely available computational application, OptFerm, is described that provides an interface allowing users to apply the proposed methods to their own models and data.The work is partially funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT (Portuguese Foundation for Science and Technology) within projects Ref. COMPETE FCOMP-01-0124-FEDER-015079 and PEst-OE/ES/UI0752/2011

A comparison of algorithms for the optimization of fermentation processes

The optimization of biotechnological processes is a complex problem that has been intensively studied in the past few years due to the economic impact of the products obtained from fermentations. In fed-batch processes, the goal is to find the optimal feeding trajectory that maximizes the final productivity. Several methods, including Evolutionary Algorithms (EAs) have been applied to this task in a number of different fermentation processes. This paper performs an experimental comparison between Particle Swarm Optimization, Differential Evolution and a real-valued EA in three distinct case studies, taken from previous work by the authors and literature, all considering the optimization of fed-batch fermentation processes.Portuguese Foundation for Science and Technology - Project POSC/EIA/59899/2004; Project SeARCH (Services and Advanced Research Computing with HTC/HPC clusters)/Contract CONCREEQ/443/2001

'DIS_turbation': An Artistic Approach to Foster Nature-Connectedness

This paper presents practice-based research on ecoacoustics, ocean soundscapes and anthropogenic noise. It explores creative strategies to the introduction, experience and performance of ocean soundscapes in artistic creation. As ocean soundscapes are increasingly a topic of concern globally, they become a crucial tool to foster an emotional affinity between people and natural environments. This research questions how to convey the experience of oceanic soundscapes and their human disruption. The paper details an artistic artefact - DIS_turbation - and its integrative approach, by exploring the vibrational and particle-motion component of ocean sound. The methods include place attachment, creative development, nature-connectedness and ecology of Æffect. The novelty lies in addressing biological processes as a creative resource to intervene in underwater noise dialogue, reveal hidden qualities of vibroacoustic ecology, develop artistic artefacts to translate particle-motion in a more grasping way, and foster inclusion with nature