Methodology for WSN communication technologies automated field tests

Wireless Sensor Networks(WSN) are networks of devices used to sense and act that applies wireless radios to communicate. To achieve a successful implementation of a wireless device it is necessary to take in consideration the existence of a wide variety of radios available, a large number of communication parameters (payload, duty cycle, etc.) and environmental conditions that may affect the device’s behaviour. However, to evaluate a specific radio towards a unique application it might be necessary to conduct trial experiments, with such a vast amount of devices, communication parameters and environmental conditions to take into consideration the number of trial cases generated can be surprisingly high. Thus, making trial experiments to achieve manual validation of wireless communication technologies becomes unsuitable due to the existence of a high number of trial cases on the field. To overcome this technological issue an automated test methodology was introduced, presenting the possibility to acquire data regarding the device’s behaviour when testing several technologies and parameters that care for a specific analysis. Therefore, this method advances the validation and analysis process of the wireless radios and allows the validation to be done without the need of specific and in depth knowledge about wireless devices

A study on the robustness of strain optimization algorithms

5th International Conference on Practical Applications of Computational Biology & Bioinformatics (PACBB 2011), ISBN 978-3-642-19913-4In recent years, there have been considerable advances in the use of genome-scale metabolic models to provide accurate phenotype simulation methods, which in turn enabled the development of efficient strain optimization algorithms for Metabolic Engineering. In this work, we address some of the limitations of previous studies regarding strain optimization algorithms, mainly its use of Flux Balance Analysis in the simulation layer.We perform a thorough analysis of previous results by relying on Flux Variability Analysis and on alternative methods for phenotype simulation, such as ROOM. This last method is also used in the simulation layer, as a basis for optimization, and the results obtained are also the target of thorough analysis and comparison with previous ones.Fundação para a Ciência e a Tecnologia (FCT) - project MIT-PT/BS-BB/0082/200

Estudo de caso de uma intervenção de promoção da alimentação saudável a partir da escola

Esta comunicação discute os resultados obtidos num estudo de caso, focado no desenvolvimento de um projeto educativo orientado para a ação na promoção de mudanças nos estilos de vida e condições de vida que levam a uma alimentação saudável. O estudo envolveu os alunos do 1º ciclo do Ensino Básico (N=14) e visou: i) analisar as dimensões do conhecimento orientado para ação construídas por esses alunos, durante o desenvolvimento do projeto de Educação Alimentar orientado para a ação (problemas identificados e suas consequências e causas; visões para o futuro em relação a esses problemas e ações desenvolvidas para os resolver); ii) analisar como evoluiu o seu grau de participação e autonomia durante o projeto. O estudo está ancorado no paradigma qualitativo, tendo sido feita a recolha de dados em contexto natural, com recurso à observação participante e diários de bordo elaborados pela investigadora, bem como à análise dos documentos produzidos pelos alunos e a um questionário de respostas abertas. Os resultados obtidos mostram que as crianças compreenderam que as causas dos problemas alimentares estão ancoradas na falta de conhecimento e em factores culturais e económicos; foram capazes de apresentar estratégias criativas que envolveram a família e a comunidade para agirem sobre essas causas visando a resolução dos problemas e agiram para as implementar promovendo as mudanças desejadas. Estes resultados mostram algumas evidências sobre as potencialidades dos projetos educativos orientados para a ação na capacitação de alunos do 1º ciclo para agirem como catalisadores de mudanças sociais, envolvendo a família e a comunidade.Instituto de Educação, Centro de Investigação em Educação (CIEd

Iterators and interaction

Eigth International Workshop on Computing with Terms and Graphs (TERMGRAPH’09), 2009We propose a method for encoding iterators (and recursion operators in general) using interaction nets. There are two main applications for this: the method can be used to obtain a visual notation for functional programs, in a visual programming system; and it can be used to extend the existing translations of the λ-calculus into interaction nets (that have been proposed as efficient implementation mechanisms) to languages with recursive types. This work can also be seen as a study of the relation between interaction net programming and functional programming

Functional programming and program transformation with interaction nets

Techon. Report DI-PURe 05.05.02.In this paper we propose to use Interaction Nets as a formalism for Visual Functional Programming. We consider the use of recursion patterns and introduce a suitable archetype/instantiation mechanism for interaction agents. We also consider program transformation by fusion, a well-known transformation technique, and show that this extends smoothly to our visual programming framework. Examples of applying this technique include transformations of two-pass functions into single-pass ones, and the introduction of accumulations

Visual programming with recursion patterns in interaction nets

In this paper we propose to use Interaction Nets as a formalism for Visual Functional Programming. We consider the use of recursion patterns as a programming idiom, and introduce a suitable archetype/instantiation mechanism for interaction agents, which allows one to define agents whose behaviour is based on recursion patterns.Fundação para a Ciência e a Tecnologia (FCT

Visualizing omics data in the OptFlux workbench

OptFlux is an open-source and extensible workbench for Metabolic Engineering (ME) tasks. Since 2012, OptFlux adoption has been steadily increasing among users, making it one of the reference go-to platforms among the ME community. The workbench supports common ME tasks such as phenotype prediction for both wild-type and mutant genotypes, metabolic control analysis and pathway analysis as well as strain optimization procedures. Moreover, a visualization plug-in is included, allowing the navigation and edition of biochemical network layouts in a multitude of standard formats. This plug-in also allows the overlap of specific phenotypic conditions in the network layouts, providing an intuitive mechanism to explore and understand the associated flux distributions. Navigation between multiple layouts is also included. However, for more specialized applications, such as the inclusion of experimental data, this framework was still lagging behind. In this work, the current visualization platform included in OptFlux is extended to support loading generic experimental data sources (e.g. transcript, protein, metabolite and flux measurements) and mapping it to the model information for posterior overlap with the layouts. The visualization features that will represent this data are also fully customizable. The inclusion of multiple conditions or time-dependent measurements is also supported for metabolite-associated data with intuitive bar-plots being displayed for immediate visual comparison. Finally, compound structural information from KEGG is also automatically downloaded and presented

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

An algorithm to assemble gene-protein-reaction associations for genome-scale metabolic model reconstruction

The considerable growth in the number of sequenced genomes and recent advances in Bioinformatics and Systems Biology fields have provided several genome-scale metabolic models (GSMs) that have been used to provide phenotype simulation methods. Given their importance in biomedical research and biotechnology applications (e.g. in Metabolic Engineering efforts), several workflows and computational platforms have been proposed for GSM reconstruction. One of the challenges of these methods is related to the assignment of gene-protein-reaction (GPR) associations that allow to add transcriptional/ translational information to GSMs, a task typically addressed through manual literature curation. This work proposes a novel algorithm to create a set of GPR rules, based on the integration of the information provided by the genome annotation with information on protein composition and function (protein complexes, sub-units, iso-enzymes, etc.) provided by the UniProt database. The methods are validated by using two state-of-the-art models for E. coli and S. cerevisiae, with competitive results.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 Tech- nology) within projects ref. COMPETE FCOMP-01-0124-FEDER-015079 and PEst-OE/EEI/UI0752/2011