Contributo para a construção de um code set da classificação internacional de funcionalidade, incapacidade e saúde, para terapeutas ocupacionais, em unidades de cuidados continuados integrados

A CIF é uma ferramenta universal desenvolvida pela OMS que permite a classificação de funcionalidade e incapacidade, através de uma visualização global do que condiciona o desempenho do indivíduo na concretização de atividades e na participação em ocupações. A ideologia da CIF e os seus componentes interrelacionam-se com a essência da TO, indo ao encontro dos modelos da profissão. As UCCI constituem uma atualidade em Portugal e o terapeuta ocupacional é um dos profissionais obrigatórios na equipa multidisciplinar destas unidades. Atendendo à relevância internacional da CIF, à sua ligação com a TO e à necessidade de tornar a CIF operacional na prática clínica diária dado que é uma ferramenta complexa e extensa, é objetivo deste estudo contribuir para a construção de um code set da CIF para terapeutas ocupacionais que exercem funções em UCCI, especificamente em UC, UMDR e ULDM. Para a concretização desta investigação, utilizou-se a técnica de Delphi, que envolveu duas rondas. Na primeira ronda foi possível contar com a participação de 37 terapeutas ocupacionais experientes na área, uma vez que exercem funções em UCCI, e na segunda ronda contou-se com a participação de 20 elementos. Obtiveram consenso na última ronda de Delphi um total de 96 categorias, constituindo esta listagem uma proposta de code set para UCCI. No que se refere às tipologias de unidades, 69 categorias obtiveram consenso em UC, 91 em UMDR e 41 em ULDM. Concluiu-se que a criação de code sets poderá constituir uma mais-valia em contexto de equipa multidisciplinar das UCCI, sendo uma forma de tornar a CIF operacional na prática clínica diária.

Disruption and phenotypic analysis of six open reading frames from chromosome VII of Saccharomyces cerevisiae reveals one essential gene

Six open reading frames (ORFs) located on chromosome VII of Saccharomyces cerevisiae (YGR205w, YGR210c, YGR211w, YGR241c, YGR243w and YGR244c) were disrupted in two different genetic backgrounds using short-flanking homology (SFH) gene replacement. Sporulation and tetrad analysis showed that YGR211w, recently identified as the yeast ZPR1 gene, is an essential gene. The other five genes are non-essential, and no phenotypes could be associated to their inactivation. Two of these genes have recently been further characterized: YGR241c (YAP1802) encodes a yeast adaptor protein and YGR244c (LSC2) encodes the b-subunit of the succinyl-CoA ligase. For each ORF, a replacement cassette with long flanking regions homologous to the target locus was cloned in pUG7, and the cognate wild-type gene was cloned in pRS416.

Analysis of a 17.9 kb region from Saccharomyces cerevisiae chromosome VII reveals the presence of eight open reading frames, including BRF1 (TFIIIB70) and GCN5 genes

We report the nucleotide sequence of a 17,893 bp DNA segment from the right arm of Saccharomyces cerevisiae chromosome VII. This fragment begins at 482 kb from the centromere. The sequence includes the BRF1 gene, encoding TFIIIB70, the 5' portion of the GCN5 gene, an open reading frame (ORF) previously identified as ORF MGA1, whose translation product shows similarity to heat-shock transcription factors and five new ORFs. Among these, YGR250 encodes a polypeptide that harbours a domain present in several polyA binding proteins. YGR245 is similar to a putative Schizosaccharomyces pombe gene, YGR248 shows significant similarity with three ORFs of S. cerevisiae situated on different chromosomes, while the remaining two ORFs, YGR247 and YGR251, do not show significant similarity to sequences present in databases.

Sequencing of a 9.9 kb segment on the right arm of yeast chromosome VII reveals four open reading frames, including PFK1, the gene coding for succinyl-CoA synthetase (beta-chain) and two ORFs sharing homology with ORFs of the yeast chromosome VIII

A 9.9 kb DNA fragment from the right arm of chromosome VII of Saccharomyces cerevisiae has been sequenced and analysed. The sequence contains four open reading frames (ORFs) longer than 100 amino acids. One gene, PFK1, has already been cloned and sequenced and the other one is the probable yeast gene coding for the beta-subunit of the succinyl-CoA synthetase. The two remaining ORFs share homology with the deduced amino acid sequence (and their physical arrangement is similar to that) of the YHR161c and YHR162w ORFs from chromosome VIII.

Sequencing of a 17.6 kb segment on the right arm of yeast chromosome VII reveals 12 ORFs, including CCT, ADE3 and TR-I genes, homologues of the yeast PMT and EF1G genes, of the human and bacterial electron-transferring flavoproteins (beta-chain) and of the Escherichia coli phosphoserine phosphohydrolase, and five new ORFs.

A 17.6 kb DNA fragment from the right arm of chromosome VII of Saccharomyces cerevisiae has been sequenced and analysed. The sequence contains twelve open reading frames (ORFs) longer than 100 amino acids. Three genes had already been cloned and sequenced: CCT, ADE3 and TR-I. Two ORFs are similar to other yeast genes: G7722 with the YAL023 (PMT2) and PMT1 genes, encoding two integral membrane proteins, and G7727 with the first half of the genes encoding elongation factors 1gamma, TEF3 and TEF4. Two other ORFs, G7742 and G7744, are most probably yeast orthologues of the human and Paracoccus denitrificans electron-transferring flavoproteins (beta chain) and of the Escherichia coli phosphoserine phosphohydrolase. The five remaining identified ORFs do not show detectable homology with other protein sequences deposited in data banks. The sequence has been deposited in the EMBL data library under Accession Number Z49133.

The complete sequence of a 9000 bp fragment of the right arm of Saccharomyces cerevisiae chromosome VII contains four previously unknown open reading frames

We report the sequence of a 9000 bp fragment from the right arm of Saccharomyces cerevisiae chromosome VII. Analysis of the sequence revealed four complete previously unknown open reading frames, which were named G7587, G7589, G7591 and G7594 following standard rules for provisional nomenclature. Outstanding features of some of these proteins were the homology of the putative protein coded by G7589 with proteins involved in transcription regulation and the transmembrane domains predicted in the putative protein coded by G7591.

Clustering an interval data set : are the main partitions similar to a priori partition?

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Dominant set approach to ECG biometrics

Electrocardiographic (ECG) signals are emerging as a recent trend in the field of biometrics. In this paper, we propose a novel ECG biometric system that combines clustering and classification methodologies. Our approach is based on dominant-set clustering, and provides a framework for outlier removal and template selection. It enhances the typical workflows, by making them better suited to new ECG acquisition paradigms that use fingers or hand palms, which lead to signals with lower signal to noise ratio, and more prone to noise artifacts. Preliminary results show the potential of the approach, helping to further validate the highly usable setups and ECG signals as a complementary biometric modality.

Shannon information and power law analysis of the chromosome code

This paper studies the information content of the chromosomes of twenty-three species. Several statistics considering different number of bases for alphabet character encoding are derived. Based on the resulting histograms, word delimiters and character relative frequencies are identified. The knowledge of this data allows moving along each chromosome while evaluating the flow of characters and words. The resulting flux of information is captured by means of Shannon entropy. The results are explored in the perspective of power law relationships allowing a quantitative evaluation of the DNA of the species.

Optimising and adapting the QoS of a dynamic set of inter-dependent tasks

Due to the growing complexity and adaptability requirements of real-time systems, which often exhibit unrestricted Quality of Service (QoS) inter-dependencies among supported services and user-imposed quality constraints, it is increasingly difficult to optimise the level of service of a dynamic task set within an useful and bounded time. This is even more difficult when intending to benefit from the full potential of an open distributed cooperating environment, where service characteristics are not known beforehand and tasks may be inter-dependent. This paper focuses on optimising a dynamic local set of inter-dependent tasks that can be executed at varying levels of QoS to achieve an efficient resource usage that is constantly adapted to the specific constraints of devices and users, nature of executing tasks and dynamically changing system conditions. Extensive simulations demonstrate that the proposed anytime algorithms are able to quickly find a good initial solution and effectively optimise the rate at which the quality of the current solution improves as the algorithms are given more time to run, with a minimum overhead when compared against their traditional versions.

A genetic algorithm for the resource constrained multi-project scheduling problem

This paper presents a genetic algorithm for the resource constrained multi-project scheduling problem. The chromosome representation of the problem is based on random keys. The schedules are constructed using a heuristic that builds parameterized active schedules based on priorities, delay times, and release dates defined by the genetic algorithm. The approach is tested on a set of randomly generated problems. The computational results validate the effectiveness of the proposed algorithm.

The daily and hourly energy consumption and load forecasting using artifitial neural network method: a case study using a set of 93 households in Portugal

It is important to understand and forecast a typical or a particularly household daily consumption in order to design and size suitable renewable energy systems and energy storage. In this research for Short Term Load Forecasting (STLF) it has been used Artificial Neural Networks (ANN) and, despite the consumption unpredictability, it has been shown the possibility to forecast the electricity consumption of a household with certainty. The ANNs are recognized to be a potential methodology for modeling hourly and daily energy consumption and load forecasting. Input variables such as apartment area, numbers of occupants, electrical appliance consumption and Boolean inputs as hourly meter system were considered. Furthermore, the investigation carried out aims to define an ANN architecture and a training algorithm in order to achieve a robust model to be used in forecasting energy consumption in a typical household. It was observed that a feed-forward ANN and the Levenberg-Marquardt algorithm provided a good performance. For this research it was used a database with consumption records, logged in 93 real households, in Lisbon, Portugal, between February 2000 and July 2001, including both weekdays and weekend. The results show that the ANN approach provides a reliable model for forecasting household electric energy consumption and load profile. © 2014 The Author.

Project scheduling under multiple resources constraints using a genetic algorithm

The resource constrained project scheduling problem (RCPSP) is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions. This paper proposes a genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities and delay times of the activities are defined by the genetic algorithm. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

Project scheduling using a competitive genetic algorithm

- The resource constrained project scheduling problem (RCPSP) is a difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms. During the last couple of years many heuristic procedures have been developed for this problem, but still these procedures often fail in finding near-optimal solutions. This paper proposes a genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities and delay times of the activities are defined by the genetic algorithm. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm

A biased random-key genetic algorithm with forward-backward improvement for the resource constrained project scheduling problem

This paper presents a biased random-key genetic algorithm for the resource constrained project scheduling problem. The chromosome representation of the problem is based on random keys. Active schedules are constructed using a priority-rule heuristic in which the priorities of the activities are defined by the genetic algorithm. A forward-backward improvement procedure is applied to all solutions. The chromosomes supplied by the genetic algorithm are adjusted to reflect the solutions obtained by the improvement procedure. The heuristic is tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.