Rapid protein domain assignment from amino acid sequence using predicted secondary structure

The elucidation of the domain content of a given protein sequence in the absence of determined structure or significant sequence homology to known domains is an important problem in structural biology. Here we address how successfully the delineation of continuous domains can be accomplished in the absence of sequence homology using simple baseline methods, an existing prediction algorithm (Domain Guess by Size), and a newly developed method (DomSSEA). The study was undertaken with a view to measuring the usefulness of these prediction methods in terms of their application to fully automatic domain assignment. Thus, the sensitivity of each domain assignment method was measured by calculating the number of correctly assigned top scoring predictions. We have implemented a new continuous domain identification method using the alignment of predicted secondary structures of target sequences against observed secondary structures of chains with known domain boundaries as assigned by Class Architecture Topology Homology (CATH). Taking top predictions only, the success rate of the method in correctly assigning domain number to the representative chain set is 73.3%. The top prediction for domain number and location of domain boundaries was correct for 24% of the multidomain set (±20 residues). These results have been put into context in relation to the results obtained from the other prediction methods assessed

An elastic net orthogonal forward regression algorithm

In this paper we propose an efficient two-level model identification method for a large class of linear-in-the-parameters models from the observational data. A new elastic net orthogonal forward regression (ENOFR) algorithm is employed at the lower level to carry out simultaneous model selection and elastic net parameter estimation. The two regularization parameters in the elastic net are optimized using a particle swarm optimization (PSO) algorithm at the upper level by minimizing the leave one out (LOO) mean square error (LOOMSE). Illustrative examples are included to demonstrate the effectiveness of the new approaches.

Detection of gyrA mutations in quinolone-resistant Salmonella enterica by denaturing high-performance liquid chromatography

Denaturing high-performance liquid chromatography (DHPLC) was evaluated as a rapid screening and identification method for DNA sequence variation detection in the quinolone resistance-determining region of gyrA from Salmonella serovars. A total of 203 isolates of Salmonella were screened using this method. DHPLC analysis of 14 isolates representing each type of novel or multiple mutations and the wild type were compared with LightCycler-based PCR-gyrA hybridization mutation assay (GAMA) and single-strand conformational polymorphism (SSCP) analyses. The 14 isolates gave seven different SSCP patterns, and LightCycler detected four different mutations. DHPLC detected 11 DNA sequence variants at eight different codons, including those detected by LightCycler or SSCP. One of these mutations was silent. Five isolates contained multiple mutations, and four of these could be distinguished from the composite sequence variants by their DHPLC profile. Seven novel mutations were identified at five different loci not previously described in quinolone-resistant salmonella. DHPLC analysis proved advantageous for the detection of novel and multiple mutations. DHPLC also provides a rapid, high-throughput alternative to LightCycler and SSCP for screening frequently occurring mutations.

Elastic net orthogonal forward regression

An efficient two-level model identification method aiming at maximising a model׳s generalisation capability is proposed for a large class of linear-in-the-parameters models from the observational data. A new elastic net orthogonal forward regression (ENOFR) algorithm is employed at the lower level to carry out simultaneous model selection and elastic net parameter estimation. The two regularisation parameters in the elastic net are optimised using a particle swarm optimisation (PSO) algorithm at the upper level by minimising the leave one out (LOO) mean square error (LOOMSE). There are two elements of original contributions. Firstly an elastic net cost function is defined and applied based on orthogonal decomposition, which facilitates the automatic model structure selection process with no need of using a predetermined error tolerance to terminate the forward selection process. Secondly it is shown that the LOOMSE based on the resultant ENOFR models can be analytically computed without actually splitting the data set, and the associate computation cost is small due to the ENOFR procedure. Consequently a fully automated procedure is achieved without resort to any other validation data set for iterative model evaluation. Illustrative examples are included to demonstrate the effectiveness of the new approaches.

Modelagem linear e identificação do modelo dinâmico de um robô móvel com acionamento diferencial

This work presents a modelling and identification method for a wheeled mobile robot, including the actuator dynamics. Instead of the classic modelling approach, where the robot position coordinates (x,y) are utilized as state variables (resulting in a non linear model), the proposed discrete model is based on the travelled distance increment Delta_l. Thus, the resulting model is linear and time invariant and it can be identified through classical methods such as Recursive Least Mean Squares. This approach has a problem: Delta_l can not be directly measured. In this paper, this problem is solved using an estimate of Delta_l based on a second order polynomial approximation. Experimental data were colected and the proposed method was used to identify the model of a real robot

Experimental Active Vibration Control in Truss Structures Considering Uncertainties in System Parameters

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Richards growth model and viability indicators for populations subject to interventions

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Genetic structure of populations of Rhizoctonia solani AG-3 on potato in eastern North Carolina

A polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method was developed to identify and differentiate genotypes of Rhizoctonia solani anastomosis group 3 subgroup PT (AG-3 PT), a fungal pathogen of potato. Polymorphic co-dominant single-locus PCR-RFLP markers were identified after sequencing of clones from a genomic library and digestion with restriction enzymes. Multilocus genotypes were determined by a combination of PCR product and digestion with a specific restriction enzyme for each of seven loci. A sample of 104 isolates from one commercial field in each of five counties in eastern North Carolina was analyzed, and evidence for high levels of gene flow between populations was revealed. When data were clone-corrected and samples pooled into one single North Carolina population, random associations of alleles were found for all loci or pairs of loci, indicating random mating. However, when all genotypes were analyzed, the observed genotypic diversity deviated from panmixia and alleles within and between loci were not randomly associated. These findings support a model of population structure for R. solani AG-3 PT on potato that includes both recombination and clonality.

Eficiência polinizadora de apis mellifera l. e polinizaç ão entomófila em pimentão variedade cascadura ikeda

The aim of this research was to identify the insects visiting flowers of sweet pepper and evaluate the effects of entomophilous pollination as a whole and, more especifically, of honeybees as pollinators of this crop. This study was carried out in the municipality of Taubaté, State of São Paulo, Brazil (21°01'S; 45°29'W; altitude: 570 m) from April to September, 2002. Insects were collected in thirty-six plants during 10 minutes/hour between 6:00 and 17:00h during days of maximum blooming. Twelve plots were subjected to the following treatments: (1) open-pollinated plots, freely visited by insects; (2) caged plots; (3) caged plots containing a hive of honeybees. Twelve species of insects visited the flowers. Exomalopsis spp. (Hymenoptera, Apidae) were the commonest ones (53,9% of visits). Fruits yielded in treatments (1) and (3) were heavier, presented higher diameter, thicker pericarp and more seeds per fruit than fruits in treatment (2). Results showed that fruits from insect pollinated plots presented better quality. Honeybeesas as pollinators were efficient as the other insects. sweet pepper, Capsicum annuum L., Solanaceae, pollination, Apis mellifera, honeybee.

Structural real time control using fluid magnetorheologic damper

In the last decades there was a great development in the study of control systems to attenuate the harmful effect of natural events in great structures, as buildings and bridges. Magnetorheological fluid (MR), that is an intelligent material, has been considered in many proposals of project for these controllers. This work presents the controller design using feedback of states through LMI (Linear Matrix Inequalities) approach. The experimental test were carried out in a structure with two degrees of freedom with a connected shock absorber MR. Experimental tests were realized in order to specify the features of this semi-active controller. In this case, there exist states that are not measurable, so the feedback of the states involves the project of an estimator. The coupling of the MR damper causes a variation in dynamics properties, so an identification methods, based on experimental input/output signal was used to compare with the numerical application. The identification method of Prediction Error Methods - (PEM) was used to find the physical characteristics of the system through realization in modal space of states. This proposal allows the project of a semi-active control, where the main characteristic is the possibility of the variation of the damping coefficient.

Performance of CMS muon reconstruction in pp collision events at √s = 7TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 pb-1 of data collected in pp collisions at s = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV/c is above 95% over the whole region of pseudorapidity covered by the CMS muon system, < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeVc is higher than 90% over the full η range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100GeV/c and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV/c. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation. © 2012 IOP Publishing Ltd and Sissa Medialab srl.

Identificação de funções de transferência utilizando como entrada um degrau

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Proposta de construção de um amortecedor de vibração ajustável, TVA, utilizando fluido magnetoreológico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Projeto e avaliação experimental de uma estratégia baseada em análise intervalar aplicada ao projeto de estabilizador de sistemas de potência robusto implementado em um sistema de geração de 10KVA

Neste trabalho, são apresentados a metodologia de projeto e resultados de testes experimentais de um estabilizador de sistema de potência (ESP), implementado em um sistema de geração em escala reduzida de 10 kVA, localizado no Laboratório de Controle e Sistema de Potência (LACSPOT) da Universidade Federal do Pará (UFPA). O projeto do ESP é baseado em uma estratégia de controle robusto com ênfase em incertezas paramétricas estruturadas, as quais são tratadas com ferramentas da teoria de análise intervalar. Estas incertezas são decorrentes de mudanças do ponto de operação do sistema, que provocam variações nos parâmetros de um modelo matemático linearizado referente ao comportamento dinâmico do sistema elétrico de potência no referido ponto de operação. Para o projeto do ESP robusto intervalar, são realizados uma serie de ensaios experimentais com o propósito de estimar os parâmetros de modelos linearizados da planta, representando satisfatoriamente a dinâmica dos modos poucos amortecidos do sistema de geração interligado. O método de identificação é baseado em técnica de identificação paramétrica, baseado em mínimos quadrados. A partir de um conjunto de dados de entrada e saída, para cada ponto de operação, um modelo linear, do tipo auto-regressivo com entrada exógenos (ARX), estimado para fim de uso do projeto do ESP. Por fim, uma série de testes experimentais é realizada no sistema de geração interligado a rede elétrica local, com o propósito de verificar a efetividade da técnica de controle robusto intervalar proposta para a sintonia do ESP. A partir da análise da função custo do sinal de erro de desvio de potência elétrica na saída do gerador síncrono e a função custo do sinal de controle do ESP comprova-se experimentalmente o bom desempenho obtido pela técnica de controle proposta em comparação com uma técnica de controle clássica.

Metodologia microbiológica convencional e reação em cadeia pela polimerase (PCR) na detecção de Salmonellasp. a partir de caldos de enriquecimento – Tetrathionato e Rappaport-Vassiliadis

The progressive increase in consumption and production of poultry meat in later years comes forth with an increase of the occurrence of foodborne diseases, including salmonellosis. Salmonellosis is caused by the ingestion of contaminated products, mainly by the consumption of poultry meat which processing and preparation for consumption were not effective to eliminate pathogens. Thus, there is a need for the development of faster more sensitive methods of detection of pathogens as a way to ensure the quality of the food offered to consumers. The goal of this essay was to evaluate the effect of enrichment broths on naturally contaminated poultry meat samples. A total of 65 samples was collected, these samples were rinsed with 370 mL of buffered peptone water (BPS) 1% according with the traditional methodology. All of the samples were enriched with both Tetrathionate (TT) and Rappaport-Vassiliadis (RV) and all were analyzed by the convencional identification method and polimerasis chain reaction (PCR). Of the 65 analized samples, 34 (52%) were positive when analized by the conventional method, while 45 (69%) were positive when analized by the PCR. Amongst the 45 positive PCR samples, 44 samples were positive when enriched with TT, while just 32 samples were positive when enriched by RV. Of the 34 positive conventional samples, 29 samples were positive when enriched by TT and 31 were positive when enriched by RV