Age, growth, and reproduction of dolphinfish (Coryphaena hippurus) caught off the coast of North Carolina

Age, growth, and reproductive data were obtained from dolphinfish (Coryphaena hippurus, size range: 89 to 1451 mm fork length [FL]) collected between May 2002 and May 2004 off North Carolina. Annual increments from scales (n=541) and daily increments from sagittal otoliths (n=107) were examined; estimated von Bertalanffy parameters were L∞ (asymptotic length)=1299 mm FL and k (growth coefficient)=1.08/yr. Daily growth increments reduced much of the residual error in length-at-age estimates for age-0 dolphinfish; the estimated average growth rate was 3.78 mm/day during the first six months. Size at 50% maturity was slightly smaller for female (460 mm FL) than male (475 mm FL) dolphinfish. Based on monthly length-adjusted gonad weights, peak spawning occurs from April through July off North Carolina; back-calculated hatching dates from age-0 dolphinfish and prior reproductive studies on the east coast of Florida indicate that dolphinfish spawning occurs year round off the U.S. east coast and highest levels range from January through June. No major changes in length-at-age or size-at-maturity have occurred since the early 1960s, even after substantial increases in fishery landings.

Acipenser generoko bi espezieren ekoizpenaren faktore mugatzaileak kultiboan

[EUS] Gaizkaten kultiboa gero eta garrantzitsuagoa da akuikulturan. Jarduera honen ondorioz lortzen den ekoizkin primarioa, hau da, kabiarra, gero eta gehiago ari da ekoizten eta kontsumitzen. Honek, hazkunde-prozesuan dagoen jarduera ekonomikoa bihurtzen du azipentserikultura. Gaizkata eme bakoitzak ekoizten duen arrautza-kopurua, hau da, kabiar kopurua, animaliaren tamaina eta egoerarekin dago erlazionatuta zuzenean, beraz, etekin ekonomikoa ere, erlazionatuta egongo da honekin. Hau honela, guztiz garrantzizkoa izango da ekoizpena murriztuko duten faktoreen identifikazioa.

Erro de medicação: a visão do enfermeiro neonatologista

O manejo da terapia medicamentosa em unidade de terapia intensiva neonatal é complexo e agrega inúmeras drogas. Nesse sentido, manter a atenção ao preparar e administrar corretamente os medicamentos é fundamental em todo o período de assistência ao recém-nascido. Portanto, faz-se necessário que os enfermeiros tenham o entendimento acerca do conceito do erro com medicação, para que possa identificá-lo, bem como os fatores contribuintes para sua ocorrência. Diante do exposto, esta pesquisa teve como objetivos: analisar o entendimento dos enfermeiros neonatologistas sobre o conceito do erro de medicação em uma unidade de terapia intensiva neonatal; conhecer na visão destes enfermeiros quais os fatores contribuintes para a ocorrência desse erro e discutir a partir desta visão como estes fatores podem afetar a segurança do neonato. Metodologia: trata-se de uma pesquisa qualitativa, do tipo descritiva. O cenário do estudo foi uma unidade de terapia intensiva neonatal de um hospital universitário, situado no município do Rio de Janeiro. Os sujeitos foram 14 enfermeiros entre plantonistas e residentes que atuavam no manejo da terapia medicamentosa. Para a coleta dos dados utilizou-se a entrevista semiestruturada, que foram analisadas através da análise de conteúdo de Bardin, emergindo 04 categorias: Diversos conceitos sobre erros de medicação; Fatores humanos contribuintes ao erro de medicação; Fatores ambientais contribuintes ao erro de medicação e Conhecendo como os fatores contribuintes ao erro podem afetar a segurança do paciente. Para as enfermeiras o erro de medicação significa errar um dos cinco certos na administração de medicamentos (paciente, dose, via, horário e medicamento certo), e este pode acontecer em alguma parte do sistema de medicação. Neste sentido, elas entendem que uma pessoa não pode ser considerada a única responsável pela ocorrência de um erro medicamentoso. Quanto aos fatores contribuintes ao erro de medicação elencaram aqueles relacionados à prescrição medicamentosa (letra ilegível, prescrição da dose e via incorretas), ao próprio profissional de enfermagem (como sobrecarga de trabalho, número reduzido de profissionais e os múltiplos vínculos empregatícios) e ao ambiente de trabalho (ambiente inadequado e estressante; conversas paralelas com os colegas e os ruídos no setor). Na visão das enfermeiras, os fatores contribuintes ao erro podem afetar a segurança do recém-nascido, levando às situações de danos a sua saúde, podendo trazer consequências clínicas e risco de óbito. O estudo aponta a necessidade de se buscar sistemas de medicação mais confiáveis e seguros. Neste sentido, é imprescindível desenvolver e implementar programas de educação centrados nos princípios gerais da segurança do paciente. Além disso, é de suma importância que as políticas públicas de saúde, direcionem ações para o aprimoramento de medidas na segurança do RN, do sistema de medicação e da cultura de segurança.

Conservação de energia em redes de sensores sem fio.

Esta dissertação tem por objetivo propor algoritmos para conservação de energia de uma rede de sensores sem fio (RSSF) aplicada ao monitoramento de um processo suave f(x , y, t), que depende das coordenadas x e y dos nós sensores, e do tempo t, de forma a aumentar a autonomia da rede. Os algoritmos rodam na camada de aplicação de cada nó, e visam a economia de energia dos nós através do gerenciamento da necessidade de transmissões. Após a primeira amostra transmitida, apenas amostras com uma variação percentual maior do que um dado limiar são transmitidas. Além disso, cada nó pode permanecer inativo (economizando energia) entre essas transmissões. Em RSSfs de salto único, são propostos dois algoritmos: um baseado na fonte, onde cada nó é responsável por todo o processamento e tomada de decisões, e outro baseado no sorvedouro, onde todo o processamento e a tomada de decisões são realizadas pelo sorvedouro. Além disso, uma extensão de algoritmo baseado na fonte é proposta, para RSSFs de múltiplos saltos. Através dos resultados obtidos, observa-se que os algoritmos conseguiram uma redução significativa da quantidade de transmissões, o que leva a um aumento do tempo de vida e o erro na reconstrução do processo é apresentada. Desta forma, pode-se conjugar a relação entre tempo de vida máximo e erro de reconstrução mínimo.

Inteligência computacional aplicada na geração de respostas impulsivas bi-auriculares e em aurilização de salas

Neste trabalho é apresentada uma nova abordagem para obter as respostas impulsivas biauriculares (BIRs) para um sistema de aurilização utilizando um conjunto de redes neurais artificiais (RNAs). O método proposto é capaz de reconstruir as respostas impulsivas associadas à cabeça humana (HRIRs) por meio de modificação espectral e de interpolação espacial. A fim de cobrir todo o espaço auditivo de recepção, sem aumentar a complexidade da arquitetura da rede, uma estrutura com múltiplas RNAs (conjunto) foi adotada, onde cada rede opera uma região específica do espaço (gomo). Os três principais fatores que influenciam na precisão do modelo arquitetura da rede, ângulos de abertura da área de recepção e atrasos das HRIRs são investigados e uma configuração ideal é apresentada. O erro de modelagem no domínio da frequência é investigado considerando a natureza logarítmica da audição humana. Mais ainda, são propostos novos parâmetros para avaliação do erro, definidos em analogia com alguns dos bem conhecidos parâmetros de qualidade acústica de salas. Através da metodologia proposta obteve-se um ganho computacional, em redução do tempo de processamento, de aproximadamente 62% em relação ao método tradicional de processamento de sinais utilizado para aurilização. A aplicabilidade do novo método em sistemas de aurilização é reforçada mediante uma análise comparativa dos resultados, que incluem a geração das BIRs e o cálculo dos parâmetros acústicos biauriculares (IACF e IACC), os quais mostram erros de magnitudes reduzidas.

Uma Metodologia para Auxiliar no Processo de Conversão de Bases Cartográficas Utilizando o Padrão da Estrutura de Dados Geoespaciais Vetoriais.

Na década de 80, o surgimento de programas de computadores mais amigáveis para usuários e produtores de informação e a evolução tecnológica fizeram com que as instituições, públicas e privadas, se aperfeiçoassem em estudos sobre sistemas de produção cartográfica apoiados por computador, visando a implementação de Sistemas de Informação Geográfica (SIG). A pouca simultaneidade de forças entre órgãos interessados, resultou em uma grande quantidade de arquivos digitais com a necessidade de padronização. Em 2007, a Comissão Nacional de Cartografia (CONCAR) homologou a Estrutura de Dados Geoespaciais Vetoriais (EDGV) a fim de minimizar o problema da falta de padronização de bases cartográficas. A presente dissertação tem como foco elaborar uma metodologia de trabalho para o processo de conversão de bases cartográficas digitais existentes no padrão da Mapoteca Topográfica Digital (MTD), do Instituto Brasileiro de Geografia e Estatística (IBGE), para o padrão da EDGV, bem como suas potencialidades e limitações para integração e padronização de bases cartográficas digitais. Será feita uma aplicação da metodologia utilizando a carta topográfica de Saquarema, na escala de 1:50.000, vetorizada na Coordenação de Cartografia (CCAR) do IBGE e disponível na Internet. Como a EDGV foi elaborada segundo técnicas de modelagem orientada a objetos, foi necessário um mapeamento para banco de dados relacional, já que este ainda é utilizado pela maioria dos usuários e produtores de informação geográfica. Um dos objetivos específicos é elaborar um esquema de banco de dados, ou seja, um banco de dados vazio contendo todas as classes de objetos, atributos e seus respectivos domínios existentes na EDGV para que possa ser utilizado no processo de produção cartográfica do IBGE. Este esquema conterá todas as descrições dos objetos e de seus respectivos atributos, além de já permitir que o usuário selecione o domínio de um determinado atributo em uma lista pré definida, evitando que ocorra erro no preenchimento dados. Esta metodologia de trabalho será de grande importância para o processo de conversão das bases cartográficas existentes no IBGE e, com isso, gerar e disponibilizar bases cartográficas no padrão da EDGV.

An extended computational model of the circulatory system for designing ventricular assist devices.

An extended computational model of the circulatory system has been developed to predict blood flow in the presence of ventricular assist devices (VADs). A novel VAD, placed in the descending aorta, intended to offload the left ventricle (LV) and augment renal perfusion is being studied. For this application, a better understanding of the global hemodynamic response of the VAD, in essence an electrically driven pump, and the cardiovascular system is necessary. To meet this need, a model has been established as a nonlinear, lumped-parameter electrical analog, and simulated results under different states [healthy, congestive heart failure (CHF), and postinsertion of VAD] are presented. The systemic circulation is separated into five compartments and the descending aorta is composed of three components to accurately yield the system response of each section before and after the insertion of the VAD. Delays in valve closing time and blood inertia in the aorta were introduced to deliver a more realistic model. Pump governing equations and optimization are based on fundamental theories of turbomachines and can serve as a practical initial design point for rotary blood pumps. The model's results closely mimic established parameters for the circulatory system and confirm the feasibility of the intra-aortic VAD concept. This computational model can be linked with models of the pump motor to provide a valuable tool for innovative VAD design.

An approach to estimating rockfish biomass based on larval production, with application to Sebastes jordani

An assessment of the total biomass of shortbelly rockfish (Sebastes jordani) off the central California coast is presented that is based on a spatially extensive but temporally restricted ichthyoplankton survey conducted during the 1991 spawning season. Contemporaneous samples of adults were obtained by trawl sampling in the study region. Daily larval production (7.56 × 1010 larvae/d) and the larval mortality rate (Z=0.11/d) during the cruise were estimated from a larval “catch curve,” wherein the logarithm of total age-specific larval abundance was regressed against larval age. For this analysis, larval age compositions at each of the 150 sample sites were determined by examination of otolith microstructure from subsampled larvae (n=2203), which were weighted by the polygonal Sette-Ahlstrom area surrounding each station. Female population weight-specific fecundity was estimated through a life table analysis that incorporated sex-specific differences in adult growth rate, female maturity, fecundity, and natural mortality (M). The resulting statistic (102.17 larvae/g) was insensitive to errors in estimating M and to the pattern of recruitment. Together, the two analyses indicated that a total biomass equal to 1366 metric tons (t)/d of age-1+ shortbelly rockfish (sexes combined) was needed to account for the observed level of spawning output during the cruise. Given the long-term seasonal distribution of spawning activity in the study area, as elucidated from a retrospective examination of California Cooperative Oceanic Fisheries Investigation (CalCOFI) ichthyoplankton samples from 1952 to 1984, the “daily” total biomass was expanded to an annual total of 67,392 t. An attempt to account for all sources of error in the derivation of this estimate was made by application of the delta-method, which yielded a coefficient of variation of 19%. The relatively high precision of this larval production method, and the rapidity with which an absolute biomass estimate can be obtained, establishes that, for some species of rockfish (Sebastes spp.), it is an attractive alternative to traditional age-structured stock assessments.

Evaluation and application of microsatellites for population identification of Fraser River chinook salmon (Oncorhynchus tshawytscha)

Variation at 13 microsatellite loci was previously surveyed in approximately 7400 chinook salmon (Oncorhynchus tshawytscha) sampled from 50 localities in the Fraser River drainage in southern British Columbia. Evaluation of the utility of the microsatellite variation for population-specific stock identification applications indicated that the accuracy of the stock composition estimates generally improved with an increasing number of loci used in the estimation procedure, but an increase in accuracy was generally marginal after eight loci were used. With 10–14 populations in a simulated fishery sample, the mean error in population-specific estimated stock composition with a 50-popula-tion baseline was <1.4%. Identification of individuals to specific populations was highest for lower Fraser River and lower and North Thompson River populations; an average of 70% of the individual fish were correctly assigned to specific populations. The average error of the estimated percentage for the seven populations present in a coded-wire tag sample was 2% per population. Estimation of stock composition in the lower river commercial net fishery prior to June is of key local fishery management interest. Chinook salmon from the Chilcotin River and Nicola River drainages were important contributors to the early commercial fishery in the lower river because they comprised approximately 50% of the samples from the net fishery prior to mid April.

Application of a laminar flamelet model to confined explosion hazards

The majority of computational studies of confined explosion hazards apply simple and inaccurate combustion models, requiring ad hoc corrections to obtain realistic flame shapes and often predicting an order of magnitude error in the overpressures. This work describes the application of a laminar flamelet model to a series of two-dimensional test cases. The model is computationally efficient applying an algebraic expression to calculate the flame surface area, an empirical correlation for the laminar flame speed and a novel unstructured, solution adaptive numerical grid system which allows important features of the solution to be resolved close to the flame. Accurate flame shapes are predicted, the correct burning rate is predicted near the walls, and an improvement in the predicted overpressures is obtained. However, in these fully turbulent calculations the overpressures are still too high and the flame arrival times too low, indicating the need for a model for the early laminar burning phase. Due to the computational expense, it is unrealistic to model a laminar flame in the complex geometries involved and therefore a pragmatic approach is employed which constrains the flame to propagate at the laminar flame speed. Transition to turbulent burning occurs at a specified turbulent Reynolds number. With the laminar phase model included, the predicted flame arrival times increase significantly, but are still too low. However, this has no significant effect on the overpressures, which are predicted accurately for a baffled channel test case where rapid transition occurs once the flame reaches the first pair of baffles. In a channel with obstacles on the centreline, transition is more gradual and the accuracy of the predicted overpressures is reduced. However, although the accuracy is still less than desirable in some cases, it is much better than the order of magnitude error previously expected.

Construction of nonparametric Bayesian models from parametric Bayes equations

We consider the general problem of constructing nonparametric Bayesian models on infinite-dimensional random objects, such as functions, infinite graphs or infinite permutations. The problem has generated much interest in machine learning, where it is treated heuristically, but has not been studied in full generality in non-parametric Bayesian statistics, which tends to focus on models over probability distributions. Our approach applies a standard tool of stochastic process theory, the construction of stochastic processes from their finite-dimensional marginal distributions. The main contribution of the paper is a generalization of the classic Kolmogorov extension theorem to conditional probabilities. This extension allows a rigorous construction of nonparametric Bayesian models from systems of finite-dimensional, parametric Bayes equations. Using this approach, we show (i) how existence of a conjugate posterior for the nonparametric model can be guaranteed by choosing conjugate finite-dimensional models in the construction, (ii) how the mapping to the posterior parameters of the nonparametric model can be explicitly determined, and (iii) that the construction of conjugate models in essence requires the finite-dimensional models to be in the exponential family. As an application of our constructive framework, we derive a model on infinite permutations, the nonparametric Bayesian analogue of a model recently proposed for the analysis of rank data.

The retrieval of structured design knowledge

Design rationale is an effective way of capturing knowledge, since it records the issues addressed, the options considered, and the arguments used when specific decisions are made during the design process. Design rationale is generally captured by identifying elements and their dependencies, i.e. in a structured way. Current retrieval methods focus mainly on either the classification of rationale or on keyword-based searches of records. Keyword-based retrieval is reasonably effective as the information in design rationale records is mainly described using text. However, most of the current keyword-based retrieval methods discard the implicit structures of these records, resulting either in poor precision of retrieval or in isolated pieces of information that are difficult to understand. This ongoing research aims to go beyond keyword-based retrieval by developing methods and tools to facilitate the provision of useful design knowledge in new design projects. Our first step is to understand the structured information derived from the relationship between lumps of text held in different nodes in the design rationale captured via a software tool currently used in industry, and study how this information can be utilised to improve retrieval performance. Specifically, methods for utilising various structured information are developed and implemented on a prototype keyword-based retrieval system developed in our earlier work. The implementation and evaluation of these methods shows that the structured information can be utilised in a number of ways, such as filtering the results and providing more complete information. This allows the retrieval system to present results that are easy to understand, and which closely match designers' queries. Like design rationale, other methods for representing design knowledge also in essence involve structured information and thus the methods proposed can be generalised to be adapted and applied for the retrieval of other kinds of design knowledge. Copyright © 2002-2012 The Design Society. All rights reserved.

Approximate Bayesian Computation for Smoothing

We consider a method for approximate inference in hidden Markov models (HMMs). The method circumvents the need to evaluate conditional densities of observations given the hidden states. It may be considered an instance of Approximate Bayesian Computation (ABC) and it involves the introduction of auxiliary variables valued in the same space as the observations. The quality of the approximation may be controlled to arbitrary precision through a parameter ε > 0. We provide theoretical results which quantify, in terms of ε, the ABC error in approximation of expectations of additive functionals with respect to the smoothing distributions. Under regularity assumptions, this error is, where n is the number of time steps over which smoothing is performed. For numerical implementation, we adopt the forward-only sequential Monte Carlo (SMC) scheme of [14] and quantify the combined error from the ABC and SMC approximations. This forms some of the first quantitative results for ABC methods which jointly treat the ABC and simulation errors, with a finite number of data and simulated samples. © Taylor & Francis Group, LLC.

Reinforcement learning using a continuous time actor-critic framework with spiking neurons.

Animals repeat rewarded behaviors, but the physiological basis of reward-based learning has only been partially elucidated. On one hand, experimental evidence shows that the neuromodulator dopamine carries information about rewards and affects synaptic plasticity. On the other hand, the theory of reinforcement learning provides a framework for reward-based learning. Recent models of reward-modulated spike-timing-dependent plasticity have made first steps towards bridging the gap between the two approaches, but faced two problems. First, reinforcement learning is typically formulated in a discrete framework, ill-adapted to the description of natural situations. Second, biologically plausible models of reward-modulated spike-timing-dependent plasticity require precise calculation of the reward prediction error, yet it remains to be shown how this can be computed by neurons. Here we propose a solution to these problems by extending the continuous temporal difference (TD) learning of Doya (2000) to the case of spiking neurons in an actor-critic network operating in continuous time, and with continuous state and action representations. In our model, the critic learns to predict expected future rewards in real time. Its activity, together with actual rewards, conditions the delivery of a neuromodulatory TD signal to itself and to the actor, which is responsible for action choice. In simulations, we show that such an architecture can solve a Morris water-maze-like navigation task, in a number of trials consistent with reported animal performance. We also use our model to solve the acrobot and the cartpole problems, two complex motor control tasks. Our model provides a plausible way of computing reward prediction error in the brain. Moreover, the analytically derived learning rule is consistent with experimental evidence for dopamine-modulated spike-timing-dependent plasticity.

Collective motion, sensor networks, and ocean sampling

This paper addresses the design of mobile sensor networks for optimal data collection. The development is strongly motivated by the application to adaptive ocean sampling for an autonomous ocean observing and prediction system. A performance metric, used to derive optimal paths for the network of mobile sensors, defines the optimal data set as one which minimizes error in a model estimate of the sampled field. Feedback control laws are presented that stably coordinate sensors on structured tracks that have been optimized over a minimal set of parameters. Optimal, closed-loop solutions are computed in a number of low-dimensional cases to illustrate the methodology. Robustness of the performance to the influence of a steady flow field on relatively slow-moving mobile sensors is also explored © 2006 IEEE.