Behavior of fish predators and their prey: habitat choice between open water and dense vegetation

Behavior of largemouth bass, Micropterus salmoides, and northern pike, Esox lucius, foraging on fathead minnows, Pimephales promelas, or bluegills, Lepomis macrochirus, was quantified in pools with 50% cover (half the pool had artificial stems at a density of 1000 stems n^-2). Both predators spent most of their time in the vegetation. Largemouth bass searched for bluegills and ambushed minnows, whereas the relatively immobile northern pike ambushed all prey. Minnows were closer to predators and were captured more frequently than bluegills. Even when minnows dispersed, they moved continually and eventually wandered within striking distance of a predator. Bluegills dispersed in the cover with predators. Bass captured the few bluegills that strayed into the open and pike captured those that approached too closely in the cover. The ability of predators to capture prey while residing in habitats containing patches of dense cover may explain their residence in areas often considered to be poor ones for foraging.Funding for this project was provided by Dingell-Johnson project F-57-R administered through the Ohio Division of Wildlife

Predator-Prey Interaction between Largemouth Bass and Bluegills as Influenced by Simulated, Submersed Vegetation

Data from the literature suggest that predatory success declines as habitat complexity increases. To explain this phenomenon, we studied the predator-prey interaction between largemouth bass Micropterus salmoides and bluegills Lepomis macrochirus in four laboratory pools (2.4-3.0 m diameter, 0.7 m deep), each with a different density (0, 50, 250, 1,000 stems/m2) of artificial plant stems. Behavior was quantified for both predator and prey during largemouth bass feeding bouts lasting 60 minutes. Predation success(number of captures) by largemouth bass was similar at 0 and 50 stems/m2, then declined to near zero at 250 and 1,000 stems/m2. As stem density increased, predator activity declined due to a decrease in behaviors associated with visual contact with prey. Reduced predation success by largemouth bass in habitats of increased complexity apparently is related to increases in visual barriers provided by plant stems as well as to adaptive changes in bluegill behavior.This research was supported in part by funds from the Federal Aid in Fish Restoration Act under Dingell-Johnson Project F-57-R, the National Science Foundation (DEB77- 16167), and the Department of Zoology

Molekularbiologische Charakterisierung des felinen Foamyvirus (FFV)

Die Arbeit erläutert Gemeinsamkeiten und Unterschiede des felinen Foamyvirus FFV zu anderen Foamyviren und vergleicht die Replikationsstrategie mit der der Orthoretroviren und Hepadnaviren

Molekularbiologische Charakterisierung des felinen Foamyvirus (FFV)

Die Arbeit erläutert Gemeinsamkeiten und Unterschiede des felinen Foamyvirus FFV zu anderen Foamyviren und vergleicht die Replikationsstrategie mit der der Orthoretroviren und Hepadnaviren

A critical discussion of the use of film in participatory research projects with homeless young people: an analysis based on case examples from England and Canada

The focus of this paper is on the complex and sometimes contradictory effects of generating films with and about young people who have experienced homelessness, through participatory research. Drawing on two projects – one in Ottawa, Canada, and the other in Manchester, UK – we scrutinise two key aspects of participatory research projects that use film: first, how to appropriately communicate the complexity of already-stigmatised lives to different publics, and second, which publics we prioritise, and how this shapes the stories that are told. Through a theoretical framework that combines Pierre Bourdieu’s account of authorised language with Arthur Frank’s socio-narratology, we analyse the potential for generating justice versus reproducing symbolic violence through participatory research and film with homeless young people. In particular, we scrutinise the distinct role played by what we are calling first, second and third publics – each with their own level of distance and relationship to the participatory research process

A statistical model for genotype determination at a major locus in a progeny test design

Considering a normally distributed quantitative trait whose genetic variation is controlled by both an autosomal major locus and a polygenic component, and whose expression is influenced by environmental factors, a mixed model was developed to classify sires and daughters for their genotypes at the major locus in a progeny test design. Repeatability and genetic parameters reflecting the polygenic variation were assumed to be known. Posterior distribution of the sire genotypes and that of the daughters given the sire genotypes were derived. A method was proposed to estimate these posterior probabilities as well as the unknown parameters, and a method using the likelihood ratios to test specific genetic hypotheses was suggested. An iterative two-step procedure similar to the EM (expectation-maximization) algorithm was used to estimate the posterior probabilities and the unknown parameters. The operational value of this approach was tested with simulated data.S’appliquant à un caractère quantitatif à distribution normale, dont la variabilité génétique est contrôlée à la fois par un locus majeur autosomal et par une composante polygénique et dont l’expression est influencée par des facteurs de milieu, un modèle mixte est développé afin de déterminer le génotype (au locus majeur) des pères et de leurs filles dans un test sur descendance. La répétabilité et les paramètres génétiques relatifs à la composante polygénique sont supposés connus. La loi a posteriori des génotypes des pères et celles des génotypes de leurs filles, conditionnellement aux génotypes des pères, sont établies. Une méthode est proposée pour estimer ces probabilités a posteriori, ainsi que les paramètres inconnus, et une méthode utilisant les rapports de vraisemblance est suggérée afin de tester des hypothèses génétiques spécifiques. Une procédure itérative en deux étapes, similaire à l’algorithme EM (expectation-maximization), est présentée afin d’estimer les probabilités a posteriori et les paramètres inconnus. L’intérêt opérationnel de cette approche est éprouvé sur des données simulées

Improving Information Systems Sustainability by Applying Machine Learning to Detect and Reduce Data Waste

Big data are key building blocks for creating information value. However, information systems are increasingly plagued with useless, waste data that can impede their effective use and threaten sustainability objectives. Using a constructive design science approach, this work first, defines digital data waste. Then, it develops an ensemble artifact comprising two components. The first component comprises 13 machine learning models for detecting data waste. Applying these to 35,576 online reviews in two domains reveals data waste of 1.9% for restaurant reviews compared to 35.8% for app reviews. Machine learning can accurately identify 83% to 99.8% of data waste; deep learning models are particularly promising, with accuracy ranging from 96.4% to 99.8%. The second component comprises a sustainability cost calculator to quantify the social, economic, and environmental benefits of reducing data waste. Eliminating 5948 useless reviews in the sample would result in saving 6.9 person hours, $2.93 in server, middleware and client costs, and 9.52 kg of carbon emissions. Extrapolating these results to reviews on the internet shows substantially greater savings. This work contributes to design knowledge relating to sustainable information systems by highlighting the new class of problem of data waste and by designing approaches for addressing this problem