993 resultados para Field variables


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The present study investigated how demographic, personality, and climate variables act to predict departmental theft. Participants in the current field survey were 153 employees from 17 departments across two stores. The results of confirmatory factor analyses supported the construct validity of the Big Five Inventory (John, Donahue, & Kentle, 1991) and the Occupational Climate Questionnaire (Furnham & Gunter, 1997) in UK work settings. The results of regression analysis indicate that the variability in departmental theft is accountable in terms of a linear combination of demographic, personality, and climate factors. We concluded that an expanded theoretical perspective (utilizing demographic, personality, and climate variables) explained more variance than might otherwise be expected from any single perspective. Indeed, climate, personality, and demographic variables operated legitimately at the departmental level. Finally, we explained aggregated personality as a form of social interaction which is the by-product of individual differences.

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Motion study is an engineering technology that analyzes human body motions. During the past decade (1990-1999) a series of studies investigated the role of motion study in developmental disabilities. This article reviews the literature on the applications of motion study in the field. A historical and conceptual review of motion study leading to the current status of studies is presented followed by a review of the research literature. Two main eras of research focus were identified. The first era (1990-1995) of studies established the superior effectiveness and efficiency of tasks designed with motion study or motion study-related principles over traditional site-based task designs. The second era (1995-1999) of studies examined the interaction between motion study-based task designs and other variables such as choice, preference, and functionally equivalent and competing task designs and communicative alternatives. Our review found that applying motion study principles as an antecedent guide and practice to eliminating or reducing ineffective motions and simplifying effective motions resulted in positive task outcomes with most of the participants.

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Background: For research on physical activity interventions to progress systematically, the mechanisms of action must be studied. In doing so, the research methods and their associated concepts and terminology become more complex. It is particularly important to clearly distinguish among determinants, correlates, mediators, moderators, and confounder variables used in physical activity research. This article examines the factors that are correlated with and that may have a causal relationship to physical activity. Methods and Results: We propose that the term correlate be used, instead of determinant, to describe statistical associations or correlations between measured variables and physical activity. Studies of the correlates of physical activity are reviewed. The findings of these studies can help to critique existing theories of health behavior change and can provide hypotheses to be tested in intervention studies from which it is possible to draw causal inferences. Mediator, moderator, and confounder variables can act to influence measured changes in physical activity. Intervening causal variables that are necessary to complete a cause-effect pathway between an intervention and physical activity are termed mediators. The relationship between an intervention and physical activity behaviors may vary for different groups; the strata by which they vary are levels of moderators of the relationship. Other factors may distort or affect the observed relationships between program exposure and physical activity, and are known as confounders. Conclusions: Consistent use of terms and additional research on mediators and moderators of intervention effects will improve our ability to understand and influence physical activity.

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The grazing trial at Kidston Gold Mine, North Queensland, was aimed specifically to assess the uptake of metals from the tailing and the potential for unacceptable contamination of saleable meat. Further aims included estimating metal dose rates and identifying potential exposure pathways including plant uptake of heavy metals, mine tailings adhered to plants and direct ingestion of mine tailing. It was found that of the 11 metals analysed (As, Zn, Co, Cd, Cr, Sn, Pb, Sb, Hg, Se and Ni) in the animal's liver, muscle and blood during the 8-month trial period, only accumulation of arsenic and zinc occurred. A risk assessment including these two metals was conducted to determine the potential for chronic metal toxicity and long-term contamination, using the estimates of metal dose rate. It was concluded that no toxicity or long-term contamination in cattle was likely at this site. Management procedures were therefore not required at this site; however, the results highlight percent ground cover and standing dry matter (DM) as important factors in decreasing metal exposure from direct ingestion of tailings and dust adhered to plants. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

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Magnetic resonance imaging (MRI) magnets have very stringent constraints on the homogeneity of the static magnetic field that they generate over desired imaging regions. The magnet system also preferably generates very little stray field external to its structure, so that ease of siting and safety are assured. This work concentrates on deriving, means of rapidly computing the effect of 'cold' and 'warm' ferromagnetic material in or around the superconducting magnet system, so as to facilitate the automated design of hybrid material MR magnets. A complete scheme for the direct calculation of the spherical harmonics of the magnetic field generated by a circular ring of ferromagnetic material is derived under the conditions of arbitrary external magnetizing fields. The magnetic field produced by the superconducting coils in the system is computed using previously developed methods. The final, hybrid algorithm is fast enough for use in large-scale optimization methods. The resultant fields from a practical example of a 4 T, clinical MRI magnet containing both superconducting coils and magnetic material are presented.

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The effects of wing shape, wing size, and fluctuating asymmetry in these measures oil the field fitness of T. nr. brassicae and T. pretiosum were investigated. Trichogramma wasps mass-reared on eggs of the factitious host Sitotroga cerealella were released in tomato paddocks and those females ovipositing on Helicoverpo spp. eggs were recaptured. Comparisons of the recaptured group with a sample from the release population were used to assess fitness. Wing data were obtained by positioning landmarks on mounted forewings. Size was then measured as the centroid size computed from landmark distances, while Procrustes analysis followed by principal component analysis was used to assess wing shape. Similar findings were obtained for both Trichogramma species: fitness of wasps was strongly related to wing size and some shape dimensions, but not to the asymmetries of these measures. Wasps which performed well in the field had larger wings and a different wing shape compared to wasps from the mass reared population. Both size and the shape dimensions were linearly associated with fitness although there was also some evidence for non-linear selection on shape. The results suggest that wing shape and wing size are reliable predictors of field fitness for these Trichogramma wasps.

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This paper proposes a template for modelling complex datasets that integrates traditional statistical modelling approaches with more recent advances in statistics and modelling through an exploratory framework. Our approach builds on the well-known and long standing traditional idea of 'good practice in statistics' by establishing a comprehensive framework for modelling that focuses on exploration, prediction, interpretation and reliability assessment, a relatively new idea that allows individual assessment of predictions. The integrated framework we present comprises two stages. The first involves the use of exploratory methods to help visually understand the data and identify a parsimonious set of explanatory variables. The second encompasses a two step modelling process, where the use of non-parametric methods such as decision trees and generalized additive models are promoted to identify important variables and their modelling relationship with the response before a final predictive model is considered. We focus on fitting the predictive model using parametric, non-parametric and Bayesian approaches. This paper is motivated by a medical problem where interest focuses on developing a risk stratification system for morbidity of 1,710 cardiac patients given a suite of demographic, clinical and preoperative variables. Although the methods we use are applied specifically to this case study, these methods can be applied across any field, irrespective of the type of response.

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Base metal resources are becoming more fine-grained and refractory and minerals separation processes require these ores to be milled to increasingly finer sizes. To cope with very fine grinding to below a P-80 of approximately 15 mum stirred milling technology has been adopted from other industries Neither this technology, nor the basic concepts of fine grinding, are well understood by the minerals processing industry. Laboratory studies were therefore carried out in order to investigate fine milling using different types of stirred mills. The variables analysed were stirrer speed, grinding media type and size, slurry solids content as well as the feed and product size. The results of the testwork have shown that all of these variables affect the grinding efficiency. The ratio of media size to material size was found to be of particular significance. The results were also analysed using the stress intensity approach and the optimum stress intensity ranges for the most efficient grinding were determined. Application of the results for process optimisation in the industrial size units is also discussed in this paper. (C) 2003 Elsevier Science Ltd. All rights reserved.

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Improvement in analysis and reporting results of osteoarthritis (OA) clinical trials has been recently obtained because of harmonization and standardization of the selection of outcome variables (OMERACT 3 and OARSI). Moreover, OARSI has recently proposed the OARSI responder criteria. This composite index permits presentation of results of symptom modifying clinical trials in OA based on individual patient responses (responder yes/no). The 2 organizations (OMERACT and OARSI) established. a task force aimed at evaluating: (1) the variability of observed placebo and active treatment effects using the OARSI responder criteria; and (2) the possibility of proposing a simplified set of criteria. The conclusions of the task force were presented and discussed during the OMERACT 6 conference, where a simplified set of responder criteria (OMERACT-OARSI set of criteria) was proposed.

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Motivated by application of current superalgebras in the study of disordered systems such as the random XY and Dirac models, we investigate gl(2\2) current superalgebra at general level k. We construct its free field representation and corresponding Sugawara energy-momentum tensor in the non-standard basis. Three screen currents of the first kind are also presented. (C) 2003 Elsevier B.V. All rights reserved.

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The refinement calculus is a well-established theory for deriving program code from specifications. Recent research has extended the theory to handle timing requirements, as well as functional ones, and we have developed an interactive programming tool based on these extensions. Through a number of case studies completed using the tool, this paper explains how the tool helps the programmer by supporting the many forms of variables needed in the theory. These include simple state variables as in the untimed calculus, trace variables that model the evolution of properties over time, auxiliary variables that exist only to support formal reasoning, subroutine parameters, and variables shared between parallel processes.

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Trials conducted in Queensland, Australia between 1997 and 2002 demonstrated that fungicides belonging to the triazole group were the most effective in minimising the severity of infection of sorghum by Claviceps africana, the causal agent of sorghum ergot. Triadimenol ( as Bayfidan 250EC) at 0.125 kg a. i./ha was the most effective fungicide. A combination of the systemic activated resistance compound acibenzolar-S-methyl ( as Bion 50WG) at 0.05 kg a. i./ha and mancozeb ( as Penncozeb 750DF) at 1.5 kg a. i./ha has the potential to provide protection against the pathogen, should triazole-resistant isolates be detected. Timing and method of fungicide application are important. Our results suggest that the triazole fungicides have no systemic activity in sorghum panicles, necessitating the need for multiple applications from first anthesis to the end of flowering, whereas acibenzolar-S-methyl is most effective when applied 4 days before flowering. The flat fan nozzles tested in the trials provided higher levels of protection against C. africana and greater droplet deposition on panicles than the tested hollow cone nozzles. Application of triadimenol by a fixed wing aircraft was as efficacious as application through a tractor-mounted boom spray.