2,603 research outputs found

    A correction to the enhanced bottom drag parameterisation of tidal turbines

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    Hydrodynamic modelling is an important tool for the development of tidal stream energy projects. Many hydrodynamic models incorporate the effect of tidal turbines through an enhanced bottom drag. In this paper we show that although for coarse grid resolutions (kilometre scale) the resulting force exerted on the flow agrees well with the theoretical value, the force starts decreasing with decreasing grid sizes when these become smaller than the length scale of the wake recovery. This is because the assumption that the upstream velocity can be approximated by the local model velocity, is no longer valid. Using linear momentum actuator disc theory however, we derive a relationship between these two velocities and formulate a correction to the enhanced bottom drag formulation that consistently applies a force that remains closed to the theoretical value, for all grid sizes down to the turbine scale. In addition, a better understanding of the relation between the model, upstream, and actual turbine velocity, as predicted by actuator disc theory, leads to an improved estimate of the usefully extractable energy. We show how the corrections can be applied (demonstrated here for the models MIKE 21 and Fluidity) by a simple modification of the drag coefficient

    USE OF THE POSTERIOR PREDICTIVE DISTRIBUTION AS A DIAGNOSTIC TOOL FOR MIXED MODELS

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    The posterior predictive distribution (the distribution of data simulated from a model) has been used to flag model-data discrepancies in the Bayesian literature, and several approaches have been developed. The approach taken here differs from the others both conceptually and as realized. It works by comparing the distance between the data and model (as represented by pseudo-data simulated from a model) with distance within the model. The distance within the model is calculated by generating pseudo-data from it, using each set of these pseudo-data to reestimate the model, and then generating pseudo-data from them, matching the way the original data are used to generate pseudo-data. Distances are calculated as the log of sums-of-squares, following ranking, and the test from comparing a mean distance to a distribution of mean distances. The power of this method compares favorably with those of standard methods, e.g. t-tests, but it is more general since it can be used for most models in the GLMM framework, whether estimated using traditional or Bayesian methods. A new kind of plot, where the distribution of the ranked pseudo-data is compared to the original data at each ranked datum, is useful for determining the region of the data where the model fails

    The behavior and natural history of the Florida a red-bellied turtle, pseudemys nelsoni : an ethological study

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    Field work was conducted in 1983-1986 to gather data on social behavior of the Florida red-bellied turtle, Pseudemys nelsoni, by direct, underwater observation (Rock Springs run, Apopka, Florida) and home range analysis using mark-recapture and telemetry techniques (Rock Springs run and Payne\u27s Prairie, Gainesville, Florida). Laboratory observations and experiments were conducted at the University of Tennessee in 1982-1986. A behavior catalog of P. nelsoni was constructed. While not comprehensive, it indicates that the social behavior of this species is complex and adapted for conditions of poor visibility. Conspecific identification probably occurs prior to courtship and other social interactions. Aggressive behavior, mostly by melanistic males, was directed toward conspecifics of both sexes. Aggressive behavior directed towards other males consisted largely of threats while females were bit and tugged on. Basking phases were not clearly discernable in P. nelsoni although some postures and behaviors were associated with the length of time an animal had spent basking. An investigation of how juvenile turtles assembled behavior revealed that alternating pairs of behaviors were the most common pattern. Variability in the patterning of behavior among observation periods and individual variation likely obscures much of the organization of their behavior. The most valuable techniques for investigating behavior patterns in this study were 1) identifying units of behavior, 2) first order transition matrices, 3) information theory, and 4) auto- and cross-associations. Precocial courtship was a frequent social event of juveniles in the laboratory. While this behavior\u27s function is not obvious, many of its attributes coincide with those given for play behavior suggesting that the function of juvenile courtship is similar to one or more of the possible functions of play. The results of two laboratory experiments, one using positive reinforcement and the second punishment, suggest that these animals can vii distinguish between a pair of turtles matched for size and pattern. To describe home range size and usage, the data were recast as a constrained nonlinear optimization problem and solved using a FORTRAN program. Home ranges were small at both the Apopka and Gainesville populations despite substantial habitat differences and the different techniques used to locate turtles. The entire home range could be traversed by an individual in one or two hours

    R\u3csup\u3e2\u3c/sup\u3e STATISTICS FOR MIXED MODELS

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    The R2 statistic, when used in a regression or ANOVA context, is appealing because it summarizes how well the model explains the data in an easy-to-understand way. R2 statistics are also useful to gauge the effect of changing a model. Generalizing R2 to mixed models is not obvious when there are correlated errors, as might occur if data are georeferenced or result from a designed experiment with blocking. Such an R2 statistic might refer only to the explanation associated with the independent variables, or might capture the explanatory power of the whole model. In the latter case, one might develop an R2 statistic from Wald or likelihood ratio statistics, but these can yield different numeric results. Example formulas for these generalizations of R2 are given. Two simulated data sets, one based on a randomized complete block design and the other with spatially correlated observations, demonstrate increases in R2 as model complexity increases, the result of modeling the covariance structure of the residuals

    AUTOMATIC MODEL SELECTION IN THE MIXED MODELS FRAMEWORK

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    Stepwise model selection is a commonly used technique in regression when there are many candidate independent variables and limited time to develop a model. This approach was adapted to the mixed models framework and gives good results, established by simulation with a known model and by application to real world data. Model selection is done using an information criterion (selected by the user). The application is primarily written in Perl. The Perl code tracks which variables are in or out of the model, calculates the information criterion, and writes and submits SAS code. Proc Mixed in SAS is used to compute the log-likelihood for a model, which is used to calculate the information criterion, which then is used to judge whether the model has improved by adding or dropping a variable, or by changing the covariance structure of the residuals. The software is currently restricted to the case where the random part of the model is assumed to be known, but how to augment the software to also select the structure for the random part of the model is discussed

    Alternative Precautionary Measures Yielding Lower C. diff Infection Rates in Healthcare Facilities

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    Background: An international healthcare concern is the persistent spread of Clostridium difficile, a Gram-positive spore forming bacterium that is responsible for the most common hospital-acquired infection, amongst patients. Objective: A systematic review was performed to summarize evidence that the interventions utilized in healthcare facilities which indicate a patient’s precautionary status are insufficient, outdated, and commonly lead to infection in neighboring patient rooms. Databases such as PubMed, NCBI, Google Scholar, and APHA’s Medical Care were searched, covering the period from 2017-2022. Studies were included if their focus concentrated on C. diff and the precautionary measures taken by employees at healthcare organizations pertaining to patients with diagnosed C. diff, infection and recurrence rates at given healthcare facilities, the utilization of PPE and appropriate sanitization protocols, and potential consequences involving patient outcomes and the contraction of C. diff infections. It was found that the status quo precautionary measures were not sufficient in decreasing C. diff infection rates within healthcare facilities, and an alternative is needed. An automatic hand hygiene compliance monitoring (HHCM) system, stimulated by motion-detection upon the entry and exit of patient rooms, that gives audio messages aloud indicating the patient’s precautionary status, the type of PPE required, and the form of sanitization required, was proposed. Methods: This new precaution protocol was implemented at a sample of healthcare facilities and was not utilized with a sample of other healthcare facilities. Data pertaining to C. diff infections and recurrences between patients and staff, as well as patient outcomes/wellness were evaluated between the experimental and control group. Results: It was found that healthcare facilities utilizing the automatic HHCM system showed a dramatic decrease in the spread of C. diff between patients and staff, and staff reported more frequent hand hygiene after providing patient care

    Alcohol Pathology and the Triarchic Model of Psychopathy: The Role of Protective Behavioral Strategies and Impulsivity

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    OVERVIEW: Psychopathy has been an area of growing interest in psychology for the last half century. Currently, the most common conceptualization of psychopathy breaks it down into two factors: primary and secondary psychopathy. More recently, psychopathy has been viewed through a more nuanced model, the Triarchic Model of Psychopathy. The present study examines the relationship between the three facets of the Triarchic Model and alcohol pathology via aspects of impulsivity and Protective Behavioral Strategies (PBS). METHOD: A college student sample of n = 967 individuals who endorsed consuming alcohol completed surveys regarding the Triarchic Model, impulsivity, PBS use, and alcohol pathology. RESULTS: Our findings indicate that boldness and disinhibition are significant predictors of alcohol pathology. Boldness was partially mediated by conscientiousness, while disinhibition was partially mediated by both conscientiousness and PBS use. Meanness was not associated with higher levels of alcohol pathology. CONCLUSIONS: It seems that aspects of psychopathy related to disinhibition and boldness are predictive of alcohol pathology, while meanness, though similar to primary psychopathy, does not relate to alcohol pathology as hypothesized. This thesis not only adds to the literature between psychopathy and alcohol pathology but allows for a more exact insight regarding aspects of psychopathy and their relation to alcohol pathology
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