924 resultados para Control Network


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The dental profession has possessed traditional standards of cross-infection control but the recent expression of real concerns by both the public and the profession over the transmissibility of infectious diseases in the dental surgery has demanded a formalized and extended approach to teaching cross-infection control in the dental curriculum. Clear curriculum content must be formulated within contemporary Workplace Health and Safety Guidelines and the Strategic Plan of the Dental School or academic health centre. The full integration demands that the area is taught as a discrete entity but recognized as an intrinsic part of each clinical encounter. This paper discusses the structure and integration of cross-infection control into the curriculum at the University of Queensland Dental School.

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This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.

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The conventional analysis for the estimation of the tortuosity factor for transport in porous media is modified here to account for the effect of pore aspect ratio. Structural models of the porous medium are also constructed for calculating the aspect ratio as a function of porosity. Comparison of the model predictions with the extensive data of Currie (1960) for the effective diffusivity of hydrogen in packed beds shows good agreement with a network model of randomly oriented intersecting pores for porosities upto about 50 percent, which is the region of practical interest. The predictions based on this network model are also found to be in better agreement with the data of Currie than earlier expressions developed for unconsolidated and grainy media.

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The aim of the study was to test a revised conceptualization of the role of coping in adjustment to a low-control stressor-women's adjustment to a failed in vitro fertilization (NF) attempt. Data were collected prior to the IVF treatment (Time I) and twice after the failed NF attempt (1 to 2 weeks after finding out the results, n = 171, and fi weeks later, n = 139). Initial adjustment was assessed at Time I, whereas measures of coping and both self-report and partner ratings of adjustment were obtained at Times ? and 3. As predicted, escapist strategies and problem-management strategies (mainly at Time ?) were associated with poor adjustment, whereas problem-appraisal coping was associated with better adjustment., There was also support for the proposed positive relationship between adjustment and emotional approach coping (on self-report adjustment).

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Peptidergic mechanisms influencing the resistance of the gastrointestinal vascular bed of the estuarine crocodile, Crocodylus porosus, were investigated. The gut was perfused in situ via the mesenteric and the celiac arteries, and the effects of different neuropeptides were tested using bolus injections. Effects on vascular resistance were recorded as changes in inflow pressures. Peptides found in sensory neurons [substance P, neurokinin A, and calcitonin gene-related peptide (CGRP)] all caused significant relaxation of the celiac vascular bed, as did vasoactive intestinal polypeptide (VIP), another well-known vasodilator. Except for VIP, the peptides also induced transitory gut contractions. Somatostatin and neuropeptide Y (NPY), which coexist in adrenergic neurons of the C. porosus, induced vasoconstriction in the celiac vascular bed without affecting the gut motility. Galanin caused vasoconstriction and occasionally activated the gut wall. To elucidate direct effects on individual vessels, the different peptides were tested on isolated ring preparations of the mesenteric and celiac arteries. Only CGRP and VIP relaxed the epinephrine-precontracted celiac artery, whereas the effects on the mesenteric artery were variable. Somatostatin and NPY did not affect the resting tonus of these vessels, but somatostatin potentiated the epinephrine-induced contraction of the celiac artery. Immunohistochemistry revealed the existence and localization of the above-mentioned peptides in nerve fibers innervating vessels of different sizes in the gut region. These data support the hypothesis of an important role for neuropeptides in the control of the vascular bed of the gastrointestinal tract in C. porosus.

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Control of chaos in the single-mode optically pumped far-infrared (NH3)-N-15 laser is experimentally demonstrated using continuous time-delay control. Both the Lorenz spiral chaos and the detuned period-doubling chaos exhibited by the laser have been controlled. While the laser is in the Lorenz spiral chaos regime the chaos has been controlled both such that the laser output is cw, with corrections of only a fraction of a percent necessary to keep it there, and to period one. The laser has also been controlled while in the period-doubling chaos regime, to both the period-one and -two states.

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Motivation: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. Results: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification. This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binder-a were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotheraaeutic peptides.

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The present study was designed to examine the main and interactive effects of task demands, work control, and task information on levels of adjustment. Task demands, work control, and task information were manipulated in an experimental setting where participants completed a letter-sorting activity (N = 128). Indicators of adjustment included measures of positive mood, participants' perceptions of task performance, and task satisfaction. Results of the present study provided some support for the main effects of objective task demands, work control, and task information on levels of adjustment. At the subjective level of analysis, there was some evidence to suggest that work control and task information interacted in their effects on levels of adjustment. There was minimal support for the proposal that work control and task information would buffer the negative effects of task demands on adjustment. There was, however, some evidence to suggest that the stress-buffering role of subjective work control was more marked at high, rather than low, levels of subjective task information.

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Cerebral responses to alternating periods of a control task and a selective letter generation paradigm were investigated with functional Magnetic Resonance Imaging (fMRI). Subjects selectively generated letters from four designated sets of six letters from the English language alphabet, with the instruction that they were not to produce letters in alphabetical order either forward or backward, repeat or alternate letters. Performance during this condition was compared with that of a control condition in which subjects recited the same letters in alphabetical order. Analyses revealed significant and extensive foci of activation in a number of cerebral regions including mid-dorsolateral frontal cortex, inferior frontal gyrus, precuneus, supramarginal gyrus, and cerebellum during the selective letter generation condition. These findings are discussed with respect to recent positron emission tomography (PET) and fMRI studies of verbal working memory and encoding/retrieval in episodic memory.

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Efficiency of presentation of a peptide epitope by a MHC class I molecule depends on two parameters: its binding to the MHC molecule and its generation by intracellular Ag processing. In contrast to the former parameter, the mechanisms underlying peptide selection in Ag processing are poorly understood. Peptide translocation by the TAP transporter is required for presentation of most epitopes and may modulate peptide supply to MHC class I molecules. To study the role of human TAP for peptide presentation by individual HLA class I molecules, we generated artificial neural networks capable of predicting the affinity of TAP for random sequence 9-mer peptides. Using neural network-based predictions of TAP affinity, we found that peptides eluted from three different HLA class I molecules had higher TAP affinities than control peptides with equal binding affinities for the same HLA class I molecules, suggesting that human TAP may contribute to epitope selection. In simulated TAP binding experiments with 408 HLA class I binding peptides, HLA class I molecules differed significantly with respect to TAP affinities of their ligands, As a result, some class I molecules, especially HLA-B27, may be particularly efficient in presentation of cytosolic peptides with low concentrations, while most class I molecules may predominantly present abundant cytosolic peptides.

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Objective To determine the efficacy of zeta-cypermethrin in controlling buffalo fly (Haematobia irritans exigua). Design Five field trials in northern and central Queensland. Procedure Zeta-cypermethrin pour-on at 2.5 mg/kg, spray at 62.5 ppm, deltamethrin pour-on and pour-on vehicle were applied to groups of 20 cattle. Buffalo fly counts were conducted three times before treatment and 3, 7, 14, 21, 28 and 35 days after treatment. Results In central Queensland where synthetic pyrethroid resistance in buffalo fly populations was rare, 2.5 mg/kg of zeta-cypermethrin pour-on gave good control of buffalo fly for 4 weeks and was better than a deltamethrin product. A zeta-cypermethrin spray used at 62.5 ppm gave 14 days control. In far-north Queensland where resistance to synthetic pyrethroids and heavy rain was common, the maximum period of efficacy of zeta-cypermethrin pour-on was reduced to 2 weeks. Conclusion In areas where there is low resistance to synthetic pyrethroids among buffalo flies, zeta-cypermethrin pour-on can be expected to give good control for 4 weeks.

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The present study examined the effects of work control and job demands on employee adjustment and work performance using a multidimensional measure of work control (assessing levels of task control, decision control and work scheduling control). It was proposed that the negative effects of job demands and employee adjustment would be moderated by high levels of task control. It was also proposed that there would be evidence of main effects of both job demands and work control (particularly task-related levels of control) on employee adjustment. To test these predictions, a study of 135 university employees holding administrative positions was undertaken. Methodological improvements over previous research included the use of both self-reported adjustment measures and supervisor ratings of work performance as outcome variables, and the assessment of the predictor and outcome measures at different points in time (self-reported adjustment was assessed at both Times 1 and 2). The results revealed some support for the proposal that the effects of job demands would be buffered by high levels of task control, but not more peripheral aspects of work control. There were also significant main effects of task control on job satisfaction.

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Power system small signal stability analysis aims to explore different small signal stability conditions and controls, namely: (1) exploring the power system security domains and boundaries in the space of power system parameters of interest, including load flow feasibility, saddle node and Hopf bifurcation ones; (2) finding the maximum and minimum damping conditions; and (3) determining control actions to provide and increase small signal stability. These problems are presented in this paper as different modifications of a general optimization to a minimum/maximum, depending on the initial guesses of variables and numerical methods used. In the considered problems, all the extreme points are of interest. Additionally, there are difficulties with finding the derivatives of the objective functions with respect to parameters. Numerical computations of derivatives in traditional optimization procedures are time consuming. In this paper, we propose a new black-box genetic optimization technique for comprehensive small signal stability analysis, which can effectively cope with highly nonlinear objective functions with multiple minima and maxima, and derivatives that can not be expressed analytically. The optimization result can then be used to provide such important information such as system optimal control decision making, assessment of the maximum network's transmission capacity, etc. (C) 1998 Elsevier Science S.A. All rights reserved.