937 resultados para Inovation models in nets


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Reviews of the sport psychology literature have identified a number of models of athlete development in sport (Alfermann & Stambulova, 2007; Durand-Bush &Salmela, 2001). However, minimal research has investigated the origins of knowledge from which each model was developed. The purpose of this study was to systematically examine the influential texts responsible for providing the basis of athlete development models in sport. A citation path analysis of the sport psychology literature was used to generate a knowledge development path of seven athlete development models in sport. The analysis identified influential texts and authors in the conceptualization of athlete development. The popula-tion of 229 texts (articles, books, book chapters) was selected in two phases. Phase1 texts were articles citing seven articles depicting models of athlete development(n  75). Phase 2 included texts cited three or more times by Phase 1 articles (n  154). The analysis revealed how the scholarship of Benjamin Bloom (1985) has been integrated into the field of sport psychology, and how two articles appearing in 1993 and 2003 helped shape present conceptualizations of athlete development

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The triggering mechanism and the temporal evolution of large flood events, especially of worst-case scenarios, are not yet fully understood. Consequently, the cumulative losses of extreme floods are unknown. To study the link between weather conditions, discharges and flood losses it is necessary to couple atmospheric, hydrological, hydrodynamic and damage models. The objective of the M-AARE project is to test the potentials and opportunities of a model chain that relates atmospheric conditions to flood losses or risks. The M-AARE model chain is a set of coupled models consisting of four main components: the precipitation module, the hydrology module, the hydrodynamic module, and the damage module. The models are coupled in a cascading framework with harmonized time-steps. First exploratory applications show that the one way coupling of the WRF-PREVAH-BASEMENT models has been achieved and provides promising new insights for a better understanding of key aspects in flood risk analysis.

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Mode of access: Internet.

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Each vol. has also a distinctive title.

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In this paper, we investigate the effects of various potential models in the description of vapor–liquid equilibria (VLE) and adsorption of simple gases on highly graphitized thermal carbon black. It is found that some potential models proposed in the literature are not suitable for the description of VLE (saturated gas and liquid densities and the vapor pressure with temperature). Simple gases, such as neon, argon, krypton, xenon, nitrogen, and methane are studied in this paper. To describe the isotherms on graphitized thermal carbon black correctly, the surface mediation damping factor introduced in our recent publication should be used to calculate correctly the fluid–fluid interaction energy between particles close to the surface. It is found that the damping constant for the noble gases family is linearly dependent on the polarizability, suggesting that the electric field of the graphite surface has a direct induction effect on the induced dipole of these molecules. As a result of this polarization by the graphite surface, the fluid–fluid interaction energy is reduced whenever two particles are near the surface. In the case of methane, we found that the damping constant is less than that of a noble gas having the similar polarizability, while in the case of nitrogen the damping factor is much greater and this could most likely be due to the quadrupolar nature of nitrogen.

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A framework for developing marketing category management decision support systems (DSS) based upon the Bayesian Vector Autoregressive (BVAR) model is extended. Since the BVAR model is vulnerable to permanent and temporary shifts in purchasing patterns over time, a form that can correct for the shifts and still provide the other advantages of the BVAR is a Bayesian Vector Error-Correction Model (BVECM). We present the mechanics of extending the DSS to move from a BVAR model to the BVECM model for the category management problem. Several additional iterative steps are required in the DSS to allow the decision maker to arrive at the best forecast possible. The revised marketing DSS framework and model fitting procedures are described. Validation is conducted on a sample problem.

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A comparison of a constant (continuous delivery of 4% FiO(2)) and a variable (initial 5% FiO(2) with adjustments to induce low amplitude EEG (LAEEG) and hypotension) hypoxic/ischemic insult was performed to determine which insult was more effective in producing a consistent degree of survivable neuropathological damage in a newborn piglet model of perinatal asphyxia. We also examined which physiological responses contributed to this outcome. Thirty-nine 1-day-old piglets were subjected to either a constant hypoxic/ischemic insult of 30- to 37-min duration or a variable hypoxic/ischemic insult of 30-min low peak amplitude EEG (LAEEG < 5 mu V) including 10 min of low mean arterial blood pressure (MABP < 70% of baseline). Control animals (n = 6) received 21% FiO(2) for the duration of the experiment. At 72 h, the piglets were euthanased, their brains removed and fixed in 4% paraformaldehyde and assessed for hypoxic/ischemic injury by histological analysis. Based on neuropathology scores, piglets were grouped as undamaged or damaged; piglets that did not survive to 72 h were grouped separately as dead. The variable insult resulted in a greater number of piglets with neuropathological damage (undamaged = 12.5%, damaged = 68.75%, dead = 18.75%) while the constant insult resulted in a large proportion of undamaged piglets (undamaged = 50%, damaged = 22.2%, dead = 27.8%). A hypoxic insult varied to maintain peak amplitude EEG < 5 mu V results in a greater number of survivors with a consistent degree of neuropathological damage than a constant hypoxic insult. Physiological variables MABP, LAEEG, pH and arterial base excess were found to be significantly associated with neuropathological outcome. (c) 2006 Elsevier B.V. All rights reserved.

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Pharmacodynamics (PD) is the study of the biochemical and physiological effects of drugs. The construction of optimal designs for dose-ranging trials with multiple periods is considered in this paper, where the outcome of the trial (the effect of the drug) is considered to be a binary response: the success or failure of a drug to bring about a particular change in the subject after a given amount of time. The carryover effect of each dose from one period to the next is assumed to be proportional to the direct effect. It is shown for a logistic regression model that the efficiency of optimal parallel (single-period) or crossover (two-period) design is substantially greater than a balanced design. The optimal designs are also shown to be robust to misspecification of the value of the parameters. Finally, the parallel and crossover designs are combined to provide the experimenter with greater flexibility.