42 resultados para 010109 Ordinary Differential Equations, Difference Equations and Dynamical Systems
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Background: Few clinical studies have focused on the alcoholindependent cardiovascular effects of the phenolic compounds of red wine (RW). Objective: We aimed to evaluate the effects of ethanol and phenolic compounds of RW on the expression of inflammatory biomarkers related to atherosclerosis in subjects at high risk of cardiovascular disease. Design: Sixty-seven high-risk, male volunteers were included in a randomized, crossover consumption trial. After a washout period, all subjects received RW (30 g alcohol/d), the equivalent amount of dealcoholized red wine (DRW), or gin (30 g alcohol/d) for 4 wk. Before and after each intervention period, 7 cellular and 18 serum inflammatory biomarkers were evaluated. Results: Alcohol increased IL-10 and decreased macrophage-derived chemokine concentrations, whereas the phenolic compounds of RW decreased serum concentrations of intercellular adhesion molecule- 1, E-selectin, and IL-6 and inhibited the expression of lymphocyte function-associated antigen 1 in T lymphocytes and macrophage-1 receptor, Sialil-Lewis X, and C-C chemokine receptor type 2 expression in monocytes. Both ethanol and phenolic compounds of RW downregulated serum concentrations of CD40 antigen, CD40 ligand, IL-16, monocyte chemotactic protein-1, and vascular cell adhesion molecule-1. Conclusion: The results suggest that the phenolic content of RW may modulate leukocyte adhesion molecules, whereas both ethanol and polyphenols of RW may modulate soluble inflammatory mediators in high-risk patients. The trial was registered in the International Standard Randomized Controlled Trial Number Register at http://www. isrctn.org/ as ISRCTN88720134
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We report experimental and numerical results showing how certain N-dimensional dynamical systems are able to exhibit complex time evolutions based on the nonlinear combination of N-1 oscillation modes. The experiments have been done with a family of thermo-optical systems of effective dynamical dimension varying from 1 to 6. The corresponding mathematical model is an N-dimensional vector field based on a scalar-valued nonlinear function of a single variable that is a linear combination of all the dynamic variables. We show how the complex evolutions appear associated with the occurrence of successive Hopf bifurcations in a saddle-node pair of fixed points up to exhaust their instability capabilities in N dimensions. For this reason the observed phenomenon is denoted as the full instability behavior of the dynamical system. The process through which the attractor responsible for the observed time evolution is formed may be rather complex and difficult to characterize. Nevertheless, the well-organized structure of the time signals suggests some generic mechanism of nonlinear mode mixing that we associate with the cluster of invariant sets emerging from the pair of fixed points and with the influence of the neighboring saddle sets on the flow nearby the attractor. The generation of invariant tori is likely during the full instability development and the global process may be considered as a generalized Landau scenario for the emergence of irregular and complex behavior through the nonlinear superposition of oscillatory motions
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We show how certain N-dimensional dynamical systems are able to exploit the full instability capabilities of their fixed points to do Hopf bifurcations and how such a behavior produces complex time evolutions based on the nonlinear combination of the oscillation modes that emerged from these bifurcations. For really different oscillation frequencies, the evolutions describe robust wave form structures, usually periodic, in which selfsimilarity with respect to both the time scale and system dimension is clearly appreciated. For closer frequencies, the evolution signals usually appear irregular but are still based on the repetition of complex wave form structures. The study is developed by considering vector fields with a scalar-valued nonlinear function of a single variable that is a linear combination of the N dynamical variables. In this case, the linear stability analysis can be used to design N-dimensional systems in which the fixed points of a saddle-node pair experience up to N21 Hopf bifurcations with preselected oscillation frequencies. The secondary processes occurring in the phase region where the variety of limit cycles appear may be rather complex and difficult to characterize, but they produce the nonlinear mixing of oscillation modes with relatively generic features
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Prevention has been a main issue of recent policy orientations in health care. This renews the interest on how different organizational designs and the definition of payment schemes to providers may affect the incentives to provide preventive health care. We present, both the normative and the positive analyses of the change from independent providers to integrated services. We show the evaluation of that change to depend on the particular way payment to providers is done. We focus on the externality resulting from referral decisions from primary to acute care providers. This makes our analysis complementary to most works in the literature allowing to address in a more direct way the issue of preventive health care.
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"Vegeu el resum a l'inici del document del fitxer adjunt."
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A variational method for Hamiltonian systems is analyzed. Two different variationalcharacterization for the frequency of nonlinear oscillations is also suppliedfor non-Hamiltonian systems
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Organizations often face the challenge of communicating their strategiesto local decision makers. The difficulty presents itself in finding away to measure performance wich meaningfully conveys how to implement theorganization's strategy at local levels. I show that organizations solvethis communication problem by combining performance measures in such away that performance gains come closest to mimicking value-added asdefined by the organization's strategy. I further show how organizationsrebalance performance measures in response to changes in their strategies.Applications to the design of performance metrics, gaming, and divisionalperformance evaluation are considered. The paper also suggests severalempirical ways to evaluate the practical importance of the communicationrole of measurement systems.
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This paper proposes a very fast method for blindly approximating a nonlinear mapping which transforms a sum of random variables. The estimation is surprisingly good even when the basic assumption is not satisfied.We use the method for providing a good initialization for inverting post-nonlinear mixtures and Wiener systems. Experiments show that the algorithm speed is strongly improved and the asymptotic performance is preserved with a very low extra computational cost.
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This paper proposes a very fast method for blindly initial- izing a nonlinear mapping which transforms a sum of random variables. The method provides a surprisingly good approximation even when the basic assumption is not fully satis¯ed. The method can been used success- fully for initializing nonlinearity in post-nonlinear mixtures or in Wiener system inversion, for improving algorithm speed and convergence.
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This work focuses on the prediction of the two main nitrogenous variables that describe the water quality at the effluent of a Wastewater Treatment Plant. We have developed two kind of Neural Networks architectures based on considering only one output or, in the other hand, the usual five effluent variables that define the water quality: suspended solids, biochemical organic matter, chemical organic matter, total nitrogen and total Kjedhal nitrogen. Two learning techniques based on a classical adaptative gradient and a Kalman filter have been implemented. In order to try to improve generalization and performance we have selected variables by means genetic algorithms and fuzzy systems. The training, testing and validation sets show that the final networks are able to learn enough well the simulated available data specially for the total nitrogen
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Rationale Methylone, a new drug of abuse sold as"bath salts' has similar effects to ecstasy or cocaine. Objective We have investigated changes in dopaminergic and serotoninergic markers, indicative of neuronal damage, induced by methylone in the frontal cortex, hippocampus and striatum of mice and according two different treatment schedules. Methods Methylone was given subcutaneously to male Swiss CD1 mice and at an ambient temperature of 26ºC. Treatment A: three doses of 25 mg/Kg at 3.5 h interval between doses for two consecutive days. Treatment B: four doses of 25 mg/Kg at 3 h interval in one day. Results Repeated methylone administration induced hyperthermia and a significant loss in body weight. Following treatment A, methylone induced transient dopaminergic (frontal cortex) and serotoninergic (hippocampus) impairment. Following treatment B, transient dopaminergic (frontal cortex) and serotonergic (frontal cortex and hippocampus) changes 7 days after treatment were found. We found evidence of astrogliosis in the CA1 and the dentate gyrus of the hippocampus following treatment B. The animals also showed an increase in immobility time in the forced swim test, pointing to a depressive-like behavior. In cultured cortical neurons, methylone (for 24 and 48 h) did not induce a remarkable cytotoxic effect. Conclusions The neural effects of methylone differ depending upon the treatment schedule. Neurochemical changes elicited by methylone are apparent when administered at an elevated ambient temperature, four times per day at 3 h intervals, which is in accordance with its short half-life.
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We present a participant study that compares biological data exploration tasks using volume renderings of laser confocal microscopy data across three environments that vary in level of immersion: a desktop, fishtank, and cave system. For the tasks, data, and visualization approach used in our study, we found that subjects qualitatively preferred and quantitatively performed better in the cave compared with the fishtank and desktop. Subjects performed real-world biological data analysis tasks that emphasized understanding spatial relationships including characterizing the general features in a volume, identifying colocated features, and reporting geometric relationships such as whether clusters of cells were coplanar. After analyzing data in each environment, subjects were asked to choose which environment they wanted to analyze additional data sets in - subjects uniformly selected the cave environment.