222 resultados para Original model


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Although praised for their rationality, humans often make poor decisions, even in simple situations. In the repeated binary choice experiment, an individual has to choose repeatedly between the same two alternatives, where a reward is assigned to one of them with fixed probability. The optimal strategy is to perseverate with choosing the alternative with the best expected return. Whereas many species perseverate, humans tend to match the frequencies of their choices to the frequencies of the alternatives, a sub-optimal strategy known as probability matching. Our goal was to find the primary cognitive constraints under which a set of simple evolutionary rules can lead to such contrasting behaviors. We simulated the evolution of artificial populations, wherein the fitness of each animat (artificial animal) depended on its ability to predict the next element of a sequence made up of a repeating binary string of varying size. When the string was short relative to the animats' neural capacity, they could learn it and correctly predict the next element of the sequence. When it was long, they could not learn it, turning to the next best option: to perseverate. Animats from the last generation then performed the task of predicting the next element of a non-periodical binary sequence. We found that, whereas animats with smaller neural capacity kept perseverating with the best alternative as before, animats with larger neural capacity, which had previously been able to learn the pattern of repeating strings, adopted probability matching, being outperformed by the perseverating animats. Our results demonstrate how the ability to make predictions in an environment endowed with regular patterns may lead to probability matching under less structured conditions. They point to probability matching as a likely by-product of adaptive cognitive strategies that were crucial in human evolution, but may lead to sub-optimal performances in other environments.

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This paper proposes a drain current model for triple-gate n-type junctionless nanowire transistors. The model is based on the solution of the Poisson equation. First, the 2-D Poisson equation is used to obtain the effective surface potential for long-channel devices, which is used to calculate the charge density along the channel and the drain current. The solution of the 3-D Laplace equation is added to the 2-D model in order to account for the short-channel effects. The proposed model is validated using 3-D TCAD simulations where the drain current and its derivatives, the potential, and the charge density have been compared, showing a good agreement for all parameters. Experimental data of short- channel devices down to 30 nm at different temperatures have been also used to validate the model.

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We address the investigation of the solvation properties of the minimal orientational model for water originally proposed by [Bell and Lavis, J. Phys. A 3, 568 (1970)]. The model presents two liquid phases separated by a critical line. The difference between the two phases is the presence of structure in the liquid of lower density, described through the orientational order of particles. We have considered the effect of a small concentration of inert solute on the solvent thermodynamic phases. Solute stabilizes the structure of solvent by the organization of solvent particles around solute particles at low temperatures. Thus, even at very high densities, the solution presents clusters of structured water particles surrounding solute inert particles, in a region in which pure solvent would be free of structure. Solute intercalates with solvent, a feature which has been suggested by experimental and atomistic simulation data. Examination of solute solubility has yielded a minimum in that property, which may be associated with the minimum found for noble gases. We have obtained a line of minimum solubility (TmS) across the phase diagram, accompanying the line of maximum density. This coincidence is easily explained for noninteracting solute and it is in agreement with earlier results in the literature. We give a simple argument which suggests that interacting solute would dislocate TmS to higher temperatures.

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Objective Deposition of monosodium urate monohydrate (MSU) crystals in the joints promotes an intense inflammatory response and joint dysfunction. This study evaluated the role of the NLRP3 inflammasome and 5-lipoxygenase (5-LOX)derived leukotriene B4 (LTB4) in driving tissue inflammation and hypernociception in a murine model of gout. Methods. Gout was induced by injecting MSU crystals into the joints of mice. Wild-type mice and mice deficient in NLRP3, ASC, caspase 1, interleukin-1 beta (IL-1 beta), IL-1 receptor type I (IL-1RI), IL-18R, myeloid differentiation factor 88 (MyD88), or 5-LOX were used. Evaluations were performed to assess neutrophil influx, LTB4 activity, cytokine (IL-1 beta, CXCL1) production (by enzyme-linked immunosorbent assay), synovial microvasculature cell adhesion (by intravital microscopy), and hypernociception. Cleaved caspase 1 and production of reactive oxygen species (ROS) were analyzed in macrophages by Western blotting and fluorometric assay, respectively. Results. Injection of MSU crystals into the knee joints of mice induced neutrophil influx and neutrophildependent hypernociception. MSU crystal-induced neutrophil influx was CXCR2-dependent and relied on the induction of CXCL1 in an NLRP3/ASC/caspase 1/IL-1 beta/MyD88-dependent manner. LTB4 was produced rapidly after injection of MSU crystals, and this was necessary for caspase 1-dependent IL-1 beta production and consequent release of CXCR2-acting chemokines in vivo. In vitro, macrophages produced LTB4 after MSU crystal injection, and LTB4 was relevant in the MSU crystalinduced maturation of IL-1 beta. Mechanistically, LTB4 drove MSU crystal-induced production of ROS and ROS-dependent activation of the NLRP3 inflammasome. Conclusion. These results reveal the role of the NLRP3 inflammasome in mediating MSU crystalinduced inflammation and dysfunction of the joints, and highlight a previously unrecognized role of LTB4 in driving NLRP3 inflammasome activation in response to MSU crystals, both in vitro and in vivo.

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We use an infinite-range Maier-Saupe model, with two sets of local quadrupolar variables and restricted orientations, to investigate the global phase diagram of a coupled system of two nematic subsystems. The free energy and the equations of state are exactly calculated by standard techniques of statistical mechanics. The nematic-isotropic transition temperature of system A increases with both the interaction energy among mesogens of system B, and the two-subsystem coupling J. This enhancement of the nematic phase is manifested in a global phase diagram in terms of the interaction parameters and the temperature T. We make some comments on the connections of these results with experimental findings for a system of diluted ferroelectric nanoparticles embedded in a nematic liquid-crystalline environment.

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PURPOSE: To evaluate the effect of N-acetylcysteine (NAC) combined with fluid resuscitation on pulmonary cell death in rats induced with controlled hemorrhagic shock (HS). METHODS: Two arteries (MAP calculation and exsanguination) and one vein (treatments) were catheterized in 22 anesthetized rats. Two groups of male albino rats were induced with controlled HS at 35mmHg MAP for 60 min. After this period, the RL group was resuscitated with Ringer's lactate and the RL+NAC group was resuscitated with Ringer's lactate combined with 150mg/Kg NAC. The control group animals were cannulated only. The animals were euthanized after 120 min of fluid resuscitation. Lung tissue samples were collected to evaluate the following: histopathology, TUNEL and imunohistochemical expression of caspase 3. RESULTS: RL showed a greater number of cells stained by TUNEL than RL + NAC, but there was no change in caspase 3 expression in any group. CONCLUSION: N-acetylcysteine associate to fluid resuscitation, after hemorrhagic shock, decreased cell death attenuating lung injury.

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Objectives: To investigate the potential of an active attachment biofilm model as a highthroughput demineralization biofilm model for the evaluation of caries-preventive agents. Methods: Streptococcus mutans UA159 biofilms were grown on bovine dentine discs in a highthroughput active attachment model. Biofilms were first formed in a medium with high buffer capacity for 24 h and then subjected to various photodynamic therapies (PACT) using the combination of Light Emitting Diodes (LEDs, Biotable (R)) and Photogem (R). Viability of the biofilms was evaluated by plate counts. To investigate treatment effects on dentine lesion formation, the treated biofilms were grown in a medium with low buffer capacity for an additional 24 h. Integrated mineral loss (IML) and lesion depth (LD) were assessed by transversal microradiography. Calcium release in the biofilm medium was measured by atomic absorption spectroscopy. Results: Compared to the water treated control group, significant reduction in viability of S. mutans biofilms was observed when the combination of LEDs and Photogem (R) was applied. LEDs or Photogem (R) only did not result in biofilm viability changes. Similar outcomes were also found for dentine lesion formation. Significant lower IML and LD values were only found in the group subjected to the combined treatment of LEDs and Photogem (R). There was a good correlation between the calcium release data and the IML or LD values. Conclusions: The high-throughput active attachment biofilm model is applicable for evaluating novel caries-preventive agents on both biofilm and demineralization inhibition. PACT had a killing effect on 24 h S. mutans biofilms and could inhibit the demineralization process. (C) 2011 Elsevier Ltd. All rights reserved.

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The study introduces a new regression model developed to estimate the hourly values of diffuse solar radiation at the surface. The model is based on the clearness index and diffuse fraction relationship, and includes the effects of cloud (cloudiness and cloud type), traditional meteorological variables (air temperature, relative humidity and atmospheric pressure observed at the surface) and air pollution (concentration of particulate matter observed at the surface). The new model is capable of predicting hourly values of diffuse solar radiation better than the previously developed ones (R-2 = 0.93 and RMSE = 0.085). A simple version with a large applicability is proposed that takes into consideration cloud effects only (cloudiness and cloud height) and shows a R-2 = 0.92. (C) 2011 Elsevier Ltd. All rights reserved.

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The purpose of this paper is to develop a Bayesian analysis for the right-censored survival data when immune or cured individuals may be present in the population from which the data is taken. In our approach the number of competing causes of the event of interest follows the Conway-Maxwell-Poisson distribution which generalizes the Poisson distribution. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the proposed model. Also, some discussions on the model selection and an illustration with a real data set are considered.

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The occupational exposure limits of different risk factors for development of low back disorders (LBDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors for LBDs interact in causing injury, since the nature and mechanism of these disorders are relatively unknown phenomena. Industrial ergonomists' role becomes further complicated because the potential risk factors that may contribute towards the onset of LBDs interact in a complex manner, which makes it difficult to discriminate in detail among the jobs that place workers at high or low risk of LBDs. The purpose of this paper was to develop a comparative study between predictions based on the neural network-based model proposed by Zurada, Karwowski & Marras (1997) and a linear discriminant analysis model, for making predictions about industrial jobs according to their potential risk of low back disorders due to workplace design. The results obtained through applying the discriminant analysis-based model proved that it is as effective as the neural network-based model. Moreover, the discriminant analysis-based model proved to be more advantageous regarding cost and time savings for future data gathering.

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Some phase space transport properties for a conservative bouncer model are studied. The dynamics of the model is described by using a two-dimensional measure preserving mapping for the variables' velocity and time. The system is characterized by a control parameter epsilon and experiences a transition from integrable (epsilon = 0) to nonintegrable (epsilon not equal 0). For small values of epsilon, the phase space shows a mixed structure where periodic islands, chaotic seas, and invariant tori coexist. As the parameter epsilon increases and reaches a critical value epsilon(c), all invariant tori are destroyed and the chaotic sea spreads over the phase space, leading the particle to diffuse in velocity and experience Fermi acceleration (unlimited energy growth). During the dynamics the particle can be temporarily trapped near periodic and stable regions. We use the finite time Lyapunov exponent to visualize this effect. The survival probability was used to obtain some of the transport properties in the phase space. For large epsilon, the survival probability decays exponentially when it turns into a slower decay as the control parameter epsilon is reduced. The slower decay is related to trapping dynamics, slowing the Fermi Acceleration, i.e., unbounded growth of the velocity.

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Dietary nitrite and nitrate have been reported as alternative sources of nitric oxide (NO). In this regard, we reported previously that sodium nitrite added to drinking water was able to exert antihypertensive effects in an experimental model of hypertension in a dose-dependent manner. Taking into consideration that nitrite is continuously converted to nitrate in the bloodstream, here we expanded our previous report and evaluate whether a single daily dose of sodium nitrite could exert antihypertensive effects in 2 kidney-1 clip (2K1C) hypertensive rats. Sham-operated and 2K1C rats were treated with vehicle or sodium nitrite (15 mg/kg/day) for 4 weeks. We evaluated the effects induced by sodium nitrite treatment on systolic blood pressure (SBP) and NO markers such as plasma nitrite, nitrite + nitrate (NOx), cGMP, and blood levels of nitrosyl-hemoglobin. In addition, we also evaluated effects of nitrite on oxidative stress and antioxidant enzymes. Dihydroethidium (DHE) was used to evaluate aortic reactive oxygen species (ROS) production by fluorescence microscopy, and plasma levels of thiobarbituric acid-reactive species (TBARS) were measured in plasma samples from all experimental groups. Red blood cell superoxide dismutase (SOD) and catalase activity were evaluated with commercial kits. Sodium nitrite treatment reduced SBP in 2K1C rats (P < 0.05). We found lower plasma nitrite and NOx levels in 2K1C rats compared with normotensive controls (both P < 0.05). Nitrite treatment restored the lower levels of nitrite and NOx. While no change was found in the blood levels of nitrosyl-hemoglobin (P > 0.05), nitrite treatment increased the plasma levels of cGMP in 2K1C rats (P < 0.05). Higher plasma TBARS levels and aortic ROS levels were found in hypertensive rats compared with controls (P < 0.05), and nitrite blunted these alterations. Lower SOD and catalase activities were found in 2K1C hypertensive rats compared with controls (both P < 0.05). Nitrite treatment restored SOD activity (P < 0.05), whereas catalase was not affected. These data suggest that even a single daily oral dose of sodium nitrite is able to lower SBP and exert antioxidant effects in renovascular hypertension.

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This study aimed to develop an equipment and system of resistance exercise (RE), based on squat-type exercise for rodents, with control of training variables. We developed an operant conditioning system composed of sound, light and feeding devices that allowed optimized RE performance by the animal. With this system, it is not necessary to impose fasting or electric shock for the animal to perform the task proposed (muscle contraction). Furthermore, it is possible to perform muscle function tests in vivo within the context of the exercise proposed and control variables such as intensity, volume (sets and repetitions), and exercise session length, rest interval between sets and repetitions, and concentric strength. Based on the experiments conducted, we demonstrated that the model proposed is able to perform more specific control of other RE variables, especially rest interval between sets and repetitions, and encourages the animal to exercise through short-term energy restriction and "disturbing" stimulus that do not promote alterations in body weight. Therefore, despite experimental limitations, we believe that this RE apparatus is closer to the physiological context observed in humans.

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A Bayesian nonparametric model for Taguchi's on-line quality monitoring procedure for attributes is introduced. The proposed model may accommodate the original single shift setting to the more realistic situation of gradual quality deterioration and allows the incorporation of an expert's opinion on the production process. Based on the number of inspections to be carried out until a defective item is found, the Bayesian operation for the distribution function that represents the increasing sequence of defective fractions during a cycle considering a mixture of Dirichlet processes as prior distribution is performed. Bayes estimates for relevant quantities are also obtained. (C) 2012 Elsevier B.V. All rights reserved.

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This work addresses the solution to the problem of robust model predictive control (MPC) of systems with model uncertainty. The case of zone control of multi-variable stable systems with multiple time delays is considered. The usual approach of dealing with this kind of problem is through the inclusion of non-linear cost constraint in the control problem. The control action is then obtained at each sampling time as the solution to a non-linear programming (NLP) problem that for high-order systems can be computationally expensive. Here, the robust MPC problem is formulated as a linear matrix inequality problem that can be solved in real time with a fraction of the computer effort. The proposed approach is compared with the conventional robust MPC and tested through the simulation of a reactor system of the process industry.