6 resultados para Cargo handling
em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)
Resumo:
Early-life environmental events, such as the handling procedure, can induce long-lasting alterations upon several behavioral and neuroendocrine systems. However, the changes within the pups that could be causally related to the effects in adulthood are still poorly understood. In the present study, we analyzed the effects of neonatal handling on behavioral (maternal odor preference) and biochemical (cyclic AMP response element-binding protein (CREB) phosphorylation, noradrenaline (NA), and serotonin (5-HT) levels in the olfactory bulb (OB)) parameters in 7-day-old male and female rat pups. Repeated handling (RH) abolished preference for the maternal odor in female pups compared with nonhandled (NH) and the single-handled (SH) ones, while in RH males the preference was not different than NH and SH groups. In both male and female pups, RH decreased NA activity in the OB, but 5-HT activity increased only in males. Since preference for the maternal odor involves the synergic action of NA and 5-HT in the OB, the maintenance of the behavior in RH males could be related to the increased 5-HT activity, in spite of reduction in the NA activity in the OB. RH did not alter CREB phosphorylation in the OB of both male and females compared with NH pups. The repeated handling procedure can affect the behavior of rat pups in response to the maternal odor and biochemical parameters related to the olfactory learning mechanism. Sex differences were already detected in 7-day-old pups. Although the responsiveness of the hypothalamic-pituitary-adrenal axis to stressors is reduced in the neonatal period, environmental interventions may impact behavioral and biochemical mechanisms relevant to the animal at that early age. (C) 2009 IBRO. Published by Elsevier Ltd. All rights reserved.
Resumo:
In this paper we present a genetic algorithm with new components to tackle capacitated lot sizing and scheduling problems with sequence dependent setups that appear in a wide range of industries, from soft drink bottling to food manufacturing. Finding a feasible solution to highly constrained problems is often a very difficult task. Various strategies have been applied to deal with infeasible solutions throughout the search. We propose a new scheme of classifying individuals based on nested domains to determine the solutions according to the level of infeasibility, which in our case represents bands of additional production hours (overtime). Within each band, individuals are just differentiated by their fitness function. As iterations are conducted, the widths of the bands are dynamically adjusted to improve the convergence of the individuals into the feasible domain. The numerical experiments on highly capacitated instances show the effectiveness of this computational tractable approach to guide the search toward the feasible domain. Our approach outperforms other state-of-the-art approaches and commercial solvers. (C) 2009 Elsevier Ltd. All rights reserved.
Resumo:
Model trees are a particular case of decision trees employed to solve regression problems. They have the advantage of presenting an interpretable output, helping the end-user to get more confidence in the prediction and providing the basis for the end-user to have new insight about the data, confirming or rejecting hypotheses previously formed. Moreover, model trees present an acceptable level of predictive performance in comparison to most techniques used for solving regression problems. Since generating the optimal model tree is an NP-Complete problem, traditional model tree induction algorithms make use of a greedy top-down divide-and-conquer strategy, which may not converge to the global optimal solution. In this paper, we propose a novel algorithm based on the use of the evolutionary algorithms paradigm as an alternate heuristic to generate model trees in order to improve the convergence to globally near-optimal solutions. We call our new approach evolutionary model tree induction (E-Motion). We test its predictive performance using public UCI data sets, and we compare the results to traditional greedy regression/model trees induction algorithms, as well as to other evolutionary approaches. Results show that our method presents a good trade-off between predictive performance and model comprehensibility, which may be crucial in many machine learning applications. (C) 2010 Elsevier Inc. All rights reserved.
Resumo:
Most models designed to study the bidirectional movement of cargos as they are driven by molecular motors rely on the idea that motors of different polarities can be coordinated by external agents if arranged into a motor-cargo complex to perform the necessary work Gross, Hither and yon: a review of bidirectional microtubule-based transport (Gross in Phys. Biol. 1:R1-R11, 2004). Although these models have provided us with important insights into these phenomena, there are still many unanswered questions regarding the mechanisms through which the movement of the complex takes place on crowded microtubules. For example (i) how does cargo-binding affect motor motility? and in connection with that-(ii) how does the presence of other motors (and also other cargos) on the microtubule affect the motility of the motor-cargo complex? We discuss these questions from a different perspective. The movement of a cargo is conceived here as a hopping process resulting from the transference of cargo between neighboring motors. In the light of this, we examine the conditions under which cargo might display bidirectional movement even if directed by motors of a single polarity. The global properties of the model in the long-time regime are obtained by mapping the dynamics of the collection of interacting motors and cargos into an asymmetric simple exclusion process (ASEP) which can be resolved using the matrix ansatz introduced by Derrida (Derrida and Evans in Nonequilibrium Statistical Mechanics in One Dimension, pp. 277-304, 1997; Derrida et al. in J. Phys. A 26: 1493-1517, 1993).
Resumo:
We consider the dynamics of cargo driven by a collection of interacting molecular motors in the context of ail asymmetric simple exclusion process (ASEP). The model is formulated to account for (i) excluded-volume interactions, (ii) the observed asymmetry of the stochastic movement of individual motors and (iii) interactions between motors and cargo. Items (i) and (ii) form the basis of ASEP models and have already been considered to study the behavior of motor density profile [A. Parmeggiani. T. Franosch, E. Frey, Phase Coexistence in driven one-dimensional transport, Phys. Rev. Lett. 90 (2003) 086601-1-086601-4]. Item (iii) is new. It is introduced here as an attempt to describe explicitly the dependence of cargo movement on the dynamics of motors in this context. The steady-state Solutions Of the model indicate that the system undergoes a phase transition of condensation type as the motor density varies. We study the consequences of this transition to the behavior of the average cargo velocity. (C) 2009 Elsevier B.V. All rights reserved.
Resumo:
Architectures based on Coordinated Atomic action (CA action) concepts have been used to build concurrent fault-tolerant systems. This conceptual model combines concurrent exception handling with action nesting to provide a general mechanism for both enclosing interactions among system components and coordinating forward error recovery measures. This article presents an architectural model to guide the formal specification of concurrent fault-tolerant systems. This architecture provides built-in Communicating Sequential Processes (CSPs) and predefined channels to coordinate exception handling of the user-defined components. Hence some safety properties concerning action scoping and concurrent exception handling can be proved by using the FDR (Failure Divergence Refinement) verification tool. As a result, a formal and general architecture supporting software fault tolerance is ready to be used and proved as users define components with normal and exceptional behaviors. (C) 2010 Elsevier B.V. All rights reserved.