969 resultados para optimal foraging theory


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Feral cats (Felis catus) have a wide global distribution and cause significant damage to native fauna. Reducing their impacts requires an understanding of how they use habitat and which parts of the landscape should be the focus of management. We reviewed 27 experimental and observational studies conducted around the world over the last 35 years that aimed to examine habitat use by feral and unowned cats. Our aims were to: (1) summarise the current body of literature on habitat use by feral and unowned cats in the context of applicable ecological theory (i.e. habitat selection, foraging theory); (2) develop testable hypotheses to help fill important knowledge gaps in the current body of knowledge on this topic; and (3) build a conceptual framework that will guide the activities of researchers and managers in reducing feral cat impacts. We found that feral cats exploit a diverse range of habitats including arid deserts, shrublands and grasslands, fragmented agricultural landscapes, urban areas, glacial valleys, equatorial to sub-Antarctic islands and a range of forest and woodland types. Factors invoked to explain habitat use by cats included prey availability, predation/competition, shelter availability and human resource subsidies, but the strength of evidence used to support these assertions was low, with most studies being observational or correlative.Wetherefore provide a list of key directions that will assist conservation managers and researchers in better understanding and ameliorating the impact of feral cats at a scale appropriate for useful management and research. Future studies will benefit from employing an experimental approach and collecting data on the relative abundance and activity of prey and other predators. This might include landscape-scale experiments where the densities of predators, prey or competitors are manipulated and then the response in cat habitat use is measured. Effective management of feral cat populations could target high-use areas, such as linear features and structurally complex habitat. Since our review shows often-divergent outcomes in the use of the same habitat components and vegetation types worldwide, local knowledge and active monitoring of management actions is essential when deciding on control programs.

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This paper presents an approach to design a nonlinear observer-based excitation controller for multimachine power systems to enhance the transient stability. The controller is designed based on the partial feedback linearization of a nonlinear power system model which transforms the model into a reducedorder linear one with an autonomous dynamical part. Then a linear state feedback stabilizing controller is designed for the reduced-order linear power system model using optimal control theory which enhances the stability of the entire system. The states of the feedback stabilizing controller are obtained from the nonlinear observer and the performance of this observer-based controller is independent of the operating points of power systems. The performance of the proposed observer-based controller is compared to that of an exact feedback linearizing observer-based controller and a partial feedback linearizing controller without observer under different operating conditions.

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This paper analyzes the impact of a geographical social grouping (neighborhood) and its relative perceived size in the spontaneous group’s identiication level and place satisfaction, as well as the intensity of and motives for discrimination against inhabitants of other places. Two studies are presented: an experimental one using the minimal group categorization paradigm and an onsite investigation of a city neighborhood. Consistent with the predictions, the results showed that smaller neighborhoods reported higher identiication and satisfaction with the place of residence, as well as higher discrimination of other neighborhoods. In line with the optimal distinctiveness theory (ODT), the indings showed that the motivation for discrimination varies as a function of the in-group size. Thus, the members of larger groups discriminate by increasing the diferentiation between the in-group and the out-group, whereas the members of smaller groups increased the value of the in-group. Furthermore, the results were consistent with a social identity theory and ODT explanation of diverse research that shows the non-trivial nature of geographical bounded social grouping and its importance in a diverse set of contexts and its impact in inter-neighborhood relationships.

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In this paper a new graph-theory and improved genetic algorithm based practical method is employed to solve the optimal sectionalizer switch placement problem. The proposed method determines the best locations of sectionalizer switching devices in distribution networks considering the effects of presence of distributed generation (DG) in fitness functions and other optimization constraints, providing the maximum number of costumers to be supplied by distributed generation sources in islanded distribution systems after possible faults. The proposed method is simulated and tested on several distribution test systems in both cases of with DG and non DG situations. The results of the simulations validate the proposed method for switch placement of the distribution network in the presence of distributed generation.

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The stochastic version of Pontryagin's maximum principle is applied to determine an optimal maintenance policy of equipment subject to random deterioration. The deterioration of the equipment with age is modelled as a random process. Next the model is generalized to include random catastrophic failure of the equipment. The optimal maintenance policy is derived for two special probability distributions of time to failure of the equipment, namely, exponential and Weibull distributions Both the salvage value and deterioration rate of the equipment are treated as state variables and the maintenance as a control variable. The result is illustrated by an example

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This paper deals with the interpretation of the discrete-time optimal control problem as a scattering process in a discrete medium. We treat the discrete optimal linear regulator, constrained end-point and servo and tracking problems, providing a unified approach to these problems. This approach results in an easy derivation of the desired results as well as several new ones.

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In this paper, several known computational solutions are readily obtained in a very natural way for the linear regulator, fixed end-point and servo-mechanism problems using a certain frame-work from scattering theory. The relationships between the solutions to the linear regulator problem with different terminal costs and the interplay between the forward and backward equations have enabled a concise derivation of the partitioned equations, the forward-backward equations, and Chandrasekhar equations for the problem. These methods have been extended to the fixed end-point, servo, and tracking problems.

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An optimal theory on how database analysis to capture the flow structures has been developed in this paper, which include the POD method as its special case. By means of the remainder minimization method in the Sobolev space, for more general optimal conditions the new theory has the potential to overcome an inherent limitation of the POD method, i.e., it cannot be used to the situations in which the optimal condition is other than the inner product global one. As an example, using the new theory, the database of a two-dimensional flow over a backward-facing step is analyzed in detail, with velocity and vorticity bases.

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We study the nature of biomolecular binding. We found that in general there exists several thermodynamic phases: a native binding phase, a non-native phase, and a glass or local trapping phase. The quantitative optimal criterion for the binding specificity is found to be the maximization of the ratio of the binding transition temperature versus the trapping transition temperature, or equivalently the ratio of the energy gap of binding between the native state and the average non-native states versus the dispersion or variance of the non-native states. This leads to a funneled binding energy landscape.

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Although the costs of parental care are at the foundations of optimal-parental-investment theory, our understanding of the nature of the underlying costs is limited by the difficulty of measuring variation in foraging effort. We simultaneously measured parental provisioning and foraging behavior in a free-living population of Zebra Finches (Taeniopygia guttata) using an electronic monitoring system. We fitted 145 adults with a passive transponder tag and remotely recorded their visits to nest boxes and feeders continuously over a 2-month period. After validating the accuracy of this monitoring system, we studied how provisioning and foraging activities varied through time (day and breeding cycle) and influenced the benefits (food received by the offspring) and costs (interclutch interval) of parental care. The provisioning rates of wild Zebra Finches were surprisingly low, with an average of only one visit per hour throughout the day. This was significantly lower than those reported for this model species in captivity and for most other passerines in the wild. Nest visitation rate only partially explained the amount of food received by the young, with parental foraging activity, including the minimum distance covered on foraging trips, being better predictors. Parents that sustained higher foraging activity and covered more distance during the first breeding attempt took longer to renest. These results demonstrate that in some species matching foraging activity with offspring provisioning may provide a better estimate of the true investment that individuals commit to a reproductive attempt.

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This paper considers tests which maximize the weighted average power (WAP). The focus is on determining WAP tests subject to an uncountable number of equalities and/or inequalities. The unifying theory allows us to obtain tests with correct size, similar tests, and unbiased tests, among others. A WAP test may be randomized and its characterization is not always possible. We show how to approximate the power of the optimal test by sequences of nonrandomized tests. Two alternative approximations are considered. The rst approach considers a sequence of similar tests for an increasing number of boundary conditions. This discretization allows us to implement the WAP tests in practice. The second method nds a sequence of tests which approximate the WAP test uniformly. This approximation allows us to show that WAP similar tests are admissible. The theoretical framework is readily applicable to several econometric models, including the important class of the curved-exponential family. In this paper, we consider the instrumental variable model with heteroskedastic and autocorrelated errors (HAC-IV) and the nearly integrated regressor model. In both models, we nd WAP similar and (locally) unbiased tests which dominate other available tests.