996 resultados para Temporal preferences


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Landing data of 21 fisheries from Karnataka (quarterly landings for the period 1956 to 1978 and annual landings for the period 1979 to 1981) were analysed to study the te111poral behaviour of the landings. The relative distribution and secular trends in each of the fisheries are reported. On an average, mackerel and oil sardine together account for about 70% of the annual landings. The fluctuation in the landings in all the fisheries was very high with the coefficient of variation attaining a minimum value of 61.53%. The inverse relationship between the landings of oil sardine and mackerel was found to be statistically significant. It is suggested that fishing effort be further increased in fisheries that have demonstrated a rising trend (about 73% of the total annual landings) as also in the case of the fisheries whose trends appear stagnant (about 21% of the annual landings). However, there seems to be some evidence of a need for regulating fishing in Hemirhamphus and Belone, Caranx and penaeid prawns. Regulations need to be made authentic with the help of sufficient information on not merely the fishery but on the whole population.

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Seasonal patterns of 21 fisheries in Karnataka (after isolation from time-series components) are presented. Depending on the pattern of seasonal fluctuation in landings, 19 fisheries have been grouped into five patterns, A, B, C, D and E. Ribbon fishes and 'other clupeids' did not exhibit any significant seasonal pattern. Pattern A with highest landings in the 4th quarter (October to December), followed by the 1, 2 and 3 quarters, is the most common in 10 species/groups (comprising 78% of the total landings). Harmonic analysis has been carried out using the seasonal indices.

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Marine landing data for Karnataka during 1956-1978 were subjected to time series analysis and cyclical periodicities isolated in the case of seven fisheries namely, ribbon fish (five year cycle); Caranx spp., Leiognathus spp, and mackerel (six year cycle each); the combined landings of Hemirhamphus spp. and Belone spp.,'Lesser Sardines' and 'Other Clupeids' (seven year cycle each). 'Total' demonstrated an eight-year cyclical periodicity.

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Breather stability and longevity in thermally relaxing nonlinear arrays is investigated under the scrutiny of the analysis and tools employed for time series and state reconstruction of a dynamical system. We briefly review the methods used in the analysis and characterize a breather in terms of the results obtained with such methods. Our present work focuses on spontaneously appearing breathers in thermal Fermi-Pasta-Ulam arrays but we believe that the conclusions are general enough to describe many other related situations; the particular case described in detail is presented as another example of systems where three incommensurable frequencies dominate their chaotic dynamics (reminiscent of the Ruelle-Takens scenario for the appearance of chaotic behavior in nonlinear systems). This characterization may also be of great help for the discovery of breathers in experimental situations where the temporal evolution of a local variable (like the site energy) is the only available/measured data. © 2005 American Institute of Physics.

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In the present study, we examined the effects of extremely low-frequency (ELF) electromagnetic fields on morphine-induced conditioned place preferences in rats. During the conditioning phase (12 days), three groups of rats were placed in a sensory cue-defined environment paired with morphine (10 mg/kg, i.p.) following exposure to either 20 Hz (1.80 mT) or 50 Hz (2.20 mT) or sham electromagnetic fields for 60 min/day, respectively, and were placed in another sensory cue-defined environment paired with physiological saline (1 ml/kg, i.p.) without exposure to electromagnetic fields. After finishing 12 days of conditioning, preference tests for the morphine-paired place were performed during a 10-day withdrawal period. The exposure to electromagnetic fields substantially potentiated morphine-induced place preferences in rodents, suggesting that ELF electromagnetic fields can increase the propensity for morphine-induced conditioned behaviors. (C) 2005 Elsevier Ireland Ltd. All rights reserved.

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Human visual function declines with age. Much of this decline is mediated by changes in the central visual pathways. In this study we compared the spatial and temporal sensitivities of striate cortical cells in young and old paralysed macaque monkeys. Ext

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A total of 91 species under 44 genera were identified among the phytoplankton community during the course of one year's investigation between May 1982 and April 1983. Bacillariophyta was the most dominant group with 72 specie, Chlorophyta 11 spp, Cyanophyta 6 spp and Pyrrophyta was represented by 2 species. The yearly percentage composition of 4 groups of phytoplankton in order of abundance were Bacillariophyta 50.77%, Cyanophyta 47.70%, Chlorophyta 1.5% and Pyrrophyta 0.02%. The highest densities of phytoplankton were recorded in monsoon months (June-July) with a peak in July (31550 cells/l) and the minimum in February (770 cells/1). Higher concentration of phytoplankton was recorded at station 2, nearer to the Chakaria Sundarbans (mangroves), but abundance of phytoplankton showed no significant difference in the two stations (Mann Whitney U test, P=0.64, Z=-0.642, U=64). Phytoplankton population in this area were positively correlated with rainfall (r=0.655, P=<0.5, df.22) and water temperature (r=0.523, P=<0.05). Skeletonema costatum was the dominant member of phytoplankton and occupied 35.23% of the annual population and occurred throughout the period of study except in September and January. Its abundance was recorded during the monsoon months (April- July) with a maximum density (24185 cells/l) in July. No significant correlation was found between abundance of S. costatum and the hydro-meteorological parameters recorded in the Chakaria mangrove area.

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The use of mixture-model techniques for motion estimation and image sequence segmentation was discussed. The issues such as modeling of occlusion and uncovering, determining the relative depth of the objects in a scene, and estimating the number of objects in a scene were also investigated. The segmentation algorithm was found to be computationally demanding, but the computational requirements were reduced as the motion parameters and segmentation of the frame were initialized. The method provided a stable description, in whichthe addition and removal of objects from the description corresponded to the entry and exit of objects from the scene.

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We propose a novel model for the spatio-temporal clustering of trajectories based on motion, which applies to challenging street-view video sequences of pedestrians captured by a mobile camera. A key contribution of our work is the introduction of novel probabilistic region trajectories, motivated by the non-repeatability of segmentation of frames in a video sequence. Hierarchical image segments are obtained by using a state-of-the-art hierarchical segmentation algorithm, and connected from adjacent frames in a directed acyclic graph. The region trajectories and measures of confidence are extracted from this graph using a dynamic programming-based optimisation. Our second main contribution is a Bayesian framework with a twofold goal: to learn the optimal, in a maximum likelihood sense, Random Forests classifier of motion patterns based on video features, and construct a unique graph from region trajectories of different frames, lengths and hierarchical levels. Finally, we demonstrate the use of Isomap for effective spatio-temporal clustering of the region trajectories of pedestrians. We support our claims with experimental results on new and existing challenging video sequences. © 2011 IEEE.

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Humans have been shown to adapt to the temporal statistics of timing tasks so as to optimize the accuracy of their responses, in agreement with the predictions of Bayesian integration. This suggests that they build an internal representation of both the experimentally imposed distribution of time intervals (the prior) and of the error (the loss function). The responses of a Bayesian ideal observer depend crucially on these internal representations, which have only been previously studied for simple distributions. To study the nature of these representations we asked subjects to reproduce time intervals drawn from underlying temporal distributions of varying complexity, from uniform to highly skewed or bimodal while also varying the error mapping that determined the performance feedback. Interval reproduction times were affected by both the distribution and feedback, in good agreement with a performance-optimizing Bayesian observer and actor model. Bayesian model comparison highlighted that subjects were integrating the provided feedback and represented the experimental distribution with a smoothed approximation. A nonparametric reconstruction of the subjective priors from the data shows that they are generally in agreement with the true distributions up to third-order moments, but with systematically heavier tails. In particular, higher-order statistical features (kurtosis, multimodality) seem much harder to acquire. Our findings suggest that humans have only minor constraints on learning lower-order statistical properties of unimodal (including peaked and skewed) distributions of time intervals under the guidance of corrective feedback, and that their behavior is well explained by Bayesian decision theory.

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OBJECTIVE: A standard view in health economics is that, although there is no market that determines the "prices" for health states, people can nonetheless associate health states with monetary values (or other scales, such as quality adjusted life year [QALYs] and disability adjusted life year [DALYs]). Such valuations can be used to shape health policy, and a major research challenge is to elicit such values from people; creating experimental "markets" for health states is a theoretically attractive way to address this. We explore the possibility that this framework may be fundamentally flawed-because there may not be any stable values to be revealed. Instead, perhaps people construct ad hoc values, influenced by contextual factors, such as the observed decisions of others. METHOD: The participants bid to buy relief from equally painful electrical shocks to the leg and arm in an experimental health market based on an interactive second-price auction. Thirty subjects were randomly assigned to two experimental conditions where the bids by "others" were manipulated to follow increasing or decreasing price trends for one, but not the other, pain. After the auction, a preference test asked the participants to choose which pain they prefer to experience for a longer duration. RESULTS: Players remained indifferent between the two pain-types throughout the auction. However, their bids were differentially attracted toward what others bid for each pain, with overbidding during decreasing prices and underbidding during increasing prices. CONCLUSION: Health preferences are dissociated from market prices, which are strongly referenced to others' choices. This suggests that the price of health care in a free-market has the capacity to become critically detached from people's underlying preferences.

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Marginal utility theory prescribes the relationship between the objective property of the magnitude of rewards and their subjective value. Despite its pervasive influence, however, there is remarkably little direct empirical evidence for such a theory of value, let alone of its neurobiological basis. We show that human preferences in an intertemporal choice task are best described by a model that integrates marginally diminishing utility with temporal discounting. Using functional magnetic resonance imaging, we show that activity in the dorsal striatum encodes both the marginal utility of rewards, over and above that which can be described by their magnitude alone, and the discounting associated with increasing time. In addition, our data show that dorsal striatum may be involved in integrating subjective valuation systems inherent to time and magnitude, thereby providing an overall metric of value used to guide choice behavior. Furthermore, during choice, we show that anterior cingulate activity correlates with the degree of difficulty associated with dissonance between value and time. Our data support an integrative architecture for decision making, revealing the neural representation of distinct subcomponents of value that may contribute to impulsivity and decisiveness.