988 resultados para Gaussian assumption
Resumo:
Numerous studies have examined which individual defense mechanisms are related with mental health, and which are linked with psychopathology. However, the idea that a flexible use of defensive mechanisms is related to psychological wellbeing remained a clinical assumption, which this study sought to test empirically. A total of 62 (N = 62) outpatients participated in the study and were assessed with the Symptom Checklist-90R and the Social Adjustment Self-rated Scale. A subsample of 40 participants was further assessed using the Hamilton Depression (HAMD-21) and Anxiety scales (HAMA-21). The first therapy session of all participants was transcribed and rated using the Defense Mechanisms Ratings Scales (), and the Overall Defensive Functioning (ODF) score, which indicates the maturity of one's defensive functioning, was computed. An indicator of flexible use of defenses was also calculated based on the Gini Concentration C measure. Results showed that defensive flexibility, but not ODF, could predict anxiety scores. Symptom severity was predicted by both ODF and defensive flexibility, although in directions opposite to our predictions. Results suggest that defensive flexibility captures another aspect of an individual's functioning not assessed by the ODF, and that it is a promising new way of documenting defensive functioning.
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The Gross-Neveu model in an S^1 space is analyzed by means of a variational technique: the Gaussian effective potential. By making the proper connection with previous exact results at finite temperature, we show that this technique is able to describe the phase transition occurring in this model. We also make some remarks about the appropriate treatment of Grassmann variables in variational approaches.
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1. Identifying those areas suitable for recolonization by threatened species is essential to support efficient conservation policies. Habitat suitability models (HSM) predict species' potential distributions, but the quality of their predictions should be carefully assessed when the species-environment equilibrium assumption is violated.2. We studied the Eurasian otter Lutra lutra, whose numbers are recovering in southern Italy. To produce widely applicable results, we chose standard HSM procedures and looked for the models' capacities in predicting the suitability of a recolonization area. We used two fieldwork datasets: presence-only data, used in the Ecological Niche Factor Analyses (ENFA), and presence-absence data, used in a Generalized Linear Model (GLM). In addition to cross-validation, we independently evaluated the models with data from a recolonization event, providing presences on a previously unoccupied river.3. Three of the models successfully predicted the suitability of the recolonization area, but the GLM built with data before the recolonization disagreed with these predictions, missing the recolonized river's suitability and badly describing the otter's niche. Our results highlighted three points of relevance to modelling practices: (1) absences may prevent the models from correctly identifying areas suitable for a species spread; (2) the selection of variables may lead to randomness in the predictions; and (3) the Area Under Curve (AUC), a commonly used validation index, was not well suited to the evaluation of model quality, whereas the Boyce Index (CBI), based on presence data only, better highlighted the models' fit to the recolonization observations.4. For species with unstable spatial distributions, presence-only models may work better than presence-absence methods in making reliable predictions of suitable areas for expansion. An iterative modelling process, using new occurrences from each step of the species spread, may also help in progressively reducing errors.5. Synthesis and applications. Conservation plans depend on reliable models of the species' suitable habitats. In non-equilibrium situations, such as the case for threatened or invasive species, models could be affected negatively by the inclusion of absence data when predicting the areas of potential expansion. Presence-only methods will here provide a better basis for productive conservation management practices.
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We study and characterize a new dynamical regime of underdamped particles in a tilted washboard potential. We find that for small friction in a finite range of forces the particles move essentially nondispersively, that is, coherently, over long intervals of time. The associated distribution of the particle positions moves at an essentially constant velocity and is far from Gaussian-like. This new regime is complementary to, and entirely different from, well-known nonlinear response and large dispersion regimes observed for other values of the external force.
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Recent findings suggest that the visuo-spatial sketchpad (VSSP) may be divided into two sub-components processing dynamic or static visual information. This model may be useful to elucidate the confusion of data concerning the functioning of the VSSP in schizophrenia. The present study examined patients with schizophrenia and matched controls in a new working memory paradigm involving dynamic (the Ball Flight Task - BFT) or static (the Static Pattern Task - SPT) visual stimuli. In the BFT, the responses of the patients were apparently based on the retention of the last set of segments of the perceived trajectory, whereas control subjects relied on a more global strategy. We assume that the patients' performances are the result of a reduced capacity in chunking visual information since they relied mainly on the retention of the last set of segments. This assumption is confirmed by the poor performance of the patients in the static task (SPT), which requires a combination of stimulus components into object representations. We assume that the static/dynamic distinction may help us to understand the VSSP deficits in schizophrenia. This distinction also raises questions about the hypothesis that visuo-spatial working memory can simply be dissociated into visual and spatial sub-components.
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Intensive numerical studies of exact ground states of the two-dimensional ferromagnetic random field Ising model at T=0, with a Gaussian distribution of fields, are presented. Standard finite size scaling analysis of the data suggests the existence of a transition at ¿c=0.64±0.08. Results are compared with existing theories and with the study of metastable avalanches in the same model.
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We present computational approaches as alternatives to a recent microwave cavity experiment by S. Sridhar and A. Kudrolli [Phys. Rev. Lett. 72, 2175 (1994)] on isospectral cavities built from triangles. A straightforward proof of isospectrality is given, based on the mode-matching method. Our results show that the experiment is accurate to 0.3% for the first 25 states. The level statistics resemble those of a Gaussian orthogonal ensemble when the integrable part of the spectrum is removed.
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We study the exact ground state of the two-dimensional random-field Ising model as a function of both the external applied field B and the standard deviation ¿ of the Gaussian random-field distribution. The equilibrium evolution of the magnetization consists in a sequence of discrete jumps. These are very similar to the avalanche behavior found in the out-of-equilibrium version of the same model with local relaxation dynamics. We compare the statistical distributions of magnetization jumps and find that both exhibit power-law behavior for the same value of ¿. The corresponding exponents are compared.
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A numerical study of Brownian motion of noninteracting particles in random potentials is presented. The dynamics are modeled by Langevin equations in the high friction limit. The random potentials are Gaussian distributed and short ranged. The simulations are performed in one and two dimensions. Different dynamical regimes are found and explained. Effective subdiffusive exponents are obtained and commented on.
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The soil CO2 emission has high spatial variability because it depends strongly on soil properties. The purpose of this study was to (i) characterize the spatial variability of soil respiration and related properties, (ii) evaluate the accuracy of results of the ordinary kriging method and sequential Gaussian simulation, and (iii) evaluate the uncertainty in predicting the spatial variability of soil CO2 emission and other properties using sequential Gaussian simulations. The study was conducted in a sugarcane area, using a regular sampling grid with 141 points, where soil CO2 emission, soil temperature, air-filled pore space, soil organic matter and soil bulk density were evaluated. All variables showed spatial dependence structure. The soil CO2 emission was positively correlated with organic matter (r = 0.25, p < 0.05) and air-filled pore space (r = 0.27, p < 0.01) and negatively with soil bulk density (r = -0.41, p < 0.01). However, when the estimated spatial values were considered, the air-filled pore space was the variable mainly responsible for the spatial characteristics of soil respiration, with a correlation of 0.26 (p < 0.01). For all variables, individual simulations represented the cumulative distribution functions and variograms better than ordinary kriging and E-type estimates. The greatest uncertainties in predicting soil CO2 emission were associated with areas with the highest estimated values, which produced estimates from 0.18 to 1.85 t CO2 ha-1, according to the different scenarios considered. The knowledge of the uncertainties generated by the different scenarios can be used in inventories of greenhouse gases, to provide conservative estimates of the potential emission of these gases.
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Stochastic processes defined by a general Langevin equation of motion where the noise is the non-Gaussian dichotomous Markov noise are studied. A non-FokkerPlanck master differential equation is deduced for the probability density of these processes. Two different models are exactly solved. In the second one, a nonequilibrium bimodal distribution induced by the noise is observed for a critical value of its correlation time. Critical slowing down does not appear in this point but in another one.
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We present an analytical scheme, easily implemented numerically, to generate synthetic Gaussian turbulent flows by using a linear Langevin equation, where the noise term acts as a stochastic stirring force. The characteristic parameters of the velocity field are well introduced, in particular the kinematic viscosity and the spectrum of energy. As an application, the diffusion of a passive scalar is studied for two different energy spectra. Numerical results are compared favorably with analytical calculations.
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Melanin is the most common pigment in animal integuments and is responsible for some of the most striking ornaments. A central tenet of sexual selection theory states that melanin-based traits can signal absolute individual quality in any environment only if their expression is condition-dependent. Significant costs imposed by an ornament would ensure that only the highest quality individuals display the most exaggerated forms of the signal. Firm evidence that melanin-based traits can be condition-dependent is still rare in birds. In an experimental test of this central assumption, we report condition-dependent expression of a melanin-based trait in the Eurasian kestrel (Falco tinnunculus). We manipulated nestling body condition by reducing or increasing the number of nestlings soon after hatching. A few days before fledging, we measured the width of sub-terminal black bands on the tail feathers. Compared to nestlings from enlarged broods, individuals raised in reduced broods were in better condition and thereby developed larger sub-terminal bands. Furthermore, in 2 years, first-born nestlings also developed larger sub-terminal bands than their younger siblings that are in poorer condition. This demonstrates that expression of melanin-based traits can be condition-dependent.
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We develop an algorithm to simulate a Gaussian stochastic process that is non-¿-correlated in both space and time coordinates. The colored noise obeys a linear reaction-diffusion Langevin equation with Gaussian white noise. This equation is exactly simulated in a discrete Fourier space.
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Research on regulation has crossed paths with the literature on policy instruments, showing that regulatory policy instruments contain cognitive and normative beliefs about policy. Thus, their usage stacks the deck in favor of one type of actor or one type of regulatory solution. In this article, we challenge the assumption that there is a predetermined relationship between ideas, regulatory policy instruments, and outcomes. We argue that different combinations of conditions lead to different outcomes, depending on how actors use the instrument. Empirically, we analyze 31 EU and UK case studies of regulatory impact assessment (RIA) - a regulatory policy instrument that has been pivotal in the so-called better regulation movement. We distinguish four main usages of RIA, that is, political, instrumental, communicative, and perfunctory. We find that in our sample instrumental usage is not so rare and that the contrast between communicative and political usages is less stark than is commonly thought. In terms of policy recommendations, our analysis suggests that there may be different paths to desirable outcomes. Policymakers should therefore explore different combinations of conditions leading to the usages they deem desirable rather than arguing for a fixed menu of variables.