39 resultados para Spatial computable general equilibrium model


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This work examines the sources of moisture affecting the semi-arid Brazilian Northeast (NEB) during its pre-rainy and rainy season (JFMAM) through a Lagrangian diagnosis method. The FLEXPART model identifies the humidity contributions to the moisture budget over a region through the continuous computation of changes in the specific humidity along back or forward trajectories up to 10 days period. The numerical experiments were done for the period that spans between 2000 and 2004 and results were aggregated on a monthly basis. Results show that besides a minor local recycling component, the vast majority of moisture reaching NEB area is originated in the south Atlantic basin and that the nearby wet Amazon basin bears almost no impact. Moreover, although the maximum precipitation in the ""Poligono das Secas'' region (PS) occurs in March and the maximum precipitation associated with air parcels emanating from the South Atlantic towards PS is observed along January to March, the highest moisture contribution from this oceanic region occurs slightly later (April). A dynamical analysis suggests that the maximum precipitation observed in the PS sector does not coincide with the maximum moisture supply probably due to the combined effect of the Walker and Hadley cells in inhibiting the rising motions over the region in the months following April.

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Changes in the oxygen isotopic composition of the planktonic foraminifer Globigerinoides ruber and in the foraminifera faunal composition in a core retrieved from the southeastern Brazilian continental margin were used to infer past changes in the hydrological balance and monsoon precipitation in the western South Atlantic since the Last Glacial Maximum (LGM). The results suggest a first-order orbital (precessional) control on the South American Monsoon precipitation. This agrees with previous studies based on continental proxies except for LGM estimates provided by pollen records. The causes for this disagreement are discussed.

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ARTIOLI, G. G., B. GUALANO, E. FRANCHINI, F. B. SCAGLIUSI, M. TAKESIAN, M. FUCHS, and A. H. LANCHA. Prevalence, Magnitude, and Methods of Rapid Weight Loss among Judo Competitors. Med. Sci. Sports Exerc., Vol. 42, No. 3, pp. 436-442, 2010. Purpose: To identify the prevalence, magnitude, and methods of rapid weight loss among judo competitors. Methods: Athletes (607 males and 215 females; age = 19.3 +/- 5.3 yr, weight = 70 +/- 7.5 kg, height = 170.6 +/- 9.8 cm) completed a previously validated questionnaire developed to evaluate rapid weight loss in judo athletes, which provides a score. The higher the score obtained, the more aggressive the weight loss behaviors. Data were analyzed using descriptive statistics and frequency analyses. Mean scores obtained in the questionnaire were used to compare specific groups of athletes using, when appropriate, Mann-Whitney U-test or general linear model one-way ANOVA followed by Tamhane post hoc test. Results: Eighty-six percent of athletes reported that have already lost weight to compete. When heavyweights are excluded, this percentage rises to 89%. Most athletes reported reductions of up to 5% of body weight (mean +/- SD: 2.5 +/- 2.3%). The most weight ever lost was 2%-5%, whereas a great part of athletes reported reductions of 5%-10% (mean +/- SD: 6 +/- 4%). The number of reductions underwent in a season was 3 +/- 5. The reductions usually occurred within 7 +/- 7 d. Athletes began cutting weight at 12.6 +/- 6.1 yr. No significant differences were found in the score obtained by male versus female athletes as well as by athletes from different weight classes. Elite athletes scored significantly higher in the questionnaire than nonelite. Athletes who began cutting weight earlier also scored higher than those who began later. Conclusions: Rapid weight loss is highly prevalent in judo competitors. The level of aggressiveness in weight management behaviors seems to not be influenced by the gender or by the weight class, but it seems to be influenced by competitive level and by the age at which athletes began cutting weight.

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Estimation of Taylor`s power law for species abundance data may be performed by linear regression of the log empirical variances on the log means, but this method suffers from a problem of bias for sparse data. We show that the bias may be reduced by using a bias-corrected Pearson estimating function. Furthermore, we investigate a more general regression model allowing for site-specific covariates. This method may be efficiently implemented using a Newton scoring algorithm, with standard errors calculated from the inverse Godambe information matrix. The method is applied to a set of biomass data for benthic macrofauna from two Danish estuaries. (C) 2011 Elsevier B.V. All rights reserved.

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We model and calibrate the arguments in favor and against short-term and long-term debt. These arguments broadly include: maturity premium, sustainability, and service smoothing. We use a dynamic-equilibrium model with tax distortions and government outlays uncertainty, and model maturity as the fraction of debt that needs to be rolled over every period. In the model, the benefits of defaulting are tempered by higher future interest rates. We then calibrate our artificial economy and solve for the optimal debt maturity for Brazil as an example of a developing country and the US as an example of a mature economy. We obtain that the calibrated costs from defaulting on long-term debt more than offset costs associated with short-term debt. Therefore, short-term debt implies higher welfare levels.

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Most models currently used to determine optimal foreign reserve holdings take the level of international debt as given. However, given the sovereign`s willingness-to-pay incentive problems, reserve accumulation may reduce sustainable debt levels. In addition, assuming constant debt levels does not allow addressing one of the puzzles behind using reserves as a means to avoid the negative effects of crisis: why do not sovereign countries reduce their sovereign debt instead? To study the joint decision of holding sovereign debt and reserves, we construct a stochastic dynamic equilibrium model calibrated to a sample of emerging markets. We obtain that the reserve accumulation does not play a quantitatively important role in this model. In fact, we find the optimal policy is not to hold reserves at all. This finding is robust to considering interest rate shocks, sudden stops, contingent reserves and reserve dependent output costs. (c) 2008 Elsevier B.V. All rights reserved.

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The main arguments in favor and against nominal and indexed debts are the incentive to default through inflation versus hedging against unforeseen shocks. We model and calibrate these arguments to assess their quantitative importance. We use a dynamic equilibrium model with tax distortion, government outlays uncertainty, and contingent-debt service. Our framework also recognizes that contingent debt can be associated with incentive problems and lack of commitment. Thus, the benefits of unexpected inflation are tempered by higher interest rates. We obtain that costs from inflation more than offset the benefits from reducing tax distortions. We further discuss sustainability of nominal debt in developing (volatile) countries. (C) 2010 Elsevier Ltd. All rights reserved.

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We formulated a general unrestricted model of the Brazilian Emerging Markets Bond Index Plus (EMBI+) spreads, a proxy for the country`s default risk. Employing algorithms that perform automated model selection, we found that macroeconomic fundamentals, such as current account deficit ratio to gross domestic product, public deficit ratio to gross domestic product and imports over foreign exchange reserves, can explain a great part of the variation in EMBI+ spreads. There is also robust evidence of systematic contagion from Argentina and Mexico and that the variance of the spread also affects its mean.

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Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.

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Objective: The purpose of this study was to investigate regional structural abnormalities in the brains of five patients with refractory obsessive-compulsive disorder (OCD) submitted to gamma ventral capsulotomy. Methods: We acquired morphometric magnetic resonance imaging (MRI) data before and after 1 year of radiosurgery using a 1.5-T MRI scanner. Images were spatially normalized and segmented using optimized voxel-based morphometry (VBM) methods. Voxelwise statistical comparisons between pre- and post-surgery MRI scans were performed using a general linear model. Findings in regions predicted a priori to show volumetric changes (orbitofrontal cortex, anterior cingulate gyrus, basal ganglia and thalamus) were reported as significant if surpassing a statistical threshold of p<0.001 (uncorrected for multiple comparisons). Results: We detected a significant regional postoperative increase in gray matter volume in the right inferior frontal gyri (Brodmann area 47, BA47) when comparing all patients pre and postoperatively. Conclusions: Our results support the current theory of frontal-striatal-thalamic-cortical (FSTC) circuitry involvement in OCD pathogenesis. Gamma ventral capsulotomy is associated with neurobiological changes in the inferior orbitofrontal cortex in refractory OCD patients. (C) 2008 Elsevier Ireland Ltd. All rights reserved.

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Although abnonnalities in brain structures involved in the neurobiology of fear and anxiety have been implicated in the pathophysiology of panic disorder (PD), relatively few studies have made use of voxel-based morphometry (VBM) magnetic resonance imaging (MRI) to determine structural brain abnormalities in PD. We have assessed gray matter volume in 19 PD patients and 20 healthy volunteers using VBM. Images were acquired using a 1.5 T MRI scanner, and were spatially normalized and segmented using optimized VBM. Statistical comparisons were performed using the general linear model. A relative increase in gay matter volume was found in the left insula of PD patients compared with controls. Additional structures showing differential increases were the left superior temporal gyrus, the midbrain, and the pons. A relative gray matter deficit was found in the right anterior cingulate cortex. The insula and anterior cingulate abnormalities may be relevant to the pathophysiology of PD, since these structures participate in the evaluation process that ascribes negative emotional meaning to potentially distressing cognitive and interoceptive sensory information. The abnormal brain stem structures may be involved in the generation of panic attacks. (C) 2007 Elsevier Ireland Ltd. All rights reserved.

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Background. Foot deformities have been related to diabetic neuropathy progression but their influence on plantar distribution during dynamic tasks is not completely understood. The purpose of the present study was to investigate the influence of metatarsal head prominence and claw toes on regional plantar pressures during gait in patients with diabetic neuropathy Methods Seventy-one adults participated in this study categorized into three groups: a control group (CG, n = 32), patients with diabetic neuropathy without any foot deformities (DG, n = 20), and patients with diabetic neuropathy with metatarsal head prominence and/or claw toes (DMHG, n = 19). Plantar pressure variables (contact area, peak pressure, and maximum mean pressure) were evaluated during gait on rearfoot, midfoot, and forefoot using capacitive insoles (Pedar-X System, Novel Inc., Munich, Germany). A general linear model was applied to repeatedly measure and analyze variance relationships between groups and areas. Results. DMHG. presented larger contact areas at the forefoot and midfoot along with higher peak pressure at the rearfoot compared to the other two groups The DG showed higher mean pressure at the midfoot compared to:the other two groups. Conclusion. The coexistence of diabetic neuropathy and metatarsal head prominence in addition to claw toes, resulted in overloading the rearfoot and enhancing the contact area of forefoot and midfoot while walking. This plantar pressure distribution is a result of a different coordination pattern adopted in order to reduce plantar loads at the anterior parts of the foot that were structurally altered. Patients with diabetic neuropathy without any forefoot deformities presented a different plantar pressure distribution than patients with deformities suggesting that both neuropathy and structural foot alterations can influence foot rollover mechanisms.

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Background: The purpose of this study was to investigate the ankle range of motion during neuropathic gait and its influence on plantar pressure distribution in two phases during stance: at heel-strike and at push-off. Methods: Thirty-one adults participated in this study (control group, n = 16; diabetic neuropathic group, n = 15). Dynamic ankle range of motion (electrogoniometer) and plantar pressures (PEDAR-X system) were acquired synchronously during walking. Plantar pressures were evaluated at rearfoot. midfoot and forefoot during the two phases of stance. General linear model repeated measures analysis of variance was applied to investigate relationships between groups, areas and stance phases. Findings: Diabetic neuropathy patients walked using a smaller ankle range of motion in stance phase and smaller ankle flexion at heel-strike (P = 0.0005). Peak pressure and pressure-time integral values were higher in the diabetic group in the midfoot at push-off phase when compared to heel-strike phase. On the other hand, the control group showed similar values of peak pressure in midfoot during both stance phases. Interpretation: The ankle mobility reduction observed could be associated to altered plantar pressure distribution observed in neuropathic subjects. Results demonstrated that midfoot and forefoot play a different role in subjects with neuropathy by receiving higher loads at push-off phase that are probably due to smaller ankle flexion at stance phase. This may explain the higher loads in anterior areas of the foot observed in diabetic neuropathy subjects and confirm an inadequate foot rollover associated to the smaller ankle range of motion at the heel-strike phase. (C) 2009 Elsevier Ltd. All rights reserved.

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Functional MRI (fMRI) data often have low signal-to-noise-ratio (SNR) and are contaminated by strong interference from other physiological sources. A promising tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). BSS is based on the assumption that the detected signals are a mixture of a number of independent source signals that are linearly combined via an unknown mixing matrix. BSS seeks to determine the mixing matrix to recover the source signals based on principles of statistical independence. In most cases, extraction of all sources is unnecessary; instead, a priori information can be applied to extract only the signal of interest. Herein we propose an algorithm based on a variation of ICA, called Dependent Component Analysis (DCA), where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We applied such method to inspect functional Magnetic Resonance Imaging (fMRI) data, aiming to find the hemodynamic response that follows neuronal activation from an auditory stimulation, in human subjects. The method localized a significant signal modulation in cortical regions corresponding to the primary auditory cortex. The results obtained by DCA were also compared to those of the General Linear Model (GLM), which is the most widely used method to analyze fMRI datasets.

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Background and Purpose-Functional MRI is a powerful tool to investigate recovery of brain function in patients with stroke. An inherent assumption in functional MRI data analysis is that the blood oxygenation level-dependent (BOLD) signal is stable over the course of the examination. In this study, we evaluated the validity of such assumption in patients with chronic stroke. Methods-Fifteen patients performed a simple motor task with repeated epochs using the paretic and the unaffected hand in separate runs. The corresponding BOLD signal time courses were extracted from the primary and supplementary motor areas of both hemispheres. Statistical maps were obtained by the conventional General Linear Model and by a parametric General Linear Model. Results-Stable BOLD amplitude was observed when the task was executed with the unaffected hand. Conversely, the BOLD signal amplitude in both primary and supplementary motor areas was progressively attenuated in every patient when the task was executed with the paretic hand. The conventional General Linear Model analysis failed to detect brain activation during movement of the paretic hand. However, the proposed parametric General Linear Model corrected the misdetection problem and showed robust activation in both primary and supplementary motor areas. Conclusions-The use of data analysis tools that are built on the premise of a stable BOLD signal may lead to misdetection of functional regions and underestimation of brain activity in patients with stroke. The present data urge the use of caution when relying on the BOLD response as a marker of brain reorganization in patients with stroke. (Stroke. 2010; 41:1921-1926.)