963 resultados para variance and coherence
Resumo:
This thesis estimates long-run time variant conditional correlation between stock and bond returns of CIVETS (Colombia, Indonesia, Vietnam, Egypt, Turkey, and South Africa) nations. Further, aims to analyse the presence of asymmetric volatility effect in both asset returns, as well as, obverses increment or decrement in conditional correlation during pre-crisis and crisis period, which lead to make a reliable diversification decision. The Constant Conditional Correlation (CCC) GARCH model of Bollerslev (1990), the Dynamic Conditional Correlation (DCC) GARCH model (Engle 2002), and the Asymmetric Dynamic Conditional Correlation (ADCC) GARCH model of Cappiello, Engle, and Sheppard (2006) were implemented in the study. The analyses present strong evidence of time-varying conditional correlation in CIVETS markets, excluding Vietnam, during 2005-2013. In addition, negative innovation effects were found in both conditional variance and correlation of the asset returns. The results of this study recommend investors to include financial assets from these markets in portfolios, in order to obtain better stock-bond diversification benefits, especially during high volatility periods.
Resumo:
The autonomic nervous system plays an important role in physiological and pathological conditions, and has been extensively evaluated by parametric and non-parametric spectral analysis. To compare the results obtained with fast Fourier transform (FFT) and the autoregressive (AR) method, we performed a comprehensive comparative study using data from humans and rats during pharmacological blockade (in rats), a postural test (in humans), and in the hypertensive state (in both humans and rats). Although postural hypotension in humans induced an increase in normalized low-frequency (LFnu) of systolic blood pressure, the increase in the ratio was detected only by AR. In rats, AR and FFT analysis did not agree for LFnu and high frequency (HFnu) under basal conditions and after vagal blockade. The increase in the LF/HF ratio of the pulse interval, induced by methylatropine, was detected only by FFT. In hypertensive patients, changes in LF and HF for systolic blood pressure were observed only by AR; FFT was able to detect the reduction in both blood pressure variance and total power. In hypertensive rats, AR presented different values of variance and total power for systolic blood pressure. Moreover, AR and FFT presented discordant results for LF, LFnu, HF, LF/HF ratio, and total power for pulse interval. We provide evidence for disagreement in 23% of the indices of blood pressure and heart rate variability in humans and 67% discordance in rats when these variables are evaluated by AR and FFT under physiological and pathological conditions. The overall disagreement between AR and FFT in this study was 43%.
Resumo:
The striatum, the largest component of the basal ganglia, is usually subdivided into associative, motor and limbic components. However, the electrophysiological interactions between these three subsystems during behavior remain largely unknown. We hypothesized that the striatum might be particularly active during exploratory behavior, which is presumably associated with increased attention. We investigated the modulation of local field potentials (LFPs) in the striatum during attentive wakefulness in freely moving rats. To this end, we implanted microelectrodes into different parts of the striatum of Wistar rats, as well as into the motor, associative and limbic cortices. We then used electromyograms to identify motor activity and analyzed the instantaneous frequency, power spectra and partial directed coherence during exploratory behavior. We observed fine modulation in the theta frequency range of striatal LFPs in 92.5 ± 2.5% of all epochs of exploratory behavior. Concomitantly, the theta power spectrum increased in all striatal channels (P < 0.001), and coherence analysis revealed strong connectivity (coefficients >0.7) between the primary motor cortex and the rostral part of the caudatoputamen nucleus, as well as among all striatal channels (P < 0.001). Conclusively, we observed a pattern of strong theta band activation in the entire striatum during attentive wakefulness, as well as a strong coherence between the motor cortex and the entire striatum. We suggest that this activation reflects the integration of motor, cognitive and limbic systems during attentive wakefulness.
Resumo:
The present study aimed to study the effects of exercise training (ET) performed by rats on a 10-week high-fructose diet on metabolic, hemodynamic, and autonomic changes, as well as intraocular pressure (IOP). Male Wistar rats receiving fructose overload in drinking water (100 g/L) were concomitantly trained on a treadmill for 10 weeks (FT group) or kept sedentary (F group), and a control group (C) was kept in normal laboratory conditions. The metabolic evaluation comprised the Lee index, glycemia, and insulin tolerance test (KITT). Arterial pressure (AP) was measured directly, and systolic AP variability was performed to determine peripheral autonomic modulation. ET attenuated impaired metabolic parameters, AP, IOP, and ocular perfusion pressure (OPP) induced by fructose overload (FT vs F). The increase in peripheral sympathetic modulation in F rats, demonstrated by systolic AP variance and low frequency (LF) band (F: 37±2, 6.6±0.3 vs C: 26±3, 3.6±0.5 mmHg2), was prevented by ET (FT: 29±3, 3.4±0.7 mmHg2). Positive correlations were found between the LF band and right IOP (r=0.57, P=0.01) and left IOP (r=0.64, P=0.003). Negative correlations were noted between KITT values and right IOP (r=-0.55, P=0.01) and left IOP (r=-0.62, P=0.005). ET in rats effectively prevented metabolic abnormalities and AP and IOP increases promoted by a high-fructose diet. In addition, ocular benefits triggered by exercise training were associated with peripheral autonomic improvement.
Resumo:
Association studies of genetic variants and obesity and/or obesity-related risk factors have yielded contradictory results. The aim of the present study was to determine the possible association of five single-nucleotide polymorphisms (SNPs) located in the IGF2, LEPR, POMC, PPARG, and PPARGC1genes with obesity or obesity-related risk phenotypes. This case-control study assessed overweight (n=192) and normal-weight (n=211) children and adolescents. The SNPs were analyzed using minisequencing assays, and variables and genotype distributions between the groups were compared using one-way analysis of variance and Pearson's chi-square or Fisher's exact tests. Logistic regression analysis adjusted for age and gender was used to calculate the odds ratios (ORs) for selected phenotype risks in each group. No difference in SNP distribution was observed between groups. In children, POMC rs28932472(C) was associated with lower diastolic blood pressure (P=0.001), higher low-density lipoprotein (LDL) cholesterol (P=0.014), and higher risk in overweight children of altered total cholesterol (OR=7.35, P=0.006). In adolescents, IGF2 rs680(A) was associated with higher glucose (P=0.012) and higher risk in overweight adolescents for altered insulin (OR=10.08, P=0.005) and homeostasis model of insulin resistance (HOMA-IR) (OR=6.34, P=0.010). PPARGrs1801282(G) conferred a higher risk of altered insulin (OR=12.31, P=0.003), and HOMA-IR (OR=7.47, P=0.005) in overweight adolescents. PARGC1 rs8192678(A) was associated with higher triacylglycerols (P=0.005), and LEPR rs1137101(A) was marginally associated with higher LDL cholesterol (P=0.017). LEPR rs1137101(A) conferred higher risk for altered insulin, and HOMA-IR in overweight adolescents. The associations observed in this population suggested increased risk for cardiovascular diseases and/or type 2 diabetes later in life for individuals carrying these alleles.
Resumo:
The objective of this work was to develop a recommendation for the chemical peeling of pequi fruit and characterize the flour obtained from the external mesocarp of "Pequizeiro", pequi tree (Caryocar brasiliense Camb.). The technology applied to obtain the external mesocarp pequi flour included the epicarp removal with NaOH solution. The Response Surface Method was used to optimize the chemical peeling process by applying the Central Composite Rotatable Design, with eleven trials including three replicates at the central point, varying the NaOH aqueous solution concentration and fruit immersion time. The mass loss was evaluated through the analysis of variance and using bi and three dimensional graphs. The chemical characteristics of the external mesocarp pequi flour evaluated were: moisture content, ashes, proteins, lipids, total carbohydrates, dietary fiber, and some minerals. The best combination for an efficient removal of the fruit peel with the lowest mass loss was reached with 7.05 minutes of immersion in a 5.08 g.L-1 NaOH aqueous solution. This study indicated that the external mesocarp pequi flour is a food source rich in dietary fiber, carbohydrates, ashes, magnesium, calcium, manganese, and copper, but it is poor in lipids, zinc, and iron.
Resumo:
The Finnish healthcare industry is currently facing significant challenges due to economic crises, aging population and major structural reforms, which have resulted in decreased job satisfaction and increased levels of turnover. This proposes that healthcare organizations need to come up with new, creative means to tackle these issues. Several researchers have argued that corporate entrepreneurship may be the necessary means to achieve this. As previous research has mainly focused on examining this concept from organizational perspective, this study looks at how it occurs on the level of individual employees. The purpose of this study is to examine how corporate entrepreneurship is manifested in individual behavior, and how this type of behavior is associated with the individual’s job satisfaction and turnover intention. Additionally, this study will examine the differences in corporate entrepreneurial behavior between private and public sector organizations, as previous research suggests that these two may be characterized differently. Data was collected with the help of a literature review as well as a survey study, which was sent out to a number of employees of four different healthcare organizations, out of which three were public and one was a private sector organization. Six distinct behavioral characteristics were recognized in previous research, which make up the measure for corporate entrepreneurial behavior. Principal components were formed from the different areas of the survey (corporate entrepreneurial behavior, job satisfaction, turnover intention), after which the association of these components were examined with linear regression analysis, which proved that corporate entrepreneurial behavior is positively correlated with both job satisfaction and intention to leave the organization. Differences between sectors were analyzed with analysis of variance and cross tabulation analysis, but neither of these suggested that any significant differences would occur. These results suggest that employees who behave entrepreneurially tend to be more satisfied with their jobs, but also consider leaving their current organizations more often than others. This may be due to the fact that healthcare organizations are not fertile for entrepreneurial behavior, which will drive entrepreneurial individuals looking for employers who may be more supportive of this type of behavior. With growing levels of dissatisfaction as well as little room for entrepreneurial behavior, the studied organizations may actually be in the process of losing those employees who have the ability and desire to behave in such manner, and who could very well be those who will eventually come up with solutions for the major challenges that these organizations are facing.
Resumo:
The GARCH and Stochastic Volatility paradigms are often brought into conflict as two competitive views of the appropriate conditional variance concept : conditional variance given past values of the same series or conditional variance given a larger past information (including possibly unobservable state variables). The main thesis of this paper is that, since in general the econometrician has no idea about something like a structural level of disaggregation, a well-written volatility model should be specified in such a way that one is always allowed to reduce the information set without invalidating the model. To this respect, the debate between observable past information (in the GARCH spirit) versus unobservable conditioning information (in the state-space spirit) is irrelevant. In this paper, we stress a square-root autoregressive stochastic volatility (SR-SARV) model which remains true to the GARCH paradigm of ARMA dynamics for squared innovations but weakens the GARCH structure in order to obtain required robustness properties with respect to various kinds of aggregation. It is shown that the lack of robustness of the usual GARCH setting is due to two very restrictive assumptions : perfect linear correlation between squared innovations and conditional variance on the one hand and linear relationship between the conditional variance of the future conditional variance and the squared conditional variance on the other hand. By relaxing these assumptions, thanks to a state-space setting, we obtain aggregation results without renouncing to the conditional variance concept (and related leverage effects), as it is the case for the recently suggested weak GARCH model which gets aggregation results by replacing conditional expectations by linear projections on symmetric past innovations. Moreover, unlike the weak GARCH literature, we are able to define multivariate models, including higher order dynamics and risk premiums (in the spirit of GARCH (p,p) and GARCH in mean) and to derive conditional moment restrictions well suited for statistical inference. Finally, we are able to characterize the exact relationships between our SR-SARV models (including higher order dynamics, leverage effect and in-mean effect), usual GARCH models and continuous time stochastic volatility models, so that previous results about aggregation of weak GARCH and continuous time GARCH modeling can be recovered in our framework.
Resumo:
To identify the causes of population decline in migratory birds, researchers must determine the relative influence of environmental changes on population dynamics while the birds are on breeding grounds, wintering grounds, and en route between the two. This is problematic when the wintering areas of specific populations are unknown. Here, we first identified the putative wintering areas of Common House-Martin (Delichon urbicum) and Common Swift (Apus apus) populations breeding in northern Italy as those areas, within the wintering ranges of these species, where the winter Normalized Difference Vegetation Index (NDVI), which may affect winter survival, best predicted annual variation in population indices observed in the breeding grounds in 1992–2009. In these analyses, we controlled for the potentially confounding effects of rainfall in the breeding grounds during the previous year, which may affect reproductive success; the North Atlantic Oscillation Index (NAO), which may account for climatic conditions faced by birds during migration; and the linear and squared term of year, which account for nonlinear population trends. The areas thus identified ranged from Guinea to Nigeria for the Common House-Martin, and were located in southern Ghana for the Common Swift. We then regressed annual population indices on mean NDVI values in the putative wintering areas and on the other variables, and used Bayesian model averaging (BMA) and hierarchical partitioning (HP) of variance to assess their relative contribution to population dynamics. We re-ran all the analyses using NDVI values at different spatial scales, and consistently found that our population of Common House-Martin was primarily affected by spring rainfall (43%–47.7% explained variance) and NDVI (24%–26.9%), while the Common Swift population was primarily affected by the NDVI (22.7%–34.8%). Although these results must be further validated, currently they are the only hypotheses about the wintering grounds of the Italian populations of these species, as no Common House-Martin and Common Swift ringed in Italy have been recovered in their wintering ranges.
Resumo:
The soil-plant transfer factors for Cs and Sr were analyzed in relationship to soil properties, crops, and varieties of crops. Two crops and two varieties of each crop: lettuce (Lactuca sativa L.), cv. Salad Bowl Green and cv. Lobjoits Green Cos, and radish (Raphanus sativus L.), cv. French Breakfast 3 and cv. Scarlet Globe, were grown on five different soils amended with Cs and Sr to give concentrations of 1 mg kg(-1) and 50 mg kg(-1) of each element. Soil-plant transfer coefficients ranged between 0.12-19.10 (Cs) and 1.48-146.10 (Sr) for lettuce and 0.09-13.24 (Cs) and 2.99-93.00 (Sr) for radish. Uptake of Cs and Sr by plants depended on both plant and soil properties. There were significant (P less than or equal to 0.05) differences between soil-plant transfer factors for each plant type at the two soil concentrations. At each soil concentration about 60% of the variance in the uptake of the Cs and Sr was due to soil properties. For a given concentration of Cs or Sr in soil, the most important factor effecting soil-plant transfer of these elements was the soil properties rather than the crops or varieties of crops. Therefore, for the varieties considered here, soil-plant transfer of Cs and Sr would be best regulated through the management of soil properties. At each concentration of Cs and Sr, the main soil properties effecting the uptake of Cs and Sr by lettuce and radish were the concentrations of K and Ca, pH and CEC. Together with the concentrations of contaminants in soils, they explained about 80% of total data variance, and were the best predictors for soil-plant transfer. The different varieties of lettuce and radish gave different responses in soil-plant transfer of Cs and Sr in different soil conditions, i.e. genotype x environment interaction caused about 30% of the variability in the uptake of Cs and Sr by plants. This means that a plant variety with a low soil-plant transfer of Cs and Sr in one soil could have an increased soil-plant transfer factor in other soils. The broad implications of this work are that in contaminated agricultural lands still used for plant growing, contaminant-excluding crop varieties may not be a reliable method for decreasing contaminant transfer to foodstuffs. Modification of soil properties would be a more reliable technique. This is particularly relevant to agricultural soils in the former USSR still affected by fallout from the Chernobyl disaster.
Resumo:
Some commonly experienced signs and symptoms occur during abstinence from tobacco, but specific signs and symptoms and their intensity vary greatly from individual to individual. The aim of this study was to re-examine psychological and psychomotor symptoms in smokers in the general population, and to explore the individual variation in these. Quitting smokers (n = 123) reported their experiences pre- and post-cessation, on a questionnaire developed for the study. Analysis of variance and frequency analysis showed significant decreases between pre- and post-cessation on positive experiences (F = 9.81, p < 0.0001) but no significant change on negative experiences, suggesting a loss of pleasure rather than increased negative affect upon quitting. The variance of the pre- to post-cessation difference score suggested wide variation in the reporting of withdrawal symptoms. These results lead us to consider the implications for treatment, using cognitive therapies and moderating the significant emphasis that is at present put on withdrawal.
Resumo:
The relationship between minimum variance and minimum expected quadratic loss feedback controllers for linear univariate discrete-time stochastic systems is reviewed by taking the approach used by Caines. It is shown how the two methods can be regarded as providing identical control actions as long as a noise-free measurement state-space model is employed.
Resumo:
A common problem in many data based modelling algorithms such as associative memory networks is the problem of the curse of dimensionality. In this paper, a new two-stage neurofuzzy system design and construction algorithm (NeuDeC) for nonlinear dynamical processes is introduced to effectively tackle this problem. A new simple preprocessing method is initially derived and applied to reduce the rule base, followed by a fine model detection process based on the reduced rule set by using forward orthogonal least squares model structure detection. In both stages, new A-optimality experimental design-based criteria we used. In the preprocessing stage, a lower bound of the A-optimality design criterion is derived and applied as a subset selection metric, but in the later stage, the A-optimality design criterion is incorporated into a new composite cost function that minimises model prediction error as well as penalises the model parameter variance. The utilisation of NeuDeC leads to unbiased model parameters with low parameter variance and the additional benefit of a parsimonious model structure. Numerical examples are included to demonstrate the effectiveness of this new modelling approach for high dimensional inputs.
Resumo:
The internal variability and coupling between the stratosphere and troposphere in CCMVal‐2 chemistry‐climate models are evaluated through analysis of the annular mode patterns of variability. Computation of the annular modes in long data sets with secular trends requires refinement of the standard definition of the annular mode, and a more robust procedure that allows for slowly varying trends is established and verified. The spatial and temporal structure of the models’ annular modes is then compared with that of reanalyses. As a whole, the models capture the key features of observed intraseasonal variability, including the sharp vertical gradients in structure between stratosphere and troposphere, the asymmetries in the seasonal cycle between the Northern and Southern hemispheres, and the coupling between the polar stratospheric vortices and tropospheric midlatitude jets. It is also found that the annular mode variability changes little in time throughout simulations of the 21st century. There are, however, both common biases and significant differences in performance in the models. In the troposphere, the annular mode in models is generally too persistent, particularly in the Southern Hemisphere summer, a bias similar to that found in CMIP3 coupled climate models. In the stratosphere, the periods of peak variance and coupling with the troposphere are delayed by about a month in both hemispheres. The relationship between increased variability of the stratosphere and increased persistence in the troposphere suggests that some tropospheric biases may be related to stratospheric biases and that a well‐simulated stratosphere can improve simulation of tropospheric intraseasonal variability.
Resumo:
Temperature and precipitation are major forcing factors influencing grapevine phenology and yield, as well as wine quality. Bioclimatic indices describing the suitability of a particular region for wine production are a commonly used tool for viticultural zoning. For this research these indices were computed for Europe by using the E-OBS gridded daily temperature and precipitation data set for the period from 1950 to 2009. Results showed strong regional contrasts based on the different index patterns and reproduced the wide diversity of local conditions that largely explain the quality and diversity of grapevines being grown across Europe. Owing to the strong inter-annual variability in the indices, a trend analysis and a principal component analysis were applied together with an assessment of their mean patterns. Significant trends were identified in the Winkler and Huglin indices, particularly for southwestern Europe. Four statistically significant orthogonal modes of variability were isolated for the Huglin index (HI), jointly representing 82% of the total variance in Europe. The leading mode was largely dominant (48% of variance) and mainly reflected the observed historical long-term changes. The other 3 modes corresponded to regional dipoles within Europe. Despite the relevance of local and regional climatic characteristics to grapevines, it was demonstrated via canonical correlation analysis that the observed inter-annual variability of the HI was strongly controlled by the large-scale atmospheric circulation during the growing season (April to September).