996 resultados para Seasonality effects
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Este artigo investiga versões do modelo de passeio aleatório dos preços de ativos em diversos horizontes de tempo, para carteiras diversificadas de ações no mercado brasileiro. Evidências contrárias a tal modelo são observadas nos horizontes diário e semanal, caracterizados por persistência. As evidências são mais fracas em períodos mais recentes. Encontramos também sazonalidades diárias, incluindo o efeito segunda-feira, e mensais. Adicionalmente, um padrão de assimetria de autocorrelações cruzadas de primeira ordem entre os retornos de carteiras de firmas agrupadas segundo seu tamanho também é observado, indicando no caso de retornos diários e semanais que retornos de firmas grandes ajudam a prever retornos de firmas pequenas. Evidências de não linearidades nos retornos são observadas em diversos horizontes de tempo.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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The oxygen isotopic composition of precipitation (δ18Oprec) is well known to be a valuable (paleo-)climate proxy. Paleosols and sediments and hemicelluloses therein have the potential to serve as archives recording the isotopic composition of paleoprecipitation. In a companion paper (Zech et al., 2014) we investigated δ18Ohemicellulose values of plants grown under different climatic conditions in a climate chamber experiment. Here we present results of compound-specific δ18O analyses of arabinose, fucose and xylose extracted from modern topsoils (n = 56) along a large humid-arid climate transect in Argentina in order to answer the question whether hemicellulose biomarkers in soils reflect δ18Oprec. The results from the field replications indicate that the homogeneity of topsoils with regard to δ18Ohemicellulose is very high for most of the 20 sampling sites. Standard deviations for the field replications are 1.5‰, 2.2‰ and 1.7‰, for arabinose, fucose and xylose, respectively. Furthermore, all three hemicellulose biomarkers reveal systematic and similar trends along the climate gradient. However, the δ18Ohemicellulose values (mean of the three sugars) do not correlate positively with δ18Oprec (r = −0.54, p < 0.014, n = 20). By using a Péclet-modified Craig-Gordon (PMCG) model it can be shown that the δ18Ohemicellulose values correlate highly significantly with modeled δ18Oleaf water values (r = 0.81, p < 0.001, n = 20). This finding suggests that hemicellulose biomarkers in (paleo-)soils do not simply reflect δ18Oprec but rather δ18Oprec altered by evaporative 18O enrichment of leaf water due to evapotranspiration. According to the modeling results, evaporative 18O enrichment of leaf water is relatively low (∼10‰) in the humid northern part of the Argentinian transect and much higher (up to 19‰) in the arid middle and southern part of the transect. Model sensitivity tests corroborate that changes in relative air humidity exert a dominant control on evaporative 18O enrichment of leaf water and thus δ18Ohemicellulose, whereas the effect of temperature changes is of minor importance. While oxygen exchange and degradation effects seem to be negligible, further factors needing consideration when interpreting δ18Ohemicellulose values obtained from (paleo-)soils are evaporative 18O enrichment of soil water, seasonality effects, wind effects and in case of abundant stem/root-derived organic matter input a partial loss of the evaporative 18O enrichment of leaf water. Overall, our results prove that compound-specific δ18O analyses of hemicellulose biomarkers in soils and sediments are a promising tool for paleoclimate research. However, disentangling the two major factors influencing δ18Ohemicellulose, namely δ18Oprec and relative air humidity controlled evaporative 18O enrichment of leaf water, is challenging based on δ18O analyses alone.
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This paper examines the evidence for a day-of-the-week effect in five Southeast Asian stock markets: South Korea, Malaysia, the Philippines, Taiwan and Thailand. Findings indicate significant seasonality for three of the five markets. Market risk, proxied by the return on the FTA World Price Index, is not sufficient to explain this calendar anomaly. Although an extension of the risk-return equation to incorporate interactive seasonal dummy variables can explain some significant day-of-the-week effects, market risk alone appears insufficient to characterize this phenomenon.
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ACKNOWLEDGMENTS. We would like to thank Fernando Gonzalez-Dominguez and Gilberto Vaughan for providing the chicken pox case reports from Mexico, and the Estonia Health Board, Department of Communicable Disease Surveillance and Control, for Estonian chicken pox case reports. KB would like to thank Mercedes Pascual, her lab, and Marisa Eisenberg for helpful comments. Jesus Cantu (research assistant, Princeton University) translated and categorized chicken pox searches from Mexico, Thailand, Australia, and the US.
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2016
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We evaluated the ratio between the number of pollen foragers and the total number of bees entering colonies of Melipona bicolor, a facultative polygynous species of stingless bees. The variables considered in our analysis were: seasonality, colony size and the number of physogastric queens in each colony. The pollen forager ratios varied significantly between seasons; the ratio was higher in winter than in summer. However, colony size and number of queens per colony had no significant effect. We conclude that seasonal differences in pollen harvest are related to the production of sexuals and to the number of individuals and their body size.
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The interplay of seasonality, the system's nonlinearities and intrinsic stochasticity, is studied for a seasonally forced susceptible-exposed-infective-recovered stochastic model. The model is explored in the parameter region that corresponds to childhood infectious diseases such as measles. The power spectrum of the stochastic fluctuations around the attractors of the deterministic system that describes the model in the thermodynamic limit is computed analytically and validated by stochastic simulations for large system sizes. Size effects are studied through additional simulations. Other effects such as switching between coexisting attractors induced by stochasticity often mentioned in the literature as playing an important role in the dynamics of childhood infectious diseases are also investigated. The main conclusion is that stochastic amplification, rather than these effects, is the key ingredient to understand the observed incidence patterns.
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OBJECTIVE: Myocardial infarction is an acute and severe cardiovascular disease that generally leads to patient admissions to intensive care units and few cases are initially admitted to infirmaries. The objective of the study was to assess whether estimates of air pollution effects on myocardial infarction morbidity are modified by the source of health information. METHODS: The study was carried out in hospitals of the Brazilian Health System in the city of São Paulo, Southern Brazil. A time series study (1998-1999) was performed using two outcomes: infarction admissions to infirmaries and to intensive care units, both for people older than 64 years of age. Generalized linear models controlling for seasonality (long and short-term trends) and weather were used. The eight-day cumulative effects of air pollutants were assessed using third degree polynomial distributed lag models. RESULTS: Almost 70% of daily hospital admissions due to myocardial infarction were to infirmaries. Despite that, the effects of air pollutants on infarction were higher for intensive care units admissions. All pollutants were positively associated with the study outcomes but SO2 presented the strongest statistically significant association. An interquartile range increase on SO2 concentration was associated with increases of 13% (95% CI: 6-19) and 8% (95% CI: 2-13) of intensive care units and infirmary infarction admissions, respectively. CONCLUSIONS: It may be assumed there is a misclassification of myocardial infarction admissions to infirmaries leading to overestimation. Also, despite the absolute number of events, admissions to intensive care units data provides a more adequate estimate of the magnitude of air pollution effects on infarction admissions.
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OBJECTIVE: Studies conducted mainly in countries located in the Northern Hemisphere have shown that season of birth influences mood seasonality. Greater mood seasonality has been observed for individuals born during spring/summer months than those born during autumn/winter months. Expanding past research to the Southern Hemisphere, in this study we examine the influence of season of birth on mood seasonality in a sample of 1,247 healthy young Brazilians. METHOD: The Seasonal Pattern Assessment Questionnaire was used to compute a global seasonality score as a measure of mood seasonality in a cross-sectional study. RESULTS: Analysis of covariance was conducted to examine the effects of month of birth and gender on mood seasonality, with age entered as a covariate. A main effect of gender was observed, F (1, 1197) = 17.86, p < .01; partial Eta-squared = .02, with mood seasonality being higher for females (M = 8) than for males (M = 7). Contradicting previous findings, no significant main effect for month of birth was observed, F (1, 1197) = 0.65, p > .05. CONCLUSION: The unexpected finding is tentatively explained by differences in geographic location and weather fluctuations between the sampling location in Brazil and other countries where season of birth has been found to influence mood seasonality. Additional studies with larger samples from the Southern Hemisphere are necessary to shed additional light on the possible significant influence of season of birth on mood.
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Time series regression models are especially suitable in epidemiology for evaluating short-term effects of time-varying exposures on health. The problem is that potential for confounding in time series regression is very high. Thus, it is important that trend and seasonality are properly accounted for. Our paper reviews the statistical models commonly used in time-series regression methods, specially allowing for serial correlation, make them potentially useful for selected epidemiological purposes. In particular, we discuss the use of time-series regression for counts using a wide range Generalised Linear Models as well as Generalised Additive Models. In addition, recently critical points in using statistical software for GAM were stressed, and reanalyses of time series data on air pollution and health were performed in order to update already published. Applications are offered through an example on the relationship between asthma emergency admissions and photochemical air pollutants
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Experimental fishing and visual censuses were conducted at nine Posidonia oceanica sites off Minorca exposed to different levels of fishing intensity to assess the effects of recreational fishing on the species that dominate the catch. Total catch per unit effort (CPUE) was highly seasonal and a statistically significant interaction term existed between the season and the level of fishing intensity. CPUE decreased everywhere at the end of the fishing season (autumn), but such a reduction was more intense at those sites exposed to the highest level of fishing. Visual censuses confirmed that there was a lower abundance of vulnerable fish in autumn. Differences vanished in spring probably because fish reshuffled between the considered sites throughout the winter, when the level of fishing intensity was extremely low. Although the average total lengths of Serranus scriba and Diplodus annularis were unaffected by the level of fishing intensity, the average total length of Coris julis was smaller at the most heavily fished sites. In conclusion, recreational fishing has a relevant impact on most of the exploited species and some of the seasonality reported for the Posidonia oceanica fish assemblages might be caused by the seasonality of the fishery.
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In terrestrial snakes, many cases of intraspecific shifts in dietary habits as a function of predator sex and body size are driven by gape-limitation - and hence, are most common in species that feed on relatively large prey, and exhibit a wide body-size range. Our data on seasnakes reveal an alternative mechanism for intraspecific niche partitioning, based on sex-specific seasonal anorexia induced by reproductive activities. Turtle-headed seasnakes (Emydocephalus annulatus) on coral reefs in the New Caledonian Lagoon feed entirely on the eggs of demersal-spawning fishes. DNA sequence data (cytochrome b gene) on eggs that we palpated from stomachs of 37 snakes showed that despite this ontogenetic-stage specialization, the prey come from a taxonomically diverse array of species including damselfish (41% of samples, at least 5 species), blennies (41%, 4 species) and gobies (19%, 5 species). The composition of snake diets shifted seasonally (with damselfish dominating in winter but not summer), presumably reflecting seasonality of fish reproduction. That seasonal shift affects male and female snakes differently, because reproduction is incompatible with foraging. Adult female seasnakes ceased feeding when they became heavily distended with developing embryos in late summer, and males ceased feeding while they were mate-searching in winter. The sex divergence in foraging habits may be amplified by sexual size dimorphism; females grow larger than males, and larger snakes (of both sexes) feed more on damselfish (which often lay their eggs in exposed sites) than on blennies and gobies (whose eggs are hidden within narrow crevices). Specific features of reproductive biology of coral-reef fish (seasonality and nest type) have generated intraspecific niche partitioning in these seasnakes, by mechanisms different from those that apply to terrestrial snakes.
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Most ecosystems undergo substantial variation over the seasons, ranging from changes in abiotic features, such as temperature, light and precipitation, to changes in species abundance and composition. How seasonality varies along latitudinal gradients is not well known in freshwater ecosystems, despite being very important in predicting the effects of climate change and in helping to advance ecological understanding. Stream temperature is often well correlated with air temperature and influences many ecosystem features such as growth and metabolism of most aquatic organisms. We evaluated the degree of seasonality in ten river mouths along a latitudinal gradient for a set of variables, ranging from air and water temperatures, to physical and chemical properties of water and growth of an invasive fish species (eastern mosquitofish, Gambusia holbrooki ). Our results show that although most of the variation in air temperature was explained by latitude and season, this was not the case for water features, including temperature, in lowland Mediterranean streams, which depended less on season and much more on local factors. Similarly, although there was evidence of latitude-dependent seasonality in fish growth, the relationship was nonlinear and weak and the significant latitudinal differences in growth rates observed during winter were compensated later in the year and did not result in overall differences in size and growth. Our results suggest that although latitudinal differences in air temperature cascade through properties of freshwater ecosystems, local factors and complex interactions often override the water temperature variation with latitude and might therefore hinder projections of species distribution models and effects of climate change