265 research outputs found

    Stainless steel plate girders subjected to shear buckling at normal and elevated temperatures

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    The final publication is available at Springer via http://dx.doi.org/10.1007/s10694-016-0602-6Numerical simulations have been widely applied, for the determination of the resistance of steel structural elements, when experimental analysis are not possible (due to cost or size limitations) or when parametric studies with high number of variables are needed. However, the numerical models must be properly validated with experimental tests in order to deliver reliable studies. With the purpose of studying the behaviour of stainless steel plate girders in fire situation, a total of 34 experimental tests from the literature have been numerically modelled. The tested girders had different configurations: rigid and non-rigid end posts, 2 and 4 panels, and transversal and longitudinal stiffeners were considered. Comparative analyses between those experimental and numerical results have been done. Good approximations to the experimental results at normal temperatures have been achieved with differences on average lower than 5%. Afterwards, the developed numerical model has been used to perform a sensitivity analysis on the influence of the initial geometric imperfections at both normal and elevated temperatures, considering different values for its maximum amplitudes, concluding that 10% of the web thickness is an appropriate value for the maximum amplitude of the geometric imperfections when modelling experimental tests. The effect of the residual stresses has also been analysed, being obtained differences lower than 2%. Finally, comparisons between the numerical results and the Eurocode 3 design procedures have been performed considering different uniform elevated temperatures.Peer ReviewedPostprint (author's final draft

    Measuring the vulnerability of the Uruguayan population to vector-borne diseases via spatially hierarchical factor models

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    We propose a model-based vulnerability index of the population from Uruguay to vector-borne diseases. We have available measurements of a set of variables in the census tract level of the 19 Departmental capitals of Uruguay. In particular, we propose an index that combines different sources of information via a set of micro-environmental indicators and geographical location in the country. Our index is based on a new class of spatially hierarchical factor models that explicitly account for the different levels of hierarchy in the country, such as census tracts within the city level, and cities in the country level. We compare our approach with that obtained when data are aggregated in the city level. We show that our proposal outperforms current and standard approaches, which fail to properly account for discrepancies in the region sizes, for example, number of census tracts. We also show that data aggregation can seriously affect the estimation of the cities vulnerability rankings under benchmark models.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS497 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

    One for all : nesting asymmetric stochastic volatility models

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    This paper proposes a new stochastic volatility model to represent the dynamic evolution of conditionally heteroscedastic time series with leverage effect. Although there are already several models proposed in the literature with the same purpose, our main justification for a further new model is that it nests some of the most popular stochastic volatility specifications usually implemented to real time series of financial returns. We derive closed-form expressions of its statistical properties and, consequently, of those of the nested specifications. Some of these properties were previously unknown in the literature although the restricted models are often fitted by empirical researchers. By comparing the properties of the restricted models, we are able to establish the advantages and limitations of each of them. Finally, we analyze the performance of a MCMC estimator of the parameters and volatilities of the new proposed model and show that, if the error distribution is known, it has appropriate finite sample properties. Furthermore, estimating the new model using the MCMC estimator, one can correctly identify the restricted true specifications. All the results are illustrated by estimating the parameters and volatilities of simulated time series and of a series of daily S&P500 returnsFinancial support from the Spanish Ministry of Education and Science, research projects ECO2009-08100 and ECO2012-32401, is acknowledged. The third author is also grateful for project MTM2010-1732

    Numerical modelling of steel plate girders at normal and elevated temperatures

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    The main goal of this study is to increase the knowledge on the behaviour of steel plate girders subjected to shear buckling at both normal and elevated temperatures. Hence, numerical models were duly validated with experimental tests from the literature. Experimental tests on steel plate girders with different configurations were numerically reproduced, showing a good agreement between numerical and experimental results. Afterwards, applying the validated numerical models, sensitivity analyses on the influence of initial imperfections were performed. Different values for the maximum amplitude of geometric imperfections were considered and residual stresses were also taken into account. Finally, the effect of the end supports configuration was also studied aiming to understand the strength enhancement given by the rigid end support at normal temperature and evaluating if that strength enhancement is maintained in case of fire.Peer ReviewedPostprint (author's final draft

    Score driven asymmetric stochastic volatility models

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    In this paper we propose a new class of asymmetric stochastic volatility (SV) models, which specifies the volatility as a function of the score of the distribution of returns conditional on volatilities based on the Generalized Autoregressive Score (GAS) model. Different specifications of the log-volatility are obtained by assuming different return error distributions. In particular, we consider three of the most popular distributions, namely, the Normal, Student-t and Generalized Error Distribution and derive the statistical properties of each of the corresponding score driven SV models. We show that some of the parameters cannot be property identified by the moments usually considered as to describe the stylized facts of financial returns, namely, excess kurtosis, autocorrelations of squares and cross-correlations between returns and future squared returns. The parameters of some restricted score driven SV models can be estimated adequately using a MCMC procedure. Finally, the new proposed models are fitted to financial returns and evaluated in terms of their in-sample and out-of-sample performanceFinancial support from the Spanish Ministry of Education and Science, research project ECO2012-32401, is acknowledged. The third author is also grateful for project MTM2010-1732

    Immune-Endocrine Links to Gregariousness in Wild House Mice

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    Social interactions are critically important for survival and impact overall-health, but also impose costs on animals, such as exposure to contagious agents. The immune system can play a critical role in modulating social behavior when animals are sick, as has been demonstrated within the context of “sickness behaviors.” Can immune molecules affect or be affected by social interactions even when animals are not sick, therefore serving a role in mediating pathogen exposure? We tested whether markers of immune function in both the blood and the brain are associated with gregariousness, quantified as number of animals interacted with per day. To do this, we used remote tracking of social interactions of a wild population of house mice (Mus musculus domesticus) to categorize animals in terms of gregariousness. Blood, hair, brain and other tissue samples from animals with extreme gregariousness phenotypes were collected. We then tested whether the levels of three important cytokines (TNF-a, IFN-g and IL- 1b) in the serum, cortex and hypothalamus of these animals could be explained by the gregariousness phenotype and/or sex of the mice. Using the hair as a long-term quantification of steroid hormones, we also tested whether corticosterone, progesterone and testosterone differed by social phenotype. We found main effects of gregariousness and sex on the serum levels of TNF-a, but not on IFN-g or IL-1b. Brain gene expression levels were not different between phenotypes. All hair steroids tended to be elevated in animals of high gregariousness phenotype, independent of sex. In sum, elements of the immune system may be associated with gregariousness, even outside of major disease events. These results extend our knowledge of the role that immune signals have in contributing to the regulation of social behaviors outside periods of illness

    Threshold stochastic volatility: properties and forecasting

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    We analyze the ability of Threshold Stochastic Volatility (TSV) models to represent and forecast asymmetric volatilities. First, we derive the statistical properties of TSV models. Second, we demonstrate the good finite sample properties of a MCMC estimator, implemented in the software package WinBUGS, when estimating the parameters of a general specification, denoted CTSV, that nests the TSV and asymmetric autoregressive stochastic volatility (A-ARSV) models. The MCMC estimator also discriminates between the two specifications and allows us to obtain volatility forecasts. Third, we analyze daily S&P 500 and FTSE 100 returns and show that the estimated CTSV model implies plug-in moments that are slightly closer to the observed sample moments than those implied by other nested specifications. Furthermore, different asymmetric specifications generate rather different European options prices. Finally, although none of the models clearly emerge as best outof- sample, it seems that including both threshold variables and correlated errors may be a good compromise.We acknowledge financial support from the Spanish Ministry of Economy and Competitiveness, research projects ECO2015-70331-C2-2-R and ECO2015-65701-P, as well as FCT grant UID/GES/00315/2013

    Uncertainty and density forecasts of ARMA models: comparison of asymptotic, bayesian and bootstrap procedures

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    The objective of this paper is to analyze the effects of uncertainty on density forecasts of stationary linear univariate ARMA models. We consider three specific sources of uncertainty: parameter estimation, error distribution, and lag order. Depending on the estimation sample size and the forecast horizon, each of these sources may have different effects. We consider asymptotic, Bayesian, and bootstrap procedures proposed to deal with uncertainty and compare their finite sample properties. The results are illustrated constructing fan charts for UK inflation.We thank the Spanish Government, research projects ECO2015–237033–C2–2–R and ECO2015–65701–P(MINECO/FEDER), for financial suppo

    The Southern European Atlantic Diet and all-cause mortality in older adults

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    The Southern European Atlantic Diet (SEAD) is the traditional diet of Northern Portugal and North-Western Spain. Higher adherence to the SEAD has been associated with lower levels of some cardiovascular risk factors and reduced risk for myocardial infarction, but whether this translates into lower all-cause mortality is uncertain. We hence examined the association between adherence to the SEAD and all-cause mortality in older adults. Methods: Data were taken from the Seniors-ENRICA-1 cohort, which included 3165 individuals representative of the non-institutionalized population aged ≥ 60 years in Spain. Food consumption was assessed with a validated diet history, and adherence to the SEAD was measured with an index comprising 9 food components: fresh fish, cod, red meat and pork products, dairy products, legumes and vegetables, vegetable soup, potatoes, whole-grain bread, and wine. Vital status was ascertained with the National Death Index of Spain. Statistical analyses were performed with Cox regression models and adjusted for the main confounders. Results: During a median follow-up of 10.9 years, 646 deaths occurred. Higher adherence to the SEAD was associated with lower all-cause mortality (fully adjusted hazard ratio [95% confidence interval] per 1-SD increment in the SEAD score 0.86 [0.79, 0.94]; p-trend < 0.001). Most food components of the SEAD showed some tendency to lower all-cause mortality, especially moderate wine consumption (hazard ratio [95% confidence interval] 0.71 [0.59, 0.86]). The results were robust in several sensitivity analyses. The protective association between SEAD and all-cause death was of similar magnitude to that found for the Mediterranean Diet Adherence Screener (hazard ratio [95% confidence interval] per 1-SD increment 0.89 [0.80, 0.98]) and the Alternate Healthy Eating Index (0.83 [0.76, 0.92]). Conclusions: Adherence to the SEAD is associated with a lower risk of all-cause death among older adults in SpainThe present study was supported by Instituto de Salud Carlos III, State Secretary of R+D+I and FEDER/FSE (FIS grants 16/609, 16/1512, 18/287, and 19/319); JPI-A Healthy Diet for a Healthy Life, State Secretary of R+D+I (the Salamander Project, grant number PCIN-2016-145); and the Cátedra de Epidemiología y Control del Riesgo Cardiovascular at UAM (grant number 820024

    Asymmetric stochastic volatility models: properties and particle filter-based simulated maximum likelihood estimation

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    The statistical properties of a general family of asymmetric stochastic volatility (A-SV)models which capture the leverage effect in financial returns are derived providing analyt- ical expressions of moments and autocorrelations of power-transformed absolute returns.The parameters of the A-SV model are estimated by a particle filter-based simulated max- imum likelihood estimator and Monte Carlo simulations are carried out to validate it. Itis shown empirically that standard SV models may significantly underestimate the value- at-risk of weekly S&P 500 returns at dates following negative returns and overestimate itafter positive returns. By contrast, the general specification proposed provide reliable fore- casts at all dates. Furthermore, based on daily S&P 500 returns, it is shown that the mostadequate specification of the asymmetry can change over time.We gratefully acknowledge the financial support from the Spanish Government, contract grants ECO2015-70331-C2-2-R and ECO2015-65701-P (MINECO/FEDER), the computer support from EUROFIDAI, and the FCT grant UID/GES/00315/2013
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