871 resultados para Conditional-value-at-risk assessment


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O objetivo deste estudo é propor a implementação de um modelo estatístico para cálculo da volatilidade, não difundido na literatura brasileira, o modelo de escala local (LSM), apresentando suas vantagens e desvantagens em relação aos modelos habitualmente utilizados para mensuração de risco. Para estimação dos parâmetros serão usadas as cotações diárias do Ibovespa, no período de janeiro de 2009 a dezembro de 2014, e para a aferição da acurácia empírica dos modelos serão realizados testes fora da amostra, comparando os VaR obtidos para o período de janeiro a dezembro de 2014. Foram introduzidas variáveis explicativas na tentativa de aprimorar os modelos e optou-se pelo correspondente americano do Ibovespa, o índice Dow Jones, por ter apresentado propriedades como: alta correlação, causalidade no sentido de Granger, e razão de log-verossimilhança significativa. Uma das inovações do modelo de escala local é não utilizar diretamente a variância, mas sim a sua recíproca, chamada de “precisão” da série, que segue uma espécie de passeio aleatório multiplicativo. O LSM captou todos os fatos estilizados das séries financeiras, e os resultados foram favoráveis a sua utilização, logo, o modelo torna-se uma alternativa de especificação eficiente e parcimoniosa para estimar e prever volatilidade, na medida em que possui apenas um parâmetro a ser estimado, o que representa uma mudança de paradigma em relação aos modelos de heterocedasticidade condicional.

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The purpose of this work is to analyze the parasitological risks of treated wastewater reuse from a stabilization pond in the city of Piracicaba, in the State of Sao Paulo (Brazil), and the level of treatment required to protect public health. Samples were taken from raw and treated wastewater in stabilization ponds and submitted to a parasitological, microbiological and physicochemical analysis. The study revealed on treated wastewater the presence of Ascaris sp. and Entamoeba coli with an average density of 1 cysts L-1 and 6 eggs L-1, respectively. For Ascaris, the annual risks of infection due to the accidental ingestion of wastewater irrigation were 7.5 x 10(-2) in 208 days and 8.7 x 10(-2) in 240 days. For Total Coliforms and Escherichia coli in treated wastewater, the average density was 1.0 x 10(5) MPN/100 ml and 2.7 x 10(4) MPN/100 ml respectively, representing 99% and 94% removal efficiency, respectively. For BOD, COD, TS and TSS removal efficiency was 69, 80, 50 and 71%, respectively. The removal efficiency for nitrogen; ammonia nitrogen and total phosphate was 24, 19 and 68%, respectively. The average density of helminths eggs in treated wastewater is higher compared to the density of the limit value of <= 1 egg L-1 and tolerable risk is above the level recommended by the World Health Organization. Multiple barriers are necessary for the reduction of organic matter, chemical contaminants and parasites from treated wastewater. Standards for the sanitary control of treated wastewater to be reused in agricultural irrigation areas should be compiled for developing countries in order to minimize public health risks.

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Switzerland implemented a risk-based monitoring of Swiss dairy products in 2002 based on a risk assessment (RA) that considered the probability of exceeding a microbiological limit value set by law. A new RA was launched in 2007 to review and further develop the previous assessment, and to make recommendations for future risk-based monitoring according to current risks. The resulting qualitative RA was designed to ascertain the risk to human health from the consumption of Swiss dairy products. The products and microbial hazards to be considered in the RA were determined based on a risk profile. The hazards included Campylobacter spp., Listeria monocytogenes, Salmonella spp., Shiga toxin-producing Escherichia coli, coagulase-positive staphylococci and Staphylococcus aureus enterotoxin. The release assessment considered the prevalence of the hazards in bulk milk samples, the influence of the process parameters on the microorganisms, and the influence of the type of dairy. The exposure assessment was linked to the production volume. An overall probability was estimated combining the probabilities of release and exposure for each combination of hazard, dairy product and type of dairy. This overall probability represents the likelihood of a product from a certain type of dairy exceeding the microbiological limit value and being passed on to the consumer. The consequences could not be fully assessed due to lack of detailed information on the number of disease cases caused by the consumption of dairy products. The results were expressed as a ranking of overall probabilities. Finally, recommendations for the design of the risk-based monitoring programme and for filling the identified data gaps were given. The aims of this work were (i) to present the qualitative RA approach for Swiss dairy products, which could be adapted to other settings and (ii) to discuss the opportunities and limitations of the qualitative method.

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Whole-body vibration exposure of locomotive engineers and the vibration attenuation of seats in 22 U.S. locomotives (built between 1959 and 2000) was studied during normal revenue service and following international measurement guidelines. Triaxial vibration measurements (duration mean 155 min, range 84-383 min) on the seat and on the floor were compared. In addition to the basic vibration evaluation (aw rms), the vector sum (av), the maximum transient vibration value (MTVV/aw), the vibration dose value (VDV/(aw T1/4)), and the vibration seat effective transmissibility factor (SEAT) were calculated. The power spectral densities are also reported. The mean basic vibration level (aw rms) was for the fore-aft axis x = 0.18 m/sec2, the lateral axis y = 0.28 m/sec2, and the vertical axis z = 0.32 m/sec2. The mean vector sum was 0.59 m/sec2 (range 0.27 to 1.44). The crest factors were generally at or above 9 in the horizontal and vertical axis. The mean MTVV/aw was 5.3 (x), 5.1 (y), and 4.8 (z), and the VDV/(aw T1/4) values ranged from 1.32 to 2.3 (x-axis), 1.33 to 1.7 (y-axis), and 1.38 to 1.86 (z-axis), generally indicating high levels of shocks. The mean seat transmissibility factor (SEAT) was 1.4 (x) and 1.2 (y) and 1 (z), demonstrating a general ineffectiveness of any of the seat suspension systems. In conclusion, these data indicate that locomotive rides are characterized by relatively high shock content (acceleration peaks) of the vibration signal in all directions. Locomotive vertical and lateral vibrations are similar, which appears to be characteristic for rail vehicles compared with many road/off-road vehicles. Tested locomotive cab seats currently in use (new or old) appear inadequate to reduce potentially harmful vibration and shocks transmitted to the seated operator, and older seats particularly lack basic ergonomic features regarding adjustability and postural support.

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We report the concentrations of 28 PAHs, 15 oxygenated PAHs (OPAHs) and 11 trace metals/metalloids (As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Se, and Zn) in muscle and gut + gill tissues of demersal fishes (Drapane africana, Cynoglossus senegalensis and Pomadasys peroteti) from three locations along the coast of the Gulf of Guinea (Ghana). The concentrations of ∑ 28PAHs in muscle tissues averaged 192 ng g− 1 dw (range: 71–481 ng g− 1 dw) and were not statistically different between locations. The concentrations of ∑ 28 PAHs were higher in guts + gills than in muscles. The PAH composition pattern was dominated by low molecular weight compounds (naphthalene, alkyl-naphthalenes and phenanthrene). All fish tissues had benzo[a]pyrene concentrations lower than the EU limit for food safety. Excess cancer risk from consumption of some fish was higher than the guideline value of 1 × 10− 6. The concentrations of ∑ 15 OPAHs in fish muscles averaged 422 ng g− 1 dw (range: 28–1715 ng g− 1dw). The ∑ 15 OPAHs/∑ 16 US-EPA PAHs concentration ratio was > 1 in 68% of the fish muscles and 100% of guts + gills. The log-transformed concentrations of PAHs and OPAHs in muscles, guts + gills were significantly (p < 0.05) correlated with their octanol–water partitioning coefficients, strongly suggesting that equilibrium partitioning from water/sediment into fish tissue was the main mechanism of bioaccumulation. The trace metal concentrations in the fish tissues were in the medium range when compared to fish from other parts of the world. The concentrations of some trace metals (Cd, Cu, Fe, Mn, Zn) were higher in guts + gills than in muscle tissues. The target hazard quotients for metals were < 1 and did not indicate a danger to the local population. We conclude that the health risk arising from the consumption of the studied fish (due to their PAHs and trace metals content) is minimal.

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Probabilistic climate data have become available for the first time through the UK Climate Projections 2009, so that the risk of tree growth change can be quantified. We assess the drought risk spatially and temporally using drought probabilities and tree species vulnerabilities across Britain. We assessed the drought impact on the potential yield class of three major tree species (Picea sitchensis, Pinus sylvestris, and Quercus robur) which presently cover around 59% (400,700 ha) of state-managed forests, across lowland and upland sites. Here we show that drought impacts result mostly in reduced tree growth over the next 80 years when using b1, a1b and a1fi IPCC emissions scenarios. We found a maximum reduction of 94% but also a maximum increase of 56% in potential stand yield class in the 2080s from the baseline climate (1961-1990). Furthermore, potential production over the national forest estate for all three species in the 2080s may decrease due to drought by 42% in the lowlands and 32% in the uplands in comparison to the baseline climate. Our results reveal that potential tree growth and forest production on the national forest estate in Britain is likely to reduce, and indicate where and when adaptation measures are required. Moreover, this paper demonstrates the value of probabilistic climate projections for an important economic and environmental sector.

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Three methodologies to assess As bioaccessibility were evaluated using playgroundsoil collected from 16 playgrounds in Madrid, Spain: two (Simplified Bioaccessibility Extraction Test: SBET, and hydrochloric acid-extraction: HCl) assess gastric-only bioaccessibility and the third (Physiologically Based Extraction Test: PBET) evaluates mouth–gastric–intestinal bioaccessibility. Aqua regia-extractable (pseudo total) As contents, which are routinely employed in riskassessments, were used as the reference to establish the following percentages of bioaccessibility: SBET – 63.1; HCl – 51.8; PBET – 41.6, the highest values associated with the gastric-only extractions. For Madridplaygroundsoils – characterised by a very uniform, weakly alkaline pH, and low Fe oxide and organic matter contents – the statistical analysis of the results indicates that, in contrast with other studies, the highest percentage of As in the samples was bound to carbonates and/or present as calcium arsenate. As opposed to the As bound to Fe oxides, this As is readily released in the gastric environment as the carbonate matrix is decomposed and calcium arsenate is dissolved, but some of it is subsequently sequestered in unavailable forms as the pH is raised to 5.5 to mimic intestinal conditions. The HCl extraction can be used as a simple and reliable (i.e. low residual standard error) proxy for the more expensive, time consuming, and error-prone PBET methodology. The HCl method would essentially halve the estimate of carcinogenic risk for children playing in Madridplaygroundsoils, providing a more representative value of associated risk than the pseudo-total concentrations used at present

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The recent deregulation in electricity markets worldwide has heightened the importance of risk management in energy markets. Assessing Value-at-Risk (VaR) in electricity markets is arguably more difficult than in traditional financial markets because the distinctive features of the former result in a highly unusual distribution of returns-electricity returns are highly volatile, display seasonalities in both their mean and volatility, exhibit leverage effects and clustering in volatility, and feature extreme levels of skewness and kurtosis. With electricity applications in mind, this paper proposes a model that accommodates autoregression and weekly seasonals in both the conditional mean and conditional volatility of returns, as well as leverage effects via an EGARCH specification. In addition, extreme value theory (EVT) is adopted to explicitly model the tails of the return distribution. Compared to a number of other parametric models and simple historical simulation based approaches, the proposed EVT-based model performs well in forecasting out-of-sample VaR. In addition, statistical tests show that the proposed model provides appropriate interval coverage in both unconditional and, more importantly, conditional contexts. Overall, the results are encouraging in suggesting that the proposed EVT-based model is a useful technique in forecasting VaR in electricity markets. (c) 2005 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

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Background: Depression is a major health problem worldwide and the majority of patients presenting with depressive symptoms are managed in primary care. Current approaches for assessing depressive symptoms in primary care are not accurate in predicting future clinical outcomes, which may potentially lead to over or under treatment. The Allostatic Load (AL) theory suggests that by measuring multi-system biomarker levels as a proxy of measuring multi-system physiological dysregulation, it is possible to identify individuals at risk of having adverse health outcomes at a prodromal stage. Allostatic Index (AI) score, calculated by applying statistical formulations to different multi-system biomarkers, have been associated with depressive symptoms. Aims and Objectives: To test the hypothesis, that a combination of allostatic load (AL) biomarkers will form a predictive algorithm in defining clinically meaningful outcomes in a population of patients presenting with depressive symptoms. The key objectives were: 1. To explore the relationship between various allostatic load biomarkers and prevalence of depressive symptoms in patients, especially in patients diagnosed with three common cardiometabolic diseases (Coronary Heart Disease (CHD), Diabetes and Stroke). 2 To explore whether allostatic load biomarkers predict clinical outcomes in patients with depressive symptoms, especially in patients with three common cardiometabolic diseases (CHD, Diabetes and Stroke). 3 To develop a predictive tool to identify individuals with depressive symptoms at highest risk of adverse clinical outcomes. Methods: Datasets used: ‘DepChron’ was a dataset of 35,537 patients with existing cardiometabolic disease collected as a part of routine clinical practice. ‘Psobid’ was a research data source containing health related information from 666 participants recruited from the general population. The clinical outcomes for 3 both datasets were studied using electronic data linkage to hospital and mortality health records, undertaken by Information Services Division, Scotland. Cross-sectional associations between allostatic load biomarkers calculated at baseline, with clinical severity of depression assessed by a symptom score, were assessed using logistic and linear regression models in both datasets. Cox’s proportional hazards survival analysis models were used to assess the relationship of allostatic load biomarkers at baseline and the risk of adverse physical health outcomes at follow-up, in patients with depressive symptoms. The possibility of interaction between depressive symptoms and allostatic load biomarkers in risk prediction of adverse clinical outcomes was studied using the analysis of variance (ANOVA) test. Finally, the value of constructing a risk scoring scale using patient demographics and allostatic load biomarkers for predicting adverse outcomes in depressed patients was investigated using clinical risk prediction modelling and Area Under Curve (AUC) statistics. Key Results: Literature Review Findings. The literature review showed that twelve blood based peripheral biomarkers were statistically significant in predicting six different clinical outcomes in participants with depressive symptoms. Outcomes related to both mental health (depressive symptoms) and physical health were statistically associated with pre-treatment levels of peripheral biomarkers; however only two studies investigated outcomes related to physical health. Cross-sectional Analysis Findings: In DepChron, dysregulation of individual allostatic biomarkers (mainly cardiometabolic) were found to have a non-linear association with increased probability of co-morbid depressive symptoms (as assessed by Hospital Anxiety and Depression Score HADS-D≥8). A composite AI score constructed using five biomarkers did not lead to any improvement in the observed strength of the association. In Psobid, BMI was found to have a significant cross-sectional association with the probability of depressive symptoms (assessed by General Health Questionnaire GHQ-28≥5). BMI, triglycerides, highly sensitive C - reactive 4 protein (CRP) and High Density Lipoprotein-HDL cholesterol were found to have a significant cross-sectional relationship with the continuous measure of GHQ-28. A composite AI score constructed using 12 biomarkers did not show a significant association with depressive symptoms among Psobid participants. Longitudinal Analysis Findings: In DepChron, three clinical outcomes were studied over four years: all-cause death, all-cause hospital admissions and composite major adverse cardiovascular outcome-MACE (cardiovascular death or admission due to MI/stroke/HF). Presence of depressive symptoms and composite AI score calculated using mainly peripheral cardiometabolic biomarkers was found to have a significant association with all three clinical outcomes over the following four years in DepChron patients. There was no evidence of an interaction between AI score and presence of depressive symptoms in risk prediction of any of the three clinical outcomes. There was a statistically significant interaction noted between SBP and depressive symptoms in risk prediction of major adverse cardiovascular outcome, and also between HbA1c and depressive symptoms in risk prediction of all-cause mortality for patients with diabetes. In Psobid, depressive symptoms (assessed by GHQ-28≥5) did not have a statistically significant association with any of the four outcomes under study at seven years: all cause death, all cause hospital admission, MACE and incidence of new cancer. A composite AI score at baseline had a significant association with the risk of MACE at seven years, after adjusting for confounders. A continuous measure of IL-6 observed at baseline had a significant association with the risk of three clinical outcomes- all-cause mortality, all-cause hospital admissions and major adverse cardiovascular event. Raised total cholesterol at baseline was associated with lower risk of all-cause death at seven years while raised waist hip ratio- WHR at baseline was associated with higher risk of MACE at seven years among Psobid participants. There was no significant interaction between depressive symptoms and peripheral biomarkers (individual or combined) in risk prediction of any of the four clinical outcomes under consideration. Risk Scoring System Development: In the DepChron cohort, a scoring system was constructed based on eight baseline demographic and clinical variables to predict the risk of MACE over four years. The AUC value for the risk scoring system was modest at 56.7% (95% CI 55.6 to 57.5%). In Psobid, it was not possible to perform this analysis due to the low event rate observed for the clinical outcomes. Conclusion: Individual peripheral biomarkers were found to have a cross-sectional association with depressive symptoms both in patients with cardiometabolic disease and middle-aged participants recruited from the general population. AI score calculated with different statistical formulations was of no greater benefit in predicting concurrent depressive symptoms or clinical outcomes at follow-up, over and above its individual constituent biomarkers, in either patient cohort. SBP had a significant interaction with depressive symptoms in predicting cardiovascular events in patients with cardiometabolic disease; HbA1c had a significant interaction with depressive symptoms in predicting all-cause mortality in patients with diabetes. Peripheral biomarkers may have a role in predicting clinical outcomes in patients with depressive symptoms, especially for those with existing cardiometabolic disease, and this merits further investigation.

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Polycyclic aromatic hydrocarbons (PAH) are widely distributed in the environment, and some are carcinogenic to human beings. The study of biomarkers has helped clarify the nature and magnitude of the human health risks posed by such substances. This article provides a review of the state-of-the-art on PAH biomarkers for human health risk assessment and also discusses their applicability within the context of environmental management in Brazil. The article discusses the methodologies for determination of some biomarkers such as 1-hydroxypyrene and PAH-DNA adducts. Cytogenetic markers, frequency of chromosomal aberrations, and micronucleus induction were considered for the evaluation of cancer risk. The current stage of studies on validation of such biomarkers was also approached.

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Watson is a fully developed suburb of some 30 years in Canberra (the capital city of Australia), A plunge dip using arsenical pesticides for tick control was operated there between 1946 and 1960, Chemical investigations revealed that many soil samples obtained from the study area contained levels of arsenic exceeding the current health-based investigation levels of 100 mg kg(-1) set by the National Health and Medical Research Council in Australia, For the speciation study, nine composite samples of surface and sub-surface soils and a composite sample of rocks were selected. ICP-MS analysis showed that arsenic levels in these samples ranged from 32 to 1597 mg kg(-1), Chemical speciation of arsenic showed that the arsenite (trivalent) components were 0.32-56% in the soil and 44.8% in the rock composite samples. Using a rat model, the absolute bioavailability of these contaminated soils relative to As3+ or As5+ ranged from 1.02 to 9.87% and 0.26 to 2.98%, respectively, An attempt was made to develop a suitable leachate test as an index of bioavailability. However, the results indicated that there was no significant correlation between the bioavailability and leachates using neutral pH water or 1 M HCl. Our results indicate that speciation is highly significant for the interpretation of bioavailability and risk assessment data; the bioavailable fractions of arsenic in soils from Watson are small and therefore the health impact upon the environment and humans due to this element is limited.

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