<strong>Background:</strong><span style="font-family:;" "=""><span style="font-family:Verdana;"> Stroke is the second leading cause of death in the world and ...<strong>Background:</strong><span style="font-family:;" "=""><span style="font-family:Verdana;"> Stroke is the second leading cause of death in the world and the third due to disability. However, there are few data available that identify the risk factors associated with it and their weight in different populations (population risk). </span><b><span style="font-family:Verdana;">Aim: </span></b><span style="font-family:Verdana;">Contribute to the knowledge of burden risk factors in stroke </span></span><span style="font-family:Verdana;">in a large cohort of Southern Italy</span><span style="font-family:;" "=""><span style="font-family:Verdana;">. </span><b><span style="font-family:Verdana;">Methods</span></b><span style="font-family:Verdana;">: The data refer to a randomized Campania cohort of 1200 subjects (35</span></span><span style="font-family:Verdana;"> </span><span style="font-family:Verdana;">-</span><span style="font-family:Verdana;"> </span><span style="font-family:;" "=""><span style="font-family:Verdana;">74 years) enrolled in 2008-09. Ten years later (2018-19) they were re-evaluated. We analyzed data from 32 patients who reported a cerebrovascular event (stroke or TIA) with the event-free group of subjects (804 subjects: 378 men and 426 women). We evaluated: absolute risk, Odds Ratio (OR), Additional Risk (AR), Risk Attributable to the Population (PAR) and, finally, the Population Attributable risk Fraction (FAP). </span><b><span style="font-family:Verdana;">Results:</span></b><span style="font-family:Verdana;"> In the comparison between the two groups (patients with events and patients without events) the risk factors with statistically significant differences were: age, Systolic Blood Pressure (SBP), BMI, cholesterol, triglycerides, glycemia and hyperinsulinemia. The ORs with the greatest impact were: blood glucose (5.1), BMI (3.3) and BPS (2.9). Linear regression analysis identified Glycemia and BMI as the only independent variables. The FAPs with the greatest impact were SBP (47.4%) and BMI (42.6%). </span><b><span style="font-family:Verdana;">Discussion and Conclusions</span></b><span style="font-family:Verdana;">: Our data confirm that the high incidence of stroke in Campania is particularly related to the high prevalence of obesity and hypertension. In the single patient, however, the risk factors with the greatest impact are: glycaemia BMI an SBP.</span></span>展开更多
This work focuses on the best financial resources allocation to define a wind power plant portfolio, considering a set of feasible sites. To accomplish the problem formulation and solution, the first step was to estab...This work focuses on the best financial resources allocation to define a wind power plant portfolio, considering a set of feasible sites. To accomplish the problem formulation and solution, the first step was to establish a long-term wind series reconstruction methodology for generating scenarios of wind energy, applying it to study five different locations of the Brazilian territory. Secondly, a risk-averse stochastic optimization model was implemented and used to define the optimal wind power plant selection </span><span style="font-family:Verdana;">that</span><span style="font-family:Verdana;"> maximize</span><span style="font-family:Verdana;">s</span><span style="font-family:Verdana;"> the portfolio financial results, considering an investment budget constraint. In a sequence, a case study was developed to illustrate a practical situation of applying the methodology to the portfolio selection problem, considering five wind power plant</span><span style="font-family:Verdana;">s</span><span style="font-family:Verdana;"> options. </span><span style="font-family:Verdana;">The case</span><span style="font-family:Verdana;"> study was supported by the proposed optimization model, using the scenarios of generation created by the reconstruction methodology. The obtained results show the model performance in terms of defining the best financial resources allocation considering the effect of the complementarity between sites, making it feasible to select the optimal set of wind power plants, characterizing a wind plant optimal portfolio that takes into account the budget constraint. The adopted methodology makes it possible to realize that the diversification of the portfolio depends on the investor risk aversion. Although applied to the Brazilian case, this model can be customized to solve a similar problem worldwide.展开更多
Roughly along the Animaqing Maji peak, the Kunlun fault section between the Tuosuo Lake and Kendingna (east Maqin) can be subdivided into two geometric segments: the Huashixia and the Maqin segments. These two segment...Roughly along the Animaqing Maji peak, the Kunlun fault section between the Tuosuo Lake and Kendingna (east Maqin) can be subdivided into two geometric segments: the Huashixia and the Maqin segments. These two segments behave differently in their Holocene slip rates and paleo-earthquake activities, with obviously higher paleo-seismic activity on the Huashixia segment than on Maqin segment. As many as four strong Holocene earthquakes are identified on the Huashixia segment from trenching and geomorphic studies. The recurrent interval for the latest three earthquakes are at about 500 a and 640 a, respectively. On the Maqin segment, at least three paleo-earthquake events can be defined from trenching, with a recurrent interval for the latest two events at about 1000 a. M = 7.5 earthquakes on Huashixia segment recur at every 411 a to 608 a with a characteristic slip at 5.75±0.57 m. Although the Maqin segment is less active, its accumulated strain energy during the long time period since last earthquake occurred (about 1070 a BP) deserves enough notice on its future earthquake probabilities.展开更多
Cyber losses in terms of number of records breached under cyber incidents commonly feature a significant portion of zeros, specific characteristics of mid-range losses and large losses, which make it hard to model the...Cyber losses in terms of number of records breached under cyber incidents commonly feature a significant portion of zeros, specific characteristics of mid-range losses and large losses, which make it hard to model the whole range of the losses using a standard loss distribution. We tackle this modeling problem by proposing a three-component spliced regression model that can simultaneously model zeros, moderate and large losses and consider heterogeneous effects in mixture components. To apply our proposed model to Privacy Right Clearinghouse (PRC) data breach chronology, we segment geographical groups using unsupervised cluster analysis, and utilize a covariate-dependent probability to model zero losses, finite mixture distributions for moderate body and an extreme value distribution for large losses capturing the heavy-tailed nature of the loss data. Parameters and coefficients are estimated using the Expectation-Maximization (EM) algorithm. Combining with our frequency model (generalized linear mixed model) for data breaches, aggregate loss distributions are investigated and applications on cyber insurance pricing and risk management are discussed.展开更多
文摘<strong>Background:</strong><span style="font-family:;" "=""><span style="font-family:Verdana;"> Stroke is the second leading cause of death in the world and the third due to disability. However, there are few data available that identify the risk factors associated with it and their weight in different populations (population risk). </span><b><span style="font-family:Verdana;">Aim: </span></b><span style="font-family:Verdana;">Contribute to the knowledge of burden risk factors in stroke </span></span><span style="font-family:Verdana;">in a large cohort of Southern Italy</span><span style="font-family:;" "=""><span style="font-family:Verdana;">. </span><b><span style="font-family:Verdana;">Methods</span></b><span style="font-family:Verdana;">: The data refer to a randomized Campania cohort of 1200 subjects (35</span></span><span style="font-family:Verdana;"> </span><span style="font-family:Verdana;">-</span><span style="font-family:Verdana;"> </span><span style="font-family:;" "=""><span style="font-family:Verdana;">74 years) enrolled in 2008-09. Ten years later (2018-19) they were re-evaluated. We analyzed data from 32 patients who reported a cerebrovascular event (stroke or TIA) with the event-free group of subjects (804 subjects: 378 men and 426 women). We evaluated: absolute risk, Odds Ratio (OR), Additional Risk (AR), Risk Attributable to the Population (PAR) and, finally, the Population Attributable risk Fraction (FAP). </span><b><span style="font-family:Verdana;">Results:</span></b><span style="font-family:Verdana;"> In the comparison between the two groups (patients with events and patients without events) the risk factors with statistically significant differences were: age, Systolic Blood Pressure (SBP), BMI, cholesterol, triglycerides, glycemia and hyperinsulinemia. The ORs with the greatest impact were: blood glucose (5.1), BMI (3.3) and BPS (2.9). Linear regression analysis identified Glycemia and BMI as the only independent variables. The FAPs with the greatest impact were SBP (47.4%) and BMI (42.6%). </span><b><span style="font-family:Verdana;">Discussion and Conclusions</span></b><span style="font-family:Verdana;">: Our data confirm that the high incidence of stroke in Campania is particularly related to the high prevalence of obesity and hypertension. In the single patient, however, the risk factors with the greatest impact are: glycaemia BMI an SBP.</span></span>
文摘This work focuses on the best financial resources allocation to define a wind power plant portfolio, considering a set of feasible sites. To accomplish the problem formulation and solution, the first step was to establish a long-term wind series reconstruction methodology for generating scenarios of wind energy, applying it to study five different locations of the Brazilian territory. Secondly, a risk-averse stochastic optimization model was implemented and used to define the optimal wind power plant selection </span><span style="font-family:Verdana;">that</span><span style="font-family:Verdana;"> maximize</span><span style="font-family:Verdana;">s</span><span style="font-family:Verdana;"> the portfolio financial results, considering an investment budget constraint. In a sequence, a case study was developed to illustrate a practical situation of applying the methodology to the portfolio selection problem, considering five wind power plant</span><span style="font-family:Verdana;">s</span><span style="font-family:Verdana;"> options. </span><span style="font-family:Verdana;">The case</span><span style="font-family:Verdana;"> study was supported by the proposed optimization model, using the scenarios of generation created by the reconstruction methodology. The obtained results show the model performance in terms of defining the best financial resources allocation considering the effect of the complementarity between sites, making it feasible to select the optimal set of wind power plants, characterizing a wind plant optimal portfolio that takes into account the budget constraint. The adopted methodology makes it possible to realize that the diversification of the portfolio depends on the investor risk aversion. Although applied to the Brazilian case, this model can be customized to solve a similar problem worldwide.
基金Sino-French Cooperative Research program ″The Shortening Mechanisms of Eastern Kunlun Lithosphere″.
文摘Roughly along the Animaqing Maji peak, the Kunlun fault section between the Tuosuo Lake and Kendingna (east Maqin) can be subdivided into two geometric segments: the Huashixia and the Maqin segments. These two segments behave differently in their Holocene slip rates and paleo-earthquake activities, with obviously higher paleo-seismic activity on the Huashixia segment than on Maqin segment. As many as four strong Holocene earthquakes are identified on the Huashixia segment from trenching and geomorphic studies. The recurrent interval for the latest three earthquakes are at about 500 a and 640 a, respectively. On the Maqin segment, at least three paleo-earthquake events can be defined from trenching, with a recurrent interval for the latest two events at about 1000 a. M = 7.5 earthquakes on Huashixia segment recur at every 411 a to 608 a with a characteristic slip at 5.75±0.57 m. Although the Maqin segment is less active, its accumulated strain energy during the long time period since last earthquake occurred (about 1070 a BP) deserves enough notice on its future earthquake probabilities.
文摘Cyber losses in terms of number of records breached under cyber incidents commonly feature a significant portion of zeros, specific characteristics of mid-range losses and large losses, which make it hard to model the whole range of the losses using a standard loss distribution. We tackle this modeling problem by proposing a three-component spliced regression model that can simultaneously model zeros, moderate and large losses and consider heterogeneous effects in mixture components. To apply our proposed model to Privacy Right Clearinghouse (PRC) data breach chronology, we segment geographical groups using unsupervised cluster analysis, and utilize a covariate-dependent probability to model zero losses, finite mixture distributions for moderate body and an extreme value distribution for large losses capturing the heavy-tailed nature of the loss data. Parameters and coefficients are estimated using the Expectation-Maximization (EM) algorithm. Combining with our frequency model (generalized linear mixed model) for data breaches, aggregate loss distributions are investigated and applications on cyber insurance pricing and risk management are discussed.
