Burden of Cardiometabolic Risk Factors on Cerebrovascular Events in a Southern Italian Population

Background: 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). Aim: Contribute to the knowledge of burden risk factors in stroke in a large cohort of Southern Italy. Methods: The data refer to a randomized Campania cohort of 1200 subjects (35 - 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). Results: 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%). Discussion and Conclusions: 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.

Optimal Portfolio Selection of Wind Power Plants Using a Stochastic Risk-Averse Optimization Model, Considering the Wind Complementarity of the Sites and a Budget Constraint

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 that maximizes 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 plants options. The case 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.

Modeling Cyber Loss Severity Using a Spliced Regression Distribution with Mixture Components

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.

金融法视阈下的行政执法和解制度探析

《中华人民共和国金融稳定法(草案)》规定了行政执法当事人承诺制度,正在为金融领域行政执法和解制度的构建提供法律依据。与此同时,虽然行政和解暂未形成理论共识,但金融法视阈下行政执法和解的实践已然先行于理论。针对金融风险处置和证券期货领域中的金融纠纷,行政机关在符合依法行政的要求下通过行使自由裁量权,借助协商民主、公众参与等私法化手段采取的行政执法和解措施,可有效化解纠纷且实现各方获益的经济及社会效果。通过对金融领域行政执法和解措施的实践检视,提出以各方均可获益作为启动行政执法和解制度的前提,通过举证责任的倾斜、“自认”的可适用性与行刑衔接的合规机制相结合,将有助于构建更加符合实践理性的行政执法和解制度。

基于渐进式认知发现的新型配电网故障定位方法

在“双碳”目标下,持续接入分布式电源的新型配电网对运行可靠性提出了更高的要求,如何在渗透率变化的场景下提高现有故障定位方法的适应能力成为亟需解决的问题。为此,采用元学习特有的学会学习机制,提出了一种基于渐进式认知发现的新型配电网故障定位方法。首先,基于现有场景数据采用网络结构搜索算法构建当前场景个性化定位模型;然后,利用元学习算法提取模型构建过程中的知识因子,组成故障定位认知发现库;进而,在数据流和知识流的共同作用下,故障定位模型渐进地实现场景持续变化下的自主进化;最后,在PSCAD仿真平台对所提方法进行了验证。结果表明:所提方法具有定位精度高、鲁棒性强的优点,且在不同渗透率的故障场景下有着良好的泛化能力。研究结果可为基于人工智能的定位方法在实际系统中的应用提供技术支持。

基于矩不确定模糊集的分布鲁棒风险-回报优化模型研究

本文研究随机变量分布不确定下的风险-回报优化模型。针对传统的风险-回报三类典型问题和分布不确定性背景,提出了更一般性条件下的分布鲁棒风险-回报优化新模型;基于矩不确定集合和优化对偶理论,化简复杂的新优化模型为常规结构的非线性优化问题。理论上证明了分布鲁棒风险-回报三类优化模型效率前沿的等价性。数值实验验证了理论分析的有效性。

结构性资产负债表衰退及其宏观经济效应与政策协整

疫后恢复政策组合拳,有力承托了中国宏观经济运行的积极因素,但当前经济下行压力依然突出,部分领域发展呈现明显波动,亟须有能够“对症下药”的理论解释和宏观政策应对。构建NK-DSGE模型,探讨结构性资产负债表衰退的宏观经济效应以及相应政策协整问题。研究结果展示,典型事实蕴含中国不存在总体资产负债表衰退,但存在结构性资产负债表衰退的证据。在宏观层面,结构性资产负债表衰退冲击会导致宏观经济较长时期下滑,乃至引发债务-通缩风险,而在微观层面,减轻资产负债表衰退企业的债务厌恶和改善正常经营企业的融资约束有助于减弱上述影响。调节效应分析表明,结构性资产负债表衰退会抑制技术进步与需求扩张对产出的促进作用,但在技术进步情形下,上述抑制作用有限。为减小福利损失,财政政策应盯住衰退类企业债务,货币政策应锚定高融资约束企业债务,并提高政策反应力度,宏观审慎政策应提高对资产价格的敏感度。上述结论为理解微观层面债务厌恶所产生的宏观合力以及设计实施相应政策搭配提供参考。

基于多层级条件风险价值的高渗透可再生能源电力系统低碳运行联合优化

在双碳目标下,风电渗透率增加给新型电力系统的安稳运行带来挑战,而条件风险价值法(Conditional Value-at-Risk,CVaR)可对风电的随机风险进行分类量化评估,以用于系统调度运行。根据CVaR提出了改进的多层级条件风险价值法(Multi-layer Conditional Value-at-Risk,MCVaR),并建立了基于MCVaR的高渗透可再生能源电力系统低碳运行联合优化模型。仿真算例结果表明,MCVaR相较于CVaR能够显著降低系统的弃风与切负荷量,同时系统的极端损失下降了49.45%。所提方法能够在满足系统可控风险约束的前提下,实现运行经济效益与低碳环保收益的综合最优化。

数字经济背景下企业社会责任信息披露、风险承担与创新投入

本文基于社会资本理论,以2007~2022年我国A股上市公司为样本,运用Heckman两阶段模型,探讨数字经济背景下,企业社会责任信息披露影响创新投入的内在机理,解释了企业风险承担能力和管理者风险承担意愿的中介作用,以及公司治理的调节效应,以拓展战略性慈善行为推动企业创新的相关研究。结果表明:社会责任信息披露促进创新投入;管理者风险承担意愿和企业风险承担水平均发挥中介作用;CEO二元性、董事会规模、管理层持股比和股权制衡度均对社会责任信息披露与创新投入的关系起促进作用。本文将社会责任信息披露的影响从伦理层面拓展到战略层面,为企业数字化战略、社会责任战略和创新战略的协同作用提供了重要启示。

老年股骨粗隆间骨折髓内固定术后髋关节功能恢复影响因素的Meta分析

目的系统评价老年股骨粗隆间骨折髓内固定术后髋关节功能恢复障碍的影响因素。方法系统检索The Co⁃chrane Library、EMbase、PubMed、Web of Science、中国知网、中国生物医学数据库、万方数据库、维普数据库中公开发表的关于老年股骨粗隆间骨折髓内固定术后髋关节功能恢复影响因素的研究,检索时限为2017年1月1日至2023年3月10日。由2名研究员根据纳入和排除标准独立进行文献筛选和数据提取,进行质量评价后使用Review Manager 5.4软件进行Meta分析。结果最终纳入7篇文献。Meta分析结果显示,骨折类型(OR=4.81,95%CI 1.64~14.11,P=0.004<0.01)、超早期负重(OR=29.95,95%CI 16.05~55.88,P<0.00001)、年龄(OR=4.32,95%CI 1.48~12.54,P=0.007<0.01)、骨密度(OR=7.36,95%CI 1.91~28.34,P=0.004<0.01)、ASA分级(OR=3.40,95%CI 2.15~5.38,P<0.00001)、血浆蛋白(OR=6.80,95%CI 1.99~23.22,P=0.002<0.01)、康复师指导(OR=4.59,95%CI 2.08~10.14,P=0.0002<0.01)、复位质量(OR=12.24,95%CI 3.84~38.98,P<0.00001)、术后并发症(OR=4.15,95%CI 1.79~9.63,P=0.0009<0.00001)、合并基础疾病(OR=12.28,95%CI 8.91~16.92,P<0.00001)、麻醉方式(全麻)(OR=5.19,95%CI 3.15~8.54,P<0.00001)、麻醉方式(椎管内麻醉)(OR=14.69,95%CI 8.23~26.23,P<0.00001)为髋关节功能恢复的影响因素。手术时机(OR=2.65,95%CI 0.16~43.16,P=0.49>0.01)不是术后髋关节功能恢复的影响因素。结论稳定型骨折、超早期负重、年龄<70岁、骨密度≥-2.5SD、ASA分级低风险、血浆蛋白水平≥30g/L、有康复师指导、良好复位、术后并发症发生率低、合并基础疾病少、选择全麻或椎管内麻醉均为老年股骨粗隆间骨折髓内固定术后髋关节功能恢复的促进因素,尚无较多证据证明手术时机为髋关节功能恢复的影响因素。

Cost Sharing Based Truthful Spectrum Auction with Collusion-Proof

Spectrum auction is an important approach of spectrum distribution in cognitive radio networks. However, a single secondary user(SU) probably can't afford the price of spectrum. Multiple SUs grouping together to participate in the auction as a whole is helpful to increase purchasing power. However, SUs could suffer from a new group cheating problem, i.e., parts of users conspire to manipulate the auction by submitting untruthful bids. Existing auction mechanisms were mainly designed to be strategy-proof only for individual user and can't deal with group cheating. In this paper, a novel spectrum auction mechanism called COSTAG(COst Sharing based Truthful Auction with Group-buying) is proposed to address the group cheating problem. COSTAG consists of a grouping rule to perform grouping and a payment rule to determine the market-clearing price in the spectrum auction. Different from single-echelon pricing approach employed in existing works, a multi-echelon pricing strategy is designed to increase the transaction rate and optimize social profit for the auction. Comprehensive theoretical analysis shows that COSTAG can satisfy the crucial economic robustness properties, both individual and group truthfulness. Simulations demonstrate that comparing with existing works, COSTAG can improve the system performance significantly.

Paleo-earthquake studies on the eastern section of the Kunlun fault

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.

急性缺血性脑血管病患者脑动脉粥样硬化性狭窄分布及危险因素

目的分析急性缺血性脑血管病患者脑动脉粥样硬化性狭窄的分布情况及危险因素。方法选取江苏大学附属徐州医院神经外科2018-02—2021-02收治的256例急性缺血性脑血管病患者为研究对象,分析病例资料和数字血管造影检查结果,探讨动脉粥样硬化性狭窄分布情况和危险因素。结果256例患者有狭窄病变600支,407支为颅内动脉狭窄,占67.83%;193例为颅外动脉狭窄,占32.17%。前循环和后循环分别为412支和188支,分别占68.67%和31.33%;107支血管累及大脑中动脉,占17.83%,为最常见累及血管。重度狭窄患者C反应蛋白(2.45±0.48)ng/L,白细胞介素-6水平(268.96±37.12)pg/L,中度狭窄患者C反应蛋白和白细胞介素-6水平分别为(2.36±0.54)mg/L和(252.55±43.72)pg/L;轻度狭窄患者C反应蛋白和白细胞介素-6水平分别为(2.21±0.32)mg/L和(244.78±40.32)pg/L,组间对比有统计学差异(P<0.05)。Logistic多因素分析显示,颅内动脉狭窄以高血压和糖尿病为独立危险因素;颅外动脉狭窄以性别、年龄、高血压和糖尿病为独立危险因素;同时狭窄者以性别、年龄、高血压、冠心病和糖尿病为独立危险因素,均存在统计学差异(P<0.05)。结论急性缺血性脑血管病患者脑动脉粥样硬化性狭窄以颅内动脉狭窄为主,前循环狭窄更为多发,主要累及大脑中动脉,脑动脉粥样硬化性狭窄以高血压和糖尿病为独立危险因素。

成山角水域动态自适应自主航行决策方法

为研究成山角分道通航制水域船舶自主航行方法,本文数字化了该水域交通环境,探究了碰撞危险度量化模型和动态避碰机理。建立了耦合船舶航向控制方法、非线性操纵运动模型和航线跟踪方法的自动航行模型。基于时序滚动提出了能适应目标船机动和自校正误差的自主航行决策方法,该方法考虑了避碰规则和良好船艺的要求。实验结果表明:本船可让清所有目标船并按计划航线航行;预设场景中,本船在31 s、3762 s右转14°、5°可安全通过。本文提出的方法可为分道通航制水域的自主航行提供理论基础。

基于贝叶斯反馈修正云模型的虚拟电厂运营风险综合评价方法

研究了虚拟电厂运营风险综合评价体系,为虚拟电厂建设运营提供支撑与指导。首先以运行风险、经济风险、安全风险和管理风险为一级指标构建了虚拟电厂风险综合评价指标库,为虚拟电厂安全可靠运行评价提供了支撑。其次提出了虚拟电厂风险综合评价模型,选用有序加权平均(ordered weighted average,OWA)—改进的层次分析法(analytic hierarchy process,AHP)对指标进行赋权,进而通过基于贝叶斯反馈修正的云模型评价方法得出各级指标的评价分数,用以评价虚拟电厂的风险程度,为虚拟电厂运行改进与优化提供判断依据。最后选取某虚拟电厂进行算例分析验证了所提基于贝叶斯改进云模型的虚拟电厂风险评价指标体系的有效性及优越性。

老年高血压脑出血患者再出血的风险预测模型构建与验证

目的构建老年高血压脑出血患者再出血的风险预测模型,并验证其效能。方法回顾性分析郑州大学第五附属医院2019-01-2021-12收治的336例老年高血压脑出血患者的临床资料,随机分为建模集(n=224)与验证集(n=112)。随访12个月,根据是否发生再出血将建模集分为发生组(n=40)和未发生组(n=184),Logistic回归分析探讨再出血的危险因素;R软件rms程序包绘制风险预测列线图模型,Bootstrap法和受试者工作特征(ROC)对构建的模型的预测效能进行验证。结果再出血发生率18.15%,建模集与验证集再出血发生率分别为17.86%、18.75%,且多发生于发病后1周内;发生组高血压病程长于未发生组[(15.15±3.20)a比(10.28±2.04)a,P<0.05],脑出血量多于未发生组[(79.91±15.56)mL比(51.12±10.58)m L,P<0.05],血肿形态不规则、合并糖尿病、凝血功能障碍、降压治疗不依从占比均高于未发生组(42.50%比22.83%,45.00%比23.91%,35.00%比15.76%,27.50%比10.33%,P<0.05),上述均为再出血的影响因素(OR=1.836、1.193、3.733、5.114、3.451、3.317,P<0.05);基于再出血的危险因素Logistic回归分析结果,构建再出血的风险预测模型,经验证C-index=0.846,校正曲线与标准曲线拟合度理想,且该模型预测再出血的曲线下面积(AUC)为0.952(95%CI:0.895~0.984),灵敏度和特异度分别为90.48%、91.21%。结论高血压病程、脑出血量、血肿形态不规则、合并糖尿病、凝血功能障碍、降压治疗不依从均是老年高血压脑出血患者再出血的危险因素,基于此构建的风险预测模型可准确预测再出血风险。

城市地下综合管廊施工风险耦合评价方法

为研究一套适用于城市地下综合管廊施工风险耦合评价方法,文中从人为、机械设备、材料、管理、环境、施工技术6个维度分析城市地下综合管廊施工风险,构建一套31个指标的城市地下综合管廊施工风险指标体系。引入风险耦合理论、机理,根据C-OWA算子可削弱专家主观经验判断的极值影响、相互作用矩阵法可同时考虑多因素之间交互作用对系统的影响,建立基于C-OWA算子理论和相互作用矩阵理论的风险评价模型,可更加科学合理地为风险指标赋值。最后以某市地下综合管廊为例,应用这种评价方法,计算得出施工风险强度为中等风险,与实际相符,验证文中方法的可行性。对高风险因素提出管控措施,有助于各单位有效控制措施、降低施工风险事故发生的概率,推进现场安全管理。

基于风险度量的多交通方式协同应急救援方案优化

近年来我国重大交通工程建设中的突发事件频繁发生,且呈现救援条件复杂,影响后果不确定等特征,因此研究多交通方式协同下的应急救援路径优化具有重要意义。本文以复杂地质环境下重大交通工程建设中的突发事件为背景,基于条件风险价值衡量由于救援时间导致的伤亡损失后果,采取多种交通方式协同进行救援。考虑到伤员数量和物资需求的不确定性以及救援资源分配的公平性,建立了最小化总风险和总成本的双目标鲁棒优化模型,用以决策多种交通方式的协同救援路径,以及物资运输和伤员转移方案。本文基于鲁棒对等转化和ε-约束法设计了相应的求解算法,并使用两个路网算例进行验证。研究结果表明,救援路径总风险与总成本之间存在着权衡关系,采用多交通方式协同救援可有效降低伤亡风险;随着伤员数量和物资需求不确定程度的增加,总风险和总成本均呈现增加趋势,管理者可依据其对风险的偏好程度决策不同不确定性水平下的最优救援方案;此外,与不考虑公平性约束相比,受灾单元物资需求和伤员转移需求满足率的标准差分别降低了12.9和12.6,平均满足率分别提高了7.5%和8.4%,有效保障了救援资源分配的合理性和公平性。本文所建立的鲁棒模型可有效处理不确定条件下的应急响应问题,帮助决策者制定合理的路径方案,以及物资运输和伤员转移方案。

机场飞行区主动安全技术防范体系构建

空地交通汇聚的机场飞行区是航空安全管控的重点和难点。首先,分析了欧美等航空强国和我国民航在机场飞行区场面活动目标监视、道面异物和健康状态检测、主动安全防范与风险智能管控等采取的信息化手段及存在的问题;然后,构建了“物联、数联、智联”飞行区主动安全技术防范体系与“端-边-云”的互联架构;最后,阐明了场面活动目标态势精确定位与感知、机场道面状态智能监测与性能快速恢复以及机场飞行区风险识别与智能决策等关键技术的研究思路,通过提升机场运行品质和安全绩效等,助力“四型机场”建设和民航高质量发展。

3维水翼非定常云空化结构分析和侵蚀风险预估

空化是在流体设备中经常发生的现象,而云空化结构的溃灭会释放出极高的压力,常被认为是造成材料空蚀破坏的主要原因,因此研究云空化的演化、溃灭和对壁面的冲击作用具有重要意义.采用隐式大涡模拟方法和基于局部流场修正的空化模型,对不同空化数下的NACA00153维水翼进行了数值模拟,考察了空化流动结构的演化过程,并采用基于能量输运的侵蚀风险预估模型对空蚀风险区域进行了预估.主要结论如下:(1)基于局部流场修正的空化模型可更好地预测空化体积;隐式大涡模拟方法较好地捕捉到了多种形式的非定常空化流动结构.(2)空化数σ对云空化发生的程度、演化特征和溃灭位置的影响不同:当σ=1.19时,空化结构较为稳定,翼型表面附着型腔体最大长度约在0.4倍的翼型弦长处,而脱落腔体溃灭的位置约在0.6倍处;当σ=1.07时,翼型表面附着型腔体最大长度约在0.5倍处,而脱落腔体溃灭的位置约在0.7倍处;当σ=0.95时,空化结构演化剧烈,会出现多尺度腔体共同脱落现象,翼型表面附着腔体最大长度约在0.7倍处,而脱落腔体溃灭的位置在翼型尾缘附近.(3)基于能量输运的预估模型可用于预测因空化腔体发生溃灭引起的翼型表面发生侵蚀破坏的风险区域.