投资组合动态VaR预测模型和预测精度评价

采用4种Backtesting检验方法,检验22个常态和时变投资组合动态VaR预测模型的风险预测精度,发现GJR_GPD_TV_Copula具有最高的投资组合风险预测精度,GJR_GPD_Copula的拟合、密度预测和组合风险预测精度都要高于GJR_SKST_Copula,且Copula模型的组合风险预测精度分别与拟合精度和密度预测精度存在较弱的正相关关系.     

A Diversity Index for Model Space Selection in the Estimation of Benchmark and Infectious Doses via Model Averaging

In chemical and microbial risk assessments, risk assessors fit dose‐response models to high‐dose data and extrapolate downward to risk levels in the range of 1–10%. Although multiple dose‐response models may be able to fit the data adequately in the experimental range, the estimated effective dose (ED) corresponding to an extremely small risk can be substantially different from model to model. In this respect, model averaging (MA) provides more robustness than a single dose‐response model in the point and interval estimation of an ED. In MA, accounting for both data uncertainty and model uncertainty is crucial, but addressing model uncertainty is not achieved simply by increasing the number of models in a model space. A plausible set of models for MA can be characterized by goodness of fit and diversity surrounding the truth. We propose a diversity index (DI) to balance between these two characteristics in model space selection. It addresses a collective property of a model space rather than individual performance of each model. Tuning parameters in the DI control the size of the model space for MA.     

An Integrated Risk Assessment Model of Township‐Scaled Land Subsidence Based on an Evidential Reasoning Algorithm and Fuzzy Set Theory

Land subsidence risk assessment (LSRA) is a multi‐attribute decision analysis (MADA) problem and is often characterized by both quantitative and qualitative attributes with various types of uncertainty. Therefore, the problem needs to be modeled and analyzed using methods that can handle uncertainty. In this article, we propose an integrated assessment model based on the evidential reasoning (ER) algorithm and fuzzy set theory. The assessment model is structured as a hierarchical framework that regards land subsidence risk as a composite of two key factors: hazard and vulnerability. These factors can be described by a set of basic indicators defined by assessment grades with attributes for transforming both numerical data and subjective judgments into a belief structure. The factor‐level attributes of hazard and vulnerability are combined using the ER algorithm, which is based on the information from a belief structure calculated by the Dempster‐Shafer (D‐S) theory, and a distributed fuzzy belief structure calculated by fuzzy set theory. The results from the combined algorithms yield distributed assessment grade matrices. The application of the model to the Xixi‐Chengnan area, China, illustrates its usefulness and validity for LSRA. The model utilizes a combination of all types of evidence, including all assessment information—quantitative or qualitative, complete or incomplete, and precise or imprecise—to provide assessment grades that define risk assessment on the basis of hazard and vulnerability. The results will enable risk managers to apply different risk prevention measures and mitigation planning based on the calculated risk states.     

儒家“义—利”价值结构与西方“财富”价值结构比较研究简

通过中国儒家和西方经济价值结构的比较研究，发现儒家以“义一利”为价值结构模型，西方以“财富”为价值结构模型。儒家价值结构的基本特征是“义体利用”，表现方式是：强国的道义在于顺天时、尽地利、忠人和；安国的道义在于民朴民富；治国的道义在于蓄储俭用。西方价值结构的基本特征是“利体义用”，表现方式是：鼓励获取财富、财富规则和财富责任。儒家“义一利”价值结构与西方“财富”价值结构是两种不同的价值评判话语体系，在中国现代“义利共体”的价值结构建构中，儒家价值结构提供着人文精神基础，西方价值结构提供着物质文明建设可资借鉴的经验。     

低压及欠平衡钻井中注气量对井内压力的影响

以多相瞬变流理论为基础,建立了井筒内气液两相流动模型,并对低压欠平衡钻井中注气量对井内压力的影响关系和规律进行计算和分析。计算分析结果表明,注气量对井内压力的影响除与注气量本身大小有关外,还与井深、井眼与钻柱结构尺寸、井内液相流量和性质等因素密切相关。单纯增大注气量并不一定就必然会导致井内压力的降低,这取决于所给条件下构成井筒内气液两相流体的静液压力和流阻间的平衡关系。介绍的模型及方法对确定低压欠平衡钻井过程中各相关参数、地面压缩机组的配置、以及设计方案等有一定指导意义。     

汽车侧围外板尾翼拉延成型工艺改善研究

为解决汽车侧围外板尾翼在拉延成型后出现起皱和开裂的问题，设计了3种造型方案.通过造型设计分析及Autoform模拟，对比3种方案，对原工艺进行整改和优化，得到了抬高造型台阶面的最优造型方案.该方案能改善进料速度、增加材料流动性，有效地消除开裂、起皱的缺陷，对同类和其他类似产品的冲压工艺设计具有参考意义.     

A Tiered Framework for Risk‐Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children's Study (NCS)

A challenge for large‐scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co‐occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure‐relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new “Tiered Exposure Ranking” (TiER) framework, developed to support various aspects of risk‐relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both “discovery‐driven” and “hypothesis‐driven” analyses. “Tier 1” applications focus on “exposomic” pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk‐relevant exposure metrics for populations and individuals. In this article, “tier 1” applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A “tier 2” application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk‐relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.     

高含水期复杂断块油藏剩余油分布及挖潜

高含水期陆相复杂断块层状油藏剩余油分布复杂,油藏模拟难度大。马11复杂断块油藏在油藏精细描述基础上,利用动静态综合分析研究与密网格大规模数值模拟研究相结合,提高了剩余油研究精度和可信度;在此基础上,针对油藏剩余油分布特点并结合当前经济技术条件,部署实施了以调整井、调剖、堵水、油水井大修为主的剩余油挖潜方案,油藏含水上升率大幅度下降、采油速度上升、采收率提高了。     

The COVID‐19 Pandemic and Families in Japan

This paper, which is authored by members of the Japanese Association of Family Therapy (JAFT), describes the COVID‐19 pandemic in Japan from a family systems perspective. The authors are active members of JAFT and include current and past presidents and officers. We describe the course of the pandemic and the ways in which government policies to mitigate the pandemic have affected Japanese families. Challenges that affect Japanese families include the inability to participate in family and social rituals, prescribed gender roles that specifically affect women, high suicide rates, and prejudice against those who are at risk of spreading the infection. The need to shelter in place has also forced family homes to function as a workplace for parents, classrooms for children, and day care services for frail elders, which has resulted in psychological distress among individuals and conflicts among families. We discuss ways that therapists have worked with Japanese families using online therapy.