Improved Transferability of Data‐Driven Damage Models Through Sample Selection Bias Correction

Damage models for natural hazards are used for decision making on reducing and transferring risk. The damage estimates from these models depend on many variables and their complex sometimes nonlinear relationships with the damage. In recent years, data‐driven modeling techniques have been used to capture those relationships. The available data to build such models are often limited. Therefore, in practice it is usually necessary to transfer models to a different context. In this article, we show that this implies the samples used to build the model are often not fully representative for the situation where they need to be applied on, which leads to a “sample selection bias.” In this article, we enhance data‐driven damage models by applying methods, not previously applied to damage modeling, to correct for this bias before the machine learning (ML) models are trained. We demonstrate this with case studies on flooding in Europe, and typhoon wind damage in the Philippines. Two sample selection bias correction methods from the ML literature are applied and one of these methods is also adjusted to our problem. These three methods are combined with stochastic generation of synthetic damage data. We demonstrate that for both case studies, the sample selection bias correction techniques reduce model errors, especially for the mean bias error this reduction can be larger than 30%. The novel combination with stochastic data generation seems to enhance these techniques. This shows that sample selection bias correction methods are beneficial for damage model transfer.     

Factors associated with a positive childbirth experience in Brazilian women: A cross-sectional study

BackgroundHaving a positive childbirth experience is an increasingly valued outcome. Few studies evaluated the women’s satisfaction with childbirth through face-to-face interviews out of the health service environment. The objective of this study was to identify factors associated with a higher level of satisfaction with the childbirth experience among Brazilian women.MethodsThis cross-sectional study involved 287 women giving birth in two hospitals in southern Brazil. Women who gave birth to healthy newborns at term were randomly selected. Face-to-face interviews were conducted 31–37 days after delivery, at the mothers’ homes, using a structured questionnaire. Satisfaction with the childbirth experience was measured using a Likert-type scale ranging from very satisfied to very dissatisfied. Prevalence ratios (PR) were estimated using Poisson regression with robust variance.ResultsFollowing hierarchical multivariate analysis, the following factors remained associated with a higher level of satisfaction with the childbirth experience: being satisfied with antenatal care (PR = 1.30; 95% confidence interval [95%CI] = 1.06−1.59), understanding the information provided by health professionals during labor and delivery (PR = 1.40; 95%CI = 1.01−1.95), not having reported disrespect and abuse (PR = 1.53; 95%CI = 1.01−2.31), and having had the baby put to the breast within the first hour of life (PR = 1.63; 95%CI = 1.26−2.11). No association was observed with type of delivery or hospital status (public or private).ConclusionsA higher level of satisfaction with the childbirth experience is related to satisfactory antenatal care, a non-abusive, respectful, and informative environment during childbirth, and to the opportunity to breastfeed the baby within the first hour of life. In clinical practice, greater attention to these basic principles of care during pregnancy and delivery could provide more positive experiences during birth.     

交易特性、社员身份与农业合作社合约选择

在威廉姆森交易成本理论的基础上，探讨交易特性对农业合作社与农户之间合约选择的影响，发现社员身份特征在其中发挥调节作用。研究结果表明，资产专用性、风险性和规模性对农业合作社与农户之间签订一体化程度不同的合约具有明显的影响，其中，专用性对合约一体化程度的影响是正向的；而风险性和规模性对双方签订一体化程度更高的合约影响是负向的。但和非社员相比，股东身份使资产专用性对双方签订一体化程度更高合约的正向影响作用变大；并使风险性、规模性对双方签订一体化程度更高合约的负向影响作用变小，即股东身份作为调节变量发挥了显著效应。     

村庄非农化、社会资本与农民家庭收入

聚焦于社会资本影响农民收入的微观和宏观机制，利用中国家庭动态追踪调查数据构建“家庭—村庄”两个层次的交互模型，考察了不同生产情景下社会资本效用的差异性以及村庄非农化过程对其产生的影响。研究表明：在微观层面，家庭社会网络规模的扩张能够同时提高农业收入和非农收入，而社会网络结构异质性的提高只有利于非农收入的增长；并且随着村庄非农化程度的提高，社会网络的效应对于农业收入逐步减弱，而对于非农收入的影响则逐步增强。在宏观层面，村庄社会融合程度的提高仅有利于农民农业收入的增长，但随着非农化进程的推进，村庄集体社会资本在农业生产中所凸显的优势将会逐渐削弱。这预示着，中国农村非农经济的迅猛发展正逐步改变乡村社会资本的经济意涵。     

Fast and approximate exhaustive variable selection for generalised linear models with APES

We present APproximated Exhaustive Search (APES), which enables fast and approximated exhaustive variable selection in Generalised Linear Models (GLMs). While exhaustive variable selection remains as the gold standard in many model selection contexts, traditional exhaustive variable selection suffers from computational feasibility issues. More precisely, there is often a high cost associated with computing maximum likelihood estimates (MLE) for all subsets of GLMs. Efficient algorithms for exhaustive searches exist for linear models, most notably the leaps‐and‐bound algorithm and, more recently, the mixed integer optimisation (MIO) algorithm. The APES method learns from observational weights in a generalised linear regression super‐model and reformulates the GLM problem as a linear regression problem. In this way, APES can approximate a true exhaustive search in the original GLM space. Where exhaustive variable selection is not computationally feasible, we propose a best‐subset search, which also closely approximates a true exhaustive search. APES is made available in both as a standalone R package as well as part of the already existing mplot package.     

宋代閤职的内外演变与磨勘叙迁探析

宋代共设有三等閤职，最初供职于閤门，后閤职官员出外任职情况变得普遍，直接推动了外任武官兼带閤职制度的发展，此后閤职作为武官兼带的一种职名，成为奖励军功以及控制武官的一种有效手段。而閤职制度的发展也使閤职作为武臣清选的地位逐渐确立，表现之一就是在磨勘叙迁上较一般武官而言具有一定的优越性。同时，内外不同的閤职在磨勘制度上也有一定的差异，这些差异的产生也加深了閤职作为武臣清选的内涵。     

挣脱生态牢笼的路径探幽——《共产党宣言》中马克思生态思想解读

《共产党宣言》蕴含着深刻的生态思想,其体系以人、社会、自然整体为背景,其核心观点认为生态问题是由资本主义生产方式引起的.马克思在唯物史观视野下,科学论证了资产阶级的所有制必然灭亡、共产主义必然实现的历史发展逻辑,廓清了人与人、人与自然之间双重和解的演化路径.其中关于科技提升、市场拓展、交通和通信发展等引起世界市场“生态扩张”的思想,对全球化程度日益加深境况下“生态文明”和“人类命运共同体”的构建具有重大的理论和实践指导价值.     

嵌套并联结构两阶段DEA下科技创新效率测度与分解

目前有许多研究将两阶段DEA模型应用到科技创新活动当中，一般将创新活动分为研发和转化两个阶段，为了进一步探讨不同转移转化方式下科技成果的转化效率以获得更多的详细信息，本文拓展了传统的两阶段DEA模型，考虑了嵌套并联结构的两阶段网络DEA模型，将科技创新活动分为科技成果研发阶段和科技成果转化阶段，并将科技成果转化阶段分为内部转化和外部转化两个并联子系统。本文选取14家中科院院属单位作为被评价对象，应用加权加法分解方法计算整体效率和各阶段子效率。通过将本文模型与传统两阶段模型进行对比发现，传统模型会低估科技成果转化效率。结果表明：整体科技创新效率均值偏低，科技成果研发效率均值高于科技成果转化效率均值，科技成果转化效率仍有很大的提升空间。科技成果转化阶段中内部转化效率普遍较高但是外部转化效率普遍较低，较低的外部转化效率是导致科技成果转化效率低下的主要原因。最后，本文将所有被评价单位分为四类机构，分析提高科技创新效率的实现路径，可以通过重点突破模式和渐进突破模式来实现整体效率的提高。     

基于债务协商视角的债转股定量研究

针对我国政府、企业和银行等金融机构共同关注的债转股问题，基于债务协商谈判思想，建立部分债务股权互换模型，计算公司证券价格，探讨了债转股对公司价值、破产概率、破产损失成本和资本结构的影响，给出了银行等债权人愿意债转股的充分条件。结果表明：在事先破产清算协议贷款下，事后全部债转股总能提高公司股权价值，但并不一定能提高债券价值。只有其协商谈判能力满足一定条件，公司债权人才愿意事后选择债转股，实现帕累托改进、提高社会福利水平。其次，在公司股东协商谈判能力的一定范围内，部分债转股能提高公司价值，其最优转股债息比例随着公司资产风险的增大而增加。再次，债转股能降低公司破产风险和破产损失成本，但同时也提高了债券风险溢价。最后，随着股东谈判能力增强，最优协商转股债务比例、杠杆率都减少，而债券风险溢价增大。本文所得结果对我国政府、企业和银行如何实施债转股提供理论参考和实践指导。