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.     

Latin American convergence and divergence towards the mortality profiles of developed countries

It is uncertain whether Latin America and Caribbean (LAC) countries are approaching a single mortality regime. Over the last three decades, LAC has experienced major public health interventions and the highest number of homicides in the world. However, these interventions and homicide rates are not evenly shared across countries. This study documents trends in life expectancy and lifespan variability for 20 LAC countries, 2000–14. By extending a previous method, we decompose differences in lifespan variability between LAC and a developed world benchmark into cause-specific effects. For both sexes, dispersion of amenable diseases through the age span makes the largest contribution to the gap between LAC and the benchmark. Additionally, for males, the concentration of homicides, accidents, and suicides in mid-life further impedes mortality convergence. Great disparity exists in the region: while some countries are rapidly approaching the developed regime, others remain far behind and suffer a clear disadvantage in population health.     

Cooperative innovation through a talent management pool: A qualitative study on coopetition in healthcare

In recent years, the Dutch healthcare sector has been confronted with increased competition. Not only are financial resources scarce, Dutch hospitals also need to compete with other hospitals in the same geographic area to attract and retain talented employees due to considerable labour shortages. However, four hospitals operating in the same region are cooperating to cope with these shortages by developing a joint Talent Management Pool. ‘Coopetiton’ is a concept used for simultaneous cooperation and competition. In this paper, a case study is performed in order to enhance our understanding of coopetition. Among other things, the findings suggest that perceptions of organizational actors on competition differ and might hinder cooperative innovation with competitors, while perceived shared problems and resource constraints stimulate coopetition. We reflect on the current coopetition literature in light of the research findings, which have implications for future research on this topic.     

经济新常态下产业园区的发展趋势

经济发展进入到一个新常态,向形态更高级、分工更复杂、结构更合理的阶段转换。在这个过程中,产业园区的发展可能就是形态更加高级,内部分工可能更加复杂,整个结构可能更加趋向合理和科学的发展方式。在经济新常态下,产业园区发展会出现一些新特点和新趋势:第一,从量的快速扩张向质的提升转变;第二,土地资源驱动园区发展模式的转换;第三,园区的产业链式和集群化的发展趋势;第四,产业园区要素与城区功能结合整合的趋势;第五,创新型科技园区加快建设和发展趋势;第六,生态化园区进一步发展趋势;第七,多样化园区融资体系探索和创新模式;第八,自由贸易园区的探索和发展。     

The Abject Embodiment of Cancer Patients: Dignity,Selfhood, and the Grotesque Body

The body is the empirical quintessence of the self. Because selfhood is symbolic, embodiment represents the personification and materialization of otherwise invisible qualities of personhood. The body and experiences of embodiment are central to our sense of being, who we think we are, and what others attribute to us. What happens, then, when one's body is humiliating? How does the self handle the implications of a gruesome body? How do people manage selfhood in light of grotesque physical appearances? This study explores these questions in the experiences of dying cancer patients and seeks to better understand relationships among body, self, and situated social interaction.     

Computing maximum likelihood estimates from type II doubly censored exponential data

It is well-known that, under Type II double censoring, the maximum likelihood (ML) estimators of the location and scale parameters, θ and δ, of a twoparameter exponential distribution are linear functions of the order statistics. In contrast, when θ is known, theML estimator of δ does not admit a closed form expression. It is shown, however, that theML estimator of the scale parameter exists and is unique. Moreover, it has good large-sample properties. In addition, sharp lower and upper bounds for this estimator are provided, which can serve as starting points for iterative interpolation methods such as regula falsi. Explicit expressions for the expected Fisher information and Cramér-Rao lower bound are also derived. In the Bayesian context, assuming an inverted gamma prior on δ, the uniqueness, boundedness and asymptotics of the highest posterior density estimator of δ can be deduced in a similar way. Finally, an illustrative example is included.     

我国西部地区生态环境存在的问题及对策

西部地区虽然经济欠发达,但在我国经济社会发展中占有重要位置。一方面西部地区是我国的重要能源基地,也是长江、澜沧江、黄河、黑河、珠江等大江大河的发源地和主要集水区;另一方面,西部地区野生动植物资源丰富,是我国许多珍稀野生动植物的主要栖息地。因此,西部地区的生态环境建设不仅对西部地区自身发     

浅析建筑市场监理运行现状与对策

文章透析了监理单位的外部管理现状 ,内部运行机制及监理业务的竞争环境 ,并提出了相应的对策与建议     

A Bayesian Adjustment for Covariate Misclassification with Correlated Binary Outcome Data

Estimated associations between an outcome variable and misclassified covariates tend to be biased when the methods of estimation that ignore the classification error are applied. Available methods to account for misclassification often require the use of a validation sample (i.e. a gold standard). In practice, however, such a gold standard may be unavailable or impractical. We propose a Bayesian approach to adjust for misclassification in a binary covariate in the random effect logistic model when a gold standard is not available. This Markov Chain Monte Carlo (MCMC) approach uses two imperfect measures of a dichotomous exposure under the assumptions of conditional independence and non-differential misclassification. A simulated numerical example and a real clinical example are given to illustrate the proposed approach. Our results suggest that the estimated log odds of inpatient care and the corresponding standard deviation are much larger in our proposed method compared with the models ignoring misclassification. Ignoring misclassification produces downwardly biased estimates and underestimate uncertainty.