Perception of Climate Risk among Rural Farmers in Vietnam: Consistency within Households and with the Empirical Record

Rural farmers in Vietnamese communes perceive climate risk and potential impacts on livelihood within a complex context that may influence individual and household decisions. In a primary survey of 1,145 residents of the Thach Ha district of Ha Tinh province, we gathered data regarding perception about stability in climate, potential risks to livelihood, demographic characteristics, orientation toward risk, and interest in expanding economic activity. Temporal analysis of meteorological and economic indicator data forms an empirical basis for comparison with human perception. We ask the basic question: Are rural farmers’ perceptions of climate consistent with the historical record and reproducible within households? We find that respondents do perceive climate anomalies, with some anchoring on recent extreme events as revealed by climate observational data, and further that spouses disproportionately share perceptions relative to randomly simulated pairings. To put climate‐related risk perception in a larger context, we examine patterns across a range of risks to livelihood faced by farmers (livestock disease, pests, markets, health), using dimension reduction techniques. We find that our respondents distinguish among potential causes of low economic productivity, with substantial emphasis on climate‐related impacts. They do not express uniform concern across risks, but rather average patterns reveal common modes and distinguish climate concern. Still, among those expressing concern about climate‐related risks to livelihood we do not find an association with expressed intention to pursue changes in economic activity as a risk management response.     

产融结合退出及影响因素分析——基于参股非上市金融公司视角的实证研究

以2007—2014年发生的我国A股上市公司参股非上市金融公司事件作为研究样本，对企业退出产融结合的现象进行了探讨，实证结果表明：每股收益越低、资产负债率越高、协同费用率越高、产融结合年限越短，企业越有可能退出产融结合。研究能帮助企业在实施产融结合后更有针对性地关注自身运营状况和财务状况，也为其建立健全风险监督与防范机制提供了一定的政策支持。     

数字化生存的道德风险与信息崇拜的伦理考辨

当代人尤其是青年人面临诸多现实世界中自我难以解决的矛盾和困惑时,期许能在电子＂伊甸园＂中找回自我价值和精神皈依。然而,虚拟空间并非想象中的天堂,类似＂面具＂的交流形式遮蔽着许多本真的存在,消解了现实世界的核心价值;游离在虚拟和现实之间的自我与社会脱离;对网络的过渡依赖性导致人格的异化;方向感的迷茫和自我定位的偏差,使得价值追求从崇高滑向流俗甚至恶俗。数字化生存方式正颠覆着传统生活方式和现实生活世界的诸多价值标准,而信息崇拜的推波助澜,更使人们产生了一种莫名的幸福被剥夺的感觉。     

国外巨灾保险体制对中国的启示

中国长期受到自然灾害的困扰,建立适合国情的巨灾保险体制已经成为必然。分析中国巨灾保险在供给和需求两方面均呈现不足状态的原因,借鉴国际上巨灾保险体制发展较好国家的经验,认为建立完善的巨灾保险体制需要从建立完备的法律体系、发展繁荣的巨灾保险市场和培养多层次的巨灾风险管理体系几个方面入手。从目前情况来看,应该从建立完善的法律体系、发展再保险市场、建立巨灾风险基金和发展政府巨灾债券几个方面着手,建设多层次的、适合中国国情的巨灾保险体制。     

Risk Perception and Information Processing: The Development and Validation of a Questionnaire to Assess Self‐Reported Information Processing

The role of information processing in understanding people's responses to risk information has recently received substantial attention. One limitation of this research concerns the unavailability of a validated questionnaire of information processing. This article presents two studies in which we describe the development and validation of the Information‐Processing Questionnaire to meet that need. Study 1 describes the development and initial validation of the questionnaire. Participants were randomized to either a systematic processing or a heuristic processing condition after which they completed a manipulation check and the initial 15‐item questionnaire and again two weeks later. The questionnaire was subjected to factor reliability and validity analyses on both measurement times for purposes of cross‐validation of the results. A two‐factor solution was observed representing a systematic processing and a heuristic processing subscale. The resulting scale showed good reliability and validity, with the systematic condition scoring significantly higher on the systematic subscale and the heuristic processing condition significantly higher on the heuristic subscale. Study 2 sought to further validate the questionnaire in a field study. Results of the second study corresponded with those of Study 1 and provided further evidence of the validity of the Information‐Processing Questionnaire. The availability of this information‐processing scale will be a valuable asset for future research and may provide researchers with new research opportunities.     

Pollutant Ground Concentrations of Nonneutrally Buoyant Particles

A methodology is suggested for the estimation of the mass density and the cumulative ground deposition of a nonvolatile, nonneutrally buoyant, air pollutant (liquid or solid) released from a polluted column (following an explosion caused during routine operation in, e.g., the chemical industry or due to any kind of hostile act) and deposited on the ground via gravitational settling. In many cases, the deposited mass due to gravitational settling constitutes a significant fraction of the original inventory released from the source. Implementation of the methodology in preliminary risk assessments can serve as an efficient tool for emergency planning for both immediate and long‐term measures such as evacuation and decontamination. The methodology considers, inter alia, an estimation of the critical particle diameter, particle size, and mass distributions along the polluted column. This methodology was developed to apply in rural regions since proper application of relevant meteorological input data can be accomplished mainly for such areas.     

An Ecological Model for Quantitative Risk Assessment for Schistosomiasis: The Case of a Patchy Environment in the Coastal Tropical Area of Northeastern Brazil

We developed a stochastic model for quantitative risk assessment for the Schistosoma mansoni (SM) parasite, which causes an endemic disease of public concern. The model provides answers in a useful format for public health decisions, uses data and expert opinion, and can be applied to any landscape where the snail Biomphalaria glabrata is the main intermediate host (South and Central America, the Caribbean, and Africa). It incorporates several realistic and case‐specific features: stage‐structured parasite populations, periodic praziquantel (PZQ) drug treatment for humans, density dependence, extreme events (prolonged rainfall), site‐specific sanitation quality, environmental stochasticity, monthly rainfall variation, uncertainty in parameters, and spatial dynamics. We parameterize the model through a real‐world application in the district of Porto de Galinhas (PG), one of the main touristic destinations in Brazil, where previous studies identified four parasite populations within the metapopulation. The results provide a good approximation of the dynamics of the system and are in agreement with our field observations, i.e., the lack of basic infrastructure (sanitation level and health programs) makes PG a suitable habitat for the persistence and growth of a parasite metapopulation. We quantify the risk of SM metapopulation explosion and quasi‐extinction and the time to metapopulation explosion and quasi‐extinction. We evaluate the sensitivity of the results under varying scenarios of future periodic PZQ treatment (based on the Brazilian Ministry of Health's plan) and sanitation quality. We conclude that the plan might be useful to slow SM metapopulation growth but not to control it. Additional investments in better sanitation are necessary.     

Evaluation of Inhaled Versus Deposited Dose Using the Exponential Dose‐Response Model for Inhalational Anthrax in Nonhuman Primate,Rabbit, and Guinea Pig

The application of the exponential model is extended by the inclusion of new nonhuman primate (NHP), rabbit, and guinea pig dose‐lethality data for inhalation anthrax. Because deposition is a critical step in the initiation of inhalation anthrax, inhaled doses may not provide the most accurate cross‐species comparison. For this reason, species‐specific deposition factors were derived to translate inhaled dose to deposited dose. Four NHP, three rabbit, and two guinea pig data sets were utilized. Results from species‐specific pooling analysis suggested all four NHP data sets could be pooled into a single NHP data set, which was also true for the rabbit and guinea pig data sets. The three species‐specific pooled data sets could not be combined into a single generic mammalian data set. For inhaled dose, NHPs were the most sensitive (relative lowest LD₅₀) species and rabbits the least. Improved inhaled LD₅₀s proposed for use in risk assessment are 50,600, 102,600, and 70,800 inhaled spores for NHP, rabbit, and guinea pig, respectively. Lung deposition factors were estimated for each species using published deposition data from Bacillus spore exposures, particle deposition studies, and computer modeling. Deposition was estimated at 22%, 9%, and 30% of the inhaled dose for NHP, rabbit, and guinea pig, respectively. When the inhaled dose was adjusted to reflect deposited dose, the rabbit animal model appears the most sensitive with the guinea pig the least sensitive species.     

Minimization of passenger takeoff and landing risk in offshore helicopter transportation: Models,approaches and analysis

Offshore petroleum industry uses helicopters to transport the employees to and from installations. Takeoff and landing represent a substantial part of the flight risks for passengers. In this paper, we propose and analyze approaches to create a safe flight schedule to perform pickup of employees by several independent flights. Two scenarios are considered. Under the non-split scenario, exactly one visit is allowed to each installation. Under the split scenario, the pickup demand of an installation can be split between several flights. Interesting links between our problem and other problems of combinatorial optimization, e.g., parallel machine scheduling and bin-packing are established. We provide worst-case analysis of the performance of some of our algorithms and report the results of computational experiments conducted on randomly generated instances based on the real sets of installations in the oil fields on the Norwegian continental shelf. This paper is the first attempt to handle takeoff and landing risk in a flight schedule that consists of several flights and lays ground for the study on more advanced and practically relevant models.     

Sensitivity Analysis Using Risk Measures

In a quantitative model with uncertain inputs, the uncertainty of the output can be summarized by a risk measure. We propose a sensitivity analysis method based on derivatives of the output risk measure, in the direction of model inputs. This produces a global sensitivity measure, explicitly linking sensitivity and uncertainty analyses. We focus on the case of distortion risk measures, defined as weighted averages of output percentiles, and prove a representation of the sensitivity measure that can be evaluated on a Monte Carlo sample, as a weighted average of gradients over the input space. When the analytical model is unknown or hard to work with, nonparametric techniques are used for gradient estimation. This process is demonstrated through the example of a nonlinear insurance loss model. Furthermore, the proposed framework is extended in order to measure sensitivity to constant model parameters, uncertain statistical parameters, and random factors driving dependence between model inputs.