Flood Catastrophe Model for Designing Optimal Flood Insurance Program: Estimating Location‐Specific Premiums in the Netherlands

As flood risks grow worldwide, a well‐designed insurance program engaging various stakeholders becomes a vital instrument in flood risk management. The main challenge concerns the applicability of standard approaches for calculating insurance premiums of rare catastrophic losses. This article focuses on the design of a flood‐loss‐sharing program involving private insurance based on location‐specific exposures. The analysis is guided by a developed integrated catastrophe risk management (ICRM) model consisting of a GIS‐based flood model and a stochastic optimization procedure with respect to location‐specific risk exposures. To achieve the stability and robustness of the program towards floods with various recurrences, the ICRM uses stochastic optimization procedure, which relies on quantile‐related risk functions of a systemic insolvency involving overpayments and underpayments of the stakeholders. Two alternative ways of calculating insurance premiums are compared: the robust derived with the ICRM and the traditional average annual loss approach. The applicability of the proposed model is illustrated in a case study of a Rotterdam area outside the main flood protection system in the Netherlands. Our numerical experiments demonstrate essential advantages of the robust premiums, namely, that they: (1) guarantee the program's solvency under all relevant flood scenarios rather than one average event; (2) establish a tradeoff between the security of the program and the welfare of locations; and (3) decrease the need for other risk transfer and risk reduction measures.     

Social influences on sorority and fraternity member smoking

Objective: To understand how the Greek system uniquely influences smoking attitudes, beliefs, and behaviors among college students who belong to a social sorority or fraternity. Participants: Active members of sororities (n = 16) and fraternities (n = 17) were interviewed between February 2013 and October 2015. Methods: In-depth interviews were conducted examining the social influences of the Greek system on member smoking. Transcribed interviews were coded and analyzed for themes. Results: Sorority and fraternity members experienced different social influences on smoking. Sorority stigmatization of smoking outside bars or parties caused sorority members to hide their smoking. Fraternity members had no social penalties for smoking and allowed smoking at the fraternity house. Fraternity members influenced both fraternity members and sorority members to smoke by sharing cigarettes and smoking at parties. Conclusions: Sororities and fraternities have created social environments that both promote smoking and stigmatize it, presenting unique challenges in college student smoking prevention and cessation efforts.     

‘There is always this feeling of otherness’: exploring the lived experiences of visually impaired immigrant women in Canada

This paper explores the experiences of immigrant women with visual impairment in the Greater Toronto and Hamilton Area (GTHA) of Canada. Conceptually, the paper draws from feminist disability theory and critical scholarship on blindness to consider the discursive and material processes shaping women’s experiences across different socio-cultural contexts. Empirically, the paper draws from in-depth interviews with seven women. The analysis is organized around three themes. The first explores women’s understandings of visual impairment. The second examines the ways in which women’s experiences of visual impairment are shaped by meanings and attitudes that circulate within their cultural communities, and the extent to which immigration might challenge or reinforce these meanings. The third examines the shifting barriers and opportunities women face with respect to social and economic participation. We close by identifying the conceptual implications of our research.     

Student and faculty perceptions about mandatory influenza vaccinations on a health sciences campus

Objective: To examine the perceptions among faculty and health professional students regarding mandatory vaccination policies on a health sciences campus. Participants: A total of 296 faculty and 244 students completed surveys during Fall 2015. Methods: The online survey administered to individuals who received the influenza vaccine during the fall 2015 influenza vaccination clinic season included five items evaluating perceptions of employer mandatory vaccination requirements. Results: Chi-square analysis indicated that although faculty and students agree mandatory vaccinations in a health care environment are appropriate, faculty are more likely than students to get vaccinated in the absence of a mandate. Additionally, a small fraction of faculty would consider employment elsewhere when facing this mandate. Conclusions: Overall, faculty and students had favorable perceptions about mandatory influenza vaccine policies. Since students were less likely to be vaccinated in the absence of a mandate, education of students should be improved to support the importance of vaccinations in a health care environment.     

Can We Perceive Near Miss? An Empirical Study

Near misses are a special kind of reinforcement which increases one’s desire to play. The aim of this paper is to examine the perception of near misses in normal population. We used a slot machine simulation running on a PC, where participants had to play four rounds with different near miss ratios (0, 15, 30 and 45%). Our sample consisted of 159 individuals with mean age of 22.8 and with no or little gambling experience. For data analysis we used chi-squared goodness-of-fit test and exact binomial test. Despite the fact, that there was a notable effect of near misses results showed that the subjects could not perceive trials of them.     

Using In Vitro High‐Throughput Screening Data for Predicting Benzo[k]Fluoranthene Human Health Hazards

Today there are more than 80,000 chemicals in commerce and the environment. The potential human health risks are unknown for the vast majority of these chemicals as they lack human health risk assessments, toxicity reference values, and risk screening values. We aim to use computational toxicology and quantitative high‐throughput screening (qHTS) technologies to fill these data gaps, and begin to prioritize these chemicals for additional assessment. In this pilot, we demonstrate how we were able to identify that benzo[k]fluoranthene may induce DNA damage and steatosis using qHTS data and two separate adverse outcome pathways (AOPs). We also demonstrate how bootstrap natural spline‐based meta‐regression can be used to integrate data across multiple assay replicates to generate a concentration–response curve. We used this analysis to calculate an in vitro point of departure of 0.751 μM and risk‐specific in vitro concentrations of 0.29 μM and 0.28 μM for 1:1,000 and 1:10,000 risk, respectively, for DNA damage. Based on the available evidence, and considering that only a single HSD17B4 assay is available, we have low overall confidence in the steatosis hazard identification. This case study suggests that coupling qHTS assays with AOPs and ontologies will facilitate hazard identification. Combining this with quantitative evidence integration methods, such as bootstrap meta‐regression, may allow risk assessors to identify points of departure and risk‐specific internal/in vitro concentrations. These results are sufficient to prioritize the chemicals; however, in the longer term we will need to estimate external doses for risk screening purposes, such as through margin of exposure methods.     

On the survival time of a repairable duplex system sustained by a cold standby unit subjected to a priority rule

We analyze the survival time of a general duplex system sustained by a cold standby unit subjected to a priority rule. The analysis is based on advanced complex function theory (sectionally holomorphic functions). As an example, we consider Weibull–Gnedenko and Erlang distributions for failure and repair. Several graphs are displaying the survival function.     

Convergence rates for uniform confidence intervals based on local polynomial regression estimators

We investigate the convergence rates of uniform bias-corrected confidence intervals for a smooth curve using local polynomial regression for both the interior and boundary region. We discuss the cases when the degree of the polynomial is odd and even. The uniform confidence intervals are based on the volume-of-tube formula modified for biased estimators. We empirically show that the proposed uniform confidence intervals attain, at least approximately, nominal coverage. Finally, we investigate the performance of the volume-of-tube based confidence intervals for independent non-Gaussian errors.