Multiobjective Prioritization Methodology and Decision Support System for Evaluating Inventory Enhancement Strategies for Disrupted Interdependent Sectors

Disruptions in the production of commodities and services resulting from disasters influence the vital functions of infrastructure and economic sectors within a region. The interdependencies inherent among these sectors trigger the faster propagation of disaster consequences that are often associated with a wider range of inoperability and amplified losses. This article evaluates the impact of inventory‐enhanced policies for disrupted interdependent sectors to improve the disaster preparedness capability of dynamic inoperability input‐output models (DIIM). In this article, we develop the dynamic cross‐prioritization plot (DCPP)—a prioritization methodology capable of identifying and dynamically updating the critical sectors based on preference assignments to different objectives. The DCPP integrates the risk assessment metrics (e.g., economic loss and inoperability), which are independently analyzed in the DIIM. We develop a computer‐based DCPP tool to determine the priority for inventory enhancement with user preference and resource availability as new dimensions. A baseline inventory case for the state of Virginia revealed a high concentration of (i) manufacturing sectors under the inoperability objective and (ii) service sectors under the economic loss objective. Simulation of enhanced inventory policies for selected critical manufacturing sectors has reduced the recovery period by approximately four days and the expected total economic loss by $33 million. Although the article focuses on enhancing inventory levels in manufacturing sectors, complementary analysis is recommended to manage the resilience of the service sectors. The flexibility of the proposed DCPP as a decision support tool can also be extended to accommodate analysis in other regions and disaster scenarios.     

Confidence distributions applied to propagating uncertainty to inference based on estimating the local false discovery rate: A fiducial continuum from confidence sets to empirical Bayes set estimates as the number of comparisons increases

Empirical Bayes estimates of the local false discovery rate can reflect uncertainty about the estimated prior by supplementing their Bayesian posterior probabilities with confidence levels as posterior probabilities. This use of coherent fiducial inference with hierarchical models generates set estimators that propagate uncertainty to varying degrees. Some of the set estimates approach estimates from plug-in empirical Bayes methods for high numbers of comparisons and can come close to the usual confidence sets given a sufficiently low number of comparisons.     

Can Psychosocial Intervention Improve Peer and Sibling Relations Among War‐affected Children? Impact and Mediating Analyses in a Randomized Controlled Trial

Social resources are considered important protectors in traumatic conditions, but few studies have analyzed their role in psychosocial interventions among war‐affected children. We examined (1) whether a psychosocial intervention (teaching recovery techniques, TRT) is effective in improving peer and sibling relations, and (2) whether these potentially improved relations mediate the intervention's impacts on children's mental health. Participants were 428 Palestinian children [10–13 (mean = 11.29, standard deviation SD = .68)‐year‐old girls (49.4 percent) and boys (50.6 percent)], who were cluster‐randomized into the TRT and wait‐list control groups. They reported the quality of peer (friendship and loneliness) and sibling (intimacy, warmth, conflict, and rivalry) relations, and posttraumatic stress, depressive and psychological distress symptoms, as well as psychosocial well‐being at baseline (T1), postintervention (T2), and six month follow‐up (T3). Results showed gender‐specific TRT intervention effects: Loneliness in peer relations reduced among boys and sibling rivalry reduced among girls. The TRT prevented the increase in sibling conflict that happened in the control group. The mediating hypothesis was partially substantiated for improved peer relations, and beneficial changes in sibling relations were generally associated with improved mental health.     

Generalizing the standardized hazard ratio to multivariate proportional hazards regression,with an application to clinical~genomic studies

The standardized hazard ratio for univariate proportional hazards regression is generalized as a scalar to multivariate proportional hazards regression. Estimators of the standardized log hazard ratio are developed, with corrections for bias and for regression to the mean in high-dimensional analyses. Tests of point and interval null hypotheses and confidence intervals are constructed. Cohort sampling study designs, commonly used in prospective–retrospective clinical genomic studies, are accommodated.     

Q-LEARNING WITH CENSORED DATA

We develop methodology for a multistage-decision problem with flexible number of stages in which the rewards are survival times that are subject to censoring. We present a novel Q-learning algorithm that is adjusted for censored data and allows a flexible number of stages. We provide finite sample bounds on the generalization error of the policy learned by the algorithm, and show that when the optimal Q-function belongs to the approximation space, the expected survival time for policies obtained by the algorithm converges to that of the optimal policy. We simulate a multistage clinical trial with flexible number of stages and apply the proposed censored-Q-learning algorithm to find individualized treatment regimens. The methodology presented in this paper has implications in the design of personalized medicine trials in cancer and in other life-threatening diseases.     

For compassion or money? The factors influencing the funding of micro loans

Aided by the Internet, microfinance institutions have found new ways to expand the reach of financing entrepreneurial projects on a small scale. Using a unique data set of individual loans posted to Kiva.org, we explore the determinants of lenders’ nonprofit lending choices in the growing microfinance industry. We find that lenders make choices in purposive ways even in the absence of market interest rates, especially with respect to the demographic characteristics of borrowers and the uses of proposed funds. Hence, the results provide valuable new information about consumer choice in charitable giving and investment.     

SOS—Satisfied or Stuck,Why Older Rural Residents Stay Put: Aging in Place or Stuck in Place in Rural Utah*

As rural communities undergo substantial demographic and economic changes, understanding the migration intentions and their antecedents of rural elderly persons becomes increasingly important. Using data drawn from a survey of adults from 24 rural Utah communities conducted in 2008, we examine whether rural residents 60 years of age or older plan to remain in their present communities (N= 621). We use structural equation models (SEM) to estimate the relationships between a variety of individual and community-level background measures, including perceptions of local service quality, leaving one's community for health care, Internet use, attachment to and satisfaction with community, and plans to age in place. Results suggest that even as the rural context of economic decline, population loss, and distance to medical services may reduce the viability of staying in a community, a desire to remain in the community is primarily a function of perceptions of the quality of local services and community satisfaction. This research highlights the need to better understand the interplay between the availability of medical services and perceptions of distance as well as to understand the complex relationship between individual and community level characteristics for migration intentions.     

Bayesian Design of Special Type of Double Sampling Plans for Compliance Testing

Bayesian acceptance sampling plans, which utilize prior information on the process variation, can be employed as an alternative to conventional types of plans for taking decisions on the disposition of submitted lots. A special type of double sampling inspection plans by attributes with small acceptance numbers using Bayesian methodology is presented in this paper emphasizing its significance over small acceptance number single sampling plans. The procedures for designing such sampling plans for specified degree of discrimination which would ensure protection to the producer and consumer are discussed with illustrations under the conditions for the application of gamma-Poisson distribution.     

Depressive Symptoms,Acute Alcohol Intoxication,and Risk Rationale Effects on Men’s Condom Use Resistance

This study examined the role of depressive symptoms, acute intoxication, and risk rationale in men’s use of condom use resistance (CUR) tactics in an experimental study. Participants included 313 heterosexual male, nonproblem drinkers, ages 21 to 30. Participants were randomized to one of four beverage conditions: no alcohol, placebo, low (.04%) alcohol dose, or high (.08%) alcohol dose. They read an eroticized scenario depicting a consensual sexual encounter with a female partner who requested a condom to prevent either pregnancy or sexually transmitted infections (STIs) (risk rationale) and then indicated their intentions to use 10 different CUR tactics. Hypotheses related to the pharmacological, dosage, and expectancy effects of alcohol were tested in a generalized linear model. In intoxicated (.04% and .08%) men who were given a pregnancy risk rationale, depressive symptoms were associated with stronger intentions to use CUR tactics than in sober (control and placebo) men. Men who received a high alcohol dose (.08%) and who were given a pregnancy risk rationale reported higher intentions to use CUR tactics than those who received a lower alcohol dose (.04%). Findings suggest that the pharmacological effects of alcohol on men’s likelihood to resist condoms vary by the saliency of the risk rationale and mood-related variables.     

The effect of natural disaster on fertility,birth spacing,and child sex ratio: evidence from a major earthquake in India

Natural disasters can lead to significant changes in health, economic, and demographic outcomes. However, the demographic effects of earthquakes have been studied only to a limited degree. This paper examines the effect of the 2001 Gujarat earthquake on reproductive outcomes. This earthquake killed more than 20,000 people; injured 167,000; and caused massive losses to property and civic assets. Using data from two large-scale District-Level Household Surveys (2002–2004 and 2007–2008), we employ difference-in-difference and fixed-effect regression models to compare the outcomes across earthquake-affected districts and their neighboring districts during 5 years before and after the earthquake. We find that the earthquake led to significant rises in childbirth rates. It also reduced birth spacing among uneducated, tribal, and Muslim women, and the incidence of male births among rural women. We find considerable variation in the demographic effects of the earthquake across location, household socioeconomic status, and parental age and education.