Evaluating and Visualizing the Economic Impact of Commercial Districts Due to an Electric Power Network Disruption

Critical infrastructure networks enable social behavior, economic productivity, and the way of life of communities. Disruptions to these cyber–physical–social networks highlight their importance. Recent disruptions caused by natural phenomena, including Hurricanes Harvey and Irma in 2017, have particularly demonstrated the importance of functioning electric power networks. Assessing the economic impact (EI) of electricity outages after a service disruption is a challenging task, particularly when interruption costs vary by the type of electric power use (e.g., residential, commercial, industrial). In contrast with most of the literature, this work proposes an approach to spatially evaluate EIs of disruptions to particular components of the electric power network, thus enabling resilience‐based preparedness planning from economic and community perspectives. Our contribution is a mix‐method approach that combines EI evaluation, component importance analysis, and GIS visualization for decision making. We integrate geographic information systems and an economic evaluation of sporadic electric power outages to provide a tool to assist with prioritizing restoration of power in commercial areas that have the largest impact. By making use of public data describing commercial market value, gross domestic product, and electric area distribution, this article proposes a method to evaluate the EI experienced by commercial districts. A geospatial visualization is presented to observe and compare the areas that are more vulnerable in terms of EI based on the areas covered by each distribution substation. Additionally, a heat map is developed to observe the behavior of disrupted substations to determine the important component exhibiting the highest EI. The proposed resilience analytics approach is applied to analyze outages of substations in the boroughs of New York City.     

R package rjmcmc: reversible jump MCMC using post‐processing

The rjmcmc package for R implements the post‐processing reversible jump Markov chain Monte Carlo (MCMC) algorithm of Barker & Link. MCMC output from each of the models is used to estimate posterior model probabilities and Bayes factors. Automatic differentiation is used to simplify implementation. The package is demonstrated on two examples.     

Electronic support groups, patient-consumers, and medicalization: the case of contested illness

This article illustrates the role electronic support groups play in consumer-driven medicalization. The analysis is based on an observational study of a year in the life of an electronic support group for sufferers of the contested illness fibromyalgia syndrome. The analysis builds on and extends scholarship concerning the growing influence of lay expertise in the context of medical uncertainty by showing how the dominant beliefs and routine practices of this electronic community simultaneously (and paradoxically) challenge the expertise of physicians and encourage the expansion of medicine's jurisdiction. Drawing on their shared embodied expertise, participants confirm the medical character of their problem and its remedy, and they empower each other to search for physicians who will recognize and treat their condition accordingly. Physician compliance is introduced as a useful concept for understanding the relationship between lay expertise, patient-consumer demand, and contemporary (and future) instances of medicalization.     

Frederick Douglass and Black Abolitionism

Frederick Douglass. WILLIAM S. McFEELY. New York and London: W. W. Norton & Company. 1991. xiii, 465 pp.

Frederick Douglass: New Literary and Historical Essays. ERIC J. SUNDQUIST (ed.). Cambridge: Cambridge University Press. 1990. vi, 295 pp.

The Frederick Douglass Papers: Series One: Speeches, Debates and Interviews, Volume 4: 1864–80. JOHN W. BLASSINGAME and JOHN R. McKIVIGAN (eds.). New Haven and London: Yale University Press. 1991. xxxvii, 663 pp.

The Black Abolitionist Papers. Volume 4: The United States, 1847–1858. C. PETER RIPLEY (ed.). Chapel Hill and London: The University of North Carolina Press. 1991. xxvi, 443 pp.

The Black Abolitionist Papers. Volume 5: The United States, 1859–1865. C. PETER RIPLEY (ed.). Chapel Hill and London: The University of North Carolina Press. 1992. xiii, 435 pp.     

Adaptation and Evaluation of a Group Curriculum for Latino Clients in a Driving Under the Influence Program

The purpose of this study was to describe the process of culturally adapting group curriculum modules for Spanish speaking clients in a Driving Under the Influence Program as well as to test the acceptability of these modules. Using the Group Topics Evaluation Scale (English and Spanish version), 90 clients rated six modules that were presented in 30 different group sessions. Spanish speaking clients were significantly more likely to rate all six modules much higher than their English speaking counterparts, indicating acceptability. This is important as driving-under-the-influence programs may provide access to Latino clients not seen elsewhere. Possible further research is discussed.     

Environmental issues affecting elder abuse victims in their reception of community based services

This study examined the dominant factors that predict the utilization of services by 129 identified elder abuse victims who reside in the community. Utilizing the Andersen Model, services accepted or rejected were analyzed from individual, family and environmental perspectives. Results indicated that service utilization is related to three "need" factors: (1) Victim has cognitive and ADL impairments, (2) Victim has poor health status (self rated), and (3) The abuser is financially dependent on the victim and is also the primary caregiver of the victim. "Enabling" factor (1) Victim lives alone. "Predisposing" factors (1) Abuser is substance abuser and (2) Abuser is female. A great proportion of the elder abuse victims in this study accepted services from an agency that provided a single entry point into the service system and had highly trained personnel utilizing a case management approach.     

Exploratory method for summarizing concomitant medication data – the mean cumulative function

Concomitant Medications are medications used by patients in a clinical trial, other than the investigational drug. These data are routinely collected in clinical trials. The data are usually collected in a longitudinal manner, for the duration of patients' participation in the trial. The routine summaries of this data are incidence‐type, describing whether or not a medication was ever administered during the study. The longitudinal aspect of the data is essentially ignored. The aim of this article is to suggest exploratory methods for graphically displaying the longitudinal features of the data using a well‐established estimator called the ‘mean cumulative function’. This estimator permits summary and a graphical display of the data, and preparation of some statistical tests to compare between groups. This estimator may also incorporate information on censoring of patient data. Copyright © 2009 John Wiley & Sons, Ltd.