The Study of Security and Separation:An Unexpected Forerunner of Attachment Theory?

John Bowlby's attachment theory has made a lasting contribution to scientific understanding of the nature and the impact of close interpersonal bonds, tracing their influence from early childhood through adulthood and into bereavement. The experience of separation and loss featured powerfully in Bowlby's account of the causes of mental health difficulties. He acknowledged many sources for his ideas. However, one potential intellectual force, namely, that of the eminent philosopher Bertrand Russell, is missing. The association between Bowlby and Russell is highlighted in this essay to illustrate how a monumental theory may emerge from ideas already around during a particular historical period. Scientific and personal features of their lives are explored to shed light on possible influence. Commonalities between their propositions about attachment are described as well as pertinent biographical details. Questions whether Bowlby was aware of Russell's writing on this topic and reasons why Russell's ideas were not acknowledged are considered

Once Upon a Virus: AIDS Legends and Vernacular Risk Perception

Once Upon a Virus explores how contemporary, or urban, legends are indicators of culturally complex attitudes toward health and illness. Tracing the rich tradition of AIDS legends in relation to current scholarship on belief, Diane Goldstein shows how such stories not only articulate widespread perceptions of risk, health care, and health policy, they also influence official and scientific approaches to the disease and its management. Notions that appear in narratives of who gets AIDS, how and why, are indicators of broad issues involving health beliefs, concerns, and needs.https://digitalcommons.usu.edu/usupress_pubs/1031/thumbnail.jp

Benchmarking of localization solutions : guidelines for the selection of evaluation points

Indoor localization solutions are key enablers for next-generation indoor navigation and track and tracing solutions. As a result, an increasing number of different localization algorithms have been proposed and evaluated in scientific literature. However, many of these publications do not accurately substantiate the used evaluation methods. In particular, many authors utilize a different number of evaluation points, but they do not (i) analyze if the number of used evaluation points is sufficient to accurately evaluate the performance of their solutions and (ii) report on the uncertainty of the published results. To remedy this, this paper evaluates the influence of the selection of evaluation points. Based on statistical parameters such as the standard error of the mean value, an estimator is defined that can be used to quantitatively analyze the impact of the number of used evaluation points on the confidence interval of the mean value of the obtained results. This estimator is used to estimate the uncertainty of the presented accuracy results, and can be used to identify if more evaluations are required. To validate the proposed estimator, two different localization algorithms are evaluated in different testbeds and using different types of technology, showing that the number of required evaluation points does indeed vary significantly depending on the evaluated solution. (C) 2017 Elsevier B.V. All rights reserved