RESCUER: Development of a Modular Chemical,Biological, Radiological,and Nuclear Robot for Intervention,Sampling, and Situation Awareness*

This paper describes the development of a robot prototype for intervention, sampling, and situation awareness in CBRN (chemical, biological, radiological, and nuclear) missions. It outlines the mission requirements, design specifications, the solutions that were developed and integrated, and the final tests done. The solution addresses one of the most important mission requirements in CBRN scenarios: the capability to decontaminate the robot once it has been used in real missions. As microdoses of CBRN contaminants are sufficient to cause significant damage to human beings, prevention of robot contamination is always of top priority. If there is a potential danger of real contamination, it can only be removed by effective decontamination. The way to deal with this problem imposes significant design conditions; the proposed design allows an easy and fast decontamination of the robot. The work presents a new way to approach this kind of robot, based on modular component architecture over a robot operating system that permits the attachment and detachment of robot components via unique electromechanical interfaces. The resulting modular robot introduces an innovative kinematic solution that can be dynamically configured for the different mission requirements.     

Anisotropic loss of toughness with physical aging of work toughened polycarbonate

We have studied the response of mechanically toughened and physically aged polycarbonate primarily using Charpy impact and ultrasonic wave speed measurements. The toughening was conducted through plastic compression on as‐received PC. The Charpy impact tests showed anisotropic toughening, both in the absorbed energy and in the mode of fracture. The amount of toughening with plastic compression, even though anisotropic, is centered around the response of annealed and quenched samples, which represent the response of an unaged PC. There was an anisotropic drop in the toughness of some samples with aging. The time of this drop was uncorrelated in the different directions and disappeared for the highly toughened samples. This transition was bimodal and statistically distributed between either a fully ductile or a fully brittle failure. As the samples were prepared in a manner to remove induced residual stresses, this drop in toughening may be associated with an intrinsic anisotropic thermal aging of the deformed material. POLYM. ENG. SCI., 54:794–804, 2014. © 2013 Society of Plastics Engineers     

An observer‐metamerism sensitivity index for electronic displays

The effect of observer metamerism induced by electronic displays depends to a large extent on their primary spectra (red, green, and blue in the most common case). In particular, for narrow‐band primary spectra whose peak wavelength lies in the range of high variability of the observer's color‐matching function, some observers can experience very large differences between actual surface colors (e.g. in a light booth) and displayed colors if the monitor is optimized for the International Commission on Illumination (CIE) 1931 standard observer. However, because narrow‐band light‐emitting diodes lead to larger color gamuts, more and more monitors with very narrow band primaries are coming onto the market without manufacturers taking into account the associated problem of observer variations. Being able to measure these variations accurately and efficiently is therefore an important objective. In this paper, we propose a new approach to predict the extent of observer metamerism for a particular multiprimary display. Unlike existing dedicated models, ours does not depend on a reference illuminant and a set of reflectance spectra and is computationally more efficient.     

Some aspects on ruggedness of SiC power devices

This article is on effects that can destroy SiC power semiconductor devices. The failure physics in SiC devices are discussed based on the well understood effects in silicon devices. In some device properties, such as surge current, short circuit, static avalanche and dynamic avalanche, SiC has significant possible advantages compared to silicon. For cosmic ray stability, there are no unique results. Regarding thermal mechanical stress on interface materials, SiC is more challenging. The same may hold for electrical stress in passivation layers at the junction termination.     

Motivational,emotional, and behavioral correlates of fear of missing out

Social media utilities have made it easier than ever to know about the range of online or offline social activities one could be engaging. On the upside, these social resources provide a multitude of opportunities for interaction; on the downside, they often broadcast more options than can be pursued, given practical restrictions and limited time. This dual nature of social media has driven popular interest in the concept of Fear of Missing Out – popularly referred to as FoMO. Defined as a pervasive apprehension that others might be having rewarding experiences from which one is absent, FoMO is characterized by the desire to stay continually connected with what others are doing. The present research presents three studies conducted to advance an empirically based understanding of the fear of missing out phenomenon. The first study collected a diverse international sample of participants in order to create a robust individual differences measure of FoMO, the Fear of Missing Out scale (FoMOs); this study is the first to operationalize the construct. Study 2 recruited a nationally representative cohort to investigate how demographic, motivational and well-being factors relate to FoMO. Study 3 examined the behavioral and emotional correlates of fear of missing out in a sample of young adults. Implications of the FoMOs measure and for the future study of FoMO are discussed.     

Measuring errors and violations on the road: A bifactor modeling approach to the Driver Behavior Questionnaire

The Driver Behavior Questionnaire (DBQ) is a self-report measure of driving behavior that has been widely used over more than 20 years. Despite this wealth of evidence a number of questions remain, including understanding the correlation between its violations and errors sub-components, identifying how these components are related to crash involvement, and testing whether a DBQ based on a reduced number of items can be effective. We address these issues using a bifactor modeling approach to data drawn from the UK Cohort II longitudinal study of novice drivers. This dataset provides observations on 12,012 drivers with DBQ data collected at .5, 1, 2 and 3 years after passing their test. A bifactor model, including a general factor onto which all items loaded, and specific factors for ordinary violations, aggressive violations, slips and errors fitted the data better than correlated factors and second-order factor structures. A model based on only 12 items replicated this structure and produced factor scores that were highly correlated with the full model. The ordinary violations and general factor were significant independent predictors of crash involvement at 6 months after starting independent driving. The discussion considers the role of the general and specific factors in crash involvement.