Studies on perchlorate complexes of copper(II) and silver(I) with substituted benzimidazoles

CuL2(ClO4)​2 [L = 2-​(2'-​quinolyl)​benzimidazole (2-​QylBzIH)​, 2,​2'-​bis(benzimidazolyl) sulfide (bBzIH2s)​, 2,​2'-​bis(benzimidazolyl)​ethane (bBzIH2e)​] and AgLClO4 [L = 2,​6-​bis(2-​benzimidazolyl)​pyridine, 2-​QylBzIH, bBzIH2s and bBzIH2e] were prepd. and characterized by cond., magnetic susceptibility, electronic, IR and proton NMR spectra. IR spectra give evidence for coordination of perchlorate in most of these complexes

User centered ecological interface design (UCEID): A novel method applied to the problem of safe and user-friendly interaction between drivers and autonomous vehicles

© Springer International Publishing AG 2018. User Centered Ecological Interface Design (UCEID) is a novel Human Factors method that integrates relationships between Ecological Interface Design (EID) and inclusive Human Centered Design. It combines existing methodology from the Cognitive Work Analysis (CWA) framework [1–3] and Inclusive User Centered Design [4, 5]. This paper offers a practical guide to UCEID by providing a high-level summary for practitioners using the example of vehicle to driver handover in a BASt Level 3 autonomous vehicle

Toward General Principles for Resilience Engineering

Maintaining the performance of infrastructure‐dependent systems in the face of surprises and unknowable risks is a grand challenge. Addressing this issue requires a better understanding of enabling conditions or principles that promote system resilience in a universal way. In this study, a set of such principles is interpreted as a group of interrelated conditions or organizational qualities that, taken together, engender system resilience. The field of resilience engineering identifies basic system or organizational qualities (e.g., abilities for learning) that are associated with enhanced general resilience and has packaged them into a set of principles that should be fostered. However, supporting conditions that give rise to such first‐order system qualities remain elusive in the field. An integrative understanding of how such conditions co‐occur and fit together to bring about resilience, therefore, has been less clear. This article contributes to addressing this gap by identifying a potentially more comprehensive set of principles for building general resilience in infrastructure‐dependent systems. In approaching this aim, we organize scattered notions from across the literature. To reflect the partly self‐organizing nature of infrastructure‐dependent systems, we compare and synthesize two lines of research on resilience: resilience engineering and social‐ecological system resilience. Although some of the principles discussed within the two fields overlap, there are some nuanced differences. By comparing and synthesizing the knowledge developed in them, we recommend an updated set of resilience‐enhancing principles for infrastructure‐dependent systems. In addition to proposing an expanded list of principles, we illustrate how these principles can co‐occur and their interdependencies.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156462/2/risa13494_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156462/1/risa13494.pd

Work domain analysis for training-system definition and acquisition

Training-needs analysis is critical for defining and procuring effective training systems. However, traditional approaches to training-needs analysis are not suitable for capturing the demands of highly automated and computerized work domains. In this article, we propose that work domain analysis can identify the functional structure of a work domain that must be captured in a training system, so that workers can be trained to deal with unpredictable contingencies that cannot be handled by computer systems. To illustrate this argument, we outline a work domain analysis of a fighter aircraft that defines its functional structure in terms of its training objectives, measures of performance, basic training functions, physical functionality, and physical context. The functional structure or training needs identified by work domain analysis can then be used as a basis for developing functional specifications for training systems, specifically its design objectives, data collection capabilities, scenario generation capabilities, physical functionality, and physical attributes. Finally, work domain analysis also provides a useful framework for evaluating whether a tendered solution fulfills the training needs of a work domain