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Deformable mirrors (DMs) have wide applications ranging from astronomical imaging to laser communications and vision science. However, they often require bulky multi-channel cables for delivering high power to their drive actuators. A low-powered DM, which is driven in a contactless fashion, could provide a possible alternative to this problem. We present a photomagnetically actuated deformable mirror (PMADM) concept, which is actuated in a contactless fashion by a permanent magnet and low-power laser heating source. We present the laboratory demonstration of prototype optical surface quality, magnetic control of focus, and COMSOL simulations of its precise photocontrol. The PMADM prototype is made of a magnetic composite (polydimethylsiloxane + ferromagnetic CrO2) and an optical-quality substrate layer and is 30.48 mm × 30.48 mm × 175 μm in dimension with an optical pupil diameter of 8 mm. It deforms to 5.76 μm when subjected to a 0.12-T magnetic flux density and relaxes to 3.76 μm when illuminated by a 50-mW laser. A maximum stroke of 8.78 μm before failure is also estimated considering a 3 × safety factor. Our work also includes simulation of astigmatism generation with the PMADM, a first step in demonstrating control of higher order modes. A fully developed PMADM may have potential application for wavefront corrections in vacuum and space environments. [ABSTRACT FROM AUTHOR]

• Decision Analysis for selecting Human Reliability Analysis technique. • Criteria and subcriteria which indicate the needs of Automotive industry in terms of HRA application. • Have been presented four selected Human Reliability Analysis techniques. The increasing level of automation and complexity in the automotive industry has led to the establishment of a work environment, where human machine interface and human reliability are becoming critical factors of performance especially for safety critical tasks. Many different methodologies for performing risk assessment considering human factors are already available in the literature, but they were often developed for domains other than the automotive industry (aviation, nuclear and process industry). Their purpose is to support the root cause evaluation and estimate the probability of faulty human actions. The present paper introduces a method to support the evaluation and the choice of a suitable Human Reliability Analysis (HRA) technique for the automotive sector considering the ones proposed from other industrial domains. The Analytic Hierarchy Process (AHP) provides a way of assisting safety managers and risk assessors in the HRA technique selection process. This allows the selected HRA techniques to be evaluated based on relevant criteria for an application in an automotive manufacturing environment. An example of selected HRA techniques in this paper will be demonstrated in a case study. The example can also suggest implications to improve existing industry guidelines, international standards and regulations, which are frequently calling for a wide range of ergonomic factors to be considered in the risk assessment process. Further the case study should show potential benefits to organizations coming from the selection and application of the right HRA technique. [ABSTRACT FROM AUTHOR]

This paper reports on an innovative human–machine interaction methodology adopted to assess the case, role and requirements for a new ground collision awareness technology. Specifically, this paper reports on the analysis of ground collision incident data and the subsequent advancement of user scenarios and bow-ties based on this data analysis, for the purpose of generating preliminary user and design requirements for this technology. In so doing, the requirements elicitation and validation methods used in this research are framed from an epistemological perspective. Accordingly, the particular methods adopted are presented and discussed in terms of concepts of evidence, bearing witness and the distinction between facts and values. As such, this paper promotes thinking about evidence-based design practices. Overall, this evidence-based approach aims to improve the development of scenarios and associated problem solving around technology cases, user requirements and user interface design features. The proposed method is useful in terms of bridging the gap from data analysis to design, and validating design decisions. In this regard, it is argued that the generation of user scenarios based on the analysis of incident data (i.e. data coding and statistical analysis), and the reframing of such scenarios in terms of bow-ties for the purpose of requirements/design envisionment, extends existing scenario-based design approaches. Although the use of bow-ties is not new, the advancement of bow-ties from data-driven scenarios is. Specifically, the bow-tie method was applied in a design context, to support problem solving around design decisions, as opposed to formal risk analysis. [ABSTRACT FROM AUTHOR]

The diagnosis of antineutrophil cytoplasmic autoantibody‐associated vasculitis in first‐episode strokes is particularly challenging, especially in patients lacking features of systemic vasculitis. We present the case of a 71‐year‐old woman with positive myeloperoxidase antineutrophil cytoplasmic antibodies and negative proteinase 3 autoantibodies. The patient presented with 1 week history of pyramidal weakness in both upper and lower limbs, hyperreflexia, and clonus. Magnetic resonance imaging of the brain demonstrated widespread bihemispheric cortical and deep white matter acute infarcts, which are consistent with features of stroke secondary to vasculitis. Myeloperoxidase antineutrophilic cytoplasmic autoantibody‐positive vasculitis diseases are more commonly associated with renal, pulmonary, and cutaneous manifestations; however, in our patient, the central nervous system features predominated. This case highlights the challenges of diagnosing primary central nervous system vasculitis, in this case, an atypical myeloperoxidase antineutrophilic cytoplasmic autoantibody‐positive disease without the classical disease course and clinical signs. [ABSTRACT FROM AUTHOR]