High-speed processing of X-ray wavefront marking data with the Unified Modulated Pattern Analysis (UMPA) model

Wavefront-marking X-ray imaging techniques use e.g., sandpaper or a grating to generate intensity fluctuations, and analyze their distortion by the sample in order to retrieve attenuation, phase-contrast, and dark-field information. Phase contrast yields an improved visibility of soft-tissue specimens, while dark-field reveals small-angle scatter from sub-resolution structures. Both have found many biomedical and engineering applications. The previously developed Unified Modulated Pattern Analysis (UMPA) model extracts these modalities from wavefront-marking data. We here present a new UMPA implementation, capable of rapidly processing large datasets and featuring capabilities to greatly extend the field of view. We also discuss possible artifacts and additional new features.Comment: 18 pages, 7 figures, submitted to Optics Expres

Assessing Graphical Robot Aids for Interactive Co-working

The shift towards more collaborative working between humans and robots increases the need for improved interfaces. Alongside robust measures to ensure safety and task performance, humans need to gain the confidence in robot co-operators to enable true collaboration. This research investigates how graphical signage can support human–robot co-working, with the intention of increased productivity. Participants are required to co-work with a KUKA iiwa lightweight manipulator on a manufacturing task. The three conditions in the experiment differ in the signage presented to the participants – signage relevant to the task, irrelevant to the task, or no signage. A change between three conditions is expected in anxiety and negative attitudes towards robots; error rate; response time; and participants’ complacency, suggested by facial expressions. In addition to understanding how graphical languages can support human–robot co-working, this study provides a basis for further collaborative research to explore human–robot co-working in more detail

Language-free graphical signage improves human performance and reduces anxiety when working collaboratively with robots

As robots become more ubiquitous, and their capabilities extend, novice users will require intuitive instructional information related to their use. This is particularly important in the manufacturing sector, which is set to be transformed under Industry 4.0 by the deployment of collaborative robots in support of traditionally low-skilled, manual roles. In the first study of its kind, this paper reports how static graphical signage can improve performance and reduce anxiety in participants physically collaborating with a semi-autonomous robot. Three groups of 30 participants collaborated with a robot to perform a manufacturing-type process using graphical information that was relevant to the task, irrelevant, or absent. The results reveal that the group exposed to relevant signage was significantly more accurate in undertaking the task. Furthermore, their anxiety towards robots significantly decreased as a function of increasing accuracy. Finally, participants exposed to graphical signage showed positive emotional valence in response to successful trials. At a time when workers are concerned about the threat posed by robots to jobs, and with advances in technology requiring upskilling of the workforce, it is important to provide intuitive and supportive information to users. Whilst increasingly sophisticated technical solutions are being sought to improve communication and confidence in human-robot co-working, our findings demonstrate how simple signage can still be used as an effective tool to reduce user anxiety and increase task performance

The Impact of Different Human-Machine Interface Feedback Modalities on Older Participants’ User Experience of CAVs in a Simulator Environment

Rapidly developing Autonomous Vehicle (AV) technology has potential to provide solutions to some of the aging population challenges, such as social isolation resulting from an inability to be independently mobile. However for AVs success, users’ acceptance is essential. Fifteen participants (M 70 years) participated in an autonomous driving simulator trial with voice-based CAV status feedback in a decision-making scenario – whether to pick up a friend on the way. The within-subject conditions/journeys were: Audio feedback (Audio)/Pick-Up; Audio/No-Pick-Up; No-Audio/Pick-Up. Additionally, the effect of feedback during different external journey conditions was also considered, resulting in two between-subjects conditions – day and night travel. Participants physiological, cognitive and affective measures show greater situational awareness and workload ratings in the No-Audio/Pick-Up condition with increased Post-trial trust rating and overall higher positive affect. These results indicate that the greatest concentration was required in the no-sound condition, suggesting that sound/multimodal feedback improved ease of operation and journey experience

Dynamic Graphical Signage Improves Response Time and Decreases Negative Attitudes towards Robots in Human-Robot Co-working

Collaborative robots, or ‘co-bots’, are a transformational technology that bridge traditionally segregated manual and automated manufacturing processes. However, to realize its full potential, human operators need confidence in robotic co-worker technologies and their capabilities. In this experiment we investigate the impact of screen-based dynamic instructional signage on 39 participants from a manufacturing assembly line. The results provide evidence that dynamic signage helps to improve response time for the experimental group with task-relevant signage compared to the control group with no signage. Furthermore, the experimental group’s negative attitudes towards robots decreased significantly with increasing accuracy on the task

Empowerment, stress vulnerability and burnout among portuguese nursing staff

The work environment in Portuguese hospitals, characterized by economic cutbacks, can lead to higher levels of burnout experienced by nursing staff. Furthermore, vulnerability to stress can negatively affect the perception of burnout in the workplace. However, structural empowerment is an organizational process that can prevent and decrease burnout among nurses. Consequently, the aim of the study was to examine to what extent structural empowerment and vulnerability to stress can play a predictive role in core burnout in a sample of Portuguese nurses. A convenience sample of 297 nursing staff members from Portuguese hospitals was used in this study. Core burnout was negatively and significantly related to all the dimensions of structural empowerment, and it was positively and significantly related to vulnerability to stress. Regression models showed that core burnout was significantly predicted by access to funds, access to opportunities and vulnerability to stress. Organizational administrations must make every effort in designing interventions focused on structural empowerment, as well as interventions focused on individual interventions that enhance skills for coping with stress.info:eu-repo/semantics/publishedVersio

Subgroup Pro-Ana

Pro-Ana is a social movement that positively promotes anorexia and related eating disorders based on the belief that these are lifestyle choices and not disorders. In this study we investigated the different behaviors and thoughts related to Pro-Ana and Anorexia as well as behaviors and thoughts related to typical diet and exercise patterns. Data were collected through an online survey format that asked questions about individual behavior and thoughts in an anonymous fashion. Our purpose was to discover whether or not the group known as Pro-Ana is really separate and distinct from individuals who are anorexic

High-speed processing of X-ray wavefront marking data with the Unified Modulated Pattern Analysis (UMPA) model

Wavefront-marking X-ray imaging techniques use e.g., sandpaper or a grating to generate intensity fluctuations, and analyze their distortion by the sample in order to retrieve attenuation, phase-contrast, and dark-field information. Phase contrast yields an improved visibility of soft-tissue specimens, while dark-field reveals small-angle scatter from sub-resolution structures. Both have found many biomedical and engineering applications. The previously developed Unified Modulated Pattern Analysis (UMPA) model extracts these modalities from wavefront-marking data. We here present a new UMPA implementation, capable of rapidly processing large datasets and featuring capabilities to greatly extend the field of view. We also discuss possible artifacts and additional new features