Kristiansen Kidd (rabbitbetty71)

The area under the receiver operating characteristics curve (AUROC) of the TyG index for predicting a high baPWV was 0.708 (95%CI 0.693-0.722, P less then 0.001) in women, higher than that in men. However, the association of the homeostatic model assessment of IR (HOMA-IR) with a high baPWV and the 10-year CVD risk was absent when adjusting for multiple risk factors in 955 participants. Conclusions The TyG index is independently associated with arterial stiffness and 10-year CVD risk.COVID-19 has severely impacted mental health in vulnerable demographics, in particular older adults, who face unprecedented isolation. Consequences, while globally severe, are acutely pronounced in low- and middle-income countries (LMICs) confronting pronounced gaps in resources and clinician accessibility. Social robots are well-recognized for their potential to support mental health, yet user compliance (i.e., trust) demands seamless affective human-robot interactions; natural 'human-like' conversations are required in simple, inexpensive, deployable platforms. We present the design, development, and pilot testing of a multimodal robotic framework fusing verbal (contextual speech) and nonverbal (facial expressions) social cues, aimed to improve engagement in human-robot interaction and ultimately facilitate mental health telemedicine during and beyond the COVID-19 pandemic. We report the design optimization of a hybrid face robot, which combines digital facial expressions based on mathematical affect space (SCARF) in Chennai, India. A procedure for deployment addressing challenges in cultural acceptance, end-user acclimatization and resource allocation is further introduced. Results indicate strong promise to stimulate human-robot psychosocial interaction through the hybrid-face robotic system. Future work is targeting deployment for telemedicine to mitigate the mental health impact of COVID-19 on older adults and PwD in both LMICs and higher income regions.A robot swarm is a decentralized system characterized by locality of sensing and communication, self-organization, and redundancy. These characteristics allow robot swarms to achieve scalability, flexibility and fault tolerance, properties that are especially valuable in the context of simultaneous localization and mapping (SLAM), specifically in unknown environments that evolve over time. So far, research in SLAM has mainly focused on single- and centralized multi-robot systems-i.e., non-swarm systems. While these systems can produce accurate maps, they are typically not scalable, cannot easily adapt to unexpected changes in the environment, and are prone to failure in hostile environments. Swarm SLAM is a promising approach to SLAM as it could leverage the decentralized nature of a robot swarm and achieve scalable, flexible and fault-tolerant exploration and mapping. However, at the moment of writing, swarm SLAM is a rather novel idea and the field lacks definitions, frameworks, and results. In this work, we present the concept of swarm SLAM and its constraints, both from a technical and an economical point of view. In particular, we highlight the main challenges of swarm SLAM for gathering, sharing, and retrieving information. We also discuss the strengths and weaknesses of this approach against traditional multi-robot SLAM. We believe that swarm SLAM will be particularly useful to produce abstract maps such as topological or simple semantic maps and to operate under time or cost constraints.Haru is a social, affective robot designed to support a wide range of research into human-robot communication. This article analyses the design process for Haru beta, identifying how both visual and performing arts were an essential part of that process, contributing to ideas of Haru's communication as a science and as an art. Initially, the article examines how a modified form of Design Thinking shaped the work of the interdisciplinary development team-including animators, performers and sketch arti