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Abstract Background Knee osteoarthritis (OA) is a leading cause of global disability. The understanding of the role of psychosocial factors in knee OA outcomes is still evolving particularly in an Asian context. The primary aim of this study is to explore psychosocial factors that prognosticate short and long-term clinical outcomes, productivity, and healthcare utilization in patients with knee OA. Secondary aims are to explore the mediation and directional relationships and the role it plays in predicting the discordance between self-reported measures (SRM), physical-performance measures (PPMs) and objective clinical parameters. Methods A multi-centre prospective cohort study of community ambulant knee OA patients seeking treatment in the tertiary healthcare institutions in Singapore will be conducted. Patients with secondary arthritis, significant cognitive impairment, severe medical comorbidities or previous knee arthroplasty will be excluded. Primary clinical outcome measure is the Knee injury and OA Outcome Score-12 (KOOS-12). Baseline characteristics include sociodemographic status, arthritis status including symptom duration and radiographic severity, comorbidities and functional status through Charlson Comorbidities Index (CCI), Barthel Index (BI) and Parker Mobility Score (PMS). Psychosocial variables include social support, kinesiophobia, negative affect, self-efficacy, injustice, chronic illness shame and the built environment. Clinical outcomes include quality of life, physical performance, global assessment, satisfaction and physical activity levels. Productivity and healthcare utilization will be assessed by a modified OA Cost and Consequences Questionnaire (OCC-Q) and the Work Productivity and Activity Impairment Questionnaire (WPAI). Variables will be collected at baseline, 4, 12 months and yearly thereafter. Regression, mediation and structural equation modelling will be used for analysis. Discussion Results will allow contextualization, identification, and phenotyping of the critical (and potentially modifiable) psychosocial parameters that predict positive clinical outcomes in the OA population to guide optimization and refinement of healthcare and community. This will facilitate: 1. identification of high-risk knee OA subpopulations that will likely experience poor outcomes and 2. formulation of targeted multidisciplinary comprehensive approaches to address these psychosocial factors to optimize non-surgical treatment care, maximize functional outcomes and create more value-based care model for knee OA. Ethics and dissemination The study has been registered under clinicaltrials.gov registry (Identifier: NCT04942236).

The higher the vehicle autonomy level is, the more the problems that need to be solved by engineers designing its sensors and control systems. Apart from the mechanical, electrical, algorithmic and validation challenges, such projects require to efficiently gather, store and handle the very large amounts of data logged from the vehicles. This is because the key functionalities of the control system in automated vehicles are based on data that is collected from a variety of sources, processed and analyzed to generate actuation signals. The article goes through the challenges, opportunities as well as solutions associated with data logging, collection, storage, annotation, reprocessing and evaluation. It highlights that effective and efficient data handling is an essential element for obtaining the required performance, reliability, safety and quality capabilities that would allow the mass production of automated vehicles. In terms of the safety of passengers and other road users, the behavior of a mass-produced automated vehicle must be predictable and more reliable than that of an ordinary driver. The multitude of variants that test sequences must cover is practically endless. Therefore, shortening the time-to-market to an acceptable length is only possible if you use the right methods of working with data.

In 2020 the Medical Council of Canada created a task force to make recommendations on the modernization of its practices for granting licensure to medical trainees. This task force solicited papers on this topic from subject matter experts. As outlined within this Concept Paper, our proposal would shift licensure away from the traditional focus on high-stakes summative exams in a way that integrates training, clinical practice, and reflection. Specifically, we propose a model of graduated licensure that would have three stages including: a trainee license for trainees that have demonstrated adequate medical knowledge to begin training as a closely supervised resident, a transition to practice license for trainees that have compiled a reflective educational portfolio demonstrating the clinical competence required to begin independent practice with limitations and support, and a fully independent license for unsupervised practice for attendings that have demonstrated competence through a reflective portfolio of clinical analytics. This proposal was reviewed by a diverse group of 30 trainees, practitioners, and administrators in medical education. Their feedback was analyzed and summarized to provide an overview of the likely reception that this proposal would receive from the medical education community.

Social network services (SNSs) are developing at an explosive speed, which makes it easy for people to be closely connected. As a result, a new SNS type, ephemeral social network (ESN), is emerging to capture the ephemeral interactions and meetings that occur in environments such as conferences and workplaces. Most ESNs require the positioning for capturing the physical proximity between people, which impacts much the scalability, privacy protection, and the cost of the system. In this paper, we propose a scalable location-sensing model based on RFID-sensing architecture for ESN in consideration of four aspects of requirements, that is, the usability, QoS, scalability, and privacy. The model includes the perspectives of the privacy, architecture, deployment, and positioning algorithms, which can meet the four key requirements. A prototyping conference-type ESN system was also developed in this paper and was tested in the ACM UbiComp 2011 conference, which verified that the model works well with good scalability, low cost, and customized privacy protection.