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We also review the recently presented security solutions for robotic systems.The novel coronavirus (COVID-19) has induced unprecedented improvements of air quality due to drastic shrinking of human activities during the pandemic lockdown in 2020. While declines of most air pollutants have been globally evidenced in most cities worldwide, there is few detailed spatial knowledge at local scale. Therefore, we present here a high resolution mapping of the 2018-2020 evolution of human activities and air pollutants in Wuhan. Human activities were assessed by nighttime light radiance. We measured the air quality index (AQI) as the maximum value among air quality sub-indices of SO2, NO2, CO, O3 and particulate matter. We also compared mean monthly pollutant concentration during January-April in 2018, 2019 and 2020. Mapping results show that variations of nighttime light radiance were heterogenous at local scale, showing both rises and declines in the same district. The radiance decreased in eight districts located mostly in the city center, as a result of lower human activity, but the radianc.This study presents methods of hygiene and the use of masks to control the disease. The zero basic reproduction number can be achieved by taking the necessary precautionary measures that prevent the transmission of infection, especially from uninfected virus carriers. The existence of time delay in implementing the quarantine strategy and the threshold values of the time delay that keeping the stability of the system are established. Also, it is found that keeping the infected people quarantined immediately is very important in combating and controlling the spread of the disease. Also, for special cases of the system parameters, the time delay can not affect the asymptotic behavior of the disease. Finally, numerical simulations have been illustrated to validate the theoretical analysis of the proposed model.

As older adults age, they may require assistance completing activities of daily living (ADLs). Robotic assistance can offset healthcare costs and allow older adults to preserve their autonomy. Younger adults are often involved in the design and purchase of these robotic technologies, and must take into account the needs and expectations of the target population (i.e., older adults) to create a robot that the end-user will adopt.

This study evaluated the opinions of both younger and older adults regarding the design and performance of the Robot Activity Support (RAS) system. It is important to understand points of agreement and divergence between these populations' perspectives so that effective robotic aids are created for older adults.

Fifty-two younger and older adults completed three scripted tasks with the RAS robot in a smart home environment. Each participant made task errors to cue the robot to offer help via three prompt modalities (guide to the object, video of forgotten step, and video of the older adults were less interested in having a similar robot in their home than younger counterparts expected. Future studies will show if older adults' opinions can be improved after making the recommended changes.Today, the whole world is facing a great medical disaster that affects the health and lives of the people the COVID-19 disease, colloquially known as the Corona virus. Deep learning is an effective means to assist radiologists to analyze the vast amount of chest X-ray images, which can potentially have a substantial role in streamlining and accelerating the diagnosis of COVID-19. Such techniques involve large datasets for training and all such data must be centralized in order to be processed. Due to medical data privacy regulations, it is often not possible to collect and share patient data in a centralized data server. In this work, we present a collaborative federated learning framework allowing multiple medical institutions screening COVID-19 from Chest X-ray images using deep learning without sharing patient data. We investigate several key properties and specificities of federated learning setting including the not independent and identically distributed (non-IID) and unbalanced data distributions that naturally arise. We experimentally demonstrate that the proposed federated learning framework provides competitive results to that of models trained by sharing data, considering two different model architectures. These findings would encourage medical institutions to adopt collaborative process and reap benefits of the rich private data in order to rapidly build a powerful model for COVID-19 screening.Case management (CM) is an integrated care strategy, characterised by a set of actions to support person-centred planning, coordination of health and social services. Decades of CM, organisational psychology and occupational research highlight how vagueness and ambiguity in role communication can create role conflict and job stress, negatively impacts staff turnover, intra-organisational collaboration, job performance, and that poor communication of CM impedes policy, quality analysis service development and practice. We conducted a detailed top-down hierarchical, quality analysis of communication about CM roles and responsibilities in a Scheme for people with disability in Australia. The study used content analysis methods and the main actions as defined in a validated CM taxonomy (Appendix 1). BTK inhibitor order We systematically searched and analysed 53 Scheme policy and practice documents of CM from 2013-2019. The results showed poor role communication with vagueness, ambiguity, gaps in the description of CM roles and responsibilities. Poor role communication has contributed to negative experiences and outcomes of CM actions of planning and coordination, as reported by CM users in many Scheme-related parliamentary inquiries, research, formal complaints, and decision appeals. The results reinforce the importance of an ontological approach in communication of CM roles and actions and provides learnings for integrated care roles across countries and contexts.

Millions of people worldwide have complex health and social care needs. Care coordination for these patients is a core dimension of integrated care and a key responsibility for primary healthcare. Registered nurses play a substantial role in care coordination. This review draws on previous theoretical work and provides a synthesis of care coordination interventions as operationalized by nurses for complex patient populations in primary healthcare.

We followed Arksey and O'Malley's methodological framework for scoping reviews. We carried out a systematic search across CINAHL, MEDLINE, Scopus and ProQuest. Only empirical studies were included. We performed a thematic analysis using deductive (the American Nurses Association Framework) and inductive approaches. Findings were discussed with a group of experts.

Thirty-four articles were included in the synthesis. Overall, nursing care coordination activities were synthesized into three categories those targeting the patient, family and caregivers; those targeting health and social care teams; and those bringing together patients and professionals.