No abstract

No abstract

Time-critical applications, such as early warning systems or live event broadcasting, present particular challenges. They have hard limits on Quality of Service constraints that must be maintained, despite network fluctuations and varying peaks of load. Consequently, such applications must adapt elastically on-demand, and so must be capable of reconfiguring themselves, along with the underlying cloud infrastructure, to satisfy their constraints. Software engineering tools and methodologies currently do not support such a paradigm. In this paper, we describe a framework that has been designed to meet these objectives, as part of the EU SWITCH project. SWITCH offers a flexible co-programming architecture that provides an abstraction layer and an underlying infrastructure environment, which can help to both specify and support the life cycle of time-critical cloud native applications. We describe the architecture, design and implementation of the SWITCH components and describe how such tools are applied to three time-critical real-world use cases.

Background The long-term prevalence and risk factors for post-acute COVID-19 sequelae (PASC) are not well described and may have important implications for unvaccinated populations and policy makers. Objective To assess health status, persistent symptoms, and effort tolerance approximately 1 year after COVID-19 infection Design Retrospective observational cohort study using surveys and clinical data Participants Survey respondents who were survivors of acute COVID-19 infection requiring Emergency Department presentation or hospitalization between March 3 and May 15, 2020. Main Measure(s) Self-reported health status, persistent symptoms, and effort tolerance Key Results The 530 respondents (median time between hospital presentation and survey 332 days [IQR 325–344]) had mean age 59.2±16.3 years, 44.5% were female and 70.8% were non-White. Of these, 41.5% reported worse health compared to a year prior, 44.2% reported persistent symptoms, 36.2% reported limitations in lifting/carrying groceries, 35.5% reported limitations climbing one flight of stairs, 38.1% reported limitations bending/kneeling/stooping, and 22.1% reported limitations walking one block. Even those without high-risk comorbid conditions and those seen only in the Emergency Department (but not hospitalized) experienced significant deterioration in health, persistent symptoms, and limitations in effort tolerance. Women (adjusted relative risk ratio [aRRR] 1.26, 95% CI 1.01–1.56), those requiring mechanical ventilation (aRRR 1.48, 1.02–2.14), and people with HIV (aRRR 1.75, 1.14–2.69) were significantly more likely to report persistent symptoms. Age and other risk factors for more severe COVID-19 illness were not associated with increased risk of PASC. Conclusions PASC may be extraordinarily common 1 year after COVID-19, and these symptoms are sufficiently severe to impact the daily exercise tolerance of patients. PASC symptoms are broadly distributed, are not limited to one specific patient group, and appear to be unrelated to age. These data have implications for vaccine hesitant individuals, policy makers, and physicians managing the emerging longer-term yet unknown impact of the COVID-19 pandemic. Supplementary Information The online version contains supplementary material available at 10.1007/s11606-021-07379-z.

SummaryThe increasing volume of data being produced, curated, and made available by research infrastructures in the environmental science domain require services that are able to optimize the delivery and staging of data for researchers and other users of scientific data. Specialized data services for managing data life cycle, for creating and delivering data products, and for customized data processing and analysis all play a crucial role in how these research infrastructures serve their communities, and many of these activities are time‐critical—needing to be carried out frequently within specific time windows. We describe our experiences identifying the time‐critical requirements of environmental scientists making use of computational research support environments. We present a microservice‐based infrastructure optimization suite, the Dynamic Real‐Time Infrastructure Planner, used for constructing virtual infrastructures for research applications on demand. We provide a case study whereby our suite is used to optimize runtime service quality for a data subscription service provided by the Euro‐Argo using EGI Federated Cloud and EUDAT's B2SAFE services, and to consider how such a case study relates to other application scenarios.