Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.

Forecasting the COVID-19 Pandemic: Lessons learned and future directions.

I.The Coronavirus Disease 2019 (COVID-19) has demonstrated that accurate forecasts of infection and mortality rates are essential for informing healthcare resource allocation, designing countermeasures, implementing public health policies, and increasing public awareness. However, there exist a multitude of modeling methodologies, and their relative performances in accurately forecasting pandemic dynamics are not currently comprehensively understood.

EPIDEMIOLOGY OF ORTHOPEDIC INJURIES IN JIU-JITSU ATHLETES.

Objective: This study aims to identify the epidemiology of orthopedic injuries in jiu-jitsu practitioners.

Methods: Ninety-six jiu-jitsu practitioners aged between 18 and 45 years, male and female, answered a questionnaire addressing personal data and history of injuries related to the sport during the last 24 months.

Results: In the period cover, 85% of the sample presented injuries related to the practice of jiu-jitsu, with an average of 60 days of absenteeism from sports practice.

Optimizing Global Navigation Satellite Systems network real-time kinematic infrastructure for homogeneous positioning performance from the perspective of tropospheric effects.

Real-time centimetre-level precise positioning from Global Navigation Satellite Systems (GNSS) is critical for activities including landslide, glacier and coastal erosion monitoring, flood modelling, precision agriculture, intelligent transport systems, autonomous vehicles and the Internet of Things. This may be achieved via the real-time kinematic (RTK) GNSS approach, which uses a single receiver and a network of continuously operating GNSS reference stations (CORS). However, existing CORS networks have often been established simply by attempting regular spacing or in clusters around cities, with little consideration of weather, climate and topography effects, which influence the GNSS tropospheric delay, a substantial GNSS positional error and which prevents homogeneous RTK accuracy attainment.