Principles of digital professionalism for the metaverse in healthcare.

Background: Experts are currently investigating the potential applications of the metaverse in healthcare. The metaverse, a groundbreaking concept that arose in the early 21st century through the fusion of virtual reality and augmented reality technologies, holds promise for transforming healthcare delivery. Alongside its implementation, the issue of digital professionalism in healthcare must be addressed.

Shannon Entropy and Herfindahl-Hirschman Index as Team's Performance and Competitive Balance Indicators in Cyclist Multi-Stage Races.

It seems that one cannot find many papers relating entropy to sport competitions. Thus, in this paper, I use (i) the Shannon intrinsic entropy () as an indicator of "teams sporting value" (or "competition performance") and (ii) the Herfindahl-Hirschman index (HHi) as a "teams competitive balance" indicator, in the case of (professional) cyclist multi-stage races. The 2022 Tour de France and 2023 Tour of Oman are used for numerical illustrations and discussion.

Development of a Mobile App for Self-Care Against COVID-19 Using the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) Model: Methodological Study.

Background: Mobile apps have been shown to play an important role in the management, care, and prevention of infectious diseases. Thus, skills for self-care-one of the most effective ways to prevent illness-can be improved through mobile health apps.

Objective: This study aimed to design, develop, and evaluate an educational mobile-based self-care app in order to help the self-prevention of COVID-19 in underdeveloped countries.

The Cross-Sectional Intrinsic Entropy-A Comprehensive Stock Market Volatility Estimator.

To take into account the temporal dimension of uncertainty in stock markets, this paper introduces a cross-sectional estimation of stock market volatility based on the intrinsic entropy model. The proposed cross-sectional intrinsic entropy () is defined and computed as a daily volatility estimate for the entire market, grounded on the daily traded prices-open, high, low, and close prices (OHLC)-along with the daily traded volume for all symbols listed on The New York Stock Exchange (NYSE) and The National Association of Securities Dealers Automated Quotations (NASDAQ). We perform a comparative analysis between the time series obtained from the and the historical volatility as provided by the estimators: close-to-close, Parkinson, Garman-Klass, Rogers-Satchell, Yang-Zhang, and intrinsic entropy (), defined and computed from historical OHLC daily prices of the Standard & Poor's 500 index (S&P500), Dow Jones Industrial Average (DJIA), and the NASDAQ Composite index, respectively, for various time intervals.

Mobile-Based Self-Care Application for COVID-19: Development Process Using the ADDIE Model.

During the COVID-19 era, technology-enhanced protection of this disease has saved lives in developed countries in which citizens have the privilege of accessing and using such technologies to fight Coronavirus. In the undeveloped countries, on the other hand, citizens have had no accession or ability to use digital technologies to prevent COVID-19. Having this in front, in the MyShield research project, we aim to address how to teach self-care skills in undeveloped countries in the era of COVID-19 using a mobile low-cost application effectively based on a standard educational model (ADDIE).