Effects of Aquatic versus Land High-Intensity Interval Training on Acute Cardiometabolic and Perceptive Responses in Healthy Young Women.

The effects of aquatic high-intensity interval training (AHIIT) on cardiometabolic and perceptive responses when compared to similar land-based exercise (LHIIT) remain unknown. Here, we aimed to (1) establish a matched intensity between mediums and (2) compare the acute cardiometabolic and perceptive responses to the two interventions in healthy young women. Twenty healthy young women performed a stationary running exercise at a matched exercise intensity.

Effectiveness of Deep Water Running on Improving Cardiorespiratory Fitness, Physical Function and Quality of Life: A Systematic Review.

Deep Water Running (DWR) is a form of aquatic aerobic exercise simulating the running patterns adopted on dry land. Little is known on the effectiveness of DWR despite gaining popularity. The objective of this study is to systematically review the effects of DWR on cardiorespiratory fitness, physical function, and quality of life in healthy and clinical populations.

Enablers and barriers of harnessing food waste to address food insecurity: a scoping review.

Despite producing sufficient food for the global population, the growing prevalence of food insecurity in developed countries is cause for concern. The millions of metric tons of food wasted each year could be used instead to drastically lower rates of food insecurity and address food sustainability. In this scoping review, we aimed to identify barriers to and enablers of harnessing food waste across food sectors, including food retail, households, and food rescue organizations, to address food insecurity in a developed country, Australia.

Unsupervised seizure identification on EEG.

Background And Objective: Epilepsy is one of the most common neurological disorders, whose development is typically detected via early seizures. Electroencephalogram (EEG) is prevalently employed for seizure identification due to its routine and low expense collection. The stochastic nature of EEG makes manual seizure inspections laborsome, motivating automated seizure identification.

Investigating sleep spindle density and schizophrenia: A meta-analysis.

Sleep abnormalities are an early feature of schizophrenia (SZ) characterized by reductions in sleep spindles that are associated with deficits in brain connectivity and cognitive function. This study investigated sleep spindle density (SSD) differences between SZ, first episode psychosis (FEP), and family high-risk (FHR) populations and matched healthy controls (HC) by investigating recent studies via a meta-analysis. We collected experimental, demographic, and methodological metrics from eligible studies across multiple online databases.

COVID-19 Vaccination Dynamics in the US: Coverage Velocity and Carrying Capacity Based on Socio-demographic Vulnerability Indices in California.

Coronavirus disease 2019 (COVID-19) disparities among vulnerable populations are of paramount concern that extend to vaccine administration. With recent uptick in infection rates, dominance of the delta variant, and authorization of a third booster shot, understanding the population-level vaccine coverage dynamics and underlying sociodemographic factors is critical for achieving equity in public health outcomes. This study aimed to characterize the scope of vaccine inequity in California counties through modeling the trends of vaccination using the Social Vulnerability Index (SVI).

A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play.

The game of chess is the longest-studied domain in the history of artificial intelligence. The strongest programs are based on a combination of sophisticated search techniques, domain-specific adaptations, and handcrafted evaluation functions that have been refined by human experts over several decades. By contrast, the AlphaGo Zero program recently achieved superhuman performance in the game of Go by reinforcement learning from self-play.

Mastering the game of Go without human knowledge.

A long-standing goal of artificial intelligence is an algorithm that learns, tabula rasa, superhuman proficiency in challenging domains. Recently, AlphaGo became the first program to defeat a world champion in the game of Go. The tree search in AlphaGo evaluated positions and selected moves using deep neural networks.