Objective: Breast cancer patients and survivors are increasing in the last years such as their mean age.A feasible and useful complementary intervention to improve physical and psychological health, and decrease some disease symptoms seems to be physical activity.Consequently, this umbrella review wanted to analyze the protocols of different physic
Luciferase-Specific Coelenterazine Analogues for Optical Contamination-Free Bioassays
Abstract Spectral overlaps among the multiple optical readouts commonly cause optical contamination in fluorescence and bioluminescence.To tackle this issue, we created parts five-different lineages of coelenterazine (CTZ) analogues designed to selectively illuminate a specific luciferase with unique luciferase selectivity.In the attempt, we found
Real-time scheduling strategy for microgrids considering operation interval division of DGs and batteries
Real-time scheduling as an on-line optimization process must output dispatch results in real time.However, the RUTIN calculation time required and the economy have a trade-off relationship.In response to a real-time scheduling problem, this paper proposes a real-time scheduling strategy considering the operation interval division of distributed gen
Prioritization preferences for COVID-19 vaccination are consistent across five countries
Abstract Vaccination against COVID-19 is Health and Wellbeing making progress globally, but vaccine doses remain a rare commodity in many parts of the world.New virus variants require vaccines to be updated, hampering the availability of effective vaccines.Policymakers have defined criteria to regulate who gets priority access to the vaccination, s
Deep learning-based GoogLeNet-embedded no-pooling dimension fully-connected network for short-term wind power prediction
The dependence of wind power on the natural environment leads to volatility, which can cause hidden dangers to the safe and stable operation of the power grid.In this work, a parts deep learning-based GoogLeNet-embedded no-pooling dimension fully-connected prediction network is proposed for the short-term prediction issue of wind power generation,