Results 151 to 160 of about 524,650 (239)
volume 22, no. 2 (Summer 2015) [PDF]
Office of University Advancement, Bryant University
core +1 more source
ABSTRACT Both universities and companies create value and innovation to maintain their position and remain competitive. Different, but still similar, with two goals that are shared. With their collaboration, they can enhance their pursuit of sustainability and as well corporate social responsibility by creating and delivering value and thus ...
Jana Hojnik +4 more
wiley +1 more source
Excess Adiposity Without Obesity in a High-Risk Population.
Palmer AB +6 more
europepmc +1 more source
First-principles study of ZnO/MoSeTe van der Waals heterostructures for photovoltaic and hydrogen evolution applications. [PDF]
Abraham DS +4 more
europepmc +1 more source
Tick‐Tock, the Time Has Come: Leveraging TikTok to Understand, Prevent, and Treat Eating Disorders
ABSTRACT Objective TikTok—a highly engaging social media platform with a powerful algorithm that displays short videos—has become massively popular in recent years. As research highlights the concerning relationship between image‐based content on social media and disordered eating symptoms, TikTok may serve as an optimal platform to understand eating ...
Macarena Kruger +3 more
wiley +1 more source
Anxiety, life-space mobility and quality of life among frail older adults in Enugu, South-East Nigeria. [PDF]
Judith II +3 more
europepmc +1 more source
Vegetation on the move: elevational shifts and greening dynamics across the Himalayan alpine zone
This study investigates alpine ‘vegetation line' (the upper limit of continuous plant community) dynamics in the Himalayan alpine zone (HAZ) over a 24‐year timescale (1999–2022) using maximum NDVI products derived from Landsat series datasets, adjusted for sampling bias using phenological modelling.
Ruolin Leng +5 more
wiley +1 more source
One Health antimicrobial resistance modelling: from science to policy. [PDF]
Redman-White CJ +9 more
europepmc +1 more source
The transferability of single or joint species distribution models ((j)SDMs) depends on their ability to predict beyond the observed environmental range and to remain consistent despite shifts in biotic interactions. Transfer accuracy may be improved by recent advances in the application of deep learning that provide greater flexibility and potentially
Marco Basile +44 more
wiley +1 more source

