A new KAUST study uses machine learning to predict disease spread with high accuracy, dynamically incorporating latest data without human bias. This approach offers a promising alternative to conventional models, providing a more accurate story of the underlying epidemic data.
A collaborative paper by Wang Yicheng and colleagues finds that households reduce risky shares of assets when income risk doubles, with potential social welfare gains of 4% if policies stabilize income risk. The study also examines the effect of progressive income tax systems on financial portfolio choices.
Researchers at NTU Singapore's Lee Kong Chian School of Medicine found that saturated fatty acids degrade protein FIT2, leading to insulin-producing cells' loss of function and death. This impairs the body's ability to secrete enough insulin, resulting in diabetes.