This study systematically evaluated the potential of red rice extract as a biological ultraviolet (UV) filter and, for the first time, comprehensively validated its UV absorption characteristics, antioxidant properties, and SPF-enhancing effects in sunscreen formulations. Rich in phenolic acids, flavonoids, anthocyanins, and procyanidins, red rice extract demonstrated strong UV-absorbing capacity and free radical scavenging activity, indicating its ability to counteract UV-induced oxidative stress and inflammation.Comparative UV absorption analysis showed that the extract exhibited stable absorption peaks and favorable photothermal stability relative to three commonly used UV filters. When incorporated into oil-in-water (O/W) and water-in-oil (W/O) sunscreen formulations, red rice extract produced concentration-dependent SPF enhancement. Notably, adding 1% extract increased SPF values by more than 10% in both systems.

Importantly, the extract also showed the potential to partially replace traditional chemical UV filters. Formulations containing 1%, 3%, and 5% red rice extract were able to substitute approximately 12.82%, 19.05%, and 26.09% of chemical UV filters, respectively, without compromising SPF performance.

Overall, this work highlights red rice extract as a promising natural UV-filtering ingredient capable of boosting SPF efficacy while reducing chemical filter usage. The findings provide scientific support for its application in developing mild, safe, and environmentally friendly sunscreen products.

A research team led by Dr. Jong-Woo Kim from the Nano Materials Research Division and Dr. Da-Seul Shin from the Materials Processing Research Division at the Korea Institute of Materials Science (KIMS) has successfully developed Korea’s first full-cycle magnetic cooling technology, encompassing materials, components, and modules. This breakthrough is expected to address the environmental issues associated with conventional gas-based refrigeration technologies and pave the way for eco-friendly, high-efficiency alternative cooling solutions to enter the market.

This study explores the profound implications of ambiguity aversion for asset price dynamics and wealth distribution. In a continuous-time macroeconomic model with heterogeneous agents and financial frictions, we demonstrate analytically and numerically that ambiguity aversion leads to a lower risk-free rate, reduced consumption, higher precautionary savings, and wealth redistribution, resulting in significant asset price misalignment. These distortions cause universal welfare loss, making a case for policy intervention. We find that while distortionary capital taxes can mitigate price misalignment, conventional monetary policy, if well-calibrated, can reduce distortions and improve welfare without such trade-offs.

A new large-scale study reveals that uncertainty in climate policy (CPU) is a significant driver for improving corporate Environmental, Social, and Governance (ESG) performance. Analysing data from 4,490 Chinese listed companies (2011-2022), researchers found a strong positive correlation between CPU and ESG scores. The primary motivation is risk mitigation: companies facing higher systemic risk use enhanced ESG performance as a strategic shield. The effect is most pronounced in non-state-owned enterprises, heavy-polluting industries, and highly competitive markets. The findings provide crucial insights for businesses strengthening sustainability strategies and for policymakers aiming to foster resilient, low-carbon economic growth.

In a remarkable stride towards environmental sustainability, researchers at the Department of Biotechnology and Medical Engineering, National Institute of Technology Rourkela, India, have developed a novel approach to predict the adsorption capacity of biochar using machine learning. This breakthrough, detailed in their latest study titled "Machine Learning-Driven Prediction of Biochar Adsorption Capacity for Effective Removal of Congo Red Dye," offers a powerful solution to combat dye pollution.