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.

A team of scientists in Chile and Spain has developed an innovative electrocatalyst made from hazelnut shell biochar that could lower the cost and environmental footprint of green hydrogen production. The study, published in Biochar, shows that a new molybdenum cobalt catalyst supported on nitrogen doped biochar can drive both the hydrogen evolution reaction and the oxygen evolution reaction with low overpotentials and strong long term stability in alkaline conditions.

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.

Centella asiatica, also known as gotu kola, is widely valued for its triterpenoid saponins, especially asiaticoside and madecassoside, which are used in pharmaceuticals, skincare, and neurological health supplements. 

Ethylene is known to influence fruit physiology, but its specific role in regulating phenolic metabolism in grape seeds has remained unclear.