In a paper published in Polymer Science & Technology, an international team of scientists developed a multifunctional conductive hydrogel (P-EPL/CCT) hydrogel flexible sensor using a physical-chemical dual cross-linking approach involving poly(vinyl alcohol) (PVA), gallic acid grafted chitosan (CS−GA), tannic acid (TA), eggshell membrane (ESM), lysozyme, and 4am-PEG-MAL for emergency cooling and wound healing following fire-works-related skin burns. The organohydrogel sensor exhibits impressive mechanical properties, such as a maximum stress of 2.15 MPa and an elongation of 605%, along with antifreeze resistance down to −39.5 °C, antimicrobial properties with bacterial inhibition exceeding 96.5%, and cytocompatibility. Additionally, serving as strain sensor with high sensitivity (GF = 1.14 at 100% strain) and rapid response times, it can effectively monitor human movement signals. The developed organohydrogel demonstrates the ability to accelerate skin healing, promote angiogenesis, and reduce scarring. Moreover, it is utilized for monitoring finger joint injuries and employing machine learning-assisted electrical signals for intelligent wound healing monitoring and protection. This study introduces a flexible device that combines multiple functionalities, showing promise for diverse applications in the biomedical field. This study is led by Chuang Du (Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, China), Weiwei Liu (Stomatological Hospital, Jilin University, Changchun 130021, China) and Lei Wang (Key Laboratory of Molecular Enzymology and Engineering of Ministry of Education, School of Life Sciences, Jilin University, Changchun 130023, China).

Rapid urbanization is reshaping how people live and how societies function. By the middle of this century, nearly 70% of the global population is expected to live in cities, making urban environments one of the most important determinants of public health—particularly mental health. This challenge is the focus of a recent expert position paper co-authored by researchers affiliated with Wroclaw Medical University and developed under the umbrella of the European Psychiatric Association.

The authors highlight that city living is associated with a range of risk factors that can negatively affect mental well-being. These include chronic exposure to noise, air and light pollution, overcrowding, social inequalities, poverty, and—paradoxically—social isolation and loneliness in densely populated areas. Together, these factors may increase the risk of mood disorders, anxiety disorders, and suicidal behavior.

Cambridge researchers have become the first to combine multiple image types – RGB (that mimics human vision), depth and infra-red – in a 3D camera set up to monitor premature babies in neonatal intensive care. The aim is to provide a second set of eyes for nurses through continuous visual monitoring of the babies’ behaviour.

A new seismic study reveals that Earth’s largest volcanic event fundamentally transformed the oceanic plate beneath the Ontong Java Plateau, the world’s largest oceanic plateau. By analyzing high-frequency seismic waves traveling through the plate, researchers discovered that massive volcanic activity not only built the plateau itself but also chemically and structurally modified the underlying oceanic plate.

The results show that the plate has a complex internal structure composed of layered formations intersected by extensive dike swarms, created as magma rose from a deep thermochemical mantle plume. Unusually slow seismic velocities indicate that this magma chemically altered the plate through a process known as refertilization. These findings demonstrate that large-scale volcanism can significantly reshape pre-existing oceanic plates, offering new insights into how tectonic plates form and evolve.

Abstract

Purpose – Stock markets are essential for households for wealth creation and for firms for raising financial resources for capacity expansion and growth. Market participants, therefore, need an understanding of stock price movements. Stock market indices and individual stock prices reflect the macroeconomic environment and are subject to external and internal shocks. It is important to disentangle the impact of macroeconomic shocks, market uncertainty and speculative elements and examine them separately for prediction. To aid households, firms and policymakers, the paper proposes a granular decomposition-based prediction framework for different time periods in India, characterized by different market states with varying degrees of uncertainty.

Design/methodology/approach – Ensemble empirical mode decomposition (EEMD) and fuzzy-C-means (FCM) clustering algorithms are used to decompose stock prices into short, medium and long-run components. Multiverse optimization (MVO) is used to combine extreme gradient boosting regression (XGBR), Facebook Prophet and support vector regression (SVR) for forecasting. Application of explainable artificial intelligence (XAI) helps identify feature contributions.

Findings – We find that historic volatility, expected market uncertainty, oscillators and macroeconomic variables explain different components of stock prices and their impact varies with the industry and the market state. The proposed framework yields efficient predictions even during the COVID-19 pandemic and the Russia–Ukraine war period. Efficiency measures indicate the robustness of the approach. Findings suggest that large-cap stocks are relatively more predictable.

Research limitations/implications – The paper is on Indian stock markets. Future work will extend it to other stock markets and other financial products.

Practical implications– The proposed methodology will be of practical use for traders, fund managers and financial advisors. Policymakers may find it useful for assessing the impact of macroeconomic shocks and reducing market volatility.

Originality/value – Development of a granular decomposition-based forecasting framework and separating the effects of explanatory variables in different time scales and macroeconomic periods.

Abstract

Purpose – This study examines the stock market efficiency in China to offer trading strategy guidance to investors and efficiency evaluation insight to policymakers.

Design/methodology/approach – This study examines the stock market efficiency in China with a new combined liquidity trading strategy by blending technical analysis into a liquidity buy-and-hold strategy.

Findings – Our results show that the combined strategy generates significant excess returns in the whole sample period, suggesting that the Chinese stock market is not consistent with the weak form efficient hypothesis. In addition, the combined strategy yields more significant risk-adjusted excess returns after the 2004 split-share reform, indicating the stock market efficiency in China does not exhibit a distinct upgrade after the reform. Our further test results reinforce the main conclusions after taking transaction costs, market states, short-selling reform and other issues into consideration.

Originality/value – Our study contributes to the literature in two ways: First, we shed light on the mixed documented results about the market efficiency form in China. Second, we contribute to the mixed relation between the 2004 split-share reform and market efficiency in China.