A study in Engineering reveals a new adsorbent made by combining cationic surfactants with montmorillonite. This adsorbent can selectively remove perchlorate from water, addressing a key issue in drinking water safety. It shows high selectivity, fast adsorption, and good stability, with potential for water treatment applications.

In order to address the challenges in contemporary global politics, economy, and research, there is an urgent need for the complete redesign of the human education system, centered on innovation, enhancing human well-being and sustainable development. Using empirical data from reputable international organizations, such as the United Nations Educational, Scientific and Cultural Organization (UNESCO), this study analyzes the uncertainties confronting world development and how the education system can be redesigned with these challenges in mind.

Anna Seigal, assistant professor of Applied Mathematics at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), has been awarded a 2025 Sloan Research Fellowship by The Alfred P. Sloan Foundation. Seigal explores the mathematics of data science using algebraic approaches to answer data analysis questions.

  In a world where urban traffic congestion and environmental concerns are escalating, innovative solutions are crucial for creating sustainable and efficient transportation systems. A groundbreaking study led by Hongbin Ma from the National Key Lab of Autonomous Intelligent Unmanned Systems at the School of Automation, Beijing Institute of Technology, introduces a pioneering approach that combines Long Range (LoRa) technology with distributed machine learning to optimize network connectivity for green and intelligent transportation systems.

A powerful AI model called Deep Novel Mutation Search (DNMS) predicts virus mutations more accurately and efficiently than traditional, time-consuming lab experiments. Focused on the SARS-CoV-2 spike protein, the model uses a specialized protein language model fine-tuned to understand the virus's specific “language.” DNMS can predict mutations that cause small, functional changes – crucial for viruses like SARS-CoV-2, which evolve through subtle adjustments to maintain function. This approach promises to enhance virus tracking and public health by predicting mutations more accurately and quickly.

Dartmouth researchers conducted the first clinical trial of an AI-powered therapy chatbot and found that, on average, people with diagnosed mental disorders experienced clinically significant improvements in their symptoms over eight weeks, according to results published in NEJM AI, a journal from the publishers of the New England Journal of Medicine. Users engaged with the software, known as Therabot, through a smartphone app and reported that interactions were comparable to working with a mental-health professional. The researchers conclude that while AI-powered therapy is in critical need of clinician oversight, it has the potential to provide real-time support for the many people who lack regular or immediate access to a professional.