Scientists generate electricity from ambient moisture using everyday ingredients
Peer-Reviewed Publication
Updates every hour. Last Updated: 30-Oct-2026 23:16 ET (31-Oct-2026 03:16 GMT/UTC)
An international research team led by scientists at Queen Mary University of London has developed an innovative method to power wearable electronics using ambient moisture and simple, non-toxic materials commonly found in the kitchen.
In June 2020, Intel announced the first hardware availability of Control-Flow Enforcement Technology (CET). This hardware-based protection mechanism has been gradually introduced since Intel’s 10th and 11th Core generations and is integrated into newer Windows and Linux operating systems. CET is designed to make so-called code-reuse attacks more difficult, in which attackers exploit existing program code to compromise systems. Researchers have shown, however, that it is still possible to transition between program libraries and thus bypass the protection mechanisms. PLaTypus restricts precisely this freedom of movement. This additional security layer was developed by Apostolos Chatzianagnostou and Marcos Bajo from the team of CISPA-Faculty Prof. Dr. Christian Rossow.
A large-scale analysis of Grokipedia, the world’s first AI-written encyclopedia, has found that while many Grokipedia articles closely resemble their Wikipedia counterparts, a substantial subset diverged markedly in style, sourcing, and political leaning.
Tumor cells exploit chemokine signaling to construct an immunosuppressive microenvironment that resists anti-tumor immune responses. A new review systematically maps the chemokine-receptor network in the tumor microenvironment and introduces a three-part “3D” targeting strategy: Decrease recruitment of suppressive cells (Tregs, MDSCs, TAMs), Develop effector T cell and NK cell function, and Dismantle physical and signaling barriers that exclude effectors from tumors. This framework ultimately provides a roadmap for precision combination immunotherapy to overcome immune evasion
As AI is being widely tested in medicine, scientists at the University of Auckland, Auckland City Hospital, and Matai Medical Research Institute in New Zealand have analyzed the current landscape of AI models for meningioma (a cancer of the brain’s soft cover) segmentation from MRI scans, and its path ahead. Their key finding is that advanced model architecture has considerably contributed to tumor detection sensitivity, rather than data characteristics, imaging modalities, or preprocessing.