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Category: robotics/AI – Page 9

Wind-powered robot could enable long-term exploration of hostile environments

Researchers at Cranfield University have created WANDER-bot, a low-cost, 3D-printed robot that is powered by wind energy. Designed to spend long durations in hostile, windy environments such as certain deserts, polar regions or even other planets, WANDER-bot doesn’t need a battery to power movement, enabling longer operations without having to pause and recharge.

Movement accounts for around 20% of battery use in most robots, so running on natural energy makes WANDER-bot an efficient solution for long-term exploration or mapping of unknown terrains. As a result, any electronic elements added to future versions for data collection or transmission purposes could have their own smaller, lighter power source. Using natural energy also counters the issue of performance degradation over time in traditional power sources, such as solar cells and radioisotope thermoelectric generators.

Designed by Dr. Saurabh Upadhyay and Sam Kurian, Research Associate in Space Engineering, the robot uses parts that are entirely 3D printed, with the design deliberately simple to allow for quick repair and replacement. This means that, in theory, you could print and construct WANDER-bot anywhere and make replacement parts in situ as needed, removing the need for time-consuming and costly resupply missions.

Designing better 2D electronics: Addressing anisotropic conductivity to cut contact resistance

The high-performance semiconductor devices powering smartphone displays, AI computing, EV batteries and more are increasingly incorporating 2D materials to overcome silicon’s scaling limits. To optimize these technologies, a University of Michigan Engineering team developed a precise mathematical framework that accounts for anisotropic—or unevenly spreading—conductivity and device geometry.

Accurate models of how currents move through anisotropic thin films, made of layered 2D materials, can enable the design of more reliable, high-performance nanoelectric devices. Specifically, the model can help engineers reduce current crowding and spreading resistance, essentially current traffic jams, that occur at vertical electrical contacts that connect with the top of a 2D surface. The study is published in ACS Applied Electronic Materials.

AI-powered imaging tracks wound healing under the skin in real time

No matter the size or severity, wounds on human skin are difficult to monitor while they heal. Biopsies disrupt the wound site and are too invasive for routine, repeated monitoring, and most medical imaging devices that could do the job are large, expensive, and booked up with more pressing diagnostics. Clinicians typically resort to visual inspection or quick measurements of the wound’s size over time.

Based on research completed as part of a multi-year collaboration with Nokia Bell Labs, biomedical engineers at Duke University are developing a solution. Using a custom-built optical coherence tomography (OCT) imaging system together with artificial intelligence (AI) models grounded in a deep understanding of tissue regeneration, researchers have shown they can accurately and objectively measure the progress of wounds healing over time.

Using their new approach, the researchers also show that a hydrogel under development to improve wound healing works better with stiffer mechanical properties. The results are a two-for-one boon in a challenging area for both clinicians and researchers.

Machine Learning–Based Sleep EEG Brain Age Index and Dementia Risk

Machine learning models using sleep EEG can generate a brain age index, and a higher BAI was validated as a prognostic marker for increased risk of future Dementia, suggesting BAI may help in early digital risk stratification.

This individual participant data meta-analysis explores the association between a machine learning–based sleep electroencephalography (EEG) brain age index and dementia risk among community-dwelling adults from 5 longitudinal cohorts.

AI chatbots’ tendency to always agree may reinforce delusions in vulnerable users

The integration of large language model-based AI chatbots into multiple facets of our everyday lives has opened us up to advantages that would have been considered impossible even a decade ago. The same development has, however, opened us up to unforeseen risks, including the impact that engaging with AI chatbots can have on people dealing with mental illness.

AI chatbots are designed to keep conversations going, often by agreeing with users. A article by researchers from King’s College, London, found that this sycophantic tendency may sometimes do more harm than good, reinforcing unusual thoughts rather than challenging them, and potentially contributing to AI-associated delusions, in which users develop or worsen false beliefs about reality.

These interactions can reinforce or even shape delusional beliefs, such as thinking one is uniquely important, being targeted by others, or being in a romantic relationship that does not exist.

New ‘PolyShell’ flaw allows unauthenticated RCE on Magento e-stores

A newly disclosed vulnerability dubbed ‘PolyShell’ affects all Magento Open Source and Adobe Commerce stable version 2 installations, allowing unauthenticated code execution and account takeover.

There are no signs of the issue being actively exploited in the wild, but eCommerce security company Sansec warns that “the exploit method is circulating already” and expects automated attacks to start soon.

Adobe has released a fix, but it is only available in the second alpha release for version 2.4.9, leaving production versions vulnerable. Sansec says that Adobe offers a “sample web server configuration that would largely limit the fallout,” but most stores rely on a setup from their hosting provider.

Survey: What are neuroscience’s most transformative new tools?

A nicely organized list of what various investigators highlight as the most transformative neuroscience tools from the past 5 years!

Which new tools—including artificial intelligence, deep-learning methods, genetic tools and advanced neuroimaging—are making the largest impact?

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