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.
Recent technological advances facilitate the reconstruction of complete brain connectomes in small organisms and partial connectomes in mammals, involving the mapping of the network of neurons and synaptic connections. Accurate cell typing of these connectomes aids in interpreting circuit functions and comparing brain organization across species.
Traditionally, cell typing relied on manual morphological classification by experts—a slow process that required detailed anatomical information. However, morphology can be deceptive or inadequate in many brain regions, especially in circuits with repeated cell types, where neurons can share very similar morphology despite differing in connectivity.
How do scientists come up with new ideas? Brain scans show that scientific creativity requires the brain’s imagination, control, and switching networks to actively communicate to generate and evaluate novel hypotheses.
Using the Mayall 4-meter telescope at Kitt Peak National Observatory, an international team of astronomers has observed C-19—an extremely metal-poor stellar stream in the Milky Way’s halo. Results of the observational campaign, published March 11 on the arXiv pre-print server, provide crucial insights into the properties of this stellar stream.
Stellar streams are remnants of dwarf galaxies or globular clusters (GCs) that once orbited a galaxy but have been disrupted and stretched out along their orbits by tidal forces of their hosts. Observations show that many stellar streams are elongated debris of tidally disrupted globular clusters.
Studies of galactic stellar streams could answer some crucial questions about the Milky Way. For instance, they could help us understand the large-scale mass distribution of the galactic dark matter halo. Moreover, the investigation of stellar streams could confirm whether or not our galaxy contains low-mass dark matter subhalos.
Researchers at Pointcloud GmbH in Zürich, Switzerland, have packed advanced 4D sensing technology — once too bulky for everyday use — onto a single silicon chip.
It’s a 4D imaging sensor that maps the physical world while simultaneously clocking the speed of every object it sees. It offers a low-cost, high-speed vision solution for everything from autonomous drones to future smartphones.
“This result demonstrates the capabilities of FMCW LiDAR FPA sensors as enablers of ubiquitous, low-cost, compact coherent 4D imaging cameras,” the researchers wrote in the study paper.
Researchers have identified a distinct and reproducible gene expression program associated with neurotransmission in the living human brain, offering unprecedented insight into the molecular mechanisms that support human cognition, emotion, and behavior. The findings were published February 19 in Molecular Psychiatry.
Neurotransmission-the electrical and chemical signaling between neurons-is fundamental to all brain function. Until now, most gene expression studies of the human brain have relied on postmortem tissue, limiting scientists’ ability to understand which genes are actively involved in real-time neuronal communication.
In this study, investigators integrated gene expression profiling from the prefrontal cortex with direct intracranial measures of neurotransmission collected from the brains of more than 100 individuals as they underwent neurosurgical procedures. By combining molecular data with real-time physiological recordings, the team identified a coordinated set of genes whose activity tracks with neuronal signaling-a transcriptional program associated with neurotransmission.
Does the universe need observers to exist? Neil deGrasse Tyson and co-hosts Chuck Nice and Gary O’Reilly explore questions about entropy, spontaneous symmetry breaking, spectroscopy and more with astrophysicist Charles Liu.
Does the universe require observers for information to exist? From Niels Bohr and the Copenhagen interpretation to modern neuroscience and philosophy, the crew explores whether measurement creates reality or reveals it. How does the double-slit experiment fit into this? Are wave and particle behaviors determined by how we measure them?
The conversation turns to information itself. What do physicists mean by “information”? How is entropy connected to hidden information in a system? We discuss entropy through everyday examples like coin flips, burning wood, and boiling water. How does this relate to quantum computing? We explore how astronomers separate cosmic redshift from stellar motion using spectroscopy, how interstellar dust and extinction curves complicate observations, and why mapping that dust is both a challenge and a source of discovery.
We discuss why the Big Bang didn’t form a black hole, how spontaneous symmetry breaking may have split the fundamental forces, and whether science can meaningfully investigate the universe’s earliest moments. Wrapping up, the team looks ahead to multi-messenger astronomy, next-generation telescope technology, exotic ideas about the speed of light, and how information continues to reshape what we know about the cosmos.
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A stunning new map of the Milky Way reveals a dramatic magnetic flip hiding in plain sight. Deep inside the Milky Way, an invisible force is quietly holding everything together — its magnetic field. Now, researchers have created one of the most detailed maps ever of this hidden structure, revealing surprising twists in how it flows through our galaxy.
For generations, scientists have studied the stars and planets to better understand how our galaxy works. Now, Dr. Jo-Anne Brown, PhD, is focused on charting something we cannot see at all: the Milky Way’s magnetic field.
“Without a magnetic field, the galaxy would collapse in on itself due to gravity,” says Brown, a professor in the Department of Physics and Astronomy at the University of Calgary.
China just released DuClaw, a new platform that lets anyone run OpenClaw AI agents instantly from a web browser without dealing with deployment, servers, or API keys. At the same time, researchers at Stanford introduced OpenJarvis, a framework that allows personal AI assistants to run entirely on your own computer instead of the cloud. Meanwhile Google is using Gemini to build the largest flash flood dataset ever created, mapping millions of disaster events across the planet. And a new toolkit called gstack is turning AI coding into something far more autonomous, allowing AI systems to plan software, test applications, and review code automatically.
🧠 What You’ll See. Baidu launches DuClaw to run OpenClaw AI agents directly from a browser. SOURCE: https://pandaily.com/baidu-ai-cloud-l… introduces OpenJarvis for fully local AI assistants SOURCE: https://www.marktechpost.com/2026/03/.… Google uses Gemini to build the largest flash flood dataset ever created SOURCE: https://www.wsj.com/articles/google-t… gstack toolkit organizes AI into automated software development workflows SOURCE: https://www.producthunt.com/products/.… 🚨 Why It Matters These developments show how quickly artificial intelligence is moving toward more autonomous systems. From browser based AI agents that run instantly, to personal assistants that operate entirely on local machines, the way people interact with AI is changing rapidly. At the same time, large scale AI systems are being used to analyze global disasters and predict floods, while new developer tools are allowing AI to plan, test, and review software almost like an engineering team. #ai #artificialintelligence #ainews.
Current vision systems for robots and drones rely on 3D sensors that, although powerful, do not always keep up with the fast-paced, unpredictable movement of the real world. These systems often struggle to measure speed instantly or are too bulky and expensive for everyday use. Now, in a paper published in the journal Nature, scientists report how they have developed a 4D imaging sensor on a chip that creates 3D maps of an environment while simultaneously tracking the speed of moving objects.
The researchers built a focal plane array (FPA), a physical grid of 61,952 stationary pixels etched onto a single silicon chip. Each one is a tiny sensor that emits laser light toward a scene and detects the reflected signal.
To “see” its surroundings, laser light from an external source is fed into the chip. This light is routed across the chip through a network of optical switches that sequentially direct it to groups of pixels. Each pixel then uses a technique called FMCW LiDAR to measure the returning signal, which is later processed to determine distance and speed. In many LiDAR systems, one set of pixels sends the light, and another receives it, but here, all pixels both send and receive, making the system much more compact.
