Toggle light / dark theme

Microscale hydrogel fibers could enable imaging inside tiny tissue structures

Researchers have developed light-transmitting hydrogel fibers that are just hundreds of micrometers in diameter. With further development, these soft fibers could one day make it possible to use imaging techniques to detect early breast cancer hidden inside very small breast ducts.

“While traditional, relatively rigid fiber probes may cause mechanical damage when entering narrow, curved or soft tissue spaces, our fibers are very soft with mechanical properties more similar to those of human soft tissues,” said research team leader Yu Zhang from Harbin Engineering University in China. “We made these fibers using a draw-spinning method that was inspired by spider-silk spinning.”

In research appearing in Optics Express, the researchers describe how they tested the new hydrogel fibers by incorporating them into an imaging system and using it to analyze standard pathology-stained breast tissue sections. The imaging system successfully reconstructed the microscopic features used by pathologists to evaluate tumors and, when combined with artificial intelligence algorithms, distinguished tumor subtypes with an accuracy of 93.97%.

Astrochemical model digs into the universe’s missing sulfur

Sulfur is one of the most abundant elements in the universe. If you peer into a diffuse interstellar cloud, you find loads of it—about the amount expected based on fusion patterns in the stars it was born in. However, if you look at a dense, cold molecular cloud—the kind where those stars actually form—it seems like 99% of the sulfur expected to be there is missing. Scientists have puzzled over this “missing sulfur problem” for decades, though a leading theory is that the element hides in icy dust grains, making it hard to detect.

A new paper published in Astronomy & Astrophysics from the Max Planck Institute for Extraterrestrial Physics and the Centro de Astrobiologia describes a new computer simulation model aimed at supporting the interpretation of laboratory results and testing our current understanding of sulfur evolution in interstellar ices.

The simulation was written in pyRate—a Python-based application that calculates how chemicals interact, especially between ice and gas phases. The paper marks the first successful model of the chemistry of a multicomponent interstellar ice analog with a rate-equation simulation. Scientists love “firsts,” but what does that actually mean in practice in this case?

Classical mechanics — Problem 15 — lagrangian

Here I described constraint — Holonomic, noholonomic, least squares principal.
I solved 15 problem.
lagrangian classical mechanics.
lagrangian methods.
lagrangian method example.
lagrangian method optimization.
lagrangian mechanics example.
lagrangian mechanics pdf.
classical mechanics lagrangian.
the lagrangian method.
lagrangian mechanics derivation.
lagrange method dynamics.
euler-lagrange equation in classical mechanics.
friction lagrangian.
lagrangian method for optimization.
lagrangian mechanics friction.
history of lagrangian mechanics.
how to learn lagrangian mechanics.
is lagrangian mechanics useful.
lagrangian method.
lagrangian mechanics tutorial.
lagrangian technique.
lagrangian method of constrained optimization.
lagrangian mechanics examples.
lagrangian mechanics explained.
lagrangian mechanics constraints.
hamiltonian mechanics problems.
hamiltonian classical mechanics.
hamiltonian mechanics pdf.
hamiltonian in classical physics.
hamiltonian mechanics examples.
classical mechanics hamiltonian.
classical hamiltonian.
a hamilton circuit.
classical mechanics hamiltonian and lagrangian formalism.
classical mechanics problems and solutions.
hamiltonian problems and solutions.
lagrangian and hamiltonian mechanics calkin pdf.
solving hamiltonian equations.
hamiltonian mechanics vs lagrangian mechanics.
what is hamiltonian in classical mechanics.
#gateexam #csirnet #nbhmphd #physics #mscmathematics #lgrangian

Quantum Computers Just Solved What AI Couldn’t — Here’s Proof

Artificial intelligence has achieved remarkable breakthroughs in recent years, from generating human-like text and images to solving complex scientific and engineering problems. Yet some challenges remain extraordinarily difficult even for the most advanced AI systems. This has fueled growing interest in quantum computing, a technology that processes information in fundamentally different ways from classical computers. Researchers are now exploring whether quantum algorithms can tackle certain optimization, simulation, and computational problems that push conventional AI systems to their limits. Recent experiments and research papers have generated excitement by demonstrating situations where quantum approaches may offer unique advantages, reigniting debate about how these two revolutionary technologies could work together in the future.

Rather than viewing quantum computing and AI as competitors, many experts believe they could become powerful partners. Quantum processors may eventually help accelerate specific machine learning tasks, improve complex simulations, and solve optimization problems that are critical to industries such as logistics, finance, materials science, and drug discovery. At the same time, scientists caution that practical large-scale quantum computing remains an active area of research, and many headline-grabbing claims require careful scrutiny and independent verification. Even so, the rapid progress in both fields suggests that the future of computing may be shaped not by AI alone, but by a combination of artificial intelligence and quantum technologies working together to tackle problems once thought impossible.

Disclaimer.

This video is intended for educational and informational purposes only. Quantum computing and artificial intelligence are rapidly evolving fields, and interpretations of research findings may change as new evidence becomes available. The content presented is based on publicly available studies, expert analysis, and current technological developments.

Like \& Subscribe.

If you enjoyed this video, please Like, Share, and Subscribe for more quantum computing news, AI breakthroughs, technology analysis, and future-tech insights.

Quantum gravity research links continuous parameters to local operators within the theory itself

A researcher at Kyushu University and his collaborators have shown that continuous parameters in quantum gravity may not be freely adjustable “dials” from outside the theory, but rather arise from operators within the theory itself, supporting the century-old claim by Albert Einstein about the fundamental laws of nature.

Einstein argued that the fundamental equations of physics contain no freely adjustable parameters. In other words, he believed that the laws of nature should not include arbitrary numbers chosen from outside a theory. Instead, such quantities should emerge naturally from physical processes.

This idea has become especially important in the search for quantum gravity, a theory that aims to combine gravity with quantum mechanics. Physicists expect that the equations governing quantum gravity should not contain freely adjustable quantities. Rather, all parameters should arise from physical fields.

Driverless cars are on the rise and now we may know why they crash

For the first time, new algorithms may be able to automatically explain why some self-driving cars crash—a question crucial to answer as more autonomous vehicles take to the roads. This new approach, developed by researchers at King’s College London, reviews past events to explain why specific instances of failure happened, in the hope that this can be used to make improvements in the future.

The research was presented at the 2026 IEEE International Conference of Robotics and Automation.

Self-driving vehicles are increasingly being rolled out across the globe, in cities like London and San Francisco, but collisions and serious breaches of road safety have put pressure on manufacturers to explain why they make the mistakes they do. This is often hard to do, and current methods only provide limited explanations for these.

How to Build a Synthethic Mind: Brain Inspired AI Exists Now

Further Reading.
Thumbnail image credit: Adobe Stock.

Brains and algorithms partially converge in natural language processing.
https://www.nature.com/articles/s4200

Strong Prediction: Language Model Surprisal Explains Multiple N400 Effects.
https://pmc.ncbi.nlm.nih.gov/articles

Foundation model of neural activity predicts response to new stimulus types.
https://www.nature.com/articles/s4158

Dendrites endow artificial neural networks with accurate, robust and parameter-efficient learning.
https://www.nature.com/articles/s4146

A Computational Perspective on NeuroAI and Synthetic Biological Intelligence.

What’s New in Science: Cosmic Surprises, Newton Supreme, A New Collider, and Feynman Dines Out?

I think this was one of my most enjoyable dialogues in our What’s new series. Maybe Sabine and I are getting more used to each other’s cadence and interests or maybe it was the subject matter. Either way, I think you will find this to be a fascinating and provocative discussion of science at the forefront, and at the not-so-forefront, because that science is interesting too! We began our discussion describing a new finding of a Giant Ring of galaxies billions of light years across in the sky. The key questions are: Is it real? And is it surprising? We both have slightly different takes on this. Next we described a new measurement of the strength of gravity on scales from 80 to 800 million light years in distance. And guess what? Gravity falls off just like Newton predicted! This may seem like a big yawn, but one of the most popular models that claims to do away with dark matter would imply that Gravity would fall off differently on these scales. Does this new result kill that idea? Stay tuned. Microsoft, which has cried wolf a number of times so far when it comes to something called Majorana qubits as the basis of a new viable quantum computer just published a new paper claiming they finally have it. Sabine and I discuss why we are both still skeptical, but why the effort is worth it. Next, CERN, the large European particle physics laboratory, and the world particle physics community seem to have converged on plans for building a huge new accelerator in the current CERN site… this time involving an underground ring 91 km in circumference, in which electrons and positrons would collide to explore the detailed properties of the Higgs particle. Is the effort worth it? Again, Sabine and I have slightly different takes on this. Fusion power, which we have talked about in a number of earlier episodes, continues to tempt humanity with the promise of unlimited energy. Many people, myself included, have tended to argue that fusion seems to be 25 years in the future, and may always be 25 years in the future. But many new efforts are underway, so who knows. Unfortunately, a group of economists has analyzed fusion in the context of other large energy programs and have argued that even if we can achieve it, it may not be as economically viable as many claim. Finally, one day Richard Feynman went to a Thai restaurant with his young companion Ralph Leighton, and wondered what he should order. Should it be the same old dish he loved or something new. An equation filled napkin later, and he had the answer. Fifty years later some cognitive scientists resurrected Feynman’s napkin and explained it, and argued it might have important implications in other social situations. Such is the power of science. Consider supporting the podcast and the Origins Project Foundation at https://www.originsproject.org/ To see commercial-free, full HD video episodes, join us at lawrence krauss.substack.com Thank you for your support! iTunes: https://podcasts.apple.com/us/podcasthttps://TheOriginsPodcast.com Twitter: / theoriginspod Instagram: / theoriginspod Facebook: / theoriginspod The Origins Podcast, a production of The Origins Project Foundation, features in-depth conversations with some of the most interesting people in the world about the issues that impact all of us in the 21st century. Host, theoretical physicist, lecturer, and author, Lawrence M. Krauss, will be joined by guests from a wide range of fields, including science, the arts, and journalism. The topics discussed on The Origins Podcast reflect the full range of the human experience — exploring science and culture in a way that seeks to entertain, educate, and inspire. Full Episodes Playlist: • Ricky Gervais — The Origins Podcast with L…

/* */