Computers and Math from Science Daily Feed

Researchers have invented a new optical element that brings us one step closer to mixing the real and virtual worlds in an ordinary pair of eyeglasses using high-definition 3D holographic images.

Researchers have developed a deep learning tool that is capable of reliably diagnosing moon blindness in horses based on photos.

Magnetic cilia -- artificial hairs whose movement is powered by embedded magnetic particles -- have been around for a while, and are of interest for applications in soft robotics, transporting objects and mixing liquids. However, existing magnetic cilia move in a fixed way. Researchers have now demonstrated a technique for creating magnetic cilia that can be 'reprogrammed,' changing their magnetic properties at room temperature to change the motion of the cilia as needed.

The mass production of conventional silicon chips relies on a successful business model with large 'semiconductor fabrication plants' or 'foundries'. New research by shows that this 'foundry' model can also be applied to the field of flexible, thin-film electronics.

Researchers have found a way to super-charge the 'engine' of sustainable fuel generation -- by giving the materials a little twist. The researchers are developing low-cost light-harvesting semiconductors that power devices for converting water into clean hydrogen fuel, using just the power of the sun. These semiconducting materials, known as copper oxides, are cheap, abundant and non-toxic, but their performance does not come close to silicon, which dominates the semiconductor market.

Crossing roads for children can be a risky calculation, especially when the vehicles are self-driven. In a new study, researchers determined pre-teenage children are safest when self-driving vehicles signaled their intent to yield with a green light when they arrived at the intersection, then stopped.

In a significant development in the field of superconductivity, researchers have successfully achieved robust superconductivity in high magnetic fields using a newly created one-dimensional (1D) system. This breakthrough offers a promising pathway to achieving superconductivity in the quantum Hall regime, a longstanding challenge in condensed matter physics.

Scientists report a new method that achieves for the first time valley polarization in centrosymmetric bulk materials in a non-material-specific way. This 'universal technique' may have major applications linked to the control and analysis of different properties for 2D and 3D materials, which can in turn enable the advancement of cutting-edge fields such us information processing and quantum computing.

A lead-vacancy (PbV) center in diamond has been developed as a quantum emitter for large-scale quantum networks by researchers. This innovative color center exhibits a sharp zero-phonon-line and emits photons with specific frequencies. The PbV color center stands out among other diamond color centers due to its ability to maintain optical properties at relatively high temperatures of 16 K. This makes it well-suited for transferring quantum information in large-scale quantum networks.

A new chip can efficiently accelerate machine-learning workloads on edge devices like smartphones while protecting sensitive user data from two common types of attacks -- side-channel attacks and bus-probing attacks.

Video gamers who exploit glitches in games can help experts better understand buggy software, students suggest.

Sure, ChatGPT can write a poem about your pet in the style of T.S Eliot, but generative artificial intelligence (AI) chatbots have a potentially more useful role to play in idea generation according to a new study.

Researchers have discovered a unique property, the quantum metric, within magnetic materials, altering the 'electron universe' geometry. This distinct electric signal challenges traditional electrical conduction and could revolutionize spintronic devices.

Using neutron scattering and voltage measurements, a group of researchers have discovered that a material's magnetic properties can predict spin current changes with temperature. The finding is a major breakthrough in the field of spintronics.

Hexagonal boron nitride (hBN) has gained widespread attention and application across various quantum fields and technologies because it contains single-photon emmiters (SPEs), along with a layered structure that is easy to manipulation. The precise mechanisms governing the development and function of SPEs within hBN have remained elusive. Now, a new study reveals significant insights into the properties of hBN, offering a solution to discrepancies in previous research on the proposed origins of SPEs within the material.

Researchers have developed a method to use an image generation AI model to create realistic images of single cells, which are then used as 'synthetic data' to train an AI model to better carry out single-cell segmentation.

Researchers are using artificial intelligence to uncover the link between the gut microbiome and Alzheimer's disease. Previous studies showed that Alzheimer's disease patients have changes in their gut bacteria as the disease develops. The study outlines a computational method to determine how bacterial byproducts called metabolites interact with receptors on cells and contribute to Alzheimer's disease.

A sensing technology that can assess the quality of components in fields such as aerospace could transform UK industry.

Physicists have shown that ultra-thin two-dimensional materials such as tungsten diselenide can rotate the polarization of visible light by several degrees at certain wavelengths under small magnetic fields suitable for use on chips.

Atrial fibrillation is the most common cardiac arrhythmia worldwide with around 59 million people concerned in 2019. This irregular heartbeat is associated with increased risks of heart failure, dementia and stroke. It constitutes a significant burden to healthcare systems, making its early detection and treatment a major goal. Researchers have recently developed a deep-learning model capable of predicting the transition from a normal cardiac rhythm to atrial fibrillation. It gives early warnings on average 30 minutes before onset, with an accuracy of around 80%. These results pave the way for integration into wearable technologies, allowing early interventions and better patient outcomes.