ScienceDaily: Computers & Math News

Dozens of mutations in the spike protein of the Omicron variant help it to evade all four of the classes of antibodies that can target SARS-CoV-2, according to a new study. This includes antibodies generated by the immune systems of vaccinated or previously infected people, as well as most of the monoclonal antibody treatments that have been developed.

Researchers have combined location density with real-world mobility data to predict the risk of infection from COVID-19 at specific locations with unprecedented accuracy.

Scientists develop a chaos-based stream cipher that can withstand attacks from large-scale quantum computers.

Scientists have developed organic microparticles that can steer through biological fluids and dissolved blood in unprecedented ways. Even in very salty liquids, the microswimmers can be propelled forward at high speed by visible light, either individually or as a swarm. Additionally, they are partially biocompatible and can take up and release cargo on demand. The material properties are so ideal they could pave the way toward designing semi-autonomous microrobots applied in biomedicine.

So far, safely charging devices anywhere in a large area has been a challenge, but researchers have developed a transfer technology that can direct power to individual devices without needing to know their location. The technology has already been tested with commercial robots, and it can also be used to charge phones, laptops, or household appliances. No plugs, no tracking, and no complex computing -- just clever use of electromagnetics. Devices can be charged while they are moving, so with a bit more development this technology could even charge electric cars on the road.

Researchers have built a machine learning framework that can define the mathematical equations describing a cell's trajectory from one state to another, such as its development from a stem cell into one of several different types of mature cell. The framework, called dynamo, can also be used to figure out the underlying mechanisms -- the specific cocktail of gene activity -- driving changes in the cell.

While cellular networks are the foundation of smart cities, they consume a lot of energy, enhancing global warming. Putting base stations (BSs) with low traffic to sleep saves energy but also reduces traffic prediction accuracy. In a new study, researchers address this trade-off using machine learning technique to switch off BSs based on their contribution to prediction accuracy. The new scheme reduces power consumption and demonstrates a prediction accuracy superior to benchmark schemes.

A team of mathematicians and physicists has discovered how ice formations are shaped by external forces, such as water temperature. Its newly published research may offer another means for gauging factors that cause ice to melt.

Computers could mimic neural networks in the brain -- and be much more energy efficient -- with a new computer component that mimics how the brain works by acting like a synaptic cell. It's called an electrochemical random access memory (ECRAM), and researchers have developed materials that offer a commercially-viable way to build these components.

Recently, magnons (units of electron spin excitation waves) have been considered for information processing. Especially, utilizing thermally excited energetic magnons have been of interest. In parallel, the demand for faster and energy-efficient electronic devices has brought attention to quantum devices using quantum spin state in diamond, which can surpass conventional performance. Now, researchers have successfully measured thermal magnon currents mediated by coherent magnon with a tiny diamond quantum sensor, paving the way for the realization of a hybrid system of quantum spin states and thermal spintronic devices.