ScienceDaily: Computers & Math News

Using methods from conservation science, a new analysis suggests that the first case of COVID-19 arose between early October and mid-November, 2019 in China, with the most likely date of origin being November 17.

'Precision agriculture' where farmers respond in real time to changes in crop growth using nanotechnology and artificial intelligence (AI) could offer a practical solution to the challenges threatening global food security, a new study reveals.

A study on the role of microscopic particles in virus transmission suggests pollen is nothing to sneeze at. In a new study, researchers investigate how pollen facilitates the spread of an RNA virus like the COVID-19 virus. The study draws on cutting-edge computational approaches for analyzing fluid dynamics to mimic the pollen movement from a willow tree, a prototypical pollen emitter. Airborne pollen grains contribute to the spread of airborne viruses, especially in crowded environments.

With the help of machine learning, computational biologists are learning to predict how cancers will evolve.

An algorithm lets machines teach themselves how to recognize landscapes, even amid the changing seasons.

Soil liquefaction was a major feature of the 2011 Christchurch, New Zealand earthquake that killed 185 people. Researchers developed a machine learning model to predict the amount of lateral movement that can be expected from liquefaction during a natural hazard event. Their model, trained on Christchurch data, was 70% accurate at determining the amount of displacement that occurred.

Coming soon to a lab tabletop near you: a method of magneto-thermal imaging that offers nanoscale and picosecond resolution previously available only in synchrotron facilities.

Researchers have developed a simple lab-based technique that allows them to look inside lithium-ion batteries and follow lithium ions moving in real time as the batteries charge and discharge, something which has not been possible until now.

Researchers have designed a deep learning-based system that accurately identifies individual skin stem cells grown under artificial conditions and tracks their motion. Using this system to perform quality control of stem cell cultures could improve the speed and efficiency of growing skin grafts for use in regenerative medicine and may also be useful for other types of stem cell cultures.

Researchers have developed an artificial intelligence-based brain age prediction model to quantify deviations from a healthy brain-aging trajectory in patients with mild cognitive impairment, according to a new study. The model has the potential to aid in early detection of cognitive impairment at an individual level.

Machine learning algorithms do a lot for us every day -- send unwanted email to our spam folder, warn us if our car is about to back into something, and give us recommendations on what TV show to watch next. Now, we are increasingly using these same algorithms to make environmental predictions for us.