Nanosized cages may play a big role in reducing energy consumption in science and industry, and machine-learning research aims to accelerate the deployment of these remarkable molecules.
Impulse online shopping, downloading music and compulsive email use are all signs of a certain personality trait that make you a target for malware attacks. New research from Michigan State University examines the behaviors -- both obvious and subtle -- that lead someone to fall victim to cybercrime involving Trojans, viruses, and malware.
Researchers at the University of Illinois and the National Center for Supercomputing Applications have advanced the use of genome wide association studies (GWAS) to identify multiple interacting markers for a given trait.
A Washington State University research team has uncovered significant and previously unknown vulnerabilities in high-performance computer chips that could lead to failures in modern electronics.
The mathematical models can be used not only for quantum networks and authentication but also for full-scale quantum computing. Quantum hashing can help protect quantum algorithms against mistakes. Relevant research is currently in progress at Kazan Federal University.
A research team from the University of Zurich has developed a new drone that can retract its propeller arms in flight and make itself small to fit through narrow gaps and holes. This is particularly useful when searching for victims of natural disasters.
Deep-learning technique reveals transparent objects in the dark.
New 'classification models' sense how well humans trust intelligent machines they collaborate with, a step toward improving the quality of interactions and teamwork.
Researchers at the Wyss Institute have created a novel 3D printing workflow that allows cardiologists to evaluate how different valve sizes will interact with each patient's unique anatomy, before the medical procedure is actually performed. This protocol uses CT scan data to produce physical models of individual patients' aortic valves, in addition to a 'sizer' device to determine the perfect replacement valve size.
A new study by MIT researchers finds that the growing practice of compiling massive, anonymized datasets about people's movement patterns is a double-edged sword: While it can provide deep insights into human behavior for research, it could also put people's private data at risk.