Scientists develop novel 3D-spiral circuit design for faster and more energy-efficient machine learning training. The design reduces interconnecting wiring needs and enhances algorithm accuracy up to 90%. This innovation may enable the next generation of energy-efficient AI devices.
Researchers used in situ observations and simulations to understand the composition and sources of aerosols in the Asian Tropopause Aerosol Layer (ATAL). They found that part of the aerosols were transported from the Earth surface and upper troposphere, influencing the ATAL's formation.
A study by University of Queensland researchers found that maternal depression is linked to higher risks of behavioral problems and poor development in children. The study suggests that reducing depressive symptoms at any stage can improve outcomes for both mothers and children.
KAUST scientists create first water-stable, n-type semiconducting polymer doped with ammonium salt, enabling stable conversion of ionic signals into electronic signals. The innovation has potential applications in glucose sensors, enzymatic fuel cells and monitoring ion channel activity.
A new study led by Dr Melyssa Roy found that later bedtimes for children between the ages of 2 and 5 years old aren't directly linked to an increased risk of obesity. The study revealed that these children slept for a longer duration, which may limit eating opportunities and reduce overall caloric intake.
Researchers are collecting DNA data from popular home genetic-testing kits to identify key genes involved in the body's response to Covid-19. The study, called Coronagenes, aims to understand why some people become ill while others remain symptom-free.
Researchers at UT Southwestern Medical Center have developed new MRI techniques to more precisely target brain structures linked to Parkinson's disease and essential tremor. These methods, including diffusion tractography, aim to reduce adverse effects associated with previous treatments.
Researchers developed a framework using graph theory to optimize digital communication networks, finding cliques within them for efficient data transmission and improvement in throughput by up to 30%. This approach has far-reaching implications for future networks, including the internet of things with larger volumes of data.