Tech
In certain materials, electrical and mechanical effects are closely linked: for example, the material may change its shape when an electrical field is applied or, conversely, an electrical field may be created when the material is deformed. Such electromechanically active materials are very important for many technical applications.
Swapping the car for walking, cycling and e-biking even just one day a week makes a significant impact on personal carbon emissions in cities.
'Active transport' - cycling, e-biking or walking - can help tackle the climate crisis according to a new study led by the University of Oxford's Transport Studies Unit and including researchers from Imperial's Centre for Environmental Policy as part of the EU-funded project PASTA: Physical Activity Through Sustainable Transport Approaches.
Is a quantum machine really more efficient than a conventional machine for performing calculations? Demonstrating this 'advantage' experimentally is particularly complex and a major research challenge around the world1. Scientists from the CNRS2, the University of Edinburgh (Scotland) and the QC Ware, Corp., (France and USA) have just proved that a quantum machine can perform a given verification task in seconds when the same exercise would take a time equivalent to the age of the universe for a conventional computer.
An important class of challenging computational problems, with applications in graph theory, neural networks, artificial intelligence and error-correcting codes can be solved by multiplying light signals, according to researchers from the University of Cambridge and Skolkovo Institute of Science and Technology in Russia.
A way of using machine learning to more accurately identify patients with a mix of psychotic and depressive symptoms has been developed by researchers at the University of Birmingham.
Patients with depression or psychosis rarely experience symptoms of purely one or the other illness. Historically, this has meant that mental health clinicians give a diagnosis of a 'primary' illness, but with secondary symptoms. Making an accurate diagnosis is a big challenge for clinicians and diagnoses often do not accurately reflect the complexity of individual experience or indeed neurobiology.
Recycling cans and bottles is a good practice. It helps keep the planet clean.
The same is true for recycling within cells in the body. Each cell has a way of cleaning out waste in order to regenerate newer, healthier cells. This "cell recycling" is called autophagy.
Targeting and changing this process has been linked to helping control or diminish certain cancers. Now, University of Cincinnati researchers have shown that completely halting this process in a very aggressive form of breast cancer may improve outcomes for patients one day.
Electrons in materials have a property known as 'spin', which is responsible for a variety of properties, the most well-known of which is magnetism. Permanent magnets, like the ones used for refrigerator doors, have all the spins in their electrons aligned in the same direction. Scientists refer to this behaviour as ferromagnetism, and the research field of trying to manipulate spin as spintronics.
Researchers have identified a new form of magnetism in so-called magnetic graphene, which could point the way toward understanding superconductivity in this unusual type of material.
The researchers, led by the University of Cambridge, were able to control the conductivity and magnetism of iron thiophosphate (FePS3), a two-dimensional material which undergoes a transition from an insulator to a metal when compressed. This class of magnetic materials offers new routes to understanding the physics of new magnetic states and superconductivity.
A pathway in the brain where alcohol addiction first develops has been identified by a team of British and Chinese researchers in a new study
Could lead to more effective interventions when tackling compulsive and impulsive drinking
More than 3 million deaths every year are related to alcohol use globally, according to the World Health Organisation
Cold Spring Harbor Laboratory (CSHL) Assistant Professor Peter Koo and collaborator Matt Ploenzke reported a way to train machines to predict the function of DNA sequences. They used "neural nets", a type of artificial intelligence (AI) typically used to classify images. Teaching the neural net to predict the function of short stretches of DNA allowed it to work up to deciphering larger patterns. The researchers hope to analyze more complex DNA sequences that regulate gene activity critical to development and disease.
How come we don't hear everything twice: After all, our ears sit on opposite sides of our head and most sounds do not reach both our ears at exactly the same time. "While this helps us determine which direction sounds are coming from, it also means that our brain has to combine the information from both ears. Otherwise, we would hear an echo," explains Basil Preisig of the Department of Psychology at the University of Zurich.
Bark beetle outbreaks and wildfire alone are not a death sentence for Colorado's beloved forests--but when combined, their toll may become more permanent, shows new research from the University of Colorado Boulder.
It finds that when wildfire follows a severe spruce beetle outbreak in the Rocky Mountains, Engelmann spruce trees are unable to recover and grow back, while aspen tree roots survive underground. The study, published last month in Ecosphere, is one of the first to document the effects of bark beetle kill on high elevation forests' recovery from wildfire.
A team of engineers and scientists has developed a method of 'multiplying' organoids: miniature collections of cells that mimic the behaviour of various organs and are promising tools for the study of human biology and disease.
The researchers, from the University of Cambridge, used their method to culture and grow a 'mini-airway', the first time that a tube-shaped organoid has been developed without the need for any external support.
DANVILLE, Pa. - Researchers at Geisinger have found that a computer algorithm developed using echocardiogram videos of the heart can predict mortality within a year.
The algorithm--an example of what is known as machine learning, or artificial intelligence (AI)--outperformed other clinically used predictors, including pooled cohort equations and the Seattle Heart Failure score. The results of the study were published in Nature Biomedical Engineering.
Older adults who are classified as having "prediabetes" due to moderately elevated measures of blood sugar usually don't go on to develop full-blown diabetes, according to a study led by researchers at Johns Hopkins Bloomberg School of Public Health.
Doctors still consider prediabetes a useful indicator of future diabetes risk in young and middle-aged adults. However, the study, which followed nearly 3,500 older adults, of median age 76, for about six and a half years, suggests that prediabetes is not a useful marker of diabetes risk in people of more advanced age.