news 2020

A transformative, cloud-computing approach to analyzing data helps researchers better understand seismic activity For the first time, we were able to identify this noise from some large machines as a distinct signal and pull it from the dataset, allowing us to separate natural signals from anthropogenic ones.

Researchers at Imperial College London and Cambridge have developed an AI algorithm that can detect and identify different types of brain injuries. The researchers found that their machine learning algorithm was able to detect, segment, quantify and differentiate between types of brain lesions using images of CT scans.

Images collected for dark energy telescope project reveal hundreds of new gravitational lens candidates Like crystal balls for the universe's deeper mysteries, galaxies and other massive space objects can serve as lenses to more distant objects and phenomena along the same path, bending light in revelatory ways.

Landing a helicopter on the deck of a ship in poor visibility is a big challenge even for the most experienced of pilots. Researchers at the Technical University of Munich (TUM) have developed an assistance system that displays key information in the visor of the pilot's helmet-mounted display. This permits precise landing approaches - even in adverse weather conditions.

Soon, your clothes may be able to monitor your vital signs, analyze the results, and warn you of health risks. In an opinion piece published in the journal Matter, members of the Fibers@MIT research group recently laid out a detailed vision for how the rapidly growing field of  advanced fibers and fabrics could transform many aspects of our lives.

"Teaching computers to teach” is key, say Carnegie Mellon researchers Intelligent tutoring systems have been shown to be effective in helping to teach certain subjects, such as algebra or grammar, but creating these computerized systems is difficult and laborious. Now, researchers at Carnegie Mellon University have shown they can rapidly build them by, in effect, teaching the computer to teach.

After analyzing 95 million traffic stop records, filed by officers with 21 state patrol agencies and 35 municipal police forces from 2011 to 2018, researchers concluded that "police stops and search decisions suffer from persistent racial bias." The largest-ever study of alleged racial profiling during traffic stops has found that blacks, who are pulled over more frequently than whites by day, are much less likely to be stopped after sunset, when "a veil of darkness" masks their race.

A new algorithm could enable faster, less expensive detection of weapons-grade nuclear materials at borders, quickly differentiating between benign and illicit radiation signatures in the same cargo. The development is a collaboration among researchers at the University of Michigan, University of Illinois, Los Alamos National Laboratory, Heriot-Watt University (Edinburgh, Scotland) and University of Edinburgh.

CMU researchers propose a multimodal system to track foods, liquid intake Food plays a big role in our health, and for that reason many people trying to improve their diet often track what they eat. A new wearable from researchers in Carnegie Mellon University's School of Computer Science helps wearers track their food habits with high fidelity.

Yale University researchers and colleagues in Hong Kong and China have developed an approach for rapidly tracking population flows that could help policymakers worldwide more effectively assess risk of disease spread and allocate limited resources as they combat the COVID-19 pandemic. The approach, described in a study published early online on April 29 , differs from existing epidemiological models by exploiting real-time data about population flows, such as phone use data and other "big data" sources that can accurately quantify the movement of people.

Open-source platform "VirtualFlow" examines billions of molecules in a very short time / Joint press release issued by Freie Universität Berlin and Technische Universität Berlin No 071/2020 from Apr 29, 2020 The development of new active compounds in medicine can take many years and potentially cost billions of euros.

Software LipidCreator enables researchers to characterise 60 lipid classes in cells with mass spectrometry Researchers increasingly aim at utilising the manifold functions of lipids in our bodies, e.g. as blood fats or in blood coagulation, to better understand and predict diseases. An international team around Robert Ahrends at the Faculty of Chemistry of the University of Vienna now presented a groundbreaking tool for efficient lipid analysis in the journal "Nature Communications".

A team of materials scientists at Lawrence Berkeley National Laboratory (Berkeley Lab) - scientists who normally spend their time researching things like high-performance materials for thermoelectrics or battery cathodes - have built a text-mining tool in record time to help the global scientific community synthesize the mountain of scientific literature on COVID-19 being generated every day.

The University of Stuttgart will be the first European institution to join the AI Horizons Network of IBM in order to advance AI research on the interaction of language and knowledge as part of a multi-year cooperation. The AI Horizons Network is a global network of researchers and doctoral students founded by IBM to further develop the use of artificial intelligence, machine learning, natural language processing, and related technologies in a series of research projects and experiments.

Stanford scholar Johannes Eichstaedt has built an algorithm that can provide, in principle, a real-time indication of community well-being by analyzing social media posts. Social media can reveal more than just a single person's mood or frame of mind. It can capture the psychological states of an entire population, according to new research by Stanford scholar Johannes Eichstaedt.

Currently, the corona pandemic is dominating the entire social life in Germany and in many other parts of the world. We are working flat out in order to better help the more than one hundred thousand seriously ill people in hospitals. One promising approach to extending current treatment methods is to use existing and approved drugs to combat the virus.

We try to follow experts' cybersecurity and privacy recommendations but quite often many of us do so halfway or we give up. There are too many steps. The repetitious procedures get cumbersome. The trade-off of reduced access to information in exchange for a vague sense of security doesn't seem worth it.

In the fight against Covid-19, an interdisciplinary research team at the Technical University of Munich (TUM) has developed a model for a contact tracing app that protects personal data. The concept is based on an encryption process that prevents the temporary contact numbers (TCNs) of infected individuals from ending up on the phones of their contacts.

Artificial intelligence has become a focus of certain ethical concerns, but it also has some major sustainability issues. Last June, researchers at the University of Massachusetts at Amherst released a startling report estimating that the amount of power required for training and searching a certain neural network architecture involves the emissions of roughly 626,000 pounds of carbon dioxide.

Imaging technology helps to detect cardiovascular diseases much earlier; however, precise examinations are still very time-consuming. Researchers from ETH and the University of Zurich have now presented a method that could greatly accelerate dynamic magnetic resonance imaging of blood flow. "Thanks to this innovation, quantitative magnetic resonance imaging could make tremendous progress," says Sebastian Kozerke, Professor of Biomedical Imaging at ETH and the University of Zurich.