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IMAGE: A major roadblock to computational design of high-entropy alloys has been removed, according to scientists at Iowa State University and Lehigh University. Engineers from the Ames Lab and Lehigh University s. view more
Credit: Ames Laboratory, U.S. Department of Energy
A major roadblock to computational design of high-entropy alloys has been removed, according to scientists at Iowa State University and Lehigh University. Engineers from the Ames Lab and Lehigh University s Department of Mechanical Engineering and Mechanics have developed a process that reduces search time used for predictive design 13,000-fold.
According to Ganesh Balasubramanian, an associate professor at Lehigh, the goal of the team s research was to accelerate the computational modeling of complex alloys. The tools available for creating random distribution of atoms in materials simulation models, he says, have been used for many, many years now and are limited in their reach for fast
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Credit: Delaneau Group
Thousands of genetic markers have already been robustly associated with complex human traits, such as Alzheimer s disease, cancer, obesity, or height. To discover these associations, researchers need to compare the genomes of many individuals at millions of genetic locations or markers, and therefore require cost-effective genotyping technologies. A new statistical method, developed by Olivier Delaneau s group at the SIB Swiss Institute of Bioinformatics and the University of Lausanne (UNIL), offers game-changing possibilities. For less than $1 in computational cost, GLIMPSE is able to statistically infer a complete human genome from a very small amount of data. The method offers a first realistic alternative to current approaches relying on a predefined set of genetic markers, and so allows a wider inclusion of underrepresented populations. The study, which suggests a paradigm shift for data generation in biomedical research, is published in
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Irvine, Calif., Jan. 5, 2021 Scientists at the University of California, Irvine have developed a new deep-learning framework that predicts gene regulation at the single-cell level.
Deep learning, a family of machine-learning methods based on artificial neural networks, has revolutionized applications such as image interpretation, natural language processing and autonomous driving. In a study published recently in
Science Advances, UCI researchers describe how the technique can also be successfully used to observe gene regulation at the cellular level. Until now, that process had been limited to tissue-level analysis.
According to co-senior author Xiaohui Xie, UCI professor of computer science, the framework enables the study of transcription factor binding at the cellular level, which was previously impossible due to the intrinsic noise and sparsity of single-cell data. A transcription factor is a protein that controls the translation of genetic information from DNA t
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IMAGE: When one rotor fails, the drone begins to spin on itself like a ballerina. (Image: UZH) view more
Credit: UZH
As anxious passengers are often reassured, commercial aircrafts can easily continue to fly even if one of the engines stops working. But for drones with four propellers - also known as quadcopters - the failure of one motor is a bigger problem. With only three rotors working, the drone loses stability and inevitably crashes unless an emergency control strategy sets in.
Researchers at the University of Zurich and the Delft University of Technology have now found a solution to this problem: They show that information from onboard cameras can be used to stabilize the drone and keep it flying autonomously after one rotor suddenly gives out.
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IMAGE: The red nodes denote the influencers chosen by their model. The model tends to choose influencers with relatively larger number of connections and also those belonging to different sub-components of. view more
Credit: SUTD
If you were an owner of a newly set-up company, you would most likely be focused on building brand awareness to reach out to as many people as possible. But how can you do so with budget constraints?
These days, businesses have turned to a select group of people who are active on social media platforms as a cost efficient way to drive their promotional efforts. Also referred to as influencers , they have the ability to influence the opinions or buying decisions of others.