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Experts reduce search times for novel high-entropy alloys 13,000-fold using Cuckoo Search

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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.
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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 the ....

Rahul Singh , Prashant Singh , Ganesh Balasubramanian , Aayush Sharma , Duaned Johnson , Lehigh University , Ames Laboratory , Lehigh University Department Of Mechanical Engineering , Iowa State University , National Science Foundation , Games Lab , Mechanical Engineering , Cuckoo Search , Nature Computational Science , Energy Office , Science National Laboratory , Iowa State , Chemistry Physics Materials Sciences , Algorithms Models , Technology Engineering Computer Science , Computer Science , Research Development , Robotry Artificial Intelligence , ராகுல் சிங் , பிரஷண்ட் சிங் , கணேஷ் பாலசுப்ரமணியன் ,

Inferring human genomes at a fraction of the cost promises to boost biomedical research

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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 i ....

United States , Simone Rubinacci , Olivier Delaneau , Diogo Ribeiro , Postdoctoral Researcher In Olivier Delaneau Group , Swiss Institute Of Bioinformatics , Group Leader , University Of Lausanne , Postdoctoral Researcher , Molecular Biology , Mathematics Statistics , Algorithms Models , Calculations Problem Solving , Medicine Health , Computer Science , Software Engineering , ஒன்றுபட்டது மாநிலங்களில் , டியோகோ ரிபேீரோ , சுவிஸ் நிறுவனம் ஆஃப் உயிர் தகவலியல் , குழு தலைவர் , போஸ்ட்‌டாக்டொரல் ஆராய்ச்சியாளர் , மூலக்கூறு உயிரியல் , கணிதம் புள்ளிவிவரங்கள் , கணக்கீடுகள் ப்ராப்லம் தீர்க்கும் , மருந்து ஆரோக்கியம் , கணினி அறிவியல் ,

UCI researchers use deep learning to identify gene regulation at single-cell level

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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 informa ....

United States , Orange County , Howard Gillman , Laiyi Fu , Emmanuel Dollinger , Xiaohui Xie , Lihua Zhang , University Of California , Information Engineering At China Xian Jiaotong University , Multiscale Cell Fate Research , National Science Foundation , Department Of Computer Science , Simons Center , School Of Electronic , Association Of American Universities , Science Advances , Qing Nie , National Science Foundation Simons Center , Computer Science , Information Engineering , Xian Jiaotong University , Chancellor Howard Gillman , Mathematics Statistics , Algorithms Models , ஒன்றுபட்டது மாநிலங்களில் , ஆரஞ்சு கவுண்டி ,

How to keep drones flying when a motor fails

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IMAGE: When one rotor fails, the drone begins to spin on itself like a ballerina. (Image: UZH)
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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. ....

Sihao Sun , Davide Scaramuzza , Giovanni Cioffi , Delft University Of Technology , Perception Group , University Of Zurich , Delft University , Rescue Robotics , Coen De Visser , Autonomous Quadrotor Flight , Rotor Failure , Onboard Vision Sensors , Algorithms Models , Transportation Travel , Technology Engineering Computer Science , Computer Science , Multimedia Networking Interface Design , Electrical Engineering Electronics , Industrial Engineering Chemistry , Mechanical Engineering , Robotry Artificial Intelligence , ஜியோவானி சிொப்பி , டெல்ஃப்ட் பல்கலைக்கழகம் ஆஃப் தொழில்நுட்பம் , கருத்து குழு , பல்கலைக்கழகம் ஆஃப் ஸுரி , டெல்ஃப்ட் பல்கலைக்கழகம் ,

SUTD develops new model of influence maximization

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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.
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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. ....

Karthik Natarajan , Singapore University Of Technology , Singapore University , Professor Karthik Natarajan , Correlation Robust Influence Maximization , Mathematics Statistics , Algorithms Models , Systems Chaos Pattern Formation Complexity , Mass Media , Technology Engineering Computer Science , Computer Science , Multimedia Networking Interface Design , Theory Design , Research Development , கார்த்திக் நடராஜன் , சிங்கப்பூர் பல்கலைக்கழகம் ஆஃப் தொழில்நுட்பம் , சிங்கப்பூர் பல்கலைக்கழகம் , ப்ரொஃபெஸர் கார்த்திக் நடராஜன் , கணிதம் புள்ளிவிவரங்கள் , அமைப்புகள் குழப்பம் முறை உருவாக்கம் சிக்கலானது , நிறை மீடியா , தொழில்நுட்பம் பொறியியல் கணினி அறிவியல் , கணினி அறிவியல் , மல்டிமீடியா நெட்வொர்க்கிங் இடைமுகம் வடிவமைப்பு , கோட்பாடு வடிவமைப்பு , ஆராய்ச்சி வளர்ச்சி ,