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A multidisciplinary policy design to protect consumers from AI collusion
Legal scholars, computer scientists and economists must work together to prevent unlawful price-surging behaviors from artificial intelligence (AI) algorithms used by rivals in a competitive market, argue Emilio Calvano and colleagues in this Policy Forum. (2020-11-26)

Fostering creativity in researchers: how automation can revolutionize materials research
Scientists at Tokyo Institute of Technology (Tokyo Tech) devise a system that combines robotics and artificial intelligence to fully automate the routine aspects of synthesizing, testing, and optimizing new materials according to fabrication conditions. Their approach can produce and test compounds ten times faster than scientists doing manual work, allowing for the rapid creation of huge shared databases. In turn, the autonomous system and database will be used to discover exotic material properties and new laws of physics. (2020-11-18)

Upgraded radar can enable self-driving cars to see clearly no matter the weather
A new kind of radar could make it possible for self-driving cars to navigate safely in bad weather. Electrical engineers at the University of California San Diego developed a clever way to improve the imaging capability of existing radar sensors so that they accurately predict the shape and size of objects in the scene. The system worked well when tested at night and in foggy conditions. (2020-11-17)

Drawing the line to answer art's big questions
Algorithms have shown that the compositional structure of Western landscape paintings changed 'suspiciously' smoothly between 1500 and 2000 AD, potentially indicating a selection bias by art curators or in art historical literature, physicists from the Korea Advanced Institute of Science and Technology (KAIST) and colleagues report in the Proceedings of the National Academy of Sciences (PNAS). (2020-11-13)

Light shed on the atomic resolution structure of phage DNA tube
Given that phages are able to destroy bacteria, they are of particular interest to science. Basic researchers from the Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP) in Berlin are especially interested in the tube used by phages to implant their DNA into bacteria. In collaboration with colleagues from Forschungszentrum Jülich and Jena University Hospital, they have now revealed the 3D structure of this crucial phage component in atomic resolution. (2020-11-13)

CCNY & partners in quantum algorithm breakthrough
Researchers led by City College of New York physicist Pouyan Ghaemi report the development of a quantum algorithm with the potential to study a class of many-electron quantums system using quantum computers. Their paper, entitled ''Creating and Manipulating a Laughlin-Type ν=1/3 Fractional Quantum Hall State on a Quantum Computer with Linear Depth Circuits,'' appears in the December issue of PRX Quantum, a journal of the American Physical Society. (2020-11-13)

Physics can assist with key challenges in artificial intelligence
Two challenges in the field of artificial intelligence have been solved by adopting a physical concept introduced a century ago to describe the formation of a magnet during a process of iron bulk cooling. Using a careful optimization procedure and exhaustive simulations, researchers have demonstrated the usefulness of the physical concept of power-law scaling to deep learning. This central concept in physics has also been found to be applicable in AI, and especially deep learning. (2020-11-12)

Novel deep learning method enables clinic-ready automated screening for diabetes-related eye disease
Researchers at Helmholtz Zentrum München together with LMU University Eye Hospital Munich and the Technical University of Munich (TUM) created a novel deep learning method that makes automated screenings for eye diseases such as diabetic retinopathy more efficient. (2020-11-12)

Machine learning algorithm could provide Soldiers feedback
A new machine learning algorithm, developed with Army funding, can isolate patterns in brain signals that relate to a specific behavior and then decode it, potentially providing Soldiers with behavioral-based feedback. (2020-11-12)

New primary care tool to prescribe referrals for community health and social services
CommunityRx-H3 is a practice-level, customizable community resource referral system that uses evidence-based algorithms to auto-generate a list of community resources to address such needs. This study evaluated the implementation of CommunityRx-H3 through the perspective of primary care practice facilitators. (2020-11-10)

New tool detects unsafe security practices in Android apps
Computer scientists at Columbia Engineering have shown for the first time that it is possible to analyze how thousands of Android apps use cryptography without needing to have the apps' actual codes. The team's new tool, CRYLOGGER, can tell when an Android app uses cryptography incorrectly--it detects the so-called 'cryptographic misuses' in Android apps. When given a list of rules that should be followed for secure cryptography, CRYLOGGER detects violations of these rules. (2020-11-09)

Researchers isolate and decode brain signal patterns for specific behaviors
A standing challenge has been isolating patterns in brain signals that relate to a specific behavior, such as finger movements. Researchers have developed a machine learning algorithm that resolved this challenge by uncovering neural patterns missed by other methods. This could both enable new neuroscience discoveries and enhance future brain-machine interfaces. (2020-11-09)

Artificial Intelligence has learned to estimate oil viscosity
A group of Skoltech scientists developed machine learning (ML) algorithms that can teach artificial intelligence (AI) to determine oil viscosity based on nuclear magnetic resonance (NMR) data. The new method can come in handy for the petroleum industry and other sectors, which have to rely on indirect measurements to characterize a substance. (2020-11-05)

Students develop tool to predict the carbon footprint of algorithms
Within the scientific community, it is estimated that artificial intelligence -- otherwise meant to serve as a means to effectively combat climate change -- will become one of the most egregious CO2 culprits should current trends continue. To raise awareness about the challenge, two University of Copenhagen students have launched a tool to calculate the carbon footprint of developing deep learning models. (2020-11-03)

A.I. tool provides more accurate flu forecasts
Yue Ning and her team at Stevens Institute of Technology trained their A.I. tool using real-world state and regional data from the U.S. and Japan, then tested its forecasts against historical flu data. By incorporating location data, the A.I. system is able to outperform other state-of-the-art forecasting methods, delivering up to an 11% increase in accuracy and predicting influenza outbreaks up to 15 weeks in advance. (2020-11-02)

Machine learning that predicts anti-cancer drug efficacy
Research on anti-cancer drug response in patient-derived artificial organoids and transcriptome learning of genes associated with anti-cancer target proteins. (2020-11-01)

Knee OA guidance for clinicians simplified and streamlined
Researchers review the similarities and differences between OARSI and ESCEO 2019 guidelines for the management of knee OA and provide a narrative to help steer health-care providers through the complexities of non-surgical management of the disease. (2020-10-29)

Researchers take a stand on algorithm design for job centers: Landing a job isn't always the right goal
Algorithms that assess the risk of citizens becoming unemployed are currently being tested in a number of Danish municipalities. But according to a new study from the University of Copenhagen, gaining employment is not the only relevant goal for those out of work -- nor should it be for an algorithm. (2020-10-29)

Machine learning helps pinpoint sources of the most common cardiac arrhythmia
Researchers have designed a new ML-based approach for detecting atrial fibrillation drivers, small patches of the heart muscle that are hypothesized to cause this most common type of cardiac arrhythmia. The team tested their approach on 11 explanted human hearts, all donated posthumously for research purposes. Turned out, that their ML model can indeed efficiently interpret data with an accuracy of up to 81%. (2020-10-29)

Super-resolution microscopy and machine learning shed new light on fossil pollen grains
Plant biology researchers at the University of Illinois and computer scientists at the University of California Irvine have developed a new method of fossil pollen identification through the combination of super-resolution microscopy and machine learning. The team developed and trained three convolutional neural network models to identify fossil pollen specimens from an unknown group of legumes. (2020-10-23)

AI detects hidden earthquakes
Tiny movements in Earth's outermost layer may provide a Rosetta Stone for deciphering the physics and warning signs of big quakes. New algorithms that work a little like human vision are now detecting these long-hidden microquakes in the growing mountain of seismic data. (2020-10-22)

Machine learning uncovers potential new TB drugs
Using a machine-learning approach that incorporates uncertainty, MIT researchers identified several promising compounds that target a protein required for the survival of the bacteria that cause tuberculosis. (2020-10-15)

Bringing a power tool from math into quantum computing
The Fourier transform is a mathematical operation essential to virtually all fields of physics and engineering. Although there already exists an algorithm that computes the Fourier transform in quantum computers, it is not versatile enough for many practical applications. In a recent study, scientists from Tokyo University of Science tackle this problem by designing a novel quantum circuit that calculates the Fourier transform in a much quicker, versatile, and more efficient way. (2020-10-14)

Assessing state of the art in AI for brain disease treatment
The range of AI technologies available for dealing with brain disease is growing fast, and exciting new methods are being applied to brain problems as computer scientists gain a deeper understanding of the capabilities of advanced algorithms. In APL Bioengineering, Italian researchers conducted a systematic literature review to understand the state of the art in the use of AI for brain disease. Their qualitative review sheds light on the most interesting corners of AI development. (2020-10-14)

Researchers improve the standard method for assessing cardiovascular disease risk
Taking into account two common kidney disease tests may greatly enhance doctors' abilities to estimate patients' cardiovascular disease risks, enabling millions of patients to have better preventive cardiovascular care. (2020-10-14)

A new approach to analyzing the morphology of dendritic spines
Dendritic spines are small protrusions from a neuron's dendrite membrane, where contact with neighboring axons is formed to receive synaptic input. Changes in the characteristics of the dendritic spines are associated with learning and memory and could be a feature of neurodegenerative disorders like Alzheimer's disease and Huntington's disease. Scientists examined a novel approach to analyzing the dendritic spine shapes. (2020-10-12)

Artificial intelligence in art: a simple tool or creative genius?
Intelligent algorithms are used to create paintings, write poems, and compose music. According to a study by an international team of researchers from the Massachusetts Institute of Technology (MIT), and the Center of Humans and Machines at the Max Planck Institute for Human Development, whether people perceive artificial intelligence (AI) as the ingenious creator of art or simply another tool used by artists depends on how information about AI art is presented. The results were published in the journal iScience. (2020-09-30)

Researchers exploit weaknesses of master game bots
Researchers at Penn State designed an algorithm to train an adversarial bot, which was able to automatically discover and exploit weaknesses of master game bots driven by reinforcement learning algorithms. (2020-09-30)

Quieter wind beneath the wings
The ability to efficiently simulate the noise generated by wings and propellers promises to accelerate the development of quieter aircraft and turbines. (2020-09-27)

Spin clean-up method brings practical quantum computers closer to reality
Researchers at Osaka City University create a quantum algorithm that removes spin contaminants while making chemical calculations on quantum computers. This allows for predictions of electronic and molecular behavior with degrees of precision not achievable with classical computers and paves the way for practical quantum computers to become a reality. (2020-09-25)

New theory predicts movement of different animals using sensing to search
A Northwestern University research team has developed a new theory that can predict the movement of an animal's sensory organs -- such as eyes, ears and nose -- while searching for something vital to its life. (2020-09-22)

Algorithms uncover cancers' hidden genetic losses and gains
Limitations in DNA sequencing technology make it difficult to detect some major mutations often linked to cancer, such as the loss or duplication of parts of chromosomes. Now, methods developed by Princeton computer scientists will allow researchers to more accurately identify these mutations in cancerous tissue, yielding a clearer picture of the evolution and spread of tumors than was previously possible. (2020-09-17)

Light processing improves robotic sensing, study finds
A team of Army researchers uncovered how the human brain processes bright and contrasting light, which they say is a key to improving robotic sensing and enabling autonomous agents to team with humans. (2020-09-14)

New perception metric balances reaction time, accuracy
Researchers at Carnegie Mellon University have developed a new metric for evaluating how well self-driving cars respond to changing road conditions and traffic, making it possible for the first time to compare perception systems for both accuracy and reaction time. (2020-09-09)

Quantum algorithm proposed to solve Dyck language problems
In the paper, Khadiev and his colleagues demonstrated an algorithm that can solve the problem in 40 seconds and also proved that it cannot be solved in less than 10 second on a quantum computer. (2020-09-04)

Quantum leap for speed limit bounds
Nature's speed limits aren't posted on road signs, but Rice University physicists have discovered a new way to deduce them that is better -- infinitely better, in some cases -- than prior methods. (2020-09-03)

Latest version of climate system model shows significant improvements in simulation performance
The simulating performance of the latest climate system model FGOALS-f3-L is evaluated and significant improvements are apparent compared with the previous version. (2020-09-02)

Managing data flow boosts cyber-physical system performance
Researchers have developed a suite of algorithms to improve the performance of cyber-physical systems - from autonomous vehicles to smart power grids - by balancing each component's need for data with how fast that data can be sent and received. (2020-09-01)

New theory hints at more efficient way to develop quantum algorithms
A new theory could bring a way to make quantum algorithm development less of an accidental process, say Purdue University scientists. (2020-08-31)

AI accurately identifies infants with low risk of serious bacterial infection
Artificial intelligence, or 'supervised machine learning,' could help identify which well-appearing infants with fever, who are 60 days old or younger, are at low risk for a serious bacterial infection, according to a study published in Pediatrics. Accurate risk determination could reduce unnecessary lumbar puncture, antibiotics and hospitalizations for these infants, as well as decreasing parental anxiety. (2020-08-27)

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