Researchers have developed an AI-powered platform that allows scientists to grow virtual tumors and optimize nanoparticle designs using artificial intelligence. The new EVONANO platform has the potential to improve targeted cancer treatments, enabling personalized therapies for individual patients.
Researchers have developed a next-generation reservoir computing that solves complex problems in less than a second, compared to current supercomputers. The new system uses significantly fewer computing resources and less data input, making it 1 million times faster for accurate forecasts.
BioDynaMo, an open-source simulation platform, enables fast and accurate modeling of complex biological systems. The tool simulates medical cases in neuroscience, oncology, and epidemiology, showcasing its potential for computational biology research.
Researchers designed novel molecules that bound tightly to SARS-CoV-2's molecular scissors, inhibiting the virus's replication. The breakthrough could lead to new treatments for COVID-19.
A team of scientists from Incheon National University developed a programmable DNA-based microfluidic chip that can perform complex mathematical calculations, such as Boolean logic operations. The chip uses a motor-operated valve system to execute a series of reactions in rapid and convenient manner.
Researchers at MIT and Institut Pasteur have created an efficient method for assembling entire genomes, including the human genome, in minutes using personal computers. This approach uses minimizer-space de Bruijn graphs to store only a small fraction of nucleotides while preserving overall genome structure, enabling faster processing ...
Researchers developed a computer model revealing how single brain cells in nematode worms sense and process environmental information to drive decision-making. The study found that sensory cells use salt cues as 'navigation beacons' to direct foraging behavior, controlling the animal's search strategy.
The RIT workshop series on sustainable computing aims to create computers with environmental consciousness from raw materials to recycling. Keynote speakers will discuss trends in computing and its environmental footprint.
Lehigh University researchers are developing a model to understand the impact of grain growth on material properties. The project aims to create new materials informatics methods, innovative stochastic differential equations, and models of grain growth to improve material performance and reliability.
A new molecule discovered by researchers at University of Limerick in Ireland enables fast decision-making in computers, breaking the von Neumann bottleneck. The device can solve problems even if individual components fail, providing smaller, faster, and more energy-efficient computing.
Physicists have developed a new method to identify and address imperfections in materials for quantum computing. The technique, terahertz scanning near-field optical microscopy, has been used to optimize fabrication protocols and reduce decoherence.
Researchers at Technical University of Munich have developed a new machine learning algorithm that can analyze complex markets and their equilibrium strategies. This breakthrough has potential applications in auction theory, wireless spectrum auctions, and more.
Researchers at George Washington University have created a nanophotonic analog processor capable of solving partial differential equations. The processor can process arbitrary inputs at the speed of light and is integrated at chip-scale.
Researchers from South Ural State University have conducted a CFD study to analyze droplet flows and determine effective barrier placement in enclosed areas. The approach allows for simulation of real classroom situations, enabling the establishment of strategies to minimize COVID-19 transmission.
Scientists created a reliable true random number generator using atomically thin two-dimensional films, overcoming long-term stability issues and power consumption concerns. The innovation uses memristors to produce fluctuating electronic signals with an exceptionally high degree of randomness.
A new study found that global marine ecosystem models differ widely in their representation of key processes, leading to underestimation of climate change impacts. Marine ecosystem models generally agree on biomass decline but disagree on magnitude and location across the world's oceans through the 21st century.
Scientists at Carnegie Mellon and University of Washington are developing new software platforms to analyze the Legacy Survey of Space and Time (LSST) dataset. The open-source platforms will enable researchers to make sense of big data and address fundamental questions about the universe, such as dark matter and dark energy.
Scientists at Nara Institute of Science and Technology create a projected touchscreen system using just one camera and projector, eliminating the need for additional detectors. The system uses slope disparity gating to capture touch data with high efficiency, enabling portable projection systems for large interactive displays.
Researchers at University of Illinois and Argonne National Laboratory will explore magnetic materials to reduce noise in quantum computing hardware. The team aims to design non-reciprocal circuitry by harnessing magnetic features, which could lead to a hybrid device for sensing and communication applications.
Quantum engineers at the University of New South Wales have discovered a new technique to control millions of spin qubits, a critical step towards building a practical quantum computer. This breakthrough uses a novel component called a dielectric resonator to focus microwave power and deliver uniform magnetic fields across the chip.
Researchers developed three criteria to assess loss of prediction efficiency when modeling large spatial datasets. The tool, called TLR estimation method, provides insight into 'fit' of approximation parameters and prediction variability.
A team of Beckman researchers developed software to boost infrared imaging-based cancer diagnosis, enhancing image resolution and accelerating recording speeds. The software integrates data analysis and reduces limitations associated with IR imaging, making it faster and more accurate.
Researchers developed a novel evidence-based material recommender system that predicts high entropy alloy formation without data descriptors, overcomes data bias and poor availability. The method recommends an FeMnCoNi alloy as the most probable HEA and successfully synthesizes it, confirming its validity.
Researchers have found that improved learning processes are associated with reduced symptoms of depression. By using brain imaging and mathematical modeling, the team identified distinct paths to depression symptoms and proposed a new approach for treating clinical depression.
Researchers developed a new framework using deep learning techniques to create 3D visualizations from X-ray data. This method is hundreds of times faster than traditional methods, enabling scientists to analyze large amounts of 3D data more efficiently.
A KAUST-led research team has developed an approach to mix high-precision calculations with lower precision for large geospatial datasets, significantly speeding up modeling without overall precision loss. The technique, implemented on high-performance computing systems, will enable larger datasets to be analyzed in shorter timeframes.
A Lehigh University team is working on a culturally tailored program to reduce American Indian smokeless tobacco use, supported by a $1.8 million grant from the American Cancer Society. The All Nations Snuff Out Smokeless (ANSOS) program aims to empower individuals to take control of their health.
Researchers used AI to optimize atomic layer deposition (ALD) processes autonomously, identifying optimal growth conditions for new materials. The study suggests a faster way of converging to optimum combinations without human input, potentially saving manufacturers time and money.
Scientists have created elements comparable to brain neurons and synapses using spins, a magnetic property of electrons. This breakthrough could lead to the development of brain-like computer hardware that can interface with standard silicon-based circuits.
Researchers from the University of Granada and the University of Cádiz have developed a computer system that can help film scriptwriters create successful storylines by analyzing common tropes in films. The system uses artificial intelligence to predict which narrative devices or plot twists are likely to work well with audiences.
Researchers investigate photonics as a solution to develop fast and energy-efficient computing systems inspired by the human brain. By mimicking biological processing systems, they aim to reduce energy losses and improve processor speeds.
Computational materials scientists at Ames Laboratory have created an algorithm that uses a hybrid approach inspired by cuckoo birds' nesting habits to find novel high-entropy alloys. The new method significantly reduces the search time for these materials, which are highly sought after for their unique properties and applications.
Researchers at Lehigh University and Iowa State University have developed a hybrid Cuckoo Search algorithm that accelerates computational modeling of complex alloys by reducing search time up to 13,000-fold. This breakthrough enables the creation of physically realizable systems that can be directly compared against experimental samples.
A study found that visual processing units are identical in size across primate species, from the world's smallest mouse lemur to humans. This preservation suggests an early evolution of primate vision and highlights the importance of conservation efforts for endangered species.
Mathematicians from RUDN University developed new symbolic integration functionality for the Sage system, building on 19th-century ideas by Karl Weierstrass. The team confirmed that Weierstrass's theory can determine whether an integral can be calculated in elementary functions.
The Argonne team developed a high-performance, iterative reconstruction system for noninvasive imaging at synchrotron facilities. Their novel optimizations enabled reconstruction of large 3D volumes in under 3 minutes using 24,576 GPUs.
Stony Brook University has installed a new supercomputer, Ookami, powered by the HPE Apollo 80 system and Fujitsu A64FX processor, offering a balance of high performance and power efficiency. The system is supported by Bright Cluster Manager software and will be available for researchers nationwide to test new computing technologies.
Researchers at Skoltech predicted high-entropy alloys with improved mechanical properties, such as hardness and fracture resistance, in the W-Mo-B system. The study aims to develop new hard materials that can withstand higher temperatures or pressures.
Eduardo Lopez Atencio and his collaborators are analyzing agent search methods in a constrained network environment to help the US Army workforce stay focused on strategic goals. This analysis will be applied to forecast workforce behaviors across an extended planning horizon.
Scientists from Nanyang Technological University (NTU Singapore) have developed an AI system that recognizes human hand gestures with high precision. The system combines skin-like electronics with computer vision and achieves accuracy even in poor environmental conditions.
Researchers found a Hopfion structure, a repeating pattern present throughout nature, in ferroelectric nanoparticles. This discovery highlights the interconnectedness of scientific fields and could lead to breakthroughs in energy storage devices and information systems.
Researchers developed Q-scores to assess true resolution at every point in cryo-EM maps, enabling accurate interpretation of atomic models. The approach validated on large molecules, achieving high-resolution maps close to 1.75 angstroms, and demonstrates improved confidence in molecular interpretations.
Gordon examines secure computation to leverage user data without compromising privacy. He investigates three key tasks: handling large volumes of data with few parties, interacting with a large number of parties, and storing dynamic data in a distributed plane.
The Tapis Project aims to simplify access to powerful supercomputers and manage data from diverse sources. The platform offers event-driven computing, streamlining workflows and enabling hands-free analysis.
Scientists developed computational models of word meanings and tested them against real-time brain activity in volunteers, revealing how the brain combines words to make sense in context. The study shows how word constraints directly affect meaning interpretation, highlighting the neural mechanisms behind spoken language understanding.
Researchers from Skoltech found that professional players move around more often and intensely than amateurs, while sitting still during game events. Machine learning methods correctly predicted a player's skill level in 77% of cases.
Computing scientists at the University of Alberta developed a methodology combining machine-learning algorithms to recognize depression using acoustic cues. The technology could lead to apps tracking mood indicators and providing support for individuals.
Tanu Malik's project aims to establish reproducibility of real-world computational and data science. Her system, Sciunit container, makes it easier to reproduce and compare scientific experiments by aligning data, programs, and environments.
Researchers at the University of Maryland introduced a new way of combining perception and motor commands using hyperdimensional computing theory, which can fundamentally alter AI tasks. This integration enables robots to fuse their perceptions with motor capabilities, creating a more efficient and faster way to complete tasks.
A new study finds that half of scientists will drop out of academia after five years, contrasting with the 1960s when a higher fraction spent their careers in academia. The study reveals a steadily growing temporary workforce and a 35-percentage-point rise in researchers never credited as primary authors.
The U.S. Department of Energy's Office of Science has awarded 62 projects under the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program for 2019. These projects aim to tackle some of the world's most challenging science problems using cutting-edge computational methods and resources.
Kenneth Miller received the 2018 Swartz Prize in Theoretical and Computational Neuroscience for his contributions to modeling cerebral cortex function. His research has led to a reliable model of synaptic plasticity, confirmed by experimental data.
A $3 million grant will support a two-year effort to develop a strategic plan for a Cyberinfrastructure Center of Excellence at USC ISI. The project aims to enhance existing cyberinfrastructure and provide a forum for knowledge sharing among large facilities and users.
The Biophysical Society has announced the winners of its Outstanding Poster Award, recognizing outstanding scientific achievements in biophysics. The student winners were selected for their research on HERG kinetics, while the postdoctoral winner was recognized for her work on cardiac resynchronization therapy.
Two new $1 million NSF grants will support RENCI's efforts to develop a high-performance platform for scientific data processing and detect unintentional data errors. The projects aim to improve scientific productivity, increase confidence in outcomes, and facilitate seamless integration of available resources and networks.
Researchers at Tel Aviv University and Tsinghua University have discovered microscale superlubricity, achieving ultra-low friction and wear between dissimilar materials under high loads. This breakthrough has enormous implications for computer hard discs and ball bearings, leading to potential energy savings and wear prevention.
The Society for Industrial and Applied Mathematics (SIAM) has awarded 16 distinguished mathematicians for their outstanding research and contributions to the field of applied mathematics and computational science. The recipients were honored at the SIAM Annual Meeting Prizes and Awards Luncheon in Portland, Oregon.
A computational model suggests that older memories are affected in depression, with longer episodes causing more extensive memory deficits. The study's findings imply that major depressive disorder could have far-reaching consequences, including the loss of remote memories that do not recover even after the depression subsides.
The Texas Advanced Computing Center (TACC) is developing innovative software solutions to enhance scientific productivity. Their interactive parallelization tool, IPT, enables researchers to convert serial code into parallel code using tens of thousands of processors, achieving significant speed-ups and user productivity enhancements. ...
A new study on turtle brain evolution reveals that their brains have changed slowly and constantly over 210 million years, with modern turtles showing a wide variety of brain shapes and sizes. The first turtles with fully formed shells were likely living on land, contradicting previous hypotheses about their origins.