Articles tagged with Computational Science
Researchers tested three common techniques to make algorithms fairer and found that one approach didn't reduce social norm bias at all. They proposed a new technique: a formula to directly measure social norm bias in an algorithm so it can be corrected. This bias can persist even after overt discrimination is removed.
The Human Brain Project Summit 2023 will highlight the scientific achievements of the project at the interface of neuroscience and technology. Researchers will present cutting-edge research on European advances in neuroscience and applications in medicine and brain-derived technologies.
Researchers have developed a sophisticated AI algorithm, SPHINKS, that can refine omics datasets and pinpoint protein kinases responsible for tumor growth in glioblastoma. The algorithm has the potential to provide personalized treatments for patients with aggressive brain cancer.
Researchers developed BirdFlow, a predictive model that utilizes eBird data and machine learning to forecast migratory patterns. The model was tested on 11 species of North American birds and found to outperform other models in tracking migration flows.
Dr. Nico Spiller to develop new analysis methods using machine learning to analyze complex brain data related to memory, decision making, and movement. The fellowship aims to provide insights into neurodegenerative diseases such as Alzheimer's and Parkinson's disease.
A new Swedish quantum computer is being made available to the industry, accompanied by a test bed and a quantum helpdesk. The test bed will allow companies and researchers to solve problems using quantum technology at a significantly lower cost than existing commercial options.
Researchers at Brookhaven National Laboratory have successfully discovered new materials using artificial intelligence and self-assembly. The AI-driven technique led to the discovery of three new nanostructures, expanding the scope of self-assembly's applications in microelectronics and catalysis.
Researchers from Brown and MIT developed a new framework that uses machine learning and sequential sampling to predict rare disasters like earthquakes and pandemics with less data. The framework, called DeepOnet, has been shown to outperform traditional modeling efforts in predicting scenarios, probabilities and timelines of rare events.
A study by NTU Singapore found that mental health chatbots engage users in empathetic conversations and offer support and guidance through psychotherapeutic exercises. The chatbots displayed a 'coach-like' personality, but were not able to deliver personalised advice.
Researchers developed a new computer model, quantitative fate mapping, to trace the origin of cells in fully grown organisms. The model helps spot which cells acquire alterations during development that change an organism's fate from healthy to disease states.
USTC scientists made a significant breakthrough in ab initio computing simulation of complex metallic heterostructures with 2.5 million atoms. This achievement is expected to be applied in the construction of 2D-materials-based transistors.
Researchers at Aalto University have developed a new optical computing approach that uses circularly polarized light to operate logic gates, resulting in ultrafast processing speeds. The technology operates about one million times faster than existing technologies and can be integrated into a single device.
Researchers at Johns Hopkins Medicine discovered that regulating the electrical charge on the inner side of the cell membrane can activate pathways responsible for cell movement. This finding has potential implications for understanding cancer cell migration and immune cell function.
A KAUST research team studied the interaction between nitrogen gas and hydrocarbons in oil reservoirs. They found a direct correlation between nitrogen solubility and oil swelling, enhancing oil recovery. The study also sheds light on CO2 storage with impurities like methane and nitrogen.
A team of researchers from the University of Pennsylvania has developed a new algorithm, metadynamics, that can navigate high-dimensional energy landscapes to find low-energy configurations. This breakthrough has the potential to revolutionize fields such as protein folding and machine learning.
A team of researchers proposes an intelligent routing scheme to optimize link load balancing in software-defined networks, achieving significant performance improvements. Their algorithms outperform traditional methods, reducing maximum bandwidth by 24.6 percent in real-world topologies.
Researchers at MIT have developed a new architecture for optical neural networks, which can perform complex linear algebra operations using light signals. The new design eliminates uncorrectable errors that limited the scalability of earlier systems, enabling larger networks with improved accuracy.
A team of quantum engineers at UNSW Sydney has developed a method to reset a quantum computer using a fast digital voltmeter to watch the temperature of an electron, reducing preparation errors from 20% to 1%. This innovation represents a modern twist on Maxwell's demon, a thought experiment that dates back to 1867.
Researchers at the University of Texas at Dallas have developed a computer-based platform for drug discovery using topological data analysis. The approach allows for virtual screening of thousands of compound candidates, narrowing them down to the most promising ones for laboratory and clinical testing.
Researchers have identified over 300 genome regions that contribute to an individual's chemical fingerprint, influencing susceptibility to diseases and response to drugs. The study's findings can help tailor treatment decisions and improve disease outcomes.
Researchers at the University of Oldenburg have developed a new statistical model that accurately describes wind turbulence and generates fully three-dimensional wind fields using limited measurement points. This breakthrough enables precise wind turbine load estimation and improves wind farm planning, with applications in various fiel...
Research has found that extreme ocean waves can arise from modulation instability in multi-directional wave systems, challenging previous assumptions. The study demonstrates that crossing sea waves can trigger the formation of extreme waves, posing a growing risk to marine infrastructure and coastal communities due to climate change.
A novel multi-modal image retrieval system, DenseBert4Ret, has been developed by researchers from Gwangju Institute of Science and Technology (GIST) using deep learning algorithms. The system outperforms state-of-the-art models in retrieving images based on both image and text features.
In an experiment pitting human expertise against artificial intelligence, researchers found that the computer program correctly predicted six out of nine proteins capable of self-assembly. This breakthrough suggests machine learning can complement human intuition in biotechnology research.
A study by researchers at the University of Notre Dame found that 57 percent of participants were habitual snoozers, with females being 50 percent more likely to snooze than males. Snoozing may be a way for some people to battle exhaustion, as only 1 in 3 Americans get enough sleep.
A new $1.328M grant will help assess and improve the reporting quality in randomized clinical trial protocols and result publications using NLP methods. The goal is to promote high reporting standards, synthesizing evidence, and open science practices throughout the scientific ecosystem.
Researchers created living brain cells in a dish that can perform goal-directed tasks and adapt to changes, opening doors for new understanding of brain function. The study also raises possibilities for alternative animal testing and biomimetic research.
A breakthrough computer model from Chalmers University of Technology reveals the properties of an atomic nucleus, providing insights into the strong force that governs neutron star behavior. The model predicts a surprisingly thin neutron skin, which could lead to increased understanding of heavy element creation in neutron stars.
The NTU-developed wind harvester generates a voltage of three volts at wind speeds as low as two meters per second, powering commercial sensor devices. The device can also store excess charge for extended periods in the absence of wind, serving as an alternative to smaller lithium-ion batteries.
Researchers aim to create a unified database network for battery data, facilitating AI analysis and predictions. The Battery Data Genome will collect data across the entire battery lifecycle, from discovery to deployment, with uniform standards for metadata.
A team of researchers at UNSW Sydney has broken new ground by proving that 'spin qubits' can hold information for up to two milliseconds, a significant improvement over previous benchmarks. By extending the coherence time, they enable more efficient quantum operations and better maintain information during calculations.
Researchers found that developing sea anemones use hydraulic muscles to regulate body pressure and sculpt tissue. The more active larvae are, the longer they take to develop, suggesting a trade-off between movement and growth.
An international team of researchers has used data science to reveal the universal rules shaping cells' power stations. The study found that genes encoding subunits of larger cellular machines are most likely to be retained in organelle DNA.
Researchers found that inland water carbon emissions are on the rise, with estimates suggesting 4.4 billion metric tons of carbon are released annually, primarily as carbon dioxide or methane. A new thermal insulation composite made from silica particles also shows promise for improving energy efficiency and reducing moisture damage.
Xiu Yang, a 2022 NSF CAREER award recipient, is working on an algorithmic approach to model and overcome hardware errors in quantum computing. He aims to enable the technology to achieve its promise of unparalleled speed in solving complex problems.
Rice University's ROBE Array algorithm slashes the size of DLRM memory structures, allowing training on 100 megabytes of memory and a single GPU. The method matches state-of-the-art DLRM training methods with improved inference efficiency.
Researchers at the University of Oldenburg and Fraunhofer IWES collaborate on a new project to develop more accurate wind flow simulations using artificial intelligence. The goal is to reduce computing times and enhance precision, ultimately accelerating innovation in wind turbine design.
Researchers have found that the arrangement of spinning electrons, not a weak external magnetic field, causes the Hall effect in Weyl antiferromagnets. This discovery has implications for next-generation memory storage devices using ferromagnets and antiferromagnets.
Researchers have created and observed novel vortices in an ultracold gas, exhibiting unexpected properties due to hidden discrete symmetries. The discovery may lead to breakthroughs in quantum computing and information processing.
A new study uses high-resolution regional model experiments to explore how lake surface temperatures may affect the climate of the Great Lakes region. Small differences in lake surface temperatures can have a significant impact on summer climate and fuel extreme weather events.
A UBC research team created a computer modelling program to predict coral reef impact and restoration plans. They found that more diverse communities are most resilient, with species having unique traits contributing to habitat quality.
Researchers have developed an algorithm to identify the protozoan Trypanosoma cruzi in photographs of blood samples taken with a mobile phone camera. The low-cost method can be reproduced and adapted for other purposes that depend on images, such as analyzing feces, skin, or colposcopies.
A research team from the Complexity Science Hub Vienna has developed a stress test to identify weaknesses and strengths in healthcare systems. They used data from Austria to show how many resident physicians can drop out before patients don't find a new doctor within reasonable distance, highlighting regional differences in resilience.
Researchers at IISc used widely-used computational techniques to predict and verify migration barrier values in lithium-ion batteries. They propose robust guidelines to choose accurate frameworks for testing materials. The study found SCAN functional had better accuracy overall, while GGA was faster but less accurate.
Scientists at Simon Fraser University have made a breakthrough in developing quantum technology by observing over 150,000 silicon 'T centre' photon-spin qubits. This discovery enables the creation of massively scalable quantum computers and quantum internet that can connect them.
A novel algorithm, BLIND, enables robots to navigate through environments with obstacles by incorporating human feedback. Humans provide labels to refine the robot's trajectory, avoiding obstacles efficiently.
Researchers developed a smartphone app that harnesses weather forecasting data to provide individuals with a granular understanding of their COVID-19 risk. The app would blend various types of data, including surveillance testing and wearable sensor data, to forecast the spread of disease across a network of human contacts.
An interdisciplinary team has created a large public database of standardized wordlists for over 2000 language varieties, providing insights into the structure of human languages. The data reveals patterns of independent parallel evolution in linguistic diversity, with many languages using similar words for related concepts.
The five-year grant will support research on foundational theory and real-world applications, including simulation of optical fibers, weather forecasting, and disease understanding. Postdoctoral researchers and graduate students will work with faculty mentors to develop data acumen and prepare for Ph.D. research.
Researchers at Tokyo Institute of Technology developed a computational DNA droplet that can recognize specific combinations of chemically synthesized microRNAs as biomarkers of tumors. The droplet can perform logic computing operations and detect multiple cancer biomarkers simultaneously.
A new AI method can distinguish between the overall sounds of healthy and unhealthy coral reefs, making it a valuable tool for monitoring reef health. The technique uses machine learning to analyze sound recordings and track the progress of reef restoration projects.
Researchers at the University of Innsbruck have successfully implemented a universal set of gates on encoded logical quantum bits, enabling fault-tolerant quantum computing. The demonstration showcases two essential gates: CNOT and T-gates, which are crucial for programming all algorithms.
A new project led by University of Illinois professor Jingrui He seeks to detect and predict insider threats in large organizations. The team will use multimodal data to identify outliers and rare category types of insider threats and propose dynamic update techniques.
A new computer-aided diagnostic tool, Deep-Lung Parenchyma-Enhancing (DLPE), uses artificial intelligence to reveal signs of pulmonary fibrosis in COVID long-haulers, helping to explain respiratory symptoms and improve disease management.
A new machine-learning framework has been developed to improve the design of catalysts, which speed up chemical reactions. The approach analyzes the conversion of carbon monoxide to methanol using a copper-based catalyst and identifies key steps that need to be tweaked to increase productivity.
Researchers developed a technique to study supermassive black holes smaller than M87's by measuring the brightness of their shadows over time. The 'shadow' signal can reveal the size and shape of a black hole's event horizon, shedding light on gravity's nature.
A new study uses artificial intelligence to predict bone fractures in cancer patients by creating a digital twin of the vertebra. The AI-assisted framework, ReconGAN, simulates how tumors affect the spine and predicts fracture risks, offering medical experts better treatment strategies and patient decisions.
The Texas Advanced Computing Center (TACC) has selected 21 scientific codes and 'grand challenge'-class science problems that will receive funding through the Characteristic Science Applications program. The program aims to improve scientific software, generate benchmarks for the Leadership-Class Computing Facility, and demonstrate the...
Scientists at the University of Oxford have developed an 'optomemristor' device that facilitates three-factor learning and emulation of biological computations, making it possible to perform complex machine learning tasks. The device uses both light and electrical signals to interact and consume very little energy.
The Taylor Geospatial Institute brings together eight leading research institutions to collaborate on geospatial technology research and development. The Institute aims to accelerate St. Louis' position as the global center of geospatial innovation, with a focus on key areas such as food security, geospatial health, and national security.