Researchers at the University of Gothenburg have successfully combined a memory function with a calculation function in the same component, enabling more efficient technologies like mobile phones and self-driving cars. The discovery opens the way for brain-like computers that can perform tasks effectively and energy efficiently.
Researchers developed an algorithm predicting COVID-19 patient outcomes based on individual data, achieving high accuracy (over 90%) for up to ten days. This innovation enables hospitals to allocate staff and resources efficiently, potentially saving lives during future pandemic waves.
A new 'image analysis pipeline' called TDAExplore gives scientists rapid insight into how cells are changed by disease, using a combination of microscopy, topology, and artificial intelligence. This approach can provide objective information on cell changes, such as the movement of proteins like actin, even with limited training data.
The WVU-led Dolly Sods GPU cluster enables researchers to accelerate computational research in fields like drug development, interstellar phenomena, and biometrics. The cluster will facilitate the analysis of massive datasets and enable real-time processing of signals from satellites in space.
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Apple iPhone 17 Pro delivers top performance and advanced cameras for field documentation, data collection, and secure research communications.
Researchers developed EDS-HAT, an AI-powered system combining machine learning and whole genome sequencing to detect clusters of similar infections in real-time. The system identified 99 clusters of infections and prevented potential transmissions in 65.7% of cases, saving the hospital $692,500.
Researchers from Okayama University developed an AI-powered image classifier to simplify and speed up the task of image analysis in cell biology. The system achieved high detection accuracy for mitotic cells in plant species, demonstrating its potential for non-experts to use.
A team of researchers has developed a simple and efficient method of quantum encryption using single photons, which can detect any attempt to hack the message. The breakthrough brings us closer to securing our data against quantum computers' potential attacks.
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Researchers at Penn State created a nanocomputing agent that controls protein function involved in cell movement and cancer metastasis. The logic gate, embedded in the focal adhesion kinase (FAK) protein, demonstrates ability to control conditional operations, introducing possibilities for precision therapeutics.
Researchers trained an artificial intelligence algorithm to predict the next designer drugs before they are even on the market, allowing law enforcement agencies to identify and regulate new versions of dangerous psychoactive drugs. The model was tested against 196 new designer drugs and found nearly all were present in its generated set.
A team of Canadian researchers has successfully simulated baryons on a quantum computer, marking an important step towards more complex simulations. This breakthrough enables scientists to study neutron stars, the earliest moments of the universe, and the revolutionary potential of quantum computers.
Researchers developed AfriBERTa, a neural network model that achieves state-of-the-art results for low-resource African languages. The model works with 11 languages spoken by over 400 million people and requires only one gigabyte of data, compared to thousands for existing models.
A team of computer scientists has developed a secure identity verification method based on zero-knowledge proof, ensuring that information cannot be replicated by hackers. The new method uses two physically separated prover-verifier pairs to confirm identities, eliminating the possibility of collusion and increasing security.
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A new study at the University of Missouri found that telehealth reduced stress for nursing home residents while increasing access to convenient care. However, it also removed socialization opportunities and created confusion for residents with cognitive difficulties.
Researchers used computer simulations to predict the presence of hydroxyl radicals, which clean pollutants from the atmosphere. The study showed that traditional models had widely varying forecasts due to uncertainties in gas emissions, and that better models can aid in combating climate change.
A new rapid screening test for glaucoma uses infra-red sensors to monitor eye movement, providing accurate results within seconds. The test could help advance early detection of the disease, a leading cause of irreversible blindness, and make it more accessible for national screening programs.
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Researchers developed carbon nanotube-based transistors that can maintain electrical properties and memory after being exposed to high levels of cosmic radiation. The transistors, especially double-shielded ones, showed promising results for future space exploration.
Research finds that online dating app tailoring affects users' perceptions of recommended partners. Users who provide information about their partner preferences tend to identify more date-worthy partners, while those without experience benefit from customizing their preferences.
A new AI-based computer algorithm created by Mount Sinai researchers can identify subtle changes in electrocardiograms to predict heart failure. The algorithm was 94% accurate at predicting healthy ejection fractions and 87% accurate at detecting weakened hearts, offering a promising alternative to traditional diagnosis methods.
A study from Lancaster University found that a serious game, 'Point of Contact', increased players' awareness of Covid-19 transmission risk and favorability towards health over livelihood. The game's impact was significant, with 87% of participants saying they would be more careful in following Covid-19 preventative guidance.
Researchers at Skoltech extend the adiabatic theorem to finite temperatures, ensuring more stable quantum dynamics. The findings have significant implications for next-generation quantum devices and computing.
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Researchers at Arizona State University have refined cryogenic electron microscopy to produce more accurate structures of biological samples. The new method uses a statistical approach to model transitory structures, which can play a vital role in biological processes.
A new study published in The Lancet Digital Health found a link between screen time and myopia in children and young adults. High levels of smart device exposure increased the risk of short-sightedness by up to 80%, according to researchers at Anglia Ruskin University.
Researchers propose a solution using tethered unmanned aerial vehicles (TUAVs) to receive signals while minimizing uplink exposure. The system uses low-power 'green antennas' that only receive signals and do not radiate EMF, offering increased data transfer speeds.
A team of researchers at Bristol's Quantum Engineering and Technology Labs has developed a silicon photonic chip that can protect quantum bits from errors using photons. This breakthrough could lead to the creation of more powerful quantum computers by reducing the fragility of qubits.
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Researchers have developed ultra-thin, defect-free superconducting flakes for use in quantum computing. The twist angle of the flakes is used to modulate the maximum supercurrent, creating an extremely sensitive magnetic field sensor. This breakthrough has potential applications in healthcare and mineral exploration.
Researchers develop a new method to perform logic operations more efficiently and reliably using magnonics. Nanostructured antiferromagnetic wires are well-suited for this purpose, enabling quick and low-energy computation.
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 researchers at Aarhus University aims to develop an optical sensor using terahertz light to decode the direction of tiny magnetic 'tornadoes' called skyrmions. Skyrmions offer a promising candidate for future bits in computer technology, requiring less power and generating less heat than current methods.
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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 from UTHealth and Baylor College of Medicine recommend that EHR developers annually assess their products to ensure safety recommendations are met. The authors suggest three strategies to complement the new CMS rules, aiming to distribute responsibility for safety improvements evenly between designers, developers, and users.
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.
A newly improved robotic cane, funded by NIH/National Eye Institute, uses a color 3D camera, inertial measurement sensor, and onboard computer to guide users to desired locations while avoiding obstacles. The device can provide accurate navigation assistance in large spaces with sensory and auditory cues.
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A new algorithm, Phe2vec, accurately identified patients with certain diseases, outperforming traditional methods in classifying diagnoses. The study suggests that this automation will facilitate further research in clinical informatics.
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 effort at the University of Kansas aims to design course modules to train students in building and maintaining more secure computer hardware. The work is supported by a $400,000 grant from the National Science Foundation's SaTC program.
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A UC Riverside materials scientist has received a $2 million grant to improve the scalability of quantum computers, allowing them to operate at room temperature. The project aims to create design guidelines and manufacturing strategies for hybrid organic-inorganic structures that can produce quantum computers on a larger scale.
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 found that people's personality, such as extroversion, and gender affect their interaction with websites. Extroverted individuals tend to prefer interactive sites that facilitate communication between users, while men and women have different preferences when it comes to interacting with computers.
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A joint research team from POSTECH and KIMS developed a faster and more accurate microstructure imaging technique using deep learning. The technique enhanced the resolution of existing microstructure images up to 4, 8, or 16 times, reducing imaging time by up to 256x compared to conventional SEM systems.
Lehigh University researcher Roberto Palmieri aims to make RDMA technology even faster by revisiting a long-held theory. His goal is to enable all machines to interact with local memory, reducing latency and improving performance.
A new $2.7 million grant from the US Department of Energy will support a three-year research effort to identify and store quantum information in solids, enabling significant advancements in quantum computing. The project aims to build a database of viable qbits by analyzing defects in solids.
Researchers at GIST develop a novel framework that achieves state-of-the-art accuracy in multi-object tracking using deep temporal appearance matching association (Deep-TAMA). The approach combines joint-inference neural networks with long-short-term-memory networks to overcome challenges such as occlusions and lighting changes.
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AI is transforming various aspects of life, such as road safety with EEG-based driver state estimation techniques and automatic image captioning for indexing large datasets. It also enhances surveillance tasks with cognitive memory-augmented networks, improving accuracy and reliability.
Researchers successfully integrate a new ultrahigh thermal-management material into computer chips, reducing heat and increasing energy efficiency. The development outperforms existing materials like diamond and silicon carbide, with temperatures rising to nearly 188 degrees Fahrenheit.
A recent NC State University study found that a low-cost computer training program called Drive Aware can significantly reduce unsafe incidents among older adults. The program, which provides cognitive training to detect road hazards, was tested on 27 senior participants and showed a 25% reduction in accidents.
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Researchers at Columbia University School of Engineering and Applied Science have developed a computer vision technique that enables machines to predict human behavior with higher accuracy. The algorithm leverages higher-level associations between people, animals, and objects to make more intuitive predictions about future actions, ope...
Correlated errors in quantum computers indicate a problem that must be acknowledged and addressed for fault-tolerant development. The study suggests that simple design changes can mitigate local effects, but the bigger concern is what could happen next.
Researchers developed a new hybrid computing approach, combining reliability of classical computers with strength of quantum systems. This method enables near-term applications and discoveries in fields like carbon dioxide removal and pharmaceutical design.
A new study by California Institute of Technology researchers found that a computer program can accurately predict which paintings a person will like, using low-level visual attributes such as contrast, saturation, and hue. The program achieved similar accuracy to deep convolutional neural networks in predicting art preferences.
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Researchers at ETH Zurich have developed a new approach to prove the robustness conditions of certain quantum-based machine learning models, guaranteeing reliable results. The team's work explores protection against errors and hackers, paving the way for more accurate and trustworthy quantum machine learning applications.
Artificial intelligence natural language computer applications hold promise for health care, but their potential and pitfalls need thoughtful exploration. The authors identify realistic applications such as relieving routine tasks and improving customer service, but also emphasize the need for 'serious guardrails' to prevent harm.
A team of researchers from Tokyo Institute of Technology and RIKEN, Japan, conducted a meta-synthesis to understand human perception and interaction with computer voices. They found that users prefer human-like voices, particularly those with high pitches and empathetic tones, and that the inclusion of vocal fillers improves interactions.
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Researchers from UTSA, UCF, AFRL, and SRI International have developed a new method that improves how artificial intelligence learns to see. By adding noise to multiple layers of a neural network, the team creates more robust representations of images recognized by AI, leading to better explanations for AI decisions.
Experts from the University of Goettingen and Hereon have developed new research strategies for polymer membranes, promising relatively inexpensive production and strong separation selectivity. Computer simulations will play a crucial role in understanding these systems.
Researchers at Northern Arizona University developed a computerized method that uses machine learning to analyze visual information, allowing for rapid sorting of thousands of pottery fragments. The system achieved accuracy comparable to human experts and provided a visual record of its thought process.
A research team from Iowa State University has developed a way to control hard-to-predict systems. The technique uses quotienting to identify the least fixed-point operator, which can result in a new model that acts as a supervisor of the system.
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A new brain-computer interface (BCI) system has been developed to restore communication in people with spinal cord injuries and neurological disorders. The system uses mental handwriting to record brain activity, allowing participants to compose sentences and communicate at a speed comparable to typing on a smartphone.
Researchers have deciphered brain activity associated with trying to write letters by hand and developed an algorithm to identify letters. The system displayed the text on a screen in real time, allowing the participant to type 90 characters per minute, more than double the previous record for typing with a brain-computer interface.
Researchers at Skoltech have developed an AI-driven drone system to detect and track Sosnovsky's hogweed, a plant causing severe burns and ecosystem damage. The system uses real-time image segmentation on board drones to identify individual plants, increasing localization efficiency by multifold.
A research team at Washington State University has developed an improved computational method to detect improper gerrymandering using the open source tool GerryChain. The tool creates a pool of alternate maps that meet legal voting criteria, allowing observers to detect extreme outliers and identify potential partisan goals.