A large-scale study linked loneliness to an increased risk of degenerative heart valve disease, including aortic valve stenosis and mitral valve regurgitation. Researchers say addressing loneliness could help delay disease progression and reduce the clinical and economic burden of valvular heart disease.
An international team of researchers used AI to create tiny 'smart' proteins that detect chosen targets, opening the way to low-cost biosensors. The protein switches can work inside living cells and generate electrical signals, making them suitable for various sensing technologies.
Researchers found that nearly half of Prairie lakes, wetlands, and reservoirs may be degraded by decades of urea use, which increases growth of microscopic plants and drains essential oxygen out of ponds. Sustainable sources of water are threatened due to agricultural impacts, drainage of wetlands, and climate change.
A study by Ebenbuild confirms strong predictive performance of patient-specific lung digital twins, validated against clinical imaging data. The model's accuracy was demonstrated through a correlation coefficient of 0.95 with experimental data, enabling locally resolved predictions of aerosol deposition at the individual patient level.
The SWIFTT platform uses Copernicus Sentinel satellite data and machine learning models to identify tree health changes, detect anomalies, and predict threats like spruce bark beetle outbreaks and wildfires. Foresters can access timely alerts, prioritize inspections, and coordinate clearing of dead wood to protect forests.
Leading women physicists from India will share their stories of navigating biases and creating practical strategies for advancing equity and inclusion in science. The webinar highlights the real-world impact of physics research and its societal benefits.
The University of Chicago's Data Science Institute is developing AI-based forecasting technology to support farmers and citizens worldwide. The project aims to deliver forecasts that inform decision-making on agriculture, public health, and extreme heat avoidance.
A growing number of fungi are becoming resistant to medication, posing serious risks for patients with weakened immune systems. A five-step plan aims to monitor and prevent the rise of resistant fungi through awareness, surveillance, infection prevention and control, optimized use, and investments.
Researchers at Osaka Metropolitan University developed a new AI-powered snake-like robot that optimizes its movement using deep reinforcement learning. The robot's 'rolling motion' achieves twice the travel speed per unit of power consumption compared to traditional slithering motion, making it more efficient on flat surfaces.
A study found that AI models trained on large amounts of registry data can identify individuals at higher risk of melanoma. The most advanced model distinguished individuals with a 33% probability of developing melanoma in about 73% of cases.
A Virginia Tech student's discovery of a rare, ancient meat-eating dinosaur sheds light on the evolution and spread of dinosaurs during the Jurassic period. The species, Ptychotherates bucculentus, had massive cheekbones and a short snout, indicating constant evolution in early dinosaurs.
According to new research, over 66 million Americans use AI tools or chatbots for physical or mental healthcare information or advice. Most turn to AI to supplement their healthcare experiences, using it before or after seeing a doctor. AI usage is driven by various factors, including wanting answers quickly, additional information, an...
Researchers at Stockholm Environment Institute developed a new method to identify and reduce risks of violating Sámi rights linked to industrial projects on traditional lands. The method highlights significant risks to human rights, particularly for the Gabna Sámi reindeer herding community.
Researchers propose an agnostic biosignature that detects life on a population level by analyzing patterns of planetary traits and spatial relationships. This method prioritizes reliability over completeness, minimizing false positives even if it misses some life-bearing planets.
A high-precision Human Immune Aging Clock (HIAC) has been developed to quantify immunosenescence and identify actionable intervention targets. The study identified RUNX1 as a functional 'brake' on T-cell senescence, and found that individuals with decelerated immune aging displayed a more youthful immune profile.
Villouta's research aims to characterize root exudates and understand their role in plant stress and productivity in hydroponic systems. He will explore how temperature variations affect spinach growth in hydroponic environments, with the goal of improving crop viability and informing best practices for other temperature-sensitive crops.
The University of Hong Kong's High West Development has been awarded the Outstanding MiC Project (Design) award for its innovative application of Modular Integrated Construction. The project features high-quality design, campus planning, and heritage sensitivity, showcasing how MiC can be integrated with these aspects.
The article reviews bidirectional capacitive power transfer, conversion topologies, resonant networks, and power control strategies. Key findings highlight the need for coordination between power electronics and coupling structures in bidirectional operation.
The CLAP system integrates authentication and processing functions within a unified memristor-based platform, offering critical security protection for resource-constrained edge computing devices. It achieves remarkable energy efficiency gains and area reductions compared to conventional implementations.
A study integrating recent omics technologies reveals key molecular alterations, regulatory networks, and potential therapeutic targets for ESCC. Key findings include identified diagnostic biomarkers, prognostic indicators, and therapeutic targets.
The 18-District Health Community Project aims to promote preventive health, enhance community well-being, and empower residents with practical knowledge. The project will provide free health screenings, public seminars, and community-based health education across all 18 districts in Hong Kong.
The collaboration aims to empower biopharmaceutical innovation by integrating AI with traditional Chinese medicine technologies. AilsynBio and Dong-E E-Jiao will focus on three key areas: drug discovery, mechanism-of-action elucidation, and lead design optimization.
The HKU Centre for the Humanities and Medicine has launched initiatives to address women's health, particularly menopause, in Hong Kong. Director Professor Olga Zayts-Spence emphasized the need for robust community support and institutional backing as women spend nearly a third of their lives in this stage.
A study by Edith Cowan University found that tracking students' moods over several weeks provides a more accurate picture than a single snapshot in time. Repeated mood monitoring can help identify students who may be struggling with mental health challenges.
Researchers developed a feature selection-based solar irradiance forecasting method to improve stand-alone photovoltaic system operation. The approach forecasts solar irradiance using a bidirectional long short-term memory hybrid network, then estimates the optimum tilt angle to increase PV output power.
A new Perspective revisits the controversy over calorie restriction's impact on mouse lifespan, arguing that genetic background may not be a key driver of life-shortening effects. The authors suggest that experimental design and sample size are more likely to cause heterogeneity in results.
Researchers found auroras on Saturn behave differently from those on Earth, appearing uneven and shifted to one side. The team attributes this to Saturn's rapid rotation, which reshapes its magnetic environment, driving an off-center magnetic bubble pattern.
Professor Sophia Chan Siu-chee received the RCN's highest honour for her outstanding work in advancing nursing development and improving population health. The award highlights her dedication to promoting professional nursing development, workforce development, and health system transformation.
Researchers developed an energy-saving control strategy for intelligent connected plug-in hybrid electric vehicles that incorporates driving-intention identification of the vehicle ahead. The approach optimizes speed, improves energy economy, and maintains comfort and safety by anticipating front-vehicle behavior.
Researchers propose an integrated eco-driving framework using deep reinforcement learning to optimize motion trajectory planning and energy management. The framework achieves substantial improvements in transverse-longitudinal comfort, energy economy, and power system health, while reducing hydrogen consumption and driving costs.
The University of Hong Kong and Grand Pharmaceutical Group have signed a research collaboration agreement to develop novel therapeutic solutions for anti-infective treatments. The partnership aims to accelerate innovative drug development by integrating academic research with industrial application.
A new study from Edith Cowan University found that higher sodium intake is associated with a faster decline in episodic memory in men. The study of over 1,200 participants suggests that diets high in salt may have broader cognitive impacts than previously understood.
The International Association for Dental, Oral, and Craniofacial Research (IADR) and the American Association for Dental, Oral, and Craniofacial Research (AADOCR) have recognized a cover paper in their Journal of Dental Research. The award honors an aesthetically pleasing image that enhances the article's impact.
A novel energy management system (EMS) reduces converter count, battery stress, and hydrogen use in stand-alone hybrid photovoltaic and proton exchange membrane fuel cell microgrids. The EMS maintains DC-link stability while adapting to changing renewable generation and load conditions.
The forum brought together leading scholars and industry experts to discuss cutting-edge breakthroughs in advanced materials, energy science, sustainability, and micro-nano engineering. Key findings include innovative designs for atmospheric water harvesting and electrocatalysts for hydrogen economy.
Spatial proteomics enables precise mapping of protein distribution in native tissue contexts, addressing critical limitations of conventional bulk proteomics. This transformative solution has far-reaching implications for disease stratification, therapeutic target discovery, and personalized treatment strategies.
A new study found that children who start primary school at older ages completed more years of schooling, had greater wealth in adulthood, and fewer teen pregnancies. This delay allowed them to develop greater literacy and was associated with better health outcomes, including lower rates of HIV infection and child death.
Researchers have developed an electrochemical impedance spectroscopy (EIS) identification algorithm to reconstruct EIS at low frequencies using short-duration sine-wave current pulses. The approach enables accurate state-of-charge estimation for LiFePO4 batteries, which is essential for battery management systems.
Researchers designed a high-efficiency bidirectional wireless power transfer system for multiple electric vehicles, supporting both grid-to-battery and battery-to-grid operations. The system achieved high efficiency under various operating conditions, with demonstrated interoperability between different vehicle-side equipment.
Researchers propose a novel SENet-CNN-Transformer model to predict electric vehicle charging duration, outperforming existing models in accuracy and reducing training time. The approach combines data enhancement, channel attention, convolutional neural networks, Transformer modeling, and transfer learning to address real-world data sca...
Researchers developed a health-aware V2G strategy using reinforcement learning to optimize charging and discharging times, resulting in significant lifecycle cost savings ($1,539) and extended battery life (21 months). The study suggests electric bus charging stations can be promising platforms for scalable V2G services.
Researchers evaluate the effectiveness of Vision Transformers and convolutional neural networks for faster and more accurate defect detection in railway track fasteners. The study finds that transformer-based models outperform traditional CNNs, suggesting their potential value for predictive health management in rail networks.
Researchers employed PCT-assisted sample preparation with DIA mass spectrometry to compare the proteomic profiles of MGA and non-neoplastic kidney tissues. They identified 1,338 differentially expressed protein groups, including 190 downregulated and 1,148 upregulated proteins.
Researchers propose a Fourier graph neural network to estimate lithium-ion battery state of health, capturing spatial and temporal feature relationships. The model achieves significant reductions in error compared to existing methods, suggesting improved accuracy and transferability.
Battery performance is critical to electrified transportation and green energy systems. Real-world diagnostics are challenging due to complex environments and varying data quality. The review emphasizes the need for adaptive models and AI integration to improve battery status prediction.
A review article highlights a deep learning-driven CNN approach for detecting and classifying dynamic road obstacles, achieving high accuracy in obstacle identification and classification. The proposed architecture shows strong performance, but real-world deployment requires continued evaluation across larger and more varied scenarios.
A new study investigates sulfide-based and oxide-based solid electrolyte systems for next-generation lithium-ion solid-state batteries. The researchers found that the oxide-based hybrid approach offered notable advantages in performance, with improved lifespan and capacity retention compared to all-solid-state sulfide cells.
A comprehensive review reorganizes the design space for electrified propulsion systems in three-dimensional transportation, proposing six design stages to guide future research. The review addresses challenges specific to TDT propulsion design, including balancing energy efficiency, weight, reliability, and emissions.
Researchers propose an efficient feature search approach for estimating lithium-ion battery state of health, reducing reliance on manually selected aging features. The method combines Bayesian optimization and ensemble regression to improve accuracy and robustness.
A new planning framework proposes integrating bidirectional electric vehicle battery networks into sustainable communities, evaluating how EVs can support local energy systems. The framework models EVs as active participants in the neighborhood energy system, simulating grid interaction and energy exchange characteristics.
Researchers developed a rapid battery-capacity estimation method using early voltage response during the first discharge cycle. The approach extracts electrochemical signatures related to battery condition and enhances features to improve prediction accuracy, reducing testing time by over 80%.
Researchers proposed a model-based diagnostic framework for electric vertical take-off and landing aircraft battery systems, improving fault detection and isolation under demanding aviation conditions. The approach achieves high detection rates, even in concurrent-fault scenarios, making it suitable for certifying eVTOL systems.
Researchers propose a personalized longitudinal motion planning policy combining reinforcement learning and imitation learning for intelligent vehicles. The approach adapts driving style to target drivers while meeting performance requirements, promoting human-like behavior and increasing acceptance.
Researchers at The University of Osaka developed a new LED structure that generates circularly polarized light from a single chip, reducing energy-conversion loss. This advancement could support smaller and more energy-efficient optical devices for next-generation technologies.
A study from Murdoch University found that both music and traffic noise can make people's imagination more vivid. Music was particularly effective in creating positive and emotional journeys, while adding traffic noise somewhat dampened this effect.
Researchers directly imaged paired electrons causing electric current to flow without resistance at sufficiently low temperatures. The experiment revealed that the paired atoms moved in a synchronized dance, with their positions dependent on those of other pairs.
A machine learning technique identifies optimal spots for tree planting to inform climate mitigation strategies. Optimised afforestation can reduce river peaks by up to 43% while preserving groundwater by up to 60%. The study's findings highlight the importance of data-driven technologies in supporting large-scale, smarter planning.
Researchers at Chalmers University of Technology have developed a new method for measuring breathing movements in patients with impaired lung function using radio frequency technology. The technique involves placing small tags on the chest wall, which can detect even slight differences in breathing movements and provide a detailed pict...
Researchers at Saitama University have identified ATP-P2X7 signaling as a neural mechanism that drives powerful colonic contractions necessary for defecation. The study reveals a new pathway involving the P2X7 receptor and cholinergic neurons, providing fresh insight into gastrointestinal motility.
The Stem Cell Report podcast has marked five years of exploration in stem cell research, capturing significant progress in human development, disease, and regenerative medicine. The anniversary episode reunites past guests to discuss the field's evolution, highlighting advances in therapies, organoid systems, and global standards.