A Newcastle University study has developed a machine learning tool that can predict the performance properties of land plant Rubisco proteins with high accuracy. This prediction will enable researchers to identify and engineer 'supercharged' Rubisco proteins that can increase atmospheric CO2 uptake and store in crops such as wheat.
SourceNewcastle University·JournalJournal of Experimental Botany·TypeExperimental study·DateSep 30, 2022
A study published in Cell Press found that when humans are involved, computer decisions are perceived as fairer. Participants deemed decisions related to positive outcomes fairer than negative ones and had concerns over fairness in systems with higher stakes. The results suggest that automated decision-making systems need careful desig...
SourceCell Press·JournalPatterns·TypeExperimental study·DateSep 29, 2022
Researchers developed a machine learning model to quickly recognize predictive risk factors and their importance for undesirable hospitalization outcomes. The model achieved an accuracy of 95.6% and identified modifiable risk factors that can be mitigated through clinical interventions.
SourceHouston Methodist·JournalAlzheimer s & Dementia Translational Research & Clinical Interventions·TypeData/statistical analysis·DateSep 29, 2022
Neuronal silencing periods enable efficient temporal sequence identification, allowing the brain to remember phone numbers and PINs. A new AI mechanism utilizing this mechanism also protects against stolen cards by recognizing personal handwriting style and timing.
SourceBar-Ilan University·JournalScientific Reports·DateSep 29, 2022
Fluke 87V Industrial Digital Multimeter
Fluke 87V Industrial Digital Multimeter is a trusted meter for precise measurements during instrument integration, repairs, and field diagnostics.
Researchers at Ohio State University have developed a new machine learning method called next-generation reservoir computing that can learn spatiotemporal chaotic systems in a fraction of the time. The algorithm is more accurate and uses less training data, making it easier to predict complex physical processes like Earth's weather.
SourceOhio State University·JournalChaos An Interdisciplinary Journal of Nonlinear Science·TypeComputational simulation/modeling·DateSep 28, 2022
A recent grant will fund a project developing new hardware for machine learning, aiming to curb unsustainable energy use in AI systems. The new algorithms being developed are made available to the research community and compatible with an openly shared computing platform.
Researchers developed a computational platform to identify metabolic vulnerabilities in ovarian cancer genes, suggesting opportunities for targeted therapies. The study found that certain genetic alterations can create vulnerabilities in cancer cell metabolism, which can be exploited to selectively kill cancer cells.
SourceMichigan Medicine - University of Michigan·JournalNature Metabolism·TypeExperimental study·DateSep 28, 2022
GQ GMC-500Plus Geiger Counter
GQ GMC-500Plus Geiger Counter logs beta, gamma, and X-ray levels for environmental monitoring, training labs, and safety demonstrations.
A blood test taken at the time of Covid-19 infection could predict who is most likely to develop long Covid. Researchers identified a 'signature' in protein levels that predicted persistent symptoms after one year.
SourceUniversity College London·JournalEBioMedicine·TypeData/statistical analysis·DateSep 27, 2022
The use of voice control smart devices in children may impede critical thinking, empathy, and compassion. Devices can't teach children how to behave politely and lack non-verbal communication skills.
SourceBMJ Group·JournalArchives of Disease in Childhood·TypeCommentary/editorial·DateSep 27, 2022
Current AI models are restricted by a lack of experience in real-world environments, despite achieving significant advancements in virtual settings. Researchers are now exploring ways to bridge this gap with foundation models that can operate in physical spaces.
SourceIntelligent Computing·JournalIntelligent Computing·TypeCommentary/editorial·DateSep 27, 2022
A recent study published in Aging-US found that feeling lonely, unhappy, or hopeless increases one's biological age more than smoking. The research used digital models of aging to analyze the effects of various factors on aging rates, revealing a significant correlation between mental health and accelerated aging.
SourceDeep Longevity Ltd·JournalAging-US·TypeData/statistical analysis·DateSep 27, 2022
A machine learning multi-city model is developed to predict municipal solid waste generation in China, using a wide range of feature variables. The model shows good performance with an R-squared value of 0.939 and is suitable for predicting MSW generation in China.
SourceHigher Education Press·JournalFrontiers of Environmental Science & Engineering·TypeExperimental study·DateSep 26, 2022
Creality K1 Max 3D Printer
Creality K1 Max 3D Printer rapidly prototypes brackets, adapters, and fixtures for instruments and classroom demonstrations at large build volume.
Physicists used machine learning to compress a complex quantum problem into four equations, capturing the physics of electrons on a lattice with high accuracy. The approach could revolutionize how scientists investigate systems containing many interacting electrons and potentially aid in designing materials with sought-after properties.
SourceSimons Foundation·JournalPhysical Review Letters·TypeComputational simulation/modeling·DateSep 26, 2022
Researchers discovered a pattern of DNA mutations that links bladder cancer to tobacco smoking using a powerful new machine learning tool. The tool identified four mutational signatures, including one tied to tobacco smoking, which could lead to more customized treatments for patients with specific cancers.
SourceUniversity of California - San Diego·JournalCell Genomics·DateSep 26, 2022
The 2022 EXPLORE Lunar Data Challenge identifies hazards on the Moon's surface using images from the Lunar Reconnaissance Orbiter. Participants train models to recognize craters and boulders, then create a map of optimal rover routes to avoid hazards.
Researchers reviewed mobile sensing designs, outcomes, and limitations to better understand its capacity for remote detection, longitudinal tracking, and exposure tracing. Despite technical and societal challenges, advances in data analytics and machine learning may improve data quality and scalability.
SourceHealth Data Science·JournalHealth Data Science·TypeData/statistical analysis·DateSep 22, 2022
A team of scientists from China published a perspective paper on the use of AI in skin diseases, highlighting its potential to assist clinicians. They propose several recommendations to improve AI-assisted diagnosis systems, including establishing a robust database and adapting algorithms to existing real-world databases.
SourceHealth Data Science·JournalHealth Data Science·TypeCommentary/editorial·DateSep 22, 2022
GoPro HERO13 Black
GoPro HERO13 Black records stabilized 5.3K video for instrument deployments, field notes, and outreach, even in harsh weather and underwater conditions.
Researchers use classical computers to make predictions about quantum systems, helping to solve physics and chemistry problems. Machine learning tools provide a bridge between the human world and quantum reality.
SourceCalifornia Institute of Technology·JournalScience·DateSep 22, 2022
Researchers developed an electronic laboratory notebook that uses knowledge graphs to describe material properties and experimental processes. The platform enables automated analysis, lossless sharing, and discovery of new materials with potential applications in energy-related devices.
SourceWaseda University·Journalnpj Computational Materials·TypeData/statistical analysis·DateSep 21, 2022
Researchers developed an AI tool using natural language processing and machine learning to identify people who inject drugs in electronic health records. The model accurately identified PWIDs in 1,000 records from 2003-2014, significantly improving clinical decision making and resource allocation.
SourceUniversity of California - Los Angeles Health Sciences·JournalOpen Forum Infectious Diseases·TypeData/statistical analysis·DateSep 21, 2022
The study used a weakly supervised deep learning algorithm to analyze human brain autopsy tissues and predict the presence or absence of cognitive impairment. The model identified a signal associated with decreasing myelin staining, which was linked to cognitive impairment in the white matter.
SourceThe Mount Sinai Hospital / Mount Sinai School of Medicine·JournalActa Neuropathologica Communications·DateSep 20, 2022
Meta Quest 3 512GB
Meta Quest 3 512GB enables immersive mission planning, terrain rehearsal, and interactive STEM demos with high-resolution mixed-reality experiences.
A multidisciplinary team at UC San Diego received NSF funding to create a system that remotely monitors patient posture, movement, and physical therapy treatments using wearable technology and machine learning. The goal is to enable personalized physical therapy treatments and improve health outcomes.
Researchers have developed an algorithm that uses smartphone camera and flash to detect low blood oxygen levels. The method produced accurate results in 80% of the participants, showing promise for remote monitoring and early detection of conditions like COVID-19.
SourceUniversity of Washington·Journalnpj Digital Medicine·DateSep 19, 2022
Researchers developed a new software tool called ProteinMPNN to create protein molecules more accurately and quickly than before. The team used machine learning algorithms, including AlphaFold, to generate new protein shapes and sequences, paving the way for novel vaccines, treatments, and sustainable biomaterials.
SourceUniversity of Washington School of Medicine/UW Medicine·JournalScience·TypeComputational simulation/modeling·DateSep 15, 2022
Researchers at Emory University used machine learning and fMRI to analyze a dog's brain activity while watching videos. The results show that dogs are more attuned to actions in their environment than to who or what is performing the action. This study offers proof of concept for decoding canine visual perception.
SourceEmory University·JournalJournal of Visualized Experiments·TypeComputational simulation/modeling·DateSep 15, 2022
Apple AirPods Pro (2nd Generation, USB-C)
Apple AirPods Pro (2nd Generation, USB-C) provide clear calls and strong noise reduction for interviews, conferences, and noisy field environments.
Researchers developed an AI diagnostic tool called CheXzero that can detect diseases on chest X-rays from natural-language descriptions contained in accompanying clinical reports. The model performed on par with human radiologists and was trained without laborious human annotation of data, making it a major advance in clinical AI design.
SourceHarvard Medical School·JournalNature Biomedical Engineering·TypeComputational simulation/modeling·DateSep 15, 2022
University of Minnesota scientists have developed a method to fine-tune traditional compressed sensing for high-quality images using modern data science tools and machine learning ideas. This approach closes the gap between traditional and deep learning methods, providing a new direction for MRI reconstruction research.
SourceUniversity of Minnesota·JournalProceedings of the National Academy of Sciences·DateSep 14, 2022
The Center for BrainHealth has launched three research projects to develop objective metrics of improved brain systems in response to interventions. These projects aim to determine the changes in the brain's physiology, structure, and function linked to gains in comprehensive psycho-social measurements over time.
Nikon Monarch 5 8x42 Binoculars
Nikon Monarch 5 8x42 Binoculars deliver bright, sharp views for wildlife surveys, eclipse chases, and quick star-field scans at dark sites.
The Florida Summer Institute in Biostatistics and Data Science recruits students from underrepresented groups, providing a rigorous quantitative education. The program introduces college students to statistical methods and applications in biomedical research, highlighting health disparities and social drivers of health.
The University of California, San Diego is part of the National Institutes of Health's Bridge to Artificial Intelligence program, aiming to create comprehensive AI-ready datasets. The program will support researchers in developing interpretable and trustworthy AI technologies to improve human health.
Researchers developed a unified machine learning model that analyzes data from patients with and without treatment, predicting depression outcomes better than separate models. The approach enables personalized medicine by designing treatment plans specific to each patient's needs.
SourceWashington University in St. Louis·JournalProceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies·TypeRandomized controlled/clinical trial·DateSep 13, 2022
Healthcare researchers caution against misusing AI algorithms in clinical research, highlighting concerns about bias, transparency, and data quality. The team advocates for evaluating ML methods against traditional statistical approaches and ensuring clinician decision-making is complemented, not replaced.
SourceDuke-NUS Medical School·JournalNature Medicine·TypeCommentary/editorial·DateSep 13, 2022
Apple iPhone 17 Pro
Apple iPhone 17 Pro delivers top performance and advanced cameras for field documentation, data collection, and secure research communications.
City digital twin technology is used to create synthetic training data for deep learning models, which are then trained on a combination of real and synthetic data. This approach yields promising results for architectural segmentation tasks, particularly for modern building styles.
SourceOsaka University·JournalJournal of Computational Design and Engineering·TypeComputational simulation/modeling·DateSep 8, 2022
Researchers find XAI methods improve AI performance and explain bias in data, enabling accurate applications like insurance decision-making. Implementing XAI helps manage power consumption and optimize AI systems for efficient Industry 4.0 growth.
SourceIncheon National University·JournalIEEE Transactions on Industrial Informatics·TypeSurvey·DateSep 8, 2022
Researchers developed an AI method to predict how well new COVID-19 variants infect human cells and evade antibodies. The system can analyze a million mutated variants, enabling the development of next-generation antibody therapies and vaccines that provide broader protection against potential future variants.
SourceETH Zurich·JournalCell·TypeExperimental study·DateSep 6, 2022
A team led by York University has developed a new technique to keep drinking water safe in refugee settlements using machine learning and ensemble forecasting systems. The approach can predict the probability of residual chlorine remaining in stored water, providing critical information for aid workers to ensure safe drinking water.
SourceYork University·JournalPLOS Water·DateSep 6, 2022
Sky-Watcher EQ6-R Pro Equatorial Mount
Sky-Watcher EQ6-R Pro Equatorial Mount provides precise tracking capacity for deep-sky imaging rigs during long astrophotography sessions.
A new method using machine learning corrects damaged DNA and unveils true mutation processes in tumour samples, helping early cancer detection and accurate diagnosis. The tool predicted over 90% of developing cancer processes, offering a significant advancement in cancer patient care.
SourceUniversity of Helsinki·JournalNature Communications·DateSep 6, 2022
Researchers from GIST developed an AI model that adjusts videogame difficulty based on player emotions, incorporating aspects such as challenge, competence, flow, and valence. The model has been verified to improve players' overall experience, regardless of their preference, and has potential applications in various fields beyond gaming.
SourceGIST (Gwangju Institute of Science and Technology)·JournalExpert Systems with Applications·TypeComputational simulation/modeling·DateSep 6, 2022
Researchers created IGLUE to score ML efficiency in 20 languages, addressing cultural bias and practical implications. The tool aims to improve solutions for visually impaired and reduce performance dropouts outside English-speaking contexts.
SourceUniversity of Copenhagen - Faculty of Science·DateSep 5, 2022
Machine learning helps researchers discover how bacterial populations adapt to environmental diversity by analyzing growth curves. The analysis reveals distinct decision-making components for lag, growth, and saturation phases, protecting the population from extinction.
SourceUniversity of Tsukuba·JournaleLife·DateSep 5, 2022
SAMSUNG T9 Portable SSD 2TB
SAMSUNG T9 Portable SSD 2TB transfers large imagery and model outputs quickly between field laptops, lab workstations, and secure archives.
Researchers at UMaine have developed a novel AI-based method for monitoring soil moisture in forests, using wireless sensor networks and machine learning to optimize energy efficiency. This approach could enable more efficient tracking of forest health, reducing costs and increasing reliability.
SourceUniversity of Maine·JournalInternational Journal of Wireless Information Networks·DateSep 2, 2022
Researchers at Drexel University have developed a computer model that uses machine learning algorithms to analyze the genetic sequence of the COVID-19 virus and predict the severity of new variants. The model provides an early warning system for public health officials, allowing them to prepare accordingly.
SourceDrexel University·JournalComputers in Biology and Medicine·TypeComputational simulation/modeling·DateSep 1, 2022
Researchers developed a new machine-learning method to understand force chains in jammed granular solids. The graph neural network approach can predict the position of force chains with high accuracy, even for complex systems and varying conditions.
SourceUniversity of Göttingen·JournalNature Communications·DateSep 1, 2022
Rigol DP832 Triple-Output Bench Power Supply
Rigol DP832 Triple-Output Bench Power Supply powers sensors, microcontrollers, and test circuits with programmable rails and stable outputs.
A large retrospective study found that visceral fat area from fully automated and normalized abdominal CT analysis predicts subsequent myocardial infarction or stroke in Black and White patients. The study suggests that body composition analysis using machine learning could be widely adopted to add prognostic utility to clinical practice.
SourceAmerican Roentgen Ray Society·JournalAmerican Journal of Roentgenology·TypeImaging analysis·DateAug 31, 2022
A Brazilian research team has developed a novel method to sort specialty and standard coffee beans using multispectral imaging and machine learning. The technique, which does not require roasting or human intervention, uses images of the beans at different wavelengths to distinguish between quality levels.
SourceFundação de Amparo à Pesquisa do Estado de São Paulo·JournalComputers and Electronics in Agriculture·DateAug 30, 2022
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.
SourceRice University·TypeExperimental study·DateAug 29, 2022
AmScope B120C-5M Compound Microscope
AmScope B120C-5M Compound Microscope supports teaching labs and QA checks with LED illumination, mechanical stage, and included 5MP camera.
A new method for generating realistic images in driving simulations uses machine learning to improve visual fidelity. This enables better testing of driverless cars and study of driver distraction, ultimately enhancing safety and interaction between humans and AI on the road.
SourceOhio State University·JournalIEEE Transactions on Intelligent Transportation Systems·TypeExperimental study·DateAug 29, 2022
A team of Japanese researchers used reinforcement learning to study fluid mixing during laminar flow, achieving exponentially fast mixing without prior knowledge. The method also enabled effective transfer learning, reducing training time for new mixing problems, and has potential applications across various industries.
SourceTokyo University of Science·JournalScientific Reports·TypeComputational simulation/modeling·DateAug 29, 2022
Researchers at Arizona State University have developed a machine learning model to predict melting temperatures for any compound. The model enables faster and more accurate calculations of melting points, which is critical for designing high-performance materials in various industries.
SourceArizona State University·JournalProceedings of the National Academy of Sciences·TypeComputational simulation/modeling·DateAug 29, 2022
A*STAR scientists have developed VarNet, an AI-based method that identifies cancer mutations in tumor samples with high accuracy. This breakthrough allows for personalized treatment strategies and better understanding of cancer.
SourceAgency for Science, Technology and Research (A*STAR), Singapore·JournalNature Communications·DateAug 28, 2022
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.
Sony Alpha a7 IV (Body Only)
Sony Alpha a7 IV (Body Only) delivers reliable low-light performance and rugged build for astrophotography, lab documentation, and field expeditions.
A study reveals that over 50% of mammal food web links have disappeared due to animal declines, leading to a collapse of global ecosystems. Restoring extinct species to their historic ranges holds great potential to reverse these declines and restore food web complexity.
SourceRice University·JournalScience·TypeData/statistical analysis·DateAug 25, 2022
ORNL researchers have won seven 2022 R&D 100 Awards for their advancements in materials science, machine learning, and energy storage. DuAlumin-3D, a high-strength aluminum alloy, and Gremlin, an AI system to identify weaknesses in machine learning models, are among the winning technologies.
A team of Brazilian researchers has developed a novel technique using light and artificial intelligence to identify the maturity stages of soybean seeds. The method utilizes chlorophyll fluorescence and machine learning algorithms to classify commercial seeds with high accuracy. This innovation avoids destroying seeds, which are then c...
SourceFundação de Amparo à Pesquisa do Estado de São Paulo·JournalFrontiers in Plant Science·DateAug 25, 2022
The special report outlines 12 suboptimal practices in data handling that can predispose machine learning systems to bias. The report presents strategies to mitigate these biases, including careful planning, multidisciplinary teams, and creating heterogeneous training datasets.
SourceRadiological Society of North America·JournalRadiology Artificial Intelligence·TypeComputational simulation/modeling·DateAug 24, 2022
Researchers used satellite imagery and machine learning to pinpoint high-priority areas for deforestation action, reducing the target area by 160,000 km². The study reveals that only 37% of the last three years' deforestation rate was covered by official monitoring in the 11 municipalities.
SourceFundação de Amparo à Pesquisa do Estado de São Paulo·JournalConservation Letters·DateAug 24, 2022
Davis Instruments Vantage Pro2 Weather Station
Davis Instruments Vantage Pro2 Weather Station offers research-grade local weather data for networked stations, campuses, and community observatories.
Researchers at Washington University in St. Louis are evaluating the potential of AI to improve health outcomes and doctor well-being. Chenyang Lu's team has developed novel methods using deep learning to predict physician burnout and surgical outcomes, transforming clinical data into accurate predictions.
SourceWashington University in St. Louis·TypeComputational simulation/modeling·DateAug 23, 2022
Researchers developed a machine learning algorithm that can predict how different driving patterns affect battery performance, improving safety and reliability. The algorithm uses non-invasive probing to provide a holistic view of battery health, suggesting routes and driving patterns that minimize degradation and charging times.
SourceUniversity of Cambridge·JournalNature Communications·TypeExperimental study·DateAug 23, 2022
A machine learning model developed by Canadian and Slovenian researchers accurately predicted fall risk in lower limb amputees, achieving up to 80% accuracy. This breakthrough has significant implications for the development of smartphone-based fall detection systems.
SourcePLOS·JournalPLOS Digital Health·TypeObservational study·DateAug 18, 2022
A team of researchers from Osaka University developed an AI algorithm to predict the risk of mortality for trauma patients. They analyzed a large dataset of patient information and blood markers to identify critical factors that guide treatment strategies more precisely.
SourceOsaka University·JournalCritical Care·TypeObservational study·DateAug 17, 2022