Scientists from CHOP and NJIT created a software tool to analyze information from a single cell, revealing relationships between different cellular characteristics. The 'single-cell multimodal deep clustering' method can help identify the causes of genetic-based diseases by integrating data on gene expression, mRNA, proteins, and organ...
SourceChildren's Hospital of Philadelphia·JournalNature Communications·TypeData/statistical analysis·DateDec 21, 2022
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.
SourceBrown University·JournalNature Computational Science·TypeComputational simulation/modeling·DateDec 19, 2022
Researchers are conducting on-site surveys and generating high-resolution damage maps for 20-square-mile region affected by the Category 4 storm. The goal is to inform protection efforts and help communities recover from the disaster.
A new machine learning model developed by Aalto University researchers can identify small molecules with unprecedented accuracy, distinguishing between mirror image molecules. This breakthrough has significant implications for understanding metabolic disorders, such as diabetes, and identifying micropollutants in the environment.
SourceAalto University·JournalNature Machine Intelligence·DateDec 19, 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.
Using machine learning to study water's phase changes, researchers found strong computational evidence in support of liquid-liquid transition. This technique can be applied to real-world systems that use water, informing water's use in industrial processes and climate models.
SourceGeorgia Institute of Technology·JournalPhysical Review Letters·TypeComputational simulation/modeling·DateDec 16, 2022
The UTEP-led Computing Alliance will receive $4.8M from Google to improve diversity in computer science fields. The project aims to attract, prepare and support Hispanic students for graduate degrees, with initiatives including lab design, financial support and research collaborations.
Researchers developed AI-powered software to measure and classify pacu fish, enabling breeders to select animals with higher fillet yield and faster weight gain. The system uses deep learning and can recognize different parts of the fish even in challenging environments.
SourceFundação de Amparo à Pesquisa do Estado de São Paulo·JournalAquaculture·DateDec 15, 2022
Apple iPhone 17 Pro
Apple iPhone 17 Pro delivers top performance and advanced cameras for field documentation, data collection, and secure research communications.
Veterinary experts warn that AI algorithms used in radiology and imaging can provide faulty or incomplete diagnoses, posing risks to patient care. The absence of regulatory oversight for veterinary AI products increases concerns over accuracy, transparency, and potential harm.
SourceNorth Carolina State University·JournalVeterinary Radiology & Ultrasound·TypeLiterature review·DateDec 14, 2022
Researchers developed a machine learning model that uses microbiome data from wastewater to estimate the number of individuals represented in a sample. The method was trained on over 1,100 people's samples and can be used to link wastewater properties to individual-level data.
SourceWashington University in St. Louis·JournalPLOS Computational Biology·TypeExperimental study·DateDec 14, 2022
Researchers developed a machine learning-based strategy for direct classification of acute aquatic toxicity, explaining 90% of training set variance and 80% of test set variance. The approach resulted in a fivefold decrease in incorrect categorization compared to QSAR regression models.
SourceUniversiteit van Amsterdam·JournalEnvironmental Science & Technology·DateDec 14, 2022
A new study found that a machine learning-based blood test can accurately predict an individual's entire diet over 19 food groups, outperforming traditional methods. The test, which uses molecular profiling, also identifies who is more likely to develop diabetes and cardiovascular disease based on each food group.
SourceMichigan Medicine - University of Michigan·JournalEuropean Heart Journal·TypeComputational simulation/modeling·DateDec 14, 2022
Using supercomputers and machine learning, researchers created simulations of millions of computer-generated universes to test astrophysical predictions. The study found that supermassive black holes grow in the same way as their host galaxies, revealing a long-elusive relationship.
SourceUniversity of Arizona·JournalMonthly Notices of the Royal Astronomical Society·TypeData/statistical analysis·DateDec 14, 2022
Kestrel 3000 Pocket Weather Meter
Kestrel 3000 Pocket Weather Meter measures wind, temperature, and humidity in real time for site assessments, aviation checks, and safety briefings.
Researchers developed an accurate predictive model to distinguish between COVID-19 positive and negative test outcomes. The study found that symptom features, such as fever and difficulty breathing, play a significant role in predicting test results, with molecular tests yielding lower positive rates due to their dependence on viral load.
SourceFlorida Atlantic University·JournalSmart Health·TypeComputational simulation/modeling·DateDec 13, 2022
Researchers have identified a method that can automatically detect doxing on Twitter with high accuracy, which could help protect users from cyberbullying. The approach uses machine learning to differentiate between self-disclosures and malicious disclosures of sensitive personal information.
SourcePenn State·JournalProceedings of the ACM on Human-Computer Interaction·DateDec 12, 2022
A team of researchers from Tokyo University of Science developed a super-hierarchical and explanatory analysis method for magnetic reversal processes, enabling the detection of subtle microscopic changes. The new algorithm can predict stable/metastable states in advance and improve the reliability of spintronics devices.
SourceTokyo University of Science·JournalScience and Technology of Advanced Materials Methods·TypeComputational simulation/modeling·DateDec 12, 2022
A Penn State-led research team found that TikTok's unique interface and algorithm make content creation and virality particularly easy yet lead to high rates of creator burnout. The platform's central role of the algorithm in determining viewership makes creators produce new content continuously, leading to burnout.
SourcePenn State·JournalComputational Communication Research·DateDec 12, 2022
A University of Houston researcher has developed a method to describe complex systems using the least number of variables possible, reducing complexity from millions to just one. This advancement speeds up science with efficiency and ability to understand and predict natural system behavior.
SourceUniversity of Houston·JournalNature Machine Intelligence·DateDec 8, 2022
Apple iPad Pro 11-inch (M4)
Apple iPad Pro 11-inch (M4) runs demanding GIS, imaging, and annotation workflows on the go for surveys, briefings, and lab notebooks.
Researchers at UCSF and IBM Research create a predictive model that encodes commands for cells to kill cancer cells. By combining words that guide engineered immune cells, they can predict which elements should be included in a cell to carry out precise behaviors. This advance allows scientists to rapidly design new cellular therapies.
SourceUniversity of California - San Francisco·JournalScience·DateDec 8, 2022
Researchers aim to provide the highest quality of care possible by understanding the sound environment of child care centers. A 48-hour monitoring period and staff evaluations helped identify factors influencing child and provider experiences.
Researchers have developed a scaled-up version of a probabilistic computer using stochastic spintronic devices, suitable for combinatorial optimization and machine learning. The new design combines conventional semiconductor chips with modified spintronic devices, achieving massive improvements in throughput and power consumption.
Garmin GPSMAP 67i with inReach
Garmin GPSMAP 67i with inReach provides rugged GNSS navigation, satellite messaging, and SOS for backcountry geology and climate field teams.
The National Cancer Institute awards $10.5 million to USC's Division of Biostatistics to develop statistical methods for uncovering new risk factors associated with cancer by integrating large volumes of health, genomic, and exposure data. The project aims to provide new insights into complex biological processes and discoveries of nov...
Machine learning is being explored as a tool to speed up the identification of biomaterials. Researchers have also developed a guide on how to incorporate ML into research programs. Additionally, studies have investigated ways to model polymers at multiple scales and created a self-healing hydrogel for sustained release of medications.
SourceAmerican Chemical Society·JournalACS Polymers Au·DateDec 5, 2022
A new AI evaluation framework, GOPHER, has been developed to assess the efficiency of genome analysis algorithms. The tool judges programs on their ability to learn genomic biology, predict patterns, handle noise, and provide interpretable decisions.
SourceCold Spring Harbor Laboratory·JournalNature Machine Intelligence·DateDec 5, 2022
Researchers developed a machine learning algorithm to identify cough sounds and determine if someone has pneumonia, aided by room impulse responses. The algorithm can work in any environment, facilitating non-face-to-face treatment and reducing medical costs.
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.
SourceUniversity of Pennsylvania School of Engineering and Applied Science·JournalProceedings of the National Academy of Sciences·DateDec 5, 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.
Researchers developed a noninvasive microphone sensor that uses machine learning to detect bowel diseases like cholera. The algorithm analyzes audio data from toilet sounds, identifying consistent tones for urination and singular tones for defecation.
A new paper by researchers at the University of Birmingham argues that a 'one size fits all' approach to treating early psychosis may not be effective. Instead, they propose using machine learning techniques to deliver tailored treatment plans that address individual needs and improve outcomes.
SourceUniversity of Birmingham·JournalTranslational Psychiatry·TypeLiterature review·DateDec 2, 2022
Researchers at Klick Applied Sciences have created a machine learning model to predict diabetes onset in patients using just 12 hours of data from continuous glucose monitors. The study showed high accuracy in identifying prediabetes, healthy patients, and those with Type 2 diabetes, offering a potential tool for early disease prevention.
SourceKlick Applied Sciences·TypeComputational simulation/modeling·DateDec 2, 2022
Researchers developed a method to measure overall fitness using wearable devices, outperforming current consumer smartwatches and fitness monitors. The model uses machine learning to predict VO2max during everyday activity, providing accurate predictions based on heart rate and accelerometer data.
SourceUniversity of Cambridge·Journalnpj Digital Medicine·DateDec 1, 2022
Scientists used AI-driven PandaOmics platform to analyze gene expression datasets from DNA repair diseases, identifying biomarkers associated with treatment response. The study focused on genes that stratify cancer patients by survival outcomes, providing potential targets for personalized therapies.
SourceInSilico Medicine·JournalCell Death and Disease·TypeData/statistical analysis·DateDec 1, 2022
Celestron NexStar 8SE Computerized Telescope
Celestron NexStar 8SE Computerized Telescope combines portable Schmidt-Cassegrain optics with GoTo pointing for outreach nights and field campaigns.
Researchers developed a new approach to analyze coercivity in soft magnetic materials using machine learning and data science. The method condenses relevant information from microscopic images into a two-dimensional feature space, visualizing the energy landscape of magnetization reversal. This study showcases how materials informatics...
SourceTokyo University of Science·JournalCommunications Physics·TypeExperimental study·DateDec 1, 2022
A study led by Kyoto University researchers found that AI-generated haiku poems, created without human intervention, were often indistinguishable from those penned by humans. In contrast, human-AI collaboration produced more creative works.
SourceKyoto University·JournalComputers in Human Behavior·TypeExperimental study·DateDec 1, 2022
Researchers developed a new method to detect lung cancer using machine learning and statistical techniques, identifying 7 specific volatile organic compounds in breath samples. This breakthrough could lead to earlier diagnosis and improved treatment outcomes for patients.
A new AI method has analyzed substance use trends among Canadian high schoolers, identifying factors such as large weekly allowances and low physical activity that increase the risk of transitioning to multiple substance use. The study found that once students start using substances, it is rare for them to stop, highlighting the need f...
SourceUniversity of Waterloo·JournalThe Lancet Regional Health - Americas·DateNov 30, 2022
A recent study published in Nature Computational Science reveals that specific regions of the brain process both individual and combined words, while others focus solely on individual words. The research could contribute to the development of wearable neurotechnology devices that can decode language directly from brain activity.
SourceCarnegie Mellon University·JournalNature Computational Science·DateNov 29, 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 neural network trained using a diverse dataset outperforms conventionally trained algorithms by reducing bias in artificial intelligence. The use of images from low-resource populations boosts the object recognition performance of machine learning systems.
SourceHarvard John A. Paulson School of Engineering and Applied Sciences·DateNov 29, 2022
A new machine learning fusion model has been developed to diagnose ovarian cancer more accurately by combining ultrasound and photoacoustic tomography imaging. The model achieved an accuracy of 90% in detecting ovarian lesions, outperforming previous methods.
SourceWashington University in St. Louis·JournalPhotoacoustics·TypeExperimental study·DateNov 29, 2022
The researchers have developed an AI algorithm called M3GNet that can predict the structure and dynamic properties of any material. The algorithm was used to create a database of over 31 million yet-to-be-synthesized materials with predicted properties, facilitating the discovery of new technological materials.
SourceUniversity of California - San Diego·JournalNature Computational Science·TypeComputational simulation/modeling·DateNov 28, 2022
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.
A Rutgers researcher has created a machine learning model that can estimate arsenic contamination in private wells without sampling the water. The model identifies geological bedrock type and soil type as primary contributors to higher arsenic concentrations, highlighting the need for targeted well testing programs.
SourceRutgers University·JournalScience of The Total Environment·DateNov 28, 2022
A Cornell-led collaboration used machine learning to predict Alzheimer's progression in cognitively normal and mildly impaired individuals. The modeling showed that MRI scans are most informative for asymptomatic cases, while PET scans are more effective for those with mild cognitive impairment.
A Penn State research team developed a novel analytical platform using machine learning to selectively measure multiple biomolecules, saving space and reducing complexity. The sensor can detect small quantities of uric acid and tyrosine, important biomarkers associated with various diseases, in saliva and sweat.
SourcePenn State·JournalAnalytica Chimica Acta·TypeExperimental study·DateNov 28, 2022
A new study using artificial intelligence has found that a simple eye test can accurately predict the risk of heart disease. The researchers developed an algorithm that can analyze retinal images to assess cardiovascular health, providing a non-invasive alternative to traditional risk scores.
SourceKingston University·JournalBritish Journal of Ophthalmology·TypeObservational study·DateNov 24, 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.
Researchers developed a new machine-learning framework that enables cooperative or competitive AI agents to consider the future behaviors of all agents, not just their teammates or competitors. This framework, FURTHER, uses two modules: an inference module and a reinforcement learning module, to enable agents to adapt their behaviors a...
SourceMassachusetts Institute of Technology·DateNov 23, 2022
Researchers developed an AI model to analyze spatial and temporal gait parameters, identifying key features for diagnosing Parkinson's. The model achieved high diagnostic accuracy, reducing the probability of error in clinical assessments.
SourceFundação de Amparo à Pesquisa do Estado de São Paulo·JournalGait & Posture·DateNov 22, 2022
A research team developed an optical chip that can train machine learning hardware, improving AI performance and reducing energy consumption. This innovation uses photonic tensor cores and electronic-photonic application-specific integrated circuits to speed up the training step in machine learning systems.
SourceGeorge Washington University·JournalOptica·DateNov 22, 2022
The University of Manchester's Centre for Robotics and AI will focus on interdisciplinary research, exploring applications of robotics in extreme environments and the intersection of AI and humanity. The centre aims to develop robots that can work safely in hostile zones, such as nuclear decommissioning sites.
Apple MacBook Pro 14-inch (M4 Pro)
Apple MacBook Pro 14-inch (M4 Pro) powers local ML workloads, large datasets, and multi-display analysis for field and lab teams.
Researchers from the University of Johannesburg deployed Few Shot Learning (FSL) for NIALM, a non-intrusive appliance load monitoring system. FSL requires only 7 test images to recognize appliances with 97.83% accuracy, making it faster and more cost-effective than traditional Machine Learning.
SourceUniversity of Johannesburg·JournalComputational Intelligence and Neuroscience·TypeImaging analysis·DateNov 21, 2022
Researchers demonstrate that tetraplegic users can operate mind-controlled wheelchairs in a cluttered environment after training, with improvements in accuracy and brain activity patterns. The study highlights the importance of long-term training and neuroplastic reorganization for successful brain-machine interface control.
SourceCell Press·JournaliScience·TypeObservational study·DateNov 18, 2022
Researchers from Kessler Foundation are enrolling participants in a national trial testing a breakthrough device for improving recovery after stroke. The EMAGINE Stroke Recovery Trial pairs therapeutic exercise with electromagnetic stimulation to enhance brain and spinal cord function.
Aranet4 Home CO2 Monitor
Aranet4 Home CO2 Monitor tracks ventilation quality in labs, classrooms, and conference rooms with long battery life and clear e-ink readouts.
Researchers at Oak Ridge National Laboratory have discovered genetic markers for autism, developed recyclable composites to drive the net-zero goal, and created a tool for real-time building evaluation. Additionally, they have made significant progress in growing hydrogen-storage crystals using a novel nano-reactor material.
SourceDOE/Oak Ridge National Laboratory·JournalNature Communications·DateNov 17, 2022
A study by University of Minnesota researchers found that personalized federated learning may offer an opportunity to develop both internal and externally validated algorithms. This technique enables multiple parties to train AI models collaboratively without exchanging or centralizing data sets, protecting sensitive medical informatio...
SourceUniversity of Minnesota Medical School·JournalJournal of the American Medical Informatics Association·TypeComputational simulation/modeling·DateNov 17, 2022
This study employs machine learning to analyze existing experimental results and predict the device performance of metal halide perovskite solar cells. The authors applied shapley additive explanations (SHAP) analysis to understand the correlations between fabrication processes, composition, and device performance.
SourceDalian Institute of Chemical Physics, Chinese Academy Sciences·JournalJournal of Energy Chemistry·DateNov 17, 2022
Researchers used weather radar to track bird movements and found peak roosting stages shifting earlier due to warmer temperatures. This shift may lead to a shortened pre-migratory season, impacting birds' survival during migration.
SourceColorado State University·JournalGlobal Change Biology·TypeData/statistical analysis·DateNov 17, 2022
Researchers used machine learning to analyze high-frequency oscillations in patients' brains during deep sleep, distinguishing between epileptogenic and non-epileptogenic regions. The study achieved an 85% accuracy rate, suggesting a promising method for predicting seizure outcomes.
SourceNational Research University Higher School of Economics·JournalFrontiers in Human Neuroscience·DateNov 16, 2022
Anker Laptop Power Bank 25,000mAh (Triple 100W USB-C)
Anker Laptop Power Bank 25,000mAh (Triple 100W USB-C) keeps Macs, tablets, and meters powered during extended observing runs and remote surveys.
Researchers developed an algorithm using amino acid sequences of proteins called T cell receptors to predict patient response to treatment, providing insights into the biology behind an effective response. The algorithm, DeepTCR, identified patterns that are predictive of patient response as accurately as known biomarkers.
SourceJohns Hopkins Medicine·JournalScience Advances·DateNov 16, 2022
Researchers modelled relationship between plant diversity and environmental conditions, capturing how diversity varies along environmental gradients. The models predict highest concentrations of plant diversity in environmentally heterogeneous tropical areas like Central America and the Amazonia.
SourceUniversity of Göttingen·JournalNew Phytologist·TypeData/statistical analysis·DateNov 15, 2022
Researchers developed a method to learn complex Boolean systems, enabling faster and more accurate diagnoses of urinary diseases, cardiac conditions, and financial risks. The technique uses optimal causation entropy to narrow down correct solutions and turn complex diagnostic processes into decision trees.
SourceEmbry-Riddle Aeronautical University·JournalPatterns·TypeData/statistical analysis·DateNov 11, 2022
CalDigit TS4 Thunderbolt 4 Dock
CalDigit TS4 Thunderbolt 4 Dock simplifies serious desks with 18 ports for high-speed storage, monitors, and instruments across Mac and PC setups.
Researchers created a new set of standards, called FAIR, to manage AI models, making them findable, accessible, interoperable and reusable. This standardization enables cross-pollination across teams and reduces duplication of effort, ultimately facilitating scientific discovery.
SourceDOE/Argonne National Laboratory·JournalScientific Data·TypeNews article·DateNov 10, 2022
A new AI-based chemical sensor can accurately detect specific gases in the air by analyzing temperature changes in a microbeam resonator. The device uses machine learning to differentiate between gases with varying thermal conductivities, achieving 100% accuracy in identifying helium, argon, and CO2.
SourceKing Abdullah University of Science & Technology (KAUST)·JournalIEEE Sensors Journal·DateNov 10, 2022
A new study published in The Journal of Nuclear Medicine found that a PET/MRI machine learning model can reliably distinguish between patients with and without lymph node metastases. This breakthrough technology has the potential to eliminate sentinel lymph node biopsy, a common procedure for breast cancer treatment.
SourceSociety of Nuclear Medicine and Molecular Imaging·JournalJournal of Nuclear Medicine·DateNov 10, 2022