Computer scientists designed a reconstruction attack that proves US Census data can be exposed and stolen with current privacy measures. The study demonstrates risks to individual respondents' privacy, highlighting the need for differential privacy techniques to protect sensitive information.
SourceUniversity of Pennsylvania School of Engineering and Applied Science·JournalProceedings of the National Academy of Sciences·DateFeb 21, 2023
Researchers developed a machine learning model using high-resolution satellite imagery to estimate aboveground carbon stocks in the Amazon. The study found that accounting for uncertainties in forest degradation classification led to lower estimates of mean carbon density, suggesting earlier estimates may have been over-optimistic.
SourceOregon State University·JournalCarbon Balance and Management·TypeComputational simulation/modeling·DateFeb 20, 2023
A new study by Tulane University demonstrates that even a single atom can act as a reservoir for computing, processing information optically. The researchers proposed a non-linear single-atom computer where input and output are encoded in light, enabling flexible computation with any desired outcome.
SourceSpringer·JournalThe European Physical Journal Plus·DateFeb 20, 2023
A Penn State-led research team found that language models can plagiarize content in three ways: verbatim, paraphrase, and idea reuse. The study highlights the need for more research into text generators and their potential ethical implications.
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 have developed a hand-held device that can rapidly and accurately identify lesions in the mouth that will develop into cancer. The Liverpool Diagnostic Infrared (LDIR) Wand employs infrared lasers to predict future cancer risk based on machine learning analysis.
Researchers used machine learning to classify hundreds of thousands of X-ray objects, discovering thousands of new cosmic objects including black holes and neutron stars. This breakthrough establishes a state-of-the-art capacity for applying machine learning techniques in fundamental astronomy research.
SourceTata Institute of Fundamental Research·JournalMonthly Notices of the Royal Astronomical Society·DateFeb 15, 2023
A new technique maps the effects of fire-induced permafrost thaw in Alaska, revealing widespread topographic change and vegetation shifts. The study used a machine learning-based approach to quantify thaw settlement across 3 million acres of land, with results showing a significant loss of evergreen forest and shrubland encroachment.
SourceFlorida Atlantic University·JournalEnvironmental Research Letters·TypeComputational simulation/modeling·DateFeb 14, 2023
A new machine learning model combines fusion gene profiling, serum PSA level, and Gleason score to predict prostate cancer recurrence with improved accuracy. The model outperformed clinical data alone and provided valuable insights into the mechanism of disease progression.
SourceElsevier·JournalAmerican Journal Of Pathology·TypeComputational simulation/modeling·DateFeb 14, 2023
A new study uses Fourier analysis to understand how deep neural networks learn complex physics. By analyzing the equation of a fully trained model, researchers were able to identify crucial information about how the network learns and generalizes. This breakthrough could accelerate the use of scientific deep learning in climate science.
SourceRice University·JournalPNAS Nexus·TypeComputational simulation/modeling·DateFeb 13, 2023
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 MIT developed a technique to improve machine-learning models' reliability without requiring additional data or extensive computing resources. The method uses a simpler companion model to estimate uncertainty, enabling more effective uncertainty quantification.
SourceMassachusetts Institute of Technology·DateFeb 13, 2023
Researchers at the University of Gothenburg have developed three AI-based decision support systems for cardiac arrest care, which can help doctors identify key factors affecting patient outcomes. The tools are based on large datasets and provide accuracy rates of up to 95% in predicting patient survival or death.
SourceUniversity of Gothenburg·JournalEBioMedicine·TypeData/statistical analysis·DateFeb 13, 2023
Researchers applied machine learning tools to study how climate impacts connectivity and biodiversity in the Pacific Ocean's Coral Triangle. They found that climate dynamics have contributed to biodiversity due to variability introduced by El Niño and La Niña events.
SourceGeorgia Institute of Technology·JournalCommunications Biology·TypeExperimental study·DateFeb 9, 2023
Rice University researchers have developed an innovative system to study mosquito feeding behavior using fake skin made with a 3D printer, eliminating the need for live volunteers. The system was tested on various mosquito repellents and showed promising results, suggesting it could be scaled up for future studies.
SourceRice University·JournalFrontiers in Bioengineering and Biotechnology·TypeExperimental study·DateFeb 9, 2023
Researchers have developed a new synthetic skin, made of hydrogels, to study how mosquitoes transmit deadly diseases. The hydrogel system can mimic different blood vessel patterns, allowing for more consistent testing and analysis. This breakthrough may help identify ways to prevent the spread of disease.
SourceTulane University·JournalFrontiers in Bioengineering and Biotechnology·TypeExperimental study·DateFeb 9, 2023
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 utilized the Chemistry42 platform to generate novel molecular structures and identified a hit molecule for CDK20, a promising target for hepatocellular carcinoma. The platform's customizable reward function and generative models enabled efficient design and optimization of molecules.
SourceInSilico Medicine·JournalJournal of Chemical Information and Modeling·TypeCase study·DateFeb 7, 2023
New research from the University of Georgia reveals that artificial intelligence can be used to find planets outside our solar system. Machine learning can analyze environments where planets are still forming, helping scientists overcome difficulties such as distance and data thickness.
SourceUniversity of Georgia·JournalThe Astrophysical Journal·DateFeb 7, 2023
Researchers used Reinforcement Learning to enable kites and gliders to adjust their orientations in real-time, accounting for turbulence. This improvement could significantly enhance the performance of airborne wind energy devices, expanding the reach of wind power to poorer communities.
SourceSpringer·JournalThe European Physical Journal E·DateFeb 7, 2023
FRIDA uses AI models similar to those powering tools like ChatGPT and DALL-E 2 to generate paintings based on user input. The robot's final products are impressionistic and whimsical, with bold brushstrokes that lack precision sought in robotic endeavors.
Apple iPhone 17 Pro
Apple iPhone 17 Pro delivers top performance and advanced cameras for field documentation, data collection, and secure research communications.
The iCPH platform combines physical and cyber elements to capture human motions, using musculoskeletal analysis and machine learning. It generates contact motion networks for humanoid robots and simulates human behaviors, enabling smooth interactions with humans.
SourceTokyo University of Science·JournalFrontiers in Robotics and AI·TypeSystematic review·DateFeb 6, 2023
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.
SourcePublic Relations Pacific LLC·JournalNature Cancer·DateFeb 2, 2023
Researchers developed a machine learning model using advanced 2D chemical descriptors to predict highly selective asymmetric catalysts without quantum chemical computations. The model demonstrated high accuracy in predicting catalyst structures and selectivity, outperforming existing methods.
SourceHokkaido University·JournalAngewandte Chemie International Edition·TypeExperimental study·DateFeb 2, 2023
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.
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.
SourceUniversity of Massachusetts Amherst·JournalMethods in Ecology and Evolution·DateFeb 1, 2023
A new approach to deep reinforcement learning demonstrates ability to stabilize large datasets used in AI models, which may lead to uncovering ways to arrest cancer development. The method has been successful in designing and refining existing therapies, with the next step being to use live cells.
SourceUniversity of Surrey·JournalIEEE Transactions on Control of Network Systems·DateFeb 1, 2023
NeuralTree is a closed-loop neuromodulation system-on-chip that can detect and classify biomarkers from real patient data and animal models of disease in-vivo, leading to high accuracy in symptom prediction. The system boasts 256 input channels, making it highly versatile and scalable.
SourceEcole Polytechnique Fédérale de Lausanne·JournalIEEE Journal of Solid-State Circuits·TypeExperimental study·DateJan 30, 2023
Researchers applied deep learning techniques to a previously studied dataset of nearby stars, uncovering eight previously unidentified signals of interest. The new approach enabled faster and more accurate results, with the potential to accelerate discovery of extraterrestrial life.
SourceSETI Institute·JournalNature Astronomy·DateJan 30, 2023
Researchers have developed an AI-based resource to assist individuals in identifying recommended actions based on their clinical profile and COVID at-home test results. The system uses a combination of symptoms and home tests to provide more accurate diagnoses and improve patient care.
SourceGeorge Mason University·JournalQuality Management in Health Care·DateJan 30, 2023
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 at Bar-Ilan University have developed a new type of artificial neural network that outperforms traditional deep learning architectures. By using tree architecture with single routes to output units, they achieve better classification success rates, paving the way for efficient and biologically-inspired AI hardware.
SourceBar-Ilan University·JournalScientific Reports·DateJan 30, 2023
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.
SourceMax Planck Florida Institute for Neuroscience·DateJan 30, 2023
Scientists developed an AI system, ProGen, that can generate artificial enzymes from scratch, working as well as those found in nature. The AI model learned aspects of evolution and was able to tune its generation for specific effects, creating proteins with unique properties.
SourceUniversity of California - San Francisco·JournalNature Biotechnology·DateJan 26, 2023
A new project aims to examine the circulation of newspaper reports on anti-Black violence between 1863 and 1921. The team will use computational methods to trace how stories spread across the country and map their impact, with potential applications for studying other forms of racial violence.
SourceUniversity of Illinois School of Information Sciences·DateJan 25, 2023
DJI Air 3 (RC-N2)
DJI Air 3 (RC-N2) captures 4K mapping passes and environmental surveys with dual cameras, long flight time, and omnidirectional obstacle sensing.
Researchers created a system to monitor underground gas pipelines using high-tech sensors that can detect weaknesses, discrepancies, and diversion in residential natural gas lines. The method uses ultrasonic sensors to transmit signals through the pipe, limiting the likelihood of gas diversions and ensuring public safety.
SourceUniversity of British Columbia Okanagan campus·JournalSensors·TypeMeta-analysis·DateJan 25, 2023
A $2.3 million grant from the US Department of Energy funds a 'solar testbed' at I-79 Technology Park in Fairmont, supporting research on battery storage, grid integration, and cybersecurity. The project aims to assess solar panel health and monitor grid interactions with solar power.
Researchers modified an algorithm to detect urinary tract infections (UTIs) in primary care settings, removing microscopy features that weren't available. The new algorithm performed well and suggests withholding antibiotics from low-risk patients to reduce antibiotic overuse.
SourceAmerican Academy of Family Physicians·JournalThe Annals of Family Medicine·DateJan 23, 2023
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.
The study, published in Nature Medicine, demonstrates the first-ever use of federated learning to train deep learning models on histopathology data from multiple hospitals without compromising data privacy. This breakthrough has the potential to unlock precision medicine through secure and AI-powered medical research.
SourceOwkin, Inc.·JournalNature Medicine·TypeData/statistical analysis·DateJan 19, 2023
Researchers successfully applied AlphaFold AI to an end-to-end platform, discovering a novel target and developing a potent hit molecule for liver cancer. The study demonstrates the potential of AI-powered drug discovery to accelerate treatment development.
SourceUniversity of Toronto·JournalChemical Science·TypeComputational simulation/modeling·DateJan 19, 2023
Researchers at the University of Wisconsin-Madison have developed a machine-learning model that detects cancers at an early stage by analyzing fragments of cell-free DNA in plasma. The technique, which uses readily available lab materials, distinguished people with any stage of cancer from healthy individuals 91% of the time.
SourceUniversity of Wisconsin-Madison·JournalScience Translational Medicine·DateJan 19, 2023
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 have developed a machine learning model that can predict the word about to be uttered by a subject based on their neural activity. The model achieved 55% accuracy using six channels of data and 70% accuracy using eight channels, comparable to other studies requiring electrodes over the entire cortical surface.
SourceNational Research University Higher School of Economics·JournalJournal of Neural Engineering·DateJan 19, 2023
MIRMI researchers create robotic waiter with precise control using the principles of a spherical pendulum, achieving 'slosh-free movement' and improving safety. The solution has potential applications in healthcare and hazardous materials transport.
SourceTechnical University of Munich (TUM)·TypeCase study·DateJan 16, 2023
A research team at Carnegie Mellon University has developed a machine learning method called SPICEMIX to analyze spatial transcriptomics data. The tool helps identify and understand gene expression patterns in cells, revealing new insights into brain cell types.
SourceCarnegie Mellon University·JournalNature Genetics·DateJan 13, 2023
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.
SourceDOE/Brookhaven National Laboratory·JournalScience Advances·DateJan 13, 2023
Researchers developed machine learning models to accurately calculate fine particulate matter in urban air pollution using AI and traffic data. The models provide a high-resolution estimation of city street pollution surface, enabling transportation and epidemiology studies to assess health impacts.
SourceCornell University·JournalTransportation Research Part D Transport and Environment·DateJan 13, 2023
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.
Researchers found that many changes to human DNA had opposing effects, with some variants making enhancers stronger while others made them weaker. This discovery has implications for understanding human evolution and the potential link between human DNA variations and psychiatric diseases.
A large randomized study found that machine learning-triggered reminders significantly increased rates of advanced care planning conversations, reducing potentially harmful therapies at end of life. The intervention also improved patient education and early palliative care referrals.
SourceUniversity of Pennsylvania School of Medicine·JournalJAMA Oncology·DateJan 12, 2023
Researchers designed a new long-acting injectable drug formulation using machine learning algorithms, achieving a slow-release rate in just one iteration. The study demonstrates the potential for machine learning to accelerate the development of innovative drug delivery technologies.
SourceUniversity of Toronto - Leslie Dan Faculty of Pharmacy·JournalNature Communications·TypeExperimental study·DateJan 10, 2023
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 new study uses machine learning to predict poor glycemic control in patients with type 2 diabetes, identifying key factors such as prior glucose levels and anti-diabetic medicines. The findings suggest that data routinely collected for diabetes monitoring can reliably identify patients at risk of hyperglycemia.
SourceUniversity of Eastern Finland·JournalClinical Epidemiology·DateJan 9, 2023
Researchers have developed a diffractive optical processor that can compute hundreds of transformations in parallel using wavelength multiplexing. The processor, which is powered by light instead of electricity, can execute multiple complex functions simultaneously at the speed of light.
SourceSPIE--International Society for Optics and Photonics·JournalAdvanced Photonics·DateJan 9, 2023
A new study reveals that high-quality coral reefs in Hawaii are popular tourist sites, but also at risk from tourism-related development and pollution. The research used social media and aerial mapping to analyze the impact of tourist visitation on live coral cover across hundreds of coastal sites.
SourcePrinceton School of Public and International Affairs·JournalNature Sustainability·TypeObservational study·DateJan 9, 2023
Researchers used machine learning to create molecule chains that display designated colors in response to different stimuli, such as light, chemicals, and energy. This breakthrough enables faster and more efficient data storage and security applications.
SourceARC Centre of Excellence in Exciton Science·JournalChem·TypeExperimental study·DateJan 8, 2023
A UVA research team developed a real-time detection method for keyhole pore generation in laser powder bed fusion, achieving a 100% prediction rate. This approach expands additive manufacturing capabilities for aerospace and other industries relying on strong metal parts.
SourceUniversity of Virginia School of Engineering and Applied Science·JournalScience·TypeExperimental study·DateJan 6, 2023
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 develop AI model to predict exhaust gas emissions from ships under different air-to-fuel ratios. The ensemble dataset and double ensemble models produce the most accurate emission predictions for CO2, NOx, and SO2 gases.
SourceNational Korea Maritime and Ocean University·JournalJournal of Cleaner Production·TypeComputational simulation/modeling·DateJan 4, 2023
Scientists have developed a new method to enhance electron-photon coupling, resulting in a hundredfold increase in light emissions. The approach uses a specially designed photonic crystal to produce stronger interactions between photons and electrons.
SourceMassachusetts Institute of Technology·JournalNature·DateJan 4, 2023
A group of scientists developed a machine learning approach to predict amine emissions from a carbon capture plant. They analyzed data from a stress test at a German power plant and found that two amines respond in opposite ways, increasing or decreasing emissions. This new method has the potential to change the way chemical plants ope...
SourceEcole Polytechnique Fédérale de Lausanne·JournalScience Advances·DateJan 4, 2023
A new computer program, DeepMosaic, uses artificial intelligence to detect mosaic mutations in genetic sequences. This method enables accurate detection of mosaic mutations, which cause hundreds of unsolved and untreatable disorders, including epilepsy.
SourceUniversity of California - San Diego·JournalNature Biotechnology·DateJan 2, 2023
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.
ETH Zurich researchers have created a range of affordable fluorescent inks with machine learning algorithms to determine the right molecular subunits. The new dyes can be used for security features and applications like solar power plants and organic light-emitting diodes.
Scientists at Caltech used machine-learning algorithm to chart sills, mapping them with precision and linking them to active volcanoes Mauna Loa and Kīlauea. The study provides new insights into magma storage and transport deep beneath Hawai‘i.
SourceCalifornia Institute of Technology·JournalScience·TypeObservational study·DateDec 22, 2022
Researchers at Drexel University used GPT-3 to spot early signs of Alzheimer's in spontaneous speech, achieving 80% accuracy. The program analyzed word-use, sentence structure and meaning from transcripts to identify characteristic profiles of Alzheimer's speech.
SourceDrexel University·JournalPLOS Digital Health·TypeComputational simulation/modeling·DateDec 22, 2022
Researchers at University of Copenhagen developed a method to map individual trees' carbon content using aerial images, improving accuracy and enabling better comparisons between countries. The method supports Rwanda in verifying commitments under schemes like REDD+ and AFR 100.
SourceUniversity of Copenhagen - Faculty of Science·JournalNature Climate Change·DateDec 22, 2022
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 recent study has identified common and unique cellular processes in six neurodegenerative diseases, providing new insights into the underlying causes of these conditions. The research used machine learning analysis to compare RNA markers in whole blood samples from patients with distinct diseases, revealing eight shared themes across...
SourceArizona State University·JournalAlzheimer s & Dementia·TypeData/statistical analysis·DateDec 21, 2022
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 found that providing language descriptions of tools can accelerate a simulated robotic arm's learning of tool manipulation. The team used GPT-3 to obtain tool descriptions and showed improved performance in tasks such as pushing, lifting, sweeping, and hammering with new tools.
SourcePrinceton University, Engineering School·TypeComputational simulation/modeling·DateDec 21, 2022