The UNC Charlotte team developed a universal AI algorithm called AutoClass to clean noisy single-cell RNA sequencing (scRNA-Seq) data. The algorithm effectively removes noise and enhances downstream analysis in multiple aspects, demonstrating its robustness and scalability.
SourceUniversity of North Carolina at Charlotte·JournalNature Communications·TypeData/statistical analysis·DateApr 7, 2022
Apple iPhone 17 Pro
Apple iPhone 17 Pro delivers top performance and advanced cameras for field documentation, data collection, and secure research communications.
Researchers have identified the complete series of 10 factors that regulate the development of brain cell types in the visual system of fruit flies. This discovery opens new avenues of research to understand how brain development evolved in different animals and holds clues for regenerative medicine.
SourceNew York University·JournalNature·TypeExperimental study·DateApr 6, 2022
A novel 'rational' neural network reveals underlying mathematical equations through Green's functions, enabling humans to understand machine-generated findings. This breakthrough in partial differential equation learning holds promise for advancing scientific exploration of weather systems, climate change, and more.
SourceCornell University·JournalScientific Reports·DateApr 5, 2022
A new study suggests that a high-salt diet can lead to the hyperactivity of brain cells, resulting in increased constriction of blood vessels and worsening of cardiometabolic diseases. The research also found that excessive salt consumption can trigger an unusual response in which neurons become more active despite reduced blood flow.
SourceMedical College of Georgia at Augusta University·DateMar 22, 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.
Researchers from the University of Cambridge and Oslo identify a century-old mathematical paradox as the Achilles' heel of modern AI. The paradox limits the existence of stable and accurate neural networks, making many AI systems untrustworthy in high-risk areas.
SourceUniversity of Cambridge·JournalProceedings of the National Academy of Sciences·TypeComputational simulation/modeling·DateMar 17, 2022
Researchers reexamined hundreds of experiments on neural activity and consciousness, finding that experiment parameters determine results. The study used artificial intelligence to predict which theory would be supported by each experiment with 80% success.
SourceTel-Aviv University·JournalNature Human Behaviour·DateMar 16, 2022
Researchers at Duke University found a collection of coordinated brain regions that predict and direct social behavior in mice. By analyzing the electrical activity of these regions, they identified how social or solitary an individual mouse is and were able to prompt them to be more gregarious. This study may lead to better diagnostic...
SourceDuke University·JournalNeuron·TypeExperimental study·DateMar 15, 2022
A study published in Frontiers in Microbiology has found that machine learning analysis of microscopy images can be used to identify bacteria resistant to antibiotics. Researchers discovered that shape changes in bacterial cells can predict drug resistance, suggesting a new approach for detecting and predicting drug resistance.
SourceOsaka University·JournalFrontiers in Microbiology·TypeImaging analysis·DateMar 15, 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 Kaunas University of Technology improved an algorithm to detect Alzheimer's disease from MRI images, achieving over 98% accuracy. The new model uses a modified neural network and adapts to variations in data, such as differences in hospital equipment and patient positions.
SourceKaunas University of Technology·JournalSensors·TypeImaging analysis·DateMar 14, 2022
A study found that intact astrocyte networks are essential for neural homeostasis, synaptic plasticity, and spatial cognitive abilities in adult mice. Disrupting these networks impairs spatial learning and memory due to altered neuronal excitability and compromised synaptic transmission.
SourceUniversity of Zurich·JournalCell Reports·TypeExperimental study·DateMar 8, 2022
A new MRI probe can monitor individual populations of neurons and reveal how they interact with each other. The technique uses genetically targeted probes to detect neural activity and provide a more precise picture of brain function.
SourceMassachusetts Institute of Technology·JournalNature Neuroscience·DateMar 3, 2022
A deep learning model has been developed to infer horizontal motion on the Sun's surface using temperature and vertical motion data. The technique shows promise for future high-resolution solar observations and laboratory plasmas.
SourceNational Institutes of Natural Sciences·JournalAstronomy and Astrophysics·TypeComputational simulation/modeling·DateFeb 24, 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.
A team of scientists developed a soft haptic sensor that can accurately estimate contact points and forces using computer vision and deep neural networks. The sensor is sensitive enough to detect even tiny forces and detailed object shapes.
SourceMax Planck Institute for Intelligent Systems·JournalNature Machine Intelligence·DateFeb 24, 2022
KAUST researchers develop an artificial electronic retina that mimics human vision and recognizes handwritten numbers with high accuracy. The retina uses perovskite nanocrystals to detect light intensity via capacitive change, offering a more energy-efficient alternative to existing systems.
SourceKing Abdullah University of Science & Technology (KAUST)·JournalLight Science & Applications·TypeComputational simulation/modeling·DateFeb 23, 2022
The University of Essex team has devised a new approach to training neural networks called Target Space, which stabilizes the learning process by tweaking neuron firing strengths. This method enables deeper neural networks with fewer training examples and computing resources, accelerating AI breakthroughs.
SourceUniversity of Essex·JournalJournal of Machine Learning Research·TypeComputational simulation/modeling·DateFeb 22, 2022
Research reveals that the brain's electrical rhythms fluctuate between high precision and low precision states several times per second, affecting how relevant information is transmitted. Cross-frequency coupling enables selective attention by modulating the strength of different frequencies, while distinguishing between different type...
SourceDeutsches Primatenzentrum (DPZ)/German Primate Center·JournalTrends in Neurosciences·DateFeb 22, 2022
Researchers studied how diverse neural network training datasets impact generalization. They found that data diversity is key to overcoming bias, but also degrade performance when neural networks are trained for multiple tasks simultaneously. The study highlights the importance of designing diverse and controlled datasets in machine le...
SourceMassachusetts Institute of Technology·JournalNature Machine Intelligence·DateFeb 21, 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 Tokyo Institute of Technology have developed a new AI processor called Hiddenite, which achieves state-of-the-art accuracy in sparse neural networks with lower computational burdens. The chip drastically reduces external memory access for enhanced computational efficiency.
SourceTokyo Institute of Technology·TypeExperimental study·DateFeb 18, 2022
A team of researchers from Skoltech and universities developed a neural network-based solution for automated recognition of chemical formulas on research paper scans. The algorithm combines molecules, functional groups, fonts, styles, and printing defects to mimic existing molecular template depiction styles.
SourceSkolkovo Institute of Science and Technology (Skoltech)·JournalChemistry - Methods·DateFeb 14, 2022
A new machine learning process has been developed to identify and classify hip fractures from X-rays, achieving 92% accuracy and confidence. This approach aims to improve patient outcomes, reduce care costs, and alleviate the bottleneck of unreported radiographs in the UK.
SourceUniversity of Bath·JournalScientific Reports·TypeComputational simulation/modeling·DateFeb 11, 2022
Neuroscientists have designed neural organoids with both mature neurons and astrocytic glial cells to study interactions between brain cells. The new technology enables the emulation of brain activity during healthy and disease states, opening doors to rapid drug screening for neurological diseases.
SourceHouston Methodist·JournalJournal of Cell Biology·TypeExperimental study·DateFeb 9, 2022
Researchers propose a new neural network-based method to visualize chemical reactions in a 2D plane, grouping similar reactions together. The visualization helps chemists understand the global chemical reaction space and identify underused or unused reaction types.
SourceSkolkovo Institute of Science and Technology (Skoltech)·JournalACS Omega·DateFeb 2, 2022
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 discovered increased activity in the hippocampus during anesthesia and sleep, preceding Alzheimer's symptoms by years. This abnormality may enable early diagnosis and treatment of the disease.
SourceTel-Aviv University·JournalCell Reports·DateFeb 1, 2022
Researchers at KTH Royal Institute of Technology and Stanford University have developed a material that enables the commercial viability of neuromorphic computers mimicking the human brain. The material, MXene, combines high speed, temperature stability, and integration compatibility in a single device.
SourceKTH, Royal Institute of Technology·JournalAdvanced Functional Materials·DateJan 28, 2022
The MIT team developed a computer model that can perform sound localization tasks as well as humans, and adapts to real-world environments. The model uses convolutional neural networks and was trained on over 400 sounds, including human voices and animal sounds.
SourceMassachusetts Institute of Technology·JournalNature Human Behaviour·DateJan 27, 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.
Cornell researchers have successfully trained various physical systems, including mechanical, optical, and electrical systems, to perform machine learning tasks. The developed training algorithm enables diverse systems to be chained together for efficient processing.
Scientists at Vienna University of Technology have developed a new type of neural network that can accurately simulate the quark-gluon plasma, a state of matter present in the early universe. The networks use gauge invariant convolutional neural networks to recognize patterns and predict properties of the plasma.
SourceVienna University of Technology·JournalPhysical Review Letters·TypeComputational simulation/modeling·DateJan 25, 2022
Researchers found that REM sleep has specific properties allowing rapid arousal in response to predatory stimuli. The medial subthalamic nucleus (mSTN) plays a key role in this process, producing a lowered arousal threshold during REM sleep for detecting predator threats.
SourceChinese Academy of Sciences Headquarters·JournalNeuron·DateJan 21, 2022
MIT researchers develop a method to test feature-attribution methods for machine-learning models. They find that even the most popular methods often miss important features in an image and some perform as poorly as a random baseline. This has major implications for high-stakes situations like medical diagnoses.
SourceMassachusetts Institute of Technology·DateJan 19, 2022
A team of scientists from Gwangju Institute of Science and Technology developed a deep learning-based approach to predict SC2 battle outcomes by considering army composition and terrain type. The proposed model leveraged parameter sharing, enabling it to analyze complex factors accurately and make predictions.
SourceGIST (Gwangju Institute of Science and Technology)·JournalExpert Systems with Applications·TypeComputational simulation/modeling·DateJan 18, 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.
A new project aims to improve the performance of Graph Neural Networks (GNNs) by leveraging weak supervision and additional information. The research has potential applications in fraud detection, agriculture, and cancer diagnosis.
SourceUniversity of Illinois School of Information Sciences·DateJan 18, 2022
Researchers at RIKEN CBS demonstrate that neural networks minimize energy cost and solve mazes efficiently, pointing to a set of universal mathematical rules. The findings will aid in analyzing impaired brain function and generating optimized neural networks for artificial intelligences.
A two-year study aims to restore functional vision among veterans and service members with head trauma-related visual dysfunction using immersive virtual reality technology. Researchers will explore the feasibility and benefits of applying new technologies to rehabilitative treatment activities.
A team of researchers used neural network data to study grid cell activity in the brain, finding that collective neural activity is shaped like a torus, or doughnut. The study provides new insights into how large networks of neurons produce properties that cannot be inferred from individual cells.
SourceNorwegian University of Science and Technology·JournalNature·TypeExperimental study·DateJan 12, 2022
Researchers have discovered a new biomarker, microstate D, associated with increased sleep disturbance and inattention symptoms in adults with ADHD. The study, published in Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, provides evidence for a more precise diagnosis of the disorder.
SourceNational Center of Competence in Research Synapsy·JournalBiological Psychiatry Cognitive Neuroscience and Neuroimaging·DateJan 6, 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.
A transdisciplinary research team at Göttingen Campus has found a new perspective on the rhythmic processes in the brain. They discovered that adapting interneurons can switch between very slow rhythms and fast rhythms, challenging previous assumptions about their function.
SourceUniversity of Göttingen·JournalProceedings of the National Academy of Sciences·TypeExperimental study·DateDec 21, 2021
A Salk Institute team has uncovered a neural network in the brain that connects breathing rhythm with feelings of pain and fear. This discovery could lead to the development of an analgesic that prevents opioid-induced respiratory depression, a major cause of overdose deaths.
A team of researchers from the University of Groningen developed an AI-based system that can identify individual Holstein cows in a milking station based on their coat pattern. The system achieved a recognition rate of 99.7% and has several advantages, including non-invasiveness, cost-effectiveness, and scalability.
SourceUniversity of Groningen·JournalExpert Systems with Applications·TypeImaging analysis·DateDec 15, 2021
Researchers at the University of Göttingen studied how blocking certain enzymes affects brain adaptability in healthy and diseased mice. In healthy mice, inhibiting these enzymes blocked neuronal plasticity, while in stroke-affected mice, it restored lost plasticity.
SourceUniversity of Göttingen·JournalJNeurosci·TypeExperimental study·DateDec 13, 2021
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.
Washington University researchers have designed a new processing-in-memory (PIM) circuit that can increase PIM computing's performance by orders of magnitude. The circuit uses resistive random-access memory PIM, allowing for analog computations and eliminating the need for digital conversions.
SourceWashington University in St. Louis·JournalIEEE Transactions on Computers·TypeComputational simulation/modeling·DateDec 9, 2021
Researchers aim to develop AI agents that reuse information, adapt quickly to new conditions and collaborate by sharing experiences. The goal is to enable machines to continually learn from their collective experiences and improve performance on novel and previous tasks.
A Michigan Tech-developed machine learning model uses probability to classify breast cancer shown in histopathology images and evaluate the uncertainty of its predictions. The model outperforms similar models and can measure uncertainty, promising time savings and referrals to human experts.
SourceMichigan Technological University·JournalIEEE Transactions on Medical Imaging·TypeComputational simulation/modeling·DateDec 1, 2021
A new strategy for ultrafast and energy-efficient all-optical computing is proposed based on convolutional neural networks. The approach uses cascaded silicon waveguides to control light amplitude and phase, achieving ultrafast computing times of several picoseconds with low energy consumption.
SourceCompuscript Ltd·JournalOpto-Electronic Advances·DateNov 30, 2021
Researchers at Tohoku University and the University of Gothenburg have developed a new spintronic technology that integrates a memristor-controlled oscillator array, allowing for efficient brain-inspired computing. This breakthrough enables sophisticated cognitive tasks like image recognition with reduced energy consumption.
SourceTohoku University·JournalNature Materials·DateNov 29, 2021
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 at the University of Gothenburg have successfully combined a memory function with a calculation function in the same component, enabling more efficient technologies like mobile phones and self-driving cars. The discovery opens the way for brain-like computers that can perform tasks effectively and energy efficiently.
SourceUniversity of Gothenburg·JournalNature Materials·TypeSurvey·DateNov 29, 2021
Researchers discovered the retrosplenial cortex as the site of value decision-making in the brain. Persistency allows value signals to be effectively represented across different brain areas, especially the RSC. Artificial intelligence networks mimicking mouse decisions showed remarkably similar results.
SourceUniversity of California - San Diego·JournalNeuron·TypeExperimental study·DateNov 23, 2021
A KAUST team developed an improved method for detecting malicious intrusions using deep learning, achieving accuracy rates of up to 99% in simulations of different kinds of attacks. This stacked deep learning approach promises an effective defense against cyberattacks and could prevent outages in critical infrastructure.
SourceKing Abdullah University of Science & Technology (KAUST)·JournalCluster Computing·TypeComputational simulation/modeling·DateNov 23, 2021
A study has developed a method using dark-field microscopy and deep learning algorithms to identify microplastics in human cells, achieving an accuracy of 93% for 1-micron polystyrene particles. The technique has the potential to screen microplastics in various samples, reducing time-consuming data acquisition and processing steps.
SourceKazan Federal University·JournalAnalytical and Bioanalytical Chemistry·TypeExperimental study·DateNov 22, 2021
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.
A new study by Ritsumeikan University reveals that whole-body dynamic balance training increases brain connectivity and improves motor learning. The research found significant changes in brain activity associated with offline learning, opening up new avenues for studying neural networks during natural tasks.
SourceRitsumeikan University·JournalMedicine & Science in Sports & Exercise·TypeExperimental study·DateNov 22, 2021
A new AI model has been developed to classify colorectal polyps, demonstrating accuracy and sensitivity at a level comparable to practicing pathologists. The model was tested in a clinical trial involving 15 pathologists, showing significant improvements in accuracy compared to traditional methods.
SourceDartmouth Health·JournalJAMA Network Open·TypeComputational simulation/modeling·DateNov 18, 2021
Researchers found that re-identifying individuals from genomic data using public face images is harder than previously thought, with success rates well below idealized settings. They developed a method to alter social media photos and reduce the risk of privacy breaches.
SourceWashington University in St. Louis·JournalScience Advances·TypeComputational simulation/modeling·DateNov 18, 2021
Researchers at Japan Advanced Institute of Science and Technology create method to estimate five-room acoustic parameters and speech transmission index using a short conversation, with potential applications in monitoring auditoriums during concerts and saving lives through smart speakers
SourceJapan Advanced Institute of Science and Technology·JournalApplied Acoustics·DateNov 18, 2021
Celestron NexStar 8SE Computerized Telescope
Celestron NexStar 8SE Computerized Telescope combines portable Schmidt-Cassegrain optics with GoTo pointing for outreach nights and field campaigns.
The research team developed a technology for remotely assessing the condition of a building during an earthquake based on the readings from the building's seismometer. The new method uses CNN machine learning to quickly assess damage levels and determine if a building can continue to be used.
SourceToyohashi University of Technology (TUT)·JournalSensors·TypeComputational simulation/modeling·DateNov 17, 2021
A study involving Drosophila found that a constant and precisely regulated energy supply is essential for nerve development, particularly during the degradation of nerve connections. Malnutrition was shown to intensify defects in this process.
SourceUniversity of Münster·JournalCell Reports·TypeExperimental study·DateNov 16, 2021
Convolutional neural networks trained to identify abnormalities on upper extremity radiographs are susceptible to a ubiquitous confounding image feature: radiograph labels. Covering these labels increases accuracy, while using them alone leads to decreased performance.
SourceAmerican Roentgen Ray Society·JournalAmerican Journal of Roentgenology·TypeObservational study·DateNov 15, 2021
Research suggests that larger bee colonies with comfortable food stores are less willing to take risks, while smaller colonies with limited resources are more likely to ignore warning signals. This study provides insights into the complex communication system of bees and its implications for understanding biological collectives.
SourceUniversity of California - San Diego·JournalJournal of The Royal Society Interface·TypeExperimental study·DateNov 9, 2021
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.
A study at the University of Turku found that brain function regulating satiety and appetite is altered before obesity develops, with family background risk factors contributing to these changes. The findings suggest the brain and central nervous system are key targets for treating obesity.
SourceUniversity of Turku·JournalInternational Journal of Obesity·TypeImaging analysis·DateNov 3, 2021
Researchers at the University of Waterloo have created a deep neural network that detects disease biomarkers with high accuracy, achieving 98 per cent detection of peptide features. This breakthrough could enable earlier and more accurate disease detection through tissue sample analysis.
SourceUniversity of Waterloo·JournalScientific Reports·DateOct 28, 2021
Scientists at Gladstone Institutes discovered that non-convulsive epileptic activity drives chronic brain inflammation in Alzheimer's models, which can be reversed by eliminating protein tau or using the anti-epileptic drug levetiracetam. This link between brain networks and immune cells may hold promising treatments for Alzheimer's di...
Researchers have trained a neural network to detect anomalies in medical images, adapting it to the nature of medical imaging and achieving better results. The new method uses weakly supervised training and can spot small-scale anomalies, accelerating the work of histopathologists and radiologists.
SourceSkolkovo Institute of Science and Technology (Skoltech)·JournalIEEE Access·DateOct 21, 2021