Articles tagged with Learning Processes
Researchers developed two models to evaluate personal learning performance, combining biometric responses with demographic data. The simplified forecast model showed higher accuracy and reduced overfitting than the full forecast model.
A novel prescription wristwatch uses photoplethysmography to detect atrial fibrillation with high accuracy, even in participants with darker skin tones. The Verily Study Watch bridges the gap between long-term monitoring and consumer devices, enabling clinicians to effectively use wearable data for Afib management.
Researchers found that phonetic encoding in babies emerged gradually over the first year of life, beginning with labial sounds and nasal sounds. Parents should speak to their babies using sing-song speech as soon as possible to help them learn language.
A new deep learning-based detection system has been developed by INU researchers to improve the detection capabilities of autonomous vehicles. The system, aided by IoT technology, generates bounding boxes and confidence scores for visible obstacles using point cloud data and RGB images as input.
A recent study published in Nature Communications has identified a key brain molecule responsible for triggering overconsumption of comfort foods after stressful events. The lateral hypothalamic proenkephalin neuron plays a crucial role in driving threat-induced eating associated with negative emotional states.
A new study published in the Journal of Vocational Rehabilitation found that Project SEARCH graduates with intellectual and developmental disabilities achieved high job retention rates (>77%) and overall satisfaction. However, challenges persist, including unmet ongoing support needs and limited follow-up services after graduation.
The study reveals that peer reaction video feedback provides valuable insights into teaching strengths and weaknesses, enhancing reflection skills. It also enables concrete feedback on performance and reduces discomfort in delivering negative feedback.
Researchers found that brittle stars, brainless marine creatures, can associate darkness with food and react accordingly, demonstrating classical conditioning. They retained this association even after a break from training, suggesting potential learning capabilities in these animals.
Researchers developed three diffractive deep neural networks using orbital angular momentum to recognize objects in images, achieving accuracy comparable to wavelength and polarization-based models. The technology has potential for real-time processing applications like image recognition and data-intensive tasks.
A novel contamination-detection method enables faster and safer T-cell therapy production, reducing the risk for patients and speeding up treatment. The method uses cutting-edge technology to identify harmful microorganisms within 24 hours.
A self-updating chatbot uses deep learning to detect new intents, slots, and values with reduced human input. The chatbot's ontology is updated accordingly, allowing it to handle a wide range of user requests and provide accurate responses.
A team of neuroscientists discovered that people who are blind can recognize basic faces using the fusiform face area, a region crucial for face processing in sighted individuals. The researchers used a device that translates images into sounds to study brain activity.
A team of researchers, including York University, used a mouse model to test how the brain learns new sensory input patterns. They found that the brain's response to image patterns that violate expectations evolves differently over time, suggesting a distinct role in sensory learning.
Researchers found that learning occurs through continuous formation of new connections between specific engram cells in different regions of the brain. This process allows us to form and store memories, with changes in synaptic wiring connectivity between these cells being a key mechanism for memory storage.
Researchers argue that the brain does not create new functions in previously unrelated areas but instead utilizes existing latent capacities. They provide alternative explanations for observed changes in brain activity following injury or deficit.
Researchers argue for a 'human-centered AI' approach to co-creativity, balancing automation with human control. They emphasize the need for interdisciplinary research on creativity, ethics, and intellectual property rights in human-AI collaboration.
Researchers discovered that cerebellar nuclei make a surprising contribution to associative learning by strengthening connections with mossy fibers. Optogenetic experiments also showed that the nuclei can support well-timed learning. The study's findings have implications for understanding cerebellum function and potential treatments f...
A review of 23 years of neuroimaging research finds that screen time affects the pre-frontal cortex and other brain regions involved in executive functions, memory, and processing. Digital experiences may shape children's brains and influence cognitive development, with both positive and negative impacts.
Researchers developed a deep learning model that can identify previously unknown quasicrystalline phases in multiphase crystalline samples. The model achieved a prediction accuracy of over 92% and successfully detected an unknown phase in Al-Si-Ru alloys.
Researchers found that tumor-resident T-cell receptor sequences showed high complementarity with the cancer testis antigen DDX53, suggesting an immune response that selects for DDX53-negative cells. This association was correlated with worse disease-free survival rates, highlighting a potential early esophageal cancer antigen.
Elea Abisamra's STEM writing program at Virginia Tech has been recognized by the journal Cell for its innovative approach to teaching science through storytelling. The program has already helped 95 kids publish books with over 150 tutors as editors, and plans to expand globally.
A new deep-learning platform, EUGENe, simplifies data analysis for genomics researchers. The software can be adapted to various projects and reproduces results from existing studies.
A study by Dr Lixin Ren found that extracurricular activities have a limited impact on math skills in preschool children, with effects dependent on behavioral regulation and approaches to learning. For children with poor self-regulation skills, structured activities can improve early math skills.
Researchers developed a deep convolutional neural network to pinpoint cardiac catheter tip locations in photoacoustic images, achieving high precision and recall. The approach has the potential to replace fluoroscopy during cardiac interventions, leading to safer procedures.
The UTSA MATRIX AI Consortium has received a $2 million grant to create new AI models that rapidly learn, adapt, and operate in uncertain conditions. The team aims to bridge the gap between human brain processing efficiency and current AI limitations, enabling more efficient and adaptive AI systems.
The C-Path Neuroscience Annual Workshop brought together stakeholders to chart a transformative course for neurology research and drug development, focusing on chronic progressive diseases such as Alzheimer's and Parkinson's. Key highlights included recommendations for innovative therapies and tools to address complex disorders.
Scientists have developed an AI system that accurately maps the surface area and outline of giant icebergs in one-hundredth of a second. This technology surpasses manual interpretation methods, which can take several minutes to delineate an iceberg's outline, and offers insights into their impact on the polar environment.
A new study finds that individuals with PTSD symptoms exhibit a blunted responsiveness to cortisol, leading to impaired fear extinction and other biological alterations. Researchers used a genetically selected rat model to demonstrate the causal link between low glucocorticoid levels and PTSD vulnerability.
The Southwest-Midwest Pediatric Device Innovation Consortium has supported over 200 pediatric device innovators and companies, developing several devices in the past five years. The consortium's portfolio includes real-world evidence research projects using digital tools for collecting and analyzing patient data.
The USPSTF concludes that routine screening for dental caries or periodontal-related disease in adults lacks sufficient evidence, potentially leading to unnecessary procedures. Preventive interventions are also not recommended, as the current evidence is insufficient to assess their benefits and harms.
Researchers have developed AI tools that can effectively detect heart valve disease and predict cardiovascular risk using digital stethoscopes. A study found that AI-powered digital stethoscopes predicted nearly 90% of valve disease diagnoses, offering a promising tool for transforming CVD care.
Researchers are combining biology, physics, computer science, and engineering to design electric circuits that mimic the brain's adaptive behavior. The goal is to create a more efficient AI application that can learn from history and adapt without significant energy consumption.
NYU Tandon's new 3D video technology is being used to enhance dance education by allowing students to learn techniques and choreography from various angles and distances. The project aims to make Point-Cloud Video suitable for streaming on standard devices, reducing bandwidth consumption and increasing accessibility.
Researchers found self-supervised models generate activity patterns similar to mammalian brains, suggesting an organizing principle. The models learn representations of the physical world to make accurate predictions, potentially unlocking human-labeled data limitations.
A new method called TWC-Swin effectively restores holographic images even under low spatial coherence and arbitrary turbulence, surpassing traditional convolutional network-based methods. The study demonstrates strong generalization capabilities, extending its application to unseen scenes.
Researchers from the UMA developed an open-source platform called Open Twins to create more accessible and versatile digital twins. This platform enables the simulation of real-world assets based on virtual replicas, predicting future behaviors and detecting anomalies, leading to more efficient companies that make data-driven decisions.
Researchers used computational models to analyze thousands of hours of transcribed audio recordings of children and adults interacting. The findings suggest that adults' ability to make context-based interpretations provides crucial feedback for babies acquiring language. These interpretations are critical for understanding what small ...
Researchers at New York University developed a novel learning procedure called Meta-learning for Compositionality (MLC) that enables neural networks to make compositional generalizations. MLC outperforms existing approaches and is on par with, and in some cases better than, human performance.
New research from Radboud University found that students' ICT skills have a significant impact on their math performance, particularly in countries with robust ICT environments. The study suggests that improving ICT infrastructure can reduce educational inequality between countries.
Researchers Joel Mejia and M. Sidury Christiansen are developing a handbook of recommended pedagogical approaches to address exclusionary language in engineering classes. They aim to improve the sense of belonging among multilingual students pursuing STEM careers by guiding faculty on strategies for changing biased language practices.
The project, funded by a $927,203 grant, uses virtual reality and machine learning to identify misconceptions in quantum information science. UCF will develop desktop and smartphone versions of QubitVR for broader impacts, aiming to empower students and professionals to harness the power of quantum computing.
A new study by Carnegie Mellon University reveals that individuals with strong communication skills and expertise are more likely to be chosen as central members of a network. As a result, teams that choose their own central member perform better than those with randomly assigned members. The study highlights the critical role of commu...
Researchers developed a novel photonic processor with adaptive neural connectivity, allowing for the creation of complex artificial neural networks. The system utilizes waveguide-coupled phase-change material to create almost 8,400 optical neurons that can adapt their connections through synaptic and structural plasticity.
Researchers found that apoptotic cells induce apoptosis in neighboring hair follicle cells during the regression cycle. The study proposes a mathematical model of the hair follicle regression cycle, which suggests that the dermal papilla plays an essential role in initiating apoptosis.
A groundbreaking study uses a $3.27 million grant to investigate whether the language of instruction impacts syntax learning in bilingual children with DLD. The research aims to determine how language proficiency in English or Spanish affects language learning.
Researchers from KTU and partners propose a gamified learning approach to acquire knowledge in programming. The method creates a personalised learning process using AI or tutors to monitor progress and adapt goals accordingly.
Researchers found that working memory was the most significant predictor of writing ability among English learner students. Cognitive functions such as phonological awareness and oral language development were also important, but only working memory consistently predicted higher scores in writing.
Researchers from GIST propose a novel approach to mitigate overfitting in pretrained models used for voice pathology detection, achieving 12.36% and 15.38% improvement in recall using contrastive learning.
A team of scientists and philosophers identifies a new law of nature that governs the evolution of complex systems, including plants, animals, stars, and minerals. The law states that complex systems evolve to states of greater patterning, diversity, and complexity, regardless of whether they are living or nonliving.
A team of neuroscientists has identified specific neurons in the auditory cortex that only respond to sounds that violate expectations, sending a message that a mistake has been made. These 'prediction-error neurons' may play a vital role in learning how to speak or play musical instruments.
The Army Research Laboratory has chosen Texas A&M University for its High-Throughput Materials Discovery for Extreme Environments Center (HTMDEC). The center aims to develop novel materials for extreme conditions, reducing experimentation costs and duration. By leveraging machine learning, physics-based simulations, and collaboration, ...
Researchers developed a novel approach to predict therapeutic targets for aging and age-related diseases. They trained a domain-specific BioGPT model on biomedical literature, which improved its performance in identifying prospective targets.
New research from Cold Spring Harbor Laboratory explores how adult brains adapt through critical periods of learning, such as caring for young. MECP2 dysfunction causes neurodevelopmental disorder Rett syndrome, but the study finds that brain circuits can be rapidly rewired in adults.
Contextual cueing enhances visual search capabilities by facilitating more effective scanning strategies. The brain learns to store relative positions of target objects in relation to distractors, leading to faster reaction times.
A new study published in JAMA Network Open suggests that reattribution of pain to mind or brain processes can lead to significant reductions in chronic back pain intensity. Participants who received pain reprocessing therapy reported being pain-free or nearly so after treatment, compared to those receiving placebo controls.
Researchers have created the first-ever map of a single animal's early visual system, reconstructing it from the eyes to neurons in a tiny parasitic wasp. The study reveals complex behaviors such as flight in an insect with just 8,600 cells compared to the human brain's 171 billion.
Researchers found that brain circuits in 'deep-blind' zebrafish are fully functional and can drive normal visual behavior through direct stimulation. This study challenges the long-held assumption that neural development depends on visual experience.
A longitudinal study led by Professor Markus Paulus found that babies' ability to imitate is influenced by their caregivers' sensitivity and imitation. As a result, children learn various skills through imitation, including language acquisition and cultural gestures.
Insilico Medicine has identified 9 potential dual-purpose targets against aging and 14 major age-related diseases using Microsoft BioGPT. The proposed genes include CCR5 and PTH, which have not been previously correlated to the aging process.
GlowTrack, a non-invasive movement tracking method using fluorescent dye markers, improves the capture of diverse movements in laboratories. This technique enables easier comparison of movement data between studies, increasing scientific discovery and advancing fields like biology, robotics, and medicine.