Research Radar
A unified intelligence feed of emerging AI, SaaS, and architectural models extracted directly from peer-reviewed scientific literature.
LLM-Based Test-Driven Interactive Code Generation: User Study and Empirical Evaluation
Enhancing Cyber-Resiliency of DER-Based Smart Grid: A Survey
Fluid Antenna System Liberating Multiuser MIMO for ISAC via Deep Reinforcement Learning
Multi-Static Target Detection and Power Allocation for Integrated Sensing and Communication in Cell-Free Massive MIMO
Using and Interpreting Fixed Effects Models
ABSTRACTFixed effects (FE) have emerged as a ubiquitous and powerful tool for eliminating unwanted variation in observational accounting studies. Unwanted variation is plentiful in accounting research because we often use rich data to test precise...
Changes in lean body mass with glucagon‐like peptide ‐1‐based therapies and mitigation strategies
Abstract Weight loss induced by glucagon‐like peptide‐1 receptor agonists (GLP‐1RAs) and dual glucagon‐like peptide‐1 receptor (GLP‐1R)/glucose‐dependent insulinotropic polypeptide receptor agonists is coming closer to the magnit...
Gaussian Process Regression Based Silver Price Forecasts
A significant number of market participants have placed a high level of importance on price estimates for the primary metal commodities for a considerable amount of time. To tackle the problem, we investigate the daily reported price of silver in ...
Canadian Network for Mood and Anxiety Treatments (CANMAT) 2023 Update on Clinical Guidelines for Management of Major Depressive Disorder in Adults: Réseau canadien pour les traitements de l'humeur et de l'anxiété (CANMAT) 2023 : Mise à jour des lignes directrices cliniques pour la prise en charge du trouble dépressif majeur chez les adultes
Background The Canadian Network for Mood and Anxiety Treatments (CANMAT) last published clinical guidelines for the management of major depressive disorder (MDD) in 2016. Owing to advances in the field, an update was needed to ...
Self-powered absorptive reconfigurable intelligent surfaces for securing satellite-terrestrial integrated networks
The Dark Energy Survey: Cosmology Results with ∼1500 New High-redshift Type Ia Supernovae Using the Full 5 yr Data Set
Abstract We present cosmological constraints from the sample of Type Ia supernovae (SNe Ia) discovered and measured during the full 5 yr of the Dark Energy Survey (DES) SN program. In contrast to most previous cosmological samples, ...
Lithium-ion battery recycling—a review of the material supply and policy infrastructure
Abstract The current change in battery technology followed by the almost immediate adoption of lithium as a key resource powering our energy needs in various applications is undeniable. Lithium-ion batteries (LIBs) are at the forefront o...
A smart mask for exhaled breath condensate harvesting and analysis
Recent respiratory outbreaks have garnered substantial attention, yet most respiratory monitoring remains confined to physical signals. Exhaled breath condensate (EBC) harbors rich molecular information that could unveil diverse insights into an i...
A Review of Vision-Based Pothole Detection Methods Using Computer Vision and Machine Learning
Potholes and other road surface damages pose significant risks to vehicles and traffic safety. The current methods of in situ visual inspection for potholes or cracks are inefficient, costly, and hazardous. Therefore, there is a pressing need to d...
Predictive analytics for market trends using AI: A study in consumer behavior
Predictive analytics, driven by artificial intelligence (AI), is revolutionizing the understanding and forecasting of market trends, particularly in the realm of consumer behavior. This study explores the application of AIpowered predictive analyt...
Neural general circulation models for weather and climate
AbstractGeneral circulation models (GCMs) are the foundation of weather and climate prediction1,2. GCMs are physics-based simulators that combine a numerical solver for large-scale dynamics with tuned representations for small-scale processes such...
Understanding Physics-Informed Neural Networks: Techniques, Applications, Trends, and Challenges
Physics-informed neural networks (PINNs) represent a significant advancement at the intersection of machine learning and physical sciences, offering a powerful framework for solving complex problems governed by physical laws. This survey provides ...
Self-Driving Laboratories for Chemistry and Materials Science
A comprehensive electron wavefunction analysis toolbox for chemists, Multiwfn
Analysis of electron wavefunction is a key component of quantum chemistry investigations and is indispensable for the practical research of many chemical problems. After more than ten years of active development, the wavefunction analysis program ...
Pore engineering of Porous Materials: Effects and Applications
AI-Driven Innovations in Building Energy Management Systems: A Review of Potential Applications and Energy Savings
Despite the tightening of energy performance standards for buildings in various countries and the increased use of efficient and renewable energy technologies, it is clear that the sector needs to change more rapidly to meet the Net Zero Emissions...
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