Results 11 to 20 of about 19,771 (142)

Computational markers show specific deficits for dyslexia and ADHD in complex learning settings [PDF]

npj Science of Learning
The current study examined how individuals with neurodevelopmental disorders navigate the complexities of learning within multidimensional environments marked by uncertain dimension values and without explicit guidance.
Yafit Gabay, Lana Jacob, Atil Mansour, Uri Hertz   +3 more
doaj   +2 more sources

AI and big data personalized training protocol for Chinese youth basketball [PDF]

Scientific Reports
Youth basketball talent development in China faces multiple challenges—homogeneous training methods, insufficient attention to individual differences, and a lack of systematic, evidence-based decision-making.
Anqi Wu, Aowei Zhang, Chao Zhou
doaj   +2 more sources

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

A Global Prospective Harmonization Framework for Suicidality, Anhedonia, and Obsessive‐Compulsive Symptoms in Psychiatric Genetic Studies: A Cross‐Continental Study Within the Ancestral Population Network

American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, EarlyView.
ABSTRACT This study aims to prospectively collect harmonized, quantitative, and dimensional psychiatric phenotypes (suicidality, anhedonia, and obsessive‐compulsive symptoms) and information on discrimination, stigma, and unfair treatment in up to 27,500 individuals across diverse ancestries and clinical populations for genetic analysis within the NIMH
Ana M. Diaz‐Zuluaga, Jacey L. Anderberg, Ana M. Ramirez‐Diaz, Andrea Horvath Marques, Catherine E. Rast, Daniel Bustamante, Deborah Jonker, Johanna Valencia‐Echeverry, Joseph Kyebuzibwa, Josselyn S. Muñoz, Kristien van der Walt, Mauricio Castaño Ramirez, Olivia Wootton, Renee M. Frederick, Rocky E. Stroud II, Ruben Gur, Sang Jin Rhee, Shaili C. Jha, Stella Gichuru, Susan Service, Victor I. Reus, Akena Dickens, Carlos Lopez‐Jaramillo, Carrie E. Bearden, Dan J. Stein, Ezra S. Susser, James J. Crowley, Jonathan Flint, Kenneth S. Kendler, Lukoye Atwoli, Michele T. Pato, Nelson B. Freimer, Roel A. Ophoff, Yong Min Ahn, Loes Olde Loohuis, Eric A. Storch, Bizu Gelaye   +36 more
wiley   +1 more source

Dynamic Spillovers Between FinTech, Blockchain, and Green Finance: A Quantile Connectedness Approach

Business Strategy and the Environment, EarlyView.
ABSTRACT This paper explores how financial innovation and environmental sustainability intersect by analyzing spillovers between FinTech, blockchain energy use, and green finance. Using a Quantile Vector Autoregression (QVAR) framework, we examine weekly data from 2018 to 2024 across 11 digital, environmental, and macro‐financial indices.
Mehmet Sahiner, Sisi Sung, James Devlin
wiley   +1 more source

Rolling optimization method of virtual power plant demand response based on Bayesian Stackelberg game

Energy Informatics
To optimize the interaction effect between internal units and demand response of virtual power plants and enhance their transaction profit, a study on the the rolling optimization method of demand response for virtual power plants based on Bayesian ...
Binxi Huang
doaj   +1 more source

Near-Optimal and Robust Mechanism Design for Covering Problems with Correlated Players [PDF]

, 2016
We consider the problem of designing incentive-compatible, ex-post individually rational (IR) mechanisms for covering problems in the Bayesian setting, where players' types are drawn from an underlying distribution and may be correlated, and the goal is ...
Minooei, Hadi, Swamy, Chaitanya
core  

Rockburst prediction based on data preprocessing and hyperband‐RNN‐DNN

Deep Underground Science and Engineering, EarlyView.
A data preprocessing workflow is proposed to address challenges in rockburst data analysis. Coupled algorithms preprocess the data set, and hyperband optimization is used to enhance RNN performance. Results show that preprocessing improves accuracy, while dense layers enhance model stability and prediction performance.
Yong Fan, Chenxi Yin, Guangdong Yang, Shengyong Ding, Bin Tian   +4 more
wiley   +1 more source

The Role of Artificial Intelligence in Modern Allergology: A Review of Applications in Diagnosis, Prediction, and Management

JEADV Clinical Practice, EarlyView.
ABSTRACT Artificial Intelligence is rapidly transforming allergology by enhancing diagnosis, risk prediction, automation, patient communication, education, and therapy development. Machine learning approaches, including convolutional neural networks, recurrent architectures, and transformer‐based models, enable analysis of complex datasets from ...
Sebastian Seurig, Stephan Traidl, Sonja Mathes   +2 more
wiley   +1 more source

Catchment conversion to agriculture alters freshwater macroinvertebrate community responses to flow disturbance: results from a replicated in‐stream experiment

Oikos, EarlyView.
Anthropogenic stressors often co‐occur in ecosystems, but their combined impacts are rarely assessed using field experiments. Press disturbances particularly can reshape community dynamics, altering their capacity to withstand or recover from acute pulse disturbances by modifying response diversity.
Bridget E. White, Anne Watson, Sean T. Atkinson, Belinda J. Robson, Russell G. Death, Mark J. Hovenden, Leon A. Barmuta   +6 more
wiley   +1 more source