Results 151 to 160 of about 2,110 (192)

MOOC‐Empowered Blended Teaching Mode in Human Anatomy: A Structural Equation Modeling Analysis

Clinical Anatomy, EarlyView.
ABSTRACT Human anatomy, a cornerstone course in medical education, faces several challenges, such as teaching resource shortages, compressed class hours, and heavy student workloads. Traditional teaching models of anatomy often fall short in stimulating interest, promoting deep understanding, and enhancing learning engagement.
Mingxin Wen, Mengjie Wu, Haiwei Meng, Rui Song, Yanlai Hu   +4 more
wiley   +1 more source

Perceptual interventions ameliorate statistical discrimination in learning agents. [PDF]

Proc Natl Acad Sci U S A
Duéñez-Guzmán EA, Comanescu R, Mao Y, McKee KR, Coppin B, Sadedin S, Chiappa S, Vezhnevets AS, Bakker MA, Bachrach Y, Isaac W, Tuyls K, Leibo JZ.   +12 more
europepmc   +1 more source

Why Are Consumers Ambivalent About AI‐Generated Images? The Moderating Role of Commercial Versus Noncommercial Content Type

Journal of Consumer Behaviour, EarlyView.
ABSTRACT Grounded in ambivalence theories, this research examined factors shaping consumer ambivalence toward AI‐generated content and investigated differences between commercial and noncommercial contexts. As a preliminary study, sentiment analysis of Reddit data using a support vector machine (SVM) revealed that most consumer sentiment toward AI ...
Garim Lee, Jinsu Park, Hye‐Young Kim, Divya Manoj   +3 more
wiley   +1 more source

Cooperative behavior and affect heuristic. When the rationality of love matters. [PDF]

Front Sociol
Oliverio A.
europepmc   +1 more source

A Stacked Ensemble Multi‐Label Model for Predicting Co‐Occurring Microvascular and Macrovascular Complications in Type 2 Diabetes

Chronic Diseases and Translational Medicine, EarlyView.
Feature importance for predicting multiple diabetes complications based on a Stacking‐Classifier Chain model. Abstract Background Type 2 diabetes mellitus (T2DM) leads to severe microvascular and macrovascular complications. Traditional single‐label prediction models fail to capture their co‐occurring nature.
Maryam Zamani, Maryam Farhadian, Nasrin Piran, Shiva Borzouei   +3 more
wiley   +1 more source

Representation gap for transition factors from social sciences in energy and emissions modeling

Kunnas S, Trutnevyte E.
europepmc   +1 more source

How media competition fuels the spread of misinformation. [PDF]

Sci Adv
Amini A, Bayiz YE, Lee EJ, Somer-Topcu Z, Marculescu R, Topcu U.   +5 more
europepmc   +1 more source

The Future of Foundation Machine Learning Potentials and DFT in Homogeneous Catalysis: Competition or Synergy?

Chemistry – A European Journal, EarlyView.
Machine‐learning potentials are increasingly taking on the exploratory tasks of homogeneous catalysis, enabling rapid conformer sampling and reaction‐space mapping. However, when selectivity depends on subtle electronic effects, electronic‐structure methods remain essential.
Maxime Ferrer, Julen Munarriz, Thijs Stuyver, Ruben Laplaza   +3 more
wiley   +1 more source

Enhancing strategic decision-making in differential games through bifurcation prediction. [PDF]

Sci Rep
García Pérez J, Epureanu B.
europepmc   +1 more source

A hidden Markov model and reinforcement learning‐based strategy for fault‐tolerant control

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract This study introduces a data‐driven control strategy integrating hidden Markov models (HMM) and reinforcement learning (RL) to achieve resilient, fault‐tolerant operation against persistent disturbances in nonlinear chemical processes. Called hidden Markov model and reinforcement learning (HMMRL), this strategy is evaluated in two case studies
Tamera Leitao, Debaprasad Dutta, Simant R. Upreti   +2 more
wiley   +1 more source