Results 171 to 180 of about 3,865,632 (281)

Potential cognitive and neural benefits of a computerised cognitive training programme based on Structure Learning in healthy adults: study protocol for a randomised controlled trial. [PDF]

Trials, 2023
Liu CL, Cheng X, Choo BL, Hong M, Teo JL, Koo WL, Tan JYJ, Ubrani MB, Suckling J, Gulyás B, Leong V, Kourtzi Z, Sahakian B, Robbins T, Chen AS.   +14 more
europepmc   +1 more source

Selective Benzene Capture by Metal‐Organic Frameworks

Advanced Functional Materials, EarlyView.
Metal‐organic frameworks (MOFs) hold significant potential for capturing benzene from air emissions and hydrocarbon mixtures in liquid phases. This capability stems from their precisely engineered structures, versatile chemistries, and diverse binding interactions.
Zongsu Han, Ankit Mondal, Jiatong Huo, Yihao Yang, Hong‐Cai Zhou   +4 more
wiley   +1 more source

Assessing Credibility in Bayesian Networks Structure Learning. [PDF]

Entropy (Basel)
Barth V, Serrão F, Maciel C.
europepmc   +1 more source

Simultaneous cluster structure learning and estimation of heterogeneous graphs for matrix-variate fMRI data. [PDF]

Biometrics, 2023
Liu D, Zhao C, He Y, Liu L, Guo Y, Zhang X.   +5 more
europepmc   +1 more source

Electroactive Metal–Organic Frameworks for Electrocatalysis

Advanced Functional Materials, EarlyView.
Electrocatalysis is crucial in sustainable energy conversion as it enables efficient chemical transformations. The review discusses how metal–organic frameworks can revolutionize this field by offering tailorable structures and active site tunability, enabling efficient and selective electrocatalytic processes.
Irena Senkovska, Yutong Luo, Ruyan Zhao, Jianjun Zhang, Mingchao Wang, Xinliang Feng, Eike Brunner, Stefan Kaskel   +7 more
wiley   +1 more source

Correction: A guide to bayesian networks software for structure and parameter learning, with a focus on causal discovery tools

Frontiers in Systems Biology
Francesco Canonaco, Francesco Canonaco, Joverlyn Gaudillo, Nicole Astrologo, Fabio Stella, Enzo Acerbi   +5 more
doaj   +1 more source

Contribution of Structure Learning Algorithms in Social Epidemiology: Application to Real-World Data. [PDF]

Int J Environ Res Public Health
Colineaux H, Lepage B, Chauvin P, Dimeglio C, Delpierre C, Lefèvre T.   +5 more
europepmc   +1 more source

Treatment of missing data in Bayesian network structure learning: an application to linked biomedical and social survey data. [PDF]

BMC Med Res Methodol, 2022
Ke X, Keenan K, Smith VA.
europepmc   +1 more source

Smart, Bio‐Inspired Polymers and Bio‐Based Molecules Modified by Zwitterionic Motifs to Design Next‐Generation Materials for Medical Applications

Advanced Functional Materials, EarlyView.
Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz, Jonas De Breuck, Sahar Salehi, Meike N. Leiske   +3 more
wiley   +1 more source

Classroom network structure learning engagement and parallel temporal attention LSTM based knowledge tracing. [PDF]

PLoS One
Shou Z, Li Y, Li D, Mo J, Zhang H.
europepmc   +1 more source