Results 231 to 240 of about 1,420,126 (325)

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

A dual hesitant fuzzy entropy-TOPSIS framework for multi-criteria evaluation of medical E-learning systems. [PDF]

Sci Rep
Abughazalah N, Khan M.
europepmc   +1 more source

The Concept of STAD (Student Team Achievement Division) Cooperative Learning Model According to Robert E. Slavin

, 2020
Firdha Isnaini, Machful Indra Kurniawan
openalex   +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

Evaluating an Innovative Oncology Education Initiative: Integrating Genomics and Histopathology in a Virtual Laboratory e-Learning Resource to Enhance Learner Engagement. [PDF]

J Med Educ Curric Dev
Reed KR, Crawford OJ, West HD, Lewis J, Hackman M, de Almeida A, Hilbourne A, Short E, Patel S, Hart K, Hassoulas A.   +10 more
europepmc   +1 more source

Gestione dei corsi di lingua e-learning e m-learning

, 2018
Laura Pederzoli
openalex   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Opportunities and Threats of E-Learning in Nursing Education: An Overview of Reviews. [PDF]

J Caring Sci
Arian M, Oghazian MB, Mazlom SR, Zarghi N, Abdollahpour S.   +4 more
europepmc   +1 more source

A Literature Review of Student Performance Prediction in E-Learning Environment

, 2020
Ruth Chweya, Siti Mariyam Shamsuddin, Samuel-Soma M. Ajibade, Samuel Moveh   +3 more
openalex   +2 more sources

Region‐to‐Region Unidirectional Connection In Vitro Brain Model for Studying Directional Propagation of Neuropathologies

Advanced Functional Materials, EarlyView.
A unidirectional cerebral organoid–organoid neural circuit is established using a microfluidic platform, enabling controlled directional propagation of electrical signals, neuroinflammatory cues, and neurodegenerative disease–related proteins between spatially separated organoids.
Kyeong Seob Hwang, Hui‐Wen Liu, Hyogeun Shin, Hyun Wook Kang, Minjin Kang, Jongbaeg Kim, Il‐Joo Cho, Nakwon Choi, Seok Chung, Hong Nam Kim   +9 more
wiley   +1 more source