Results 121 to 130 of about 1,699,128 (261)

Self-paced Multi-view Learning for CT-based severity assessment of COVID-19. [PDF]

Biomed Signal Process Control, 2023
Liu Y, Chen B, Zhang Z, Yu H, Ru S, Chen X, Lu G.   +6 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

scAWMV: an adaptively weighted multi-view learning framework for the integrative analysis of parallel scRNA-seq and scATAC-seq data. [PDF]

Bioinformatics, 2023
Zeng P, Ma Y, Lin Z.
europepmc   +1 more source

Patterning the Void: Combining L‐Systems with Archimedean Tessellations as a Perspective for Tissue Engineering Scaffolds

Advanced Functional Materials, EarlyView.
This study introduces a novel multi‐scale scaffold design using L‐fractals arranged in Archimedean tessellations for tissue regeneration. Despite similar porosity, tiles display vastly different tensile responses (1–100 MPa) and deformation modes. In vitro experiments with hMSCs show geometry‐dependent growth and activity. Over 55 000 tile combinations
Maria Kalogeropoulou, Kenny A. van Kampen, Pierpaolo Fucile, Carlos Mota, Lorenzo Moroni   +4 more
wiley   +1 more source

Human gut microbiome aging clocks based on taxonomic and functional signatures through multi-view learning. [PDF]

Gut Microbes, 2022
Chen Y, Wang H, Lu W, Wu T, Yuan W, Zhu J, Lee YK, Zhao J, Zhang H, Chen W.   +9 more
europepmc   +1 more source

Semantic consistency enhancement and contribution-driven network for partial multi-view incomplete multi-label classification

Journal of King Saud University: Computer and Information Sciences
In recent years, multi-view multi-label learning has garnered considerable attention due to its broad application prospects, such as bioinformatics and medical imaging.
Yishan Jiang, Lian Zhao, Zhixian Jiang, Yinghao Ye, Xiaohuan Lu   +4 more
doaj   +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

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

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

On multi-view feature learning

, 2012
ICML2012
openaire   +2 more sources