Results 91 to 100 of about 135,232 (227)

Improved predictive formulae for wave overtopping at sloped breakwaters using interpretable machine learning models. [PDF]

PLoS One
Habib MA, Abolfathi S, O'Sullivan JJ, Salauddin M.   +3 more
europepmc   +1 more source

Artificial Intelligence‐Driven Development in Rechargeable Battery Materials: Progress, Challenges, and Future Perspectives

Advanced Functional Materials, EarlyView.
AI is transforming the research paradigm of battery materials and reshaping the entire landscape of battery technology. This comprehensive review summarizes the cutting‐edge applications of AI in the advancement of battery materials, underscores the critical challenges faced in harnessing the full potential of AI, and proposes strategic guidance for ...
Qingyun Hu, Junyuan Lu, Jian Hui, Ziyuan Rao, Yang Ren, Hong Wang   +5 more
wiley   +1 more source

PseudoknotVisualizer: Visualization of pseudoknots on three-dimensional RNA structures. [PDF]

PLoS Comput Biol
Otagaki T, Terai G, Asai K, Iwakiri J.
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

A design of multiple color image encryption scheme based on finite algebraic structures. [PDF]

Sci Rep
Qayyum T, Shah T, Khan I, Popa IL.
europepmc   +1 more source

Recycling of Thermoplastics with Machine Learning: A Review

Advanced Functional Materials, EarlyView.
This review shows how machine learning is revolutionizing mechanical, chemical, and biological pathways, overcoming traditional challenges and optimizing sorting, efficiency, and quality. It provides a detailed analysis of effective feature engineering strategies and establishes a forward‐looking research agenda for a truly circular thermoplastic ...
Rodrigo Q. Albuquerque, Florian Stephan, Annalena Pongratz, Christian Brütting, Katharina Krause, Holger Ruckdäschel   +5 more
wiley   +1 more source

Mini Review: Synergizing Driven Quantum Dynamics, AI, and Quantum Computing for Next-Gen Materials Science. [PDF]

J Phys Chem Lett
Akanbi OS, Shannon JP, Delhommelle J, Desgranges C.   +3 more
europepmc   +1 more source

Evaluating Online Tutorials for Data Structures and Algorithms Courses

, 2013
S. Hall, C. Shaffer, Eric Fouh, Mai Elshehaly, Daniel A. Breakiron   +4 more
semanticscholar   +1 more source

Design patterns for the data structures and algorithms course

Technical Symposium on Computer Science Education, 1999
B. R. Preiss
semanticscholar   +1 more source

The Synergy of Artificial Intelligence and 3D Bioprinting: Unlocking New Frontiers in Precision and Tissue Fabrication

Advanced Functional Materials, EarlyView.
Advances in integrating artificial intelligence into 3D bioprinting are systematically reviewed here. Machine learning, computer vision, robotics, natural language processing, and expert systems are examined for their roles in optimizing bioprinting parameters, real‐time monitoring, quality control, and predictive maintenance.
Joao Vitor Silva Robazzi, Irem Deniz Derman, Deepak Gupta, Logan Haugh, Yogendra Pratap Singh, Vaibhav Pal, Yasar Ozer Yilmaz, Suihong Liu, Andre Luis Dias, Rogerio Andrade Flauzino, Ibrahim Tarik Ozbolat   +10 more
wiley   +1 more source