Results 181 to 190 of about 354,068 (263)

A Generational Approach to Neurology Education: Engaging Generation Z Learners. [PDF]

Neurol Educ
Mustafa R.
europepmc   +1 more source

Distinct Microstructural Characteristic Lengths Defining Notch Fatigue Crack Initiation and Propagation, and Defect Tolerance in Advanced Steels

Advanced Engineering Materials, EarlyView.
Schematic representation of modes of microcrack nucleation, growth and temporary arrestment at different boundaries, with the criteria for crack propagation in three scenarios: (1) large notch, (2) defect/small sharp notch, and (3) long crack. This work revisits and integrates results on the fatigue behavior of advanced bainitic steels (in particular ...
Lucia Morales‐Rivas
wiley   +1 more source

A cross-cultural examination of ethical reasoning in legal education: the interplay of critical thinking, case analysis skills, and professional identity formation. [PDF]

Front Psychol
Yuan X.
europepmc   +1 more source

Superlubricity and Corrosion Inhibition Properties of Solvate Ionic Liquids in Hybrid Carbon Fiber Reinforced Plastic–Steel Interfaces

Advanced Engineering Materials, EarlyView.
Solvate ionic liquids lubrication reduced the coefficient of friction by ∼60% compared to dry sliding, reaching steady‐state values as low as 0.04–0.05. Corrosion weight‐loss measurements in 1 M HCl further demonstrated significant inhibition behavior, with only 100 ppm of [Li(G3)][TFSI] (∼68.5 μL/L) reducing corrosion‐product weight loss by 63 ...
Sameh Dabees, Timothy Harte, Bhagya Dharmasiri, Y. Athulya Wickramasingha, David J. Hayne, Daniel J. Eyckens, Luke C. Henderson   +6 more
wiley   +1 more source

Safeguarding traditional Chinese medicine intangible cultural heritage and enabling its potential public health reuse: a theory-informed qualitative study in Jiangsu, China. [PDF]

Front Public Health
Li J, Dong S, Liu H, Shen J.
europepmc   +1 more source

Influence of TiC and TiN Ceramic Reinforcements on the Microstructure, Thermal Expansion Behavior, and Tensile Properties of Invar 36 Manufactured by Laser Powder Bed Fusion

Advanced Engineering Materials, EarlyView.
This study examines Invar composites reinforced with titanium carbide (TiC) and titanium nitride (TiN) using laser powder bed fusion (LPBF). It presents the influence of reinforcements on microstructure, tensile properties, and thermal expansion. Results show that TiC effectively strengthens Invar while maintaining low thermal expansion, whereas TiN ...
Ayodeji Nathaniel Oyedeji, Natasha Sacks, Johannes Pötschke, Björn Matthey   +3 more
wiley   +1 more source

Student satisfaction-oriented physical education teacher education curriculum: A framework for evaluating implementation effectiveness and optimizing quality. [PDF]

PLoS One
Liu T, Ren Y.
europepmc   +1 more source

3D‐Printed Titanium Gyroid Scaffold Structure Integrated With Tough Hybrid Materials for Cartilage Replacement

Advanced Engineering Materials, EarlyView.
This study proposes a potential device design for joint cartilage replacement. Silica‐polytetrahydrofuran (SiO2‐PolyTHF) hybrids with customizable mechanical properties were developed to mimic the characteristics of a natural meniscus. These were synthesized through a two‐pot sol–gel hybrid process.
Yu‐Chien Lin, Gloria R. Young, Francesca Tallia, Reece N. Oosterbeek, Shaaz Ghouse, Edward Spiers, Nupur Kohli, Tom Briggs, Marc Masen, Siwei Li, Ren‐Jei Chung, Jonathan R. T. Jeffers, Julian R. Jones   +12 more
wiley   +1 more source

Associations of Perceived Classical Chinese Text Reading Ability with Confucian Virtue Cognition and Practice Among Chinese Adolescents: The Indirect Role of Internalization Experience. [PDF]

Behav Sci (Basel)
Shen L, Wu B, Yuan B.
europepmc   +1 more source

A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

Advanced Engineering Materials, EarlyView.
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin, Marta Campolucci, Nicolas de Andrade Ishiki, Nathan Mirgot, Nadir Zhamantay, Frédéric Kanoufi, Jennifer Peron, Jean Charlety, Emiliano Fonda, Valérie Briois, Marco Faustini, Maria‐Letizia De Marco, Christine Goyhenex, Ovidiu Ersen, Hervé Bulou   +14 more
wiley   +1 more source