Prevention of COVID-19 pandemic through technological innovation: ensuring global innovative capability, absorptive capacity, and adaptive healthcare competency. [PDF]
Anser MK +7 more
europepmc +1 more source
A Dislocation Perspective on Strength and Toughness in Ceramics
Dislocations in ceramics enjoy a long but yet under‐appreciated history. The three research waves for dislocations in ceramics highlight the topic evolution over the last 90 years. This review focuses on the impact of dislocation on strength and toughness in ceramics.
Xufei Fang
wiley +1 more source
Advancing sustainable nursing leadership: the interplay of green absorptive capacity, intellectual capital, and knowledge management among nursing managers. [PDF]
Mohamed HS +6 more
europepmc +1 more source
Estimating a panel MSK dataset for comparative analyses of national absorptive capacity systems, economic growth, and development in low and middle income countries. [PDF]
Khan MS.
europepmc +1 more source
A combined experimental–computational framework identifies energy‐dependent laser absorptivity for NiTi in laser powder‐bed fusion, applicable to conduction and transition modes. Single‐track experiments and thermofluid smoothed particle hydrodynamics simulations are coupled through inverse analysis of melt pool geometry.
Mohamadreza Afrasiabi +3 more
wiley +1 more source
Retraction: Impact of abusive supervision on psychological engagement and absorptive capacity among students: mediating role of knowledge hiding. [PDF]
Frontiers Editorial Office.
europepmc +1 more source
This work shows that the mechanical performance of multimaterial digital light processing (DLP) printed thermoset composites is governed by resin compatibility and interfacial design rather than spatial patterning alone. Brittle and ductile resin combinations produced premature interfacial failure, while graded interfaces and mechanically compatible ...
Ahmed M. H. Ibrahim +3 more
wiley +1 more source
The Interactions of Absorptive Capacity, Buffer Inventory, and Toxic Emissions on Firm Value. [PDF]
Yiu LMD, Wu KYK.
europepmc +1 more source
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source

