Results 151 to 160 of about 1,005,083 (338)
This review outlines how understanding bone's biology, hierarchical architecture, and mechanical anisotropy informs the design of lattice structures that replicate bone morphology and mechanical behavior. Additive manufacturing enables the fabrication of orthopedic implants that incorporate such structures using a range of engineering materials ...
Stylianos Kechagias +4 more
wiley +1 more source
Empirical research often requires a method how to convert a deterministic economic theory into an econometric model. A popular method is to add a random error term on the utility scale. This method, however, violates stochastic dominance.
Pavlo R. Blavatskyy
core
Lead‐free bismuth halide perovskite memristors exhibit stable low‐voltage resistive switching behavior. The conductance‐activated quasi‐linear memristor model quantitatively reproduces the experimental hysteresis, confirming ion migration‐driven filament dynamics.
So‐Yeon Kim +4 more
wiley +1 more source
Portfolio diversification based on stochastic dominance under incomplete probability information
Juuso Liesiö, Peng Xu, Timo Kuosmanen
semanticscholar +1 more source
Genetic modification and yield risk: A stochastic dominance analysis of corn in the USA. [PDF]
Nolan E, Santos P.
europepmc +1 more source
Beyond Optimal Forecasting [PDF]
forecasting,forecast loss functions,stochastic dominance.
Richard A. Ashley.
core
Recent Advances of Slip Sensors for Smart Robotics
This review summarizes recent progress in robotic slip sensors across mechanical, electrical, thermal, optical, magnetic, and acoustic mechanisms, offering a comprehensive reference for the selection of slip sensors in robotic applications. In addition, current challenges and emerging trends are identified to advance the development of robust, adaptive,
Xingyu Zhang +8 more
wiley +1 more source
Consistent Testing for Poverty Dominance [PDF]
poverty, stochastic dominance, random poverty line ...
Thuysbaert, Bram, Zitikis, Ricardas
core
Excitonic Landscapes in Monolayer Lateral Heterostructures Revealed by Unsupervised Machine Learning
Hyperspectral photoluminescence data from graded MoxW1 − xS2 alloys and monolayer MoS2–WS2 lateral heterostructures are analyzed using unsupervised machine learning. The combined use of PCA, t‐SNE, and DBSCAN uncovers distinct excitonic regions that trace how composition, strain, and defects modulate optical responses in these 2D materials.
Maninder Kaur +4 more
wiley +1 more source
Unobserved heterogeneity in auctions under restricted stochastic dominance
Yao Luo
semanticscholar +1 more source

