Results 111 to 120 of about 1,027,169 (250)
Hybrid symbolic‐numeric algorithms for computational convex analysis [PDF]
, 2007 Yves Lucet
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Micromachined Double‐Membrane Mechanically Tunable Metamaterial for Thermal Infrared Filtering
Advanced Photonics Research, EarlyView.Herein, a mechanically tunable double‐layer plasmonic metamaterial leveraging the extraordinary optical transmission effect observed in subwavelength arrays of openings within thin metal layers is presented. The concept is experimentally validated by integrating the proposed metamaterial structure into an electrostatic parallel‐plate actuator to create
Oleg Bannik +7 more
wiley +1 more source
Improvement of Jensen, Jensen-Steffensen's, and Jensen's functionals related inequalities for various types of convexity [PDF]
arXivIn this paper we deal with improvement of Jensen, Jensen-Steffensen's and Jensen's functionals related inequalities for uniformly convex, phi-convex and superquadratic functions.
arxiv
Complexity Analysis for Certain Convex Programming Problems
, 1999 Marie-Cécile Darracq
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Advanced Robotics Research, EarlyView.CubiX, a wire‐driven robot, extends beyond physical limitations by skillfully utilizing the environment. It connects to objects via wires deployed by drones, enabling movement, object manipulation, and task execution. By integrating with tools or robots, CubiX gains new capabilities like walking and heavy lifting, demonstrating functional exibility and
Shintaro Inoue +5 more
wiley +1 more source
An Analysis of Elusive Relationships in Floating Zone Growth Using Data Mining Techniques
Advanced Theory and Simulations, EarlyView.Ultra‐pure silicon single‐crystals can be grown by the Floating Zone (FZ) method. This study investigates intricate relationships between process stability measures and multiple growth parameters by applying data mining techniques on FZ simulations. Regression Trees identified multivariate relationships that help explaining complex interactions between
Lucas Vieira +3 more
wiley +1 more source
Advanced Theory and Simulations, EarlyView.Data is generated from finite element simulations and an encoding using a Moore domain. The data is then used to train a meta‐model to predict the soft unit's deformation state depending on its chamber shape and properties as well as the surrounding environment.
Philip Frederik Ligthart +1 more
wiley +1 more source
Crystal Structure Prediction of Cs–Te with Supervised Machine Learning
Advanced Theory and Simulations, EarlyView.High‐throughput density functional theory calculations combined with machine learning models are employed to predict stable Cs– Te binary crystals. By systematically evaluating various structural descriptors and learning algorithms, the superiority of models based on atomic coordination environments is revealed.
Holger‐Dietrich Saßnick +1 more
wiley +1 more source
SyMO: A Hybrid Approach for Multi‐Objective Optimization of Crystal Growth Processes
Advanced Theory and Simulations, EarlyView.The hybrid SyMO (Symbolic regression Multi‐objective Optimization) framework combines Computational Fluid Dynamics (CFD), machine learning, and mathematical optimization techniques to investigate the effects of various process parameters, furnace geometries, and radiation shield material properties on key crystal quality metrics in Czochralski silicon (
Milena Petkovic, Natasha Dropka
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Structural Insights into an Antiparallel Chair‐Type G‐Quadruplex From the Intron of NOP56 Oncogene
Advanced Science, EarlyView.This study first reports that the intron 1 of NOP56 oncogene forms an antiparallel chair‐type G4 structure composed of two G‐tetrads and one C∙G∙C∙G tetrad. NOP56 gene transcription can be inhibited by PDS that binds and stabilizes NOP56‐G4. Solution NMR structures of the free NOP56‐G4 and NOP56‐G4‐PDS complex provide valuable insights into G4 ...
Zhenzhen Yan +11 more
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