Results 121 to 130 of about 140,252 (207)

Machine learning‐driven advances in carbon‐based quantum dots: Opportunities accompanied by challenges

Responsive Materials, EarlyView.
Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen, Siwei Yang, Xiangqian Cui, Ziheng Liu, Hang Wang, Yongqiang Li, Peng He, Miao Wang, Guqiao Ding   +8 more
wiley   +1 more source

Reinforcement learning-driven dynamic optimization strategy for parametric design of 3D models. [PDF]

Sci Rep
Zhong G, Vijay VC.
europepmc   +1 more source

Digital Twin‐Based Optimization of Service Availability in LEO Mega Constellations Considering Handover Delays in Open RAN

International Journal of Satellite Communications and Networking, EarlyView.
ABSTRACT As non‐terrestrial networks (NTNs) become integral to future 6G systems, ensuring seamless connectivity and service continuity over low Earth orbit (LEO) satellite constellations is essential. This work investigates the impact of open radio access network (RAN) functional splits on handover performance in NTNs, focusing on minimizing service ...
Siva Satya Sri Ganesh Seeram, Luca Feltrin, Mustafa Ozger, Cicek Cavdar   +3 more
wiley   +1 more source

Commutative Algebra Modeling in Materials Science - A Case Study on Metal-Organic Frameworks (MOFs). [PDF]

J Chem Inf Model
Khaemba CS, Feng H, Chen D, Chen CL, Wei GW, Wei GW.   +5 more
europepmc   +1 more source

Liquid‐Processed 2D Aromatic Amorphous Carbon: Defect Engineering and Universal Transport Scaling

Small, EarlyView.
Liquid‐processed graphene oxide (GO) thin films undergo a controllable crystalline–to–amorphous transition driven by thermal quenching. By kinetically tuning oxygen‐driven defect formation during reduction, scalable 2D aromatic amorphous carbon phases are stabilized, directly linking nanoscale disorder and defect topology to electronic transport ...
Fabiola Liscio, Andrea Fondacaro, Gaetana Petrone, Federico Chianese, Jasper Rikkert Plaisier, Sara Fiori, Orlando Castellano, Alice Apponi, Nicolò Galvani, Verónica Montes García, Veronica Valentini, Stefano Iacobucci, Damiano Ricciarelli, Giuseppe Fisicaro, Antonino Lamagna, Giovanni Maria Vinai, Ernesto Placidi, Alessandro Bellucci, Daniele Maria Trucchi, Paolo Samorì, Alessandro Ruocco, Samuel Lara Avila, Andrea Liscio   +22 more
wiley   +1 more source

Geometric-topological deep transfer learning for precise vessel segmentation in 3D medical volumes. [PDF]

NPJ Digit Med
Wu J, Wen Z, Zhou H, Sun N, Zhang Y.
europepmc   +1 more source

Mind and Cosmos as Throughput Systems: A Convergence Through the Throughput Model

Systems Research and Behavioral Science, EarlyView.
ABSTRACT This paper advances a conceptual and mathematical foundations approach by applying the throughput model (TPM) to cosmic phenomena, reframing the universe as an extended information processing system. TPM's four stages, Perception, Information, Judgement and Decision Choice, are reformulated in explicit information‐theoretic and dynamical ...
Waymond Rodgers
wiley   +1 more source

A Classification of Intrinsic Ergodicity for Recognisable Random Substitution Systems. [PDF]

Commun Math Phys
Gohlke P, Mitchell A.
europepmc   +1 more source

Aligning Real‐Time Recurrence Computational Fluid Dynamics Simulations with Plant Data for the Ruhrstahl–Heraeus Degassing Process of Steel

steel research international, EarlyView.
Uncertainties exist in computational fluid dynamics (CFD) modeling of complex metallurgical processes, even when partly validated by laboratory experiments. rCFD enables computationally efficient prediction of long‐term RH degassing and can be adapted to vary flow conditions.
Xiaomeng Zhang, Maria Thumfart, Roman Rössler, Stefan Pirker   +3 more
wiley   +1 more source

Connected Components on Lie Groups and Applications to Multi-Orientation Image Analysis. [PDF]

J Math Imaging Vis
van den Berg NJ, Mula O, Vis L, Duits R.
europepmc   +1 more source