Results 141 to 150 of about 2,027,139 (291)

Nonlinear Knowledge in Kernel Approximation [PDF]

, 2006
Prior knowledge over arbitrary general sets is incorporated into nonlinear kernel approximation problems in the form of linear constraints in a linear program.
Mangasarian, Olvi, Wild, Edward
core  

Kernel-based clustering via Isolation Distributional Kernel

, 2023
Clustering has become one of the widely used automatic data-labeling techniques applied in a variety of disciplines. Kernel-based clustering is a technique designed to identify non-linearly separable clusters with irregular shapes.
Ye Zhu (13101348), KM Ting (13907250)
core  

Metasurface‐Enabled Helical Wavefront Fingerprint Metrology for Quantitative Retrieval of Liquid Optical Constants

Advanced Science, EarlyView.
A metasurface‐enabled helical wavefront fingerprint (MHWF) paradigm is proposed for quantitative and specific retrieval of a liquid medium's refractive index and extinction coefficient. The liquid's complex dielectric response governs the wavefront evolution of the metasurface‐generated focused vortex beam, forming a distinctive three‐dimensional ...
Yuting Zhou, Hongliang Li, Simeng Li, Feiyu Jiao, Yansong Du, Jin Tae Kim, Sang‐Shin Lee, Duk‐Yong Choi, Fei Ding, Xuechao Yu, Xun Guan   +10 more
wiley   +1 more source

RNA Promotes Synapsin Condensates That Organize Synaptic Vesicles in Live Neurons and Enable Localized Translation in Reconstituted System

Advanced Science, EarlyView.
Condensates at synapses organize synaptic vesicles (SVs) and are crucial for efficient neurotransmitter release, yet how RNA contributes to this mesoscale architecture remains poorly understood. Here we uncover that RNA modulates synapsin–driven condensates.
Branislava Rankovic, Zachary M. Geisterfer, Akshita Chhabra, Vladimir M. Jovanovic, Ian Seim, Christian Hoffmann, Antonela Condric, Gerard Aguilar Pérez, Rinse de Boer, Lars T. Hofstede, Jingao Sun, Kiara Freitag, Katja Nowick, Marina Jendrach, Frank L. Heppner, Vladimir Despic, Michaela Müller‐McNicoll, Stephan Sigrist, Geert van den Bogaart, Sofiia Reshetniak, Amy S. Gladfelter, Dragomir Milovanovic   +21 more
wiley   +1 more source

Neuromorphic Devices and Computing for Sensing, Memory, and Control

Advanced Science, EarlyView.
This review introduces neuromorphic devices made from diverse materials. These devices mimic neuronal functions and architectures and, when integrated with artificial or biological computing, can form closed loops with neurons for pressure, optical, acoustic, and biochemical sensing and modulation.
Zhengguang Zhu, Nicholas Schaffer, Xiao Yang   +2 more
wiley   +1 more source

Heat kernel approach to the one-loop effective action for nonlinear electrodynamics

Journal of High Energy Physics
We develop a heat kernel method to compute the one-loop effective action for a general class of nonlinear electrodynamic (NLED) theories in four dimensional Minkowski spacetime.
Evgeny I. Buchbinder, Darren T. Grasso, Joshua R. Pinelli   +2 more
doaj   +1 more source

The influence of return bends on the downstream pressure drop and condensation heat transfer in tubes [PDF]

, 1971
The influence of return bends on the downstream pressure drop and heat transfer coefficient of condensing refrigerant R-12 was studied experimentally. Flow patterns in glass return bends of 1/2 to 1 in. radius and 0.315 in. I. D.
Traviss, Donald P., Rohsenow, Warren M.
core  

Grain Boundary Structure Ordering via Electroshock Treatment Enhances Strength‐Ductility Synergy

Advanced Science, EarlyView.
Electroshock treatment triggers atomic rearrangement, transforming disordered grain boundaries into ordered states without inducing recrystallization. This grain boundary ordering effectively relieves strain concentration and strengthens boundaries, enabling a simultaneous improvement in both strength and ductility.
Jiancheng Chen, Feng Wang, Dongsheng Qian, Huiling Wang, Jinsong Wu, Mingwang Fu, Lin Hua   +6 more
wiley   +1 more source

Heterogeneous Media Heat Transfer Simulations Based on 3D-Fractional Parametric Laplace Kernel

International Journal of Differential Equations
This paper introduces a new Mittag–Leffler–Laplace memory kernel defined by Φ˜μ,ν,κα,ρs=∫0∞Eρ−μξκ/κξνα−1e−sξdξ, s>0, and develops a unified framework for modeling heat transfer in heterogeneous media with nonlocal temporal memory.
Rabha W. Ibrahim, Ali A. Jizany, Hasan Kahtan   +2 more
doaj   +1 more source

Fusing Direct and Indirect Measurements Through Multi‐Fidelity Learning For Accelerated Electrocaloric Materials Discovery

Advanced Science, EarlyView.
A multi‐fidelity framework integrates sparse direct and abundant indirect electrocaloric measurements. Multi‐objective active learning accelerates BaTiO3‐based electrocaloric materials discovery at –70∘C$^{\circ }{\rm C}$. A diffuse transition enables an electrocaloric strength of 0.06×$\times$10−6 Km/V at –70℃ with an operational temperature span of ...
Bo Wang, Pengfei Dang, Yuan Tian, Zhengwang He, Wei Gu, Lixue Zhang, Turab Lookman, Yumei Zhou, Dezhen Xue   +8 more
wiley   +1 more source