Results 61 to 70 of about 260,346 (290)

Photon Avalanching Nanoparticles: The Next Generation of Upconverting Nanomaterials?

Advanced Functional Materials, EarlyView.
This Perspective outlines the mechanistic foundations that enable photon‐avalanche (PA) behavior in lanthanide nanomaterials and contrasts them with emerging application spaces and forward‐looking design strategies. By bridging threshold engineering, energy‐transfer dynamics, and materials engineering, we provide a coherent roadmap for advancing the ...
Kimoon Lee, Yunseo Kim, Hyeong‐ku Jo, Dongjoon Yoon, Byeonghyeok Im, WonJeong Yu, Eui‐Rim On, Changhwan Lee   +7 more
wiley   +1 more source

A Data Driven Review of In Vitro Electrical and Mechanical Stimulation for Post‐Acute Phase Wound Healing

Advanced Healthcare Materials, EarlyView.
This review examines how in vitro electrical and mechanical stimulation modulates wound healing in fibroblasts and keratinocytes. Analyzing over 560 experimental data points, we relate stimulation parameters to proliferation and migration outcomes, evaluate platform designs, and highlight the need for multi‐parameter optimization to advance targeted ...
Matthew K. Burgess, Ellen F. Marsh, Veronica M. Lucian, Malavika Nair   +3 more
wiley   +1 more source

A new family of kernels from the beta polynomial kernels with applications in density estimation

IJAIN (International Journal of Advances in Intelligent Informatics), 2020
One of the fundamental data analytics tools in statistical estimation is the non-parametric kernel method that involves probability estimates production.
Israel Uzuazor Siloko, Wilson Nwankwo, Edith Akpevwe Siloko   +2 more
doaj   +1 more source

Unveiling the Role of Curvature in Carbon for Improved Energy Release of Ammonium Perchlorate

Advanced Materials, EarlyView.
High‐curvature carbon materials identified via machine learning and simulation can enhance the heat release and combustion performance of ammonium perchlorate. ABSTRACT The catalytic role of carbon curvature in the thermal decomposition of ammonium perchlorate (AP) remains largely unexplored. To address this gap, this study employs machine learning and
Dan Liu, Keliang Song, Haorui Zhang, Zhipeng Liu, Guansong He, Junru Wang, Wenming Yang, Xu Zhao, Zhijian Yang   +8 more
wiley   +1 more source

The stochastic approximation method for the estimation of a multivariate probability density

, 2008
We apply the stochastic approximation method to construct a large class of recursive kernel estimators of a probability density, including the one introduced by Hall and Patil (1994).
Mokkadem, Abdelkader, Pelletier, Mariane, Slaoui, Yousri   +2 more
core   +5 more sources

Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Advanced Materials, EarlyView.
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll, Ivan Pinto‐Huguet, Enzo Rotunno, Thomas Galvani, Catalina Coll, Payam Habibzadeh Kavkani, Maria Chiara Spadaro, Yann‐Michel Niquet, Martin Børstad Eriksen, Sara Martí‐Sánchez, Georgios Katsaros, Giordano Scappucci, Peter Krogstrup, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Pablo Ordejón, Stephan Roche, Vincenzo Grillo, Jordi Arbiol   +19 more
wiley   +1 more source

Flexoelectrically Induced Polar Topology in Twisted SrTiO3 Membranes

Advanced Materials, EarlyView.
Twisted SrTiO3 bilayers host polar vortices of flexoelectric origin, revealed through combined experiment and theory. By reconstructing polarization from the toroidal moment of strain gradients, the work establishes a 3D chiral state with broken inversion and mirror symmetries.
Isabel Tenreiro, Hugo Aramberri, Víctor Rouco, Gabriel Sánchez‐Santolino, Mariona Cabero, Fernando Gallego, David Sánchez‐Manzano, José M. González‐Calbet, Federico Mompeán, Mar García‐Hernández, Alberto Rivera‐Calzada, Jorge Íñiguez‐González, Carlos León, Jacobo Santamaría   +13 more
wiley   +1 more source

Improving Radio Source Count Estimation Using Kernel Density Estimation

The Astrophysical Journal
Radio source counts provide a fundamental census of cosmic radio emission, yet their estimation is usually based on coarse histograms that suffer from bin-choice bias, boundary effects, and survey incompleteness.
Luozhenhan Liu, Zunli Yuan, Wenjie Wang, Chuanqi Li   +3 more
doaj   +1 more source

Optimal Bandwidth Selection for Kernel Density Functionals Estimation

Journal of Probability and Statistics, 2015
The choice of bandwidth is crucial to the kernel density estimation (KDE) and kernel based regression. Various bandwidth selection methods for KDE and local least square regression have been developed in the past decade.
Su Chen
doaj   +1 more source

Bayesian Bandwidth Selection for a Nonparametric Regression Model with Mixed Types of Regressors

Econometrics, 2016
This paper develops a sampling algorithm for bandwidth estimation in a nonparametric regression model with continuous and discrete regressors under an unknown error density.
Xibin Zhang, Maxwell L. King, Han Lin Shang   +2 more
doaj   +1 more source