Results 41 to 50 of about 597,354 (286)

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Parabolic Marcinkiewicz integrals on product spaces and extrapolation

Open Mathematics, 2016
In this paper, we study the the parabolic Marcinkiewicz integral MΩ,hρ1,ρ2${\cal M}_{\Omega, h}^{{\rho _{1,}}{\rho _2}}$ on product domains Rn × Rm (n, m ≥ 2). Lp estimates of such operators are obtained under weak conditions on the kernels.
Ali Mohammed, Al-Dolat Mohammed
doaj   +1 more source

Thickness‐Dependent Skyrmion Evolution in Fe3GeTe2 During Magnetization Reversal

Advanced Functional Materials, EarlyView.
Thickness‐ and field‐dependent magnetic domain behavior in 2D van der Waals Fe3GeTe2 is studied using Lorentz TEM and micromagnetic simulations. A patch‐like domain phase evolves from skyrmions during magnetization reversal, and step edges between thickness regions act as pinning sites.
Jennifer Garland, John Fullerton, PeiYu Cai, Rabindra Basnet, Santosh Karki Chhetri, Jin Hu, Elton J. G. Santos, Yue Li, Charudatta Phatak, Amanda Petford‐Long   +9 more
wiley   +1 more source

Meda Inequality for Rearrangements of the Convolution on the Heisenberg Group and Some Applications

Journal of Inequalities and Applications, 2009
The Meda inequality for rearrangements of the convolution operator on the Heisenberg group ℍn is proved. By using the Meda inequality, an O'Neil-type inequality for the convolution is obtained. As applications of these results, some sufficient
V. S. Guliyev, A. Serbetci, E. Güner, S. Balcı   +3 more
doaj   +2 more sources

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

Advanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha, Yingshan Ma, Yong Nam An, Sung‐Un An, Hyeon Hak Jung, Suvi‐Tuuli Varjamo, Jiwon Yoo, Junho Min, Hanvit Kim, Faisal Ahmed, Sang Hoon Chae, Young Min Song, Weiwei Cai, Tawfique Hasan, Zhipei Sun, Dong‐Ho Kang, Hyeon‐Jin Shin, Yunyun Dai, Hoon Hahn Yoon   +18 more
wiley   +1 more source

Mesoporous Carbon Thin Films with Large Mesopores as Model Material for Electrochemical Applications

Advanced Functional Materials, EarlyView.
Mesoporous carbon thin films possessing 70 nm mesopores are prepared on titanium substrates by soft templating of resol resins with a self‐synthesized poly(ethylene oxide)‐block‐poly(hexyl acrylate) block copolymer. A strategy to avoid corrosion of the metal substrate is presented, and the films are extensively characterized in terms of morphology ...
Lysander Q. Wagner, Joshua Schober, Pascal Dippell, Chantal Glatthaar, Smail Mekhilef, David Schäfer, Hannes Hergert, Marcus Rohnke, Matthias T. Elm, Bernd M. Smarsly   +9 more
wiley   +1 more source

Bioprinting Organs—Science or Fiction?—A Review From Students to Students

Advanced Healthcare Materials, EarlyView.
Bioprinting artificial organs has the potential to revolutionize the medical field. This is a comprehensive review of the bioprinting workflow delving into the latest advancements in bioinks, materials and bioprinting techniques, exploring the critical stages of tissue maturation and functionality.
Nicoletta Murenu, Camilla Mussoni, Mateo S. Andrade Mier, Paula Buettner, Nathaly Chicaiza‐Cabezas, Yi‐Yu Robin Dai, Jessica Faber, Maren Fiedler, Zan Lamberger, Xuen Jen Ng, Vanessa Moessler, Anna Rederer, Jonas Roeder, Sabrina Stecher, Katinka Theis, Jeanette Weigelt, Silvia Budday, Gregor Lang, Natascha Schaefer   +18 more
wiley   +1 more source

Lp estimates for maximal functions along surfaces of revolution on product spaces

Open Mathematics, 2019
This paper is concerned with establishing Lp estimates for a class of maximal operators associated to surfaces of revolution with kernels in Lq(Sn−1 × Sm−1), q > 1.
Ali Mohammed, Reyyashi Musa
doaj   +1 more source

In Vivo Skin 3‐D Surface Reconstruction and Wrinkle Depth Estimation Using Handheld High Resolution Tactile Sensing

Advanced Healthcare Materials, EarlyView.
A compact handheld GelSight probe reconstructs in vivo 3‐D skin topography with micron‐level precision using a custom elastic gel and a learning‐based surface normal to height map pipeline. The device quantifies wrinkle depth across various body locations and detects changes in wrinkle depth following moisturizer application.
Akhil Padmanabha, Arpit Agarwal, Catherine Li, Austin Williams, Dinesh K. Patel, Sankalp Chopkar, Achu Wilson, Ahmet Ozkan, Wenzhen Yuan, Sonal Choudhary, Arash Mostaghimi, Zackory Erickson, Carmel Majidi   +12 more
wiley   +1 more source

Weighted L^p boundedness of maximal operators with rough kernels

AIMS Mathematics
In this paper, we study the weighted spaces $ L^p(\omega, \mathbb{R}^d) $ boundedness of certain class of maximal operators when their kernels belong to the space $ L^{q}(\mathbb{S} ^{d-1}) $, $ q > 1 $.
Hussain Al-Qassem , Mohammed Ali
doaj   +1 more source