Results 31 to 40 of about 10,108 (182)

A Subset of Pro‐inflammatory CXCL10+ LILRB2+ Macrophages Derives From Recipient Monocytes and Drives Renal Allograft Rejection

Advanced Science, EarlyView.
This study uncovers a recipient‐derived monocyte‐to‐macrophage trajectory that drives inflammation during kidney transplant rejection. Using over 150 000 single‐cell profiles and more than 850 biopsies, the authors identify CXCL10+ macrophages as key predictors of graft loss.
Alexis Varin, Jovanne Palvair, Lennie Messager, Jamal Bamoulid, Jasper Callemeyn, Mélanie Chaintreuil, Ludivine Dal Zuffo, Didier Ducloux, Imane Farhat, Mathieu Legendre, Laurent Martin, Florian Renosi, Xavier Roussel, Thibaut Vaulet, Maarten Naesens, Claire Tinel, Baptiste Lamarthée   +16 more
wiley   +1 more source

Ultrahigh‐Linear Bio‐Inspired Janus Elastomeric Strain Sensor with High Sensitivity and Stretchability via Surface Wrinkle Engineering

Advanced Science, EarlyView.
A bio‐inspired Micro‐wrinkled Janus elastomeric flexible strain sensor mimicking wrinkled‐leaf viburnum is developed. Endowed with a synergistic sensing mechanism including wrinkle‐guided microcracks, modulus‐gradient‐driven strain division, and a parallel conductive circuit, it achieves ultra‐high linearity, sensitivity, wide strain range, and ...
Jing Lin, Ye Li, Simi Yu, Xing Cheng, Longxin Qian, Yufei Chen, Womin Li, Zhipeng Yang, Yinlei Lin, Dechao Hu, Jianyi Luo, Lan Liu   +11 more
wiley   +1 more source

Study of Resistive Switching Dynamics and Memory States Equilibria in Analog Filamentary Conductive‐Metal‐Oxide/HfOx ReRAM via Compact Modeling

Advanced Electronic Materials, EarlyView.
A physics‐based compact model for Conductive‐Metal‐Oxide/HfOx ReRAM, accounting for ion dynamics, electronic conduction, and thermal effects, is presented. Accurate and versatile simulations of analog non‐volatile conductance modulation and memory state stabilization enable reliable circuit‐level studies, advancing the optimization of neuromorphic and ...
Matteo Galetta, Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Stephan Menzel, Antonio La Porta, Tommaso Stecconi, Folkert Horst, Bert Jan Offrein, Valeria Bragaglia   +9 more
wiley   +1 more source

Probabilistic Modeling for Prediction Errors to Enhance Balancing Market Participation of Photovoltaic Systems: Error Threshold Estimation, Multisite Aggregation, and Overloading Effects

Advanced Energy and Sustainability Research, EarlyView.
This study proposes a method to increase the value of solar power in balancing markets by managing prediction errors. The approach models prediction uncertainties and quantifies reserve requirements based on a probabilistic model. This enables the more reliable participation of photovoltaic plants in balancing markets across multiple sites, especially ...
Jindan Cui, Xue Fang, Takashi Oozeki, Yuzuru Ueda   +3 more
wiley   +1 more source

Accelerated Screening of Halide Double Perovskites via Hybrid Density Functional Theory and Machine Learning for Thermoelectric Energy Conversion

Advanced Energy and Sustainability Research, EarlyView.
This study integrates hybrid density functional theory, Boltzmann transport theory, and machine learning to accelerate the discovery of lead‐free halide double perovskites for thermoelectric energy conversion. By screening 102 compounds, the authors identify high‐performing candidates such as Rb2GeI6 and Cs2SnBr6, offering a sustainable pathway toward ...
Souraya Goumri‐Said, Ghouti Abdellaoui, Mohammed Benali Kanoun   +2 more
wiley   +1 more source

Laparoscopic Colorectal Surgery in the Era of Robotics: Evolution, Eclipse, or Equilibrium?

Annals of Gastroenterological Surgery, EarlyView.
ABSTRACT Minimally invasive colorectal surgery has undergone a remarkable transformation over the past three decades. Laparoscopy, once viewed with skepticism, is now firmly established as a standard approach, supported by robust randomized trials demonstrating oncologic safety and improved recovery compared to open surgery.
Amanjeet Singh, Archit Gupta, Azhar Perwaiz, Adarsh Chaudhary   +3 more
wiley   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source

Bayesian Exploration of Metal‐Organic Framework‐Derived Nanocomposites for High‐Performance Supercapacitors

Advanced Intelligent Discovery, EarlyView.
An AI‐assisted approach is introduced to decode synthesis–performance relationships in metal‐organic framework‐derived supercapacitor materials using Bayesian optimization and predictive modeling, streamlining the search for optimal energy storage properties.
David Gryc, Pritam Banerjee, Felipe Jacques Lima Duarte, Joerg R. Jinschek, Premkumar Murugesan, Babak Rezaei, Stephan Sylvest Keller, Roland A. Fischer, Mian Zahid Hussain   +8 more
wiley   +1 more source