Results 141 to 150 of about 154,123 (277)

Ultra‐Wide‐Field Noninvasive Imaging Through Scattering Media Via Physics‐Guided Deep Learning

Advanced Science, EarlyView.
We propose a physics‐guided adaptive dual‐domain learning method for ultra‐wide‐field noninvasive imaging through scattering media, namely UNI‐Net. Our method not only reduces the requirement for real experimental data by an order of magnitude but also enables clear imaging of complex scenes with an ultra‐large field of view, which is 164 times the OME
Lintao Peng, Mingwei He, Jeff Zhu, Sujit K. Sahoo, Liheng Bian, Cuong Dang   +5 more
wiley   +1 more source

Wireless, Deep‐Seeing Smart Pill: A NIR‐II Fluorescence Imaging Capsule Endoscope for Gastrointestinal Cancer

Advanced Science, EarlyView.
A novel near‐infrared‐II fluorescent imaging capsule endoscope that detects specific fluorescence signals above 900 nm enables highly sensitive, targeted imaging of gastrointestinal cancer tissue. This wirelessly powered and magnetically controlled “smart pill” achieves high sensitivity and deep tissue penetration, allowing precise, non‐invasive ...
Weicheng Wang, Jinlei Jiang, Zhengting Wang, Shuqi Liu, Wei Wang, Xi Chen, Qirui Zhao, Xinyuan Cui, Cheng Zhou, Shengsheng Cui, Daxiang Cui   +10 more
wiley   +1 more source

Heterojunction‐Engineered Mass Spectrometry Platform for Deciphering Serum Metabolic Fingerprints in Diagnosis of Respiratory Diseases

Advanced Science, EarlyView.
Hollow Co3O4/TiO2 heterojunctions are engineered for high‐throughput laser desorption/ionization mass spectrometry. The built‐in electric field drives efficient charge separation and photothermal conversion, while the hierarchical mesoporous network enables robust salt and protein tolerance.
Junyu Chen, Chaoqi Wang, Xi Yu, Yuming Jiang, Yijiao Qu, Huihui Fu, Yuyin Bu, Xiaoyong Zhang, Zongxiu Nie   +8 more
wiley   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

Efficient In‐Hardware Matrix–Vector Multiplication and Addition Exploiting Bilinearity of Schottky Barrier Transistors Processed on Industrial FDSOI

Advanced Electronic Materials, EarlyView.
ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez, Niladri Bhattacharjee, Yuxuan He, Giulio Galderisi, Brojogopal Sapui, Sara Mannaa, Ian O'Connor, Violetta Sessi, Peter Javorka, Thomas Mikolajick, Jens Trommer   +10 more
wiley   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Determinants of Knowledge and Usage of Generative Artificial Intelligence in Agricultural Extension: Evidence From Tennessee Extension Personnel

Agribusiness, EarlyView.
ABSTRACT This paper examines the determinants of generative AI (GenAI) knowledge and usage among agricultural extension professionals. Drawing on survey data from agricultural extension personnel in Tennessee, we employ regression analyses and latent Dirichlet allocation (LDA) for topic modeling of open‐ended responses to study the knowledge and usage ...
Abdelaziz Lawani, Jason de Koff, James Muriuki, Anna‐Liisa Ihuhwa   +3 more
wiley   +1 more source

Farmers’ Protests in Germany: Media Coverage and Types of Bias

Agribusiness, EarlyView.
ABSTRACT The German farmers’ protests of 2024 sparked widespread media coverage and public debate. Yet, media coverage was not always positive, reflecting the media's attention‐seeking and selective focus. Occurrences of farmers blocking media outlets reflected distrust in how their concerns were portrayed.
Felix Schlichte, Doris Läpple
wiley   +1 more source

Consumers' Willingness to Pay a Premium for Climate‐Friendly Food Production: The Role of Production Method Information and Social Norms

Agribusiness, EarlyView.
ABSTRACT This study examines whether information about production methods and social norms can increase consumers' willingness to pay (WTP) a price premium for food produced using climate‐friendly farming methods. A randomized survey experiment was conducted with 1568 respondents across Denmark, Lithuania, and Spain, who were assigned to one of four ...
Kassa Tarekegn Erekalo, Tove Christensen, Sigrid Denver, Marilena Gemtou, Spyros Fountas, Søren Marcus Pedersen   +5 more
wiley   +1 more source

Harnessing Large Language Models to Advance Microbiome Research: From Sequence Analysis to Clinical Applications

Advanced Intelligent Discovery, EarlyView.
Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing, He Wang, Yangyang Sun, Xiaoquan Su, Shunyao Wu   +4 more
wiley   +1 more source