Results 71 to 80 of about 24,548 (256)

Large Language Model‐Informed Dual‐Track AI Framework for the Synergistic Design of Crack‐Free and High‐Strength Superalloys

Advanced Science, EarlyView.
This paper illustrates a knowledge‐augmented dual‐track AI framework for advanced superalloy design. First, Large Language Models translate metallurgical heuristics into explicit rules to rapidly prune a vast compositional search space. Subsequently, LLM‐distilled priors safely guide a reinforcement learning agent during autonomous process optimization,
Jian Yao, Junkang Wu, Jie Su, Fuzhu Wang, Zi Wang, Li Wang, Liming Tan, Lan Huang, Feng Liu, Yong Liu   +9 more
wiley   +1 more source

A Semantic Segmentation Algorithm in Workshop Scenarios

The classification of workshop objectives based on deep learning is the foundation of intelligent workshop management. There are various types of targets in the workshop, with variable geometric shapes and disorderly distribution of targets. In this article, we propose a deep learning based solution that can improve the speed and accuracy of target ...
Yin, Hongmei, Jin, Gege, Li, Zhijun, Chen, Chen, Hua, Jiyong   +4 more
openaire   +1 more source

CD177 Deficiency Defines a Stable Subtype of Human Neutrophil Granulocytes with Tumor Promoting Activity

Advanced Science, EarlyView.
Human neutrophils exist as two epigenetically imprinted subtypes defined by stable CD177 expression or absence — a ratio that persists across time, circadian rhythms, and inflammation. CD177− neutrophils display a distinct molecular landscape enriched in arginase 1 and lipid metabolism markers, accumulate in head‐and‐neck tumors, and associate with ...
Marcel Jung, Alexander Beer, Susmita Ghosh, Ekaterina Pylaeva, Belal Alshaar, Tobias Tertel, Nils Bastian Leimkühler, Thomas Schroeder, Janine Gronewold, Nina Hagemann, Ayan Mohamud Yusuf, Benedikt Frank, Yiqiao Zhang, Dennis Nagel, Kim Schloeßer, Laura Karsch, Emily Hedtfeld, Sabrina Lohmann, Kathrin Blank, Andreas Kraus, Max Krumbein, Nastassia Kabankova, Hongxiao Wang, Almke Bader, Mathis Richter, Fengjun Zhang, Raphael Chevre, Bernd Giebel, Stephan Lang, Anika Grüneboom, Daniela Maier‐Begandt, Anja Hasenberg, Oliver Soehnlein, Hans Christian Reinhardt, Sven Heiles, Jianxu Chen, Jadwiga Jablonska, Albert Sickmann, Dirk M. Hermann, Matthias Gunzer   +39 more
wiley   +1 more source

A Machine Vision‐Guided Microphysiological Platform With Automated Microfluidics Enables Longitudinal Biomarker Monitoring and Emulation of Translationally Relevant Exposure Scenarios

Advanced Science, EarlyView.
A pneumatically actuated multi‐tissue microphysiological system is integrated with AI‐based machine vision and automatic sampling and replenishment systems. The platform allows for the emulation of translationally relevant long‐term pharmacokinetic exposure scenarios for multiple weeks while enabling longitudinal monitoring of response biomarkers ...
Jibbe Keulen, Yi Zhong, Laura Dangel, Sonia Youhanna, Reza Zandi Shafagh, Jinhye Ryu, Domnica‐Gabriela Gurau, Mathias Haag, Thomas E. Mürdter, Yingxin Liang, Iro Beligiani, Nicole Ziegler, Sabine Willems, Nayere Taebnia, Wouter van der Wijngaart, Volker M. Lauschke   +15 more
wiley   +1 more source

Hardware‐Attentive Programmable Fourier Ptychography Enables Task‐Adaptive Label‐Free Virtual Staining

Advanced Science, EarlyView.
Task‐adaptive programmable optics enables label‐free virtual staining through optical‐attention‐guided acquisition and reconstruction. By optimizing wavelength, illumination angle, exposure time, and imaging depth, the framework learns task‐relevant optical measurements, generating clinically interpretable virtual stains with improved fidelity, non ...
Tianyue He, Wenyi Jing, Le Zhang, Qican Zhang, Tingdong Kou, Xin He, Yan Qiu, Yang Lu, Jian Cui, Yongfu Wen, Zhenrong Zheng, Hongying Zhang, Dayong Jin, Junfei Shen   +13 more
wiley   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Real-Time Semantic Reconstruction and Semantically Constrained Path Planning for Agricultural Robots in Greenhouses

Agronomy
To address perception and navigation challenges in precision agriculture caused by GPS signal loss and weakly structured environments in greenhouses, this study proposes an integrated framework for real-time semantic reconstruction and path planning ...
Tianrui Quan, Junjie Luo, Shuxin Xie, Xuesong Ren, Yubin Miao   +4 more
doaj   +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

Retracted: A Lightweight Semantic Segmentation Algorithm Based on Deep Convolutional Neural Networks. [PDF]

Comput Intell Neurosci, 2023
Intelligence And Neuroscience C.
europepmc   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source