Results 131 to 140 of about 15,069,486 (297)

Automated Extraction of Multicomponent Alloy Data Using Large Language Models for Sustainable Design

Advanced Science, EarlyView.
A large language model (LLM) based pipeline is developed to automatically extract a comprehensive and accurate multicomponent alloy database from literature corpus. The extracted dataset is integrated with sustainability indicators to identify potential alloys that outperform existing industrial benchmark materials in terms of both performance and ...
Aravindan Kamatchi Sundaram, Mohit Chakraborty, Sai Mani Kumar Devathi, B. Pabitramohan Prusty, Rohit Batra   +4 more
wiley   +1 more source

Semantic Core for Sensor Telemetry Ingestion for Digital Twins

Smart Cities
Digital twin platforms for smart cities must continuously receive different types of data from sensors, gateways, and services, but in real situations these data are heterogeneous in terms of indicator names, measurement units, time rules, and object ...
Oleksandr Osolinskyi, Khrystyna Lipianina-Honcharenko, Myroslav Komar   +2 more
doaj   +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

Strategy of Triple‐Gradient in Binary Pixels for Flexible Pressure Sensing with High Sensitivity and Wide‐Range Linearity

Advanced Science, EarlyView.
A flexible pressure sensor with triple‐gradient design of conductivity, modulus, and dimension in binary micro‐dome pixels is proposed. Based on precisely‐designed CNT/PDMS matrix, the device exhibits a linear sensitivity of 974.1 kPa−1 across range up to 1.8 MPa (R2 > 0.99), offering an effective strategy for potential applications in healthcare ...
Yifan Liu, Xiao Xu, Fengming Hu, Yuanzhe Liang, Zidong Yin, Biao Qi, Ruolin Liu, Ziyi Dai, Jianyi Luo, Bingpu Zhou   +9 more
wiley   +1 more source

Semantic Communications With World Models

IEEE Transactions on Communications
Semantic communication is a promising technique for emerging wireless applications, which reduces transmission overhead by transmitting only task-relevant features instead of raw data. However, existing methods struggle under extremely low bandwidth and varying channel conditions, where corrupted or missing semantics lead to severe reconstruction ...
Peiwen Jiang, Jiajia Guo, Chao-Kai Wen, Shi Jin, Jun Zhang   +4 more
openaire   +3 more sources

CoSP: Reconfigurable Metamaterial Inverse Design via Contrastive Pretrained Large Language Model

Advanced Science, EarlyView.
In this work, CoSP (contrastive multi‐state pretrain), an intelligent inverse design method for reconfigurable metamaterials based on a contrastive pretrained large language model, is proposed. Numerical experiments demonstrate that CoSP can design reconfigurable metamaterial structures for multi‐state, multi‐band optical responses, showing great ...
Shujie Yang, Yuqi Zhang, Xuzhe Zhao, Yansong Tang, Kaichen Dong   +4 more
wiley   +1 more source

SemanticST: A Scalable Multi‐Contextual Graph Learning Framework for Uncovering Spatial Niches and Robust Multi‐Sample Integration in Spatial Transcriptomics

Advanced Science, EarlyView.
Technical limitations often let dominant signals overshadow rare cell types and fine‐grained heterogeneity in spatial transcriptomics. SemanticST, a graph neural network using multi‐semantic graph fusion and a novel min‐cut loss, recovers these subtle patterns.
Roxana Zahedi, Ahmadreza Argha, Nona Farbehi, Ivan Bakhshayeshi, Thantrira Porntaveetus, Youqiong Ye, Nigel H. Lovell, Hamid Alinejad‐Rokny   +7 more
wiley   +1 more source

Deep Learning‐Driven Discovery and Engineering of an Efficient PETase for Depolymerization and Detoxification of PET Microplastics Under Physiological Conditions

Advanced Science, EarlyView.
A deep learning–driven pipeline mining 246 million protein sequences uncovers AhPETase, an evolutionarily distinct PET hydrolase. Engineered variant AhPETaseM1 degrades post‐consumer PET microplastics under physiological conditions and reverses microplasticinduced cytotoxicity in human lung and colon cells, establishing enzymatic microplastic ...
Yuxuan Wang, Shijie He, Yuheng Chang, Sheng Mao, Jianan Canal Li, Binbin Chen, Hongxun Gao, Mingchun Xu, Chenxu Liu, Yajie Wang   +9 more
wiley   +1 more source

Normal Jonsson theories and their Kaiser classes

Қарағанды университетінің хабаршысы. Математика сериясы
We present results concerning new notion connected with the study of Jonsson theories. The new notion is a Kaiser class of models for arbitrary Jonsson theories.
A.R. Yeshkeyev, M.T. Kassymetova, N.M. Mussina   +2 more
doaj   +1 more source

Learning Work Function via Implicit Reasoning on Electrostatic Potential Landscapes

Advanced Science, EarlyView.
StructPot‐CLR establishes a cross‐modal contrastive learning framework that aligns the crystal structures of 2D materials with plane‐averaged electrostatic potential landscapes for physically informed work‐function prediction. The model achieves an MAE of 0.265 eV and an R2 of 0.902 on the held‐out test set while accurately preserving key morphological
Haoyu Wan, Yue Wu, Tianhao Su, Deng Pan
wiley   +1 more source