Results 11 to 20 of about 45,791 (216)

CD-PHY: Physical layer security in wireless networks through constellation diversity [PDF]

MILCOM 2012 - 2012 IEEE Military Communications Conference, 2012
A common approach for introducing security at the physical layer is to rely on the channel variations of the wireless environment. This type of approach is not always suitable for wireless networks where the channel remains static for most of the network lifetime.
Mohammad Iftekhar Husain, Suyash Mahant, Ramalingam Sridhar   +2 more
openaire   +2 more sources

Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks

Advanced Science, EarlyView.
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu, Longfei Lv, Fan Zhang, Si Zhou, Weiwei Gao, Jijun Zhao   +5 more
wiley   +1 more source

Remote Magnetomechanical Neuromodulation Uncovers Therapeutic Mechanisms for Alleviating Parkinsonian Symptoms in Freely Moving Mice

Advanced Science, EarlyView.
Magnetomechanical neuromodulation using magnetic nanodiscs enables remote activation of neurons. In a hemiparkinsonian mouse model, alternating magnetic fields actuate the nanodiscs to generate torque that opens mechanosensitive ion channels within the subthalamic nucleus, thereby modulating basal ganglia motor circuitry.
Anouk Wolters, Lorenzo Signorelli, Christian Herff, Sophia Gimple, Renzo Riemens, Gunter Kenis, Kim Rijkers, Hamed Shabani, Jyh‐Jang Sun, Yasin Temel, Hans Clusmann, Danijela Gregurec, Sarah‐Anna Hescham   +12 more
wiley   +1 more source

High‐Efficiency Precipitate Recycling Strategy Paves the Way for Efficient Sb2S3 Solar Cells Fabricated by CBD Method

Advanced Science, EarlyView.
A novel PR strategy was proposed to improve CBD‐derived Sb2S3 film quality. It synergistically optimized the CBO of CdS/Sb2S3 interface and the back‐contact barrier, while the VS2 donor defect was converted into SSb2 acceptor defect with lower concentration.
Yeyang Lin, Zixian Cai, Mingen Zheng, Ye Huang, Weihuang Wang, Qiqiang Zhu, Qing Gao, Jianhui Chen, Shuying Cheng   +8 more
wiley   +1 more source

Physics‐encoded transfer learning for scale‐up modeling of CHO cell bioreactors

AIChE Journal, EarlyView.
Abstract Developing reliable predictive models for mammalian cell bioreactors, particularly Chinese hamster ovary (CHO) cultures widely used in biopharmaceutical manufacturing, remains challenging due to severe data scarcity in industrial‐scale reactors.
Muyang Li, Ming Xiao, Zhe Wu
wiley   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

Advanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu   +3 more
wiley   +1 more source

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

Advanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

Advanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia, Marcelo A. Dias, Parvez Alam   +2 more
wiley   +1 more source

ParamNet: A Physics‐Guided Deep Learning Framework for Intelligent Self‐Inversion of Vacuum Optical Levitation Systems

Advanced Intelligent Systems, EarlyView.
A physics‐guided deep learning framework, ParamNet, is introduced for the intelligent self‐inversion of vacuum optical tweezers. By fuzing dual‐branch time–frequency features with physical dynamical constraints, it achieves high‐accuracy calibration of trap parameters from short‐window, low‐frequency trajectories, outperforming traditional methods ...
Qi Zheng, Wenfeng Fan, Feng Li, Jian Wu, Wei Quan   +4 more
wiley   +1 more source

Intra‐articular Orthobiologics Show Statistically but Not Clinically Meaningful Improvements Compared With Viscosupplementation in Knee Osteoarthritis: A Network Meta‐analysis of Randomized Controlled Trials

Arthroscopy, EarlyView.
Purpose To evaluate the comparative effectiveness of intra‐articular platelet‐rich plasma (PRP), stromal vascular fraction (SVF), bone marrow aspirate concentrate (BMAC), umbilical cord‐derived mesenchymal stem cell (UC‐MSC), and hyaluronic acid (HA) for pain relief and functional improvement in patients with knee osteoarthritis through network meta ...
Joo Hyung Han, Min Jung, Kwangho Chung, Hyun‐Soo Moon, Se‐Han Jung, Sung‐Hwan Kim   +5 more
wiley   +1 more source