Results 211 to 220 of about 1,930,168 (250)

Routine physics work efficacy and efficiency improvement through a shared-duty physicist-of-the-day model in a multi-hospital radiation oncology network. [PDF]

J Appl Clin Med Phys
Chen GP, Prah DE, Paulson ES.
europepmc   +1 more source

Deciphering Anti‐Cancer Drug Efficacy Through Nanomechanical Vibrations in Living Gastric Cancer Organoids

Advanced Science, EarlyView.
This study developed an efficacy assessment platform that integrates patient‐derived gastric cancer organoids, atomic force microscopy (AFM)‐based nanomechanical vibration detection, deep learning analysis, and organoid mechanical modeling. It detects picomolar drug effects within 0.1 s signal, achieves 97% classification accuracy, and offers non ...
Ting Zhang, Qiubo Chen, Shihai Lan, Liang Zhu, Shuaiyu Liu, Yan Xia, Yalu Zhang, Hanhui Yao, Yongman Liu, Shangquan Wu, Qingchuan Zhang   +10 more
wiley   +1 more source

Fractional Physics Informed Neural Networks for Surrogate Modeling of Non-Markovian Discrete-Time Quantum Walks. [PDF]

Entropy (Basel)
Zhu Z, Liu M, Liang C, Yang F, Shen J, Wen X, Shen L, Wang Y.   +7 more
europepmc   +1 more source

Physics‐Aware Machine‐Learning‐Driven Inverse Design of Broadband Ultra‐Open Acoustic Metamaterials

Advanced Science, EarlyView.
A physics‐aware machine‐learning framework enables inverse design of ultra‐open acoustic silencers by decoupling spectral and radial design spaces. The approach rapidly identifies broadband, compact, and highly ventilated architectures, while revealing hidden linear design rules that link geometry, impedance matching, and acoustic performance.
Zhiwei Yang, Mengyu Li, Xiaohang Xie, Ao Chen, Thomas G. Bifano, Xin Zhang   +5 more
wiley   +1 more source

Monitoring and risk assessment of airborne graphene oxide released during a pilot study of 3D printing with polylactic acid filaments. [PDF]

J Environ Health Sci Eng
Salcines C, Domat M, Ruiz J, Castanon-Jano L, Blanco-Fernandez E, Valiente R.   +5 more
europepmc   +1 more source

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

Bridging TG-116 and TG-232: A retrospective multi-vendor evaluation of deviation index re-centering and process control in digital radiography. [PDF]

J Appl Clin Med Phys
AbuAzzah E, Alrehily F, Gameraddin M, Alshoabi S, Alsharif W, Alsultan KD, Alshamrani A, Al-Radadi K, Badawy R, Al-Jabri S, Al-Harbi T, Al-Hazme N.   +11 more
europepmc   +1 more source

Gestational Hypoxia Disrupts Medial Ganglionic Eminence Progenitor Dynamics and Interneuron Development in Schizophrenia

Advanced Science, EarlyView.
FES‐derived MGE spheroids exhibit progenitor‐stage alterations in developmental trajectory and hypoxia‐responsive transcriptional programs, followed by functional disruption. Gestational hypoxia recapitulates impaired progenitor proliferation, shortened cell‐cycle progression, interneuron developmental abnormalities, and schizophrenia‐like behaviors in
Peiyan Ni, Qiancheng Zhang, Youhui Jiang, Huiying Yao, Chuqing Zhou, Xiaoyi Tian, Shiyingnan Gao, Jun Zhao, Xinyi Ren, Naxin Xu, Mengshan Fu, Liansheng Zhao, Xueyu Qi, Xueli Yu, Wanjun Guo, Sangmi Chung, Fan Guo, Tao Li   +17 more
wiley   +1 more source

Detection, Reconstruction, and Overheating Warning of Three-Dimensional Dynamic Temperature Fields Inside Conductive Polymer Gels. [PDF]

Polymers (Basel)
Zhang J, Ni K, Wang X.
europepmc   +1 more source

Trustworthy Multimodal Attention Framework for Creep Rupture Life Prediction Under Data‐Scarce Conditions: A Case Study on IN718

Advanced Science, EarlyView.
An attention‐based multimodal deep learning framework is developed to predict the creep life of Ni‐based superalloys by fusing processing parameters with microstructural micrographs. The model achieves high accuracy (R2 = 0.92), aligns with metallurgical principles by capturing δ‐phase influence, and incorporates uncertainty quantification, offering a ...
Haopeng Lv, Dayong Wu, Ziyuan Rao, Qian Wang, Haikun Ma, Jie Kang, Wang Li, Huicong Dong, Yandong Wang, Zhinan Yang, Ru Su   +10 more
wiley   +1 more source