Results 241 to 250 of about 1,501,866 (307)

Healthcare Provision Shifts Under DIP Reform: From Conventional Medicine to Traditional Medicine. [PDF]

Inquiry
Pan X, Dai Z, Xiao Y, Ma C, Wang D, Wu J.   +5 more
europepmc   +1 more source

INB3P: A Multi‐Modal and Interpretable Co‐Attention Framework Integrating Property‐Aware Explanations and Memory‐Bank Contrastive Fusion for Blood–Brain Barrier Penetrating Peptide Discovery

Advanced Science, EarlyView.
INB3P is a multimodal framework for blood–brain barrier‐penetrating peptide prediction under extreme data scarcity and class imbalance. By combining physicochemical‐guided augmentation, sequence–structure co‐attention, and imbalance‐aware optimization, it improves predictive performance and interpretability.
Jingwei Lv, Qianyang Wu, Jian Liu, Binlu Yang, Yuanhao Li, Junlin Xu, Yajie Meng, Leyi Wei, Zilong Zhang, Quan Zou, Xiulai Li, Feifei Cui   +11 more
wiley   +1 more source

Huimin Insurance and unequal economic welfare between urban and rural areas: evidence from Chinese cities. [PDF]

Front Public Health
Ma J, Li S, Xue W.
europepmc   +1 more source

Pellet Printing for Soft Robotic Devices

Advanced Science, EarlyView.
Fused Granulate Fabrication (FGF) is established here as a reliable method for fabricating soft, airtight robotic devices. Through coordinated optimization of hardware, material selection, and process parameters, this approach enables high‐speed printing of thermoplastic elastomers with silicone‐like softness and modulus.
Yijia Wu, Ju‐Hung Chen, Ariana Olivares, Katherine Kostak, Stefan Pedicone, Savita V. Kendre, Markus P. Nemitz   +6 more
wiley   +1 more source

Customizing Tactile Sensors via Machine Learning‐Driven Inverse Design

Advanced Science, EarlyView.
ABSTRACT Replicating the sophisticated sense of touch in artificial systems requires tactile sensors with precisely tailored properties. However, manually navigating the complex microstructure‐property relationship results in inefficient and suboptimal designs.
Baocheng Wang, Depeng Kong, Zhiao He, Jikai Liang, Yuyao Lu, Zikang Deng, Honghe Li, Mengke Wang, M. Jamal Deen, Zhiqiu Ye, Shuyao Zhou, Huayong Yang, Honghao Lyu, Jun Chen, Kaichen Xu, Geng Yang   +15 more
wiley   +1 more source

Feasibility of automated AI-based contouring and stable radiomic feature assessment by HyperSight-CBCT Imaging for adaptive high-precision radiotherapy of prostate cancer. [PDF]

Sci Rep
Schmidt R, Bajerski D, Bicu AS, Siefert V, Eckl M, Willam M, Froelich MF, Schoenberg SO, Ehmann M, Buergy D, Stieler F, Fleckenstein J, Giordano FA, Boda-Heggemann J, Dreher C.   +14 more
europepmc   +1 more source

Fabrication of High‐Density Multimodal Neural Probes Based on Heterogeneously Integrated CMOS

Advanced Science, EarlyView.
A chiplet‐based methodology democratizes active neural probe development on standard bulk CMOS services. This yields the first probe combining high‐density electrophysiology (416 electrodes) with calcium imaging (832 photodiodes) and complete on‐chip signal processing across 13 shanks.
Ju Hee Mun, Miji Kim, Wooyeon Shin, Yongjun Park, Kanghwan Kim, Il‐Joo Cho, Jae Won Shim, Min Soo Kim, Sunwoo Lee, Jeongjin Kim, Changhyuk Lee   +10 more
wiley   +1 more source

Under-Five Undernutrition Prevalence, Its Inequality, Associated Socio-Economic and Demographic Factors in Uganda: Secondary Analysis of 2019/2020 National Panel Data. [PDF]

Nutr Metab Insights
Orech S, Mine MR, Okello F, Nabachenje P, Nankafu B, Uside KA, Lubaale YM.   +6 more
europepmc   +1 more source

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

Low-income families. [PDF]

CMAJ
Perera S, Nadarajah J, van den Heuvel M.
europepmc   +1 more source