Results 151 to 160 of about 344,689 (283)

A Phase‐Resolved Geometric Deep Learning Framework Maps Structural Determinants of Disease‐Associated Protein Aggregation and Guides Suppressor Design

Advanced Science, EarlyView.
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio, Wei Xuan Wilson Loo, Yan Shan Loo, Wen Xin Tan, Hui Xuan Lim, Huitao Liu, Chen Seng Ng   +6 more
wiley   +1 more source

Open-source large language model-based on-premises pipeline for automated data extraction from unstructured electronic health records: a pilot study. [PDF]

BMJ Health Care Inform
Ntinopoulos V, Rodriguez Cetina Biefer H, Rings L, Rosalia RA, Dzemali O.   +4 more
europepmc   +1 more source

Intrinsic Coupling of Radiative Cooling and Triboelectric Responses in Dual‐Function ZrO2 Nanocomposites for Adaptive Thermoregulation

Advanced Science, EarlyView.
A novel nanocomposite design strategy utilizes ZrO2 to intrinsically couple passive daytime radiative cooling and triboelectric functionality within a single material platform. Fabricated via direct ink writing, the multifunctional breathable architecture provides effective sub‐ambient cooling, motion‐driven energy harvesting, and adaptive ...
Yoon Young Choi, Pranto Karua, Md Salauddin, Lili Cai   +3 more
wiley   +1 more source

gender.neutral@work.de: An experimental approach to the discrimination of nonbinary individuals during job applications. [PDF]

Br J Soc Psychol
Dörr L, Ball E, Vogel P, Niedlich C, Steffens MC.   +4 more
europepmc   +1 more source

CauFinder: Steering Cell‐State and Phenotype Transitions by Causal Disentanglement Learning

Advanced Science, EarlyView.
CauFinder combines causal disentanglement modeling and network control to prioritize causal drivers of cell‐state transitions from observational transcriptomic data. The framework separates transition‐relevant signals from spurious associations, nominates intervention targets across biological and disease contexts, and identifies DAAM1 as an actionable
Chengming Zhang, Zexi Chen, Yuanxiang Miao, Zuolin Shen, Deyu Cai, Shijie Tang, Yun Xue, Weifeng Guo, Hongbin Ji, Jian Liu, Kazuyuki Aihara, Luonan Chen   +11 more
wiley   +1 more source

Medical termination of pregnancy (Amendment) Act 2021: From the lenses of LGBTQIA+ community in India

Journal of Family Medicine and Primary Care
The article presents the LGBTQIA + inclusivity analysis of the Medical Termination of Pregnancy (Amendment) Act 2021, which aims to provide safe abortion services across India.
Atul Shendge, Abhishek Royal, Alpana Dange, Vaibhav Kumar   +3 more
doaj  

Dual‐Module Near‐Infrared Fluorophores Discovery System via Knowledge Transfer

Advanced Science, EarlyView.
This study presents a dual‐module deep learning system for the design of near‐infrared (NIR) fluorophores. A large molecular library is generated and analyzed, leading to the suggestions of promising candidates. The effectiveness of the system is further validated through the synthesis, characterization, and in vivo imaging, demonstrating its potential
Yixin Zhu, Xia Ling, Xianhe Zhang, Chuanjiang Jian, Leilei Shi, Wentao Song, Xiaonan Wang, Bin Liu   +7 more
wiley   +1 more source

The Largest Number Representable in 64 Bits. [PDF]

Entropy (Basel)
Tromp J.
europepmc   +1 more source

Causal‐Guided Ultra‐Long‐Term Time Series Forecasting Via Anticipated Covariates

Advanced Science, EarlyView.
Often treated as unknown, information from the future remains underutilized.We demonstrate that in a coupled dynamical system, providing the future state of the effect enables accurate forecasting of the cause for a long timesteps. A time series forecasting paradigm that introduces anticipated covariates to represent such known future states is ...
Jintong Zhao, Yufei Liu, Ruixi Huang, Zhongxue Gan, Siyang Leng   +4 more
wiley   +1 more source

Polarization Dynamics in Ferroelectrics: Insights Enabled by Machine Learning Molecular Dynamics

Advanced Science, EarlyView.
Machine learning molecular dynamics is presented as a route to capture polarization switching, domain wall kinetics, topological polar textures, and polar mechanical coupling beyond the limits of conventional atomistic methods. This Perspective surveys recent progress and identifies key methodological directions, including long‐range electrostatics ...
Dongyu Bai, Ri He, Junxian Liu, Liangzhi Kou   +3 more
wiley   +1 more source