Results 91 to 100 of about 10,090 (236)

A Circuit of Mechanically Regulated Transcription Factors Balances Regenerative and Fibrotic Memory of Mesenchymal Stromal Cells

Advanced Science, EarlyView.
Producing MSCs on rigid culture substrates induces a scar‐making phenotype, jeapordizing therapeutic success. ‘Tissue‐soft’ surfaces prevent MSC fibrogenesis and preserve regenerative traits. An epigenetic network, driven by HOXA11 and SALL1, maintains ‘soft memory’ by keeping chromatin open in relaxed MSCs, promoting anti‐fibrotic programs.
Fereshteh Sadat Younesi, Andrew E. Miller, Li Diao, Xinying Guo, Natalie Andonian, Elham Karimizadeh, Thomas H. Barker, Boris Hinz   +7 more
wiley   +1 more source

Organizational Learning Process in Single, Double and Triple Loop Companies in a Post-Crisis Situation in the Textile Sector in Tunisia

Journal of Entrepreneurship & Organization Management, 2017
It is an “exploratory” research that tries to determine the most adopted organizational learning processes in postcrisis Textile companies in Tunisia to guarantee their continuity and their survival. The research methodology is summarized by the following steps: • Exploratory qualitative study (non-formal because of the refusal to allow recorded ...
openaire   +1 more source

Cross‐Modal Denoising and Integration of Spatial Multi‐Omics Data with CANDIES

Advanced Science, EarlyView.
In this paper, we introduce CANDIES, which leverages a conditional diffusion model and contrastive learning to effectively denoise and integrate spatial multi‐omics data. We conduct extensive evaluations on diverse synthetic and real datasets, CANDIES shows superior performance on various downstream tasks, including denoising, spatial domain ...
Ye Liu, Wanpeng Zou, Yuekai Li, Jiayi Wang, Mingxuan Cai, Hongmin Cai   +5 more
wiley   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

The Role of Triple-Loop Learning in the Adoption of Digital Carbon Footprint : The Invisible Environmental Impact of Digital Services Companies

, 2021
The global demand for digital services has been growing steadily, which has led to an increase in the utilization of data and consumption of energy, causing an increment of the global digital carbon footprint. Therefore, corporations providing digital services are gradually enforced to be able to measure and quantify their digital carbon footprint ...
Mignoli, Viola, Naerbout, Nathalie Ehlerts   +1 more
openaire   +1 more source

Harnessing Phase Separation for the Development of High‐Performance Hydrogels

Advanced Science, EarlyView.
ABSTRACT Hydrogels are indispensable for the development of next‐generation bioelectronics, soft robotics, and biomedical devices, where their mechanical properties determine performance and reliability. Among strategies to enhance hydrogel mechanics, phase separation enables controlled heterogeneity resulting in gel networks that are reinforced by ...
Yue Shao, Yiming Ma, Baihao Shao, Molly M. Stevens   +3 more
wiley   +1 more source

DNA Nanoarray for Multiplexed RNA Detection With Single‐Molecule Readout

Advanced Science, EarlyView.
A carrier‐based DNA nanoarray integrates programmable nucleic acid hybridization with solid‐state nanopore readout for direct RNA detection at single‐molecule resolution. A ternary encoding system enables 27 carriers with 81 addressable sensing sites, allowing the simultaneous identification of targets spanning a wide size range, from short microRNAs ...
Yunxuan Li, Yesheng Wang, Chunmiao Yu, Siyu Hou, Elli Mylona, Plamena Naydenova, Jingyuan Zhao, Hong Yuan, Jingsong Duan, Hendrik F. P. Runge, Stephen Baker, Jinbo Zhu, Ulrich F. Keyser   +12 more
wiley   +1 more source

Revisiting Target‐Aware de novo Molecular Generation with TarPass: Between Rational Design and Texas Sharpshooter

Advanced Science, EarlyView.
TarPass provides a rigorous benchmark for target‐aware de novo molecular generation by jointly evaluating protein‐ligand interactions, molecular plausibility, and drug‐likeness on 18 well‐studied targets. Results show that current models often fail to consistently surpass random baseline in target‐specific enrichment, while post hoc multi‐tier virtual ...
Rui Qin, Zijie Chen, Yurong Li, Meijing Fang, Longji Shen, Yilong Su, Odin Zhang, Qinghan Wang, Qun Su, Jike Wang, Tingjun Hou, Yu Kang   +11 more
wiley   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Advanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang, Waleed Mohammed, Dierk Raabe   +2 more
wiley   +1 more source

STAID: A Self‐Refining Deep Learning Framework for Spatial Cell‐Type Deconvolution with Biologically Informed Modeling

Advanced Science, EarlyView.
STAID is a unified deep learning framework that couples iterative pseudo‐spot refinement with neural network training through a feedback loop and exploits gene co‐expression information to model higher‐order interactions, achieving accurate and robust cell‐type deconvolution in spatial transcriptomics.
Jixin Liu, Shuli Sun, Zhengliang Lv, Xinyu Liu, Yihua Wang, Bingqiang Liu   +5 more
wiley   +1 more source