Results 61 to 70 of about 3,979 (237)

UniMR: A Plug‐and‐Play Framework of Automated Molecular Recognition for Scanning Tunneling Microscopy

Advanced Science, EarlyView.
UniMR, a training‐free framework for automated molecular recognition in STM images. By integrating adaptive feature selection with CLIP embeddings and Gaussian Mixture Modeling, UniMR achieves robust performance across diverse molecular systems and low‐resolution conditions.
Ziqiang Cao, Lingyin Zhang, Bingzheng Wu, Haonan Chen, Junhao Sun, Linghao Yan, Wenfei Li, Yangyang Wu, Zhifang Wang, Qigang Zhong, Lifeng Chi   +10 more
wiley   +1 more source

Conversion of Transplanted Mature Hepatocytes into Afp+ Reprogrammed Cells for Liver Regeneration After Injury

Advanced Science, EarlyView.
Donor‐derived tdTomato+ mature hepatocytes were FACS‐isolated and transplanted into Fah−/− host mice. During regeneration, these cells convert into proliferative, unipotent Afp+ rHeps. Their plasticity is governed by a PPARγ/AFP‐dependent metabolic switch, segregating into pro‐proliferative Afplow and pro‐survival Afphigh subpopulations.
Ting Fang, Chao Yang, Hua Qiu, Yuan Du, Xicheng Wang, Yuting Li, Mingyang Xu, Changcheng Liu, Xiuhua Li, Na Guo, Jun Shi, Wencheng Zhang, Zhiying He   +12 more
wiley   +1 more source

Representation and structuring of knowledge in the semantic oriented computing environment. Part 1. Integration conceptual graphs and logical networks based on formalization of structured situations

Известия высших учебных заведений. Поволжский регион:Технические науки, 2023
Background. A technique for deep knowledge structuring in a semantic-oriented intelligent computing environment based on the expansion of the descriptive capabilities of Petri nets by integrating them with conceptual graphs is proposed.
V.I. Volchikhin, N.S. Karamysheva, M.A. Mitrokhin, S.A. Zinkin   +3 more
doaj   +1 more source

Biomechanics‐Driven 3D Architecture Inference from Histology Using CellSqueeze3D

Advanced Science, EarlyView.
CellSqueeze3D reconstructs 3D cellular architecture from standard 2D histology images using biomechanical constraints and optimization. Validated on clinical datasets, it enables accurate tissue phenotyping, predicts gene mutations, and reveals significant correlations between nuclear‐cytoplasmic ratio entropy and tumor progression.
Yan Kong, Hui Lu
wiley   +1 more source

Notes on Modified Planar Kelvin–Stuart Models: Simulations, Applications, Probabilistic Control on the Perturbations

Axioms
In this paper, we propose a new modified planar Kelvin–Stuart model. We demonstrate some modules for investigating the dynamics of the proposed model.
Nikolay Kyurkchiev, Tsvetelin Zaevski, Anton Iliev, Vesselin Kyurkchiev, Asen Rahnev   +4 more
doaj   +1 more source

Disentangling the relationships between denomination of origin regulatory councils activities and Spanish wineries' export performance

Agribusiness, EarlyView.
Abstract World markets for quality differentiated agri‐food products are highly competitive, presenting significant challenges for firms aiming to compete effectively. Government agencies and business organizations often implement various export promotion policies to address these challenges.
Nicolás Depetris‐Chauvin, Marta Fernández‐Olmos   +1 more
wiley   +1 more source

Creating Shared Value as an Antecedent of Value Co‐Creation: B2B Relationships in the Agri‐Food Sector

Agribusiness, EarlyView.
ABSTRACT This study analyzes the effects of value co‐creation and creation of shared value in agricultural input marketing. This study used a sample of 178 agricultural companies in Costa Rica. The data were analyzed using partial least squares structural equation modeling (PLS‐SEM) with SMART PLS software. Our findings reveal the significant influence
Luis Ricardo Solís‐Rivera, Marcelo Royo‐Vela   +1 more
wiley   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Named Entity Recognition Models for Machine Learning Interatomic Potentials: A User‐Centric Approach to Knowledge Extraction from Scientific Literature

Advanced Intelligent Discovery, EarlyView.
Named entity recognition pipeline for knowledge extraction from scientific literature. Machine learning interatomic potential (MLIP) is an emerging technique that has helped achieve molecular dynamics simulations with unprecedented balance between efficiency and accuracy. Recently, the body of MLIP literature has been growing rapidly, which propels the
Bowen Zheng, Grace X. Gu
wiley   +1 more source

Practical Access to Dynamic Programming on Tree Decompositions

Algorithms, 2019
Parameterized complexity theory has led to a wide range of algorithmic breakthroughs within the last few decades, but the practicability of these methods for real-world problems is still not well understood.
Max Bannach, Sebastian Berndt
doaj   +1 more source