Results 131 to 140 of about 5,625 (248)

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

Advanced Intelligent Systems, EarlyView.
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy, Vitalii Kapitan, Andrey Ustyuzhanin   +2 more
wiley   +1 more source

Dual‐Scale Transformer Fusion With Meta Learning for Micro Metastasis Detection in Thyroid Cancer

Advanced Intelligent Systems, EarlyView.
A dual‐scale transformer model enhanced by meta‐learning enables accurate detection of tiny metastatic lesions in thyroid cancer. By combining cellular and tissue‐level features, the method outperforms existing models and shows strong adaptability to rare cases with limited data.
Jingtao Wang, Junhai Shi, Hengli Ni, Limei Zhao, Jing Huang, Jianming Li   +5 more
wiley   +1 more source

A New Fuzzy Logic Classifier Based on Multiscale Permutation Entropy and Its Application in Bearing Fault Diagnosis. [PDF]

Entropy (Basel), 2019
Du W, Guo X, Wang Z, Wang J, Yu M, Li C, Wang G, Wang L, Guo H, Zhou J, Shao Y, Xue H, Yao X.   +12 more
europepmc   +1 more source

Material‐Based Intelligence: Autonomous Adaptation and Embodied Computation in Physical Substrates

Advanced Intelligent Systems, EarlyView.
This perspective formulates a unifying framework for Material‐Based Intelligence (MBI), defining the physical requirements for materials to achieve embodied action, active memory and embodied information processing through intrinsic nonequilibrium dynamics. The design of intelligent materials often draws parallels with the complex adaptive behaviors of
Vladimir A. Baulin, Rudolf M. Füchslin, Achille Giacometti, Helmut Hauser, Marco Werner   +4 more
wiley   +1 more source

Deformable Attention Multiscale Feature Fusion Network‐Dehaze: An Adaptive Image Dehazing Method Based on Deformable Attention Multiscale Fusion Network

Advanced Intelligent Systems, EarlyView.
This paper presents the deformable attention multiscale feature fusion network‐dehaze adaptive image dehazing network, which integrates three core modules (revised residual shrinkage unit, multiscale attention, cross‐scale feature fusion). It incorporates deformable convolution and multiscale attention mechanisms to address the detail loss issue of ...
Ruipeng Wang, Yajun Chen, Hao Liu, Mingrui Li, Zhiqi Li   +4 more
wiley   +1 more source

Mucin Glycoprotein Nanoparticles Enable a Selective Antisense Therapy for Oncogenic MicroRNAs

Advanced NanoBiomed Research, EarlyView.
Mucin glycoproteins are turned into nanoparticles by employing synthetic DNA strands, which have a dual function: they stabilize the nanoparticles and act as binding sites for intracellular miRNA‐21. Thus, upon internalization into tumor cells, these mucin nanoparticles can deplete miRNA‐21 from the cytosol, which induces apoptosis in vitro and in vivo.
Ceren Kimna, Thomas Mayer, Di Zhang, Matthias Marczynski, Carolin A. Rickert, Fabio Henkel, Lennart J. K. Weiss, Friedrich C. Simmel, Yuxia Luan, Oliver Lieleg   +9 more
wiley   +1 more source

Optimized Dynamic Mode Decomposition via Non-Convex Regularization and Multiscale Permutation Entropy. [PDF]

Entropy (Basel), 2018
Dang Z, Lv Y, Li Y, Yi C.
europepmc   +1 more source

Prospecting of Architectural Features Using LiDAR‐UAV Technology, Deep Neural Networks and Visualization Techniques: A Case Study in Kuélap and Cambolín (NW Peru)

Archaeological Prospection, EarlyView.
ABSTRACT High‐resolution and accurate synoptic images of terrestrial topography, even in densely forested areas, have proven valuable for archaeology by enabling the identification and characterization of relief patterns associated with ancient human activities. This study presents a novel approach that integrates digital terrain models (DTMs) obtained
Jhon A. Zabaleta‐Santisteban, Rolando Salas López, Angel J. Medina‐Medina, Katerin M. Tuesta‐Trauco, Abner S. Rivera‐Fernandez, Nerci M. Noriega‐Salazar, José A. Sánchez‐Vega, Teodoro B. Silva‐Melendez, Marlen A. Grandez‐Alberca, Jhonsy O. Silva‐López, Nilton B. Rojas‐Briceño, Manuel Oliva‐Cruz, Alexander Cotrina‐Sanchez, Elgar Barboza   +13 more
wiley   +1 more source

Multimodal Integration of Protein Interactomes With Genomic and Molecular Data Discovers Distinct Rheumatoid Arthritis Endotypes

Arthritis &Rheumatology, EarlyView.
Objective Rheumatoid arthritis (RA) is a heterogeneous autoimmune disease characterized by clinical and molecular heterogeneity, notably in the presence of anti–cyclic citrullinated peptide (CCP) antibodies. Patients with CCP+ RA exhibit more severe disease progression and distinct treatment responses compared to patients with CCP− RA.
Javad Rahimikollu, Priyamvada Guha Roy, Akash Kishore, Danica Morgan Lee, Lauren A. Vanderlinden, Kiran Nazarali, Fan Zhang, Dana P. Ascherman, Daniella M. Schwartz, Larry Moreland, Jishnu Das   +10 more
wiley   +1 more source

Design Strategies for Electrolytes in Lithium Metal Batteries: Insights into Liquid and Solid‐State Systems

Batteries &Supercaps, EarlyView.
This review systematically analyzes electrolyte design strategies for lithium metal batteries, covering both liquid and solid‐state systems in parallel. Liquid strategies such as high‐concentration, fluorinated, and additive‐engineered electrolytes are discussed, as well as polymer‐, ceramic‐, and composite‐based solid electrolytes, highlighting their ...
Un Hwan Lee, Seonhye Park, Joonhee Kang
wiley   +1 more source