Results 11 to 20 of about 6,958 (188)
Element-wise physics-informed neural network approach for 2D linear elasticity problems
Vietnam Journal of MechanicsPhysics-Informed Neural Networks (PINNs) have emerged as a promising framework for solving solid mechanics problems. Most existing PINN frameworks approximate continuous displacement fields and are trained using collocation points.
Si T. Do, Dai D. Mai
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Spatial biology in cancer epigenetics
Molecular Oncology, EarlyView.Spatial epigenomics combines molecular profiling with tissue architecture to reveal how gene regulation is organized within intact tissues. In cancer, these technologies uncover the mechanisms driving tumor heterogeneity and microenvironmental interactions, opening new opportunities for biomarker discovery and precision medicine.
Eva Crespo‐García, Manel Esteller
wiley +1 more source
FEBS Open Bio, EarlyView.This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill +4 more
wiley +1 more source
Chronobiology of Cancer: How Aging Fuels Oncogenesis at the Molecular Level
Aging and Cancer, EarlyView.This graphical abstract illustrates the key biological pathways linking aging with cancer development and progression. In the upper left, cumulative exposure to ultraviolet radiation, toxins, and reactive oxygen species (ROS) causes DNA damage and genomic instability, whereas age‐related decline in repair mechanisms, such as ATM/ATR, BER, and NER ...
Anu Singh, Aroonima Misra, Sufian Zaheer
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Early Clinical, Imaging, and Pathological Characteristics of SRPK3/TTN‐Digenic Myopathy
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective SRPK3/TTN‐digenic myopathy was recently established as a skeletal muscle myopathy caused by digenic inheritance. This study characterizes the early clinical presentation of SRPK3/TTN‐digenic myopathy in one previously reported and seven newly identified pediatric patients.
Rotem Orbach +23 more
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Quantum Computing: Circuits, Algorithms, and Applications
IEEE AccessQuantum computing, a transformative field that emerged from quantum mechanics and computer science, has gained immense attention for its potential to revolutionize computation.
Muhammad Ali Shafique +2 more
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Advanced Engineering Materials, EarlyView.A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed +6 more
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Advanced Engineering Materials, EarlyView.A simplified thermoplastic pultrusion model is developed to predict thermal fields in glass fiber/polyethylene terephthalate (GF/PET) composites with reduced computational cost. By combining effective material homogenization, validation against literature data, and Gaussian‐process‐based optimization, the study reveals how heating limits, pulling speed,
Elder Soares +3 more
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Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization
Advanced Engineering Materials, EarlyView.Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier +17 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang +2 more
wiley +1 more source