Results 221 to 230 of about 507,216 (286)

Automatic Determination of Quasicrystalline Patterns from Microscopy Images

Advanced Intelligent Discovery, EarlyView.
This work introduces a user‐friendly machine learning tool to automatically extract and visualize quasicrystalline tiling patterns from atomically resolved microscopy images. It uses feature clustering, nearest‐neighbor analysis, and support vector machines. The method is broadly applicable to various quasicrystalline systems and is released as part of
Tano Kim Kender, Marco Corrias, Cesare Franchini   +2 more
wiley   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source

Expression graph network framework for biomarker discovery. [PDF]

Brief Bioinform
Liu Y, Huse J, Kannan K.
europepmc   +1 more source

The excluded minor theorem for the Petersen graph contracting exactly two edges of a perfect matching and one other edge

Yuqi Xu, Linsong Wei, Weihua Yang
openalex   +1 more source

Perfect Dominating Sets in Fuzzy Graphs

, 2013
Assistant Professor,Department of Mathematics,Saranathan College of Engineering, Trichy, Tamilmadu, India
openalex   +1 more source

Inverse Design of Alloys via Generative Algorithms: Optimization and Diffusion within Learned Latent Space

Advanced Intelligent Discovery, EarlyView.
This work presents a novel generative artificial intelligence (AI) framework for inverse alloy design through operations (optimization and diffusion) within learned compact latent space from variational autoencoder (VAE). The proposed work addresses challenges of limited data, nonuniqueness solutions, and high‐dimensional spaces.
Mohammad Abu‐Mualla, Ellis Crabtree, Fredrick Michael, Yayue Pan, Jida Huang   +4 more
wiley   +1 more source

Development and validation of a nomogram model for assessing the severity of acute pancreatitis from the perspective of PICS. [PDF]

Front Nutr
Liu D, Liu H, Yao J, Chen G, Wang W, Cao B, Hu J, Wu W.   +7 more
europepmc   +1 more source

Connected greedy colourings of perfect graphs and other classes: the good, the bad and the ugly [PDF]

Laurent Beaudou, Caroline Brosse, Oscar Defrain, Florent Foucaud, Aurélie Lagoutte, Vincent Limouzy, Lucas Pastor   +6 more
openalex   +1 more source

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source

A Complete Energy Model for Graphene Flake Growth with the Fewest Possible Dangling Bonds. [PDF]

Nanomaterials (Basel)
Grozev IG, Kalchevski DA, Trifonov DV, Kolev SK, Aleksandrov HA, Popov VN, Milenov TI.   +6 more
europepmc   +1 more source