Simultaneous Representation Learning of Multi-Omics and Clinical Outcome Data via a Supervised Knowledge-Guided Bayesian Factor Model. [PDF]
Zhang Q, Chang C, Jin C, Shen L, Long Q.
europepmc +1 more source
Influence of Geometric Design on Mechanical Performance of Auxetic Metastructure
Strategic geometric reinforcement transforms auxetic performance. This study evaluates 3D‐printed arrowhead metastructures, revealing that a modified design with local ring reinforcement suppresses premature failure to achieve superior energy absorption and structural efficiency.
Muhammad Gulzari +3 more
wiley +1 more source
A dual diffusion model-based representation learning framework for antimicrobial peptides classification. [PDF]
Kong W, Fu L, Jiang X, Zhao W.
europepmc +1 more source
A Dislocation Perspective on Strength and Toughness in Ceramics
Dislocations in ceramics enjoy a long but yet under‐appreciated history. The three research waves for dislocations in ceramics highlight the topic evolution over the last 90 years. This review focuses on the impact of dislocation on strength and toughness in ceramics.
Xufei Fang
wiley +1 more source
Multi-to-uni modal knowledge transfer pre-training for molecular representation learning. [PDF]
Xiong Z +9 more
europepmc +1 more source
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source
Graph latent diffusion-based molecular representation learning for enhanced generalization in molecular property prediction. [PDF]
Koge D, Ono N, Abe T, Kanaya S.
europepmc +1 more source
Stretching the Printability Metric in Direct‐Ink Writing with Highly Extensible Yield‐Stress Fluids
This study introduces “drawability” as a new metric for assessing printability in direct‐ink writing, focusing on gap‐spanning performance and speed robustness. By designing yield‐stress fluids with high extensibility, we demonstrate that extensional strain‐to‐break significantly enhances printability.
Chaimongkol Saengow +9 more
wiley +1 more source
IRN2Vec: A representation learning model for road network intersections by integrating geospatial attributes and travel behaviors. [PDF]
Yang X.
europepmc +1 more source
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone +11 more
wiley +1 more source

