Results 211 to 220 of about 1,074,720 (325)

Simplex polynomial in complex networks and its applications to compute the Euler characteristic. [PDF]

Front Comput Neurosci
Wang Z, Fu X, Deng B, Chen Y, Zhao H.
europepmc   +1 more source

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

Advanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows, G. Zhang, S. Anand, Z. Chen, J. Lin, A. Desai, S. Martiniani, F. Caravelli   +7 more
wiley   +1 more source

Polymer-Metal Hybrid Composites: An Overview of the Role of Metal Architecture. [PDF]

Materials (Basel)
Pavlovic A, Santulli C, Fragassa C.
europepmc   +1 more source

Legume genome structures and histories inferred from Cercis canadensis and Chamaecrista fasciculata genomes. [PDF]

Plant J
Lee HO, Stai JS, Xu Q, Hewavithana T, Soman P, Batra R, Liu A, Jordan BD, Walstead R, Jenkins J, Williams M, Webber J, Grimwood J, Lovell JT, Brůna T, Shu S, Keymanesh K, Eichenberger J, Schmutz J, Goodstein DM, Barry K, Sankoff D, Jin L, Leebens-Mack JH, Cannon SB.   +24 more
europepmc   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

On the topology of conormal complexes and posets of matroids

We introduce the poset of biflats of a matroid $M$, a Lagrangian analog of the lattice of flats of $M$, and study the topology of its order complex, which we call the biflats complex.
Partida, Ethan, Nathanson, Anastasia
core  

A Drift-Aware Clustering and Recovery Strategy for Surface-Deployed Wireless Sensor Networks in Ocean Environments. [PDF]

Sensors (Basel)
Wang L, Hong QX.
europepmc   +1 more source

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

Advanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia, Marcelo A. Dias, Parvez Alam   +2 more
wiley   +1 more source

Zagreb indices of hyper carbon nanotube graphs. [PDF]

Discov Nano
Shabbir A, Nadeem MF, Bashir Y, Husin MN, Muda Y.   +4 more
europepmc   +1 more source

Artificial Intelligence‐Driven Network Pharmacology: A Methodological Paradigm Shift Bridging Traditional Wisdom and Modern Science

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence is redefining network pharmacology (NP). By integrating knowledge graph engineering, geometric deep learning, multiomics anchoring, and generative reasoning, AI‐driven NP (AI‐NP) transforms static target mapping into dynamic, predictive modeling.
Cong Wang, Sile Hu, Rigahai Ji, Riguna A, Siqige Hao, Ma Zhuo, Yi‐Hung Chen, Bisihalatu Hu, Ulana Bai, Xigui Hada   +9 more
wiley   +1 more source