Results 71 to 80 of about 5,352,010 (246)
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
POTENTIAL REDUCTION METHOD FOR HARMONICALLY CONVEX-PROGRAMMING
, 1995 In this paper, we introduce a potential reduction method for harmonically convex programming. We show that, if the objective function and the m constraint functions are all k-harmonically convex in the feasible set, then the number of iterations needed ...
Zhang, S (Shuzhong), ZHANG, S, STURM, JF
core +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
Advanced Intelligent Discovery, EarlyView.This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
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Zhejiang Daxue xuebao. Lixue ban, 2018 Based on the theory of local fractional calculus on fractal sets,the author established an identity involving local fractional integrals. Using the identity, some generalized Ostrowski type inequalities for generalized harmonically s-convex functions ...
SUNWenbing(孙文兵)
doaj +1 more source
A Critical Assessment of Bonding Descriptors for Predicting Materials Properties
Advanced Intelligent Discovery, EarlyView.The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik +6 more
wiley +1 more source
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.Quantitative phase maps of single cells recorded in flow cytometry modality feed a hierarchical architecture of machine learning models for the label‐free identification of subtypes of ovarian cancer. The employment of a priori clinical information improves the classification performance, thus emulating the clinical application of liquid biopsy during ...
Daniele Pirone +11 more
wiley +1 more source
Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers
Advanced Intelligent Systems, EarlyView.Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica +38 more
wiley +1 more source
Janowski harmonic close-to-convex functions
International Journal of Mathematical Analysis, 2014 A harmonic mapping in the open unit disc D{double-struck} = {z||z| < 1} onto domain Ω* ⊂ ℂ is a complex valued harmonic function w = f(z) which maps D{double-struck} univalently Ω*. Each such mapping has a canonical representation f(z) = h(z) + g(z), where h(z) and g(z) are analytic in D{double-struck} and h(0) = g(0) = 0, and are called analytic part ...
Turhan, N. +2 more
openaire +2 more sources
Advanced Physics Research, EarlyView.The electronic band structure determines all the charge transport properties of crystalline solids. It also controls the optical response of the material. Bonding characters are strongly influenced by the band structure. The band structures of Mg2TmH6 (Tm = Rh, Pd, Ir, Pt) compounds shown above confirm their metallic nature.
Md Ashraful Alam +3 more
wiley +1 more source
The Anatomical Record, EarlyView.Abstract The human mandibular symphysis concentrates multiaxial loads during function and remodels throughout growth, but the precise mechanisms underlying cortical bone shape during growth remain relatively unexplored. Approaches based solely on thickness or external cortical contours provide only partial insights and do not capture the functional ...
Ana Ribeiro +3 more
wiley +1 more source