Results 31 to 40 of about 3,776 (198)

Integral Operator Defined by k-th Hadamard Product

open access: yesJournal of Mathematical and Fundamental Sciences, 2013
We introduce an integral operator on the class A of analytic functions in the unit disk involving k Æ’{ th Hadamard product (convolution) corresponding to the differential operator defined recently by Al-Shaqsi and Darus.
Maslina Darus, Rabha W. Ibrahim
doaj   +1 more source

New Subclasses of Multivalent Analytic Functions Associated with a Linear Operator

open access: yesAbstract and Applied Analysis, 2013
Making use of a linear operator, which is defined here by means of the Hadamard product (or convolution), we consider two subclasses and of multivalent analytic functions with negative coefficients in the open unit disk. Some modified Hadamard products,
Ding-Gong Yang, Jin-Lin Liu
doaj   +1 more source

The Application of Generalized Quasi-Hadamard Products of Certain Subclasses of Analytic Functions with Negative and Missing Coefficients

open access: yesMathematics, 2019
In this paper, we introduce a new generalized differential operator using a new generalized quasi-Hadamard product, and certain new classes of analytic functions using subordination.
En Ao, Shuhai Li
doaj   +1 more source

Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks

open access: yesAdvanced Science, EarlyView.
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu   +5 more
wiley   +1 more source

A Phase‐Resolved Geometric Deep Learning Framework Maps Structural Determinants of Disease‐Associated Protein Aggregation and Guides Suppressor Design

open access: yesAdvanced Science, EarlyView.
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio   +6 more
wiley   +1 more source

Product of four Hadamard matrices

open access: yesJournal of Combinatorial Theory, Series A, 1992
The authors show the following interesting theorem on Hadamard matrices: If there exist Hadamard matrices of order \(4m\), \(4n\), \(4p\) and \(4q\), then there exists an Hadamard matrix of order \(16mnpq\).
Craigen, R.   +2 more
openaire   +2 more sources

Laser Preset of MnOx Layer on High‐Entropy Alloy Surface for Ampere‐Level Ultra‐Stable OER Performance

open access: yesAdvanced Science, EarlyView.
3D printing enables a high entropy alloy‐derived, in situ formed MnOx overlayer that suppresses oxidation–reconstruction and mitigates anodic dissolution, while enhancing electrolyte wetting and bubble release to accelerate interfacial mass transport and OER kinetics.
Benzhi Wang   +8 more
wiley   +1 more source

MEROMORPHIC FUNCTIONS AND THE HADAMARD PRODUCT

open access: yesDemonstratio Mathematica, 1992
Let \({\mathcal A}\) stand for a set of functions \(F(z)= z^{-1}+a_ 0+a_ 1 z\dots\) holomorphic in the ring \(\mathbb{P}=\{z ...
Jakubowski, Zbigniew J.   +1 more
openaire   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

open access: yesAdvanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy   +8 more
wiley   +1 more source

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