Results 11 to 20 of about 16,403 (208)

Mean and variance heterogeneity loci impact kernel compositional traits in maize. [PDF]

Plant Genome
Abstract Maize (Zea mays) kernel composition is critical for food, feed, and industrial applications. Improving traits such as starch, protein, oil, fiber, and ash requires understanding their genetic basis. We conducted genome‐wide association studies (GWAS) and variance genome‐wide association studies (vGWAS) analyses using 954 inbred lines from the ...
Ismail YMA, Mujjabi C, Olatoye MO, Gray S, Lipka AE, Bohn MO.   +5 more
europepmc   +2 more sources

Meshless Galerkin method based on RBFs and reproducing Kernel for quasi-linear parabolic equations with dirichlet boundary conditions

Mathematical Modelling and Analysis, 2021
The main aim of this paper is to present a hybrid scheme of both meshless Galerkin and reproducing kernel Hilbert space methods. The Galerkin meshless method is a powerful tool for solving a large class of multi-dimension problems.
Mehdi Mesrizadeh, Kamal Shanazari
doaj   +1 more source

Benefits of Open Quantum Systems for Quantum Machine Learning

Advanced Quantum Technologies, EarlyView., 2023
Quantum machine learning (QML), poised to transform data processing, faces challenges from environmental noise and dissipation. While traditional efforts seek to combat these hindrances, this perspective proposes harnessing them for potential advantages. Surprisingly, under certain conditions, noise and dissipation can benefit QML.
María Laura Olivera‐Atencio, Lucas Lamata, Jesús Casado‐Pascual   +2 more
wiley   +1 more source

A novel method for fractal-fractional differential equations

Alexandria Engineering Journal, 2022
We consider the reproducing kernel Hilbert space method to construct numerical solutions for some basic fractional ordinary differential equations (FODEs) under fractal fractional derivative with the generalized Mittag–Leffler (M-L) kernel.
Nourhane Attia, Ali Akgül, Djamila Seba, Abdelkader Nour, Jihad Asad   +4 more
doaj   +1 more source

Aveiro method in reproducing kernel Hilbert spaces under complete dictionary [PDF]

Mathematical Methods in the Applied Sciences, 2017
Aveiro method is a sparse representation method in reproducing kernel Hilbert spaces, which gives orthogonal projections in linear combinations of reproducing kernels over uniqueness sets. It, however, suffers from determination of uniqueness sets in the underlying reproducing kernel Hilbert space.
Weixiong Mai, Tao Qian
openaire   +4 more sources

Path Integrals on Euclidean Space Forms [PDF]

, 2015
In this paper we develop a quantization method for flat compact manifolds based on path integrals. In this method the Hilbert space of holomorphic functions in the complexification of the manifold is used. This space is a reproducing kernel Hilbert space.
Capobianco, Guillermo, Reartes, Walter
core   +1 more source

A pseudo-spectral method based on reproducing kernel for solving the time-fractional diffusion-wave equation [PDF]

, 2022
In this paper, we focus on the development and study of the finite difference/pseudo-spectral method to obtain an approximate solution for the time-fractional diffusion-wave equation in a reproducing kernel Hilbert space.
Al-Omari, Shrideh K. Qasem, Aracı, Serkan, Fardi, Mojtaba   +2 more
core   +1 more source

Noncanonical Quantization of Gravity. I. Foundations of Affine Quantum Gravity [PDF]

, 1999
The nature of the classical canonical phase-space variables for gravity suggests that the associated quantum field operators should obey affine commutation relations rather than canonical commutation relations. Prior to the introduction of constraints, a
DeWitt B. S., Echeverria-Enriquez A., Gel’fand I. M., John R. Klauder   +3 more
core   +3 more sources

A Novel Method for Solutions of Fourth-Order Fractional Boundary Value Problems

Fractal and Fractional, 2019
In this paper, we find the solutions of fourth order fractional boundary value problems by using the reproducing kernel Hilbert space method. Firstly, the reproducing kernel Hilbert space method is introduced and then the method is applied to this kind ...
Ali Akgül, Esra Karatas Akgül
doaj   +1 more source

Soft and hard classification by reproducing kernel Hilbert space methods [PDF]

Proceedings of the National Academy of Sciences, 2002
Reproducing kernel Hilbert space (RKHS) methods provide a unified context for solving a wide variety of statistical modelling and function estimation problems. We consider two such problems: We are given a training set { y i ,
openaire   +3 more sources