Results 51 to 60 of about 148,863 (263)

Solving a System of Linear Volterra Integral Equations Using the Modified Reproducing Kernel Method

Abstract and Applied Analysis, 2013
A numerical technique based on reproducing kernel methods for the exact solution of linear Volterra integral equations system of the second kind is given.
Li-Hong Yang, Hong-Ying Li, Jing-Ran Wang   +2 more
doaj   +1 more source

Natural Frequencies of Levodopa‐Induced Dyskinesia in Parkinson's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Abnormal involuntary movements, known as dyskinesias, are common complications of levodopa treatment in patients with Parkinson's disease and can significantly impair quality of life. The underlying pathophysiology remains unclear, and current therapeutic options are limited.
Ioannis U. Isaias, Federica Avantaggiato, Gianni Pezzoli, Andrea Canessa   +3 more
wiley   +1 more source

The computation of the viability kernel for switched systems

Advances in Difference Equations, 2018
The computation of the viability kernel provides the guarantee for the security evolution of the systems. In this paper, we focus on the computation of the viability kernel for discrete-time and continuous-time switched systems.
Jianfeng Lv, Yan Gao
doaj   +1 more source

Stage‐Dependent β‐Synuclein Links MRI and Cognitive Decline in Alzheimer's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Synaptic degeneration drives cognitive decline in Alzheimer's disease (AD), but synaptic biomarkers are scarce. Brain‐enriched β‐synuclein emerged as a synaptic damage marker. We investigated its diagnostic, prognostic, and structural correlates across the AD continuum.
Ulaş Ay, Merve Alaylioglu, Erdi Sahin, Sanem Sultan Yoruk Oner, Gulce Iskan, Gulce Cosku Yilmaz Cakan, Gozde Kizilates‐Evin, Emre Hari, Elif Kurt, Erdinc Dursun, Basar Bilgic, Hasmet Hanagasi, Hakan Gurvit, Tamer Demiralp, Duygu Gezen‐Ak, Bedia Samanci   +15 more
wiley   +1 more source

Consistency of Restricted Maximum Likelihood Estimators in High-Dimensional Kernel Linear Mixed-Effects Models with Applications in Estimating Genetic Heritability

Mathematics
Restricted maximum likelihood (REML) estimators are commonly used to obtain unbiased estimators for the variance components in linear mixed models. In modern applications, particularly in genomic studies, the dimension of the design matrix with respect ...
Xiaoxi Shen, Qing Lu
doaj   +1 more source

Invertibility of Generalized Space-Time Autoregressive Model with Random Weight

Cauchy: Jurnal Matematika Murni dan Aplikasi, 2021
The generalized linear process accomplishes stationarity and invertibility properties. The invertibility property must be having a series of convergence conditions of the process parameter.
Yundari Yundari, Setyo Wira Rizki
doaj   +1 more source

CSF Cytokine Network Organization Predicts Progression Independent of Relapse and MRI Activity in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Progression independent of relapse activity is a major determinant of long‐term disability in multiple sclerosis, but its immunopathologic basis remains incompletely understood. We investigated whether relapse‐independent progression in radiologically stable relapsing–remitting multiple sclerosis is associated with distinct ...
Antonio Bruno, Matteo Conti, Ettore Dolcetti, Federica Azzolini, Angela Borrelli, Roberta Fantozzi, Mario Stampanoni Bassi, Giovanni Galifi, Giuseppe Maccarrone, Luca Montaguti, Marco Cervigni, Maddalena Dal Pozzo, Roberto Furlan, Annamaria Finardi, Girolama Alessandra Marfia, Marco Salvetti, Antonella Conte, Fabio Buttari, Diego Centonze, Luana Gilio   +19 more
wiley   +1 more source

Linear Kernels and Linear-Time Algorithms for Finding Large Cuts [PDF]

Algorithmica, 2017
The maximum cut problem in graphs and its generalizations are fundamental combinatorial problems. Several of these cut problems were recently shown to be fixed-parameter tractable and admit polynomial kernels when parameterized above the tight lower bound measured by the size and order of the graph.
Michael Etscheid, Matthias Mnich
openaire   +4 more sources

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga   +2 more
wiley   +1 more source

Linear Kernels for Outbranching Problems in Sparse Digraphs [PDF]

Algorithmica, 2016
Extended abstract accepted for IPEC'15, 27 ...
Marthe Bonamy, Lukasz Kowalik, Michal Pilipczuk, Arkadiusz Socala   +3 more
openaire   +5 more sources