760 research outputs found
A rescaled method for RBF approximation
In the recent paper [8], a new method to compute stable kernel-based
interpolants has been presented. This \textit{rescaled interpolation} method
combines the standard kernel interpolation with a properly defined rescaling
operation, which smooths the oscillations of the interpolant. Although
promising, this procedure lacks a systematic theoretical investigation. Through
our analysis, this novel method can be understood as standard kernel
interpolation by means of a properly rescaled kernel. This point of view allow
us to consider its error and stability properties
A rescaled method for RBF approximation
A new method to compute stable kernel-based interpolants
has been presented by the second and third authors. This rescaled interpolation method combines the
standard kernel interpolation with a properly defined rescaling operation, which
smooths the oscillations of the interpolant. Although promising, this procedure
lacks a systematic theoretical investigation.
Through our analysis, this novel method can be understood as standard
kernel interpolation by means of a properly rescaled kernel. This point of view
allow us to consider its error and stability properties.
First, we prove that the method is an instance of the Shepard\u2019s method,
when certain weight functions are used. In particular, the method can reproduce
constant functions.
Second, it is possible to define a modified set of cardinal functions strictly
related to the ones of the not-rescaled kernel. Through these functions, we
define a Lebesgue function for the rescaled interpolation process, and study its
maximum - the Lebesgue constant - in different settings.
Also, a preliminary theoretical result on the estimation of the interpolation
error is presented.
As an application, we couple our method with a partition of unity algorithm.
This setting seems to be the most promising, and we illustrate its behavior with
some experiments
Neurohumoral stimulation in type-2-diabetes as an emerging disease concept
Neurohumoral stimulation comprising both autonomic-nervous-system dysfunction and activation of hormonal systems including the renin-angiotensin-aldosterone system (RAAS) was found to be associated with Type-2-diabetes (T2D). Therapeutic strategies such as RAAS interference proved to be beneficial in both T2D treatment and prevention. In addition to an activated RAAS, hyperleptinemia in obesity, hyperinsulinemia in conditions of peripheral insulin resistance and overall oxidative stress in T2D represent known activators of the sympathetic component of the autonomic nervous system. Here, we hypothesize that sympathetic activation may cause peripheral insulin resistance defined as partial blocking of insulin effects on glucose uptake. Resulting hyperinsulinemia or hyperglycemia-related oxidative stress may further aggravate sympatho-excitation. This notion leads to a secondary hypothesis: sympathetic activation worsens from obesity towards insulin resistance, and further towards T2D. In this review, existing evidence relating to neurohumoral stimulation in T2D and consequences thereof, such as oxidative stress and inflammation, are discussed. The aim of this review is to provide a rationale for therapies, which are able to intercept neuroendocrine pathways in T2D and precursor states such as obesity
IL METODO DELLE SOLUZIONI FONDAMENTALI PER LA SOLUZIONE DEL PROBLEMA DIRETTO M/EEG
The research already started on the mesh-free solution of the M / EEG direct problem has led to the development of a solver based on the method of fundamental solutions (MFS, method of fundamental solutions) able to manage the physical-geometric complexity of realistic models of the head more efficiently than traditional
An Improved Solver for the M/EEG Forward Problem
Noninvasive investigation of the brain activity via
electroencephalography (EEG) and magnetoencephalography
(MEG) involves a typical inverse problem whose solution process
requires an accurate and fast forward solver. We propose the
Method of Fundamental Solutions (MFS) as a truly meshfree
alternative to the Boundary Element Method (BEM) for solving
the M/EEG forward problem. The solution of the forward
problem is obtained, via the Method of Particular Solutions
(MPS), by numerically solving a set of coupled boundary value
problems for the 3D Laplace equation. Numerical accuracy and
computational load are investigated for spherical geometries and
comparisons with a state-of-the-art BEM solver shows that the
proposed method is competitive
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