OBJECTIVE To determine the prevalence of residual β-cell function (RBF) in children after 3-6 years of type 1 diabetes, and to examine the association between RBF and incidence of severe hypoglycemia, glycemic control, and insulin requirements. RESEARCH DESIGN AND METHODS A total of 342 children (173 boys) 4.8-18.9 years of age with type 1 diabetes for 3-6 years were included. RBF was assesse...

Radial Basis Function (RBF) methods that employ infinitely differentiable basis functions featuring a shape parameter are theoretically spectrally accurate methods for scattered data interpolation and for solving Partial Differential Equations. It is also theoretically known that RBF methods are most accurate when the linear systems associated with the methods are extremely ill-conditioned. Thi...

This study proposes RBF Network hybrid learning with Particle Swarm Optimization for better convergence, error rates and classification results. In conventional RBF Network structure, different layers perform different tasks. Hence, it is useful to split the optimization process of hidden layer and output layer of the network accordingly. RBF Network hybrid learning involves two phases. The fir...

This paper presents an axiomatic approach for constructing radial basis function (RBF) neural networks. This approach results in a broad variety of admissible RBF models, including those employing Gaussian RBF's. The form of the RBF's is determined by a generator function. New RBF models can be developed according to the proposed approach by selecting generator functions other than exponential ...

A novel particle swarm optimisation (PSO) tuned radial basis function (RBF) network model is proposed for identification of non-linear systems. At each stage of orthogonal forward regression (OFR) model construction process, PSO is adopted to tune one RBF unit’s centre vector and diagonal covariance matrix by minimising the leave-one-out (LOO) mean square error (MSE). This PSO aided OFR automat...

Dautzenberg M, Kahnert A, Stasch JP, Just A. Role of soluble guanylate cyclase in renal hemodynamics and autoregulation in the rat. Am J Physiol Renal Physiol 307: F1003–F1012, 2014. First published September 10, 2014; doi:10.1152/ajprenal.00229.2014.—We studied the influence of soluble guanylate (sGC) on renal blood flow (RBF), glomerular filtration rate (GFR), and RBF autoregulation and its r...

this paper extends the sequential learning algorithm strategy of two different types of adaptive radial basis function-based (rbf) neural networks, i.e. growing and pruning radial basis function (gap-rbf) and minimal resource allocation network (mran) to cater for on-line identification of non-linear systems. the original sequential learning algorithm is based on the repetitive utilization of s...

The first appearance of G1 during Drosophila embryogenesis, at cell cycle 17, is accompanied by the down-regulation of E2F-dependent transcription. Mutant alleles of rbf were generated and analyzed to determine the role of RBF in this process. Embryos lacking both maternal and zygotic RBF products show constitutive expression of PCNA and RNR2, two E2F-regulated genes, indicating that RBF is req...

The receptor-binding factor (RBF) for the avian oviduct progesterone (Pg) receptor (PR) has previously been shown to be a unique 10-kDa nuclear matrix protein that generates high affinity PR-binding sites on avian DNA. This paper describes the use of Southwestern blot and DNA gel shift analyses with RBF protein to identify a minimal 54-base pair RBF-binding element in the matrix-associated regi...

Hierarchical RBF networks consist of multiple RBF networks assembled in different level or cascade architecture. In this paper, an evolved hierarchical RBF network was employed to detect the breast cancel. For evolving a hierarchical RBF network model, Extended Compact Genetic Programming (ECGP), a tree-structure based evolutionary algorithm and the Differential Evolution (DE) are used to find ...