Two-stage mixed discrete-continuous identification of radial basis function (RBF) neural models for nonlinear systems

The identification of nonlinear dynamic systems using radial basis function (RBF) neural models is studied in this paper. Given a model selection criterion, the main objective is to effectively and efficiently build a parsimonious compact neural model that generalizes well over unseen data. This is achieved by simultaneous model structure selection and optimization of the parameters over the continuous parameter space. It is a mixed-integer hard problem, and a unified analytic framework is proposed to enable an effective and efficient two-stage mixed discrete-continuous; identification procedure. This novel framework combines the advantages of an iterative discrete two-stage subset selection technique for model structure determination and the calculus-based continuous optimization of the model parameters. Computational complexity analysis and simulation studies confirm the efficacy of the proposed algorithm.

Neural Network Modeling of Rheological Parameters of Grouts Containing Viscosity-Modifying Agent

The development of artificial neural network (ANN) models to predict the rheological behavior of grouts is described is this paper and the sensitivity of such parameters to the variation in mixture ingredients is also evaluated. The input parameters of the neural network were the mixture ingredients influencing the rheological behavior of grouts, namely the cement content, fly ash, ground-granulated blast-furnace slag, limestone powder, silica fume, water-binder ratio (w/b), high-range water-reducing admixture, and viscosity-modifying agent (welan gum). The six outputs of the ANN models were the mini-slump, the apparent viscosity at low shear, and the yield stress and plastic viscosity values of the Bingham and modified Bingham models, respectively. The model is based on a multi-layer feed-forward neural network. The details of the proposed ANN with its architecture, training, and validation are presented in this paper. A database of 186 mixtures from eight different studies was developed to train and test the ANN model. The effectiveness of the trained ANN model is evaluated by comparing its responses with the experimental data that were used in the training process. The results show that the ANN model can accurately predict the mini-slump, the apparent viscosity at low shear, the yield stress, and the plastic viscosity values of the Bingham and modified Bingham models of the pseudo-plastic grouts used in the training process. The results can also predict these properties of new mixtures within the practical range of the input variables used in the training with an absolute error of 2%, 0.5%, 8%, 4%, 2%, and 1.6%, respectively. The sensitivity of the ANN model showed that the trend data obtained by the models were in good agreement with the actual experimental results, demonstrating the effect of mixture ingredients on fluidity and the rheological parameters with both the Bingham and modified Bingham models.

Effects of IL-13 on Mucociliary Differentiation of Pediatric Asthmatic Bronchial Epithelial Cells

Goblet cell hyperplasia (GCH) and decreased ciliated cells are characteristic of asthma. We examined the effects of IL-13 (2 and 20 ng/mL) on in vitro mucociliary differentiation in pediatric bronchial epithelial cells (PBECs) of normal PBEC [PBEC(N)] and asthmatic PBEC [PBEC(A)] children. Markers of differentiation, real-time PCR for MUC5AC, MUC5AC ELISA, and transepithelial electrical resistance (TEER) were assessed. Stimulation with 20 ng/mL IL-13 in PBEC(N) resulted in GCH [20 ng/mL IL-13: mean, 33.8% (SD, 7.2) versus unstimulated: mean, 18.9% (SD, 5.0); p < 0.0001] and decreased ciliated cell number [20 ng/mL IL-13: mean, 8% (SD, 5.6) versus unstimulated: mean, 22.7% (SD,7.6); p < 0.01]. PBEC(N) stimulated with 20 ng/mL IL-13 resulted in >5-fold (SD, 3.2) increase in MUC5AC mRNA expression, p < 0.001, compared with unstimulated PBEC(N). In PBEC(A), GCH was also seen [20 ng/mL IL-13: mean, 44.7% (SD, 16.4) versus unstimulated: mean, 30.4% (SD, 13.9); p < 0.05] with a decreased ciliated cell number [20 ng/mL IL-13: mean, 8.8% (SD, 7.5) versus unstimulated: mean, 16.3% (SD, 4.2); p < 0.001]. We also observed an increase in MUC5AC mRNA expression with 20 ng/mL IL-13 in PBEC(A), p < 0.05. IL-13 drives PBEC(N) toward an asthmatic phenotype and worsens the phenotype in PBEC(A) with reduced ciliated cell numbers and increased goblet cells.

Neural network forecasts of input-output technology

A significant part of the literature on input-output (IO) analysis is dedicated to the development and application of methodologies forecasting and updating technology coefficients and multipliers. Prominent among such techniques is the RAS method, while more information demanding econometric methods, as well as other less promising ones, have been proposed. However, there has been little interest expressed in the use of more modern and often more innovative methods, such as neural networks in IO analysis in general. This study constructs, proposes and applies a Backpropagation Neural Network (BPN) with the purpose of forecasting IO technology coefficients and subsequently multipliers. The RAS method is also applied on the same set of UK IO tables, and the discussion of results of both methods is accompanied by a comparative analysis. The results show that the BPN offers a valid alternative way of IO technology forecasting and many forecasts were more accurate using this method. Overall, however, the RAS method outperformed the BPN but the difference is rather small to be systematic and there are further ways to improve the performance of the BPN.

Genetic differentiation across the social transition in a socially polymorphic sweat bee, Halictus rubicundus

Eusociality is widely considered a major evolutionary transition. The socially polymorphic sweat bee Halictus rubicundus, solitary in cooler regions of its holarctic range and eusocial in warmer parts, is an excellent model organism to address this transition, and specifically the question of whether sociality is associated with a strong barrier to gene flow between phenotypically divergent populations. Mitochondrial DNA (COI) from specimens collected across the British Isles, where both solitary and social phenotypes are represented, displayed limited variation, but placed all specimens in the same European lineage; haplotype network analysis failed to differentiate solitary and social lineages. Microsatellite genetic variability was high and enabled us to quantify genetic differentiation among populations and social phenotypes across Great Britain and Ireland. Results from conceptually different analyses consistently showed greater genetic differentiation between geographically distant populations, independently of their social phenotype, suggesting that the two social forms are not reproductively isolated. A landscape genetic approach revealed significant isolation by distance (Mantel test r = 0.622, p

Chloroquine causes lysosomal dysfunction in neural retina and RPE: Implications for retinopathy

Chronic use of chloroquine has been shown to induce numerous pathophysiological defects in the retina. This drug has the ability to alter pH of intracellular compartments and lysosomal function of the retinal pigment epithelium (RPE) and retinal neurons may constitute the basis of chloroquine retinopathy. The aim of the current study was to investigate pathogenic alterations in retinal cells continuously exposed to chloroquine using appropriate in vivo and in vitro models.

On the set of hypercyclic vectors for the differentiation

Let D be the differentiation operator Df = f' acting on the Fréchet space H of all entire functions in one variable with the standard (compact-open) topology. It is known since the 1950’s that the set H(D) of hypercyclic vectors for the operator D is non-empty. We treat two questions raised by Aron, Conejero, Peris and Seoane-Sepúlveda whether the set H(D) contains (up to the zero function) a non-trivial subalgebra of H or an infinite-dimensional closed linear subspace of H. In the present article both questions are answered affirmatively.