Exponential stabilization of neural networks with various activation functions and mixed time-varying delays

This paper presents some results on the global exponential stabilization for neural networks with various activation functions and time-varying continuously distributed delays. Based on augmented time-varying Lyapunov-Krasovskii functionals, new delay-dependent conditions for the global exponential stabilization are obtained in terms of linear matrix inequalities. A numerical example is given to illustrate the feasibility of our results.

Design of H∞ control of neural networks with time-varying delays

This paper deals with the H∞ control problem of neural networks with time-varying delays. The system under consideration is subject to time-varying delays and various activation functions. Based on constructing some suitable Lyapunov-Krasovskii functionals, we establish new sufficient conditions for H∞ control for two cases of time-varying delays: (1) the delays are differentiable and have an upper bound of the delay-derivatives and (2) the delays are bounded but not necessary to be differentiable. The derived conditions are formulated in terms of linear matrix inequalities, which allow simultaneous computation of two bounds that characterize the exponential stability rate of the solution. Numerical examples are given to illustrate the effectiveness of our results.

A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings

Electrical load forecasting plays a vital role in order to achieve the concept of next generation power system such as smart grid, efficient energy management and better power system planning. As a result, high forecast accuracy is required for multiple time horizons that are associated with regulation, dispatching, scheduling and unit commitment of power grid. Artificial Intelligence (AI) based techniques are being developed and deployed worldwide in on Varity of applications, because of its superior capability to handle the complex input and output relationship. This paper provides the comprehensive and systematic literature review of Artificial Intelligence based short term load forecasting techniques. The major objective of this study is to review, identify, evaluate and analyze the performance of Artificial Intelligence (AI) based load forecast models and research gaps. The accuracy of ANN based forecast model is found to be dependent on number of parameters such as forecast model architecture, input combination, activation functions and training algorithm of the network and other exogenous variables affecting on forecast model inputs. Published literature presented in this paper show the potential of AI techniques for effective load forecasting in order to achieve the concept of smart grid and buildings.

New inequality-based approach to passivity analysis of neural networks with interval time-varying delay

This paper is concerned with the problem of passivity analysis of neural networks with an interval time-varying delay. Unlike existing results in the literature, the time-delay considered in this paper is subjected to interval time-varying without any restriction on the rate of change. Based on novel refined Jensen inequalities and by constructing an improved Lyapunov-Krasovskii functional (LKF), which fully utilizes information of the neuron activation functions, new delay-dependent conditions that ensure the passivity of the network are derived in terms of tractable linear matrix inequalities (LMIs) which can be effectively solved by various computational tools. The effectiveness and improvement over existing results of the proposed method in this paper are illustrated through numerical examples.

Somatostatin modulates G-CSF-induced but not interleukin-3-induced proliferative responses in myeloid 32D cells via activation of somatostatin receptor subtype 2

Somatostatin, originally identified as a peptide involved in neurotransmission, functions as an inhibitor of multiple cellular responses, including hormonal secretion and proliferation. Somatostatin acts through activation of G-protein-coupled receptors of which five subtypes have been identified. We have recently established that human CD34/c-kit expressing hematopoietic progenitors and acute myeloid leukemia (AML) cells exclusively express SSTR2. A major mechanism implicated in the antiproliferative action of somatostatin involves activation of the SH2 domain-containing protein tyrosine phosphatase SHP-1. While 0.1-1 x 10(-9) M of somatostatin, or its synthetic stable analog octreotide, can inhibit G-CSF-induced proliferation of AML cells, little or no effects are seen on GM-CSF- or IL-3-induced responses.
MATERIALS AND METHODS: To study the mechanisms underlying the antiproliferative responses of myeloblasts to somatostatin, clones of the IL-3-dependent murine cell line 32D that stably express SSTR2 and G-CSF receptors were generated. RESULTS: Similar to AML cells, octreotide inhibited G-CSF-induced but not IL-3-induced proliferative responses of 32D[G-CSF-R/SSTR2] cells. Somatostatin induced SHP-1 activity and inhibited G-CSF-induced, but not IL-3-induced, activation of the signal transducer and activator of transcription proteins STAT3 and STAT5.
CONCLUSION: Based on these data and previous results, we propose a model in which recruitment and activation of the tyrosine phosphatase SHP-1 by SSTR2 is involved in the selective negative action of somatostatin on G-CSF-R signaling.

Multi-wavelets from B-spline super-functions with approximation order

Approximation order is an important feature of all wavelets. It implies that polynomials up to degree p−1 are in the space spanned by the scaling function(s). In the scalar case, the scalar sum rules determine the approximation order or the left eigenvectors of the infinite down-sampled convolution matrix H determine the combinations of scaling functions required to produce the desired polynomial. For multi-wavelets the condition for approximation order is similar to the conditions in the scalar case. Generalized left eigenvectors of the matrix H_f; a finite portion of H determines the combinations of scaling functions that produce the desired superfunction from which polynomials of desired degree can be reproduced. The superfunctions in this work are taken to be B-splines. However, any refinable function can serve as the superfunction. The condition of approximation order is derived and new, symmetric, compactly supported and orthogonal multi-wavelets with approximation orders one, two, three and four are constructed.

Gut health immunomodulatory and anti-inflammatory functions of gut enzyme digested high protein micro-nutrient dietary supplement-Enprocal

Background: Enprocal is a high-protein micro-nutrient rich formulated supplementary food designed to meet the nutritional needs of the frail elderly and be delivered to them in every day foods. We studied the potential of Enprocal to improve gut and immune health using simple and robust bioassays for gut cell proliferation, intestinal integrity/permeability, immunomodulatory, anti-inflammatory and anti-oxidative activities. Effects of Enprocal were compared with whey protein concentrate 80 (WPC), heat treated skim milk powder, and other commercially available milk derived products.

Results: Enprocal (undigested) and digested (Enprocal D) selectively enhanced cell proliferation in normal human intestinal epithelial cells (FHs74-Int) and showed no cytotoxicity. In a dose dependent manner Enprocal induced cell death in Caco-2 cells (human colon adencarcinoma epithelial cells). Digested Enprocal (Enprocal D: gut enzyme cocktail treated) maintained the intestinal integrity in transepithelial resistance (TEER) assay, increased the permeability of horseradish peroxidase (HRP) and did not induce oxidative stress to the gut epithelial cells. Enprocal D upregulated the surface expression of co-stimulatory (CD40, CD86, CD80), MHC I and MHC II molecules on PMA differentiated THP-1 macrophages in coculture transwell model, and inhibited the monocyte/lymphocyte (THP-1/Jurkat E6-1 cells)-epithelial cell adhesion. In cytokine secretion analyses, Enprocal D down-regulated the secretion of proinflammatory cytokines (IL-1β and TNF-α) and up-regulated IFN-γ, IL-2 and IL-10.

Conclusion: Our results indicate that Enprocal creates neither oxidative injury nor cytotoxicity, stimulates normal gut cell proliferation, up regulates immune cell activation markers and may aid in the production of antibodies. Furthermore, through downregulation of proinflammatory cytokines, Enprocal appears to be beneficial in reducing the effects of chronic gut inflammatory diseases such as inflammatory bowel disease (IBD). Stimulation of normal human fetal intestinal cell proliferation without cell cytotoxicity indicates it may also be given as infant food particularly for premature babies.

Identification of nonlinear systems using hybrid functions

Most real systems have nonlinear behavior and thus model linearization may not produce an accurate representation of them. This paper presents a method based on hybrid functions to identify the parameters of nonlinear real systems. A hybrid function is a combination of two groups of orthogonal functions: piecewise orthogonal functions (e.g. Block-Pulse) and continuous orthogonal functions (e.g. Legendre polynomials). These functions are completed with an operational matrix of integration and a product matrix. Therefore, it is possible to convert nonlinear differential and integration equations into algebraic equations. After mathematical manipulation, the unknown linear and nonlinear parameters are identified. As an example, a mechanical system with single degree of freedom is simulated using the proposed method and the results are compared against those of an existing approach.

Leptin's metabolic and immune functions can be uncoupled at the ligand/receptor interaction level.

The adipocyte-derived cytokine leptin acts as a metabolic switch, connecting the body's metabolism to high-energy consuming processes such as reproduction and immune responses. We here provide genetic and biochemical evidence that the metabolic and immune functions of leptin can be uncoupled at the receptor level. First, homozygous mutant fatt/fatt mice carry a spontaneous splice mutation causing deletion of the leptin receptor (LR) immunoglobulin-like domain (IGD) in all LR isoforms. These mice are hyperphagic and morbidly obese, but display only minimal changes in size and cellularity of the thymus, and cellular immune responses are unaffected. These animals also displayed liver damage in response to concavalin A comparable to wild-type and heterozygous littermates. Second, treatment of healthy mice with a neutralizing nanobody targeting IGD induced weight gain and hyperinsulinaemia, but completely failed to block development of experimentally induced autoimmune diseases. These data indicate that leptin receptor deficiency or antagonism profoundly affects metabolism, with little concomitant effects on immune functions.