B-spline recurrent neural network and its application to modelling of non-linear dynamic systems

A new recurrent neural network based on B-spline function approximation is presented. The network can be easily trained and its training converges more quickly than that for other recurrent neural networks. Moreover, an adaptive weight updating algorithm for the recurrent network is proposed. It can speed up the training process of the network greatly and its learning speed is more quickly than existing algorithms, e.g., back-propagation algorithm. Examples are presented comparing the adaptive weight updating algorithm and the constant learning rate method, and illustrating its application to modelling of nonlinear dynamic system.published_or_final_versio

Identification and characterization of EBP, a novel EEN binding protein that inhibits Ras signaling and is recruited into the nucleus by the MLL-EEN fusion protein

The chimeric MLL-EEN fusion protein is created as a result of chromosomal translocation t(11;19)(q23;p13). EEN, an Src homology 3 (SH3) domain-containing protein in the endophilin family, has been implicated in endocytosis, although little is known about its role in leukemogenesis mediated by the MLL-EEN fusion protein. In this study, we have identified and characterized EBP, a novel EEN binding protein that interacts with the SH3 domain of EEN through a proline-rich motif PPERP. EBP is a ubiquitous protein that is normally expressed in the cytoplasm but is recruited to the nucleus by MLL-EEN with a punctate localization pattern characteristic of the MLL chimeric proteins. EBP interacts simultaneously with EEN and Sos, a guanine-nucleotide exchange factor for Ras. Coexpressoin of EBP with EEN leads to suppression of Ras-induced cellular transformation and Ras-mediated activation of Elk-1. Taken together, our findings suggest a new mechanism for MLL-EEN-mediated leukemogenesis in which MLL-EEN interferes with the Ras-suppressing activities of EBP through direct interaction. © 2004 by The American Society of Hematology.postprin

Nonlinear observer design with unknown nonlinearity via B-spline network approach

A novel approach is proposed to the state estimation of a class of nonlinear systems which consist of known linear part and unknown nonlinear part. A linear observer is first designed then a nonlinear compensation term in the nonlinear observer is determined using the proposed “deconvolution method”. The B-spline neural network is used to model the estimated compensation term. Three simulation examples are given to compare the effectiveness of the proposed approach and some analytical approaches.published_or_final_versio

State estimation with measurement error compensation using neural network

For a system with redundant sensors, the estimated state from the Kalman filter is biased if sensor mounting error existed. To remove this bias, the mounting errors must be compensated first before using the Kalman filter. It is shown that only the projection part of the sensors errors in the measurement space needs to be compensated. If the state of a system is unavailable, a neurofuzzy network can be used to estimate the compensation term. This method is simpler, as it does not require a model for the errors as that proposed in [2]. A sub-optimal Kalman filter with measurement compensation that restrains each row of the Kalman gain matrix to be in the measurement space is also derived. An example is presented to illustrate the performance of the proposed methods.published_or_final_versio

Fault detection of redundant systems based on B-spline neural network

The fault detection and isolation of redundant sensor systems based on B-spline neural networks is presented in this paper. The network is trained using an algorithm with an adaptive learning rate. To further save computation time, the residual vector is transformed from a multivariate B-spline function to an univariate B-spline function. The detection of abrupt and drifting faults using the proposed method is discusses. The performance of the proposed method is illustrated by an example involving a redundant system consisting of six sensors.published_or_final_versio

Phenolic contents, antioxidant and α-glucosidase inhibition properties of Nepalese strain buckwheat vegetables

The sprouts, microgreens and leafy greens of common and tartary buckwheat of Nepalese strain were compared for the phenolic contents and biological activity. The tartary buckwheat samples expressed higher total phenolic and flavonoid contents compared to the common buckwheat. The sprouts had the highest total phenolic contents (9333.48 ± 150.23 and 6976.21 ± 213.65 mgGAE/100g dw in tartary and common buckwheat, respectively) whereas, the highest total flavonoid content was present in the leafy greens (7635.39 ± 141.40 and 4414.61 ± 70.85 mgRE/100g dw in tartary and common buckwheat respectively). The high performance liquid chromatography (HPLC) results revealed that the tartary buckwheat vegetables had higher rutin, (3800.28 ± 434.41 mg/100g in leafy greens), quercetin (159.75 ± 9.04 mg/100g in sprouts) and chlorogenic acid (293.47 ± 65.06 mg/100g in microgreens) contents than those of common buckwheat. However, other phenolics like vitexin, isovitexin, orientin and isoorientin contents were more abundant in common buckwheat. In biochemical assay, all three types of vegetable of common and tartary buckwheat showed higher antioxidant and α-glucosidase inhibition effect in dose dependent manner. Based on these results, it can be conformed that all the vegetables (microgreens, sprouts and leafy greens) of both varieties of buckwheat of Nepalese strains can be regarded as a potent sour ce of functional food.Key words: Antioxidant, α-glucosidase, buckwheat vegetables, Nepalese strain buckwheat, phenolics

Assessment of Energy Storage Alternatives in the Puget Sound Energy System

As part of an ongoing study co-funded by the Bonneville Power Administration, under its Technology Innovation Grant Program, and the U.S. Department of Energy, the Pacific Northwest National Laboratory (PNNL) has developed an approach and modeling tool for assessing the net benefits of using energy storage located close to the customer in the distribution grid to manage demand. PNNL in collaboration with PSE and Primus Power has evaluated the net benefits of placing a zinc bromide battery system at two locations in the PSE system (Baker River / Rockport and Bainbridge Island). Energy storage can provide a number of benefits to the utility through the increased flexibility it provides to the grid system. Applications evaluated in the assessment include capacity value, balancing services, arbitrage, distribution deferral and outage mitigation. This report outlines the methodology developed for this study and Phase I results

Beyond Gross-Pitaevskii Mean Field Theory

A large number of effects related to the phenomenon of Bose-Einstein Condensation (BEC) can be understood in terms of lowest order mean field theory, whereby the entire system is assumed to be condensed, with thermal and quantum fluctuations completely ignored. Such a treatment leads to the Gross-Pitaevskii Equation (GPE) used extensively throughout this book. Although this theory works remarkably well for a broad range of experimental parameters, a more complete treatment is required for understanding various experiments, including experiments with solitons and vortices. Such treatments should include the dynamical coupling of the condensate to the thermal cloud, the effect of dimensionality, the role of quantum fluctuations, and should also describe the critical regime, including the process of condensate formation. The aim of this Chapter is to give a brief but insightful overview of various recent theories, which extend beyond the GPE. To keep the discussion brief, only the main notions and conclusions will be presented. This Chapter generalizes the presentation of Chapter 1, by explicitly maintaining fluctuations around the condensate order parameter. While the theoretical arguments outlined here are generic, the emphasis is on approaches suitable for describing single weakly-interacting atomic Bose gases in harmonic traps. Interesting effects arising when condensates are trapped in double-well potentials and optical lattices, as well as the cases of spinor condensates, and atomic-molecular coupling, along with the modified or alternative theories needed to describe them, will not be covered here.Comment: Review Article (19 Pages) - To appear in 'Emergent Nonlinear Phenomena in Bose-Einstein Condensates: Theory and Experiment', Edited by P.G. Kevrekidis, D.J. Frantzeskakis and R. Carretero-Gonzalez (Springer Verlag

Assessment of Energy Storage Alternatives in the Puget Sound Energy System Volume 2: Energy Storage Evaluation Tool

This volume presents the battery storage evaluation tool developed at Pacific Northwest National Laboratory (PNNL), which is used to evaluate benefits of battery storage for multiple grid applications, including energy arbitrage, balancing service, capacity value, distribution system equipment deferral, and outage mitigation. This tool is based on the optimal control strategies to capture multiple services from a single energy storage device. In this control strategy, at each hour, a look-ahead optimization is first formulated and solved to determine battery base operating point. The minute by minute simulation is then performed to simulate the actual battery operation. This volume provide background and manual for this evaluation tool