An adaptive neural-wavelet model for short term load forecasting

This paper proposed a novel model for short term load forecast in the competitive electricity market. The prior electricity demand data are treated as time series. The forecast model is based on wavelet multi-resolution decomposition by autocorrelation shell representation and neural networks (multilayer perceptrons, or MLPs) modeling of wavelet coefficients. To minimize the influence of noisy low level coefficients, we applied the practical Bayesian method Automatic Relevance Determination (ARD) model to choose the size of MLPs, which are then trained to provide forecasts. The individual wavelet domain forecasts are recombined to form the accurate overall forecast. The proposed method is tested using Queensland electricity demand data from the Australian National Electricity Market. (C) 2001 Elsevier Science B.V. All rights reserved.

Ethanol-related adaptive changes and physical dependence in rats after exposure to ethanol

Adaptive changes that occur after chronic exposure to ethanol are an important component in the development of physical dependence. We have focused our research on ethanol-induced changes in the expression of several genes that may be important in adaptation. In this article, we describe adaptive changes at the level of the N-methyl-D-aspartate receptor, in the protein expression and activity of the Egr transcription factors, and in the expression of a novel gene of unknown function. (C) 2001 Elsevier Science Inc. All rights reserved.

The effects of time delays in adaptive phase measurements

It is not possible to make measurements of the phase of an optical mode using linear optics without introducing an extra phase uncertainty. This extra phase variance is quite large for heterodyne measurements, however it is possible to reduce it to the theoretical limit of log (n) over bar (4 (n) over bar (2)) using adaptive measurements. These measurements are quite sensitive to experimental inaccuracies, especially time delays and inefficient detectors. Here it is shown that the minimum introduced phase variance when there is a time delay of tau is tau/(8 (n) over bar). This result is verified numerically, showing that the phase variance introduced approaches this limit for most of the adaptive schemes using the best final phase estimate. The main exception is the adaptive mark II scheme with simplified feedback, which is extremely sensitive to time delays. The extra phase variance due to time delays is considered for the mark I case with simplified feedback, verifying the tau /2 result obtained by Wiseman and Killip both by a more rigorous analytic technique and numerically.

Feedback-stabilization of an arbitrary pure state of a two-level atom

Unit-efficiency homodyne detection of the resonance fluorescence of a two-level atom collapses the quantum state of the atom to a stochastically moving point on the Bloch sphere. Recently, Hofmann, Mahler, and Hess [Phys. Rev. A 57, 4877 (1998)] showed that by making part of the coherent driving proportional to the homodyne photocurrent one can stabilize the state to any point on the bottom-half of the sphere. Here we reanalyze their proposal using the technique of stochastic master equations, allowing their results to be generalized in two ways. First, we show that any point on the upper- or lower-half, but not the equator, of the sphere may be stabilized. Second, we consider nonunit-efficiency detection, and quantify the effectiveness of the feedback by calculating the maximal purity obtainable in any particular direction in Bloch space.

Adaptive multiscale principal components analysis for online monitoring of wastewater treatment

Fault detection and isolation (FDI) are important steps in the monitoring and supervision of industrial processes. Biological wastewater treatment (WWT) plants are difficult to model, and hence to monitor, because of the complexity of the biological reactions and because plant influent and disturbances are highly variable and/or unmeasured. Multivariate statistical models have been developed for a wide variety of situations over the past few decades, proving successful in many applications. In this paper we develop a new monitoring algorithm based on Principal Components Analysis (PCA). It can be seen equivalently as making Multiscale PCA (MSPCA) adaptive, or as a multiscale decomposition of adaptive PCA. Adaptive Multiscale PCA (AdMSPCA) exploits the changing multivariate relationships between variables at different time-scales. Adaptation of scale PCA models over time permits them to follow the evolution of the process, inputs or disturbances. Performance of AdMSPCA and adaptive PCA on a real WWT data set is compared and contrasted. The most significant difference observed was the ability of AdMSPCA to adapt to a much wider range of changes. This was mainly due to the flexibility afforded by allowing each scale model to adapt whenever it did not signal an abnormal event at that scale. Relative detection speeds were examined only summarily, but seemed to depend on the characteristics of the faults/disturbances. The results of the algorithms were similar for sudden changes, but AdMSPCA appeared more sensitive to slower changes.

RNA trafficking and stabilization elements associate with multiple brain proteins

Two of the best understood somatic cell mRNA cytoplasmic trafficking elements are those governing localization of beta-actin and myelin basic protein mRNAs. These cis-acting elements bind the trans-acting factors fibroblast ZBP-1 and hnRNP A2, respectively. It is not known whether these elements fulfil other roles in mRNA metabolism. To address this question we have used Edman sequencing and western blotting to identify six rat brain proteins that bind the beta-actin element (zipcode). All are known RNA-binding proteins and differ from ZBP-1. Comparison with proteins that bind the hnRNP A2 and AU-rich response elements, A2RE/A2RE11 and AURE, showed that AURE and zipcode bind a similar set of proteins that does not overlap with those that bind A2RE11. The zipcode-binding protein, KSRP, and hnRNP A2 were selected for further study and were shown by confocal immunolluorescence microscopy to have similar distributions in the central nervous system, but they were found in largely separate locations in cell nuclei. In the cytoplasm of cultured oligodendrocytes they were segregated into separate populations of cytoplasmic granules. We conclude that not only may there be families of trans-acting factors for the same cis-acting element, which are presumably required at different stages of mRNA processing and metabolism, but independent factors may also target different and multiple RNAs in the same cell.

The development and psychometric properties of a measure of social and adaptive functioning for children and adolescents

Developed, piloted, and examined the psychometric properties of the Child and Adolescent Social and Adaptive Functioning Scale (CASAFS), a self-report measure designed to examine the social functioning of young people in the areas of school performance, peer relationships, family relationships, and home duties/self-care. The findings of confirmatory and exploratory factor analysis support a 4-factor solution consistent with the hypothesized domains. Fit indexes suggested that the 4-correlated factor model represented a satisfactory solution for the data, with the covariation between factors being satisfactorily explained by a single, higher order factor reflecting social and adaptive functioning in general. The internal consistency and 12-month test-retest reliability of the total scale was acceptable. A significant, negative correlation was found between the CASAFS and a measure of depressive symptoms, showing that high levels of social functioning are associated with low levels of depression. Significant differences in CASAFS total and subscale scores were found between clinically depressed adolescents and a matched sample of nonclinical controls. Adolescents who reported elevated but subclinical levels of depression also reported lower levels of social functioning in comparison to nonclinical controls.

Was there a second adaptive radiation of giant tortoises in the Indian Ocean? Using mitochondrial DNA to investigate speciation and biogeography of Aldabrachelys (Reptilia, Testudinidae)

A radiation of five species of giant tortoises (Cylindraspis ) existed in the southwest Indian Ocean, on the Mascarene islands, and another (of Aldabrachelys ) has been postulated on small islands north of Madagascar, from where at least eight nominal species have been named and up to five have been recently recognized. Of 37 specimens of Madagascan and small-island Aldabrachelys investigated by us, 23 yielded significant portions of a 428-base-pair (bp) fragment of mitochondrial (cytochrome b and tRNA-Glu), including type material of seven nominal species (A. arnoldi, A. dussumieri, A. hololissa, A. daudinii, A. sumierei, A. ponderosa and A. gouffei ). These and nearly all the remaining specimens, including 15 additional captive individuals sequenced previously, show little variation. Thirty-three exhibit no differences and the remainder diverge by only 1-4 bp (0.23-0.93%). This contrasts with more widely accepted tortoise species which show much greater inter- and intraspecific differences. The non-Madagascan material examined may therefore only represent a single species and all specimens may come from Aldabra where the common haplotype is known to occur. The present study provides no evidence against the Madagascan origin for Aldabra tortoises suggested by a previous molecular phylogenetic analysis, the direction of marine currents and phylogeography of other reptiles in the area. Ancient mitochondrial DNA from the extinct subfossil A. grandidieri of Madagascar differs at 25 sites (5.8%) from all other Aldabrachelys samples examined here.

A new wavelet-based adaptive method for solving population balance equations

A new wavelet-based adaptive framework for solving population balance equations (PBEs) is proposed in this work. The technique is general, powerful and efficient without the need for prior assumptions about the characteristics of the processes. Because there are steeply varying number densities across a size range, a new strategy is developed to select the optimal order of resolution and the collocation points based on an interpolating wavelet transform (IWT). The proposed technique has been tested for size-independent agglomeration, agglomeration with a linear summation kernel and agglomeration with a nonlinear kernel. In all cases, the predicted and analytical particle size distributions (PSDs) are in excellent agreement. Further work on the solution of the general population balance equations with nucleation, growth and agglomeration and the solution of steady-state population balance equations will be presented in this framework. (C) 2002 Elsevier Science B.V. All rights reserved.