An ultra-short-term wind power prediction method using “offline classification and optimization, online model matching” based on time series features

The applicability of ultra-short-term wind power prediction (USTWPP) models is reviewed. The USTWPP method proposed extracts featrues from historical data of wind power time series (WPTS), and classifies every short WPTS into one of several different subsets well defined by stationary patterns. All the WPTS that cannot match any one of the stationary patterns are sorted into the subset of nonstationary pattern. Every above WPTS subset needs a USTWPP model specially optimized for it offline. For on-line application, the pattern of the last short WPTS is recognized, then the corresponding prediction model is called for USTWPP. The validity of the proposed method is verified by simulations.

Improved Equivalent Frame Analysis Method for Flat Plate Structures in Vicinity of Edge Columns

This paper proposes a modification to the ACI 318-02 equivalent frame method of analysis of reinforced concrete flat plate exterior panels. Two existing code methods were examined: ACI 318 and BS 8110. The derivation of the torsional stiffness of the edge strip as proposed by ACI 318 is examined and a more accurate estimate of this value is proposed, based on both theoretical analysis and experimental results. A series of 1/3-scale models of flat plate exterior panels have been tested. Unique experimental results were obtained by measuring strains in reinforcing bars at approximately 200 selected locations in the plate panel throughout the entire loading history. The measured strains were used to calculate curvature and, hence, bending moments; these were used along with moments in the columns to assess the accuracy of the equivalent frame methods. The proposed method leads to a more accurate prediction of the moments in the plate at the column front face, at the panel midspan, and in the edge column. Registered Subscribers: View the full article. This document is available as a free download to qualified members. An electronic (PDF) version is available for purchase and download. Click on the Order Now button to continue with the download.

A comparative study of the synthesis of 3-substituted catechols using an enzymatic and a chemoenzymatic method

A series of cis-dihydrodiol metabolites, available from the bacterial dioxygenase-catalysed oxidation of monosubstituted benzene substrates using Pseudomonas putida UV4, have been converted to the corresponding catechols using both a heterogeneous catalyst (Pd/C) and a naphthalene cis-diol dehydrogenase enzyme present in whole cells of the recombinant strain Escherichia coli DH5 alpha(pUC129: nar B). A comparative study of the merits of both routes to 3-substituted catechols has been carried out and the two methods have been found to be complementary. A similarity in mechanism for catechol formation under both enzymatic and chemoenzymatic conditions, involving regioselective oxidation of the hydroxyl group at C-1, has been found using deuterium labelled toluene cis-dihydrodiols. The potential, of combining a biocatalytic step (dioxygenase-catalysed cis-dihydroxylation) with a chemocatalytic step (Pd/C-catalysed dehydrogenation), into a one-pot route to catechols, from the parent substituted benzene substrates, has been realised.

Convergence acceleration of the doubly periodic Green's function for the analysis of thin wire arrays

A method is proposed to accelerate the evaluation of the Green's function of an infinite double periodic array of thin wire antennas. The method is based on the expansion of the Green's function into series corresponding to the propagating and evanescent waves and the use of Poisson and Kummer transformations enhanced with the analytic summation of the slowly convergent asymptotic terms. Unlike existing techniques the procedure reported here provides uniform convergence regardless of the geometrical parameters of the problem or plane wave excitation wavelength. In addition, it is numerically stable and does not require numerical integration or internal tuning parameters, since all necessary series are directly calculated in terms of analytical functions. This means that for nonlinear problem scenarios that the algorithm can be deployed without run time intervention or recursive adjustment within a harmonic balance engine. Numerical examples are provided to illustrate the efficiency and accuracy of the developed approach as compared with the Ewald method for which these classes of problems requires run time splitting parameter adaptation.

Developing a simple, rapid method for identifying and monitoring jellyfish aggregations from the air

Within the marine environment, aerial surveys have historically centred on apex predators, such as pinnipeds, cetaceans and sea birds. However, it is becoming increasingly apparent that the utility of this technique may also extend to subsurface species such as pre-spawning fish stocks and aggregations of jellyfish that occur close to the surface. In light of this, we tested the utility of aerial surveys to provide baseline data for 3 poorly understood scyphozoan jellyfish found throughout British and Irish waters: Rhizostoma octopus, Cyanea capillata and Chrysaora hysoscella. Our principal objectives were to develop a simple sampling protocol to identify and quantify surface aggregations, assess their consistency in space and time, and consider the overall applicability of this technique to the study of gelatinous zooplankton. This approach provided a general understanding of range and relative abundance for each target species, with greatest suitability to the study of R. octopus. For this species it was possible to identify and monitor extensive, temporally consistent and previously undocumented aggregations throughout the Irish Sea, an area spanning thousands of square kilometres. This finding has pronounced implications for ecologists and fisheries managers alike and, moreover, draws attention to the broad utility of aerial surveys for the study of gelatinous aggregations beyond the range of conventional ship-based techniques.

NON-GAUSSIAN STATISTICS OF OIL PRICING TIME-SERIES: A CASE STUDY

The stochastic nature of oil price fluctuations is investigated over a twelve-year period, borrowing feedback from an existing database (USA Energy Information Administration database, available online). We evaluate the scaling exponents of the fluctuations by employing different statistical analysis methods, namely rescaled range analysis (R/S), scale windowed variance analysis (SWV) and the generalized Hurst exponent (GH) method. Relying on the scaling exponents obtained, we apply a rescaling procedure to investigate the complex characteristics of the probability density functions (PDFs) dominating oil price fluctuations. It is found that PDFs exhibit scale invariance, and in fact collapse onto a single curve when increments are measured over microscales (typically less than 30 days). The time evolution of the distributions is well fitted by a Levy-type stable distribution. The relevance of a Levy distribution is made plausible by a simple model of nonlinear transfer. Our results also exhibit a degree of multifractality as the PDFs change and converge toward to a Gaussian distribution at the macroscales.

The impact of a PCR assay for candidemia on antifungal drug prescribing in critical care: an interrupted time series pilot study.

Objective To evaluate the feasibility of conducting a definitive study to assess the impact of introducing a rapid PCR-based test for candidemia on antifungal drug prescribing. Method Prospective, single centre, interrupted time series study consisting of three periods of six months' duration. The assay was available during the second period, during which the PCR assay was available for routine use by physicians Monday–Friday with guaranteed 24-h turnaround time. For each period total antifungal drug use, expressed as treatment-days, was recorded and an adjustment was made to exclude estimated use for proven candidemia. Also, during the intervention period, antifungal prescribing decisions for up to 72 h after each PCR result became available were recorded as either concordant or discordant with that result. Results While overall antifungal use remained relatively stable throughout, after adjustment for candidemia, there was a 38% reduction in use following introduction of the PCR test; however, this was nonsignificant at the 95% level. During the intervention period overall concordance between the PCR result and prescribing decisions was 84%. Conclusions The PCR assay for candidemia was requested, prescribing decisions were generally concordant with the results produced and there was an apparent decrease in antifungal prescription, although this was sustained even after withdrawal of the intervention; these findings should be more thoroughly evaluated in a larger trial.

Nonlinear time series prediction based on a power-law noise model

In this paper we investigate the influence of a power-law noise model, also called noise, on the performance of a feed-forward neural network used to predict time series. We introduce an optimization procedure that optimizes the parameters the neural networks by maximizing the likelihood function based on the power-law model. We show that our optimization procedure minimizes the mean squared leading to an optimal prediction. Further, we present numerical results applying method to time series from the logistic map and the annual number of sunspots demonstrate that a power-law noise model gives better results than a Gaussian model.

Identification of dyes on ancient Chinese paper samples using the subtracted shifted Raman spectroscopy method

The Stein Collection in the British Library contains the Diamond Sutra, the world's oldest, dated, printed document. The paper of the Diamond Sutra and other documents from the Stein collection is believed to be dyed yellow by a natural extract, called huangbo, from the bark of Phellodendron amurense, which contains three major yellow chromophores: berberine, palmatine, and jatrorrhizine, Conservation of these documents requires definite information on the chemical composition of the dyes but no suitable, completely noninvasive analytical method is known. Here we report resonance Raman studies of a series of prate dyes, of plant materials and extracts, and of dyed ancient and modern paper samples. Resonance Raman spectroscopy is used to enhance the spectra of the dyes over the signals from the paper matrixes in which they are held. The samples an give resonance Raman spectra which are dominated by intense fluorescence, but by using SSRS (subtracted shifted Raman spectroscopy) we have obtained reliable spectra of the pure dyes, native bark from the Phellodendron amurense, modern paper dyed with huangbo extracted from this bark, and ancient paper samples. For both ancient paper samples whose pigment bands were detected, the relative intensities of the bands due to berberine and palmatine suggest that the ancient paper is richer in berberine than its modern counterpart, This is the first nondestructive in situ method for detection of these pigments in manuscripts, and as such has considerable potential benefit for the treatment of irreplaceable documents that are believed to be dyed with huangbo but documents on which conservation work cannot proceed without definite identification of the chemical compounds that they contain.

Moving Object Scanning Apparatus and Method

Apparatus for scanning a moving object includes a visible waveband sensor oriented to collect a series of images of the object as it passes through a field of view. An image processor uses the series of images to form a composite image. The image processor stores image pixel data for a current image and predecessor image in the series. It uses information in the current image and its predecessor to analyse images and derive likelihood measures indicating probabilities that current image pixels correspond to parts of the object. The image processor estimates motion between the current image and its predecessor from likelihood weighted pixels. It generates the composite image from frames positioned according to respective estimates of object image motion. Image motion may alternatively be detected be a speed sensor such as Doppler radar sensing object motion directly and providing image timing signals

Temporal extension of Laplacian Eigenmaps for unsupervised dimensionality reduction of time series

A novel non-linear dimensionality reduction method, called Temporal Laplacian Eigenmaps, is introduced to process efficiently time series data. In this embedded-based approach, temporal information is intrinsic to the objective function, which produces description of low dimensional spaces with time coherence between data points. Since the proposed scheme also includes bidirectional mapping between data and embedded spaces and automatic tuning of key parameters, it offers the same benefits as mapping-based approaches. Experiments on a couple of computer vision applications demonstrate the superiority of the new approach to other dimensionality reduction method in term of accuracy. Moreover, its lower computational cost and generalisation abilities suggest it is scalable to larger datasets. © 2010 IEEE.

Detecting sequence dependent transcriptional pauses from RNA and protein number time series

Background: Evidence suggests that in prokaryotes sequence-dependent transcriptional pauses a?ect the dynamics of transcription and translation, as well as of small genetic circuits. So far, a few pause-prone sequences have been identi?ed from in vitro measurements of transcription elongation kinetics.

Results: Using a stochastic model of gene expression at the nucleotide and codon levels with realistic parameter values, we investigate three di?erent but related questions and present statistical methods for their analysis. First, we show that information from in vivo RNA and protein temporal numbers is su?cient to discriminate between models with and without a pause site in their coding sequence. Second, we demonstrate that it is possible to separate a large variety of models from each other with pauses of various durations and locations in the template by means of a hierarchical clustering and a random forest classi?er. Third, we introduce an approximate likelihood function that allows to estimate the location of a pause site.

Conclusions: This method can aid in detecting unknown pause-prone sequences from temporal measurements of RNA and protein numbers at a genome-wide scale and thus elucidate possible roles that these sequences play in the dynamics of genetic networks and phenotype.

Structural and magnetic properties of Ni1-xZnxFe2O4 (x=0, 0.5 and 1) nanopowders prepared by sol-gel method

A series of nanostructured Ni-Zn ferrites Ni1-xZnxFe2O4 (x=0, 0.5 and 1) with a grain size from 24 to 65 nm have been prepared with a sol-gel method. The effect of composition and sintering temperature on morphology, magnetic properties, Curie temperature, specific heating rate at 295 kHz and hysteresis loss have been studied. The highest coercivity of 50 and 40 Oe, were obtained for NiFe2O4 and Ni0.5Zn0.5Fe2O4 samples with the grain size of 35 and 29 nm, respectively. The coercivity of Ni and Ni-Zn mixed ferrites decreased with temperature. The Bloch exponent was 1.5 for all samples. As the grain size increased, the Curie temperature of NiFe2O4 increased from 849 to 859 K. The highest saturation magnetization of 70 emu/g at 298 K and the highest specific heating rate of 1.6 K/s under radiofrequency heating at 295 kHz were observed over NiFe2O4 calcined at 1073 K. Both the magnitude of the hysteresis loss and the temperature dependence of the loss are influenced by the sintering temperature and composition.

A facile method for the synthesis of Au/PEDOT:PSS nanocomposite

In this work, we have successfully synthesized Au nanoparticles (NPs) in situ in PEDOT:PSS deploying a room temperature atmospheric pressure microplasma. The size of the AuNPs is a function of the gold salt precursor concentration and the plasma processing time. The Au/polymer colloids after processing remain well dispersed over a prolonged period of time. Both gold salt concentration and the plasma processing time have influence on the electrical conductivity of the dried Au/PEDOT:PSS nanocomposite films. An enhanced electrical conductivity of the Au/PEDOT:PSS nanocomposite films has been attributed to (i) the interfacial ligand formation between the S atoms in PEDOT:PSS molecules and the Au surface and (ii) charge transfer from the AuNPs to the holes of PEDOT:PSS molecules.

A modified method for measuring antibiotic use in healthcare settings: implications for antibiotic stewardship and benchmarking

Objectives: To determine whether adjusting the denominator of the common hospital antibiotic use measurement unit (defined daily doses/100 bed-days) by including age-adjusted comorbidity score (100 bed-days/age-adjusted comorbidity score) would result in more accurate and meaningful assessment of hospital antibiotic use. 

Methods: The association between the monthly sum of age-adjusted comorbidity and monthly antibiotic use was measured using time-series analysis (January 2008 to June 2012). For the purposes of conducting internal benchmarking, two antibiotic usage datasets were constructed, i.e. 2004-07 (first study period) and 2008-11 (second study period). Monthly antibiotic use was normalized per 100 bed-days and per 100 bed-days/age-adjusted comorbidity score. 

Results: Results showed that antibiotic use had significant positive relationships with the sum of age-adjusted comorbidity score (P = 0.0004). The results also showed that there was a negative relationship between antibiotic use and (i) alcohol-based hand rub use (P = 0.0370) and (ii) clinical pharmacist activity (P = 0.0031). Normalizing antibiotic use per 100 bed-days contributed to a comparative usage rate of 1.31, i.e. the average antibiotic use during the second period was 31% higher than during the first period. However, normalizing antibiotic use per 100 bed-days per age-adjusted comorbidity score resulted in a comparative usage rate of 0.98, i.e. the average antibiotic use was 2% lower in the second study period. Importantly, the latter comparative usage rate is independent of differences in patient density and case mix characteristics between the two studied populations. 

Conclusions: The proposed modified antibiotic measure provides an innovative approach to compare variations in antibiotic prescribing while taking account of patient case mix effects.