bluuebunny/crossref_metadata_2025 huggingface dataset:
A Study of Fermentation for Human Interleukin-11 with Recombinant E. Coli
Authors: Zhao Kaili , Gan Yiru , Zhang Zisheng Jason
Published: December 2005

Recombinant human interleukin-11(rhIL-11) is still the only therapy drug for thrombocytopenia. Although the biological properties and clinical behaviors of rhIL-11 have been studied extensively, its bioprocess development data have rarely been reported. In this work, fermentation conditions for recombinant E. coli, which expressed interleukin-11 as a fusion protein, were investigated. Batch and fed-batch fermentation experiments were performed in shake flasks and in a BioFlo fermenter with different medium and carbon sources under different operational parameters. Based on the results of the study, M9Ca medium was shown as the better medium and glycerol was identified to be a better carbon source than glucose for the expression of rhIL-11. When glycerol was used as the carbon source in fed-batch fermentation, a dry cell weight of 9.2 g/L and a rhIL-11 expression of 22%, were achieved. The results could be used as references in the optimization of the fermentation process.
Reproducible Research: A Bioinformatics Case Study
Authors: Gentleman Robert
Published: December 2005

While scientific research and the methodologies involved have gone through substantial technological evolution the technology involved in the publication of the results of these endeavors has remained relatively stagnant. Publication is largely done in the same manner today as it was fifty years ago. Many journals have adopted electronic formats, however, their orientation and style is little different from a printed document. The documents tend to be static and take little advantage of computational resources that might be available. Recent work, Gentleman and Temple Lang (2003), suggests a methodology and basic infrastructure that can be used to publish documents in a substantially different way. Their approach is suitable for the publication of papers whose message relies on computation. Stated quite simply, Gentleman and Temple Lang (2003) propose a paradigm where documents are mixtures of code and text. Such documents may be self-contained or they may be a component of a compendium which provides the infrastructure needed to provide access to data and supporting software. These documents, or compendiums, can be processed in a number of different ways. One transformation will be to replace the code with its output -- thereby providing the familiar, but limited, static document. In this paper we apply these concepts to a seminal paper in bioinformatics, namely The Molecular Classification of Cancer, Golub et al (1999). The authors of that paper have generously provided data and other information that have allowed us to largely reproduce their results. Rather than reproduce this paper exactly we demonstrate that such a reproduction is possible and instead concentrate on demonstrating the usefulness of the compendium concept itself.
Asymptotic Optimality of Likelihood-Based Cross-Validation
Authors: van der Laan Mark J. , Dudoit Sandrine , Keles Sunduz
Published: December 2005

Likelihood-based cross-validation is a statistical tool for selecting a density estimate based on n i.i.d. observations from the true density among a collection of candidate density estimators. General examples are the selection of a model indexing a maximum likelihood estimator, and the selection of a bandwidth indexing a nonparametric (e.g. kernel) density estimator. In this article, we establish a finite sample result for a general class of likelihood-based cross-validation procedures (as indexed by the type of sample splitting used, e.g. V-fold cross-validation). This result implies that the cross-validation selector performs asymptotically as well (w.r.t. to the Kullback-Leibler distance to the true density) as a benchmark model selector which is optimal for each given dataset and depends on the true density. Crucial conditions of our theorem are that the size of the validation sample converges to infinity, which excludes leave-one-out cross-validation, and that the candidate density estimates are bounded away from zero and infinity. We illustrate these asymptotic results and the practical performance of likelihood-based cross-validation for the purpose of bandwidth selection with a simulation study. Moreover, we use likelihood-based cross-validation in the context of regulatory motif detection in DNA sequences.
Multiple Testing. Part II. Step-Down Procedures for Control of the Family-Wise Error Rate
Authors: van der Laan Mark J. , Dudoit Sandrine , Pollard Katherine S.
Published: December 2005

The present article proposes two step-down multiple testing procedures for asymptotic control of the family-wise error rate (FWER): the first procedure is based on maxima of test statistics (step-down maxT), while the second relies on minima of unadjusted p-values (step-down minP). A key feature of our approach is the characterization and construction of a test statistics null distribution (rather than data generating null distribution) for deriving cut-offs for these test statistics (i.e., rejection regions) and the resulting adjusted p-values. For general null hypotheses, corresponding to submodels for the data generating distribution, we identify an asymptotic domination condition for a null distribution under which the step-down maxT and minP procedures asymptotically control the Type I error rate, for arbitrary data generating distributions, without the need for conditions such as subset pivotality. Inspired by this general characterization, we then propose as an explicit null distribution the asymptotic distribution of the vector of null value shifted and scaled test statistics. Step-down procedures based on consistent estimators of the null distribution are shown to also provide asymptotic control of the Type I error rate. A general bootstrap algorithm is supplied to conveniently obtain consistent estimators of the null distribution.
Error-Rate and Decision-Theoretic Methods of Multiple Testing: Which Genes Have High Objective Probabilities of Differential Expression?
Authors: Bickel David R.
Published: December 2005

Given a multiple testing situation, the null hypotheses that appear to have sufficiently low probabilities of truth may be rejected using a simple, nonparametric method based on decision theory. This applies not only to posterior levels of belief, but also to conditional probabilities in the sense of relative frequencies, as seen from their equality to local false discovery rates (dFDRs). This approach neither requires the estimation of probability densities, nor of their ratios. Decision theory can also inform the selection of false discovery rate weights. An application to gene expression microarrays is presented with a discussion of the applicability of the assumption of "clumpy dependence."
A Mixed Model Approach to Identify Yeast Transcriptional Regulatory Motifs via Microarray Experiments
Authors: Yu Xiang , Chu Tzu-Ming , Gibson Greg , Wolfinger Russell D
Published: December 2005

A genome-wide location analysis method has been introduced as a means to simultaneously study protein-DNA binding interactions for a large number of genes on a microarray platform. Identification of interactions between transcription factors (TF) and genes provide insight into the mechanisms that regulate a variety of cellular responses. Drawing proper inferences from the experimental data is key to finding statistically significant TF-gene binding interactions. We describe how the analysis and interpretation of genome-wide location data can be fit into a traditional statistical modeling framework that considers the data across all arrays and formulizes appropriate hypothesis tests. The approach is illustrated with data from a yeast transcription factor binding experiment that illustrates how identified TF-gene interactions can enhance initial exploration of transcriptional regulatory networks. Examples of five kinds of transcriptional regulatory structure are also demonstrated. Some stark differences with previously published results are explored.
Combining Nearest Neighbor Classifiers Versus Cross-Validation Selection
Authors: Paik Minhui , Yang Yuhong
Published: December 2005

Various discriminant methods have been applied for classification of tumors based on gene expression profiles, among which the nearest neighbor (NN) method has been reported to perform relatively well. Usually cross-validation (CV) is used to select the neighbor size as well as the number of variables for the NN method. However, CV can perform poorly when there is considerable uncertainty in choosing the best candidate classifier. As an alternative to selecting a single “winner," we propose a weighting method to combine the multiple NN rules. Four gene expression data sets are used to compare its performance with CV methods. The results show that when the CV selection is unstable, the combined classifier performs much better.
Maximum Likelihood for Genome Phylogeny on Gene Content
Authors: Zhang Hongmei , Gu Xun
Published: December 2005

With the rapid growth of entire genome data, reconstructing the phylogenetic relationship among different genomes has become a hot topic in comparative genomics. Maximum likelihood approach is one of the various approaches, and has been very successful. However, there is no reported study for any applications in the genome tree-making mainly due to the lack of an analytical form of a probability model and/or the complicated calculation burden. In this paper we studied the mathematical structure of the stochastic model of genome evolution, and then developed a simplified likelihood function for observing a specific phylogenetic pattern under four genome situation using gene content information. We use the maximum likelihood approach to identify phylogenetic trees. Simulation results indicate that the proposed method works well and can identify trees with a high correction rate. Real data application provides satisfied results. The approach developed in this paper can serve as the basis for reconstructing phylogenies of more than four genomes.
Classifying Gene Expression Profiles from Pairwise mRNA Comparisons
Authors: Geman Donald , d'Avignon Christian , Naiman Daniel Q. , Winslow Raimond L.
Published: December 2005

We present a new approach to molecular classification based on mRNA comparisons. Our method, referred to as the top-scoring pair(s) (TSP) classifier, is motivated by current technical and practical limitations in using gene expression microarray data for class prediction, for example to detect disease, identify tumors or predict treatment response. Accurate statistical inference from such data is difficult due to the small number of observations, typically tens, relative to the large number of genes, typically thousands. Moreover, conventional methods from machine learning lead to decisions which are usually very difficult to interpret in simple or biologically meaningful terms. In contrast, the TSP classifier provides decision rules which i) involve very few genes and only relative expression values (e.g., comparing the mRNA counts within a single pair of genes); ii) are both accurate and transparent; and iii) provide specific hypotheses for follow-up studies. In particular, the TSP classifier achieves prediction rates with standard cancer data that are as high as those of previous studies which use considerably more genes and complex procedures. Finally, the TSP classifier is parameter-free, thus avoiding the type of over-fitting and inflated estimates of performance that result when all aspects of learning a predictor are not properly cross-validated.
Statistical Methods for Identifying Conserved Residues in Multiple Sequence Alignment
Authors: Ahola Virpi , Aittokallio Tero , Uusipaikka Esa , Vihinen Mauno
Published: December 2005

The assessment of residue conservation in a multiple sequence alignment is a central issue in bioinformatics. Conserved residues and regions are used to determine structural and functional motifs or evolutionary relationships between the sequences of a multiple sequence alignment. For this reason, residue conservation is a valuable measure for database and motif search or for estimating the quality of alignments. In this paper, we present statistical methods for identifying conserved residues in multiple sequence alignments. While most earlier studies examine the positional conservation of the alignment, we focus on the detection of individual conserved residues at a position. The major advantages of multiple comparison methods originate from their ability to select conserved residues simultaneously and to consider the variability of the residue estimates. Large-scale simulations were used for the comparative analysis of the methods. Practical performance was studied by comparing the structurally and functionally important residues of Src homology 2 (SH2) domains to the assignments of the conservation indices. The applicability of the indices was also compared in three additional protein families comprising different degrees of entropy and variability in alignment positions. The results indicate that statistical multiple comparison methods are sensitive and reliable in identifying conserved residues.
Statistical Analysis of Adsorption Models for Oligonucleotide Microarrays
Authors: Burden Conrad J , Pittelkow Yvonne E , Wilson Susan R
Published: December 2005

Recent analyses have shown that the relationship between intensity measurements from high density oligonucleotide microarrays and known concentration is non linear. Thus many measurements of so-called gene expression are neither measures of transcript nor mRNA concentration as might be expected.

Intensity as measured in such microarrays is a measurement of fluorescent dye attached to probe-target duplexes formed during hybridization of a sample to the probes on the microarray. We develop several dynamic adsorption models relating fluorescent dye intensity to target RNA concentration, the simplest of which is the equilibrium Langmuir isotherm, or hyperbolic response function. Using data from the Affymerix HG-U95A Latin Square experiment, we evaluate various physical models, including equilibrium and non-equilibrium models, by applying maximum likelihood methods. We show that for these data, equilibrium Langmuir isotherms with probe dependent parameters are appropriate. We describe how probe sequence information may then be used to estimate the parameters of the Langmuir isotherm in order to provide an improved measure of absolute target concentration.
Validation and Discovery in Markov Models of Genetics Data
Authors: De Gruttola Victor , Foulkes Andrea S
Published: December 2005

Markov models provide a natural framework for modeling cellular and molecular level changes over time. Kalbfleisch and Lawless propose using a Chi-squared statistic for assessing the appropriateness of assuming a first-order, homogeneous Markov process. While this statistic provides a global test of the Markov assumption, it does not permit identification of individual departures. We consider two approaches for discovering specific departures from the Markov assumption. First, we propose a diagnostic that tests whether the number of observed transitions out of a given state at a given time point is different than expected. Second, we construct statistics based on the number of observations in each state at each time point. In both cases, we construct multiple correlated statistics and testing is achieved through simulations. These approaches are applied to HIV genetics sequences measured over time.
Multiple Testing and Data Adaptive Regression: An Application to HIV-1 Sequence Data.
Authors: Birkner Merrill D. , Sinisi Sandra E. , van der Laan Mark J.
Published: December 2005

Analysis of viral strand sequence data and viral replication capacity could potentially lead to biological insights regarding the replication ability of HIV-1. Determining specific target codons on the viral strand will facilitate the manufacturing of target-specific antiretrovirals. Various algorithmic and analysis techniques can be applied to this application. In this paper, we apply two techniques to a data set consisting of 317 patients, each with 282 sequenced protease and reverse transcriptase codons. The first application is recently developed multiple testing procedures to find codons which have significant univariate associations with the replication capacity of the virus. A single-step multiple testing procedure (Pollard and van der Laan 2003) method was used to control the family wise error rate (FWER) at the five percent alpha level as well as the application of augmentation multiple testing procedures to control the generalized family wise error (gFWER) or the tail probability of the proportion of false positives (TPPFP). We also applied a data adaptive multiple regression algorithm to obtain a prediction of viral replication capacity based on an entire mutant/non-mutant sequence profile. This is a loss-based, cross-validated Deletion/Substitution/Addition regression algorithm (Sinisi and van der Laan 2004), which builds candidate estimators in the prediction of a univariate outcome by minimizing an empirical risk. These methods are two separate techniques with distinct goals used to analyze this structure of viral data.
Pixel-level Signal Modelling with Spatial Correlation for Two-Colour Microarrays
Authors: Ekstrøm Claus T , Bak Søren , Rudemo Mats
Published: December 2005

Statistical models for spot shapes and signal intensities are used in image analysis of laser scans of microarrays. Most models have essentially been based on the assumption of independent pixel intensity values, but models that allow for spatial correlation among neighbouring pixels can accommodate errors in the microarray slide and should improve the model fit. Five spatial correlation structures, exponential, Gaussian, linear, rational quadratic and spherical, are compared for a dataset with 50-mer two-colour oligonucleotide microarrays and 452 probes for selected Arabidopsis genes. Substantial improvement in model fit is obtained for all five correlation structures compared to the model with independent pixel values, and the Gaussian and the spherical models seem to be slightly better than the other three models. We also conclude that for the data set analysed the correlation seems negligible for non-neighbouring pixels.
Reverse Engineering Galactose Regulation in Yeast through Model Selection
Authors: Thorsson Vesteinn , Hörnquist Michael , Siegel Andrew F , Hood Leroy
Published: December 2005

We examine the application of statistical model selection methods to reverse-engineering the control of galactose utilization in yeast from DNA microarray experiment data. In these experiments, relationships among gene expression values are revealed through modifications of galactose sugar level and genetic perturbations through knockouts. For each gene variable, we select predictors using a variety of methods, taking into account the variance in each measurement. These methods include maximization of log-likelihood with Cp, AIC, and BIC penalties, bootstrap and cross-validation error estimation, and coefficient shrinkage via the Lasso.
FADO: A Statistical Method to Detect Favored or Avoided Distances between Occurrences of Motifs using the Hawkes' Model
Authors: Gusto Gaelle , Schbath Sophie
Published: December 2005

We propose an original statistical method to estimate how the occurrences of a given process along a genome, genes or motifs for instance, may be influenced by the occurrences of a second process. More precisely, the aim is to detect avoided and/or favored distances between two motifs, for instance, suggesting possible interactions at a molecular level. For this, we consider occurrences along the genome as point processes and we use the so-called Hawkes' model. In such model, the intensity at position t depends linearly on the distances to past occurrences of both processes via two unknown profile functions to estimate. We perform a non parametric estimation of both profiles by using B-spline decompositions and a constrained maximum likelihood method. Finally, we use the AIC criterion for the model selection. Simulations show the excellent behavior of our estimation procedure. We then apply it to study (i) the dependence between gene occurrences along the E. coli genome and the occurrences of a motif known to be part of the major promoter for this bacterium, and (ii) the dependence between the yeast S. cerevisiae genes and the occurrences of putative polyadenylation signals. The results are coherent with known biological properties or previous predictions, meaning this method can be of great interest for functional motif detection, or to improve knowledge of some biological mechanisms.
Empirical Bayes Microarray ANOVA and Grouping Cell Lines by Equal Expression Levels
Authors: Lönnstedt Ingrid , Rimini Rebecca , Nilsson Peter
Published: December 2005

In the exploding field of gene expression techniques such as DNA microarrays, there are still few general probabilistic methods for analysis of variance. Linear models and ANOVA are heavily used tools in many other disciplines of scientific research. The usual F-statistic is unsatisfactory for microarray data, which explore many thousand genes in parallel, with few replicates.We present three potential one-way ANOVA statistics in a parametric statistical framework. The aim is to separate genes that are differently regulated across several treatment conditions from those with equal regulation. The statistics have different features and are evaluated using both real and simulated data. Our statistic B1 generally shows the best performance, and is extended for use in an algorithm that groups cell lines by equal expression levels for each gene. An extension is also outlined for more general ANOVA tests including several factors.The methods presented are implemented in the freely available statistical language R. They are available at http://www.math.uu.se/staff/pages/?uname=ingrid.
Statistical Inference in Evolutionary Models of DNA Sequences via the EM Algorithm
Authors: Hobolth Asger , Jensen Jens Ledet
Published: December 2005

We describe statistical inference in continuous time Markov processes of DNA sequences related by a phylogenetic tree. The maximum likelihood estimator can be found by the expectation maximization (EM) algorithm and an expression for the information matrix is also derived. We provide explicit analytical solutions for the EM algorithm and information matrix.
The Relative Inefficiency of Sequence Weights Approaches in Determining a Nucleotide Position Weight Matrix
Authors: Newberg Lee A , McCue Lee Ann , Lawrence Charles E
Published: December 2005

Approaches based upon sequence weights, to construct a position weight matrix of nucleotides from aligned inputs, are popular but little effort has been expended to measure their quality.We derive optimal sequence weights that minimize the sum of the variances of the estimators of base frequency parameters for sequences related by a phylogenetic tree. Using these we find that approaches based upon sequence weights can perform very poorly in comparison to approaches based upon a theoretically optimal maximum-likelihood method in the inference of the parameters of a position-weight matrix. Specifically, we find that among a collection of primate sequences, even an optimal sequences-weights approach is only 51% as efficient as the maximum-likelihood approach in inferences of base frequency parameters.We also show how to employ the variance estimators to obtain a greedy ordering of species for sequencing. Application of this ordering for the weighted estimators to a primate collection yields a curve with a long plateau that is not observed with maximum-likelihood estimators. This plateau indicates that the use of weighted estimators on these data seriously limits the utility of obtaining the sequences of more than two or three additional species.
Continuous Covariates in Genetic Association Studies of Case-Parent Triads: Gene and Gene-Environment Interaction Effects, Population Stratification, and Power Analysis
Authors: Lim Sooyeol , Beyene Joseph , Greenwood Celia M. T.
Published: December 2005

We propose a multinomial logistic regression method which permits estimation and likelihood ratio tests for allele effects, their interactions with continuous covariates, and assessment of the degree of population stratification in genetic association studies of case-parent triads. Our approach overcomes the constraint imposed by the categorical nature of explanatory variables in the log-linear model. We also demonstrate that the multinomial logistic method can yield efficient inference in the presence of missing parental genotype data via the use of the Expectation-Maximization (EM) algorithm. We performed simulations to compare the multinomial logistic model with the case-pseudosibling conditional logistic model approach, both of which permit the incorporation of continuous covariates. Simulation results indicate that the multinomial logistic model and the conditional logistic model lead to similar estimates in large samples. A simulation-based method of sample size estimation is also used to show that the two models are approximately equivalent in sample size requirements. When parental genotype data are missing, either completely at random or dependent on covariates, the use of the EM algorithm gives multinomial logistic model greater power. Since the multinomial logistic model offers the possibility of assessing the degree of population stratification in the sample and can also provide efficient inference in the presence of missing parental genotypes, the proposed model has an important application in epidemiological family-based association studies.
Weighted Analysis of Paired Microarray Experiments
Authors: Kristiansson Erik , Sjögren Anders , Rudemo Mats , Nerman Olle
Published: December 2005

In microarray experiments quality often varies, for example between samples and between arrays. The need for quality control is therefore strong. A statistical model and a corresponding analysis method is suggested for experiments with pairing, including designs with individuals observed before and after treatment and many experiments with two-colour spotted arrays. The model is of mixed type with some parameters estimated by an empirical Bayes method. Differences in quality are modelled by individual variances and correlations between repetitions. The method is applied to three real and several simulated datasets. Two of the real datasets are of Affymetrix type with patients profiled before and after treatment, and the third dataset is of two-colour spotted cDNA type. In all cases, the patients or arrays had different estimated variances, leading to distinctly unequal weights in the analysis. We suggest also plots which illustrate the variances and correlations that affect the weights computed by our analysis method. For simulated data the improvement relative to previously published methods without weighting is shown to be substantial.
A Probabilistic Approach to Large-Scale Association Scans: A Semi-Bayesian Method to Detect Disease-Predisposing Alleles
Authors: Schrodi Steven J
Published: December 2005

Recent analytic and technological breakthroughs have set the stage for genome-wide linkage disequilibrium studies to map disease-susceptibility variants. This paper discusses a probabilistic methodology for making disease-mapping inferences in large-scale case-control genetic studies. The semi-Bayesian approach promoted compares the probability of the observed data under disease hypotheses to the probability of the data under a null hypothesis defined by data at all the markers interrogated in a large study. This method automatically adjusts for the effects of diffuse population stratification. It is claimed that this characterization of the evidence for or against disease models may facilitate more appropriate inductions for large-scale genetic studies. Results include (i) an analytic solution for the population stratification-adjusted Bayes factor, (ii) the relationship between sample size and Bayes factors, (iii) an extension to an approximate Bayes factor calculated across closely-linked sites, and (iv) an extension across multiple studies. Although this paper deals exclusively with genetic studies, it is possible to generalize the approach to treat many different large-scale experiments including studies of gene expression and proteomics.
Integrating Complementary and Alternative Medicine With Primary Health Care Through Public Health To Improve Chronic Disease Management
Authors: Willison Kevin D , Mitmaker Lisa , Andrews Gavin J.
Published: December 2005

The purpose of this review is to consider how the practice of public health could play a pivotal role towards enhancing chronic disease management by integrating and aiding the common goals shared between primary health care (PHC) and complementary and alternative medicine (CAM). While these three systems are by no means unified, they are also not totally separate systems either. Improving their collaboration, so as to better meet the health care needs of individuals with chronic disorders, may be facilitated through an enhanced integrative health care infrastructure.
Acute Respiratory Distress Syndrome Successfully Treated with Low Level Laser Therapy
Authors: Gunn Chan
Published: December 2005

Acute respiratory distress syndrome (ARDS) is a medical emergency, which may be precipitated by an acute injury to the lung. The injury can also follow direct chest trauma from aspiration of gastric contents or inhalation of toxic gasses. ARDS is not itself a specific disease but a syndrome - a group of symptoms and signs that make up one of the most important forms of respiratory failure.ARDS is devastating because it can develop quite suddenly in persons whose lungs had been perfectly normal - it kills at least 60% of its victims. The fundamental problem is the sudden appearance of large amounts of fluid in the lung preventing blood from entering the alveoli and decreasing oxygen extraction resulting in hypoxemia.The tragic feature of ARDS is that it drowns its victim. The appearance of fluid in the lungs  a lethal situation - is from neuro-inflammation.Important to keep in mind when treating ARDS are: a) Inflammation and Inflammatory exudates Gap Formation, b) Interstitial and Alveolar Inflammation, c) Inflammation and the Nervous System, d) Cholinergic anti-inflammatory pathway.Neuro-inflammation can be relieved by stimulation of the vagus nerve. Low-level laser therapy, a simple modality with few undesirable side effects, is used to relieve respiratory distress
Characteristics and Reduction of Sheath Circulating Currents in Underground Power Cable Systems
Authors: Jung C.K. , Lee J.B. , Kang J.W. , Wang Xinheng , Song Yong-Hua
Published: December 2005

Sheath current can cause sheath loss and reduce the permissible current of a power cable transmission system. High sheath current is usually caused by mixed cable burying formation, different length between sections, poor connection of the bonding leads, and connection of distribution cable onto transmission systems. This paper analyses the characteristics of sheath circulating current at various conditions and presents a useful method to reduce it in a mixed burying formation system. It can effectively reduce the current by up to 90%. The method is validated by practical measurements and simulations using ATP, and has been implemented in actual systems. In addition, a special equipment is designed to measure and analyze the sheath circulating current. It can measure and analyze nine currents at a same time.
Available Transfer Capability Determination Using Power Transfer Distribution Factors
Authors: Venkatesh Dr. Paramasivam , Gnanadass Ramachandran , Padhy Dr.Narayana Prasad
Published: December 2005

Electric power industries throughout the world have been restructured to introduce competition among the market participants and bring several competitive opportunities. A fair competition needs open access and non-discriminatory operation of the transmission network. Open access to the transmission system places an emphasis on the intensive use of the interconnected network reliably, which requires knowledge of the network capability. Available Transfer Capability (ATC) is a measure of the remaining power transfer capability of the transmission network for further transactions. This paper describes the assessment of ATC using AC Power transfer distribution factors (ACPTDFs) in combined economic emission dispatch (CEED) environment. The ACPTDFs are derived using sensitivity based approach for the system intact case and utilized to check the line flow limits during ATC determination. The obtained ATC results are compared with Newton Raphson Load Flow method (NRLF) to justify its accuracy. Simultaneous bilateral and multilateral wheeling transactions have been carried out on IEEE 6, 30 and 118 bus systems for the assessment of ATC. The solutions obtained are quite encouraging and useful in the present restructuring environment.
Non-Linear Pricing in Transmission Constrained Electricity Markets: A Congestion Rents Application
Authors: Santiago Jeovani E , Martinez Marcelino M
Published: December 2005

Based on recent research of non-linear pricing for single-node unit commitment models, this paper proposes a transmission constrained non-linear pricing alternative based coordination functions added to the classic decomposition Lagrangian relaxation algorithm to solve transmission constrained unit commitment models. The new coordination algorithms finds agents purchase and sell prices that coordinate the market in the absence of classic equilibrium. Since non-linear prices differ for each agent connected to a transmission node, the value of the congestion rents are redefined so that the new pricing mechanism is taken in to account. The redefinition of congestion rents is necessary so that the implementation of financial transmission rights, in their varied forms, is still possible in order to provide a price hedging mechanism in the nodal spot market.In this study, we propose a solution of unit commitment problem with network constraints and FTR´s using non-linear prices. The proposes prices have been applied to IEEE 14 and 30 test systems with 20 and 35 generators for a single period. The result shows that the proposed prices are capable to obtain satisfactory schedules without any interest conflicts.
A Novel Approach for Classifying Transient Phenomena in Power Transformers
Authors: Tag Eldin El Sayed M.
Published: December 2005

The role of a power transformer protective relay is to rapidly operate the tripping during internal faults and block the tripping during magnetizing inrush. This paper presents a new approach for classifying transient phenomena in power transformer, which may be implemented in digital relaying for transformer differential protection. Discrimination between internal faults, external faults with current transformer saturation and magnetizing inrush currents is achieved by combining wavelet transforms and fuzzy logic. The wavelet transform is applied for the analysis of the power transformer transient phenomena because of its ability to extract information from the transient signals in both time and frequency domain. Fuzzy logic is used because of the uncertainty in the differential current signals and relay settings. MATLAB power system toolbox is used to generate current signals at both sides of a power transformer in a typical system with various conditions. The simulation results obtained show that the new algorithm provides a high operating sensitivity for internal faults and remains stable for external faults and inrush currents.
A Transmission Pricing Mechanism Based on Power Tracing for Central Transmission Utility in India
Authors: Abhyankar A. R , Khaparde S. A , Soman S. A , Pentayya P.
Published: December 2005

In India, apart from state owned generators, a central sector power pool has been created consisting of central sector power stations. The Central Transmission Utility (CTU) has built an EHV network to transfer this power to the constituents of the regional network. To recover the costs incurred, the CTU levies the Transmission Service Charges (TSC) over the constituents. The constituents are billed for network usage charges which are proportional to their allocated share in the central sector power generation. An ideal pricing mechanism would have been to find out the usage of the network by the constituents and charge accordingly. In this paper, a real power tracing based method for recovery of Transmission Service Charge (TSC) from the constituents of Western regional grid in India is proposed. The method uses proportionality based real power tracing to find out the network usage by various constituents. Loss allocation on EHV network to the various constituents is also done. Actual data of power flows over the EHV network of Western regional grid for one day is considered.
Time-Overcurrent Relay Coordination: A Review
Authors: Birla Dinesh , Maheshwari Rudra Prakash , Gupta Hari Om
Published: December 2005

When two protective apparatus installed in series have characteristics, which provide a specified operating sequence, they are said to be coordinated or selective. The coordination of directional overcurrent relays poses serious problems in the modern complex power system networks, which are interconnected. Researchers have looked upon the problem of coordination from different considerations by making use of computer aids. Many efforts have been made to the automation of the coordination process in the area of relay coordination. This paper compiles the most of the significant developments in the area of time-overcurrent relay coordination using different techniques and methodologies. It is hoped that this work will be useful for future generation researchers to find the relevant references to advance the research work in future.
Pulse Multiplication in the Self-Commutating Parallel Converter by Means of Multi-Level DC Voltage Reinjection
Authors: Liu Yonghe , Perera Bernard , Arrillaga Jos , Watson Neville R.
Published: December 2005

A multi-level dc voltage reinjection concept is described that multiplies the pulse number of the twelve-pulse dual parallel converter. The ideal reinjection waveform for complete elimination of the harmonic content is first derived, and a practical approximation is proposed which converts the standard dual converter into a sixty-pulse scheme, thus meeting the strictest harmonic standards without the assistance of filters or Pulse Width Modulation.
An Approach for the Modeling of an Autonomous Induction Generator Taking Into Account the Saturation Effect
Authors: Djamila Dr. Rekioua , Toufik Pr. Rekioua , Kassa Idjdarene , Abdelmounaim Dr. Tounzi
Published: December 2005

This paper deals with a model to simulate the operating of an autonomous induction generator. The model used is a diphase one obtained by the application of the Park transform. This model permits, when adopting some simplifying hypothesis, to take account of the saturation effect. This is achieved using a variable inductance function of the magnetising current. The non linearity is then based on the approximation of the magnetising inductance with regards to the current. In our case, we use a polynomial function, of 12th degree to perform it. This approach is simple and very accurate. The developed model has been used to study the operating of an induction machine when a capacitive bank is connected to the stator windings. The simulation calculation was achieved using MATLAB®-SIMULINK® package. This paper presents transient analysis of the self-excited induction generator. In order to simulate the voltage build-up process and the dynamic behaviour of the machine, we first establish the machine's model based on a d-q axis considering the machines saturation effect. Secondly, effect of excitation capacitors or load imbalances on voltage build-up process is investigated. Simulations results for a 5.5 kW induction generator are presented and discussed. Several experimentations are presented to validate simulations and verify the effectiveness of the developed model.
An Aumann-Shapley Value Based Congestion Cost Allocating Method In Bilateral Transaction Environment
Authors: Yang Hongming , Wang Yu , Lai Mingyong
Published: December 2005

In bilateral transaction market, the congestion relief cost should be allocated in an equitable manner among all the market participants contributing to the congestion. Unfortunately in the allocation of the congestion relief cost to the congested lines, which is the first step of cost allocation, the previously proposed shadow price method and the aggregated allocation method both have some shortcomings. To overcome these shortcomings, a cost allocation method based on the Aumann-Shapley value is proposed. By means of the Aumann-Shapley value, a solution concept in the cooperative game with infinitely many players, the proposed method takes all orders of relieving congestion on the lines into consideration and satisfies the consistency of the allocation, thus guarantees equitable allocation of the congestion relief cost to the congested lines. In addition, the calculating procedure is both simple and accurate due to the use of the Gauss Integration method. Test results show that this method can lead to better allocation than do the shadow price method and the aggregated allocation method.
Sensitivity Based Redispatching Method for Congestion Management in a Pool Model
Authors: Fattahi Abbas , Ehsan Mehdi
Published: December 2005

This paper proposes a new bid based redispatching method to relieve congestion in a pool type market, based on bilateral generation exchanges between generation units. Sensitivity analysis is used to find and implement the cheapest consecutive bilateral exchanges that would remove congestion in an iterative process. Congestion cost is calculated as exchange cost during congestion removal and is divided between congested parts using load flow results in each iteration. Divided cost is recovered from consumers, based on their relative contributions on congested parts using generalized load distribution factors. IEEE 39 and 118 bus test systems are used for case study to evaluate the merits of proposed method and the results are discussed in comparison with other conventional methods.
Real Power Tracing: An Optimization Approach
Authors: Abhyankar A. R , Soman S. A , Khaparde S. A
Published: December 2005

Most tracing algorithms have used variants of proportionality based tracing algorithm. However, proportional sharing is not an inherent characteristic of the system. It is a rule enforced to arrive at a solution in a simple and fair manner. We propose a multi-commodity network flow optimization approach for optimal tracing of power flows. The resulting optimization formulation is shown to be sparse linear programming (LP) problem. The paper is devoted to the constraint modeling of this optimization approach. A unified formulation that models lossy MW flow network and provides consistent results for generation and load tracing is presented. Optimal tracing provides complete power audit information like share of loads in generation, generators' contribution in loads, loss allocation to generators and loads, and decomposition of branch flows into generation and load components. Illustrative examples and results on IEEE 30 bus system show the workability of the proposed approach.
Emergent Technologies In Electrical Microgeneration
Authors: Zamora Dr. Inmaculada , San Martin Jose Ignacio , Mazón Angel Javier , San Martín José Javier , Aperribay Victor
Published: December 2005

Currently, evolution of energy sector is being characterized by liberalization, increase of energy needs and technological advances. This evolution has eliminated the scale economy on which the generation, transmission and distribution systems are based. So, tendency of generation systems is oriented to integrated devices, which will supply the customers demand, either in medium voltage or low voltage networks. The interconnection of small modular generation sources to the low voltage distribution network establishes a new concept, the electrical micro-grid. These micro-grids can be connected to the electrical distribution network or work in an autonomous way and can include different technologies, such as: micro-turbines, wind mills, fuel cells, photovoltaic cells, etc., together with energy storage devices, such as: batteries, condensers, fly-wheels, etc. The content of this paper cover different aspects related with generation and distribution of electrical power in a small scale, and horizontal technologies for industrial, commercial and domestic energy systems. So, this paper presents a revision of current developed technologies, which can be used for electrical microgeneration installations.
Optimal Placement of Reactive Power Compensation Banks for the Maximization of New Generation Capacity
Authors: Vovos Panagis N. , Bialek Janusz W
Published: December 2005

The aim of this paper is to present a novel method for the optimal placement of capacitor and reactor banks, with the objective of maximizing network capacity to absorb new generation. The method is an extension of the Optimal Power Flow used as a tool for network capacity analysis. It can be used to a) plot graphs of the bank investment cost with respect to the increase in network capacity and b) find the optimum investment for the network operator in order to maximize his revenue. A 12-bus low voltage network was used as a test case. The results demonstrate the efficiency of the method to allocate new banks. At a small investment cost, network capacity could nearly double.
Superconducting Magnetic Energy Storage Control Strategy for Power System Stability Improvement
Authors: Griffo Antonio , Lauria Davide
Published: December 2005

Transient stability is recognized as a critical problem for modern electrical power systems, since the deregulation could involve more and more restricted margins. Continuous improvements in power electronics technology gives the possibility to improve significantly the dynamic behaviour. Recently, a great attention in the relevant literature has been paid to Superconducting Magnetic Energy Storage (SMES) devices, showing their intrinsic ability to improve power transmission capability. In the paper, a control strategy for these devices is derived starting from a Control Lyapunov function, thus determining reference values for SMES active and reactive powers injections, able to counteract the effects of large disturbances. Hence, a new topology of the power conditioning system for interfacing SMES device with a power system is proposed. Finally, a control law based upon quasi-sliding technique is employed for tracking the required active and reactive powers. In the last part of the paper an application is presented, with reference to a test system, allowing to outline the flexibility and the goodness of the proposed control strategy.
Natural Heat Transfer Coefficients of Chicken Drum Shaped Bodies
Authors: Ngadi Michael , Ikediala Julian N.
Published: December 2005

Average heat transfer coefficients of chicken drum shaped bodies were estimated using aluminum chicken drum shaped models. Three model drum sizes namely small, medium and large, and three frying oil viscosities for three temperature differences were used. Estimated heat transfer coefficients were in the range from 67 to 163 W/m²K. Increasing temperature difference increased heat transfer coefficient. Conversely, increasing the size of the chicken drum model bodies and oil viscosities decreased the heat transfer coefficient. A heat transfer correlation equation between average Nu and Ra was derived. The methodology developed in this study could be used to estimate heat transfer coefficients of chicken drum during deep-fat frying.