First Observation of Vector Boson Pairs in a Hadronic Final State at the Tevatron Collider

We present the first observation in hadronic collisions of the electroweak production of vector boson pairs (VV, V=W, Z) where one boson decays to a dijet final state. The data correspond to 3.5  fb-1 of integrated luminosity of pp̅ collisions at √s=1.96  TeV collected by the CDF II detector at the Fermilab Tevatron. We observe 1516±239(stat)±144(syst) diboson candidate events and measure a cross section σ(pp̅ →VV+X) of 18.0±2.8(stat)±2.4(syst)±1.1(lumi)  pb, in agreement with the expectations of the standard model.

First Observation of Vector Boson Pairs in a Hadronic Final State at the Tevatron Collider

We present the first observation in hadronic collisions of the electroweak production of vector boson pairs (VV, V=W,Z) where one boson decays to a dijet final state . The data correspond to 3.5 inverse femtobarns of integrated luminosity of ppbar collisions at sqrt(s)=1.96 TeV collected by the CDFII detector at the Fermilab Tevatron. We observe 1516+/-239(stat)+/-144(syst) diboson candidate events and measure a cross section sigma(ppbar->VV+X) of 18.0+/-2.8(stat)+/-2.4(syst)+/-1.1(lumi) pb, in agreement with the expectations of the standard model.

Stimulation by adenosine 3′,5′-cyclic monophosphate of protein synthesis by adenohypophyseal polyribosomes

Addition of dibutyryl 3′,5′-cyclic AMP to slices of bovine pituitary stimulated incorporation of [3H]leucine into protein, whether or not actinomycin D was present; therefore the influence of 3′,5′-cyclic AMP on protein synthesis by bovine pituitary polysomes was studied. If the cyclic nucleotide was added to the complete protein-synthesizing system (including pH 5.0 enzyme), stimulation of [3H]leucine incorporation occurred only with pH 5.0 enzyme from rat liver; there was no stimulation when homologous enzyme, i.e., from bovine pituitary, was used. Addition of 3′,5′-cyclic AMP to the polysomes, before addition of pH 5.0 enzyme, resulted in stimulation of protein synthesis with either source of enzyme, but stimulation was facilitated to a greater degree, over the range 0.5-2 mM 3′,5′-cyclic AMP, when rat liver was the source. The stimulation of protein synthesis was prevented by the addition of cycloheximide. With rat liver pH 5.0 enzyme the product of hydrolysis of 3′,5′-cyclic AMP was mainly 5′-AMP whereas with pituitary pH 5.0 enzyme there was also dephosphorylation and deamination resulting in production of hypoxanthine and other bases. However, using either source of pH 5.0 enzyme and the complete protein-synthesizing system (i.e., including an ATP-regenerating mechanism) most of the 3H from hydrolysis of [3H]3′,5′-cyclic AMP was incorporated into ATP. The data are seen as compatible with a stimulation by 3′,5′-cyclic AMP of translation by pituitary polysomes; the significance of the importance of the source of pH 5.0 enzyme used in the system is obscure.

Reaction of benzisoxazolium cations with cyclic β-diketones

Reaction of 2-ethylbenzisoxazolium fluoborate (III) with dimedone, dihydroresorcinol, 2-methyldihydroresorcinol and 2-methylcyclopentane-1,3-dione in the presence of base leads to the formation of amides VIII, XI, X and XIII respectively, via the benzoketoketenimine intermediate (IX) and an intramolecular migration. The 7-hydroxy-2-ethylbenzisoxazolium salt (IV) gives the amide (XIV) by double migration. Amides VIII, XI, X and XIII undergo intramolecular Michael reaction to furnish the benzoxazinones (XVI, XVIII, XVII and XXVI). Stereochemistry of this addition is discussed and the conformation in which the CN bond at C-1′ is attached equatorially to the cyclohexanone ring is assigned to the Spirans (XX, XXX and XXVIII). Effect of acids and bases on the amide (VIII) and the spiran (XVI) is described.

Search for new color-octet vector particle decaying to t tbar in p pbar collisions at sqrt{s} = 1.96 TeV

We present the result of a search for a massive color-octet vector particle, (e.g. a massive gluon) decaying to a pair of top quarks in proton-antiproton collisions with a center-of-mass energy of 1.96 TeV. This search is based on 1.9 fb$^{-1}$ of data collected using the CDF detector during Run II of the Tevatron at Fermilab. We study $t\bar{t}$ events in the lepton+jets channel with at least one $b$-tagged jet. A massive gluon is characterized by its mass, decay width, and the strength of its coupling to quarks. These parameters are determined according to the observed invariant mass distribution of top quark pairs. We set limits on the massive gluon coupling strength for masses between 400 and 800 GeV$/c^2$ and width-to-mass ratios between 0.05 and 0.50. The coupling strength of the hypothetical massive gluon to quarks is consistent with zero within the explored parameter space.

Synthesis, structure, transformation studies and catalytic properties of open-framework cadmium thiosulfate compounds

Five new thiosulfate based inorganic-organic hybrid open-framework compounds have been synthesized employing mild reaction conditions. Of the five compounds, [Na-2(H2O)(8)][Cd(C10H8N2)( S2O3)(2)]center dot 2H(2)O, I and [Cd-2(C10H8N2)(2)(HS2O3)(2)(S2O3)(2)][(C10H9N2)(2)(C10H8N2)(2)]center dot 8H(2)O, II have one-dimensional (1D) structures and [Cd(C10H8N2)(H2O)(2)(S2O3)]center dot 2H(2)O, III, [Cd-2(C10H8N2)(3)(S2O3)(2)], IV and [Cd-2(C10H8N2)(2.5)(S2O3)(2)], V have three- dimensional (3D) structures. The 1D structures are somewhat related, formed by the bonding between tetrahedral Cd centers (CdN2S2) and 4,4'-bipyridine (bpy) units. The inter-chain spaces are occupied by the hanging thiosulfate units in both the cases along with Na(H2O)(6) chains in I and free bpy units in II. The three 3D structures have one-dimensional cadmium thiosulfate chains linked by bpy units. Interpenetration has been observed in all the 3D structures. The 3D structures appear to be related and can be derived from fgs net. Transformation studies on the 1D compound, [Na-2(H2O)(8)][Cd(C10H8N2)(S2O3)(2)]center dot 2H(2)O, I, indicated a facile formation of [Cd(C10H8N2)(H2O)(2)(S2O3)]center dot 2H(2)O, III. Prolonged heating of I gave rise to a 3D cadmium sulfate phase, [Cd-2(C10H8N2)(2)(H2O)(3)(SO4)(2)]center dot 2H(2)O, VI. Compound VI has one-dimensional cadmium sulfate chains formed by six-membered rings connected by bpy units to form a 3D structure, which appears to resemble the topological arrangement of III. Transformation studies of III indicates the formation of IV and V, and at a higher temperature a new 3D cadmium sulfate, [Cd(C10H8N2)(SO4)], VII. Compound VII has a 4 x 4 grid cadmium sulfate layers pillared by bpy units. All the compounds were characterized by PXRD, TGA, IR and UV-visible studies. Preliminary studies on the possible use of the 3D compounds (III-VII) in heterogeneous cyanosilylation of imines appear to be promising.

Comparison of Multiclass SVM Classification Methods to Use in a Supportive System for Distance Relay Coordination

This paper aims at evaluating the methods of multiclass support vector machines (SVMs) for effective use in distance relay coordination. Also, it describes a strategy of supportive systems to aid the conventional protection philosophy in combating situations where protection systems have maloperated and/or information is missing and provide selective and secure coordinations. SVMs have considerable potential as zone classifiers of distance relay coordination. This typically requires a multiclass SVM classifier to effectively analyze/build the underlying concept between reach of different zones and the apparent impedance trajectory during fault. Several methods have been proposed for multiclass classification where typically several binary SVM classifiers are combined together. Some authors have extended binary SVM classification to one-step single optimization operation considering all classes at once. In this paper, one-step multiclass classification, one-against-all, and one-against-one multiclass methods are compared for their performance with respect to accuracy, number of iterations, number of support vectors, training, and testing time. The performance analysis of these three methods is presented on three data sets belonging to training and testing patterns of three supportive systems for a region and part of a network, which is an equivalent 526-bus system of the practical Indian Western grid.

Inference on Cointegration in Vector Autoregressive Models (summary section only)

In the thesis we consider inference for cointegration in vector autoregressive (VAR) models. The thesis consists of an introduction and four papers. The first paper proposes a new test for cointegration in VAR models that is directly based on the eigenvalues of the least squares (LS) estimate of the autoregressive matrix. In the second paper we compare a small sample correction for the likelihood ratio (LR) test of cointegrating rank and the bootstrap. The simulation experiments show that the bootstrap works very well in practice and dominates the correction factor. The tests are applied to international stock prices data, and the .nite sample performance of the tests are investigated by simulating the data. The third paper studies the demand for money in Sweden 1970—2000 using the I(2) model. In the fourth paper we re-examine the evidence of cointegration between international stock prices. The paper shows that some of the previous empirical results can be explained by the small-sample bias and size distortion of Johansen’s LR tests for cointegration. In all papers we work with two data sets. The first data set is a Swedish money demand data set with observations on the money stock, the consumer price index, gross domestic product (GDP), the short-term interest rate and the long-term interest rate. The data are quarterly and the sample period is 1970(1)—2000(1). The second data set consists of month-end stock market index observations for Finland, France, Germany, Sweden, the United Kingdom and the United States from 1980(1) to 1997(2). Both data sets are typical of the sample sizes encountered in economic data, and the applications illustrate the usefulness of the models and tests discussed in the thesis.

Electron diffraction patterns from the Al-Mn decagonal phase

The variety of electron diffraction patterns arising from the decagonal phase has been explored using a stereographic analysis for generating the important zone axes as intersection points corresponding to important relvectors. An indexing scheme employing a set of five vectors and an orthogonal vector has been followed. A systematic tilting from the decagonal axis to one of the twofold axes has been adopted to generate a set of experimental diffraction patterns corresponding to the expected patterns from the stereographic analysis with excellent agreement.

Switching frequency variation control in hysteresis PWM controller for IM drives using variable parabolic bands for current error space phasor

Variation of switching frequency over the entire operating speed range of an induction motor (M drive is the major problem associated with conventional two-level three-phase hysteresis controller as well as the space phasor based PWM hysteresis controller. This paper describes a simple hysteresis current controller for controlling the switching frequency variation in the two-level PWM inverter fed IM drives for various operating speeds. A novel concept of continuously variable hysteresis boundary of current error space phasor with the varying speed of the IM drive is proposed in the present work. The variable parabolic boundary for the current error space phasor is suggested for the first time in this paper for getting the switching frequency pattern with the hysteresis controller, similar to that of the constant switching frequency voltage-controlled space vector PWM (VC-SVPWM) based inverter fed IM drive. A generalized algorithm is also developed to determine parabolic boundary for controlling the switching frequency variation, for any IM load. Only the adjacent inverter voltage vectors forming a triangular sector, in which tip of the machine voltage vector ties, are switched to keep current error space vector within the parabolic boundary. The controller uses a self-adaptive sector identification logic, which provides smooth transition between the sectors and is capable of taldng the inverter up to six-step mode of operation, if demanded by drive system. The proposed scheme is simulated and experimentally verified on a 3.7 kW IM drive.

Stability of scheduled message communication over degraded broadcast channels

We develop a multi-class discrete-time processor-sharing queueing model for scheduled message communication over a discrete memoryless degraded broadcast channel. The framework we consider here models both the random message arrivals and the subsequent reliable communication by suitably combining techniques from queueing theory and information theory. Requests for message transmissions are assumed to arrive according to i.i.d. arrival processes. Then, (i) we derive an outer bound to the stability region of message arrival rate vectors achievable by the class of stationary scheduling policies, (ii) we show for any message arrival rate vector that satisfies the outer bound, that there exists a stationary "state-independent" policy that results in a stable system for the corresponding message arrival processes, and (iii) under an asymptotic regime, we show that the stability region of information arrival rate vectors is the information-theoretic capacity region of a degraded broadcast channel.

An intelligent approach using support vector machines for monitoring and identification of faults on transmission systems

Power system disturbances are often caused by faults on transmission lines. When faults occur in a power system, the protective relays detect the fault and initiate tripping of appropriate circuit breakers, which isolate the affected part from the rest of the power system. Generally Extra High Voltage (EHV) transmission substations in power systems are connected with multiple transmission lines to neighboring substations. In some cases mal-operation of relays can happen under varying operating conditions, because of inappropriate coordination of relay settings. Due to these actions the power system margins for contingencies are decreasing. Hence, power system protective relaying reliability becomes increasingly important. In this paper an approach is presented using Support Vector Machine (SVM) as an intelligent tool for identifying the faulted line that is emanating from a substation and finding the distance from the substation. Results on 24-bus equivalent EHV system, part of Indian southern grid, are presented for illustration purpose. This approach is particularly important to avoid mal-operation of relays following a disturbance in the neighboring line connected to the same substation and assuring secure operation of the power systems.

Cluster based core vector machine

Core Vector Machine(CVM) is suitable for efficient large-scale pattern classification. In this paper, a method for improving the performance of CVM with Gaussian kernel function irrespective of the orderings of patterns belonging to different classes within the data set is proposed. This method employs a selective sampling based training of CVM using a novel kernel based scalable hierarchical clustering algorithm. Empirical studies made on synthetic and real world data sets show that the proposed strategy performs well on large data sets.

Minimum enclosing spheres formulations for support vector ordinal regression

We present two new support vector approaches for ordinal regression. These approaches find the concentric spheres with minimum volume that contain most of the training samples. Both approaches guarantee that the radii of the spheres are properly ordered at the optimal solution. The size of the optimization problem is linear in the number of training samples. The popular SMO algorithm is adapted to solve the resulting optimization problem. Numerical experiments on some real-world data sets verify the usefulness of our approaches for data mining.

Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network

In this paper. we propose a novel method using wavelets as input to neural network self-organizing maps and support vector machine for classification of magnetic resonance (MR) images of the human brain. The proposed method classifies MR brain images as either normal or abnormal. We have tested the proposed approach using a dataset of 52 MR brain images. Good classification percentage of more than 94% was achieved using the neural network self-organizing maps (SOM) and 98% front support vector machine. We observed that the classification rate is high for a Support vector machine classifier compared to self-organizing map-based approach.