Site characterization model using least-square support vector machine and relevance vector machine based on corrected SPT data (N-c)

Statistical learning algorithms provide a viable framework for geotechnical engineering modeling. This paper describes two statistical learning algorithms applied for site characterization modeling based on standard penetration test (SPT) data. More than 2700 field SPT values (N) have been collected from 766 boreholes spread over an area of 220 sqkm area in Bangalore. To get N corrected value (N,), N values have been corrected (Ne) for different parameters such as overburden stress, size of borehole, type of sampler, length of connecting rod, etc. In three-dimensional site characterization model, the function N-c=N-c (X, Y, Z), where X, Y and Z are the coordinates of a point corresponding to N, value, is to be approximated in which N, value at any half-space point in Bangalore can be determined. The first algorithm uses least-square support vector machine (LSSVM), which is related to aridge regression type of support vector machine. The second algorithm uses relevance vector machine (RVM), which combines the strengths of kernel-based methods and Bayesian theory to establish the relationships between a set of input vectors and a desired output. The paper also presents the comparative study between the developed LSSVM and RVM model for site characterization. Copyright (C) 2009 John Wiley & Sons,Ltd.

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.

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.

Expression of lactate transporters MCT1, MCT2, MCT4 and the ancillary protein CD147 in horse muscle and red blood cells

Monocarboxylate transporters (MCTs) transport lactate and protons across cell membranes. During intense exercise, lactate and protons accumulate in the exercising muscle and are transported to the plasma. In the horse, MCTs are responsible for the majority of lactate and proton removal from exercising muscle, and are therefore also the main mechanism to hinder the decline in pH in muscle cells. Two isoforms, MCT1 and MCT4, which need an ancillary protein CD147, are expressed in equine muscle. In the horse, as in other species, MCT1 is predominantly expressed in oxidative fibres, where its likely role is to transport lactate into the fibre to be used as a fuel at rest and during light work, and to remove lactate during intensive exercise when anaerobic energy production is needed. The expression of CD147 follows the fibre type distribution of MCT1. These proteins were detected in both the cytoplasm and sarcolemma of muscle cells in the horse breeds studied: Standardbred and Coldblood trotters. In humans, training increases the expression of both MCT1 and MCT4. In this study, the proportion of oxidative fibres in the muscle of Norwegian-Swedish Coldblood trotters increased with training. Simultaneously, the expression of MCT1 and CD147, measured immunohistochemically, seemed to increase more in the cytoplasm of oxidative fibres than in the fast fibre type IIB. Horse MCT4 antibody failed to work in immunohistochemistry. In the future, a quantitative method should be introduced to examine the effect of training on muscle MCT expression in the horse. Lactate can be taken up from plasma by red blood cells (RBCs). In horses, two isoforms, MCT1 and MCT2, and the ancillary protein CD147 are expressed in RBC membranes. The horse is the only species studied in which RBCs have been found to express MCT2, and the physiological role of this protein in RBCs is unknown. The majority of horses express all three proteins, but 10-20% of horses express little or no MCT1 or CD147. This leads to large interindividual variation in the capacity to transport lactate into RBCs. Here, the expression level of MCT1 and CD147 was bimodally distributed in three studied horse breeds: Finnhorse, Standardbred and Thoroughbred. The level of MCT2 expression was distributed unimodally. The expression level of lactate transporters could not be linked to performance markers in Thoroughbred racehorses. In the future, better performance indexes should be developed to better enable the assessment of whether the level of MCT expression affects athletic performance. In human subjects, several mutations in MCT1 have been shown to cause decreased lactate transport activity in muscle and signs of myopathy. In the horse, two amino acid sequence variations, one of which was novel, were detected in MCT1 (V432I and K457Q). The mutations found in horses were in different areas compared to mutations found in humans. One mutation (M125V) was detected in CD147. The mutations found could not be linked with exercise-induced myopathy. MCT4 cDNA was sequenced for the first time in the horse, but no mutations could be detected in this protein.

Lattice vibrations and specific heat of zinc blende

The dispersion relations, frequency distribution function and specific heat of zinc blende have been calculated using Houston's method on (1) A short range force (S. R.) model of the type employed in diamond by Smith and (2) A long range model assuming an effective charge Ze on the ions. Since the elastic constant data on ZnS are not in agreement with one another the following values were used in these calculations: {Mathematical expression}. As compared to the results on the S. R. model, the Coulomb force causes 1. A splitting of the optical branches at (000) and a larger dispersion of these branches; 2. A rise in the acoustic frequency branches the effect being predominant in a transverse acoustic branch along [110]; 3. A bridging of the gap of forbidden frequencies in the S. R. model; 4. A reduction of the moments of the frequency distribution function and 5. A flattening of the Θ- T curve. By plotting (Θ/Θ0) vs. T., the experimental data of Martin and Clusius and Harteck are found to be in perfect coincidence with the curve for the short range model. The values of the elastic constants deduced from the ratio Θ0 (Theor)/Θ0 (Expt) agree with those of Prince and Wooster. This is surprising as several lines of evidence indicate that the bond in zinc blende is partly covalent and partly ionic. The conclusion is inescapable that the effective charge in ZnS is a function of the wave vector {Mathematical expression}.

Cloning, expression, purification, crystallization and preliminary X-ray crystallographic study of the putative SAICAR synthetase (PH0239) from Pyrococcus horikoshii OT3

The study of proteins involved in de novo biosynthesis of purine nucleotides is central in the development of antibiotics and anticancer drugs. In view of this, a protein from the hyperthermophile Pyrococcus horikoshii OT3 was isolated, purified and crystallized using the microbatch method. Its primary structure was found to be similar to that of SAICAR synthetase, which catalyses the seventh step of de novo purine biosynthesis. A diffraction-quality crystal was obtained using Hampton Research Crystal Screen II condition No. 34, consisting of 0.05 M cadmium sulfate hydrate, 0.1 M HEPES buffer pH 7.5 and 1.0 M sodium acetate trihydrate, with 40%(v/v) 1,4-butanediol as an additive. The crystal belonged to space group P3(1), with unit-cell parameters a = b = 95.62, c = 149.13 angstrom. Assuming the presence of a hexamer in the asymmetric unit resulted in a Matthews coefficient (V-M) of 2.3 angstrom(3) Da(-1), corresponding to a solvent content of about 46%. A detailed study of this protein will yield insights into structural stability at high temperatures and should be highly relevant to the development of antibiotics and anticancer drugs targeting the biosynthesis of purine nucleotides.

Japanese Encephalitis Virus Utilizes the Canonical Pathway To Activate NF-kappa B but It Utilizes the Type I Interferon Pathway To Induce Major Histocompatibility Complex Class I Expression in Mouse Embryonic Fibroblasts

Flaviviruses have been shown to induce cell surface expression of major histocompatibility complex class I (MHC-I) through the activation of NF-kappa B. Using IKK1(-/-), IKK2(-/-), NEMO-/-, and IKK1-/- IKK2-/- double mutant as well as p50(-/-) RelA(-/-) cRel(-/-) triple mutant mouse embryonic fibroblasts infected with Japanese encephalitis virus (JEV), we show that this flavivirus utilizes the canonical pathway to activate NF-kappa B in an IKK2- and NEMO-, but not IKK1-, dependent manner. NF-kappa B DNA binding activity induced upon virus infection was shown to be composed of RelA: p50 dimers in these fibroblasts. Type I interferon (IFN) production was significantly decreased but not completely abolished upon virus infection in cells defective in NF-kappa B activation. In contrast, induction of classical MHC-I (class 1a) genes and their cell surface expression remained unaffected in these NF-kappa B-defective cells. However, MHC-I induction was impaired in IFNAR(-/-) cells that lack the alpha/beta IFN receptor, indicating a dominant role of type I IFNs but not NF-kappa B for the induction of MHC-I molecules by Japanese encephalitis virus. Our further analysis revealed that the residual type I IFN signaling in NF-kappa B-deficient cells is sufficient to drive MHC-I gene expression upon virus infection in mouse embryonic fibroblasts. However, NF-kappa B could indirectly regulate MHC-I expression, since JEV-induced type I IFN expression was found to be critically dependent on it.

ErbB-2 expression and its association with other biological parameters of breast cancer among Indian women

Overexpression of the epidermal growth factor receptor family genes, which include ErbB-1, 2, 3 and 4, has been implicated in a number of cancers. We have studied the extent of ErbB-2 overexpression among Indian women with sporadic breast cancer. Methods: Immmunohistochemistry and genomic polymerase chain reaction (PCR) were used to study the ErbB2 overexpression. ErbB2 status was correlated with other clinico-pathological parameters, including patient survival. Results: ErbB-2 overexpression was detected in 43.2% (159/368) of the cases by immunohistochemistry. For a sub-set of patients (n = 55) for whom total DNA was available, ErbB-2 gene amplification was detected in 25.5% (14/55) of the cases by genomic PCR. While the ErbB2 overexpression was significantly higher in patients with lymphnode (χ2 = 12.06, P≤ 0.001), larger tumor size (χ2 = 8.22, P = 0.042) and ductal carcinoma (χ2 = 15.42, P ≤ 0.001), it was lower in patients with disease-free survival (χ2 = 22.13, P ≤ 0.001). Survival analysis on a sub-set of patients for whom survival data were available (n = 179) revealed that ErbB-2 status (χ2 =25.94, P ≤ 0.001), lymphnode status (χ2 = 12.68, P ≤ 0.001), distant metastasis (χ2 = 19.49, P ≤ 0.001) and stage of the disease (χ2 = 28.04, P ≤0.001) were markers of poor prognosis. Conclusions: ErbB-2 overexpression was significantly greater compared with the Western literature, but comparable to other Indian studies. Significant correlation was found between ErbB-2 status and lymphnode status, tumor size and ductal carcinoma. ErbB-2 status, lymph node status, distant metastasis and stage of the disease were found to be prognostic indicators.

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.

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.