Low PAPR full-diversity space-frequency codes for MIMO-OFDM systems

Use of precoding transforms such as Hadamard Transforms and Phase Alteration for Peak to Average Power Ratio (PAPR) reduction in OFDM systems are well known. In this paper we propose use of Inverse Discrete Fourier Transform (IDFT) and Hadamard transform as precoding transforms in MIMO-OFDM systems to achieve low peak to average power ratio (PAPR). We show that while our approach using IDFT does not disturb the diversity gains of the MIMO-OFDM systems (spatial, temporal and frequency diversity gains), it offers a better trade-off between PAPR reduction and ML decoding complexity compared to that of the Hadamard transform precoding. We study in detail the amount of PAPR reduction achieved for the following two recently proposed full-diversity Space-Frequency coded MIMO-OFDM systems using both the IDFT and the Hadamard transform: (i) W. Su. Z. Safar, M. Olfat, K. J. R. Liu (IEEE Trans. on Signal Processing, Nov. 2003), and (ii) W. Su, Z. Safar, K. J. R. Liu (IEEE Trans. on Information Theory, Jan. 2005).

High levels of catalytic antibodies correlate with favorable outcome in sepsis

Sepsis is the leading cause of death in intensive care units and results from a deleterious systemic host response to infection. Although initially perceived as potentially deleterious, catalytic antibodies have been proposed to participate in removal of metabolic wastes and protection against infection. Here we show that the presence in plasma of IgG endowed with serine protease-like hydrolytic activity strongly correlates with survival from sepsis. Variances of catalytic rates of IgG were greater in the case of patients with severe sepsis than healthy donors (P < 0.001), indicating that sepsis is associated with alterations in plasma levels of hydrolytic IgG. The catalytic rates of IgG from patients who survived were significantly greater than those of IgG from deceased patients (P < 0.05). The cumulative rate of survival was higher among patients exhibiting high rates of IgG-mediated hydrolysis as compared with patients with low hydrolytic rates (P < 0.05). An inverse correlation was also observed between the markers of severity of disseminated intravascular coagulation and rates of hydrolysis of patients' IgG. Furthermore, IgG from three surviving patients hydrolyzed factor VIII, one of which also hydrolyzed factor IX, suggesting that, in some patients, catalytic IgG may participate in the control of disseminated microvascular thrombosis. Our observations provide the first evidence that hydrolytic antibodies might play a role in recovery from a disease.

Metabolism of ubiquinone in relation to vitamin a status in the rat

1. 1. Biosynthetic experiments in vitro with slices of livers from normal and vitamin A-deficient rats confirmed that synthesis of ubiquinone did not increase in vitamin A deficiency. 2. 2. During development of deficiency of vitamin A in the rat, there was a definite increase in the synthesis of ubiquinone at the 10-days stage but this reverted to low, initial level by 20 days and after. 3. 3. Vitamin A analogues, 3-dehydroretinal, 5,6-monoepoxyretinal and retinoic acid, which supported growth have restored ubiquinone concentration to the normal levels and relieved the lowering in its catabolism. The biologically inert 5,8-monoepoxyretinal was the least active of the analogues tested. 4. 4. The concentration and synthesis of ubiquinone in the liver decreased under conditions of hypervitaminosis A. 5. 5. The experimental evidence does not support the hypothesis of inverse relationship between vitamin A and ubiquinone synthesis.

Propagation of a spherical shock in an inhomogeneous self-gravitating or nongravitating system

The propagation of a shock wave of finite strength due to an explosion into inhomogeneous nongravitating and self-gravitating systems has been considered, using similarity principles, supposing that the density varies as an inverse power of distance from the centre of explosion. A large number of systems, characterised by different density exponents and different adiabatic coefficients of the gas have been considered for different shock strengths. The numerical integration from the shock inward has been continued to the surface of singularity where density tends to infinity and which acts like a piston in the self-gravitating case and to the surface where the velocity gradient tends to infinity in the nongravitating case. The effect of variation of shock strength, density exponent and adiabatic coefficient on the location of these singularities and on the distribution of flow parameters behind the shock has been studied. The initial energy of the system and the manner of release of the explosion energy influence strongly the flow behind the shock. The results have been graphically depicted.

Diffractive W and Z production at the Fermilab Tevatron

We report on a measurement of the fraction of events with a W or Z boson produced diffractively in antiproton-proton collisions at a center of mass energy of 1.96 TeV, using data from 0.6 inverse femtobarns of integrated luminosity collected with the CDF-II detector equipped with a Roman-pot spectrometer that detects the antiproton (pbar) from pbar+p --> pbar+[X+W/Z]. We find that (0.97 +/- 0.11)% of Ws and (0.85 +/- 0.22)% of Zs are produced diffractively in a region of (anti)proton fractional momentum loss (\xi) of 0.03-1t p+[X+W/Z]+pbar, and on exclusive Z production, pbar+p-->pbar+Z+p. No signal is seen above background for these processes, and comparisons are made with expectations.

Self-regularized pseudo time-marching schemes for structural system identification with static measurements

We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time,recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through a pseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets of measurements involving various load cases, we expedite the speed of thePD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small.

Self-regularized pseudo time-marching schemes for structural system identification with static measurements

We explore the application of pseudo time marching schemes, involving either deterministic integration or stochastic filtering, to solve the inverse problem of parameter identification of large dimensional structural systems from partial and noisy measurements of strictly static response. Solutions of such non-linear inverse problems could provide useful local stiffness variations and do not have to confront modeling uncertainties in damping, an important, yet inadequately understood, aspect in dynamic system identification problems. The usual method of least-square solution is through a regularized Gauss-Newton method (GNM) whose results are known to be sensitively dependent on the regularization parameter and data noise intensity. Finite time, recursive integration of the pseudo-dynamical GNM (PD-GNM) update equation addresses the major numerical difficulty associated with the near-zero singular values of the linearized operator and gives results that are not sensitive to the time step of integration. Therefore, we also propose a pseudo-dynamic stochastic filtering approach for the same problem using a parsimonious representation of states and specifically solve the linearized filtering equations through apseudo-dynamic ensemble Kalman filter (PD-EnKF). For multiple sets ofmeasurements involving various load cases, we expedite the speed of the PD-EnKF by proposing an inner iteration within every time step. Results using the pseudo-dynamic strategy obtained through PD-EnKF and recursive integration are compared with those from the conventional GNM, which prove that the PD-EnKF is the best performer showing little sensitivity to process noise covariance and yielding reconstructions with less artifacts even when the ensemble size is small. Copyright (C) 2009 John Wiley & Sons, Ltd.

Search for standard model Higgs boson production in association with a W boson using a neural network discriminant at CDF

We present a search for standard model Higgs boson production in association with a W boson in proton-antiproton collisions at a center of mass energy of 1.96 TeV. The search employs data collected with the CDF II detector that correspond to an integrated luminosity of approximately 1.9 inverse fb. We select events consistent with a signature of a single charged lepton, missing transverse energy, and two jets. Jets corresponding to bottom quarks are identified with a secondary vertex tagging method, a jet probability tagging method, and a neural network filter. We use kinematic information in an artificial neural network to improve discrimination between signal and background compared to previous analyses. The observed number of events and the neural network output distributions are consistent with the standard model background expectations, and we set 95% confidence level upper limits on the production cross section times branching fraction ranging from 1.2 to 1.1 pb or 7.5 to 102 times the standard model expectation for Higgs boson masses from 110 to $150 GeV/c^2, respectively.

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.

New Method for Delexicalization and its Application to Prosodic Tagging for Text-to-Speech Synthesis

This paper describes a new flexible delexicalization method based on glottal excited parametric speech synthesis scheme. The system utilizes inverse filtered glottal flow and all-pole modelling of the vocal tract. The method provides a possibil- ity to retain and manipulate all relevant prosodic features of any kind of speech. Most importantly, the features include voice quality, which has not been properly modeled in earlier delex- icalization methods. The functionality of the new method was tested in a prosodic tagging experiment aimed at providing word prominence data for a text-to-speech synthesis system. The ex- periment confirmed the usefulness of the method and further corroborated earlier evidence that linguistic factors influence the perception of prosodic prominence.

The Influence of Titania on Creep in Superplastic Zirconia

Detailed high-temperature compression creep experiments on a pure 3 mol% yttria-stabilized tetragonal zirconia (3YTZ) and 3YTZ doped with 4.8 wt% TiO2 revealed that both materials exhibit a similar transition in stress exponents from n similar to 1 to n similar to 2 with a decrease in stress. The stress exponent of 1 and the inverse grain size dependence p of similar to 3 are consistent with the Coble diffusion creep at high stresses; the increase in stress exponent at low stresses is attributed to an interface-controlled diffusion creep process. Measurements revealed that grain-boundary sliding contributes to >similar to 50% of the total strain in both regions with n similar to 1 and n similar to 2, indicating the operation of the same fundamental deformation process in both regions. The creep data indicate that doping with TiO2 leads to an increase in the grain-boundary diffusion coefficients. The increase observed in the dihedral angle with doping is also consistent with the increase in grain boundary diffusion coefficient and the reported enhanced ductility in such materials.

Essays on the Modeling and Prediction of Volatility and Higher Moments of Stock Returns (summary section only)

One of the most fundamental and widely accepted ideas in finance is that investors are compensated through higher returns for taking on non-diversifiable risk. Hence the quantification, modeling and prediction of risk have been, and still are one of the most prolific research areas in financial economics. It was recognized early on that there are predictable patterns in the variance of speculative prices. Later research has shown that there may also be systematic variation in the skewness and kurtosis of financial returns. Lacking in the literature so far, is an out-of-sample forecast evaluation of the potential benefits of these new more complicated models with time-varying higher moments. Such an evaluation is the topic of this dissertation. Essay 1 investigates the forecast performance of the GARCH (1,1) model when estimated with 9 different error distributions on Standard and Poor’s 500 Index Future returns. By utilizing the theory of realized variance to construct an appropriate ex post measure of variance from intra-day data it is shown that allowing for a leptokurtic error distribution leads to significant improvements in variance forecasts compared to using the normal distribution. This result holds for daily, weekly as well as monthly forecast horizons. It is also found that allowing for skewness and time variation in the higher moments of the distribution does not further improve forecasts. In Essay 2, by using 20 years of daily Standard and Poor 500 index returns, it is found that density forecasts are much improved by allowing for constant excess kurtosis but not improved by allowing for skewness. By allowing the kurtosis and skewness to be time varying the density forecasts are not further improved but on the contrary made slightly worse. In Essay 3 a new model incorporating conditional variance, skewness and kurtosis based on the Normal Inverse Gaussian (NIG) distribution is proposed. The new model and two previously used NIG models are evaluated by their Value at Risk (VaR) forecasts on a long series of daily Standard and Poor’s 500 returns. The results show that only the new model produces satisfactory VaR forecasts for both 1% and 5% VaR Taken together the results of the thesis show that kurtosis appears not to exhibit predictable time variation, whereas there is found some predictability in the skewness. However, the dynamic properties of the skewness are not completely captured by any of the models.

Executive Stock Options: Exercise Policy and Market Reaction

In this paper I investigate the exercise policy, and the market reaction to that, of the executive stock option holders in Finland. The empirical tests are conducted with aggregated firm level data from 34 firms and 41 stock option programs. I find some evidence of an inverse relation between the exercise intensity of the options holders and the future abnormal return of the company share price. This finding is supported by the view that information about future company prospect seems to be the only theoretical attribute that could delay the exercise of the options. Moreover, a high concentration of exercises in the beginning of the exercise window is predicted and the market is expected to react to deviations from this. The empirical findings however show that the market does not react homogenously to the information revealed by the late exercises.

Image reconstruction by inhomogeneous diffusion for positron emission tomography

In positron emission tomography (PET), image reconstruction is a demanding problem. Since, PET image reconstruction is an ill-posed inverse problem, new methodologies need to be developed. Although previous studies show that incorporation of spatial and median priors improves the image quality, the image artifacts such as over-smoothing and streaking are evident in the reconstructed image. In this work, we use a simple, yet powerful technique to tackle the PET image reconstruction problem. Proposed technique is based on the integration of Bayesian approach with that of finite impulse response (FIR) filter. A FIR filter is designed whose coefficients are determined based on the surface diffusion model. The resulting reconstructed image is iteratively filtered and fed back to obtain the new estimate. Experiments are performed on a simulated PET system. The results show that the proposed approach is better than recently proposed MRP algorithm in terms of image quality and normalized mean square error.