Simultaneous prediction of acidity parameters (pH and titratable acidity) in Kefir using near infrared reflectance spectroscopy.

Acidity in terms of pH and titratable acids influences the texture and flavour of fermented dairy products, such as Kefir. However, the methods for determining pH and titratable acidity (TA) are time consuming. Near infrared (NIR) spectroscopy is a non-destructive method, which simultaneously predicts multiple traits from a single scan and can be used to predict pH and TA. The best pH NIR calibration model was obtained with no spectral pre-treatment applied, whereas smoothing was found to be the best pre-treatment to develop the TA calibration model. Using cross-validation, the prediction results were found acceptable for both pH and TA. With external validation, similar results were found for pH and TA, and both models were found to be acceptable for screening purposes.

Simultaneous adsorption of Cd(II) and phosphate on Al13 pillared montmorillonite

Al13 pillared montmorillonites (AlPMts) prepared with different Al/clay ratios were used to remove Cd(II) and phosphate from aqueous solution. The structure of AlPMts was characterized by X-ray diffraction (XRD), Thermogravimetric analysis (TG), and N2 adsorption–desorption. The basal spacing, intercalated amount of Al13 cations, and specific surface area of AlPMts increased with the increase of the Al/clay ratio. In the single adsorption system, with the increase of the Al/clay ratio, the adsorption of phosphate on AlPMts increased but that of Cd(II) decreased. Significantly enhanced adsorptions of Cd(II) and phosphate on AlPMts were observed in a simultaneous system. For both contaminants, the adsorption of one contaminant would increase with the increase of the initial concentration of the other one and increase in the Al/clay ratio. The enhancement of the adsorption of Cd(II) was much higher than that of phosphate on AlPMt. This suggests that the intercalated Al13 cations are the primary co-adsorption sites for phosphate and Cd(II). X-ray photoelectron spectroscopy (XPS) indicated comparable binding energy of P2p but a different binding energy of Cd3d in single and simultaneous systems. The adsorption and XPS results suggested that the formation of P-bridge ternary surface complexes was the possible adsorption mechanism for promoted uptake of Cd(II) and phosphate on AlPMt.

Optimal simultaneous maximum a posterioriestimation of states, noise statistics and parameters I. Algorithm

The simultaneous state and parameter estimation problem for a linear discrete-time system with unknown noise statistics is treated as a large-scale optimization problem. The a posterioriprobability density function is maximized directly with respect to the states and parameters subject to the constraint of the system dynamics. The resulting optimization problem is too large for any of the standard non-linear programming techniques and hence an hierarchical optimization approach is proposed. It turns out that the states can be computed at the first levelfor given noise and system parameters. These, in turn, are to be modified at the second level.The states are to be computed from a large system of linear equations and two solution methods are considered for solving these equations, limiting the horizon to a suitable length. The resulting algorithm is a filter-smoother, suitable for off-line as well as on-line state estimation for given noise and system parameters. The second level problem is split up into two, one for modifying the noise statistics and the other for modifying the system parameters. An adaptive relaxation technique is proposed for modifying the noise statistics and a modified Gauss-Newton technique is used to adjust the system parameters.

Optimal simultaneous maximum a posterioriestimation of states, noise statistics and parameters II. Numerical performance

A very general and numerically quite robust algorithm has been proposed by Sastry and Gauvrit (1980) for system identification. The present paper takes it up and examines its performance on a real test example. The example considered is the lateral dynamics of an aircraft. This is used as a vehicle for demonstrating the performance of various aspects of the algorithm in several possible modes.

A simple, one-tube assay for the simultaneous detection and diagnosis of ten Australian poultry Eimeria

Coccidiosis is a costly worldwide enteric disease of chickens caused by parasites of the genus Eimeria. At present, there are seven described species that occur globally and a further three undescribed, operational taxonomic units (OTUs X, Y, and Z) that are known to infect chickens from Australia. Species of Eimeria have both overlapping morphology and pathology and frequently occur as mixed-species infections. This makes definitive diagnosis with currently available tests difficult and, to date, there is no test for the detection of the three OTUs. This paper describes the development of a PCR-based assay that is capable of detecting all ten species of Eimeria, including OTUs X, Y, and Z in field samples. The assay is based on a single set of generic primers that amplifies a single diagnostic fragment from the mitochondrial genome of each species. This one-tube assay is simple, low-cost, and has the capacity to be high throughput. It will therefore be of great benefit to the poultry industry for Eimeria detection and control, and the confirmation of identity and purity of vaccine strains.

On the Solution of Certain Simultaneous Pairs of Dual Integral Equations

Mit einer direkten Methode, bei der der Erdelyi-Kober- und der modifizierte Hankel-Operator Anwendung finden, werden gewisse Systeme aus zwei bzw. drei Paaren dualer Integralgleichungen mit Bessel-Kernen in geschlossener Form gelöst. Für bestimmte Funktionenklassen und Ordnungen der Bessel-Funktionen ist die Vorgehensweise angebrachter und geeigneter als die bereits existierenden Methoden.

Information flow, trading activity and commodity futures volatility

Based on unique news data relating to gold and crude oil, we investigate how news volume and sentiment, shocks in trading activity, market depth and trader positions unrelated to information flow covary with realized volatility. Positive shocks to the rate of news arrival, and negative shocks to news sentiment exhibit the largest effects. After controlling for the level of news flow and cross-correlations, net trader positions play only a minor role. These findings are at odds with those of [Wang (2002a). The Journal of Futures Markets, 22, 427–450; Wang (2002b). The Financial Review, 37, 295–316], but are consistent with the previous literature which doesn't find a strong link between volatility and trader positions.

Modeling Asymmetries in Financial Data with Multiplicative Error Models

This thesis addresses modeling of financial time series, especially stock market returns and daily price ranges. Modeling data of this kind can be approached with so-called multiplicative error models (MEM). These models nest several well known time series models such as GARCH, ACD and CARR models. They are able to capture many well established features of financial time series including volatility clustering and leptokurtosis. In contrast to these phenomena, different kinds of asymmetries have received relatively little attention in the existing literature. In this thesis asymmetries arise from various sources. They are observed in both conditional and unconditional distributions, for variables with non-negative values and for variables that have values on the real line. In the multivariate context asymmetries can be observed in the marginal distributions as well as in the relationships of the variables modeled. New methods for all these cases are proposed. Chapter 2 considers GARCH models and modeling of returns of two stock market indices. The chapter introduces the so-called generalized hyperbolic (GH) GARCH model to account for asymmetries in both conditional and unconditional distribution. In particular, two special cases of the GARCH-GH model which describe the data most accurately are proposed. They are found to improve the fit of the model when compared to symmetric GARCH models. The advantages of accounting for asymmetries are also observed through Value-at-Risk applications. Both theoretical and empirical contributions are provided in Chapter 3 of the thesis. In this chapter the so-called mixture conditional autoregressive range (MCARR) model is introduced, examined and applied to daily price ranges of the Hang Seng Index. The conditions for the strict and weak stationarity of the model as well as an expression for the autocorrelation function are obtained by writing the MCARR model as a first order autoregressive process with random coefficients. The chapter also introduces inverse gamma (IG) distribution to CARR models. The advantages of CARR-IG and MCARR-IG specifications over conventional CARR models are found in the empirical application both in- and out-of-sample. Chapter 4 discusses the simultaneous modeling of absolute returns and daily price ranges. In this part of the thesis a vector multiplicative error model (VMEM) with asymmetric Gumbel copula is found to provide substantial benefits over the existing VMEM models based on elliptical copulas. The proposed specification is able to capture the highly asymmetric dependence of the modeled variables thereby improving the performance of the model considerably. The economic significance of the results obtained is established when the information content of the volatility forecasts derived is examined.

Instrument for simultaneous assessment of tear film surface quality and subjective vision

To develop and test a custom-built instrument to simultaneously assess tear film surface quality (TFSQ) and subjective vision score (SVS).

The use of metabolomics to monitor simultaneous changes in metabolic variables following supramaximal low volume high intensity exercise

High Intensity Exercise (HIE) stimulates greater physiological remodeling when compared to workload matched low-moderate intensity exercise. This study utilized an untargeted metabolomics approach to examine the metabolic perturbations that occur following two workload matched supramaximal low volume HIE trials. In a randomized order, 7 untrained males completed two exercise protocols separated by one week; 1) HIE150%: 30 x 20s cycling at 150% VO2peak, 40s passive rest; 2) HIE300%: 30 x 10s cycling at 300% VO2peak, 50 s passive rest. Total exercise duration was 30 minutes for both trials. Blood samples were taken at rest, during and immediately following exercise and at 60 minutes post exercise. Gas chromatography-mass spectrometry (GC-MS) analysis of plasma identified 43 known metabolites of which 3 demonstrated significant fold changes (HIE300% compared to the HIE150% value) during exercise, 14 post exercise and 23 at the end of the recovery period. Significant changes in plasma metabolites relating to lipid metabolism [fatty acids: dodecanoate (p=0.042), hexadecanoate (p=0.001), octadecanoate (p=0.001)], total cholesterol (p=0.001), and glycolysis [lactate (p=0.018)] were observed following exercise and during the recovery period. The HIE300% protocol elicited greater metabolic changes relating to lipid metabolism and glycolysis when compared to HIE150% protocol. These changes were more pronounced throughout the recovery period rather than during the exercise bout itself. Data from the current study demonstrate the use of metabolomics to monitor intensity-dependent changes in multiple metabolic pathways following exercise. The small sample size indicates a need for further studies in a larger sample cohort to validate these findings.

Analytical method for solving a set of inhomogeneous infinite simultaneous equations

It is shown that a method based on the principle of analytic continuation can be used to solve a set of inhomogeneous infinite simultaneous equations encountered in the analysis of surface acoustic wave propagation along the periodically perturbed surface of a piezoelectric medium.

A heterogeneous computing approach to simulation of the Heston Stochastic Volatility Model

Stochastic volatility models are of fundamental importance to the pricing of derivatives. One of the most commonly used models of stochastic volatility is the Heston Model in which the price and volatility of an asset evolve as a pair of coupled stochastic differential equations. The computation of asset prices and volatilities involves the simulation of many sample trajectories with conditioning. The problem is treated using the method of particle filtering. While the simulation of a shower of particles is computationally expensive, each particle behaves independently making such simulations ideal for massively parallel heterogeneous computing platforms. In this paper, we present our portable Opencl implementation of the Heston model and discuss its performance and efficiency characteristics on a range of architectures including Intel cpus, Nvidia gpus, and Intel Many-Integrated-Core (mic) accelerators.

Elements of Volatility at High Frequency

Volatility is central in options pricing and risk management. It reflects the uncertainty of investors and the inherent instability of the economy. Time series methods are among the most widely applied scientific methods to analyze and predict volatility. Very frequently sampled data contain much valuable information about the different elements of volatility and may ultimately reveal the reasons for time varying volatility. The use of such ultra-high-frequency data is common to all three essays of the dissertation. The dissertation belongs to the field of financial econometrics. The first essay uses wavelet methods to study the time-varying behavior of scaling laws and long-memory in the five-minute volatility series of Nokia on the Helsinki Stock Exchange around the burst of the IT-bubble. The essay is motivated by earlier findings which suggest that different scaling laws may apply to intraday time-scales and to larger time-scales, implying that the so-called annualized volatility depends on the data sampling frequency. The empirical results confirm the appearance of time varying long-memory and different scaling laws that, for a significant part, can be attributed to investor irrationality and to an intraday volatility periodicity called the New York effect. The findings have potentially important consequences for options pricing and risk management that commonly assume constant memory and scaling. The second essay investigates modelling the duration between trades in stock markets. Durations convoy information about investor intentions and provide an alternative view at volatility. Generalizations of standard autoregressive conditional duration (ACD) models are developed to meet needs observed in previous applications of the standard models. According to the empirical results based on data of actively traded stocks on the New York Stock Exchange and the Helsinki Stock Exchange the proposed generalization clearly outperforms the standard models and also performs well in comparison to another recently proposed alternative to the standard models. The distribution used to derive the generalization may also prove valuable in other areas of risk management. The third essay studies empirically the effect of decimalization on volatility and market microstructure noise. Decimalization refers to the change from fractional pricing to decimal pricing and it was carried out on the New York Stock Exchange in January, 2001. The methods used here are more accurate than in the earlier studies and put more weight on market microstructure. The main result is that decimalization decreased observed volatility by reducing noise variance especially for the highly active stocks. The results help risk management and market mechanism designing.

Analytical method for solving a set of infinite simultaneous equations

It is shown that a method based on the principle of analytic continuation can be used to solve a set of infinite simultaneous equations encountered in solving for the electric field of a periodic electrode structure.

Synthesis of Thioesters by Simultaneous Activation of Carboxylic Acids and Alcohols Using PPh3/NBS with Benzyltriethylammonium Tetrathiomolybdate as the Sulfur Transfer Reagent

A new and simple route for the synthesis of thioesters starting from carboxylic acids and alcohols is reported by using tetrathiomolybdate as the key sulfur transfer reagent. Triphenylphosphane and N-bromosuccinimide were used for the activation of the carboxylic acid and alcohol in the same pot followed by the transfer of sulfur from tetrathiomolybdate. Thioesters were obtained in good to moderate yields. Primary alcohols show excellent reactivity and gave good yields of the corresponding thioesters, whereas secondary alcohols gave moderate yields and tertiary alcohols were very less reactive and gave poor yields of the corresponding thioesters.