Theory for determining alignment parameters of symmetric top molecule using (n+1) LIF

Expressions used for extracting the population and alignment parameters of a symmetric top molecule from (n + 1) laser-induced fluorescence (LIF) are derived by employing the tensor density matrix method. The molecular population and alignment are described by molecular state multipoles. The LIF intensity is a complex function of the initial molecular state multipoles, the dynamic factors, and the excitation-detection geometrical factors. The problem of how to extract the initial molecular state multipoles from (2 + 1) LIF, as an example, is discussed in detail. (C) 2000 American Institute of Physics. [S0021-9606(00)30744-9].

Prediction of soil adsorption coefficients from retention parameters on three reversed-phase liquid chromatographic columns

Reversed-phase high-performance liquid chromatographic (RP-HPLC) retention parameters, which are determined by the intermolecular interactions in retention process, can be considered as the chemical molecular descriptors in linear free energy relationships (LFERs). On the basis of the characterization and comparison of octadecyl-bonded silica gel (ODS), cyano-bonded silica gel (CN), and phenyl-bonded silica gel (Ph) columns with linear solvation energy relationships (LSERs), a new multiple linear regression model using RP-HPLC retention parameters on ODS and CN columns as variables for estimation of soil adsorption coefficients was developed. It was tested on a set of reference substances from various chemical classes. The results showed that the multicolumn method was more promising than a single-column method was for the estimation of soil adsorption coefficients. The accuracy of the suggested model is identical with that of LSERs.

Discriminating the xanthones in an extract of Swertia franchetiana by retention parameters

The quantitative structure-retention relationship is one of the most actively studied topics in the field of chromatography. In this paper, retention parameters of components were used to discriminate the xanthones in a methanol extract of Swertia franchetiana. The extract was analysed by HPLC under two different multistage linear gradient conditions and the retention parameters calculated from these retention data. It was found that the retention parameters of xanthones are in a specific region in the plot of log k(w) vs. S and the xanthones in the extract could be distinguished from other components by this feature. Furthermore, xanthone aglycones and xanthone glucosides could also be discriminated by retention parameters. Copyright (C) 2005 John Wiley Sons, Ltd.

Conservação de espermatozóides bovinos por liofilização (freeze-drying).

2008

Variation of modal parameters of pile-supported structures in seismically liquefiable soils.

This paper presents experimental results that aimed to investigate the effects of soil liquefaction on the modal parameters (i.e. frequency and damping ratio) of pile-supported structures. The tests were carried out using the shaking table facility of the Bristol Laboratory for Advanced Dynamics Engineering (BLADE) at the University of Bristol (UK) whereby four pile-supported structures (two single piles and two pile groups) with and without superstructure mass were tested. The experimental investigation aimed to monitor the variation in natural frequency and damping of the four physical models at different degrees of excess pore water pressure generation and in full-liquefaction condition. The experimental results showed that the natural frequency of pile-supported structures may decrease considerably owing to the loss of lateral support offered by the soil to the pile. On the other hand, the damping ratio of structure may increase to values in excess of 20%. These findings have important design consequences: (a) for low-period structures, substantial reduction of spectral acceleration is expected; (b) during and after liquefaction, the response of the system may be dictated by the interactions of multiple loadings, that is, horizontal, axial and overturning moment, which were negligible prior to liquefaction; and (c) with the onset of liquefaction due to increased flexibility of pile-supported structure, larger spectral displacement may be expected, which in turn may enhance Pdelta effects and consequently amplification of overturning moment. Practical implications for pile design are discussed.

Aqueous solutions of HEC and hmHEC: effects of molecular mass versus hydrophobic associations on hydrodynamic and thermodynamic parameters.

Aqueous solutions of amphiphilic polymers usually comprise of inter- and intramolecular associations of hydrophobic groups often leading to a formation of a rheologically significant reversible network at low concentrations that can be identified using techniques such as static light scattering and rheometry. However, in most studies published till date comparing water soluble polymers with their respective amphiphilic derivatives, it has been very difficult to distinguish between the effects of molecular mass versus hydrophobic associations on hydrodynamic (intrinsic viscosity [g]) and thermodynamic parameters (second virial coefficient A2), owing to the differences between their degrees of polymerization. This study focuses on the dilute and semi-dilute solutions of hydroxyethyl cellulose (HEC) and its amphiphilic derivatives (hmHEC) of the same molecular mass, along with other samples having a different molecular mass using capillary viscometry, rheometry and static light scattering. The weight average molecular masses (MW) and their distributions for the nonassociative HEC were determined using size exclusion chromatography. Various empirical approaches developed by past authors to determine [g] from dilute solution viscometry data have been discussed. hmHEC with a sufficiently high degree of hydrophobic modification was found to be forming a rheologically significant network in dilute solutions at very low concentrations as opposed to the hmHEC with a much lower degree of hydrophobic modification which also enveloped the hydrophobic groups inside the supramolecular cluster as shown by their [g] and A2. The ratio A2MW/[g], which takes into account hydrodynamic as well as thermodynamic parameters, was observed to be less for associative polymers compared to that of the non-associative polymers.

Double Jeopardy Without Parameters: Re-characterization in International Criminal Law

Olusanya, O. (2004). Double Jeopardy Without Parameters: Re-characterization in International Criminal Law. Series Supranational Criminal Law: Capita Selecta, volume 2. Antwerp: Intersentia. RAE2008

Estimation of long-run parameters in unbalanced cointegration

This paper analyses the asymptotic properties of nonlinear least squares estimators of the long run parameters in a bivariate unbalanced cointegration framework. Unbalanced cointegration refers to the situation where the integration orders of the observables are different, but their corresponding balanced versions (with equal integration orders after filtering) are cointegrated in the usual sense. Within this setting, the long run linkage between the observables is driven by both the cointegrating parameter and the difference between the integration orders of the observables, which we consider to be unknown. Our results reveal three noticeable features. First, superconsistent (faster than √ n-consistent) estimators of the difference between memory parameters are achievable. Next, the joint limiting distribution of the estimators of both parameters is singular, and, finally, a modified version of the ‘‘Type II’’ fractional Brownian motion arises in the limiting theory. A Monte Carlo experiment and the discussion of an economic example are included.

PARAMETERS AFFECTING THE IMAGING AND DETECTION OF MICROBUBBLES IN BLOOD

Stabilized micron-sized bubbles, known as contrast agents, are often injected into the body to enhance ultrasound imaging of blood flow. The ability to detect such bubbles in blood depends on the relative magnitude of the acoustic power backscattered from the microbubbles (‘signal’) to the power backscattered from the red blood cells (‘noise’). Erythrocytes are acoustically small (Rayleigh regime), weak scatterers, and therefore the backscatter coefficient (BSC) of blood increases as the fourth power of frequency throughout the diagnostic frequency range. Microbubbles, on the other hand, are either resonant or super-resonant in the range 5-30 MHz. Above resonance, their total scattering cross-section remains constant with increasing frequency. In the present thesis, a theoretical model of the BSC of a suspension of red blood cells is presented and compared to the BSC of Optison® contrast agent microbubbles. It is predicted that, as the frequency increases, the BSC of red blood cell suspensions eventually exceeds the BSC of the strong scattering microbubbles, leading to a dramatic reduction in signal-to-noise ratio (SNR). This decrease in SNR with increasing frequency was also confirmed experimentally by use of an active cavitation detector for different concentrations of Optison® microbubbles in erythrocyte suspensions of different hematocrits. The magnitude of the observed decrease in SNR correlated well with theoretical predictions in most cases, except for very dense suspensions of red blood cells, where it is hypothesized that the close proximity of erythrocytes inhibits the acoustic response of the microbubbles.

Experimental quantification and modelling of attrition of infant formulae during pneumatic conveying

Infant formula is often produced as an agglomerated powder using a spray drying process. Pneumatic conveying is commonly used for transporting this product within a manufacturing plant. The transient mechanical loads imposed by this process cause some of the agglomerates to disintegrate, which has implications for key quality characteristics of the formula including bulk density and wettability. This thesis used both experimental and modelling approaches to investigate this breakage during conveying. One set of conveying trials had the objective of establishing relationships between the geometry and operating conditions of the conveying system and the resulting changes in bulk properties of the infant formula upon conveying. A modular stainless steel pneumatic conveying rig was constructed for these trials. The mode of conveying and air velocity had a statistically-significant effect on bulk density at a 95% level, while mode of conveying was the only factor which significantly influenced D[4,3] or wettability. A separate set of conveying experiments investigated the effect of infant formula composition, rather than the pneumatic conveying parameters, and also assessed the relationships between the mechanical responses of individual agglomerates of four infant formulae and their compositions. The bulk densities before conveying, and the forces and strains at failure of individual agglomerates, were related to the protein content. The force at failure and stiffness of individual agglomerates were strongly correlated, and generally increased with increasing protein to fat ratio while the strain at failure decreased. Two models of breakage were developed at different scales; the first was a detailed discrete element model of a single agglomerate. This was calibrated using a novel approach based on Taguchi methods which was shown to have considerable advantages over basic parameter studies which are widely used. The data obtained using this model compared well to experimental results for quasi-static uniaxial compression of individual agglomerates. The model also gave adequate results for dynamic loading simulations. A probabilistic model of pneumatic conveying was also developed; this was suitable for predicting breakage in large populations of agglomerates and was highly versatile: parts of the model could easily be substituted by the researcher according to their specific requirements.

Optimisation of granola breakfast cereal manufacturing process by wet granulation and pneumatic conveying

This study has considered the optimisation of granola breakfast cereal manufacturing processes by wet granulation and pneumatic conveying. Granola is an aggregated food product used as a breakfast cereal and in cereal bars. Processing of granola involves mixing the dry ingredients (typically oats, nuts, etc.) followed by the addition of a binder which can contain honey, water and/or oil. In this work, the design and operation of two parallel wet granulation processes to produce aggregate granola products were incorporated: a) a high shear mixing granulation process followed by drying/toasting in an oven. b) a continuous fluidised bed followed by drying/toasting in an oven. In high shear granulation the influence of process parameters on key granule aggregate quality attributes such as granule size distribution and textural properties of granola were investigated. The experimental results show that the impeller rotational speed is the single most important process parameter which influences granola physical and textural properties. After that binder addition rate and wet massing time also show significant impacts on granule properties. Increasing the impeller speed and wet massing time increases the median granule size while also presenting a positive correlation with density. The combination of high impeller speed and low binder addition rate resulted in granules with the highest levels of hardness and crispness. In the fluidised bed granulation process the effect of nozzle air pressure and binder spray rate on key aggregate quality attributes were studied. The experimental results show that a decrease in nozzle air pressure leads to larger in mean granule size. The combination of lowest nozzle air pressure and lowest binder spray rate results in granules with the highest levels of hardness and crispness. Overall, the high shear granulation process led to larger, denser, less porous and stronger (less likely to break) aggregates than the fluidised bed process. The study also examined the particle breakage of granola during pneumatic conveying produced by both the high shear granulation and the fluidised bed granulation process. Products were pneumatically conveyed in a purpose built conveying rig designed to mimic product conveying and packaging. Three different conveying rig configurations were employed; a straight pipe, a rig consisting two 45° bends and one with 90° bend. Particle breakage increases with applied pressure drop, and a 90° bend pipe results in more attrition for all conveying velocities relative to other pipe geometry. Additionally for the granules produced in the high shear granulator; those produced at the highest impeller speed, while being the largest also have the lowest levels of proportional breakage while smaller granules produced at the lowest impeller speed have the highest levels of breakage. This effect clearly shows the importance of shear history (during granule production) on breakage during subsequent processing. In terms of the fluidised bed granulation, there was no single operating parameter that was deemed to have a significant effect on breakage during subsequent conveying. Finally, a simple power law breakage model based on process input parameters was developed for both manufacturing processes. It was found suitable for predicting the breakage of granola breakfast cereal at various applied air velocities using a number of pipe configurations, taking into account shear histories.

Power system parameters forecasting using Hilbert-Huang transform and machine learning

A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and a feature analysis of initial retrospective data using the Hilbert-Huang transform and machine learning algorithms. The random forests and gradient boosting trees learning techniques were examined. The decision tree techniques were used to rank the importance of variables employed in the forecasting models. The Mean Decrease Gini index is employed as an impurity function. The resulting hybrid forecasting models employ the radial basis function neural network and support vector regression. A part from introduction and references the paper is organized as follows. The second section presents the background and the review of several approaches for short-term forecasting of power system parameters. In the third section a hybrid machine learningbased algorithm using Hilbert-Huang transform is developed for short-term forecasting of power system parameters. Fourth section describes the decision tree learning algorithms used for the issue of variables importance. Finally in section six the experimental results in the following electric power problems are presented: active power flow forecasting, electricity price forecasting and for the wind speed and direction forecasting.