Novel Mass Spectrometric Analysis Methods for Anabolic Androgenic Steroids in Sports Drug Testing

The feasibility of different modern analytical techniques for the mass spectrometric detection of anabolic androgenic steroids (AAS) in human urine was examined in order to enhance the prevalent analytics and to find reasonable strategies for effective sports drug testing. A comparative study of the sensitivity and specificity between gas chromatography (GC) combined with low (LRMS) and high resolution mass spectrometry (HRMS) in screening of AAS was carried out with four metabolites of methandienone. Measurements were done in selected ion monitoring mode with HRMS using a mass resolution of 5000. With HRMS the detection limits were considerably lower than with LRMS, enabling detection of steroids at low 0.2-0.5 ng/ml levels. However, also with HRMS, the biological background hampered the detection of some steroids. The applicability of liquid-phase microextraction (LPME) was studied with metabolites of fluoxymesterone, 4-chlorodehydromethyltestosterone, stanozolol and danazol. Factors affecting the extraction process were studied and a novel LPME method with in-fiber silylation was developed and validated for GC/MS analysis of the danazol metabolite. The method allowed precise, selective and sensitive analysis of the metabolite and enabled simultaneous filtration, extraction, enrichment and derivatization of the analyte from urine without any other steps in sample preparation. Liquid chromatographic/tandem mass spectrometric (LC/MS/MS) methods utilizing electrospray ionization (ESI), atmospheric pressure chemical ionization (APCI) and atmospheric pressure photoionization (APPI) were developed and applied for detection of oxandrolone and metabolites of stanozolol and 4-chlorodehydromethyltestosterone in urine. All methods exhibited high sensitivity and specificity. ESI showed, however, the best applicability, and a LC/ESI-MS/MS method for routine screening of nine 17-alkyl-substituted AAS was thus developed enabling fast and precise measurement of all analytes with detection limits below 2 ng/ml. The potential of chemometrics to resolve complex GC/MS data was demonstrated with samples prepared for AAS screening. Acquired full scan spectral data (m/z 40-700) were processed by the OSCAR algorithm (Optimization by Stepwise Constraints of Alternating Regression). The deconvolution process was able to dig out from a GC/MS run more than the double number of components as compared with the number of visible chromatographic peaks. Severely overlapping components, as well as components hidden in the chromatographic background could be isolated successfully. All studied techniques proved to be useful analytical tools to improve detection of AAS in urine. Superiority of different procedures is, however, compound-dependent and different techniques complement each other.

Towards real-time understanding of processes in pharmaceutical powder technology

There is a need for better understanding of the processes and new ideas to develop traditional pharmaceutical powder manufacturing procedures. Process analytical technology (PAT) has been developed to improve understanding of the processes and establish methods to monitor and control processes. The interest is in maintaining and even improving the whole manufacturing process and the final products at real-time. Process understanding can be a foundation for innovation and continuous improvement in pharmaceutical development and manufacturing. New methods are craved for to increase the quality and safety of the final products faster and more efficiently than ever before. The real-time process monitoring demands tools, which enable fast and noninvasive measurements with sufficient accuracy. Traditional quality control methods have been laborious and time consuming and they are performed off line i.e. the analysis has been removed from process area. Vibrational spectroscopic methods are responding this challenge and their utilisation have increased a lot during the past few years. In addition, other methods such as colour analysis can be utilised in noninvasive real-time process monitoring. In this study three pharmaceutical processes were investigated: drying, mixing and tabletting. In addition tablet properties were evaluated. Real-time monitoring was performed with NIR and Raman spectroscopies, colour analysis, particle size analysis and compression data during tabletting was evaluated using mathematical modelling. These methods were suitable for real-time monitoring of pharmaceutical unit operations and increase the knowledge of the critical parameters in the processes and the phenomena occurring during operations. They can improve our process understanding and therefore, finally, enhance the quality of final products.

A comparison of the molecular orbital (ab initio, CNDO and EHT) methods applied to the conformational study of thiocarbonohydrazide in its basic and diprotonated forms

Conformational preferences of thiocarbonohydrazide (H2NNHCSNHNH2) in its basic and N,N′-diprotonated forms are examined by calculating the barrier to internal rotation around the C---N bonds, using the theoretical LCAO—MO (ab initio and semiempirical CNDO and EHT) methods. The calculated and experimental results are compared with each other and also with values for N,N′-dimethylthiourea which is isoelectronic with thiocarbonohydrazide. The suitability of these methods for studying rotational isomerism seems suspect when lone pair interactions are present.

Some Methods for Summarizing Survivorship Data in Nonstandard Situations

One difficulty in summarising biological survivorship data is that the hazard rates are often neither constant nor increasing with time or decreasing with time in the entire life span. The promising Weibull model does not work here. The paper demonstrates how bath tub shaped quadratic models may be used in such a case. Further, sometimes due to a paucity of data actual lifetimes are not as certainable. It is shown how a concept from queuing theory namely first in first out (FIFO) can be profitably used here. Another nonstandard situation considered is one in which lifespan of the individual entity is too long compared to duration of the experiment. This situation is dealt with, by using ancilliary information. In each case the methodology is illustrated with numerical examples.

Comparative analysis of traffic state estimation ─ Cumulative counts-based and trajectory-based methods

The Macroscopic Fundamental Diagram (MFD) relates space-mean density and flow. Since the MFD represents the area-wide network traffic performance, studies on perimeter control strategies and network-wide traffic state estimation utilising the MFD concept have been reported. Most previous works have utilised data from fixed sensors, such as inductive loops, to estimate the MFD, which can cause biased estimation in urban networks due to queue spillovers at intersections. To overcome the limitation, recent literature reports the use of trajectory data obtained from probe vehicles. However, these studies have been conducted using simulated datasets; limited works have discussed the limitations of real datasets and their impact on the variable estimation. This study compares two methods for estimating traffic state variables of signalised arterial sections: a method based on cumulative vehicle counts (CUPRITE), and one based on vehicles’ trajectory from taxi Global Positioning System (GPS) log. The comparisons reveal some characteristics of taxi trajectory data available in Brisbane, Australia. The current trajectory data have limitations in quantity (i.e., the penetration rate), due to which the traffic state variables tend to be underestimated. Nevertheless, the trajectory-based method successfully captures the features of traffic states, which suggests that the trajectories from taxis can be a good estimator for the network-wide traffic states.

Evaluation of Two MCDM Methods for UAV Emergency Landing

One of the major impediments for the use of UAVs in civilian environment is the capability to replicate some of the functionality of safe manned aircraft operations. One critical aspect is emergency landing. Once the possible landing sites have been rated, a decision on the most suitable choice to land is required. This is a multi-criteria decision making (MCDM) problem which needs to take into account various factors in its selection of landing site. This report summarises relevant literature in MCDM in the context of emergency forced landing and proposes and compares two algorithms and methods for this task.

Numerical modelling of particle deposition in idealized porous channels

This project provides a steppingstone to comprehend the mechanisms that govern particulate fouling in metal foam heat exchangers. The method is based on development of an advanced Computational Fluid Dynamics model in addition to performing analytical validation. This novel method allows an engineer to better optimize heat exchanger designs, thereby mitigating fouling, reducing energy consumption caused by fouling, economize capital expenditure on heat exchanger maintenance, and reduce operation downtime. The robust model leads to the establishment of an alternative heat exchanger configuration that has lower pressure drop and particulate deposition propensity.

Exploring methods of preparing functional cartilage-bone xenografts for joint repair

This thesis explores the feasibility of donor-receiver concept for joint replacement where cartilage-bone tissues can be taken from either human or other mammals and prepared scientifically for repairing focal joint defects in knees, hips and shoulders. The manufactured construct is immunologically inert and is capable of acting as a scaffold for engineering new cartilage-bone laminates when placed in the joint. Innovative manufacturing procedures and assessment techniques were developed for appraising this tissue-based scaffold. This research has demonstrated that tissue replacement technology can be applied in situations where blood vessels are absent such as in articular cartilage.

"Small-particle limit" the second harmonic generation from noble metal nanoparticles

In this paper, we have probed the origin of SHG in copper nanoparticles by polarization-resolved hyper-Rayleigh scattering (HRS). Results obtained with various sizes of copper nanoparticles at four different wavelengths covering the wavelength range 738-1907 nm reveal that the origin of second harmonic generation (SHG) in these particles is purely dipolar in nature as long as the size (d) of the particles remains smaller compared to the wavelength (;.) of light ("small-particle limit"). However, contribution of the higher order multipoles coupled with retardation effect becomes apparent with an increase in the d/lambda ratio. We have identified the "small-particle limit" in the second harmonic generation from noble metal nanoparticles by evaluating the critical d/lambda ratio at which the retardation effect sets in the noble metal nanoparticles. We have found that the second-order nonlinear optical property of copper nanoparticles closely resembles that of gold, but not that of silver. (C) 2009 Elsevier B.V. All rights reserved.

Univariate, bivariate, and multivariate methods in corpus-based lexicography : A study of synonymy

In this dissertation, I present an overall methodological framework for studying linguistic alternations, focusing specifically on lexical variation in denoting a single meaning, that is, synonymy. As the practical example, I employ the synonymous set of the four most common Finnish verbs denoting THINK, namely ajatella, miettiä, pohtia and harkita ‘think, reflect, ponder, consider’. As a continuation to previous work, I describe in considerable detail the extension of statistical methods from dichotomous linguistic settings (e.g., Gries 2003; Bresnan et al. 2007) to polytomous ones, that is, concerning more than two possible alternative outcomes. The applied statistical methods are arranged into a succession of stages with increasing complexity, proceeding from univariate via bivariate to multivariate techniques in the end. As the central multivariate method, I argue for the use of polytomous logistic regression and demonstrate its practical implementation to the studied phenomenon, thus extending the work by Bresnan et al. (2007), who applied simple (binary) logistic regression to a dichotomous structural alternation in English. The results of the various statistical analyses confirm that a wide range of contextual features across different categories are indeed associated with the use and selection of the selected think lexemes; however, a substantial part of these features are not exemplified in current Finnish lexicographical descriptions. The multivariate analysis results indicate that the semantic classifications of syntactic argument types are on the average the most distinctive feature category, followed by overall semantic characterizations of the verb chains, and then syntactic argument types alone, with morphological features pertaining to the verb chain and extra-linguistic features relegated to the last position. In terms of overall performance of the multivariate analysis and modeling, the prediction accuracy seems to reach a ceiling at a Recall rate of roughly two-thirds of the sentences in the research corpus. The analysis of these results suggests a limit to what can be explained and determined within the immediate sentential context and applying the conventional descriptive and analytical apparatus based on currently available linguistic theories and models. The results also support Bresnan’s (2007) and others’ (e.g., Bod et al. 2003) probabilistic view of the relationship between linguistic usage and the underlying linguistic system, in which only a minority of linguistic choices are categorical, given the known context – represented as a feature cluster – that can be analytically grasped and identified. Instead, most contexts exhibit degrees of variation as to their outcomes, resulting in proportionate choices over longer stretches of usage in texts or speech.

Numerical simulation of conductive particle behaviour at the surface of a plate electrode affected by a DC corona field

The electric field in certain electrostatic devices can be modeled by a grounded plate electrode affected by a corona discharge generated by a series of parallel wires connected to a DC high-voltage supply. The system of differential equations that describe the behaviour (i.e., charging and motion) of the conductive particle in such an electric field has been numerically solved, using several simplifying assumptions. Thus, it was possible to investigate the effect of various electrical and mechanical factors on the trajectories of conductive particles. This model has been employed to study the behaviour of coalparticles in fly-ash corona separators.

A Comparison of Methods for Describing Irregular Animal Growth and Testing for Treatment Effects

In many designed experiments with animals liveweight is recorded several times during the trial. Such data are commonly referred to as repeated measures data. An aim of such experiments is generally to compare the growth patterns for the applied treatments. This paper discusses some of the methods of analysing repeated measures data and illustrates the use of cubic smoothing splines to describe irregular cattle growth data. Animal production for a consuming world : proceedings of 9th Congress of the Asian-Australasian Association of Animal Production Societies [AAAP] and 23rd Biennial Conference of the Australian Society of Animal Production [ASAP] and 17th Annual Symposium of the University of Sydney, Dairy Research Foundation, [DRF]. 2-7 July 2000, Sydney, Australia.