Acepromazine pharmacokinetics: A forensic perspective

Acepromazine (ACP) is a useful therapeutic drug, but is a prohibited substance in competition horses. The illicit use of ACP is difficult to detect due to its rapid metabolism, so this study investigated the ACP metabolite 2-(1-hydroxyethyl)promazine sulphoxide (HEPS) as a potential forensic marker. Acepromazine maleate, equivalent to 30 mg of ACP, was given IV to 12 racing-bred geldings. Blood and urine were collected for 7 days post-administration and analysed for ACP and HEPS by liquid chromatography–mass spectrometry (LC–MS). Acepromazine was quantifiable in plasma for up to 3 h with little reaching the urine unmodified. Similar to previous studies, there was wide variation in the distribution and metabolism of ACP. The metabolite HEPS was quantifiable for up to 24 h in plasma and 144 h in urine. The metabolism of ACP to HEPS was fast and erratic, so the early phase of the HEPS emergence could not be modelled directly, but was assumed to be similar to the rate of disappearance of ACP. However, the relationship between peak plasma HEPS and the y-intercept of the kinetic model was strong (P = 0.001, r2 = 0.72), allowing accurate determination of the formation pharmacokinetics of HEPS. Due to its rapid metabolism, testing of forensic samples for the parent drug is redundant with IV administration. The relatively long half-life of HEPS and its stable behaviour beyond the initial phase make it a valuable indicator of ACP use, and by determining the urine-to-plasma concentration ratios for HEPS, the approximate dose of ACP administration may be estimated.

Statistical and scientometric analysis of international research in geographical and environmental education

Certain statistic and scientometric features of articles published in the journal “International Research in Geographical and Environmental Education” are examined in this paper, for the period 1992-2009, by applying nonparametric statistics and Shannon’s entropy (diversity) formula. The main findings of this analysis are: a) after 2004 the research priorities of researchers in geographical and environmental education seem to have changed, b) “teacher education” has been the most recurrent theme throughout these 18 years, followed by “values & attitudes” and “inquiry & problem solving” c) the themes “GIS” and “Sustainability” were the most “stable” throughout the 18 years, meaning that they maintained their ranks as publication priorities more than other themes, d) citations of IRGEE increase annually, e) the average thematic diversity of articles published during the period 1992-2009 is 82.7% of the maximum thematic diversity (very high), meaning that the Journal has the capacity to attract a wide readership for the 10 themes it has successfully covered throughout the 18 years of its publication.

PartSS : An efficient partition-based filtering for edit distance constraints

This paper introduces PartSS, a new partition-based fil- tering for tasks performing string comparisons under edit distance constraints. PartSS offers improvements over the state-of-the-art method NGPP with the implementation of a new partitioning scheme and also improves filtering abil- ities by exploiting theoretical results on shifting and scaling ranges, thus accelerating the rate of calculating edit distance between strings. PartSS filtering has been implemented within two major tasks of data integration: similarity join and approximate membership extraction under edit distance constraints. The evaluation on an extensive range of real-world datasets demonstrates major gain in efficiency over NGPP and QGrams approaches.

Bayesian algorithms with applications

Advances in algorithms for approximate sampling from a multivariable target function have led to solutions to challenging statistical inference problems that would otherwise not be considered by the applied scientist. Such sampling algorithms are particularly relevant to Bayesian statistics, since the target function is the posterior distribution of the unobservables given the observables. In this thesis we develop, adapt and apply Bayesian algorithms, whilst addressing substantive applied problems in biology and medicine as well as other applications. For an increasing number of high-impact research problems, the primary models of interest are often sufficiently complex that the likelihood function is computationally intractable. Rather than discard these models in favour of inferior alternatives, a class of Bayesian "likelihoodfree" techniques (often termed approximate Bayesian computation (ABC)) has emerged in the last few years, which avoids direct likelihood computation through repeated sampling of data from the model and comparing observed and simulated summary statistics. In Part I of this thesis we utilise sequential Monte Carlo (SMC) methodology to develop new algorithms for ABC that are more efficient in terms of the number of model simulations required and are almost black-box since very little algorithmic tuning is required. In addition, we address the issue of deriving appropriate summary statistics to use within ABC via a goodness-of-fit statistic and indirect inference. Another important problem in statistics is the design of experiments. That is, how one should select the values of the controllable variables in order to achieve some design goal. The presences of parameter and/or model uncertainty are computational obstacles when designing experiments but can lead to inefficient designs if not accounted for correctly. The Bayesian framework accommodates such uncertainties in a coherent way. If the amount of uncertainty is substantial, it can be of interest to perform adaptive designs in order to accrue information to make better decisions about future design points. This is of particular interest if the data can be collected sequentially. In a sense, the current posterior distribution becomes the new prior distribution for the next design decision. Part II of this thesis creates new algorithms for Bayesian sequential design to accommodate parameter and model uncertainty using SMC. The algorithms are substantially faster than previous approaches allowing the simulation properties of various design utilities to be investigated in a more timely manner. Furthermore the approach offers convenient estimation of Bayesian utilities and other quantities that are particularly relevant in the presence of model uncertainty. Finally, Part III of this thesis tackles a substantive medical problem. A neurological disorder known as motor neuron disease (MND) progressively causes motor neurons to no longer have the ability to innervate the muscle fibres, causing the muscles to eventually waste away. When this occurs the motor unit effectively ‘dies’. There is no cure for MND, and fatality often results from a lack of muscle strength to breathe. The prognosis for many forms of MND (particularly amyotrophic lateral sclerosis (ALS)) is particularly poor, with patients usually only surviving a small number of years after the initial onset of disease. Measuring the progress of diseases of the motor units, such as ALS, is a challenge for clinical neurologists. Motor unit number estimation (MUNE) is an attempt to directly assess underlying motor unit loss rather than indirect techniques such as muscle strength assessment, which generally is unable to detect progressions due to the body’s natural attempts at compensation. Part III of this thesis builds upon a previous Bayesian technique, which develops a sophisticated statistical model that takes into account physiological information about motor unit activation and various sources of uncertainties. More specifically, we develop a more reliable MUNE method by applying marginalisation over latent variables in order to improve the performance of a previously developed reversible jump Markov chain Monte Carlo sampler. We make other subtle changes to the model and algorithm to improve the robustness of the approach.

Microstructural studies of quenched partially-melted Y-123 materials and Y-123 with Y-211, PtO2 and CeO2 additions

The microstructure of YBa2Cu3O7-delta (Y-123) materials partially-melted in air and quenched from the temperature range 900-1100 degrees C, has been characterized using a combination of X-ray diffractometry, optical microscopy, scanning electron microscopy, electron microprobe analyses, transmission electron microscopy and energy and wave dispersive X-ray spectrometries. The microstructural studies reveal significant changes in the character of the quenched partial-melt as a function of temperature and time before quenching. BaCu2O2 and BaCuO2 are found to co-exist in stoichiometric samples quenched from the temperature range 920-960 degrees C. Under suitable cooling conditions, large pockets of melt cristallize as BaCuO2 with an exsolution of BaCu2O2 in the form of thin plates (approximate to 50-100 nm thick) along facets. Y2BaCuO5 (Y-211) additions are associated with the formation of BaCu2O2 at 1100 degrees C. Preliminary results on the effects of PtO2 and CeO2 additions to Y-123 (and Y-123 with Y-211 additions) show that these enhace the formation of BaCu2O2 at the melting temperature of 1100 degrees C. (C) 1998 Elsevier Science S.A. All rights reserved.

Progress towards slip-casting YBa2Cu3O7-x monoliths

Sintered bars of YBa2Cu3O7-x obtained by slip-casting are investigated for drying and sintering behaviour. High J(cm) values (approximate to 10(6) A/cm(2) at 77K) are obtained, although J(ct) values are low (approximate to 10(2) A/cm(2) at 77K). Microstructural characterisation is undertaken on selected samples which demonstrate significant differences in physical density and critical current density.

Reaction products between Bi-Sr-Ca-Cu-oxide thick films and alumina substrates

The structure and composition of reaction products between Bi-Sr-Ca-Cu-oxide (BSCCO) thick films and alumina substrates have been characterized using a combination of electron diffraction, scanning electron microscopy and energy dispersive X-ray spectrometry (EDX). Sr and Ca are found to be the most reactive cations with alumina. Sr4Al6O12SO4 is formed between the alumina substrates and BSCCO thick films prepared from paste with composition close to Bi-2212 (and Bi-2212 + 10 wt.% Ag). For paste with composition close to Bi(Pb)-2223 + 20 wt.% Ag, a new phase with f.c.c. structure, lattice parameter about a = 24.5 A and approximate composition Al3Sr2CaBi2CuOx has been identified in the interface region. Understanding and control of these reactions is essential for growth of high quality BSCCO thick films on alumina. (C) 1997 Elsevier Science S.A.

Microstructural investigation of Bi-Sr-Ca-Cu-oxide thick films on alumina substrates

The microstructure of Bi-Sr-Ca-Cu-oxide (BSCCO) thick films on alumina substrates has been characterized using a combination of X-ray diffractometry, scanning electron microscopy, transmission electron microscopy of sections across the film/substrate interface and energy-dispersive X-ray spectrometry. A reaction layer formed between the BSCCO films and the alumina substrates. This chemical interaction is largely responsible for off-stoichiometry of the films and is more significant after partial melting of the films. A new phase with fee structure, lattice parameter a = 2.45 nm and approximate composition Al3Sr2CaBi2CuOx has been identified as reaction product between BSCCO and Al2O3.

Characterizing multi-agent team behavior from partial team tracings : evidence from the English Premier League

Real-world AI systems have been recently deployed which can automatically analyze the plan and tactics of tennis players. As the game-state is updated regularly at short intervals (i.e. point-level), a library of successful and unsuccessful plans of a player can be learnt over time. Given the relative strengths and weaknesses of a player’s plans, a set of proven plans or tactics from the library that characterize a player can be identified. For low-scoring, continuous team sports like soccer, such analysis for multi-agent teams does not exist as the game is not segmented into “discretized” plays (i.e. plans), making it difficult to obtain a library that characterizes a team’s behavior. Additionally, as player tracking data is costly and difficult to obtain, we only have partial team tracings in the form of ball actions which makes this problem even more difficult. In this paper, we propose a method to overcome these issues by representing team behavior via play-segments, which are spatio-temporal descriptions of ball movement over fixed windows of time. Using these representations we can characterize team behavior from entropy maps, which give a measure of predictability of team behaviors across the field. We show the efficacy and applicability of our method on the 2010-2011 English Premier League soccer data.

Efficient solution of two-sided nonlinear space-fractional diffusion equations using fast Poisson preconditioners

We develop a fast Poisson preconditioner for the efficient numerical solution of a class of two-sided nonlinear space fractional diffusion equations in one and two dimensions using the method of lines. Using the shifted Gr¨unwald finite difference formulas to approximate the two-sided(i.e. the left and right Riemann-Liouville) fractional derivatives, the resulting semi-discrete nonlinear systems have dense Jacobian matrices owing to the non-local property of fractional derivatives. We employ a modern initial value problem solver utilising backward differentiation formulas and Jacobian-free Newton-Krylov methods to solve these systems. For efficient performance of the Jacobianfree Newton-Krylov method it is essential to apply an effective preconditioner to accelerate the convergence of the linear iterative solver. The key contribution of our work is to generalise the fast Poisson preconditioner, widely used for integer-order diffusion equations, so that it applies to the two-sided space fractional diffusion equation. A number of numerical experiments are presented to demonstrate the effectiveness of the preconditioner and the overall solution strategy.

A preconditioned Lanczos method for space-fractional reaction-diffusion equations on two-dimensional unstructured meshes

We consider a two-dimensional space-fractional reaction diffusion equation with a fractional Laplacian operator and homogeneous Neumann boundary conditions. The finite volume method is used with the matrix transfer technique of Ilić et al. (2006) to discretise in space, yielding a system of equations that requires the action of a matrix function to solve at each timestep. Rather than form this matrix function explicitly, we use Krylov subspace techniques to approximate the action of this matrix function. Specifically, we apply the Lanczos method, after a suitable transformation of the problem to recover symmetry. To improve the convergence of this method, we utilise a preconditioner that deflates the smallest eigenvalues from the spectrum. We demonstrate the efficiency of our approach for a fractional Fisher’s equation on the unit disk.

Optimally increasing secure connectivity in multihop wireless ad hoc networks

We consider the problem of how to maximize secure connectivity of multi-hop wireless ad hoc networks after deployment. Two approaches, based on graph augmentation problems with nonlinear edge costs, are formulated. The first one is based on establishing a secret key using only the links that are already secured by secret keys. This problem is in NP-hard and does not accept polynomial time approximation scheme PTAS since minimum cutsets to be augmented do not admit constant costs. The second one is based of increasing the power level between a pair of nodes that has a secret key to enable them physically connect. This problem can be formulated as the optimal key establishment problem with interference constraints with bi-objectives: (i) maximizing the concurrent key establishment flow, (ii) minimizing the cost. We show that both problems are NP-hard and MAX-SNP (i.e., it is NP-hard to approximate them within a factor of 1 + e for e > 0 ) with a reduction to MAX3SAT problem. Thus, we design and implement a fully distributed algorithm for authenticated key establishment in wireless sensor networks where each sensor knows only its one- hop neighborhood. Our witness based approaches find witnesses in multi-hop neighborhood to authenticate the key establishment between two sensor nodes which do not share a key and which are not connected through a secure path.

Fast exact nearest neighbour matching in high dimensions using d-D Sort

Data structures such as k-D trees and hierarchical k-means trees perform very well in approximate k nearest neighbour matching, but are only marginally more effective than linear search when performing exact matching in high-dimensional image descriptor data. This paper presents several improvements to linear search that allows it to outperform existing methods and recommends two approaches to exact matching. The first method reduces the number of operations by evaluating the distance measure in order of significance of the query dimensions and terminating when the partial distance exceeds the search threshold. This method does not require preprocessing and significantly outperforms existing methods. The second method improves query speed further by presorting the data using a data structure called d-D sort. The order information is used as a priority queue to reduce the time taken to find the exact match and to restrict the range of data searched. Construction of the d-D sort structure is very simple to implement, does not require any parameter tuning, and requires significantly less time than the best-performing tree structure, and data can be added to the structure relatively efficiently.

Prediction of multilocus identity-by-descent

Previous studies have enabled exact prediction of probabilities of identity-by-descent (IBD) in randommating populations for a few loci (up to four or so), with extension to more using approximate regression methods. Here we present a precise predictor of multiple-locus IBD using simple formulas based on exact results for two loci. In particular, the probability of non-IBD X ABC at each of ordered loci A, B, and C can be well approximated by XABC = XABXBC/XB and generalizes to X123. . .k = X12X23. . .Xk-1,k/ Xk-2, where X is the probability of non-IBD at each locus. Predictions from this chain rule are very precise with population bottlenecks and migration, but are rather poorer in the presence of mutation. From these coefficients, the probabilities of multilocus IBD and non-IBD can also be computed for genomic regions as functions of population size, time, and map distances. An approximate but simple recurrence formula is also developed, which generally is less accurate than the chain rule but is more robust with mutation. Used together with the chain rule it leads to explicit equations for non-IBD in a region. The results can be applied to detection of quantitative trait loci (QTL) by computing the probability of IBD at candidate loci in terms of identity-by-state at neighboring markers.

Raman spectroscopic study of the hydroxy-phosphate mineral plumbogummite PbAl3(PO4)2(OH,H2O)6

Plumbogummite PbAl3(PO4)2(OH,H2O)6 is a mineral of environmental significance and is a member of the alunite-jarosite supergroup. The molecular structure of the mineral has been investigated by Raman spectroscopy. The spectra of different plumbogummite specimens differ although there are many common features. The Raman spectra prove the spectral profile consisting of overlapping bands and shoulders. Raman bands and shoulders observed at 971, 980, 1002 and 1023 cm−1 (China sample) and 913, 981, 996 and 1026 cm−1 (Czech sample) are assigned to the ν1 symmetric stretching modes of the (PO4)3−, at 1002 and 1023 cm−1 (China) and 996 and 1026 cm−1 to the ν1 symmetric stretching vibrations of the (O3POH)2− units, and those at 1057, 1106 and 1182 (China) and at 1102, 1104 and 1179 cm−1 (Czech) to the ν3 (PO4)3− and ν3 (PO3) antisymmetric stretching vibrations. Raman bands and shoulders at 634, 613 and 579 cm−1 (China) and 611 and 596 cm−1 (Czech) are attributed to the ν4 (δ) (PO4)3− bending vibrations and those at 507, 494 and 464 cm−1 (China) and 505 and 464 cm−1 (Czech) to the ν2 (δ) (PO4)3− bending vibrations. The Raman spectrum of the OH stretching region is complex. Raman bands and shoulders are identified at 2824, 3121, 3249, 3372, 3479 and 3602 cm−1 for plumbogummite from China, and at 3077, 3227, 3362, 3480, 3518 and 3601 cm−1 for the Czech Republic sample. These bands are assigned to the ν OH stretching modes of water molecules and hydrogen ions. Approximate O–H⋯O hydrogen bond lengths inferred from the Raman spectra vary in the range >3.2–2.62 Å (China) and >3.2–2.67 Å (Czech). The minority presence of some carbonate ions in the plumbogummite (China sample) is connected with distinctive intensity increasing of the Raman band at 1106 cm−1, in which may participate the ν1 (CO3)2− symmetric stretching vibration overlapped with phosphate stretching vibrations.