A novel and rational approach towards designing aluminium chelators

Aluminium (Al) is known to be neurotoxic and has been associated with the aetiology of Alzheimer's Disease. To date, only desferrioxamine (DFO), a trihydroxamic acid siderophore has been used in the clinical environment for the removal of Al from the body. However, this drug is expensive, orally inactive and is associated with many side effects. These studies employed a theoretical approach, with the use of quantum mechanics (QM) via semi-empirical molecular orbital (MO) calculations, and a practical approach using U87-MG glioblastoma cells as a model for evaluating the influence of potential chelators on the passage of aluminium into cells. Preliminary studies involving the Cambridge Structural Database (CSD) identified that Al prefers binding to bidentate ligands in a 3:1 manner, whereby oxygen was the exclusive donating atom. Statistically significant differences in M-O bond lengths when compared to other trivalent metal ions such as Fe3+ were established and used as an acceptance criterion for subsequent MO calculations. Of the semi-empirical methods parameterised for Al, the PM3 Hamiltonian was found to give the most reliable final optimised geometries of simple 3:1 Al complexes. Consequently the PM3 Hamiltonian was used for evaluating the Hf of 3:1 complexes with more complicated ligands. No correlation exists between published stability constants and individual parameters calculated via PM3 optimisations, although investigation of the dicarboxylates reveals a correlation of 0.961 showing promise for affinity prediction of closely related ligands. A simple and inexpensive morin spectrofluorescence assay has been developed and optimised producing results comparable to atomic absorption spectroscopy methods for the quantitative analysis of Al. This assay was used in subsequent in vitro models, initially on E. coli, which indicated that Al inhibits the antimicrobial action of ciprofloxacin, a potent quinolone antibiotic. Ensuing studies using the second model, U87-MG cells, investigated the influence of chelators on the transmembrane transport of Al, identifying 1,2-diethylhydroxypyridin-4-one as a ligand showing greatest potential for chelating Al in the clinical situation. In conclusion, these studies have explored semi-empirical MO Hamiltonians and an in-vitro U87-MG cell line, both as possible methods for predicting effective chelators of Al.

Detection of signals corrupted by the combination of Gaussian and Non-Gaussian noise

The detection of signals in the presence of noise is one of the most basic and important problems encountered by communication engineers. Although the literature abounds with analyses of communications in Gaussian noise, relatively little work has appeared dealing with communications in non-Gaussian noise. In this thesis several digital communication systems disturbed by non-Gaussian noise are analysed. The thesis is divided into two main parts. In the first part, a filtered-Poisson impulse noise model is utilized to calulate error probability characteristics of a linear receiver operating in additive impulsive noise. Firstly the effect that non-Gaussian interference has on the performance of a receiver that has been optimized for Gaussian noise is determined. The factors affecting the choice of modulation scheme so as to minimize the deterimental effects of non-Gaussian noise are then discussed. In the second part, a new theoretical model of impulsive noise that fits well with the observed statistics of noise in radio channels below 100 MHz has been developed. This empirical noise model is applied to the detection of known signals in the presence of noise to determine the optimal receiver structure. The performance of such a detector has been assessed and is found to depend on the signal shape, the time-bandwidth product, as well as the signal-to-noise ratio. The optimal signal to minimize the probability of error of; the detector is determined. Attention is then turned to the problem of threshold detection. Detector structure, large sample performance and robustness against errors in the detector parameters are examined. Finally, estimators of such parameters as. the occurrence of an impulse and the parameters in an empirical noise model are developed for the case of an adaptive system with slowly varying conditions.

Non-classical inhibitors of dihydrofolate reductase

This thesis comprises two main objectives. The first objective involved the stereochemical studies of chiral 4,6-diamino-1-aryl-1,2-dihydro-s-triazines and an investigation on how the different conformations of these stereoisomers may affect their binding affinity to the enzyme dihydrofolate reductase (DHFR). The ortho-substituted 1-aryl-1,2-dihydro-s-triazines were synthesised by the three component method. An ortho-substitution at the C6' position was observed when meta-azidocycloguanil was decomposed in acid. The ortho-substituent restricts free rotation and this gives rise to atropisomerism. Ortho-substituted 4,6-diamino-1-aryl-2-ethyl-1,2-dihydro-2-methyl-s-triazine contains two elements of chirality and therefore exists as four stereoisomers: (S,aR), (R,aS), (R,aR) and (S,aS). The energy barriers to rotation of these compounds were calculated by a semi-empirical molecular orbital program called MOPAC and they were found to be in excess of 23 kcal/mol. The diastereoisomers were resolved and enriched by C18 reversed phase h.p.l.c. Nuclear overhauser effect experiments revealed that (S,aR) and (R,aS) were the more stable pair of stereoisomers and therefore existed as the major component. The minor diastereoisomers showed greater binding affinity for the rat liver DHFR in in vitro assay. The second objective entailed the investigation into the possibility of retaining DHFR inhibitory activity by replacing the classical diamino heterocyclic moiety with an amidinyl group. 4-Benzylamino-3-nitro-N,N-dimethyl-phenylamidine was synthesised in two steps. One of the two phenylamidines indicated weak inhibition against the rat liver DHFR. This weak activity may be due to the failure of the inhibitor molecule to form strong hydrogen bonds with residue Glu-30 at the active site of the enzyme.

Evaluating productive efficiency:comparative study of commercial banks in Gulf countries

Financial institutes are an integral part of any modern economy. In the 1970s and 1980s, Gulf Cooperation Council (GCC) countries made significant progress in financial deepening and in building a modern financial infrastructure. This study aims to evaluate the performance (efficiency) of financial institutes (banking sector) in GCC countries. Since, the selected variables include negative data for some banks and positive for others, and the available evaluation methods are not helpful in this case, so we developed a Semi Oriented Radial Model to perform this evaluation. Furthermore, since the SORM evaluation result provides a limited information for any decision maker (bankers, investors, etc...), we proposed a second stage analysis using classification and regression (C&R) method to get further results combining SORM results with other environmental data (Financial, economical and political) to set rules for the efficient banks, hence, the results will be useful for bankers in order to improve their bank performance and to the investors, maximize their returns. Mainly there are two approaches to evaluate the performance of Decision Making Units (DMUs), under each of them there are different methods with different assumptions. Parametric approach is based on the econometric regression theory and nonparametric approach is based on a mathematical linear programming theory. Under the nonparametric approaches, there are two methods: Data Envelopment Analysis (DEA) and Free Disposal Hull (FDH). While there are three methods under the parametric approach: Stochastic Frontier Analysis (SFA); Thick Frontier Analysis (TFA) and Distribution-Free Analysis (DFA). The result shows that DEA and SFA are the most applicable methods in banking sector, but DEA is seem to be most popular between researchers. However DEA as SFA still facing many challenges, one of these challenges is how to deal with negative data, since it requires the assumption that all the input and output values are non-negative, while in many applications negative outputs could appear e.g. losses in contrast with profit. Although there are few developed Models under DEA to deal with negative data but we believe that each of them has it is own limitations, therefore we developed a Semi-Oriented-Radial-Model (SORM) that could handle the negativity issue in DEA. The application result using SORM shows that the overall performance of GCC banking is relatively high (85.6%). Although, the efficiency score is fluctuated over the study period (1998-2007) due to the second Gulf War and to the international financial crisis, but still higher than the efficiency score of their counterpart in other countries. Banks operating in Saudi Arabia seem to be the highest efficient banks followed by UAE, Omani and Bahraini banks, while banks operating in Qatar and Kuwait seem to be the lowest efficient banks; this is because these two countries are the most affected country in the second Gulf War. Also, the result shows that there is no statistical relationship between the operating style (Islamic or Conventional) and bank efficiency. Even though there is no statistical differences due to the operational style, but Islamic bank seem to be more efficient than the Conventional bank, since on average their efficiency score is 86.33% compare to 85.38% for Conventional banks. Furthermore, the Islamic banks seem to be more affected by the political crisis (second Gulf War), whereas Conventional banks seem to be more affected by the financial crisis.

Shell-side transfer in shell-and-tube heat exchangers

Local mass transfer coefficients were determined by using the electrochemical technique. A simple model of a heat exchanger with segmental nickel tube joined to p.v.c. rods replaced the exchanger tubes. Measurements were made for both no-Ieakage, semi-leakage and total leakage configurations. Baffle-spacings of 47.6 mm, 66.6 mm, 97 mm and 149.2 mm wer studied. Also studied were the overall exchanger pressure drops for each configuration. The comparison of the heat transfer data with this work showed good agreement at high flow rates for the no-leakage case, but the agreement became poor for lower flow rates and leakage configurations. This disagreement was explained by non-analogous driving forces existing in the two systems. The no-leakage data showed length-wise variation of transfer coefficients along the exchanger length. The end compartments showing transfer coefficients inferior by up to 26% compared to tbe internal compartments, depending on Reynolds number. With the introduction of leakage streams this variation however became smaller than the experimental accuracy. A model is outlined to show the characteristic behaviour of individual electrode segments within the compartment. This was able to discriminate between cross and window zones for the no- leakage case, but no such distinction could be made for the leakage case. A flow area was found which, when incorporated in the Reynolds number, enabled the correlation of baffle-cut and baffle-spacing parameters for the no-leakage case . This area is the free flow area determined at the baffle edge. Addition of the leakage area to this flow area resulted in correlation of all commercial leakage geometrical parameters. The procedures used to correlate the pressure drop data from a total of eighteen different configurations on a single curve are also outlined.

Lexical database enrichment through semi-automated morphological analysis

Derivational morphology proposes meaningful connections between words and is largely unrepresented in lexical databases. This thesis presents a project to enrich a lexical database with morphological links and to evaluate their contribution to disambiguation. A lexical database with sense distinctions was required. WordNet was chosen because of its free availability and widespread use. Its suitability was assessed through critical evaluation with respect to specifications and criticisms, using a transparent, extensible model. The identification of serious shortcomings suggested a portable enrichment methodology, applicable to alternative resources. Although 40% of the most frequent words are prepositions, they have been largely ignored by computational linguists, so addition of prepositions was also required. The preferred approach to morphological enrichment was to infer relations from phenomena discovered algorithmically. Both existing databases and existing algorithms can capture regular morphological relations, but cannot capture exceptions correctly; neither of them provide any semantic information. Some morphological analysis algorithms are subject to the fallacy that morphological analysis can be performed simply by segmentation. Morphological rules, grounded in observation and etymology, govern associations between and attachment of suffixes and contribute to defining the meaning of morphological relationships. Specifying character substitutions circumvents the segmentation fallacy. Morphological rules are prone to undergeneration, minimised through a variable lexical validity requirement, and overgeneration, minimised by rule reformulation and restricting monosyllabic output. Rules take into account the morphology of ancestor languages through co-occurrences of morphological patterns. Multiple rules applicable to an input suffix need their precedence established. The resistance of prefixations to segmentation has been addressed by identifying linking vowel exceptions and irregular prefixes. The automatic affix discovery algorithm applies heuristics to identify meaningful affixes and is combined with morphological rules into a hybrid model, fed only with empirical data, collected without supervision. Further algorithms apply the rules optimally to automatically pre-identified suffixes and break words into their component morphemes. To handle exceptions, stoplists were created in response to initial errors and fed back into the model through iterative development, leading to 100% precision, contestable only on lexicographic criteria. Stoplist length is minimised by special treatment of monosyllables and reformulation of rules. 96% of words and phrases are analysed. 218,802 directed derivational links have been encoded in the lexicon rather than the wordnet component of the model because the lexicon provides the optimal clustering of word senses. Both links and analyser are portable to an alternative lexicon. The evaluation uses the extended gloss overlaps disambiguation algorithm. The enriched model outperformed WordNet in terms of recall without loss of precision. Failure of all experiments to outperform disambiguation by frequency reflects on WordNet sense distinctions.

An empirical investigation of the effect of rights issue announcements on share returns and the determinants of abnormal returns on the Kuala Lumpur Stock Exchange

This thesis examines the effect of rights issue announcements on stock prices by companies listed on the Kuala Lumpur Stock Exchange (KLSE) between 1987 to 1996. The emphasis is to report whether the KLSE is semi strongly efficient with respect to the announcement of rights issues and to check whether the implications of corporate finance theories on the effect of an event can be supported in the context of an emerging market. Once the effect is established, potential determinants of abnormal returns identified by previous empirical work and corporate financial theory are analysed. By examining 70 companies making clean rights issue announcements, this thesis will hopefully shed light on some important issues in long term corporate financing. Event study analysis is used to check on the efficiency of the Malaysian stock market; while cross-sectional regression analysis is executed to identify possible explanators of the rights issue announcements' effect. To ensure the results presented are not contaminated, econometric and statistical issues raised in both analyses have been taken into account. Given the small amount of empirical research conducted in this part of the world, the results of this study will hopefully be of use to investors, security analysts, corporate financial managements, regulators and policy makers as well as those who are interested in capital market based research of an emerging market. It is found that the Malaysian stock market is not semi strongly efficient since there exists a persistent non-zero abnormal return. This finding is not consistent with the hypothesis that security returns adjust rapidly to reflect new information. It may be possible that the result is influenced by the sample, consisting mainly of below average size companies which tend to be thinly traded. Nevertheless, these issues have been addressed. Another important issue which has emerged from the study is that there is some evidence to suggest that insider trading activity existed in this market. In addition to these findings, when the rights issue announcements' effect is compared to the implications of corporate finance theories in predicting the sign of abnormal returns, the signalling model, asymmetric information model, perfect substitution hypothesis and Scholes' information hypothesis cannot be supported.

Is there a global model of learning organizations? An empirical, cross-nation study

This paper develops and tests a learning organization model derived from HRM and dynamic capability literatures in order to ascertain the model's applicability across divergent global contexts. We define a learning organization as one capable of achieving on-going strategic renewal, arguing based on dynamic capability theory that the model has three necessary antecedents: HRM focus, developmental orientation and customer-facing remit. Drawing on a sample comprising nearly 6000 organizations across 15 countries, we show that learning organizations exhibit higher performance than their less learning-inclined counterparts. We also demonstrate that innovation fully mediates the relationship between our conceptualization of the learning organization and organizational performance in 11 of the 15 countries we examined. It is the first time in our knowledge that these questions have been tested in a major, cross-global study, and our work contributes to both HRM and dynamic capability literatures, especially where the focus is the applicability of best practice parameters across national boundaries.

A modified semi-oriented radial measure for target setting with negative data

Over the last few years Data Envelopment Analysis (DEA) has been gaining increasing popularity as a tool for measuring efficiency and productivity of Decision Making Units (DMUs). Conventional DEA models assume non-negative inputs and outputs. However, in many real applications, some inputs and/or outputs can take negative values. Recently, Emrouznejad et al. [6] introduced a Semi-Oriented Radial Measure (SORM) for modelling DEA with negative data. This paper points out some issues in target setting with SORM models and introduces a modified SORM approach. An empirical study in bank sector demonstrates the applicability of the proposed model. © 2014 Elsevier Ltd. All rights reserved.

Nonlinear semi-analytical model for simulation of few-mode fiber transmission

In this letter, a nonlinear semi-analytical model (NSAM) for simulation of few-mode fiber transmission is proposed. The NSAM considers the mode mixing arising from the Kerr effect and waveguide imperfections. An analytical explanation of the model is presented, as well as simulation results for the transmission over a two mode fiber (TMF) of 112 Gb/s using coherently detected polarization multiplexed quadrature phase-shift-keying modulation. The simulations show that by transmitting over only one of the two modes on TMFs, long-haul transmission can be realized without increase of receiver complexity. For a 6000-km transmission link, a small modal dispersion penalty is observed in the linear domain, while a significant increase of the nonlinear threshold is observed due to the large core of TMF. © 2006 IEEE.

Semi-supervised Gaussian process latent variable model with pairwise constraints

In machine learning, Gaussian process latent variable model (GP-LVM) has been extensively applied in the field of unsupervised dimensionality reduction. When some supervised information, e.g., pairwise constraints or labels of the data, is available, the traditional GP-LVM cannot directly utilize such supervised information to improve the performance of dimensionality reduction. In this case, it is necessary to modify the traditional GP-LVM to make it capable of handing the supervised or semi-supervised learning tasks. For this purpose, we propose a new semi-supervised GP-LVM framework under the pairwise constraints. Through transferring the pairwise constraints in the observed space to the latent space, the constrained priori information on the latent variables can be obtained. Under this constrained priori, the latent variables are optimized by the maximum a posteriori (MAP) algorithm. The effectiveness of the proposed algorithm is demonstrated with experiments on a variety of data sets. © 2010 Elsevier B.V.