Cyclic Imide and Open-Chain Amide Carboxylic Acid Derivatives from the Facile Reaction of cis-Cyclohexane-1,2-dicarboxylic Anhydride with Three Substituted Anilines

The structures of the compounds from the reaction of cis-cyclohexane-1,2-dicarboxylic anhydride with 4-chloroaniline [rac-N-(4-chlorophenyl)-2-carboxycycloclohexane-1-carboxamide] (1), 4-bromoaniline [2-(4-bromophenyl)-perhydroisoindolyl-1,3-dione] (2) and 3-hydroxy-4-carboxyaniline (5-aminosalicylic acid) [2-(3-hydroxy-4-carboxyphenyl)-perhydroisoindolyl-1,3-dione] (3) have been determined at 200 K. Crystals of the open-chain amide carboxylic acid 1 are orthorhombic, space group Pbcn, with unit cell dimensions a = 20.1753(10), b = 8.6267(4), c = 15.9940(9) Å, and Z = 8. Compounds 2 and 3 are cyclic imides, with 1 monoclinic having space group P21 and cell dimensions a = 11.5321(3), b = 6.7095(2), c = 17.2040(5) Å, β = 102.527(3)o. Compound 3 is orthorhombic with cell dimensions a = 6.4642(3), b = 12.8196(5), c = 16.4197(7) Å. Molecules of 1 form hydrogen-bonded cyclic dimers which are extended into a two-dimensional layered structure through amide-group associations: 3 forms into one-dimensional zigzag chains through carboxylic acid…imide O-atom hydrogen bonds, while compound 2 is essentially unassociated. With both cyclic imides 2 and 3, disorder is found which involves the presence of partial enantiomeric replacement of the cis-cyclohexane-1,2-substituted ring systems.

Nitric oxide synthase type-II is synthesized by human gingival tissue and cultured human gingival fibroblasts

Nitric oxide is known to be an important inflammatory mediator, and is implicated in the pathophysiology of a range of inflammatory disorders. The aim of this study was to determine the localization and distribution of endothelial NOS (NOS-II) in human gingival tissue, and to ascertain if human gingival fibroblasts express NOS-II when stimulated with interferon gamma (IFN-gamma) and bacterial lipopolysaccharide (LPS). The distribution of NOS-II in inflamed and non-inflamed specimens of human gingivae was studied using a monoclonal antibody against nitric oxide synthase II. Cultures of fibroblasts derived from healthy human gingivae were used for the cell culture experiments. The results from immunohistochemical staining of the tissues indicated an upregulation of NOS-II expression in inflamed compared to non-inflamed gingival tissue. Fibroblasts and inflammatory cells within the inflamed connective tissue were positively stained for NOS-II. In addition, basal keratinocytes also stained strongly for NOS-II, in both healthy and inflamed tissue sections. When cultured human gingival fibroblasts were stimulated by INF-gamma and Porphyromonas gingivalis LPS, NOS-II was more strongly expressed than when the cells were exposed to LPS or IFN-gamma alone. These data suggest that, as for other inflammatory diseases, NO plays a role in the pathophysiology of periodontitis.

A qualitative investigation into the different health experiences of people living with type II diabetes, in the rural environments

Study Rationale The objective of the study was to explore if and how rural culture influences type II diabetes management and to better understand the social processes that rural people construct in coping with diabetes and its complications. In particular, the study aimed to analyse the interface and interactions between rural people with type II diabetes and the Australian health care system. Theoretical framework and methods The research applied constructivist grounded theory methods within an interpretive interactionist framework. Data from 39 semi-structured interviews with rural and urban people with type II diabetes plus a mix of rural health care providers were analysed to develop a theoretical understanding of the social processes that define diabetes management in that context. Results The analysis suggests that although type II diabetes imposes limitations that require adjustment and adaptation these processes are actively negotiated by rural people within the environmental context to fit the salient social understandings of autonomy and self-reliance. Thus people normalised self-reliant diabetes management behaviours because this was congruent with the rural culture. Factors that informed the actions of normalisation were the relationships between participants and health care professions, support and access to individual resources. Conclusions The findings point to ways in which rural self-reliance is conceived as the primary strategy of diabetic management. People face the paradox of engaging with a health care system that at the same time maximises individual responsibility for health and minimises the social support by which individuals manage the condition. The emphasis on self-reliance gives some legitimacy to a lack of prevention and chronic care services. Success of diabetic management behaviours is contingent on relative resources. Where there is good primary care there develop a number of downstream effects including a sense of empowerment to manage difficult rural environmental circumstances. This has particular bearing on health outcomes for people with fewer resources.

Marginal reversible jump Markov chain Monte Carlo with application to motor unit number estimation

Motor unit number estimation (MUNE) is a method which aims to provide a quantitative indicator of progression of diseases that lead to loss of motor units, such as motor neurone disease. However the development of a reliable, repeatable and fast real-time MUNE method has proved elusive hitherto. Ridall et al. (2007) implement a reversible jump Markov chain Monte Carlo (RJMCMC) algorithm to produce a posterior distribution for the number of motor units using a Bayesian hierarchical model that takes into account biological information about motor unit activation. However we find that the approach can be unreliable for some datasets since it can suffer from poor cross-dimensional mixing. Here we focus on improved inference by marginalising over latent variables to create the likelihood. In particular we explore how this can improve the RJMCMC mixing and investigate alternative approaches that utilise the likelihood (e.g. DIC (Spiegelhalter et al., 2002)). For this model the marginalisation is over latent variables which, for a larger number of motor units, is an intractable summation over all combinations of a set of latent binary variables whose joint sample space increases exponentially with the number of motor units. We provide a tractable and accurate approximation for this quantity and also investigate simulation approaches incorporated into RJMCMC using results of Andrieu and Roberts (2009).

First year design "Visualisation II": The hybridisation of analogue and digital tools

This paper discusses first year students’ responses and outcomes to the integration of digital technologies in their second semester foundational visualisation class; ‘Visualisation II’. As the second class in the Visualisation series, previous analogue knowledge taught in ‘Visualisation I’ is compounded with new digital technologies establishing the introduction to a myriad of hybrid visualisation tools and techniques for design exploration and design artefact. This research examines the differentiation between analogue and digital design, common precedents of the two, and reflects upon the environment and class structure with the learning experiences and confidence of surveyed participants.

Performance of elite seated discus throwers in F30s classes : part II: does feet positioning matter?

Background: Studies on the relationship between performance and design of the throwing frame have been limited. Part I provided only a description of the whole body positioning. Objectives: The specific objectives were (a) to benchmark feet positioning characteristics (i.e. position, spacing and orientation) and (b) to investigate the relationship between performance and these characteristics for male seated discus throwers in F30s classes. Study Design: Descriptive analysis. Methods: A total of 48 attempts performed by 12 stationary discus throwers in F33 and F34 classes during seated discus throwing event of 2002 International Paralympic Committee Athletics World Championships were analysed in this study. Feet positioning was characterised by tridimensional data of the front and back feet position as well as spacing and orientation corresponding to the distance between and the angle made by both feet, respectively. Results: Only 4 of 30 feet positioning characteristics presented a coefficient correlation superior to 0.5, including the feet spacing on mediolateral and anteroposterior axes in F34 class as well as the back foot position and feet spacing on mediolateral axis in F33 class. Conclusions: This study provided key information for a better understanding of the interaction between throwing technique of elite seated throwers and their throwing frame.

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.

Supply chain benefits expectation management framework

Organizations invest heavily in Supply Chain Management Systems expecting the benefits promised by the software vendors and the implementation partners. However, both academic and industry reports suggest that there is growing dissatisfaction among client organizations due to an increasing gap in benefits purported by the software vendors and benefits realised by the client. In order to better manage expectations of the client organization, this study proposes a Benefit Expectation Management Framework for Supply Chain Management Systems, based on Expectation-Confirmation Theory. This study derives 60 expected benefits of Supply Chain Management Systems through 41 vendor-reported customer stories and academic papers. Through comparing those benefits with the received benefits by a case organization that has implemented SAP Supply Chain Management Systems for seven years, two salient factors – long timetable and multiple stakeholders – have been identified as the controlling factors affecting the confirmation level of Supply Chain Management System expectations and further impacting the satisfaction of a client organization. The case study also highlights the likely causes for realized benefits and enduring issues in relation to the Supply Chain Management Systems.

Expander graph based key distribution mechanisms in wireless sensor networks

Secure communications between large number of sensor nodes that are randomly scattered over a hostile territory, necessitate efficient key distribution schemes. However, due to limited resources at sensor nodes such schemes cannot be based on post deployment computations. Instead, pairwise (symmetric) keys are required to be pre-distributed by assigning a list of keys, (a.k.a. key-chain), to each sensor node. If a pair of nodes does not have a common key after deployment then they must find a key-path with secured links. The objective is to minimize the keychain size while (i) maximizing pairwise key sharing probability and resilience, and (ii) minimizing average key-path length. This paper presents a deterministic key distribution scheme based on Expander Graphs. It shows how to map the parameters (e.g., degree, expansion, and diameter) of a Ramanujan Expander Graph to the desired properties of a key distribution scheme for a physical network topology.

Fourier Lucas-Kanade Algorithm

In this paper we propose a framework for both gradient descent image and object alignment in the Fourier domain. Our method centers upon the classical Lucas & Kanade (LK) algorithm where we represent the source and template/model in the complex 2D Fourier domain rather than in the spatial 2D domain. We refer to our approach as the Fourier LK (FLK) algorithm. The FLK formulation is advantageous when one pre-processes the source image and template/model with a bank of filters (e.g. oriented edges, Gabor, etc.) as: (i) it can handle substantial illumination variations, (ii) the inefficient pre-processing filter bank step can be subsumed within the FLK algorithm as a sparse diagonal weighting matrix, (iii) unlike traditional LK the computational cost is invariant to the number of filters and as a result far more efficient, and (iv) this approach can be extended to the inverse compositional form of the LK algorithm where nearly all steps (including Fourier transform and filter bank pre-processing) can be pre-computed leading to an extremely efficient and robust approach to gradient descent image matching. Further, these computational savings translate to non-rigid object alignment tasks that are considered extensions of the LK algorithm such as those found in Active Appearance Models (AAMs).

Ruthenium(II) dichloro or dithiocyanato complexes with 4,4′:2′,2″:4″,4‴-quaterpyridinium ligands : towards photosensitisers with enhanced low-energy absorption properties

Fourteen new complexes of the form cis-\[RuIIX2(R2qpy2+)2]4+ (R2qpy2+ = a 4,4′:2′,2″:4″,4‴-quaterpyridinium ligand, X = Cl− or NCS−) have been prepared and isolated as their PF6− salts. Characterisation involved various techniques including 1H NMR spectroscopy and +electrospray or MALDI mass spectrometry. The UV–Vis spectra display intense intraligand π → π∗ absorptions, and also metal-to-ligand charge-transfer (MLCT) bands with two resolved maxima in the visible region. Red-shifts in the MLCT bands occur as the electron-withdrawing strength of the pyridinium groups increases, while replacing Cl− with NCS− causes blue-shifts. Cyclic voltammograms show quasi-reversible or reversible RuIII/II oxidation waves, and several ligand-based reductions that are irreversible. The variations in the redox potentials correlate with changes in the MLCT energies. A single-crystal X-ray structure has been obtained for a protonated form of a proligand salt, \[(4-(CO2H)Ph)2qpyH3+]\[HSO4]3·3H2O. Time-dependent density functional theory calculations give adequate correlations with the experimental UV–Vis spectra for the two carboxylic acid-functionalised complexes in DMSO. Despite their attractive electronic absorption spectra, these dyes are relatively inefficient photosensitisers on electrodes coated with TiO2 or ZnO. These observations are attributed primarily to weak electronic coupling with the surfaces, since the DFT-derived LUMOs include no electron density near the carboxylic acid anchors.

Detection of banana bunchy top virus in virus-infected plants using polymerase chain reaction

Polymerase chain reaction (PCR) was developed for the detection of Banana bunchy top virus (BBTV) at maximum after 210 min and at minimum after 90 min using Pc-1 and Pc-2, respectively. PCR detection of BBTV in crude sap indicated that the freezing of banana tissue in liquid nitrogen (LN2) before extraction was more effective than using sand as the extraction technique. BBTV was also detected using PCR assay in 69 healthy and diseased plants using Na-PO4 buffer containing 1 % SDS. PCR detection of BBTV in nucleic acid extracts using seven different extraction buffers to adapt the use of PCR in routine detection in the field was studied. Results proved that BBTV was detected with high sensitivity in nucleic acid extracts more than in infectious sap. The results also suggested the common aetiology for the BBTV by the PCR reactions of BBTV in nucleic acid extracts from Australia, Burundi, Egypt, France, Gabon, Philippines and Taiwan. Results also proved a positive relation between the Egyptian-BBTV isolate and abaca bunchy top isolate from the Philippines, but there no relation was found with the Cucumber mosaic cucumovirus (CMV) isolates from Egypt and Philippines and Banana bract mosaic virus (BBMV) were found.

Engine performance characteristics for biodiesels of different degrees of saturation and carbon chain lengths

This experimental study examines the effect on performance and emission outputs of a compression ignition engine operating on biodiesels of varying carbon chain length and the degree of unsaturation. A well-instrumented, heavy-duty, multi-cylinder, common-rail, turbo-charged diesel engine was used to ensure that the results contribute in a realistic way to the ongoing debate about the impact of biofuels. Comparative measurements are reported for engine performance as well as the emissions of NOx, particle number and size distribution, and the concentration of the reactive oxygen species (which provide a measure of the toxicity of emitted particles). It is shown that the biodiesels used in this study produce lower mean effective pressure, somewhat proportionally with their lower calorific values; however, the molecular structure has been shown to have little impact on the performance of the engine. The peak in-cylinder pressure is lower for the biodiesels that produce a smaller number of emitted particles, compared to fossil diesel, but the concentration of the reactive oxygen species is significantly higher because of oxygen in the fuels. The differences in the physicochemical properties amongst the biofuels and the fossil diesel significantly affect the engine combustion and emission characteristics. Saturated short chain length fatty acid methyl esters are found to enhance combustion efficiency, reduce NOx and particle number concentration, but results in high levels of fuel consumption.

A comparative study on the mineralogy, chemistry and chronology of the Apollo 16 crystalline impact melt breccias. Part II: Chronology.

The controversy on how to interpret the ages of lunar highland breccias has recently been discussed by James [1]. Are the measured ages testimony of true events in lunar history; do they represent the age of the ancient crustal rocks, mixed ages of unequilibrated matrix-phenocryst relationships, or merely thermal events subsequent to the formational event ? It is certain from analyses of terrestrial impact melt breccias that the melt matrix of whole impact melt sheets is isotopically equilibrated due to the extensive mixing process of the early cratering stage [2,3]. It has been shown that isotopic equilibration takes place between impact melt matrix and target rock clasts therein, with the intensity of isotopic exchange depending on the degree of shock metamorphism, thermal metamorphism and the size of the clasts [4]. Therefore, impact melt breccias - if they are relatively clast-poor and mineralogically well studied - can be considered to be the most reliable source for information on the impact history of the lunar highland.

Breast cancer detection from thermal images using bispectral invariant features

Highly sensitive infrared (IR) cameras provide high-resolution diagnostic images of the temperature and vascular changes of breasts. These images can be processed to emphasize hot spots that exhibit early and subtle changes owing to pathology. The resulting images show clusters that appear random in shape and spatial distribution but carry class dependent information in shape and texture. Automated pattern recognition techniques are challenged because of changes in location, size and orientation of these clusters. Higher order spectral invariant features provide robustness to such transformations and are suited for texture and shape dependent information extraction from noisy images. In this work, the effectiveness of bispectral invariant features in diagnostic classification of breast thermal images into malignant, benign and normal classes is evaluated and a phase-only variant of these features is proposed. High resolution IR images of breasts, captured with measuring accuracy of ±0.4% (full scale) and temperature resolution of 0.1 °C black body, depicting malignant, benign and normal pathologies are used in this study. Breast images are registered using their lower boundaries, automatically extracted using landmark points whose locations are learned during training. Boundaries are extracted using Canny edge detection and elimination of inner edges. Breast images are then segmented using fuzzy c-means clustering and the hottest regions are selected for feature extraction. Bispectral invariant features are extracted from Radon projections of these images. An Adaboost classifier is used to select and fuse the best features during training and then classify unseen test images into malignant, benign and normal classes. A data set comprising 9 malignant, 12 benign and 11 normal cases is used for evaluation of performance. Malignant cases are detected with 95% accuracy. A variant of the features using the normalized bispectrum, which discards all magnitude information, is shown to perform better for classification between benign and normal cases, with 83% accuracy compared to 66% for the original.