Analysis of classification accuracy for pre-filtered multichannel remote sensing data

Noise is one of the main factors degrading the quality of original multichannel remote sensing data and its presence influences classification efficiency, object detection, etc. Thus, pre-filtering is often used to remove noise and improve the solving of final tasks of multichannel remote sensing. Recent studies indicate that a classical model of additive noise is not adequate enough for images formed by modern multichannel sensors operating in visible and infrared bands. However, this fact is often ignored by researchers designing noise removal methods and algorithms. Because of this, we focus on the classification of multichannel remote sensing images in the case of signal-dependent noise present in component images. Three approaches to filtering of multichannel images for the considered noise model are analysed, all based on discrete cosine transform in blocks. The study is carried out not only in terms of conventional efficiency metrics used in filtering (MSE) but also in terms of multichannel data classification accuracy (probability of correct classification, confusion matrix). The proposed classification system combines the pre-processing stage where a DCT-based filter processes the blocks of the multichannel remote sensing image and the classification stage. Two modern classifiers are employed, radial basis function neural network and support vector machines. Simulations are carried out for three-channel image of Landsat TM sensor. Different cases of learning are considered: using noise-free samples of the test multichannel image, the noisy multichannel image and the pre-filtered one. It is shown that the use of the pre-filtered image for training produces better classification in comparison to the case of learning for the noisy image. It is demonstrated that the best results for both groups of quantitative criteria are provided if a proposed 3D discrete cosine transform filter equipped by variance stabilizing transform is applied. The classification results obtained for data pre-filtered in different ways are in agreement for both considered classifiers. Comparison of classifier performance is carried out as well. The radial basis neural network classifier is less sensitive to noise in original images, but after pre-filtering the performance of both classifiers is approximately the same.

Simple shade plots aid better long-term choices of data pre-treatment in multivariate assemblage studies

Shade plots, simple visual representations of abundance matrices from multivariate species assemblage studies, are shown to be an effective aid in choosing an overall transformation (or other pre-treatment) of quantitative data for long-term use, striking an appropriate balance between dominant and less abundant taxa in ensuing resemblance-based multivariate analyses. Though the exposition is entirely general and applicable to all community studies, detailed illustrations of the comparative power and interpretative possibilities of shade plots are given in the case of two estuarine assemblage studies in south-western Australia: (a) macrobenthos in the upper Swan Estuary over a two-year period covering a highly significant precipitation event for the Perth area; and (b) a wide-scale spatial study of the nearshore fish fauna from five divergent estuaries. The utility of transformations of intermediate severity is again demonstrated and, with greater novelty, the potential importance seen of further mild transformation of all data after differential down-weighting (dispersion weighting) of spatially clumped' or schooled' species. Among the new techniques utilized is a two-way form of the RELATE test, which demonstrates linking of assemblage structure (fish) to continuous environmental variables (water quality), having removed a categorical factor (estuary differences). Re-orderings of sample and species axes in the associated shade plots are seen to provide transparent explanations at the species level for such continuous multivariate patterns.

CARBON MONOXIDE AND PREGNANCY: A SEARCH FOR A POSSIBLE THERAPEUTIC IN THE TREATMENT OF PRE-ECLAMPSIA

Pre-eclampsia (PE) is a pregnancy disorder that affects roughly 5-7% of all pregnancies and is a leading cause of both maternal and fetal/neonatal morbidity and mortality. With no present cure for the disease, researchers are interested in the lower incidence of PE observed among the cigarette smoking pregnant population. However, women who use smokeless tobacco do not experience the same decreased incidence of PE, leading to hypothesis of protection against PE from the largest combustible product of cigarette smoke, carbon monoxide (CO). Studies evaluated levels of CO in PE women and found that they were statistically lower than those of healthy pregnancy. Researchers have found CO to possess many cytoprotective and regulatory properties and specifically within the placenta, it has been found to increase perfusion pressure, decrease oxidative stress, decreases ischemia/reperfusion induced apoptosis and maintain endothelial functioning. The idea for use of CO as a possible therapeutic for PE has thus become a real possibility. This study determined CO levels in pregnant women ± smoking as well as in PE women±smoking, as to discover a possible therapeutic range for future treatments. The best correlated automated CO measurement device with blood CO levels was determined, for use in future clinical studies. This thesis also sought a possible CO delivery concentration, in order to achieve the CO levels observed in the human correlation study. A threshold level of maternal CO exposure in a murine animal model was found, for which fetal and maternal negative toxicities were not observed. The results of this thesis lend a few more pieces to the complicated puzzle involving CO and PE and offer another step toward the possibility of a therapeutic treatment/prevention using this gaseous molecule.

Turning the categories inside-out: Complex identifications and multiple interactions in religious ethnography

This paper challenges the fixed boundaries that ethnographers have often constructed between religious insiders and outsiders. Drawing on Neitz's observations, it argues that the main task of reflexive fieldwork is locating the self in relation to ambiguous and shifting boundaries. We offer a comparative analysis of the experiences of two differently socially located researchers to illustrate how religious identity emerges as a continuum, on which one's place is negotiated with one's research participants. We also examine the importance of intersecting multiple identities. Finally, the paper questions whether social identity categories are the primary way that we relate with our respondents. It explores the spiritual and emotional dimensions of research relationships and argues that these may transform, reinforce and generally interact with social identities. Comparing our experiences, we outline the consequences of these reflections for data gathering and analysis.

Tight junctional abnormality in multiple sclerosis white matter affects all calibres of vessel and is associated with blood-brain barrier leakage and active demyelination

Blood-brain barrier (BBB) hyperpermeability in multiple sclerosis (MS) is associated with lesion pathogenesis and has been linked to pathology in microvascular tight junctions (TJs). This study quantifies the uneven distribution of TJ pathology and its association with BBB leakage. Frozen sections from plaque and normal-appearing white matter (NAWM) in 14 cases were studied together with white matter from six neurological and five normal controls. Using single and double immunofluorescence and confocal microscopy, the TJ-associated protein zonula occludens-1 (ZO-1) was examined across lesion types and tissue categories, and in relation to fibrinogen leakage. Confocal image data sets were analysed for 2198 MS and 1062 control vessels. Significant differences in the incidence of TJ abnormalities were detected between the different lesion types in MS and between MS and control white matter. These were frequent in oil-red O (ORO)+ active plaques, affecting 42% of vessel segments, but less frequent in ORO- inactive plaques (23%), NAWM (13%), and normal (3.7%) and neurological controls (8%). A similar pattern was found irrespective of the vessel size, supporting a causal role for diffusible inflammatory mediators. In both NAWM and inactive lesions, dual labelling showed that vessels with the most TJ abnormality also showed most fibrinogen leakage. This was even more pronounced in active lesions, where 41% of vessels in the highest grade for TJ alteration showed severe leakage. It is concluded that disruption of TJs in MS, affecting both paracellular and transcellular paths, contributes to BBB leakage. TJ abnormality and BBB leakage in inactive lesions suggests either failure of TJ repair or a continuing pathological process. In NAWM, it suggests either pre-lesional change or secondary damage. Clinically inapparent TJ pathology has prognostic implications and should be considered when planning disease-modifying therapy