Analysis of four gutta-percha techniques used to fill mesial root canals of mandibular molars

P>Aim To compare the percentage of gutta-percha, sealer and voids and the influence of isthmuses in mesial root canals of mandibular molars filled with different techniques. Methodology Canals in 60 mesial roots of mandibular first molars were prepared with ProTaper instruments to size F2 (size 25, 0.08 taper) and filled using a single-cone, lateral compaction, System B or Thermafil techniques. An epoxy resin sealer was labelled with Rhodamine-B dye to allow analysis under a confocal microscope. The percentage of gutta-percha, sealer and area of voids was calculated at 2, 4 and 6 mm from the apex, using Image Tool 3.0 software. Statistical analysis was performed using nonparametric Kruskal-Wallis and Dunn tests (P < 0.05). The influence of isthmuses on the presence or absence of voids was evaluated using the Fisher test. Results At the 2 mm level, the percentage of gutta-percha, sealer and voids was similar amongst the System B, lateral compaction and single-cone techniques. The single-cone technique revealed significantly less gutta-percha, more sealer and voids in comparison with the Thermafil technique at the 2 and 4 mm level (P < 0.05). The analysis of all sections (2, 4 and 6 mm) revealed that more gutta-percha and less sealer and voids were found in root canals filled with Thermafil and System B techniques (P < 0.05). The Fisher test revealed that the presence of isthmuses increased the occurence of voids in the lateral compaction group only (P < 0.05). Conclusion Gutta-percha, sealer filled area and voids were dependent on the canal-filling technique. The presence of isthmuses may influence the quality of root filling.

Bacterial leakage in root canals obturated by different techniques. Part 1: microbiologic evaluation

Objective. This study compared the coronal bacterial leakage of root canals obturated by different techniques and with different lengths of obturation. Study design. The canals of palatal roots of 160 maxillary molars were instrumented and divided into different groups according to the obturation technique used (lateral condensation, Microseal system, Touch `n Heat + Ultrafil system, or Tagger`s hybrid technique) and the length of obturation (5 mm or 10 mm). The roots were impermeabilized, sterilized in ethylene oxide, and mounted on a device for evaluation of the bacterial leakage. Results. Tagger`s hybrid technique produced a statistically greater number of specimens with coronal leakage than the other techniques. There was no statistically significant difference between the lateral condensation, Touch `n Heat + Ultrafil, and Microseal groups. Root canals with 10 mm of obturation produced a statistically significantly smaller number of specimens with leakage than root canals with 5 mm of obturation. Conclusion. Tagger`s hybrid technique produced a greater number of specimens with coronal leakage than the other techniques, and a greater number of root canals with 5 mm of obturation leaked than root canals with 10 mm of obturation.

Effect of power Doppler and digital subtraction techniques on the comparison of myocardial contrast echocardiography with SPECT

Objective-To compare the accuracy and feasibility of harmonic power Doppler and digitally subtracted colour coded grey scale imaging for the assessment of perfusion defect severity by single photon emission computed tomography (SPECT) in an unselected group of patients. Design-Cohort study. Setting-Regional cardiothoracic unit. Patients-49 patients (mean (SD) age 61 (11) years; 27 women, 22 men) with known or suspected coronary artery disease were studied with simultaneous myocardial contrast echo (MCE) and SPECT after standard dipyridamole stress. Main outcome measures-Regional myocardial perfusion by SPECT, performed with Tc-99m tetrafosmin, scored qualitatively and also quantitated as per cent maximum activity. Results-Normal perfusion was identified by SPECT in 225 of 270 segments (83%). Contrast echo images were interpretable in 92% of patients. The proportion of normal MCE by grey scale, subtracted, and power Doppler techniques were respectively 76%, 74%, and 88% (p < 0.05) at > 80% of maximum counts, compared with 65%, 69%, and 61% at < 60% of maximum counts. For each technique, specificity was lowest in the lateral wail, although power Doppler was the least affected. Grey scale and subtraction techniques were least accurate in the septal wall, but power Doppler showed particular problems in the apex. On a per patient analysis, the sensitivity was 67%, 75%, and 83% for detection of coronary artery disease using grey scale, colour coded, and power Doppler, respectively, with a significant difference between power Doppler and grey scale only (p < 0.05). Specificity was also the highest for power Doppler, at 55%, but not significantly different from subtracted colour coded images. Conclusions-Myocardial contrast echo using harmonic power Doppler has greater accuracy than with grey scale imaging and digital subtraction. However, power Doppler appears to be less sensitive for mild perfusion defects.

Supervisory control of wastewater treatment plants by combining principal component analysis and fuzzy c-means clustering

In this paper a methodology for integrated multivariate monitoring and control of biological wastewater treatment plants during extreme events is presented. To monitor the process, on-line dynamic principal component analysis (PCA) is performed on the process data to extract the principal components that represent the underlying mechanisms of the process. Fuzzy c-means (FCM) clustering is used to classify the operational state. Performing clustering on scores from PCA solves computational problems as well as increases robustness due to noise attenuation. The class-membership information from FCM is used to derive adequate control set points for the local control loops. The methodology is illustrated by a simulation study of a biological wastewater treatment plant, on which disturbances of various types are imposed. The results show that the methodology can be used to determine and co-ordinate control actions in order to shift the control objective and improve the effluent quality.

Exploratory spatial data analysis techniques for examining urban crime

Regional planners, policy makers and policing agencies all recognize the importance of better understanding the dynamics of crime. Theoretical and application-oriented approaches which provide insights into why and where crimes take place are much sought after. Geographic information systems and spatial analysis techniques, in particular, are proving to be essential or studying criminal activity. However, the capabilities of these quantitative methods continue to evolve. This paper explores the use of geographic information systems and spatial analysis approaches for examining crime occurrence in Brisbane, Australia. The analysis highlights novel capabilities for the analysis of crime in urban regions.

Solution techniques for transport problems involving steep concentration gradients: application to noncatalytic fluid solid reactions

Some efficient solution techniques for solving models of noncatalytic gas-solid and fluid-solid reactions are presented. These models include those with non-constant diffusivities for which the formulation reduces to that of a convection-diffusion problem. A singular perturbation problem results for such models in the presence of a large Thiele modulus, for which the classical numerical methods can present difficulties. For the convection-diffusion like case, the time-dependent partial differential equations are transformed by a semi-discrete Petrov-Galerkin finite element method into a system of ordinary differential equations of the initial-value type that can be readily solved. In the presence of a constant diffusivity, in slab geometry the convection-like terms are absent, and the combination of a fitted mesh finite difference method with a predictor-corrector method is used to solve the problem. Both the methods are found to converge, and general reaction rate forms can be treated. These methods are simple and highly efficient for arbitrary particle geometry and parameters, including a large Thiele modulus. (C) 2001 Elsevier Science Ltd. All rights reserved.

Techniques to determine ignition, flame stability and burnout of blended coals in p.f. power station boilers

The blending of coals has become popular to improve the performance of coals, to meet specifications of power plants and, to reduce the cost of coals, This article reviews the results and provides new information on ignition, flame stability, and carbon burnout studies of blended coals. The reviewed studies were conducted in laboratory-, pilot-, and full-scale facilities. The new information was taken in pilot-scale studies. The results generally show that blending a high-volatile coal with a low-volatile coal or anthracite can improve the ignition, flame stability and burnout of the blends. This paper discusses two general methods to predict the performance of blended coals: (1) experiment; and (2) indices. Laboratory- and pilot-scale tests, at least, provide a relative ranking of the combustion performance of coal/blends in power station boilers. Several indices, volatile matter content, heating value and a maceral index, can be used to predict the relative ranking of ignitability and flame stability of coals and blends. The maceral index, fuel ratio, and vitrinite reflectance can also be used to predict the absolute carbon burnout of coal and blends within limits. (C) 2000 Elsevier Science Ltd. All rights reserved.

Molecular genetics of schizophrenia

1. Schizophrenia is a chronic, disabling brain disease that affects approxmately 1% of the world's population. It is characterized by delusions, hallucinations and formal thought disorder, together with a decline in socio-occupational functioning. While the causes for schizophrenia remain unknown, evidence from family, twin and adoption studies clearly demonstrates that it aggregates in families, with this clustering largely attributable to genetic rather than cultural or environmental factors. Identifying the genes involved, however, has proven to be a difficult task because schizophrenia is a complex trait characterized by an imprecise phenotype, the existence of phenocopies and the presence of low disease penetrance, 2. The current working hypothesis for schizophrenia causation is that multiple genes of small to moderate effect confer compounding risk through interactions with each other and with non-genetic risk factors, The same genes may be commonly involved in conferring risk across populations or they may vary in number and strength between different populations. To search for evidence of such genetic loci, both candidate gene and genome-wide linkage studies have been used in clinical cohorts collected from a variety of populations. Collectively, these works provide some evidence for the involvement of a number of specific genes (e.g. the 5-hydroxytryptamine (5-HT) type 2a receptor (5-HT2a) gene and the dopamine D-3 receptor gene) and as yet unidentified factors localized to specific chromosomal regions, including 6p, 6q, 8p, 13q and 22q, These data provide suggestive, but no conclusive, evidence for causative genes. 3. To enable further progress there is a need to: (i) collect fine-grained clinical datasets while searching the schizophrenia phenotype for subgroups or dimensions that may provide a more direct route to causative genes; and (ii) integrate recent refinements in molecular genetic technology, including modern composite marker maps, DNA expression assays and relevant animal models, while using the latest analytical techniques to extract maximum information in order to help distinguish a true result from a false-positive finding.

A mixture model-based approach to the clustering of microarray expression data

Motivation: This paper introduces the software EMMIX-GENE that has been developed for the specific purpose of a model-based approach to the clustering of microarray expression data, in particular, of tissue samples on a very large number of genes. The latter is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. A feasible approach is provided by first selecting a subset of the genes relevant for the clustering of the tissue samples by fitting mixtures of t distributions to rank the genes in order of increasing size of the likelihood ratio statistic for the test of one versus two components in the mixture model. The imposition of a threshold on the likelihood ratio statistic used in conjunction with a threshold on the size of a cluster allows the selection of a relevant set of genes. However, even this reduced set of genes will usually be too large for a normal mixture model to be fitted directly to the tissues, and so the use of mixtures of factor analyzers is exploited to reduce effectively the dimension of the feature space of genes. Results: The usefulness of the EMMIX-GENE approach for the clustering of tissue samples is demonstrated on two well-known data sets on colon and leukaemia tissues. For both data sets, relevant subsets of the genes are able to be selected that reveal interesting clusterings of the tissues that are either consistent with the external classification of the tissues or with background and biological knowledge of these sets.

Monitoring the composition and form of urban environments based on the vegetation-impervious surface-soil (VIS) model by sub-pixel analysis techniques

The majority of the world's population now resides in urban environments and information on the internal composition and dynamics of these environments is essential to enable preservation of certain standards of living. Remotely sensed data, especially the global coverage of moderate spatial resolution satellites such as Landsat, Indian Resource Satellite and Systeme Pour I'Observation de la Terre (SPOT), offer a highly useful data source for mapping the composition of these cities and examining their changes over time. The utility and range of applications for remotely sensed data in urban environments could be improved with a more appropriate conceptual model relating urban environments to the sampling resolutions of imaging sensors and processing routines. Hence, the aim of this work was to take the Vegetation-Impervious surface-Soil (VIS) model of urban composition and match it with the most appropriate image processing methodology to deliver information on VIS composition for urban environments. Several approaches were evaluated for mapping the urban composition of Brisbane city (south-cast Queensland, Australia) using Landsat 5 Thematic Mapper data and 1:5000 aerial photographs. The methods evaluated were: image classification; interpretation of aerial photographs; and constrained linear mixture analysis. Over 900 reference sample points on four transects were extracted from the aerial photographs and used as a basis to check output of the classification and mixture analysis. Distinctive zonations of VIS related to urban composition were found in the per-pixel classification and aggregated air-photo interpretation; however, significant spectral confusion also resulted between classes. In contrast, the VIS fraction images produced from the mixture analysis enabled distinctive densities of commercial, industrial and residential zones within the city to be clearly defined, based on their relative amount of vegetation cover. The soil fraction image served as an index for areas being (re)developed. The logical match of a low (L)-resolution, spectral mixture analysis approach with the moderate spatial resolution image data, ensured the processing model matched the spectrally heterogeneous nature of the urban environments at the scale of Landsat Thematic Mapper data.