Effect of processing induced particle alignment on the fracture toughness and fracture behavior of multiphase dental ceramics

Objective. To investigate the processing induced particle alignment on fracture behavior of four multiphase dental ceramics (one porcelain, two glass-ceramics and a glass-infiltrated-alumina composite). Methods. Disks (empty set12mm x 1.1 mm-thick) and bars (3 mm x 4 mm x 20 mm) of each material were processed according to manufacturer instructions, machined and polished. Fracture toughness (K(IC)) was determined by the indentation strength method using 3-point bending and biaxial flexure fixtures for the fracture of bars and disks, respectively. Microstructural and fractographic analyses were performed with scanning electron microscopy, energy dispersive spectroscopy and X-ray diffraction. Results. The isotropic microstructure of the porcelain and the leucite-based glass-ceramic resulted in similar fracture toughness values regardless of the specimen geometry. On the other hand, materials containing second-phase particles with high aspect ratio (lithium disilicate glass-ceramic and glass-infiltrated-alumina composite) showed lower fracture toughness for disk specimens compared to bars. For the lithium disilicate glass-ceramic disks, it was demonstrated that the occurrence of particle alignment during the heat-pressing procedure resulted in an unfavorable pattern that created weak microstructural paths during the biaxial test. For the glass-infiltrated-alumina composite, the microstructural analysis showed that the large alumina platelets tended to align their large surfaces perpendicularly to the direction of particle deposition during slip casting of green preforms. Significance. The fracture toughness of dental ceramics with anisotropic microstructure should be determined by means of biaxial testing, since it results in lower values. (C) 2009 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Integrating high and moderate spatial resolution image data to estimate forest age structure

The collection of spatial information to quantify changes to the state and condition of the environment is a fundamental component of conservation or sustainable utilization of tropical and subtropical forests, Age is an important structural attribute of old-growth forests influencing biological diversity in Australia eucalypt forests. Aerial photograph interpretation has traditionally been used for mapping the age and structure of forest stands. However this method is subjective and is not able to accurately capture fine to landscape scale variation necessary for ecological studies. Identification and mapping of fine to landscape scale vegetative structural attributes will allow the compilation of information associated with Montreal Process indicators lb and ld, which seek to determine linkages between age structure and the diversity and abundance of forest fauna populations. This project integrated measurements of structural attributes derived from a canopy-height elevation model with results from a geometrical-optical/spectral mixture analysis model to map forest age structure at a landscape scale. The availability of multiple-scale data allows the transfer of high-resolution attributes to landscape scale monitoring. Multispectral image data were obtained from a DMSV (Digital Multi-Spectral Video) sensor over St Mary's State Forest in Southeast Queensland, Australia. Local scene variance levels for different forest tapes calculated from the DMSV data were used to optimize the tree density and canopy size output in a geometric-optical model applied to a Landsat Thematic Mapper (TU) data set. Airborne laser scanner data obtained over the project area were used to calibrate a digital filter to extract tree heights from a digital elevation model that was derived from scanned colour stereopairs. The modelled estimates of tree height, crown size, and tree density were used to produce a decision-tree classification of forest successional stage at a landscape scale. The results obtained (72% accuracy), were limited in validation, but demonstrate potential for using the multi-scale methodology to provide spatial information for forestry policy objectives (ie., monitoring forest age structure).

MapScript: A map algebra programming language incorporating neighborhood analysis

Map algebra is a data model and simple functional notation to study the distribution and patterns of spatial phenomena. It uses a uniform representation of space as discrete grids, which are organized into layers. This paper discusses extensions to map algebra to handle neighborhood operations with a new data type called a template. Templates provide general windowing operations on grids to enable spatial models for cellular automata, mathematical morphology, and local spatial statistics. A programming language for map algebra that incorporates templates and special processing constructs is described. The programming language is called MapScript. Example program scripts are presented to perform diverse and interesting neighborhood analysis for descriptive, model-based and processed-based analysis.

Using a cartographic modeling language to manipulate spectral satellite imagery

Land related information about the Earth's surface is commonIJ found in two forms: (1) map infornlation and (2) satellite image da ta. Satellite imagery provides a good visual picture of what is on the ground but complex image processing is required to interpret features in an image scene. Increasingly, methods are being sought to integrate the knowledge embodied in mop information into the interpretation task, or, alternatively, to bypass interpretation and perform biophysical modeling directly on derived data sources. A cartographic modeling language, as a generic map analysis package, is suggested as a means to integrate geographical knowledge and imagery in a process-oriented view of the Earth. Specialized cartographic models may be developed by users, which incorporate mapping information in performing land classification. In addition, a cartographic modeling language may be enhanced with operators suited to processing remotely sensed imagery. We demonstrate the usefulness of a cartographic modeling language for pre-processing satellite imagery, and define two nerv cartographic operators that evaluate image neighborhoods as post-processing operations to interpret thematic map values. The language and operators are demonstrated with an example image classification task.

Genetics of cognition: Outline of a collaborative twin study

Amultidisciplinary collaborative study examining cognition in a large sample of twins is outlined. A common experimental protocol and design is used in The Netherlands, Australia and Japan to measure cognitive ability using traditional IQ measures (i.e., psychometric IQ), processing speed (e.g., reaction time [RT] and inspection time [IT]), and working memory (e.g., spatial span, delayed response [DR] performance). The main aim is to investigate the genetic covariation among these cognitive phenotypes in order to use the correlated biological markers in future linkage and association analyses to detect quantitativetrait loci (QTLs). We outline the study and methodology, and report results from our preliminary analyses that examines the heritability of processing speed and working memory indices, and their phenotypic correlation with IQ. Heritability of Full Scale IQ was 87% in the Netherlands, 83% in Australia, and 71% in Japan. Heritability estimates for processing speed and working memory indices ranged from 33–64%. Associations of IQ with RT and IT (−0.28 to −0.36) replicated previous findings with those of higher cognitive ability showing faster speed of processing. Similarly, significant correlations were indicated between IQ and the spatial span working memory task (storage [0.31], executive processing [0.37]) and the DR working memory task (0.25), with those of higher cognitive ability showing better memory performance. These analyses establish the heritability of the processing speed and working memory measures to be used in our collaborative twin study of cognition, and support the findings that individual differences in processing speed and working memory may underlie individual differences in psychometric IQ.

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.

Recent advances in processing and characterization of periodic mesoporous MCM-41 silicate molecular sieves

The discovery of periodic mesoporous MCM-41 and related molecular sieves has attracted significant attention from a fundamental as well as applied perspective. They possess well-defined cylindrical/hexagonal mesopores with a simple geometry, tailored pore size, and reproducible surface properties. Hence, there is an ever-growing scientific interest in the challenges posed by their processing and characterization and by the refinement of various sorption models. Further, MCM-41-based materials are currently under intense investigation with respect to their utility as adsorbents, catalysts, supports, ion-exchangers, and molecular hosts. In this article, we provide a critical review of the developments in these areas with particular emphasis on adsorption characteristics, progress in controlling the pore sizes, and a comparison of pore size distributions using traditional and newer models. The model proposed by the authors for adsorption isotherms and criticalities in capillary condensation and hysteresis is found to explain unusual adsorption behavior in these materials while providing a convenient characterization tool.

Spatial distribution and developmental appearance of postjunctional P2X(1) receptors on smooth muscle cells of the mouse vas deferens

P2X(1)-type purinoceptors, have been shown to mediate fast transmission between sympathetic varicosities and smooth muscle cells in the mouse vas deferens but the spatial organization of these receptors on the smooth muscle cells remains inconclusive. Voltage clamp techniques were used to estimate the amplitudes of spontaneous excitatory junction currents (SEJCs) in cells of the vas deferens longitudinal smooth muscle layer. These currents involved the activation of about 6% of the P2X-type channels present on the cell, as compared to whole cell currents produced when isolated smooth muscle cells were exposed to maximal concentrations of either ATP or alpha,beta -MeATP. Immunofluorescence staining of the vas deferens with antibodies against P2X(1) receptor showed a diffuse, grainy distribution over the entire membrane of each smooth muscle cell. Anti-P2X(1) staining was not markedly clustered beneath anti-SV2-stained sympathetic varicosities. Similar results were obtained for cells in the urinary bladder. During development, P2X(1) mRNA was detected as early as embryonic day 15 (E15). Increasing intensities of diffuse immunostaining for P2X(1) were observed in the walls of the bladder, tail artery, and aorta from E15 until 6 weeks postnatal. The vas deferens showed increasing intensities of diffuse staining of its smooth muscle layers between 2 and 6 weeks postnatal, consistent with the time-course of development of fast purinergic transmission described previously. Together, the results suggest that the response of smooth muscle of the vas deferens to ATP released from sympathetic varicosities relies on rapidly desensitizing P2X(1) receptors, distributed diffusely across the smooth muscle cell surface. Synapse 42:1-11, 2001. (C) 2001 Wiley-Liss, Inc.

Habitat complexity, spatial interference, and "minimum risk distribution": a framework for population stability

In the past century, the debate over whether or not density-dependent factors regulate populations has generally focused on changes in mean population density, ignoring the spatial variance around the mean as unimportant noise. In an attempt to provide a different framework for understanding population dynamics based on individual fitness, this paper discusses the crucial role of spatial variability itself on the stability of insect populations. The advantages of this method are the following: (1) it is founded on evolutionary principles rather than post hoc assumptions; (2) it erects hypotheses that can be tested; and (3) it links disparate ecological schools, including spatial dynamics, behavioral ecology, preference-performance, and plant apparency into an overall framework. At the core of this framework, habitat complexity governs insect spatial variance. which in turn determines population stability. First, the minimum risk distribution (MRD) is defined as the spatial distribution of individuals that results in the minimum number of premature deaths in a population given the distribution of mortality risk in the habitat (and, therefore, leading to maximized population growth). The greater the divergence of actual spatial patterns of individuals from the MRD, the greater the reduction of population growth and size from high, unstable levels. Then, based on extensive data from 29 populations of the processionary caterpillar, Ochrogaster lunifer, four steps are used to test the effect of habitat interference on population growth rates. (1) The costs (increasing the risk of scramble competition) and benefits (decreasing the risk of inverse density-dependent predation) of egg and larval aggregation are quantified. (2) These costs and benefits, along with the distribution of resources, are used to construct the MRD for each habitat. (3) The MRD is used as a benchmark against which the actual spatial pattern of individuals is compared. The degree of divergence of the actual spatial pattern from the MRD is quantified for each of the 29 habitats. (4) Finally, indices of habitat complexity are used to provide highly accurate predictions of spatial divergence from the MRD, showing that habitat interference reduces population growth rates from high, unstable levels. The reason for the divergence appears to be that high levels of background vegetation (vegetation other than host plants) interfere with female host-searching behavior. This leads to a spatial distribution of egg batches with high mortality risk, and therefore lower population growth. Knowledge of the MRD in other species should be a highly effective means of predicting trends in population dynamics. Species with high divergence between their actual spatial distribution and their MRD may display relatively stable dynamics at low population levels. In contrast, species with low divergence should experience high levels of intragenerational population growth leading to frequent habitat-wide outbreaks and unstable dynamics in the long term. Six hypotheses, erected under the framework of spatial interference, are discussed, and future tests are suggested.