Animations of micro-computed tomography of a pleistocene terebratulid brachiopod

The dorsal valve of a Pleistocene terebratulid brachiopod, Terebratula scillae Seguenza, 1871, has developed a malignant cyst due to colonization in vivo by an endolithic sponge.This trace fossil is a compound boring and bioclaustration structure, representing a boring that has grown in unison with the growth of the cyst. The brachiopod has grown to adult size and growthlines indicate that it was colonised by the sponge when about half grown. Malformation of the shell may not have caused the death of the brachiopod and the sponge does not appear to have outlived its host; both symbionts seem to have died more or less simultaneously. This minus-minus relationship of two symbionts is considered to be a case of 'accidental symbiosis'.

Animation of micro-computed tomography of bioerosion trace Entobia megastoma made by East Australian bioeroding sponge Cliona celata

Endolithic bioerosion is difficult to analyse and to describe, and it usually requires damaging of the sample material. Sponge erosion (Entobia) may be one of the most difficult to evaluate as it is simultaneously macroscopically inhomogeneous and microstructurally intricate. We studied the bioerosion traces of the two Australian sponges Cliona celata Grant, 1826 (sensu Schönberg 2000) and Cliona orientalis Thiele, 1900 with a newly available radiographic technology: high resolution X-ray micro-computed tomography (MCT). MCT allows non-destructive visualisation of live and dead structures in three dimensions and was compared to traditional microscopic methods. MCT and microscopy showed that C. celata bioerosion was more intense in the centre and branched out in the periphery. In contrast, C. orientalis produced a dense, even trace meshwork and caused an overall more intense erosion pattern than C. celata. Extended pioneering filaments were not usually found at the margins of the studied sponge erosion, but branches ended abruptly or tapered to points. Results obtained with MCT were similar in quality to observations from transparent optical spar under the dissecting microscope. Microstructures could not be resolved as well as with e.g. scanning electron microscopy (SEM). Even though sponge scars and sponge chips were easily recognisable on maximum magnification MCT images, they lacked the detail that is available from SEM. Other drawbacks of MCT involve high costs and presently limited access. Even though MCT cannot presently replace traditional techniques such as corrosion casts viewed by SEM, we obtained valuable information. Especially for the possibility to measure endolithic pore volumes, we regard MCT as a very promising tool that will continue to be optimised. A combination of different methods will produce the best results in the study of Entobia.

Various ratios of C1-C5 hydrocarbons, gas composition and computed temperature at DSDP Leg 64 Holes

I have evaluated shipboard data and preliminary interpretations related to organic geochemistry in light of additional shore-based analyses. Data on interstitial gas, the C/N ratio, and fluorescence indicate that organic matter was altered by sills and that these were all single intrusions except the upper sill complex at Site 481, which was a multiple emplacement. Site 477 had the highest in situ temperature, estimated from interstitial gas composition to be 225°C.

Technical developments for computed tomography on the CENBG nanobeam line

The use of ion microbeams as probes for computedtomography has proven to be a powerful tool for the three-dimensional characterization of specimens a few tens of micrometers in size. Compared to other types of probes, the main advantage is that quantitative information about mass density and composition can be obtained directly, using specific reconstruction codes. At the Centre d’Etudes Nucléaires de Bordeaux Gradignan (CENBG), this technique was initially developed for applications in cellular biology. However, the observation of the cell ultrastructure requires a sub-micron resolution. The construction of the nanobeamline at the Applications Interdisciplinaires des Faisceaux d’Ions en Region Aquitaine (AIFIRA) irradiation facility has opened new perspectives for such applications. The implementation of computedtomography on the nanobeamline of CENBG has required a careful design of the analysis chamber, especially microscopes for precise sample visualization, and detectors for scanning transmission ion microscopy (STIM) and for particle induced X-ray emission (PIXE). The sample can be precisely positioned in the three directions X, Y, Z and a stepper motor coupled to a goniometer ensures the rotational motion. First images of 3D tomography were obtained on a reference sample containing microspheres of certified diameter, showing the good stability of the beam and the sample stage, and the precision of the motion.

Automatic quantification of matrix cracking and fiber rotation by X-ray computed tomography in shear-deformed carbon fiber-reinforced laminates

The deformation and damage mechanisms of carbon fiber-reinforced epoxy laminates deformed in shear were studied by means of X-ray computed tomography. In particular, the evolution of matrix cracking, interply delamination and fiber rotation was ascertained as a function of the applied strain. In order to provide quantitative information, an algorithm was developed to automatically determine the crack density and the fiber orientation from the tomograms. The investigation provided new insights about the complex interaction between the different damage mechanisms (i.e. matrix cracking and interply delamination) as a function of the applied strain, ply thickness and ply location within the laminate as well as quantitative data about the evolution of matrix cracking and fiber rotation during deformation

Geometrical characterization of undisturbed soil samples using X-ray computed tomography image analysis. Effect of soil management on soil structure

El estudio de la estructura del suelo es de vital importancia en diferentes campos de la ciencia y la tecnología. La estructura del suelo controla procesos físicos y biológicos importantes en los sistemas suelo-planta-microorganismos. Estos procesos están dominados por la geometría de la estructura del suelo, y una caracterización cuantitativa de la heterogeneidad de la geometría del espacio poroso es beneficiosa para la predicción de propiedades físicas del suelo. La tecnología de la tomografía computerizada de rayos-X (CT) nos permite obtener imágenes digitales tridimensionales del interior de una muestra de suelo, proporcionando información de la geometría de los poros del suelo y permitiendo el estudio de los poros sin destruir las muestras. Las técnicas de la geometría fractal y de la morfología matemática se han propuesto como una poderosa herramienta para analizar y cuantificar características geométricas. Las dimensiones fractales del espacio poroso, de la interfaz poro-sólido y de la distribución de tamaños de poros son indicadores de la complejidad de la estructura del suelo. Los funcionales de Minkowski y las funciones morfológicas proporcionan medios para medir características geométricas fundamentales de los objetos geométricos tridimensionales. Esto es, volumen, superficie, curvatura media de la superficie y conectividad. Las características del suelo como la distribución de tamaños de poros, el volumen del espacio poroso o la superficie poro-solido pueden ser alteradas por diferentes practicas de manejo de suelo. En este trabajo analizamos imágenes tomográficas de muestras de suelo de dos zonas cercanas con practicas de manejo diferentes. Obtenemos un conjunto de medidas geométricas, para evaluar y cuantificar posibles diferencias que el laboreo pueda haber causado en el suelo. ABSTRACT The study of soil structure is of vital importance in different fields of science and technology. Soil structure controls important physical and biological processes in soil-plant-microbial systems. Those processes are dominated by the geometry of soil pore structure, and a quantitative characterization of the spatial heterogeneity of the pore space geometry is beneficial for prediction of soil physical properties. The technology of X-ray computed tomography (CT) allows us to obtain three-dimensional digital images of the inside of a soil sample providing information on soil pore geometry and enabling the study of the pores without disturbing the samples. Fractal geometry and mathematical morphological techniques have been proposed as powerful tools to analyze and quantify geometrical features. Fractal dimensions of pore space, pore-solid interface and pore size distribution are indicators of soil structure complexity. Minkowski functionals and morphological functions provide means to measure fundamental geometrical features of three-dimensional geometrical objects, that is, volume, boundary surface, mean boundary surface curvature, and connectivity. Soil features such as pore-size distribution, pore space volume or pore-solid surface can be altered by different soil management practices. In this work we analyze CT images of soil samples from two nearby areas with contrasting management practices. We performed a set of geometrical measures, some of them from mathematical morphology, to assess and quantify any possible difference that tillage may have caused on the soil.

Neural-network-based classification of cognitively normal, demented, Alzheimer disease and vascular dementia from single photon emission with computed tomography image data from brain.

Single photon emission with computed tomography (SPECT) hexamethylphenylethyleneamineoxime technetium-99 images were analyzed by an optimal interpolative neural network (OINN) algorithm to determine whether the network could discriminate among clinically diagnosed groups of elderly normal, Alzheimer disease (AD), and vascular dementia (VD) subjects. After initial image preprocessing and registration, image features were obtained that were representative of the mean regional tissue uptake. These features were extracted from a given image by averaging the intensities over various regions defined by suitable masks. After training, the network classified independent trials of patients whose clinical diagnoses conformed to published criteria for probable AD or probable/possible VD. For the SPECT data used in the current tests, the OINN agreement was 80 and 86% for probable AD and probable/possible VD, respectively. These results suggest that artificial neural network methods offer potential in diagnoses from brain images and possibly in other areas of scientific research where complex patterns of data may have scientifically meaningful groupings that are not easily identifiable by the researcher.

A methodology for improving computed individual regressions predictions.

This research proposes a methodology to improve computed individual prediction values provided by an existing regression model without having to change either its parameters or its architecture. In other words, we are interested in achieving more accurate results by adjusting the calculated regression prediction values, without modifying or rebuilding the original regression model. Our proposition is to adjust the regression prediction values using individual reliability estimates that indicate if a single regression prediction is likely to produce an error considered critical by the user of the regression. The proposed method was tested in three sets of experiments using three different types of data. The first set of experiments worked with synthetically produced data, the second with cross sectional data from the public data source UCI Machine Learning Repository and the third with time series data from ISO-NE (Independent System Operator in New England). The experiments with synthetic data were performed to verify how the method behaves in controlled situations. In this case, the outcomes of the experiments produced superior results with respect to predictions improvement for artificially produced cleaner datasets with progressive worsening with the addition of increased random elements. The experiments with real data extracted from UCI and ISO-NE were done to investigate the applicability of the methodology in the real world. The proposed method was able to improve regression prediction values by about 95% of the experiments with real data.