High-resolution imaging of ordered mixed-layer clays

HRTEM has been used to examine illite/smectite from the Mancos shale, rectorite from Garland County, Arkansas; illite from Silver Hill, Montana; Na-smectite from Crook County, Wyoming; corrensite from Packwood, Washington; and diagenetic chlorite from the Tuscaloosa formation. Thin specimens were prepared by ion milling, ultra-microtome sectioning and/or grain dispersal on a porous carbon substrate. Some smectite-bearing clays were also examined after intercalation with dodecylamine hydrochloride (DH). Intercalation of smectite with DH proved to be a reliable method of HRTEM imaging of expanded smectite, d(001) 16 A which could then be distinguished from unexpanded illite, d(001) 10 A. Lattice fringes of basal spacings of DH-intercalated rectorite and illite/smectite showed 26 A periodicity. These data support XRD studies which suggest that these samples are ordered, interstratified varieties of illite and smectite. The ion-thinned, unexpanded corrensite sample showed discrete crystallites containing 10 A and 14 A basal spacings corresponding with collapsed smectite and chlorite, respectively. Regions containing disordered layers of chlorite and smectite were also noted. Crystallites containing regular alternations of smectite and chlorite were not common. These HRTEM observations of corrensite did not corroborate XRD data. Particle sizes parallel to the c axis ranged widely for each sample studied, and many particles showed basal dimensions equivalent to > five layers. -J.M.H.

High resolution imaging of boron carbide microstructures

Two samples of boron carbide have been examined using high resolution transmission electron microscopy (HRTEM). A hot pressed B13C2 sample shows a high density of variable width twins normal to (10-11). Subtle shifts or offsets of lattice fringes along the twin plane and normal to (10 5) were also observed. A B4C powder showed little evidence of stacking disorder in crystalline regions.

Identifying vulnerable carotid plaques in vivo using high resolution magnetic resonance imaging-based finite element analysis

Object. Individuals with carotid atherosclerosis develop symptoms following rupture of vulnerable plaques. Biomechanical stresses within this plaque may increase vulnerability to rupture. In this report the authors describe the use of in vivo carotid plaque imaging and computational mechanics to document the magnitude and distribution of intrinsic plaque stresses. Methods. Ten (five symptomatic and five asymptomatic) individuals underwent plaque characterization magnetic resonance (MR) imaging. Plaque geometry and composition were determined by multisequence review. Intrinsic plaque stress profiles were generated from 3D meshes by using finite element computational analysis. Differences in principal (shear) stress between normal and diseased sections of the carotid artery and between symptomatic and asymptomatic plaques were noted. Results. There was a significant difference in peak principal stress between diseased and nondiseased segments of the artery (mean difference 537.65 kPa, p < 0.05). Symptomatic plaques had higher mean stresses than asymptomatic plaques (627.6 kPa compared with 370.2 kPa, p = 0.05), which were independent of luminal stenosis and plaque composition. Conclusions. Significant differences in plaque stress exist between plaques from symptomatic individuals and those from asymptomatic individuals. The MR imaging-based computational analysis may therefore be a useful aid to identification of vulnerable plaques in vivo.

Assessment of inflammatory burden contralateral to the symptomatic carotid stenosis using high-resolution ultrasmall, superparamagnetic iron oxide-enhanced MRI

BACKGROUND AND PURPOSE It is well known that the vulnerable atheromatous plaque has a thin, fibrous cap and large lipid core with associated inflammation. This inflammation can be detected on MRI with use of a contrast medium, Sinerem, an ultrasmall superparamagnetic iron oxide (USPIO). Although the incidence of macrophage activity in asymptomatic disease appears low, we aimed to explore the incidence of MRI-defined inflammation in asymptomatic plaques in patients with known contralateral symptomatic disease. METHODS Twenty symptomatic patients underwent multisequence MRI before and 36 hours after USPIO infusion. Images were manually segmented into quadrants, and the signal change in each quadrant was calculated after USPIO administration. A mixed mathematical model was developed to compare the mean signal change across all quadrants in the 2 groups. Patients had a mean symptomatic stenosis of 77% compared with 46% on their asymptomatic side, as measured by conventional angiography. RESULTS There were 11 (55%) men, and the median age was 72 years (range, 53 to 84 years). All patients had risk factors consistent with severe atherosclerotic disease. All symptomatic carotid stenoses had inflammation, as evaluated by USPIO-enhanced imaging. On the contralateral sides, inflammatory activity was found in 19 (95%) patients. Contralaterally, there were 163 quadrants (57%) with a signal loss after USPIO when compared with 217 quadrants (71%) on the symptomatic side (P=0.007). CONCLUSIONS - This study adds weight to the argument that atherosclerosis is a truly systemic disease. It suggests that investigation of the contralateral side in patients with symptomatic carotid stenosis can demonstrate inflammation in 95% of plaques, despite a mean stenosis of only 46%. Thus, inflammatory activity may be a significant risk factor in asymptomatic disease in patients who have known contralateral symptomatic disease. Patients with symptomatic carotid disease should have their contralateral carotid artery followed up.

The'cave' mineral oxammite: a high resolution thermogravimetry and Raman spectroscopic study

The thermal decomposition of natural ammonium oxalate known as oxammite has been studied using a combination of high resolution thermogravimetry coupled to an evolved gas mass spectrometer and Raman spectroscopy coupled to a thermal stage. Three mass loss steps were found at 57, 175 and 188°C attributed to dehydration, ammonia evolution and carbon dioxide evolution respectively. Raman spectroscopy shows two bands at 3235 and 3030 cm-1 attributed to the OH stretching vibrations and three bands at 2995, 2900 and 2879 cm-1, attributed to the NH vibrational modes. The thermal degradation of oxammite may be followed by the loss of intensity of these bands. No intensity remains in the OH stretching bands at 100°C and the NH stretching bands show no intensity at 200°C. Multiple CO symmetric stretching bands are observed at 1473, 1454, 1447 and 1431cm-1, suggesting that the mineral oxammite is composed of a mixture of chemicals including ammonium oxalate dihydrate, ammonium oxalate monohydrate and anhydrous ammonium oxalate.

Automated road pavement marking detection from high resolution aerial images based on Multi-resolution image analysis and anisotropic Gaussian filtering

Road features extraction from remote sensed imagery has been a long-term topic of great interest within the photogrammetry and remote sensing communities for over three decades. The majority of the early work only focused on linear feature detection approaches, with restrictive assumption on image resolution and road appearance. The widely available of high resolution digital aerial images makes it possible to extract sub-road features, e.g. road pavement markings. In this paper, we will focus on the automatic extraction of road lane markings, which are required by various lane-based vehicle applications, such as, autonomous vehicle navigation, and lane departure warning. The proposed approach consists of three phases: i) road centerline extraction from low resolution image, ii) road surface detection in the original image, and iii) pavement marking extraction on the generated road surface. The proposed method was tested on the aerial imagery dataset of the Bruce Highway, Queensland, and the results demonstrate the efficiency of our approach.

Road network extraction with new vectorization and pruning from high-resolution RS images

With the increasing resolution of remote sensing images, road network can be displayed as continuous and homogeneity regions with a certain width rather than traditional thin lines. Therefore, road network extraction from large scale images refers to reliable road surface detection instead of road line extraction. In this paper, a novel automatic road network detection approach based on the combination of homogram segmentation and mathematical morphology is proposed, which includes three main steps: (i) the image is classified based on homogram segmentation to roughly identify the road network regions; (ii) the morphological opening and closing is employed to fill tiny holes and filter out small road branches; and (iii) the extracted road surface is further thinned by a thinning approach, pruned by a proposed method and finally simplified with Douglas-Peucker algorithm. Lastly, the results from some QuickBird images and aerial photos demonstrate the correctness and efficiency of the proposed process.

Extraction of road lanes from high-resolution stereo aerial imagery based on maximum likelihood segmentation and texture enhancement

Accurate road lane information is crucial for advanced vehicle navigation and safety applications. With the increasing of very high resolution (VHR) imagery of astonishing quality provided by digital airborne sources, it will greatly facilitate the data acquisition and also significantly reduce the cost of data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lanes from aerial images with employment of the image analysis procedures. This algorithm starts with constructing the (Digital Surface Model) DSM and true orthophotos from the stereo images. Next, a maximum likelihood clustering algorithm is used to separate road from other ground objects. After the detection of road surface, the road traffic and lane lines are further detected using texture enhancement and morphological operations. Finally, the generated road network is evaluated to test the performance of the proposed approach, in which the datasets provided by Queensland department of Main Roads are used. The experiment result proves the effectiveness of our approach.

Campylobacter jejuni and campylobacter coli genotyping by high-resolution melting analysis of a flaA fragment

The highly variable flagellin-encoding flaA gene has long been used for genotyping Campylobacter jejuni and Campylobacter coli. High-resolution melting (HRM) analysis is emerging as an efficient and robust method for discriminating DNA sequence variants. The objective of this study was to apply HRM analysis to flaA-based genotyping. The initial aim was to identify a suitable flaA fragment. It was found that the PCR primers commonly used to amplify the flaA short variable repeat (SVR) yielded a mixed PCR product unsuitable for HRM analysis. However, a PCR primer set composed of the upstream primer used to amplify the fragment used for flaA restriction fragment length polymorphism (RFLP) analysis and the downstream primer used for flaA SVR amplification generated a very pure PCR product, and this primer set was used for the remainder of the study. Eighty-seven C. jejuni and 15 C. coli isolates were analyzed by flaA HRM and also partial flaA sequencing. There were 47 flaA sequence variants, and all were resolved by HRM analysis. The isolates used had previously also been genotyped using single-nucleotide polymorphisms (SNPs), binary markers, CRISPR HRM, and flaA RFLP. flaAHRManalysis provided resolving power multiplicative to the SNPs, binary markers, and CRISPR HRM and largely concordant with the flaA RFLP. It was concluded that HRM analysis is a promising approach to genotyping based on highly variable genes.

Wavelet based approaches and high resolution methods for complex process models

Many industrial processes and systems can be modelled mathematically by a set of Partial Differential Equations (PDEs). Finding a solution to such a PDF model is essential for system design, simulation, and process control purpose. However, major difficulties appear when solving PDEs with singularity. Traditional numerical methods, such as finite difference, finite element, and polynomial based orthogonal collocation, not only have limitations to fully capture the process dynamics but also demand enormous computation power due to the large number of elements or mesh points for accommodation of sharp variations. To tackle this challenging problem, wavelet based approaches and high resolution methods have been recently developed with successful applications to a fixedbed adsorption column model. Our investigation has shown that recent advances in wavelet based approaches and high resolution methods have the potential to be adopted for solving more complicated dynamic system models. This chapter will highlight the successful applications of these new methods in solving complex models of simulated-moving-bed (SMB) chromatographic processes. A SMB process is a distributed parameter system and can be mathematically described by a set of partial/ordinary differential equations and algebraic equations. These equations are highly coupled; experience wave propagations with steep front, and require significant numerical effort to solve. To demonstrate the numerical computing power of the wavelet based approaches and high resolution methods, a single column chromatographic process modelled by a Transport-Dispersive-Equilibrium linear model is investigated first. Numerical solutions from the upwind-1 finite difference, wavelet-collocation, and high resolution methods are evaluated by quantitative comparisons with the analytical solution for a range of Peclet numbers. After that, the advantages of the wavelet based approaches and high resolution methods are further demonstrated through applications to a dynamic SMB model for an enantiomers separation process. This research has revealed that for a PDE system with a low Peclet number, all existing numerical methods work well, but the upwind finite difference method consumes the most time for the same degree of accuracy of the numerical solution. The high resolution method provides an accurate numerical solution for a PDE system with a medium Peclet number. The wavelet collocation method is capable of catching up steep changes in the solution, and thus can be used for solving PDE models with high singularity. For the complex SMB system models under consideration, both the wavelet based approaches and high resolution methods are good candidates in terms of computation demand and prediction accuracy on the steep front. The high resolution methods have shown better stability in achieving steady state in the specific case studied in this Chapter.