Monitoring and failure mechanism interpretation of an unstable slope in Southern Switzerland based on terrestrial laser scanner

We present the application of terrestrial laser scanning (TLS) for the monitoring and characterization of an active landslide area in Val Canaria (Ticino, Southern Swiss Alps). At catchment scale, the study area is affected by a large Deep Seated Gravitational Slope Deformation (DSGSD) area presenting, in the lower boundary, several retrogressive landslides active since the 1990s. Due to its frequent landslide events this area was periodically monitored by TLS since 2006. Periodic acquisitions provided new information on 3D displacements at the bottom of slope and the detection of centimetre to decimetre level scale changes (e.g. rockfall and pre-failure deformations). In October 2009, a major slope collapse occured at the bottom of the most unstable area. Based on the comparison between TLS data before and after the collapse, we carried out a detailed failure mechanism analysis and volume calculation.

Development of In Situ Detection Methods for Materials-Related Distress (MRD) in Concrete Pavements: Phase 2, HR-1081, 2005

This project utilized information from ground penetrating radar (GPR) and visual inspection via the pavement profile scanner (PPS) in proof-of-concept trials. GPR tests were carried out on a variety of portland cement concrete pavements and laboratory concrete specimens. Results indicated that the higher frequency GPR antennas were capable of detecting subsurface distress in two of the three pavement sites investigated. However, the GPR systems failed to detect distress in one pavement site that exhibited extensive cracking. Laboratory experiments indicated that moisture conditions in the cracked pavement probably explain the failure. Accurate surveys need to account for moisture in the pavement slab. Importantly, however, once the pavement site exhibits severe surface cracking, there is little need for GPR, which is primarily used to detect distress that is not observed visually. Two visual inspections were also conducted for this study by personnel from Mandli Communications, Inc., and the Iowa Department of Transportation (DOT). The surveys were conducted using an Iowa DOT video log van that Mandli had fitted with additional equipment. The first survey was an extended demonstration of the PPS system. The second survey utilized the PPS with a downward imaging system that provided high-resolution pavement images. Experimental difficulties occurred during both studies; however, enough information was extracted to consider both surveys successful in identifying pavement surface distress. The results obtained from both GPR testing and visual inspections were helpful in identifying sites that exhibited materials-related distress, and both were considered to have passed the proof-of-concept trials. However, neither method can currently diagnose materials-related distress. Both techniques only detected the symptoms of materials-related distress; the actual diagnosis still relied on coring and subsequent petrographic examination. Both technologies are currently in rapid development, and the limitations may be overcome as the technologies advance and mature.

Rockfall detection from LIDAR point clouds: A clustering approach using R

The analysis of rockfall characteristics and spatial distribution is fundamental to understand and model the main factors that predispose to failure. In our study we analysed LiDAR point clouds aiming to: (1) detect and characterise single rockfalls; (2) investigate their spatial distribution. To this end, different cluster algorithms were applied: 1a) Nearest Neighbour Clutter Removal (NNCR) in combination with the Expectation?Maximization (EM) in order to separate feature points from clutter; 1b) a density based algorithm (DBSCAN) was applied to isolate the single clusters (i.e. the rockfall events); 2) finally we computed the Ripley's K-function to investigate the global spatial pattern of the extracted rockfalls. The method allowed proper identification and characterization of more than 600 rockfalls occurred on a cliff located in Puigcercos (Catalonia, Spain) during a time span of six months. The spatial distribution of these events proved that rockfall were clustered distributed at a welldefined distance-range. Computations were carried out using R free software for statistical computing and graphics. The understanding of the spatial distribution of precursory rockfalls may shed light on the forecasting of future failures.

From Regional Landslide Detection to Site-Specific Slope Deformation Monitoring and Modelling Based on Active Remote Sensors

Landslide processes can have direct and indirect consequences affecting human lives and activities. In order to improve landslide risk management procedures, this PhD thesis aims to investigate capabilities of active LiDAR and RaDAR sensors for landslides detection and characterization at regional scales, spatial risk assessment over large areas and slope instabilities monitoring and modelling at site-specific scales. At regional scales, we first demonstrated recent boat-based mobile LiDAR capabilities to model topography of the Normand coastal cliffs. By comparing annual acquisitions, we validated as well our approach to detect surface changes and thus map rock collapses, landslides and toe erosions affecting the shoreline at a county scale. Then, we applied a spaceborne InSAR approach to detect large slope instabilities in Argentina. Based on both phase and amplitude RaDAR signals, we extracted decisive information to detect, characterize and monitor two unknown extremely slow landslides, and to quantify water level variations of an involved close dam reservoir. Finally, advanced investigations on fragmental rockfall risk assessment were conducted along roads of the Val de Bagnes, by improving approaches of the Slope Angle Distribution and the FlowR software. Therefore, both rock-mass-failure susceptibilities and relative frequencies of block propagations were assessed and rockfall hazard and risk maps could be established at the valley scale. At slope-specific scales, in the Swiss Alps, we first integrated ground-based InSAR and terrestrial LiDAR acquisitions to map, monitor and model the Perraire rock slope deformation. By interpreting both methods individually and originally integrated as well, we therefore delimited the rockslide borders, computed volumes and highlighted non-uniform translational displacements along a wedge failure surface. Finally, we studied specific requirements and practical issues experimented on early warning systems of some of the most studied landslides worldwide. As a result, we highlighted valuable key recommendations to design new reliable systems; in addition, we also underlined conceptual issues that must be solved to improve current procedures. To sum up, the diversity of experimented situations brought an extensive experience that revealed the potential and limitations of both methods and highlighted as well the necessity of their complementary and integrated uses.

Detection of Varicosavirus and Ophiovirus in lettuce associated with lettuce big-vein symptoms in Brazil

During surveys undertaken from 1998 to 2003 in the major vegetable growing areas of the city of São Paulo green belt, lettuce (Lactuca sativa) and endive (Cichorium endivia) plants were observed, which showed chlorotic thickening of foliar veins, defective growth and, in some cases, failure to form complete heads. Biological and serological [DAS-Enzyme linked immunosorbent assay (Elisa)] tests together with electron microscope observations, revealed the presence of Lettuce big-vein virus and Mirafiori lettuce virus, in these plants both responsible for the lettuce big-vein syndrome.

Eye Fundus Image Analysis for Automatic Detection of Diabetic Retinopathy

Diabetes is a rapidly increasing worldwide problem which is characterised by defective metabolism of glucose that causes long-term dysfunction and failure of various organs. The most common complication of diabetes is diabetic retinopathy (DR), which is one of the primary causes of blindness and visual impairment in adults. The rapid increase of diabetes pushes the limits of the current DR screening capabilities for which the digital imaging of the eye fundus (retinal imaging), and automatic or semi-automatic image analysis algorithms provide a potential solution. In this work, the use of colour in the detection of diabetic retinopathy is statistically studied using a supervised algorithm based on one-class classification and Gaussian mixture model estimation. The presented algorithm distinguishes a certain diabetic lesion type from all other possible objects in eye fundus images by only estimating the probability density function of that certain lesion type. For the training and ground truth estimation, the algorithm combines manual annotations of several experts for which the best practices were experimentally selected. By assessing the algorithm’s performance while conducting experiments with the colour space selection, both illuminance and colour correction, and background class information, the use of colour in the detection of diabetic retinopathy was quantitatively evaluated. Another contribution of this work is the benchmarking framework for eye fundus image analysis algorithms needed for the development of the automatic DR detection algorithms. The benchmarking framework provides guidelines on how to construct a benchmarking database that comprises true patient images, ground truth, and an evaluation protocol. The evaluation is based on the standard receiver operating characteristics analysis and it follows the medical practice in the decision making providing protocols for image- and pixel-based evaluations. During the work, two public medical image databases with ground truth were published: DIARETDB0 and DIARETDB1. The framework, DR databases and the final algorithm, are made public in the web to set the baseline results for automatic detection of diabetic retinopathy. Although deviating from the general context of the thesis, a simple and effective optic disc localisation method is presented. The optic disc localisation is discussed, since normal eye fundus structures are fundamental in the characterisation of DR.

Head-to-head comparison of dipyridamole, dobutamine and pacing stress echocardiography for the detection of myocardial ischemia in an animal model of coronary artery stenosis

To compare the sensitivity of dipyridamole, dobutamine and pacing stress echocardiography for the detection of myocardial ischemia we produced a physiologically significant stenosis in the left circumflex artery of 14 open-chest dogs (range: 50 to 89% reduction in luminal diameter). In each study, dobutamine (5 to 40 µg kg-1 min-1 in 3-min stages) and pacing (20 bpm increments, each 2 min, up to 260 bpm) were performed randomly, and then followed by dipyridamole (up to 0.84 mg/kg over 10 min). The positivity of stress echocardiography tests was quantitatively determined by a significant (P<0.05) reduction of or failure to increase absolute and percent systolic wall thickening in the stenotic artery supplied wall, as compared to the opposite wall (areas related to the left anterior descending artery). Systolic and diastolic frozen images were analyzed off-line by two blinded observers in the control and stress conditions. The results showed that 1) the sensitivity of dobutamine, dipyridamole and pacing stress tests was 57, 57 and 36%, respectively; 2) in animals with positive tests, the mean percent change of wall thickening in left ventricular ischemic segments was larger in the pacing (-19 ± 11%) and dipyridamole (-18 ± 16%) tests as compared to dobutamine (-9 ± 6%) (P = 0.05), but a similar mean reduction of wall thickening was observed when this variable was normalized to a control left ventricular segment (area related to the left anterior descending artery) (pacing: -16 ± 7%; dipyridamole: -25 ± 16%; dobutamine: -26 ± 10%; not significant), and 3) a significant correlation was observed between magnitude of coronary stenosis and left ventricular segmental dysfunction induced by ischemia in dogs submitted to positive stress tests. We conclude that the dobutamine and dipyridamole stress tests showed identical sensitivities for the detection of myocardial ischemia in this one-vessel disease animal model with a wide range of left circumflex artery stenosis. The pacing stress test was less sensitive, but the difference was not statistically significant. The magnitude of segmental left ventricular dysfunction induced by ischemia was similar in all stress tests evaluated.

Detection of multiple mycoplasma infection in cell cultures by PCR

A total of 301 cell cultures from 15 laboratories were monitored for mycoplasma (Mollicutes) using PCR and culture methodology. The infection was detected in the cell culture collection of 12 laboratories. PCR for Mollicutes detected these bacteria in 93 (30.9%) samples. Although the infection was confirmed by culture for 69 (22.9%) samples, PCR with generic primers did not detect the infection in five (5.4%). Mycoplasma species were identified with specific primers in 91 (30.2%) of the 98 samples (32.6%) considered to be infected. Mycoplasma hyorhinis was detected in 63.3% of the infected samples, M. arginini in 59.2%, Acholeplasma laidlawii in 20.4%, M. fermentans in 14.3%, M. orale in 11.2%, and M. salivarium in 8.2%. Sixty (61.2%) samples were co-infected with more than one mycoplasma species. M. hyorhinis and M. arginini were the microorganisms most frequently found in combination, having been detected in 30 (30.6%) samples and other associations including up to four species were detected in 30 other samples. Failure of the treatments used to eliminate mycoplasmas from cell cultures might be explained by the occurrence of these multiple infections. The present results indicate that the sharing of non-certified cells among laboratories may disseminate mycoplasma in cell cultures.

Simultaneous detection of the C282Y, H63D and S65C mutations in the hemochromatosis gene using quenched-FRET real-time PCR

Hereditary hemochromatosis (HH) is a common autosomal disorder of iron metabolism mainly affecting Caucasian populations. Three recurrent disease-associated mutations have been detected in the hemochromatosis gene (HFE): C282Y, H63D, and S65C. Although HH phenotype has been associated with all three mutations, C282Y is considered the most relevant mutation responsible for hemochromatosis. Clinical complications of HH include cirrhosis of the liver, congestive cardiac failure and cardiac arrhythmias, endocrine pancreatic disease, which can be prevented by early diagnosis and treatment. Therefore, a reliable genotyping method is required for presymptomatic diagnosis. We describe the simultaneous detection of the C282Y, H63D and S65C mutations in the hemochromatosis gene by real-time PCR followed by melting curve analysis using fluorescence resonance energy transfer (FRET) probes. The acceptor fluorophore may be replaced by a quencher, increasing multiplex possibilities. Real-time PCR results were compared to the results of sequencing and conventional PCR followed by restriction digestion and detection by agarose gel electrophoresis (PCR-RFLP). Genotypes from 80 individuals obtained both by the conventional PCR-RFLP method and quenched-FRET real-time PCR were in full agreement. Sequencing also confirmed the results obtained by the new method, which proved to be an accurate, rapid and cost-effective diagnostic assay. Our findings demonstrate the usefulness of real-time PCR for the simultaneous detection of mutations in the HFE gene, which allows a reduction of a significant amount of time in sample processing compared to the PCR-RFLP method, eliminates the use of toxic reagents, reduces the risk of contamination in the laboratory, and enables full process automation.

Doppler vortography : detection and quantification of the vortices in the left ventricle

Nous proposons une nouvelle méthode pour quantifier la vorticité intracardiaque (vortographie Doppler), basée sur l’imagerie Doppler conventionnelle. Afin de caractériser les vortex, nous utilisons un indice dénommé « Blood Vortex Signature (BVS) » (Signature Tourbillonnaire Sanguine) obtenu par l’application d’un filtre par noyau basé sur la covariance. La validation de l’indice BVS mesuré par vortographie Doppler a été réalisée à partir de champs Doppler issus de simulations et d’expériences in vitro. Des résultats préliminaires obtenus chez des sujets sains et des patients atteints de complications cardiaques sont également présentés dans ce mémoire. Des corrélations significatives ont été observées entre la vorticité estimée par vortographie Doppler et la méthode de référence (in silico: r2 = 0.98, in vitro: r2 = 0.86). Nos résultats suggèrent que la vortographie Doppler est une technique d’échographie cardiaque prometteuse pour quantifier les vortex intracardiaques. Cet outil d’évaluation pourrait être aisément appliqué en routine clinique pour détecter la présence d’une insuffisance ventriculaire et évaluer la fonction diastolique par échocardiographie Doppler.

Antibody Based Diagnostic for Detection Of Vibrios and their Biological Control using Antagonistic Bacteria in Macrobrachium Rosenbergii Larval Rearing Systems

The main objective of the work undertaken here was to develop an appropriate microbial technology to protect the larvae of M.rosenbergii in hatchery from vibriosis. This technology precisely is consisted of a rapid detection system of vibrios and effective antagonistic probiotics for the management of vibrios. The present work was undertaken with the realizations that to stabilize the production process of commercial hatcheries an appropriate, comprehensive and fool proof technology is required primarily for the rapid detection of Vibrio and subsequently for its management. Nine species of Vibrio have been found to be associated with larvae of M. rosenbergii in hatchery. Haemolytic assay of the Vibrio and Aeromonas on prawn blood agar showed that all isolates of V. alginolyticus and Aeromonas sp., from moribund, necrotized larve were haemolytic and the isolates of V.cholerae, V.splendidus II, V.proteolyticus and V.fluvialis from the larvae obtained from apparently healthy larval rearing systems were non-haemolytic. Hydrolytic enzymes such as lipase, chitinase and gelatinase were widespread amongst the Vibrio and Aeromonas isolates. Dominance of V.alginolyticus among the isolates from necrotic larvae and the failure in isolating them from rearing water strongly suggest that they infect larvae and multiply in the larval body and cause mortality in the hatchery. The observation suggested that the isolate V. alginolyticus was a pathogen to the larvae of M.rosenbergii. To sum up, through this work, nine species of Vibrio and genus Aeromonas associated with M.rosenbergii larval rearing systems could be isolated and segregated based on the haemolytic activity and the antibodies (PA bs) for use in diagnosis or epidemiological studies could be produced, based on a virulent culture of V.alginolyticus. This could possibly replace the conventional biochemical tests for identification. As prophylaxis to vibriosis, four isolates of Micrococcus spp. and an isolate of Pseudomonas sp. could be obtained which could possibly be used as antagonistic probiotics in the larval rearing system of M.rosenbergii.

Detection of faults in a high speed packaging machine using a multilayer perceptron (MLP)

In high speed manufacturing systems, continuous operation is desirable, with minimal disruption for repairs and service. An intelligent diagnostic monitoring system, designed to detect developing faults before catastrophic failure, or prior to undesirable reduction in output quality, is a good means of achieving this. Artificial neural networks have already been found to be of value in fault diagnosis of machinery. The aim here is to provide a system capable of detecting a number of faults, in order that maintenance can be scheduled in advance of sudden failure, and to reduce the necessity to replace parts at intervals based on mean time between failures. Instead, parts will need to be replaced only when necessary. Analysis of control information in the form of position error data from two servomotors is described.

DGGE with genomic DNA: Suitable for detection of numerically important organisms but not for identification of the most abundant organisms

Identification of all important community members as well as of the numerically dominant members of a community are key aspects of microbial community analysis of bioreactor samples. A systematic study was conducted with artificial consortia to test whether denaturing gradient gel electrophoresis (DGCE) is a reliable technique to obtain such community data under conditions where results would not be affected by differences in DNA extraction efficiency from cells. A total of 27 consortia were established by mixing DNA extracted from Escherichia coli K12, Burkholderia cepacia and Stenotrophomonas maltophilia in different proportions. Concentrations of DNA of single organisms in the consortia were either 0.04, 0.4 or 4 ng/mu l. DGGE-PCR of genomic DNA with primer sets targeted at the V3 and V6-V8 regions of the 16S rDNA failed to detect the three community members in only 7% of consortia, but provided incorrect information about dominance or co-dominance for 85% and 89% of consortia with the primer sets for the V6-V8 and V3 regions, respectively. The high failure rate in detection of dominant B. cepacia with the primers for the V6-V8 region was attributable to a single nucleoticle primer mismatch in the target sequences of both, the forward and reverse primer. Amplification bias in PCR of E. coli and S. maltophilia for the V6-V8 region and for all three organisms for the V3 region occurred due to interference of genomic DNA in PCR-DGGE, since a nested PCR approach, where PCR-DGGE was started from mixtures of 16S rRNA genes of the organisms, provided correct information about the relative abundance of original DNA in the sample. Multiple bands were not observed in pure culture amplicons produced with the V6-V8 primer pair, but pure culture V3 DGGE profiles of E. coli, S. maltophilia and B. cepacia contained 5, 3 and 3 bands, respectively. These results demonstrate DGGE was suitable for identification of all important community members in the three-membered artificial consortium, but not for identification of the dominant organisms in this small community. Multiple DGGE bands obtained for single organisms with the V3 primer pair could greatly confound interpretation of DGGE profiles. (C) 2008 Elsevier Ltd. All rights reserved.

Non-destructive evaluation tool for monitoring and detection of structural damage by using neural network.

This work studies the capability of generalization of Neural Network using vibration based measurement data aiming at operating condition and health monitoring of mechanical systems. The procedure uses the backpropagation algorithm to classify the input patters of a system with different stiffness ratios. It has been investigated a large set of input data, containing various stiffness ratios as well as a reduced set containing only the extreme ones in order to study generalizing capability of the network. This allows to definition of Neural Networks capable to use a reduced set of data during the training phase. Once it is successfully trained, it could identify intermediate failure condition. Several conditions and intensities of damages have been studied by using numerical data. The Neural Network demonstrated a good capacity of generalization for all case. Finally, the proposal was tested with experimental data.

Detection of porcine circovirus genotypes 2a and 2b in aborted foetuses from infected swine herds in the State of São Paulo, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)