3D geoelectrical monitoring to follow hydric soil behaviour during rainfall

RESUME Durant les dernières années, les méthodes électriques ont souvent été utilisées pour l'investigation des structures de subsurface. L'imagerie électrique (Electrical Resistivity Tomography, ERT) est une technique de prospection non-invasive et spatialement intégrée. La méthode ERT a subi des améliorations significatives avec le développement de nouveaux algorithmes d'inversion et le perfectionnement des techniques d'acquisition. La technologie multicanale et les ordinateurs de dernière génération permettent la collecte et le traitement de données en quelques heures. Les domaines d'application sont nombreux et divers: géologie et hydrogéologie, génie civil et géotechnique, archéologie et études environnementales. En particulier, les méthodes électriques sont souvent employées dans l'étude hydrologique de la zone vadose. Le but de ce travail est le développement d'un système de monitorage 3D automatique, non- invasif, fiable, peu coûteux, basé sur une technique multicanale et approprié pour suivre les variations de résistivité électrique dans le sous-sol lors d'événements pluvieux. En raison des limitations techniques et afin d'éviter toute perturbation physique dans la subsurface, ce dispositif de mesure emploie une installation non-conventionnelle, où toutes les électrodes de courant sont placées au bord de la zone d'étude. Le dispositif le plus approprié pour suivre les variations verticales et latérales de la résistivité électrique à partir d'une installation permanente a été choisi à l'aide de modélisations numériques. Les résultats démontrent que le dispositif pôle-dipôle offre une meilleure résolution que le dispositif pôle-pôle et plus apte à détecter les variations latérales et verticales de la résistivité électrique, et cela malgré la configuration non-conventionnelle des électrodes. Pour tester l'efficacité du système proposé, des données de terrain ont été collectées sur un site d'étude expérimental. La technique de monitorage utilisée permet de suivre le processus d'infiltration 3D pendant des événements pluvieux. Une bonne corrélation est observée entre les résultats de modélisation numérique et les données de terrain, confirmant par ailleurs que le dispositif pôle-dipôle offre une meilleure résolution que le dispositif pôle-pôle. La nouvelle technique de monitorage 3D de résistivité électrique permet de caractériser les zones d'écoulement préférentiel et de caractériser le rôle de la lithologie et de la pédologie de manière quantitative dans les processus hydrologiques responsables d'écoulement de crue. ABSTRACT During the last years, electrical methods were often used for the investigation of subsurface structures. Electrical resistivity tomography (ERT) has been reported to be a useful non-invasive and spatially integrative prospecting technique. The ERT method provides significant improvements, with the developments of new inversion algorithms, and the increasing efficiency of data collection techniques. Multichannel technology and powerful computers allow collecting and processing resistivity data within few hours. Application domains are numerous and varied: geology and hydrogeology, civil engineering and geotechnics, archaeology and environmental studies. In particular, electrical methods are commonly used in hydrological studies of the vadose zone. The aim of this study was to develop a multichannel, automatic, non-invasive, reliable and inexpensive 3D monitoring system designed to follow electrical resistivity variations in soil during rainfall. Because of technical limitations and in order to not disturb the subsurface, the proposed measurement device uses a non-conventional electrode set-up, where all the current electrodes are located near the edges of the survey grid. Using numerical modelling, the most appropriate arrays were selected to detect vertical and lateral variations of the electrical resistivity in the framework of a permanent surveying installation system. The results show that a pole-dipole array has a better resolution than a pole-pole array and can successfully follow vertical and lateral resistivity variations despite the non-conventional electrode configuration used. Field data are then collected at a test site to assess the efficiency of the proposed monitoring technique. The system allows following the 3D infiltration processes during a rainfall event. A good correlation between the results of numerical modelling and field data results can be observed since the field pole-dipole data give a better resolution image than the pole-pole data. The new device and technique makes it possible to better characterize the zones of preferential flow and to quantify the role of lithology and pedology in flood- generating hydrological processes.

Ammonium accumulation and cell death in a rat 3D brain cell model of glutaric aciduria type I.

Glutaric aciduria type I (glutaryl-CoA dehydrogenase deficiency) is an inborn error of metabolism that usually manifests in infancy by an acute encephalopathic crisis and often results in permanent motor handicap. Biochemical hallmarks of this disease are elevated levels of glutarate and 3-hydroxyglutarate in blood and urine. The neuropathology of this disease is still poorly understood, as low lysine diet and carnitine supplementation do not always prevent brain damage, even in early-treated patients. We used a 3D in vitro model of rat organotypic brain cell cultures in aggregates to mimic glutaric aciduria type I by repeated administration of 1 mM glutarate or 3-hydroxyglutarate at two time points representing different developmental stages. Both metabolites were deleterious for the developing brain cells, with 3-hydroxyglutarate being the most toxic metabolite in our model. Astrocytes were the cells most strongly affected by metabolite exposure. In culture medium, we observed an up to 11-fold increase of ammonium in the culture medium with a concomitant decrease of glutamine. We further observed an increase in lactate and a concomitant decrease in glucose. Exposure to 3-hydroxyglutarate led to a significantly increased cell death rate. Thus, we propose a three step model for brain damage in glutaric aciduria type I: (i) 3-OHGA causes the death of astrocytes, (ii) deficiency of the astrocytic enzyme glutamine synthetase leads to intracerebral ammonium accumulation, and (iii) high ammonium triggers secondary death of other brain cells. These unexpected findings need to be further investigated and verified in vivo. They suggest that intracerebral ammonium accumulation might be an important target for the development of more effective treatment strategies to prevent brain damage in patients with glutaric aciduria type I.

Complex landslide behaviour and structural controlled by the structures: A 3D conceptual model example of Åknes rockslide, Norway

Åknes is an active complex large rockslide of approximately 30?40 Mm3 located within the Proterozoic gneisses of western Norway. The observed surface displacements indicate that this rockslide is divided into several blocks moving in different directions at velocities of between 3 and 10 cm year?1. Because of regional safety issues and economic interests this rockslide has been extensively monitored since 2004. The understanding of the deformation mechanism is crucial for the implementation of a viable monitoring system. Detailed field investigations and the analysis of a digital elevation model (DEM) indicate that the movements and the block geometry are controlled by the main schistosity (S1) in gneisses, folds, joints and regional faults. Such complex slope deformations use pre-existing structures, but also result in new failure surfaces and deformation zones, like preferential rupture in fold-hinge zones. Our interpretation provides a consistent conceptual three-dimensional (3D) model for the movements measured by various methods that is crucial for numerical stability modelling. In addition, this reinterpretation of the morphology confirms that in the past several rockslides occurred from the Åknes slope. They may be related to scars propagating along the vertical foliation in folds hinges. Finally, a model of the evolution of the Åknes slope is presented.

Debris flow susceptibility mapping at a regional scale

Debris flow susceptibility mapping at a regional scale has been the subject of various studies. The complexity of the phenomenon and the variability of local controlling factors limit the use of process-based models for a first assessment. GISbased approaches associating an automatic detection of the source areas and a simple assessment of the debris flow spreading may provide a substantial basis for a preliminary susceptibility assessment at the regional scale. The use of a digital elevation model, with a 10 m resolution, for the Canton de Vaud territory (Switzerland), a lithological map and a land use map, has allowed automatic identification of the potential source areas. The spreading estimates are based on basic probabilistic and energy calculations that allow to define the maximal runout distance of a debris flow.

A Modulated Closed Form solution for Quantitative Susceptibility Mapping - A thorough evaluation and comparison to iterative methods based on edge prior knowledge.

The aim of this study is to perform a thorough comparison of quantitative susceptibility mapping (QSM) techniques and their dependence on the assumptions made. The compared methodologies were: two iterative single orientation methodologies minimizing the l2, l1TV norm of the prior knowledge of the edges of the object, one over-determined multiple orientation method (COSMOS) and anewly proposed modulated closed-form solution (MCF). The performance of these methods was compared using a numerical phantom and in-vivo high resolution (0.65mm isotropic) brain data acquired at 7T using a new coil combination method. For all QSM methods, the relevant regularization and prior-knowledge parameters were systematically changed in order to evaluate the optimal reconstruction in the presence and absence of a ground truth. Additionally, the QSM contrast was compared to conventional gradient recalled echo (GRE) magnitude and R2* maps obtained from the same dataset. The QSM reconstruction results of the single orientation methods show comparable performance. The MCF method has the highest correlation (corrMCF=0.95, r(2)MCF =0.97) with the state of the art method (COSMOS) with additional advantage of extreme fast computation time. The l-curve method gave the visually most satisfactory balance between reduction of streaking artifacts and over-regularization with the latter being overemphasized when the using the COSMOS susceptibility maps as ground-truth. R2* and susceptibility maps, when calculated from the same datasets, although based on distinct features of the data, have a comparable ability to distinguish deep gray matter structures.

DETERMINATION OF CELL-SPECIFIC NEUROTOXICITY OF MALONATE, METHYLMALONATE AND PROPIONATE IN A 3D RAT BRAIN CELL AGGREGATE SYSTEM

Malonate, methylmalonate and propionate are potentially neurotoxic metabolites in branched-chain organic acidurias. Their effects were tested on cultured 3D rat brain cell aggregates, using dosages of 0.1, 1.0 and 10.0 mM with a short but intense (twice a day over 3 days) and a longer but less intense treatment (every 3 rdday over 9 days). CNS cell-specific immunohistochemical stainings allowed the follow-up of neurons (axons, phosphorylated medium-weight neurofilament), astrocytes (glial fibrillary acidic protein) and oligodendrocytes (myelin basic protein). Methylmalonate and malonate were quantified by tandem mass spectrometry. Tandem mass spectrometry analysis of harvested brain cell aggregates revealed clear intracellular accumulation of methylmalonate and malonate. In immunohistochemical stainings oligodendrocytes appeared the most affected brain cells. The MBP signal disappeared already at 0.1 mM treatment with each metabolite. Mature astrocytes were not affected by propionate, while immature astrocytes on intense treatment with propionate developed cell swelling. 1 mM methylmalonate induced cell swelling of both immature and mature astrocytes , while 1 mM malonate only affected mature astrocytes. Neurons were not affected by methylmalonate, but 10.0 mM malonate on less intense treatment and 0.1, 1.0 and 10.0 mM propionate on intense treatment affected axonal growth. Our study shows significant uptake and deleterious effects of these metabolites on brain cells, principally on astrocytes and oligodendrocytes. This may be explained by the absence of the pathway in glial cells, which thus are not able to degrade these metabolites. Further studies are ongoing to elucidate the underlying mechanisms of the observed neurotoxic effects.

3D visualization software to analyze topological outcomes of topoisomerase reactions.

The action of various DNA topoisomerases frequently results in characteristic changes in DNA topology. Important information for understanding mechanistic details of action of these topoisomerases can be provided by investigating the knot types resulting from topoisomerase action on circular DNA forming a particular knot type. Depending on the topological bias of a given topoisomerase reaction, one observes different subsets of knotted products. To establish the character of topological bias, one needs to be aware of all possible topological outcomes of intersegmental passages occurring within a given knot type. However, it is not trivial to systematically enumerate topological outcomes of strand passage from a given knot type. We present here a 3D visualization software (TopoICE-X in KnotPlot) that incorporates topological analysis methods in order to visualize, for example, knots that can be obtained from a given knot by one intersegmental passage. The software has several other options for the topological analysis of mechanisms of action of various topoisomerases.

Advanced mapping of environmental data: Geostatistics, Machine Learning and Bayesian Maximum Entropy

This book combines geostatistics and global mapping systems to present an up-to-the-minute study of environmental data. Featuring numerous case studies, the reference covers model dependent (geostatistics) and data driven (machine learning algorithms) analysis techniques such as risk mapping, conditional stochastic simulations, descriptions of spatial uncertainty and variability, artificial neural networks (ANN) for spatial data, Bayesian maximum entropy (BME), and more.