886 resultados para Surface-based deformationsMesh deformationsDiscrete ElasticaPython


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Surface based measurements systems play a key role in defining the ground truth for climate modeling and satellite product validation. The Italian-French station of Concordia is operative year round since 2005 at Dome C (75°S, 123°E, 3230 m) on the East Antarctic Plateau. A Baseline Surface Radiation Network (BSRN) site was deployed and became operational since January 2006 to measure downwelling components of the radiation budget, and successively was expanded in April 2007 to measure upwelling radiation. Hence, almost a decade of measurement is now available and suitable to define a statistically significant climatology for the radiation budget of Concordia including eventual trends, by specifically assessing the effects of clouds and water vapor on SW and LW net radiation. A well known and robust clear sky-id algorithm (Long and Ackerman, 2000) has been operationally applied on downwelling SW components to identify cloud free events and to fit a parametric equation to determine clear-sky reference along the Antarctic daylight periods (September to April). A new model for surface broadband albedo has been developed in order to better describe the features the area. Then, a novel clear-sky LW parametrization, based on a-priori assumption about inversion layer structure, combined with daily and annual oscillations of the surface temperature, have been adopted and validated. The longwave based method is successively exploited to extend cloud radiative forcing studies to nighttime period (winter). Results indicated inter-annual and intra-annual warming behaviour, i.e. 13.70 W/m2 on the average, specifically approaching neutral effect in summer, when SW CRF compensates LW CRF, and warming along the rest of the year due prevalentely to CRF induced on the LW component.

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Purpose Accurate three-dimensional (3D) models of lumbar vertebrae can enable image-based 3D kinematic analysis. The common approach to derive 3D models is by direct segmentation of CT or MRI datasets. However, these have the disadvantages that they are expensive, timeconsuming and/or induce high-radiation doses to the patient. In this study, we present a technique to automatically reconstruct a scaled 3D lumbar vertebral model from a single two-dimensional (2D) lateral fluoroscopic image. Methods Our technique is based on a hybrid 2D/3D deformable registration strategy combining a landmark-to-ray registration with a statistical shape model-based 2D/3D reconstruction scheme. Fig. 1 shows different stages of the reconstruction process. Four cadaveric lumbar spine segments (total twelve lumbar vertebrae) were used to validate the technique. To evaluate the reconstruction accuracy, the surface models reconstructed from the lateral fluoroscopic images were compared to the associated ground truth data derived from a 3D CT-scan reconstruction technique. For each case, a surface-based matching was first used to recover the scale and the rigid transformation between the reconstructed surface model Results Our technique could successfully reconstruct 3D surface models of all twelve vertebrae. After recovering the scale and the rigid transformation between the reconstructed surface models and the ground truth models, the average error of the 2D/3D surface model reconstruction over the twelve lumbar vertebrae was found to be 1.0 mm. The errors of reconstructing surface models of all twelve vertebrae are shown in Fig. 2. It was found that the mean errors of the reconstructed surface models in comparison to their associated ground truths after iterative scaled rigid registrations ranged from 0.7 mm to 1.3 mm and the rootmean squared (RMS) errors ranged from 1.0 mm to 1.7 mm. The average mean reconstruction error was found to be 1.0 mm. Conclusion An accurate, scaled 3D reconstruction of the lumbar vertebra can be obtained from a single lateral fluoroscopic image using a statistical shape model based 2D/3D reconstruction technique. Future work will focus on applying the reconstructed model for 3D kinematic analysis of lumbar vertebrae, an extension of our previously-reported imagebased kinematic analysis. The developed method also has potential applications in surgical planning and navigation.

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Seventeen bones (sixteen cadaveric bones and one plastic bone) were used to validate a method for reconstructing a surface model of the proximal femur from 2D X-ray radiographs and a statistical shape model that was constructed from thirty training surface models. Unlike previously introduced validation studies, where surface-based distance errors were used to evaluate the reconstruction accuracy, here we propose to use errors measured based on clinically relevant morphometric parameters. For this purpose, a program was developed to robustly extract those morphometric parameters from the thirty training surface models (training population), from the seventeen surface models reconstructed from X-ray radiographs, and from the seventeen ground truth surface models obtained either by a CT-scan reconstruction method or by a laser-scan reconstruction method. A statistical analysis was then performed to classify the seventeen test bones into two categories: normal cases and outliers. This classification step depends on the measured parameters of the particular test bone. In case all parameters of a test bone were covered by the training population's parameter ranges, this bone is classified as normal bone, otherwise as outlier bone. Our experimental results showed that statistically there was no significant difference between the morphometric parameters extracted from the reconstructed surface models of the normal cases and those extracted from the reconstructed surface models of the outliers. Therefore, our statistical shape model based reconstruction technique can be used to reconstruct not only the surface model of a normal bone but also that of an outlier bone.

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So far, no experimental data of the infrared and Raman spectra of 13C isotopologue of dimethyl ether are available. With the aim of providing some clues of its low-lying vibrational bands and with the hope of contributing in a next spectral analysis, a number of vibrational transition frequencies below 300 cm−1 of the infrared spectrum and around 400 cm−1 of the Raman spectrum have been predicted and their assignments were proposed. Calculations were carried out through an ab initio three dimensional potential energy surface based on a previously reported one for the most abundant dimethyl ether isotopologue (M. Villa et al., J. Phys. Chem. A 115 (2011) 13573). The potential function was vibrationally corrected and computed with a highly correlated CCSD(T) method involving the COC bending angle and the two large amplitude CH3 internal rotation degrees of freedom. Also, the Hamiltonian parameters could represent a support for the spectral characterization of this species. Although the computed vibrational term values are expected to be very accurate, an empirical adjustment of the Hamiltonian has been performed with the purpose of anticipating some workable corrections to any possible divergence of the vibrational frequencies. Also, the symmetry breaking derived from the isotopic substitution of 13C in the dimethyl ether was taken into account when the symmetrization procedure was applied.

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During the period from 2011 - 2015 with the aim of this study was to systematically review and in particular the revised classification of the Persian Gulf (and the Strait of Hormuz) and to obtain new information about the final confirmed list of fish species of Iranian waters of the Persian Gulf (and Hormuz Strait), samples of museums, surveys and sampling, and comparative study of all available sources and documentation was done. Classification systematic of sharks and batoids and bony fishes. Based on the results, the final list of approved fish of the Persian Gulf (including the Strait of Hormuz and Gulf of Oman border region) are 907 species in 157 families, of which 93 species of fish with 28 cartilaginous families (including 18 families with 60 species and 10 families with 34 species of shark and batoids); and 129 families with 814 species of bony fishes are. The presence of 11 new family with only one representative species in the area include Veliferidae, Zeidae, Sebastidae, Stomiidae, Dalatiidae, Zanclidae, Pempheridae, Lophiidae Kuhliidae, Etmoptridae and Chlorophthalmidae also recently introduced and approved. The two families based Creediidae Clinidae and their larvae samples for newly identified area. 62 families with mono-species and 25 families with more than 10 species are present including Gobiidae (53), Carangide (48), Labride (41), Blenniidae (34), Apogonidae (32) and Lutjanidae (31) of bony fishes, Carcharhinidae (26) of sharks and Dasyatidae (12) in terms of number of species of batoids most families to have their data partitioning. Also, 13 species as well as endemic species introduced the Persian Gulf and have been approved in terms of geographical expansion of the Persian Gulf are unique to the area.Two species of the family Poeciliidae and Cyprinodontidae have species of fresh water to the brackish coastal habitats have found a way;in addition to 11 types of families Carcharhinidae, Clupeidae, Chanidae, Gobidae, Mugilidae, Sparidae also as a species, with a focus on freshwater river basins in the south of the country have been found. In this study, it was found that out of 907 species have been reported from the study area, 294 species (32.4 %) to benthic habitats (Benthic habitats) and 613 species (67.6 %) in pelagic habitats (Pelagic habitats) belong. Coral reefs and rocky habitats in the range of benthic fish (129 species - 14.3 %) and reef associated fishes in the range of pelagic fishes (432 species – 47.8 %), the highest number and percentage of habitat diversity (Species habitats) have been allocated. As well as fish habitats with sea grass and algae beds in benthic habitat (17 species- 1.9 %) and pelagic - Oceanic (Open sea) in the whole pelagic fish (30 species – 3.3 %), the lowest number and percentage of habitat diversity into account. From the perspective of animal geography (Zoogeography) and habitat overlaps and similarities (Habitat overlapping) fish fauna of the Persian Gulf compared with other similar seas (tropical and subtropical, and warm temperate) in the Indian Ocean area - calm on the surface, based on the presence of certain species that the fish fauna of the Persian Gulf to the Red Sea and the Bay of Bengal (East Arabian Sea) compared to other regions in the Indian Ocean (Pacific) is closer (about 50%), and the Mediterranean (East area) and The Hawaiian Islands have the lowest overlap and similarity of habitat and species (about 10%).

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The objective of this study was to determine the best performance of an anaerobic sequencing batch biofilm reactor (AnSBBR) based on the use of four different bed materials as support for biomass immobilization. The bed materials utilized were Polyurethane foam (PU), vegetal carbon (VC), synthetic pumice (SP), and recycled low-density polyethylene (PE). The AnSBBR. with I total volume Of 7.2 L, was operated in 8-h batch cycles over 10 months, and fed with domestic sewage with an average influent chemical oxygen demand (COD) of 358 +/- 110 mg/L. The average effluent COD values were 121 +/- 31, 208 +/- 54, 233 +/- 52, and 227 +/- 51 mg/L. for PU, VC, SP, and PE, respectively. A modified first-order kinetic model was adjusted to temporal profiles of COD during a batch cycle, and the apparent kinetic constants were 0.52 +/- 0.05, 0.37 +/- 0.05, 0.80 +/- 0.04, and 0.30 +/- 0.021h(-1) for PU, VC, SP, and PE, respectively. Specific substrate utilization rates of 1.08, 0.11, and 0.86 mg COD/mg VS day were obtained for PU, VC, and PE, respectively. Although SP yielded the highest kinetic coefficient, PU was considered the best support, since SP presented loss of chemical constituents during the reactor`s operational phase. In addition, findings oil the microbial community were associated with the reactor`s performance data. Although PE did not show a satisfactory performance, an interesting microbial diversity was found oil its surface. Based oil the morphology and denaturing gradient gel electrophoresis (DGGE) results, PE showed the best capacity for promoting the attachment of methanogenic organisms, and is therefore a material that merits further analysis. PU was considered the Most suitable material showing the best performance in terms of efficiency of solids and COD removal. (C) 2007 Elsevier Ltd. All rights reserved.

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This paper presents observations of summertime anti-winds monitored under ideal conditions in the Lake Tekapo hydro-catchment situated in the central Southern Alps, New Zealand. Onset and cessation of anti-winds was observed to coincide with the change in phase of the surface limbs of thermally generated valley and mountain winds under settled anti-cyclonic conditions. Anti-winds were best developed in the early morning before surface heating and associated convective mixing of the valley atmosphere began to mask the boundaries between the surface based limb of the mountain-valley wind and the corresponding anti-wind. By mid-day, the anti-valley wind exceeded the height of the surrounding ridgeline and became embedded in the topographically channeled gradient wind. Observations presented here have both theoretical and applied implications with regard to the development of thermally generated wind systems in deep alpine valleys, and their role in the dispersion of air pollution.

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OBJECTIVE To examine cortical thickness and volumetric changes in the cortex of patients with polymicrogyria, using an automated image analysis algorithm. METHODS Cortical thickness of patients with polymicrogyria was measured using magnetic resonance imaging (MRI) cortical surface-based analysis and compared with age-and sex-matched healthy subjects. We studied 3 patients with disorder of cortical development (DCD), classified as polymicrogyria, and 15 controls. Two experienced neuroradiologists performed a conventional visual assessment of the MRIs. The same data were analyzed using an automated algorithm for tissue segmentation and classification. Group and individual average maps of cortical thickness differences were produced by cortical surface-based statistical analysis. RESULTS Patients with polymicrogyria showed increased thickness of the cortex in the same areas identified as abnormal by radiologists. We also identified a reduction in the volume and thickness of cortex within additional areas of apparently normal cortex relative to controls. CONCLUSIONS Our findings indicate that there may be regions of reduced cortical thickness, which appear normal from radiological analysis, in the cortex of patients with polymicrogyria. This finding suggests that alterations in neuronal migration may have an impact in the cortical formation of the cortical areas that are visually normal. These areas are associated or occur concurrently with polymicrogyria.

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Declarative memory impairments are common in patients with bipolar illness, suggesting underlying hippocampal pathology. However, hippocampal volume deficits are rarely observed in bipolar disorder. Here we used surface-based anatomic mapping to examine hippocampal anatomy in bipolar patients treated with lithium relative to matched control subjects and unmedicated patients with bipolar disorder. High-resolution brain magnetic resonance images were acquired from 33 patients with bipolar disorder ( 21 treated with lithium and 12 unmedicated), and 62 demographically matched healthy control subjects. Three-dimensional parametric mesh models were created from manual tracings of the hippocampal formation. Total hippocampal volume was significantly larger in lithium-treated bipolar patients compared with healthy controls (by 10.3%; p=0.001) and unmedicated bipolar patients ( by 13.9%; p=0.003). Statistical mapping results, confirmed by permutation testing, revealed localized deficits in the right hippocampus, in regions corresponding primarily to cornu ammonis vertical bar subfields, in unmedicated bipolar patients, as compared to both normal controls (p=0.01), and in lithium-treated bipolar patients (p=0.03). These findings demonstrate the sensitivity of these anatomic mapping methods for detecting subtle alterations in hippocampal structure in bipolar disorder. The observed reduction in subregions of the hippocampus in unmedicated bipolar patients suggests a possible neural correlate for memory deficits frequently reported in this illness. Moreover, increased hippocampal volume in lithium-treated bipolar patients may reflect postulated neurotrophic effects of this agent, a possibility warranting further study in longitudinal investigations.

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The use of human brain tissue obtained at autopsy for neurochemical, pharmacological and physiological analyses is reviewed. RNA and protein samples have been found suitable for expression profiling by techniques that include RT-PCR, cDNA microarrays, western blotting, immunohistochemistry and proteomics. The rapid development of molecular biological techniques has increased the impetus for this work to be applied to studies of brain disease. It has been shown that most nucleic acids and proteins are reasonably stable post-mortem. However, their abundance and integrity can exhibit marked intra- and intercase variability, making comparisons between case-groups difficult. Variability can reveal important functional and biochemical information. The correct interpretation of neurochemical data must take into account such factors as age, gender, ethnicity, medicative history, immediate ante-mortem status, agonal state and post-mortem and post-autopsy intervals. Here we consider issues associated with the sampling of DNA, RNA and proteins using human autopsy brain tissue in relation to various ante- and post-mortem factors. We conclude that valid and practical measures of a variety of parameters may be made in human brain tissue, provided that specific factors are controlled.

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In 1903, the eastern slope of Turtle Mountain (Alberta) was affected by a 30 M m3-rockslide named Frank Slide that resulted in more than 70 casualties. Assuming that the main discontinuity sets, including bedding, control part of the slope morphology, the structural features of Turtle Mountain were investigated using a digital elevation model (DEM). Using new landscape analysis techniques, we have identified three main joint and fault sets. These results are in agreement with those sets identified through field observations. Landscape analysis techniques, using a DEM, confirm and refine the most recent geology model of the Frank Slide. The rockslide was initiated along bedding and a fault at the base of the slope and propagated up slope by a regressive process following a surface composed of pre-existing discontinuities. The DEM analysis also permits the identification of important geological structures along the 1903 slide scar. Based on the so called Sloping Local Base Level (SLBL) an estimation was made of the present unstable volumes in the main scar delimited by the cracks, and around the south area of the scar (South Peak). The SLBL is a method permitting a geometric interpretation of the failure surface based on a DEM. Finally we propose a failure mechanism permitting the progressive failure of the rock mass that considers gentle dipping wedges (30°). The prisms or wedges defined by two discontinuity sets permit the creation of a failure surface by progressive failure. Such structures are more commonly observed in recent rockslides. This method is efficient and is recommended as a preliminary analysis prior to field investigation.

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Des progrès significatifs ont été réalisés dans le domaine de l'intégration quantitative des données géophysique et hydrologique l'échelle locale. Cependant, l'extension à de plus grandes échelles des approches correspondantes constitue encore un défi majeur. Il est néanmoins extrêmement important de relever ce défi pour développer des modèles fiables de flux des eaux souterraines et de transport de contaminant. Pour résoudre ce problème, j'ai développé une technique d'intégration des données hydrogéophysiques basée sur une procédure bayésienne de simulation séquentielle en deux étapes. Cette procédure vise des problèmes à plus grande échelle. L'objectif est de simuler la distribution d'un paramètre hydraulique cible à partir, d'une part, de mesures d'un paramètre géophysique pertinent qui couvrent l'espace de manière exhaustive, mais avec une faible résolution (spatiale) et, d'autre part, de mesures locales de très haute résolution des mêmes paramètres géophysique et hydraulique. Pour cela, mon algorithme lie dans un premier temps les données géophysiques de faible et de haute résolution à travers une procédure de réduction déchelle. Les données géophysiques régionales réduites sont ensuite reliées au champ du paramètre hydraulique à haute résolution. J'illustre d'abord l'application de cette nouvelle approche dintégration des données à une base de données synthétiques réaliste. Celle-ci est constituée de mesures de conductivité hydraulique et électrique de haute résolution réalisées dans les mêmes forages ainsi que destimations des conductivités électriques obtenues à partir de mesures de tomographic de résistivité électrique (ERT) sur l'ensemble de l'espace. Ces dernières mesures ont une faible résolution spatiale. La viabilité globale de cette méthode est testée en effectuant les simulations de flux et de transport au travers du modèle original du champ de conductivité hydraulique ainsi que du modèle simulé. Les simulations sont alors comparées. Les résultats obtenus indiquent que la procédure dintégration des données proposée permet d'obtenir des estimations de la conductivité en adéquation avec la structure à grande échelle ainsi que des predictions fiables des caractéristiques de transports sur des distances de moyenne à grande échelle. Les résultats correspondant au scénario de terrain indiquent que l'approche d'intégration des données nouvellement mise au point est capable d'appréhender correctement les hétérogénéitées à petite échelle aussi bien que les tendances à gande échelle du champ hydraulique prévalent. Les résultats montrent également une flexibilté remarquable et une robustesse de cette nouvelle approche dintégration des données. De ce fait, elle est susceptible d'être appliquée à un large éventail de données géophysiques et hydrologiques, à toutes les gammes déchelles. Dans la deuxième partie de ma thèse, j'évalue en détail la viabilité du réechantillonnage geostatique séquentiel comme mécanisme de proposition pour les méthodes Markov Chain Monte Carlo (MCMC) appliquées à des probmes inverses géophysiques et hydrologiques de grande dimension . L'objectif est de permettre une quantification plus précise et plus réaliste des incertitudes associées aux modèles obtenus. En considérant une série dexemples de tomographic radar puits à puits, j'étudie deux classes de stratégies de rééchantillonnage spatial en considérant leur habilité à générer efficacement et précisément des réalisations de la distribution postérieure bayésienne. Les résultats obtenus montrent que, malgré sa popularité, le réechantillonnage séquentiel est plutôt inefficace à générer des échantillons postérieurs indépendants pour des études de cas synthétiques réalistes, notamment pour le cas assez communs et importants où il existe de fortes corrélations spatiales entre le modèle et les paramètres. Pour résoudre ce problème, j'ai développé un nouvelle approche de perturbation basée sur une déformation progressive. Cette approche est flexible en ce qui concerne le nombre de paramètres du modèle et lintensité de la perturbation. Par rapport au rééchantillonage séquentiel, cette nouvelle approche s'avère être très efficace pour diminuer le nombre requis d'itérations pour générer des échantillons indépendants à partir de la distribution postérieure bayésienne. - Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending corresponding approaches beyond the local scale still represents a major challenge, yet is critically important for the development of reliable groundwater flow and contaminant transport models. To address this issue, I have developed a hydrogeophysical data integration technique based on a two-step Bayesian sequential simulation procedure that is specifically targeted towards larger-scale problems. The objective is to simulate the distribution of a target hydraulic parameter based on spatially exhaustive, but poorly resolved, measurements of a pertinent geophysical parameter and locally highly resolved, but spatially sparse, measurements of the considered geophysical and hydraulic parameters. To this end, my algorithm links the low- and high-resolution geophysical data via a downscaling procedure before relating the downscaled regional-scale geophysical data to the high-resolution hydraulic parameter field. I first illustrate the application of this novel data integration approach to a realistic synthetic database consisting of collocated high-resolution borehole measurements of the hydraulic and electrical conductivities and spatially exhaustive, low-resolution electrical conductivity estimates obtained from electrical resistivity tomography (ERT). The overall viability of this method is tested and verified by performing and comparing flow and transport simulations through the original and simulated hydraulic conductivity fields. The corresponding results indicate that the proposed data integration procedure does indeed allow for obtaining faithful estimates of the larger-scale hydraulic conductivity structure and reliable predictions of the transport characteristics over medium- to regional-scale distances. The approach is then applied to a corresponding field scenario consisting of collocated high- resolution measurements of the electrical conductivity, as measured using a cone penetrometer testing (CPT) system, and the hydraulic conductivity, as estimated from electromagnetic flowmeter and slug test measurements, in combination with spatially exhaustive low-resolution electrical conductivity estimates obtained from surface-based electrical resistivity tomography (ERT). The corresponding results indicate that the newly developed data integration approach is indeed capable of adequately capturing both the small-scale heterogeneity as well as the larger-scale trend of the prevailing hydraulic conductivity field. The results also indicate that this novel data integration approach is remarkably flexible and robust and hence can be expected to be applicable to a wide range of geophysical and hydrological data at all scale ranges. In the second part of my thesis, I evaluate in detail the viability of sequential geostatistical resampling as a proposal mechanism for Markov Chain Monte Carlo (MCMC) methods applied to high-dimensional geophysical and hydrological inverse problems in order to allow for a more accurate and realistic quantification of the uncertainty associated with the thus inferred models. Focusing on a series of pertinent crosshole georadar tomographic examples, I investigated two classes of geostatistical resampling strategies with regard to their ability to efficiently and accurately generate independent realizations from the Bayesian posterior distribution. The corresponding results indicate that, despite its popularity, sequential resampling is rather inefficient at drawing independent posterior samples for realistic synthetic case studies, notably for the practically common and important scenario of pronounced spatial correlation between model parameters. To address this issue, I have developed a new gradual-deformation-based perturbation approach, which is flexible with regard to the number of model parameters as well as the perturbation strength. Compared to sequential resampling, this newly proposed approach was proven to be highly effective in decreasing the number of iterations required for drawing independent samples from the Bayesian posterior distribution.

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Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale for the purpose of improving predictions of groundwater flow and solute transport. However, extending corresponding approaches to the regional scale still represents one of the major challenges in the domain of hydrogeophysics. To address this problem, we have developed a regional-scale data integration methodology based on a two-step Bayesian sequential simulation approach. Our objective is to generate high-resolution stochastic realizations of the regional-scale hydraulic conductivity field in the common case where there exist spatially exhaustive but poorly resolved measurements of a related geophysical parameter, as well as highly resolved but spatially sparse collocated measurements of this geophysical parameter and the hydraulic conductivity. To integrate this multi-scale, multi-parameter database, we first link the low- and high-resolution geophysical data via a stochastic downscaling procedure. This is followed by relating the downscaled geophysical data to the high-resolution hydraulic conductivity distribution. After outlining the general methodology of the approach, we demonstrate its application to a realistic synthetic example where we consider as data high-resolution measurements of the hydraulic and electrical conductivities at a small number of borehole locations, as well as spatially exhaustive, low-resolution estimates of the electrical conductivity obtained from surface-based electrical resistivity tomography. The different stochastic realizations of the hydraulic conductivity field obtained using our procedure are validated by comparing their solute transport behaviour with that of the underlying ?true? hydraulic conductivity field. We find that, even in the presence of strong subsurface heterogeneity, our proposed procedure allows for the generation of faithful representations of the regional-scale hydraulic conductivity structure and reliable predictions of solute transport over long, regional-scale distances.

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We present a method for analyzing the curvature (second derivatives) of the conical intersection hyperline at an optimized critical point. Our method uses the projected Hessians of the degenerate states after elimination of the two branching space coordinates, and is equivalent to a frequency calculation on a single Born-Oppenheimer potential-energy surface. Based on the projected Hessians, we develop an equation for the energy as a function of a set of curvilinear coordinates where the degeneracy is preserved to second order (i.e., the conical intersection hyperline). The curvature of the potential-energy surface in these coordinates is the curvature of the conical intersection hyperline itself, and thus determines whether one has a minimum or saddle point on the hyperline. The equation used to classify optimized conical intersection points depends in a simple way on the first- and second-order degeneracy splittings calculated at these points. As an example, for fulvene, we show that the two optimized conical intersection points of C2v symmetry are saddle points on the intersection hyperline. Accordingly, there are further intersection points of lower energy, and one of C2 symmetry - presented here for the first time - is found to be the global minimum in the intersection space

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Vertical electric soundings, 2D resistivity imaging and several logging measurements were performed at Kappelen test site to identify the various geolelectric facies that allowed determining the tabular and horizontal structure of the aquifer. The surface-based geoelectric methods allowed for a reliable characterization of the overall structure and the geometry of the aquifer, while geophysical logging methods allowed for inferring detailed hydrogeophysical characteristics, such as the electrical resistivity, total porosity, global and matrix density and hydraulic conductivity. The synoptic interpretation and integration of this broad and diverse database allows for constraining the key hydrological characteristics and hence forms the basis for the detailed hydraulic modelling of flow and transport process.