The Effect Of Induced Intraocular Straylight (cataract Simulation) On Sensitivity Measures Of Standard Automated Perimetry, Pulsar Perimetry And Moorfields Motion Displacement Test

Purpose: To investigate the effect of incremental increases in intraocular straylight on threshold measurements made by three modern forms of perimetry: Standard Automated Perimetry (SAP) using Octopus (Dynamic, G-Pattern), Pulsar Perimetry (PP) (TOP, 66 points) and the Moorfields Motion Displacement Test (MDT) (WEBS, 32 points).Methods: Four healthy young observers were recruited (mean age 26yrs [25yrs, 28yrs]), refractive correction [+2 D, -4.25D]). Five white opacity filters (WOF), each scattering light by different amounts were used to create incremental increases in intraocular straylight (IS). Resultant IS values were measured with each WOF and at baseline (no WOF) for each subject using a C-Quant Straylight Meter (Oculus, Wetzlar, Germany). A 25 yr old has an IS value of ~0.85 log(s). An increase of 40% in IS to 1.2log(s) corresponds to the physiological value of a 70yr old. Each WOFs created an increase in IS between 10-150% from baseline, ranging from effects similar to normal aging to those found with considerable cataract. Each subject underwent 6 test sessions over a 2-week period; each session consisted of the 3 perimetric tests using one of the five WOFs and baseline (both instrument and filter were randomised).Results: The reduction in sensitivity from baseline was calculated. A two-way ANOVA on mean change in threshold (where subjects were treated as rows in the block and each increment in fog filters was treated as column) was used to examine the effect of incremental increases in straylight. Both SAP (p<0.001) and Pulsar (p<0.001) were significantly affected by increases in straylight. The MDT (p=0.35) remained comparatively robust to increases in straylight.Conclusions: The Moorfields MDT measurement of threshold is robust to effects of additional straylight as compared to SAP and PP.

Orthotropic active strain models for the numerical simulation of cardiac biomechanics

An active strain formulation for orthotropic constitutive laws arising in cardiac mechanics modeling is introduced and studied. The passive mechanical properties of the tissue are described by the Holzapfel-Ogden relation. In the active strain formulation, the Euler-Lagrange equations for minimizing the total energy are written in terms of active and passive deformation factors, where the active part is assumed to depend, at the cell level, on the electrodynamics and on the specific orientation of the cardiac cells. The well-posedness of the linear system derived from a generic Newton iteration of the original problem is analyzed and different mechanical activation functions are considered. In addition, the active strain formulation is compared with the classical active stress formulation from both numerical and modeling perspectives. Taylor-Hood and MINI finite elements are employed to discretize the mechanical problem. The results of several numerical experiments show that the proposed formulation is mathematically consistent and is able to represent the main key features of the phenomenon, while allowing savings in computational costs.

S-system parameter estimation for noisy metabolic profiles using newton-flow analysis.

Biochemical systems are commonly modelled by systems of ordinary differential equations (ODEs). A particular class of such models called S-systems have recently gained popularity in biochemical system modelling. The parameters of an S-system are usually estimated from time-course profiles. However, finding these estimates is a difficult computational problem. Moreover, although several methods have been recently proposed to solve this problem for ideal profiles, relatively little progress has been reported for noisy profiles. We describe a special feature of a Newton-flow optimisation problem associated with S-system parameter estimation. This enables us to significantly reduce the search space, and also lends itself to parameter estimation for noisy data. We illustrate the applicability of our method by applying it to noisy time-course data synthetically produced from previously published 4- and 30-dimensional S-systems. In addition, we propose an extension of our method that allows the detection of network topologies for small S-systems. We introduce a new method for estimating S-system parameters from time-course profiles. We show that the performance of this method compares favorably with competing methods for ideal profiles, and that it also allows the determination of parameters for noisy profiles.

Prediction of infant drug exposure through breastfeeding: population PK modeling and simulation of fluoxetine

BACKGROUND: Risks of significant infant drug exposurethrough breastmilk are poorly defined for many drugs, and largescalepopulation data are lacking. We used population pharmacokinetics(PK) modeling to predict fluoxetine exposure levels ofinfants via mother's milk in a simulated population of 1000 motherinfantpairs.METHODS: Using our original data on fluoxetine PK of 25breastfeeding women, a population PK model was developed withNONMEM and parameters, including milk concentrations, wereestimated. An exponential distribution model was used to account forindividual variation. Simulation random and distribution-constrainedassignment of doses, dosing time, feeding intervals and milk volumewas conducted to generate 1000 mother-infant pairs with characteristicssuch as the steady-state serum concentrations (Css) and infantdose relative to the maternal weight-adjusted dose (relative infantdose: RID). Full bioavailability and a conservative point estimate of1-month-old infant CYP2D6 activity to be 20% of the adult value(adjusted by weigth) according to a recent study, were assumed forinfant Css calculations.RESULTS: A linear 2-compartment model was selected as thebest model. Derived parameters, including milk-to-plasma ratios(mean: 0.66; SD: 0.34; range, 0 - 1.1) were consistent with the valuesreported in the literature. The estimated RID was below 10% in >95%of infants. The model predicted median infant-mother Css ratio was0.096 (range 0.035 - 0.25); literature reported mean was 0.07 (range0-0.59). Moreover, the predicted incidence of infant-mother Css ratioof >0.2 was less than 1%.CONCLUSION: Our in silico model prediction is consistent withclinical observations, suggesting that substantial systemic fluoxetineexposure in infants through human milk is rare, but further analysisshould include active metabolites. Our approach may be valid forother drugs. [supported by CIHR and Swiss National Science Foundation(SNSF)]

SIMULIT : un modèle de simulation pour l'analyse et la planification de l'activité hospitalière

Le modèle développé à l'Institut universitaire de médecine sociale et préventive de Lausanne utilise un programme informatique pour simuler les mouvements d'entrées et de sorties des hôpitaux de soins généraux. Cette simulation se fonde sur les données récoltées de routine dans les hôpitaux; elle tient notamment compte de certaines variations journalières et saisonnières, du nombre d'entrées, ainsi que du "Case-Mix" de l'hôpital, c'est-à-dire de la répartition des cas selon les groupes cliniques et l'âge des patients.

Intravenous streptomycin dosing regimen in a patient undergoing hemodialysis: Plasma level monitoring and pharmacokinetic simulation

Introduction: Streptomycin, as other aminoglycosides, exhibits concentration-dependent bacterial killing but has a narrow therapeutic window. It is primarily eliminated unchanged by the kidneys. Data and dosing information to achieve a safe regimen in patients with chronic renal failure undergoing hemodialysis (HD) are scarce. Although main adverse reactions are related to prolonged, elevated serum concentrations, literature recommendation is to administer streptomycin after each HD. Patients (or Materials) and Methods: We report the case of a patient with end-stage renal failure, undergoing HD, who was successfully treated with streptomycin for gentamicin-resistant Enterococcus faecalis bacteremia with prosthetic arteriovenous fistula infection. Streptomycin was administered intravenously 7.5 mg/kg, 3 hours before each dialysis (3 times a week) during 6 weeks in combination with amoxicillin. Streptomycin plasma levels were monitored with repeated blood sampling before, after, and between HD sessions. A 2-compartment model was used to reconstruct the concentration time profile over days on and off HD. Results: Streptomycin trough plasma-concentration was 2.8 mg/L. It peaked to 21.4 mg/L 30 minutes after intravenous administration, decreased to 18.2 mg/L immediately before HD, and dropped to 4.5 mg/L at the end of a 4-hour HD session. Plasma level increased again to 5.7 mg/L 2 hours after the end of HD and was 2.8 mg/L 48 hours later, before the next administration and HD. The pharmacokinetics of streptomycin was best described with a 2-compartment model. The computer simulation fitted fairly well to the observed concentrations during or between HD sessions. Redistribution between the 2 compartments after the end of HD reproduced the rebound of plasma concentrations after HD. No significant toxicity was observed during treatment. The outcome of the infection was favorable, and no sign of relapse was observed after a follow-up of 3 months. Conclusion: Streptomycin administration of 7.5 mg/kg 3 hours before HD sessions in a patient with end-stage renal failure resulted in an effective and safe dosing regimen. Monitoring plasma levels along with pharmacokinetic simulation document the suitability of this dosing scheme, which should replace current dosage recommendations for streptomycin in HD.

Direct simulation of interface dynamics: linking capillary pressure, interfacial area and surface energy

We perform direct numerical simulations of drainage by solving Navier- Stokes equations in the pore space and employing the Volume Of Fluid (VOF) method to track the evolution of the fluid-fluid interface. After demonstrating that the method is able to deal with large viscosity contrasts and to model the transition from stable flow to viscous fingering, we focus on the definition of macroscopic capillary pressure. When the fluids are at rest, the difference between inlet and outlet pressures and the difference between the intrinsic phase average pressure coincide with the capillary pressure. However, when the fluids are in motion these quantities are dominated by viscous forces. In this case, only a definition based on the variation of the interfacial energy provides an accurate measure of the macroscopic capillary pressure and allows separating the viscous from the capillary pressure components.

Stochastic Population Projection for Germany - based on the Quadratic Spline approach to modelling age specific fertility rates

This contribution builds upon a former paper by the authors (Lipps and Betz 2004), in which a stochastic population projection for East- and West Germany is performed. Aim was to forecast relevant population parameters and their distribution in a consistent way. We now present some modifications, which have been modelled since. First, population parameters for the entire German population are modelled. In order to overcome the modelling problem of the structural break in the East during reunification, we show that the adaptation process of the relevant figures by the East can be considered to be completed by now. As a consequence, German parameters can be modelled just by using the West German historic patterns, with the start-off population of entire Germany. Second, a new model to simulate age specific fertility rates is presented, based on a quadratic spline approach. This offers a higher flexibility to model various age specific fertility curves. The simulation results are compared with the scenario based official forecasts for Germany in 2050. Exemplary for some population parameters (e.g. dependency ratio), it can be shown that the range spanned by the medium and extreme variants correspond to the s-intervals in the stochastic framework. It seems therefore more appropriate to treat this range as a s-interval covering about two thirds of the true distribution.

Estimation of jump-diffusion processes via empirical characteristic functions

Preface The starting point for this work and eventually the subject of the whole thesis was the question: how to estimate parameters of the affine stochastic volatility jump-diffusion models. These models are very important for contingent claim pricing. Their major advantage, availability T of analytical solutions for characteristic functions, made them the models of choice for many theoretical constructions and practical applications. At the same time, estimation of parameters of stochastic volatility jump-diffusion models is not a straightforward task. The problem is coming from the variance process, which is non-observable. There are several estimation methodologies that deal with estimation problems of latent variables. One appeared to be particularly interesting. It proposes the estimator that in contrast to the other methods requires neither discretization nor simulation of the process: the Continuous Empirical Characteristic function estimator (EGF) based on the unconditional characteristic function. However, the procedure was derived only for the stochastic volatility models without jumps. Thus, it has become the subject of my research. This thesis consists of three parts. Each one is written as independent and self contained article. At the same time, questions that are answered by the second and third parts of this Work arise naturally from the issues investigated and results obtained in the first one. The first chapter is the theoretical foundation of the thesis. It proposes an estimation procedure for the stochastic volatility models with jumps both in the asset price and variance processes. The estimation procedure is based on the joint unconditional characteristic function for the stochastic process. The major analytical result of this part as well as of the whole thesis is the closed form expression for the joint unconditional characteristic function for the stochastic volatility jump-diffusion models. The empirical part of the chapter suggests that besides a stochastic volatility, jumps both in the mean and the volatility equation are relevant for modelling returns of the S&P500 index, which has been chosen as a general representative of the stock asset class. Hence, the next question is: what jump process to use to model returns of the S&P500. The decision about the jump process in the framework of the affine jump- diffusion models boils down to defining the intensity of the compound Poisson process, a constant or some function of state variables, and to choosing the distribution of the jump size. While the jump in the variance process is usually assumed to be exponential, there are at least three distributions of the jump size which are currently used for the asset log-prices: normal, exponential and double exponential. The second part of this thesis shows that normal jumps in the asset log-returns should be used if we are to model S&P500 index by a stochastic volatility jump-diffusion model. This is a surprising result. Exponential distribution has fatter tails and for this reason either exponential or double exponential jump size was expected to provide the best it of the stochastic volatility jump-diffusion models to the data. The idea of testing the efficiency of the Continuous ECF estimator on the simulated data has already appeared when the first estimation results of the first chapter were obtained. In the absence of a benchmark or any ground for comparison it is unreasonable to be sure that our parameter estimates and the true parameters of the models coincide. The conclusion of the second chapter provides one more reason to do that kind of test. Thus, the third part of this thesis concentrates on the estimation of parameters of stochastic volatility jump- diffusion models on the basis of the asset price time-series simulated from various "true" parameter sets. The goal is to show that the Continuous ECF estimator based on the joint unconditional characteristic function is capable of finding the true parameters. And, the third chapter proves that our estimator indeed has the ability to do so. Once it is clear that the Continuous ECF estimator based on the unconditional characteristic function is working, the next question does not wait to appear. The question is whether the computation effort can be reduced without affecting the efficiency of the estimator, or whether the efficiency of the estimator can be improved without dramatically increasing the computational burden. The efficiency of the Continuous ECF estimator depends on the number of dimensions of the joint unconditional characteristic function which is used for its construction. Theoretically, the more dimensions there are, the more efficient is the estimation procedure. In practice, however, this relationship is not so straightforward due to the increasing computational difficulties. The second chapter, for example, in addition to the choice of the jump process, discusses the possibility of using the marginal, i.e. one-dimensional, unconditional characteristic function in the estimation instead of the joint, bi-dimensional, unconditional characteristic function. As result, the preference for one or the other depends on the model to be estimated. Thus, the computational effort can be reduced in some cases without affecting the efficiency of the estimator. The improvement of the estimator s efficiency by increasing its dimensionality faces more difficulties. The third chapter of this thesis, in addition to what was discussed above, compares the performance of the estimators with bi- and three-dimensional unconditional characteristic functions on the simulated data. It shows that the theoretical efficiency of the Continuous ECF estimator based on the three-dimensional unconditional characteristic function is not attainable in practice, at least for the moment, due to the limitations on the computer power and optimization toolboxes available to the general public. Thus, the Continuous ECF estimator based on the joint, bi-dimensional, unconditional characteristic function has all the reasons to exist and to be used for the estimation of parameters of the stochastic volatility jump-diffusion models.

Data-driven clustering : new methods and applications

Abstract : This work is concerned with the development and application of novel unsupervised learning methods, having in mind two target applications: the analysis of forensic case data and the classification of remote sensing images. First, a method based on a symbolic optimization of the inter-sample distance measure is proposed to improve the flexibility of spectral clustering algorithms, and applied to the problem of forensic case data. This distance is optimized using a loss function related to the preservation of neighborhood structure between the input space and the space of principal components, and solutions are found using genetic programming. Results are compared to a variety of state-of--the-art clustering algorithms. Subsequently, a new large-scale clustering method based on a joint optimization of feature extraction and classification is proposed and applied to various databases, including two hyperspectral remote sensing images. The algorithm makes uses of a functional model (e.g., a neural network) for clustering which is trained by stochastic gradient descent. Results indicate that such a technique can easily scale to huge databases, can avoid the so-called out-of-sample problem, and can compete with or even outperform existing clustering algorithms on both artificial data and real remote sensing images. This is verified on small databases as well as very large problems. Résumé : Ce travail de recherche porte sur le développement et l'application de méthodes d'apprentissage dites non supervisées. Les applications visées par ces méthodes sont l'analyse de données forensiques et la classification d'images hyperspectrales en télédétection. Dans un premier temps, une méthodologie de classification non supervisée fondée sur l'optimisation symbolique d'une mesure de distance inter-échantillons est proposée. Cette mesure est obtenue en optimisant une fonction de coût reliée à la préservation de la structure de voisinage d'un point entre l'espace des variables initiales et l'espace des composantes principales. Cette méthode est appliquée à l'analyse de données forensiques et comparée à un éventail de méthodes déjà existantes. En second lieu, une méthode fondée sur une optimisation conjointe des tâches de sélection de variables et de classification est implémentée dans un réseau de neurones et appliquée à diverses bases de données, dont deux images hyperspectrales. Le réseau de neurones est entraîné à l'aide d'un algorithme de gradient stochastique, ce qui rend cette technique applicable à des images de très haute résolution. Les résultats de l'application de cette dernière montrent que l'utilisation d'une telle technique permet de classifier de très grandes bases de données sans difficulté et donne des résultats avantageusement comparables aux méthodes existantes.

Inferring landscape effects on dispersal from genetic distances: how far can we go?

Functional connectivity affects demography and gene dynamics in fragmented populations. Besides species-specific dispersal ability, the connectivity between local populations is affected by the landscape elements encountered during dispersal. Documenting these effects is thus a central issue for the conservation and management of fragmented populations. In this study, we compare the power and accuracy of three methods (partial correlations, regressions and Approximate Bayesian Computations) that use genetic distances to infer the effect of landscape upon dispersal. We use stochastic individual-based simulations of fragmented populations surrounded by landscape elements that differ in their permeability to dispersal. The power and accuracy of all three methods are good when there is a strong contrast between the permeability of different landscape elements. The power and accuracy can be further improved by restricting analyses to adjacent pairs of populations. Landscape elements that strongly impede dispersal are the easiest to identify. However, power and accuracy decrease drastically when landscape complexity increases and the contrast between the permeability of landscape elements decreases. We provide guidelines for future studies and underline the needs to evaluate or develop approaches that are more powerful.

Integration of local-scale hydrological and regional-scale geophysical based on a nonlinear Bayesian sequential simulation approach

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed a downscaling procedure based on a non-linear Bayesian sequential simulation approach. The basic objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity, which is available throughout the model space. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariate kernel density function. This method is then applied to the stochastic integration of low-resolution, re- gional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this downscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the downscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

Stochastic models and numerical algorithms for a class of regulatory gene networks.

Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.

Integrated application of geochemical and geophysical methods for hydrogeological impact assessment for tunneling in fractured rock

The interaction of tunneling with groundwater is a problem both from an environmental and an engineering point of view. In fact, tunnel drilling may cause a drawdown of piezometric levels and water inflows into tunnels that may cause problems during excavation of the tunnel. While the influence of tunneling on the regional groundwater systems may be adequately predicted in porous media using analytical solutions, such an approach is difficult to apply in fractured rocks. Numerical solutions are preferable and various conceptual approaches have been proposed to describe and model groundwater flow through fractured rock masses, ranging from equivalent continuum models to discrete fracture network simulation models. However, their application needs many preliminary investigations on the behavior of the groundwater system based on hydrochemical and structural data. To study large scale flow systems in fractured rocks of mountainous terrains, a comprehensive study was conducted in southern Switzerland, using as case studies two infrastructures actually under construction: (i) the Monte Ceneri base railway tunnel (Ticino), and the (ii) San Fedele highway tunnel (Roveredo, Graubiinden). The chosen approach in this study combines the temporal and spatial variation of geochemical and geophysical measurements. About 60 localities from both surface and underlying tunnels were temporarily and spatially monitored during more than one year. At first, the project was focused on the collection of hydrochemical and structural data. A number of springs, selected in the area surrounding the infrastructures, were monitored for discharge, electric conductivity, pH, and temperature. Water samples (springs, tunnel inflows and rains) were taken for isotopic analysis; in particular the stable isotope composition (δ2Η, δ180 values) can reflect the origin of the water, because of spatial (recharge altitude, topography, etc.) and temporal (seasonal) effects on precipitation which in turn strongly influence the isotopic composition of groundwater. Tunnel inflows in the accessible parts of the tunnels were also sampled and, if possible, monitored with time. Noble-gas concentrations and their isotope ratios were used in selected locations to better understand the origin and the circulation of the groundwater. In addition, electrical resistivity and VLF-type electromagnetic surveys were performed to identify water bearing fractures and/or weathered areas that could be intersected at depth during tunnel construction. The main goal of this work was to demonstrate that these hydrogeological data and geophysical methods, combined with structural and hydrogeological information, can be successfully used in order to develop hydrogeological conceptual models of the groundwater flow in regions to be exploited for tunnels. The main results of the project are: (i) to have successfully tested the application of electrical resistivity and VLF-electromagnetic surveys to asses water-bearing zones during tunnel drilling; (ii) to have verified the usefulness of noble gas, major ion and stable isotope compositions as proxies for the detection of faults and to understand the origin of the groundwater and its flow regimes (direct rain water infiltration or groundwater of long residence time); and (iii) to have convincingly tested the combined application of a geochemical and geophysical approach to assess and predict the vulnerability of springs to tunnel drilling. - L'interférence entre eaux souterraines et des tunnels pose des problèmes environnementaux et de génie civile. En fait, la construction d'un tunnel peut faire abaisser le niveau des nappes piézométriques et faire infiltrer de l'eau dans le tunnel et ainsi créer des problème pendant l'excavation. Alors que l'influence de la construction d'un tunnel sur la circulation régionale de l'eau souterraine dans des milieux poreux peut être prédite relativement facilement par des solution analytiques de modèles, ceci devient difficile dans des milieux fissurés. Dans ce cas-là, des solutions numériques sont préférables et plusieurs approches conceptuelles ont été proposées pour décrire et modéliser la circulation d'eau souterraine à travers les roches fissurées, en allant de modèles d'équivalence continue à des modèles de simulation de réseaux de fissures discrètes. Par contre, leur application demande des investigations importantes concernant le comportement du système d'eau souterraine basées sur des données hydrochimiques et structurales. Dans le but d'étudier des grands systèmes de circulation d'eau souterraine dans une région de montagnes, une étude complète a été fait en Suisse italienne, basée sur deux grandes infrastructures actuellement en construction: (i) Le tunnel ferroviaire de base du Monte Ceneri (Tessin) et (ii) le tunnel routière de San Fedele (Roveredo, Grisons). L'approche choisie dans cette étude est la combinaison de variations temporelles et spatiales des mesures géochimiques et géophysiques. Environs 60 localités situées à la surface ainsi que dans les tunnels soujacents ont été suiviès du point de vue temporel et spatial pendant plus de un an. Dans un premier temps le projet se focalisait sur la collecte de données hydrochimiques et structurales. Un certain nombre de sources, sélectionnées dans les environs des infrastructures étudiées ont été suivies pour le débit, la conductivité électrique, le pH et la température. De l'eau (sources, infiltration d'eau de tunnel et pluie) a été échantillonnés pour des analyses isotopiques; ce sont surtout les isotopes stables (δ2Η, δ180) qui peuvent indiquer l'origine d'une eaux, à cause de la dépendance d'effets spatiaux (altitude de recharge, topographie etc.) ainsi que temporels (saisonaux) sur les précipitations météoriques , qui de suite influencent ainsi la composition isotopique de l'eau souterraine. Les infiltrations d'eau dans les tunnels dans les parties accessibles ont également été échantillonnées et si possible suivies au cours du temps. La concentration de gaz nobles et leurs rapports isotopiques ont également été utilisées pour quelques localités pour mieux comprendre l'origine et la circulation de l'eau souterraine. En plus, des campagnes de mesures de la résistivité électrique et électromagnétique de type VLF ont été menées afin d'identifier des zone de fractures ou d'altération qui pourraient interférer avec les tunnels en profondeur pendant la construction. Le but principal de cette étude était de démontrer que ces données hydrogéologiques et géophysiques peuvent être utilisées avec succès pour développer des modèles hydrogéologiques conceptionels de tunnels. Les résultats principaux de ce travail sont : i) d'avoir testé avec succès l'application de méthodes de la tomographie électrique et des campagnes de mesures électromagnétiques de type VLF afin de trouver des zones riches en eau pendant l'excavation d'un tunnel ; ii) d'avoir prouvé l'utilité des gaz nobles, des analyses ioniques et d'isotopes stables pour déterminer l'origine de l'eau infiltrée (de la pluie par le haut ou ascendant de l'eau remontant des profondeurs) et leur flux et pour déterminer la position de failles ; et iii) d'avoir testé d'une manière convainquant l'application combinée de méthodes géochimiques et géophysiques pour juger et prédire la vulnérabilité de sources lors de la construction de tunnels. - L'interazione dei tunnel con il circuito idrico sotterraneo costituisce un problema sia dal punto di vista ambientale che ingegneristico. Lo scavo di un tunnel puô infatti causare abbassamenti dei livelli piezometrici, inoltre le venute d'acqua in galleria sono un notevole problema sia in fase costruttiva che di esercizio. Nel caso di acquiferi in materiale sciolto, l'influenza dello scavo di un tunnel sul circuito idrico sotterraneo, in genere, puô essere adeguatamente predetta attraverso l'applicazione di soluzioni analitiche; al contrario un approccio di questo tipo appare inadeguato nel caso di scavo in roccia. Per gli ammassi rocciosi fratturati sono piuttosto preferibili soluzioni numeriche e, a tal proposito, sono stati proposti diversi approcci concettuali; nella fattispecie l'ammasso roccioso puô essere modellato come un mezzo discreto ο continuo équivalente. Tuttavia, una corretta applicazione di qualsiasi modello numerico richiede necessariamente indagini preliminari sul comportamento del sistema idrico sotterraneo basate su dati idrogeochimici e geologico strutturali. Per approfondire il tema dell'idrogeologia in ammassi rocciosi fratturati tipici di ambienti montani, è stato condotto uno studio multidisciplinare nel sud della Svizzera sfruttando come casi studio due infrastrutture attualmente in costruzione: (i) il tunnel di base del Monte Ceneri (canton Ticino) e (ii) il tunnel autostradale di San Fedele (Roveredo, canton Grigioni). L'approccio di studio scelto ha cercato di integrare misure idrogeochimiche sulla qualité e quantité delle acque e indagini geofisiche. Nella fattispecie sono state campionate le acque in circa 60 punti spazialmente distribuiti sia in superficie che in sotterraneo; laddove possibile il monitoraggio si è temporalmente prolungato per più di un anno. In una prima fase, il progetto di ricerca si è concentrato sull'acquisizione dati. Diverse sorgenti, selezionate nelle aree di possibile influenza attorno allé infrastrutture esaminate, sono state monitorate per quel che concerne i parametri fisico-chimici: portata, conduttività elettrica, pH e temperatura. Campioni d'acqua sono stati prelevati mensilmente su sorgenti, venute d'acqua e precipitazioni, per analisi isotopiche; nella fattispecie, la composizione in isotopi stabili (δ2Η, δ180) tende a riflettere l'origine delle acque, in quanto, variazioni sia spaziali (altitudine di ricarica, topografia, etc.) che temporali (variazioni stagionali) della composizione isotopica delle precipitazioni influenzano anche le acque sotterranee. Laddove possibile, sono state campionate le venute d'acqua in galleria sia puntualmente che al variare del tempo. Le concentrazioni dei gas nobili disciolti nell'acqua e i loro rapporti isotopici sono stati altresi utilizzati in alcuni casi specifici per meglio spiegare l'origine delle acque e le tipologie di circuiti idrici sotterranei. Inoltre, diverse indagini geofisiche di resistività elettrica ed elettromagnetiche a bassissima frequenza (VLF) sono state condotte al fine di individuare le acque sotterranee circolanti attraverso fratture dell'ammasso roccioso. Principale obiettivo di questo lavoro è stato dimostrare come misure idrogeochimiche ed indagini geofisiche possano essere integrate alio scopo di sviluppare opportuni modelli idrogeologici concettuali utili per lo scavo di opere sotterranee. I principali risultati ottenuti al termine di questa ricerca sono stati: (i) aver testato con successo indagini geofisiche (ERT e VLF-EM) per l'individuazione di acque sotterranee circolanti attraverso fratture dell'ammasso roccioso e che possano essere causa di venute d'acqua in galleria durante lo scavo di tunnel; (ii) aver provato l'utilità di analisi su gas nobili, ioni maggiori e isotopi stabili per l'individuazione di faglie e per comprendere l'origine delle acque sotterranee (acque di recente infiltrazione ο provenienti da circolazioni profonde); (iii) aver testato in maniera convincente l'integrazione delle indagini geofisiche e di misure geochimiche per la valutazione della vulnérabilité delle sorgenti durante lo scavo di nuovi tunnel. - "La NLFA (Nouvelle Ligne Ferroviaire à travers les Alpes) axe du Saint-Gothard est le plus important projet de construction de Suisse. En bâtissant la nouvelle ligne du Saint-Gothard, la Suisse réalise un des plus grands projets de protection de l'environnement d'Europe". Cette phrase, qu'on lit comme présentation du projet Alptransit est particulièrement éloquente pour expliquer l'utilité des nouvelles lignes ferroviaires transeuropéens pour le développement durable. Toutefois, comme toutes grandes infrastructures, la construction de nouveaux tunnels ont des impacts inévitables sur l'environnement. En particulier, le possible drainage des eaux souterraines réalisées par le tunnel peut provoquer un abaissement du niveau des nappes piézométriques. De plus, l'écoulement de l'eau à l'intérieur du tunnel, conduit souvent à des problèmes d'ingénierie. Par exemple, d'importantes infiltrations d'eau dans le tunnel peuvent compliquer les phases d'excavation, provoquant un retard dans l'avancement et dans le pire des cas, peuvent mettre en danger la sécurité des travailleurs. Enfin, l'infiltration d'eau peut être un gros problème pendant le fonctionnement du tunnel. Du point de vue de la science, avoir accès à des infrastructures souterraines représente une occasion unique d'obtenir des informations géologiques en profondeur et pour échantillonner des eaux autrement inaccessibles. Dans ce travail, nous avons utilisé une approche pluridisciplinaire qui intègre des mesures d'étude hydrogéochimiques effectués sur les eaux de surface et des investigations géophysiques indirects, tels que la tomographic de résistivité électrique (TRE) et les mesures électromagnétiques de type VLF. L'étude complète a été fait en Suisse italienne, basée sur deux grandes infrastructures actuellement en construction, qui sont le tunnel ferroviaire de base du Monte Ceneri, une partie du susmentionné projet Alptransit, situé entièrement dans le canton Tessin, et le tunnel routière de San Fedele, situé a Roveredo dans le canton des Grisons. Le principal objectif était de montrer comment il était possible d'intégrer les deux approches, géophysiques et géochimiques, afin de répondre à la question de ce que pourraient être les effets possibles dû au drainage causés par les travaux souterrains. L'accès aux galeries ci-dessus a permis une validation adéquate des enquêtes menées confirmant, dans chaque cas, les hypothèses proposées. A cette fin, nous avons fait environ 50 profils géophysiques (28 imageries électrique bidimensionnels et 23 électromagnétiques) dans les zones de possible influence par le tunnel, dans le but d'identifier les fractures et les discontinuités dans lesquelles l'eau souterraine peut circuler. De plus, des eaux ont été échantillonnés dans 60 localités situées la surface ainsi que dans les tunnels subjacents, le suivi mensuelle a duré plus d'un an. Nous avons mesurés tous les principaux paramètres physiques et chimiques: débit, conductivité électrique, pH et température. De plus, des échantillons d'eaux ont été prélevés pour l'analyse mensuelle des isotopes stables de l'hydrogène et de l'oxygène (δ2Η, δ180). Avec ces analyses, ainsi que par la mesure des concentrations des gaz rares dissous dans les eaux et de leurs rapports isotopiques que nous avons effectués dans certains cas spécifiques, il était possible d'expliquer l'origine des différents eaux souterraines, les divers modes de recharge des nappes souterraines, la présence de possible phénomènes de mélange et, en général, de mieux expliquer les circulations d'eaux dans le sous-sol. Le travail, même en constituant qu'une réponse partielle à une question très complexe, a permis d'atteindre certains importants objectifs. D'abord, nous avons testé avec succès l'applicabilité des méthodes géophysiques indirectes (TRE et électromagnétiques de type VLF) pour prédire la présence d'eaux souterraines dans le sous-sol des massifs rocheux. De plus, nous avons démontré l'utilité de l'analyse des gaz rares, des isotopes stables et de l'analyses des ions majeurs pour la détection de failles et pour comprendre l'origine des eaux souterraines (eau de pluie par le haut ou eau remontant des profondeurs). En conclusion, avec cette recherche, on a montré que l'intégration des ces informations (géophysiques et géochimiques) permet le développement de modèles conceptuels appropriés, qui permettant d'expliquer comment l'eau souterraine circule. Ces modèles permettent de prévoir les infiltrations d'eau dans les tunnels et de prédire la vulnérabilité de sources et des autres ressources en eau lors de construction de tunnels.