Testing for local adaptation in brown trout using reciprocal transplants.

ABSTRACT: BACKGROUND: Local adaptation can drive the divergence of populations but identification of the traits under selection remains a major challenge in evolutionary biology. Reciprocal transplant experiments are ideal tests of local adaptation, yet rarely used for higher vertebrates because of the mobility and potential invasiveness of non-native organisms. Here, we reciprocally transplanted 2500 brown trout (Salmo trutta) embryos from five populations to investigate local adaptation in early life history traits. Embryos were bred in a full-factorial design and raised in natural riverbeds until emergence. Customized egg capsules were used to simulate the natural redd environment and allowed tracking the fate of every individual until retrieval. We predicted that 1) within sites, native populations would outperform non-natives, and 2) across sites, populations would show higher performance at 'home' compared to 'away' sites. RESULTS: There was no evidence for local adaptation but we found large differences in survival and hatching rates between sites, indicative of considerable variation in habitat quality. Survival was generally high across all populations (55% +/- 3%), but ranged from 4% to 89% between sites. Average hatching rate was 25% +/- 3% across populations ranging from 0% to 62% between sites. CONCLUSION: This study provides rare empirical data on variation in early life history traits in a population network of a salmonid, and large-scale breeding and transplantation experiments like ours provide powerful tests for local adaptation. Despite the recently reported genetic and morphological differences between the populations in our study area, local adaptation at the embryo level is small, non-existent, or confined to ecological conditions that our experiment could not capture.

Mapping the structural core of human cerebral cortex.

Structurally segregated and functionally specialized regions of the human cerebral cortex are interconnected by a dense network of cortico-cortical axonal pathways. By using diffusion spectrum imaging, we noninvasively mapped these pathways within and across cortical hemispheres in individual human participants. An analysis of the resulting large-scale structural brain networks reveals a structural core within posterior medial and parietal cerebral cortex, as well as several distinct temporal and frontal modules. Brain regions within the structural core share high degree, strength, and betweenness centrality, and they constitute connector hubs that link all major structural modules. The structural core contains brain regions that form the posterior components of the human default network. Looking both within and outside of core regions, we observed a substantial correspondence between structural connectivity and resting-state functional connectivity measured in the same participants. The spatial and topological centrality of the core within cortex suggests an important role in functional integration.

Mycorrhizal ecology and evolution: the past, the present, and the future.

1406 I. 1407 II. 1408 III. 1410 IV. 1411 V. 1413 VI. 1416 VII. 1418 1418 References 1419 SUMMARY: Almost all land plants form symbiotic associations with mycorrhizal fungi. These below-ground fungi play a key role in terrestrial ecosystems as they regulate nutrient and carbon cycles, and influence soil structure and ecosystem multifunctionality. Up to 80% of plant N and P is provided by mycorrhizal fungi and many plant species depend on these symbionts for growth and survival. Estimates suggest that there are c. 50 000 fungal species that form mycorrhizal associations with c. 250 000 plant species. The development of high-throughput molecular tools has helped us to better understand the biology, evolution, and biodiversity of mycorrhizal associations. Nuclear genome assemblies and gene annotations of 33 mycorrhizal fungal species are now available providing fascinating opportunities to deepen our understanding of the mycorrhizal lifestyle, the metabolic capabilities of these plant symbionts, the molecular dialogue between symbionts, and evolutionary adaptations across a range of mycorrhizal associations. Large-scale molecular surveys have provided novel insights into the diversity, spatial and temporal dynamics of mycorrhizal fungal communities. At the ecological level, network theory makes it possible to analyze interactions between plant-fungal partners as complex underground multi-species networks. Our analysis suggests that nestedness, modularity and specificity of mycorrhizal networks vary and depend on mycorrhizal type. Mechanistic models explaining partner choice, resource exchange, and coevolution in mycorrhizal associations have been developed and are being tested. This review ends with major frontiers for further research.

Local-scale spatial variation in diversity of social wasps in an Amazonian rain forest in Caxiuanã, Pará, Brazil (Hymenoptera, Vespidae, Polistinae)

Polistine wasps are important in Neotropical ecosystems due to their ubiquity and diversity. Inventories have not adequately considered spatial attributes of collected specimens. Spatial data on biodiversity are important for study and mitigation of anthropogenic impacts over natural ecosystems and for protecting species. We described and analyzed local-scale spatial patterns of collecting records of wasp species, as well as spatial variation of diversity descriptors in a 2500-hectare area of an Amazon forest in Brazil. Rare species comprised the largest fraction of the fauna. Close range spatial effects were detected for most of the more common species, with clustering of presence-data at short distances. Larger spatial lag effects could also be identified in some species, constituting probably cases of exogenous autocorrelation and candidates for explanations based on environmental factors. In a few cases, significant or near significant correlations were found between five species (of Agelaia, Angiopolybia, and Mischocyttarus) and three studied environmental variables: distance to nearest stream, terrain altitude, and the type of forest canopy. However, association between these factors and biodiversity variables were generally low. When used as predictors of polistine richness in a linear multiple regression, only the coefficient for the forest canopy variable resulted significant. Some level of prediction of wasp diversity variables can be attained based on environmental variables, especially vegetation structure. Large-scale landscape and regional studies should be scheduled to address this issue.

Modeling the impact of lesions in the human brain.

Lesions of anatomical brain networks result in functional disturbances of brain systems and behavior which depend sensitively, often unpredictably, on the lesion site. The availability of whole-brain maps of structural connections within the human cerebrum and our increased understanding of the physiology and large-scale dynamics of cortical networks allow us to investigate the functional consequences of focal brain lesions in a computational model. We simulate the dynamic effects of lesions placed in different regions of the cerebral cortex by recording changes in the pattern of endogenous ("resting-state") neural activity. We find that lesions produce specific patterns of altered functional connectivity among distant regions of cortex, often affecting both cortical hemispheres. The magnitude of these dynamic effects depends on the lesion location and is partly predicted by structural network properties of the lesion site. In the model, lesions along the cortical midline and in the vicinity of the temporo-parietal junction result in large and widely distributed changes in functional connectivity, while lesions of primary sensory or motor regions remain more localized. The model suggests that dynamic lesion effects can be predicted on the basis of specific network measures of structural brain networks and that these effects may be related to known behavioral and cognitive consequences of brain lesions.

An architecture for adaptive replication-based multimedia streaming in P2P networks

This PhD thesis addresses the issue of scalable media streaming in large-scale networking environments. Multimedia streaming is one of the largest sink of network resources and this trend is still growing as testified by the success of services like Skype, Netflix, Spotify and Popcorn Time (BitTorrent-based). In traditional client-server solutions, when the number of consumers increases, the server becomes the bottleneck. To overcome this problem, the Content-Delivery Network (CDN) model was invented. In CDN model, the server copies the media content to some CDN servers, which are located in different strategic locations on the network. However, they require heavy infrastructure investment around the world, which is too expensive. Peer-to-peer (P2P) solutions are another way to achieve the same result. These solutions are naturally scalable, since each peer can act as both a receiver and a forwarder. Most of the proposed streaming solutions in P2P networks focus on routing scenarios to achieve scalability. However, these solutions cannot work properly in video-on-demand (VoD) streaming, when resources of the media server are not sufficient. Replication is a solution that can be used in these situations. This thesis specifically provides a family of replication-based media streaming protocols, which are scalable, efficient and reliable in P2P networks. First, it provides SCALESTREAM, a replication-based streaming protocol that adaptively replicates media content in different peers to increase the number of consumers that can be served in parallel. The adaptiveness aspect of this solution relies on the fact that it takes into account different constraints like bandwidth capacity of peers to decide when to add or remove replicas. SCALESTREAM routes media blocks to consumers over a tree topology, assuming a reliable network composed of homogenous peers in terms of bandwidth. Second, this thesis proposes RESTREAM, an extended version of SCALESTREAM that addresses the issues raised by unreliable networks composed of heterogeneous peers. Third, this thesis proposes EAGLEMACAW, a multiple-tree replication streaming protocol in which two distinct trees, named EAGLETREE and MACAWTREE, are built in a decentralized manner on top of an underlying mesh network. These two trees collaborate to serve consumers in an efficient and reliable manner. The EAGLETREE is in charge of improving efficiency, while the MACAWTREE guarantees reliability. Finally, this thesis provides TURBOSTREAM, a hybrid replication-based streaming protocol in which a tree overlay is built on top of a mesh overlay network. Both these overlays cover all peers of the system and collaborate to improve efficiency and low-latency in streaming media to consumers. This protocol is implemented and tested in a real networking environment using PlanetLab Europe testbed composed of peers distributed in different places in Europe.

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.

The evolution of lncRNA repertoires and expression patterns in tetrapods.

Only a very small fraction of long noncoding RNAs (lncRNAs) are well characterized. The evolutionary history of lncRNAs can provide insights into their functionality, but the absence of lncRNA annotations in non-model organisms has precluded comparative analyses. Here we present a large-scale evolutionary study of lncRNA repertoires and expression patterns, in 11 tetrapod species. We identify approximately 11,000 primate-specific lncRNAs and 2,500 highly conserved lncRNAs, including approximately 400 genes that are likely to have originated more than 300 million years ago. We find that lncRNAs, in particular ancient ones, are in general actively regulated and may function predominantly in embryonic development. Most lncRNAs evolve rapidly in terms of sequence and expression levels, but tissue specificities are often conserved. We compared expression patterns of homologous lncRNA and protein-coding families across tetrapods to reconstruct an evolutionarily conserved co-expression network. This network suggests potential functions for lncRNAs in fundamental processes such as spermatogenesis and synaptic transmission, but also in more specific mechanisms such as placenta development through microRNA production.

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.

Gene Ontology Function prediction in Mollicutes using Protein-Protein Association Networks

Abstract Background: Many complex systems can be represented and analysed as networks. The recent availability of large-scale datasets, has made it possible to elucidate some of the organisational principles and rules that govern their function, robustness and evolution. However, one of the main limitations in using protein-protein interactions for function prediction is the availability of interaction data, especially for Mollicutes. If we could harness predicted interactions, such as those from a Protein-Protein Association Networks (PPAN), combining several protein-protein network function-inference methods with semantic similarity calculations, the use of protein-protein interactions for functional inference in this species would become more potentially useful. Results: In this work we show that using PPAN data combined with other approximations, such as functional module detection, orthology exploitation methods and Gene Ontology (GO)-based information measures helps to predict protein function in Mycoplasma genitalium. Conclusions: To our knowledge, the proposed method is the first that combines functional module detection among species, exploiting an orthology procedure and using information theory-based GO semantic similarity in PPAN of the Mycoplasma species. The results of an evaluation show a higher recall than previously reported methods that focused on only one organism network.

EEG-based functional networks in schizophrenia.

Schizophrenia is often considered as a dysconnection syndrome in which, abnormal interactions between large-scale functional brain networks result in cognitive and perceptual deficits. In this article we apply the graph theoretic measures to brain functional networks based on the resting EEGs of fourteen schizophrenic patients in comparison with those of fourteen matched control subjects. The networks were extracted from common-average-referenced EEG time-series through partial and unpartial cross-correlation methods. Unpartial correlation detects functional connectivity based on direct and/or indirect links, while partial correlation allows one to ignore indirect links. We quantified the network properties with the graph metrics, including mall-worldness, vulnerability, modularity, assortativity, and synchronizability. The schizophrenic patients showed method-specific and frequency-specific changes especially pronounced for modularity, assortativity, and synchronizability measures. However, the differences between schizophrenia patients and normal controls in terms of graph theory metrics were stronger for the unpartial correlation method.

Simulated-annealing-based conditional simulation for the local-scale characterization of heterogeneous aquifers

Simulated-annealing-based conditional simulations provide a flexible means of quantitatively integrating diverse types of subsurface data. Although such techniques are being increasingly used in hydrocarbon reservoir characterization studies, their potential in environmental, engineering and hydrological investigations is still largely unexploited. Here, we introduce a novel simulated annealing (SA) algorithm geared towards the integration of high-resolution geophysical and hydrological data which, compared to more conventional approaches, provides significant advancements in the way that large-scale structural information in the geophysical data is accounted for. Model perturbations in the annealing procedure are made by drawing from a probability distribution for the target parameter conditioned to the geophysical data. This is the only place where geophysical information is utilized in our algorithm, which is in marked contrast to other approaches where model perturbations are made through the swapping of values in the simulation grid and agreement with soft data is enforced through a correlation coefficient constraint. Another major feature of our algorithm is the way in which available geostatistical information is utilized. Instead of constraining realizations to match a parametric target covariance model over a wide range of spatial lags, we constrain the realizations only at smaller lags where the available geophysical data cannot provide enough information. Thus we allow the larger-scale subsurface features resolved by the geophysical data to have much more due control on the output realizations. Further, since the only component of the SA objective function required in our approach is a covariance constraint at small lags, our method has improved convergence and computational efficiency over more traditional methods. Here, we present the results of applying our algorithm to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the local-scale porosity structure. Our procedure is first tested on a synthetic data set, and then applied to data collected at the Boise Hydrogeophysical Research Site.

Implicit methods for qualitative modeling of gene regulatory networks.

Advancements in high-throughput technologies to measure increasingly complex biological phenomena at the genomic level are rapidly changing the face of biological research from the single-gene single-protein experimental approach to studying the behavior of a gene in the context of the entire genome (and proteome). This shift in research methodologies has resulted in a new field of network biology that deals with modeling cellular behavior in terms of network structures such as signaling pathways and gene regulatory networks. In these networks, different biological entities such as genes, proteins, and metabolites interact with each other, giving rise to a dynamical system. Even though there exists a mature field of dynamical systems theory to model such network structures, some technical challenges are unique to biology such as the inability to measure precise kinetic information on gene-gene or gene-protein interactions and the need to model increasingly large networks comprising thousands of nodes. These challenges have renewed interest in developing new computational techniques for modeling complex biological systems. This chapter presents a modeling framework based on Boolean algebra and finite-state machines that are reminiscent of the approach used for digital circuit synthesis and simulation in the field of very-large-scale integration (VLSI). The proposed formalism enables a common mathematical framework to develop computational techniques for modeling different aspects of the regulatory networks such as steady-state behavior, stochasticity, and gene perturbation experiments.

Voltage fluctuations in IC power supply distribution

The supply voltage decrease and powerconsumption increase of modern ICs made the requirements for low voltage fluctuation caused by packaging and on-chip parasitic impedances more difficult to achieve. Most of the research works on the area assume that all the nodes of the chip are fed at thesame voltage, in such a way that the main cause of disturbance or fluctuation is the parasitic impedance of packaging. In the paper an approach to analyze the effect of high and fast current demands on the on-chip power supply network. First an approach to model the entire network by considering a homogeneous conductive foil is presented. The modification of the timing parameters of flipflops caused by spatial voltage drops through the IC surface are also investigated.

Effects of particulate matters on inflammatory markers in the general adult population

Summary: Particulate air pollution is associated with increased cardiovascular risk. The induction of systemic inflammation following particle inhalation represents a plausible mechanistic pathway. The purpose of this study was to assess the associations of short-term exposure to ambient particulate matters of aerodynamic diameter less than 10 μm (PM10) with circulating inflammatory markers in 6183 adults in Lausanne, Switzerland. The results show that short-term exposure to PM10 was associated with higher levels of circulating IL-6 and TNF-α. The positive association of PM10 with markers of systemic inflammation materializes the link between air pollution and cardiovascular risk. Background: Variations in short-term exposure to particulate matters (PM) have been repeatedly associated with daily all-cause mortality. Particle-induced inflammation has been postulated to be one of the important mechanisms for increased cardiovascular risk. Experimental in-vitro, in-vivo and controlled human studies suggest that interleukin 6 (IL-6) and tumor-necrosis-factor alpha (TNF-α) could represent key mediators of the inflammatory response to PM. The associations of short-term exposure to ambient PM with circulating inflammatory markers have been inconsistent in studies including specific subgroups so far. The epidemiological evidence linking short-term exposure to ambient PM and systemic inflammation in the general population is scarce. So far, large-scale population-based studies have not explored important inflammatory markers such as IL-6, IL-1β or TNF-α. We therefore analyzed the associations between short-term exposure to ambient PM10 and circulating levels of high-sensitive CRP (hs-CRP), IL-6, IL-1β and TNF-α in the population-based CoLaus study. Objectives: To assess the associations of short-term exposure to ambient particulate matters of aerodynamic diameter less than 10 μm (PM10) with circulating inflammatory markers, including hs-CRP, IL-6, IL-1β and TNF-α, in adults aged 35 to 75 years from the general population. Methodology: All study subjects were participants to the CoLaus study (www.colaus.ch) and the baseline examination was carried out from 2003 to 2006. Overall, 6184 participants were included. For the present analysis, 6183 participants had data on at least one of the four measured circulating inflammatory markers. The monitoring data was obtained from the website of Swiss National Air Pollution Monitoring Network (NABEL). We analyzed data on PM10 as well as outside air temperature, pressure and humidity. Hourly concentrations of PM10 were collected from 1 January 2003 to 31 December 2006. Robust linear regression (PROC ROBUSTREG) was used to evaluate the relationship between cytokine inflammatory and PM10. We adjusted all analyses for age, sex, body mass index, smoking status, alcohol consumption, diabetes status, hypertension status, education levels, zip code, and statin intake. All data were adjusted for the effects of weather by including temperature, barometric pressure, and season as covariates in the adjusted models. We performed simple and multiple logistic regression analyses. Descriptive statistical analysis used the Wilcoxon rank sum test (for medians). All data analyses were performed using SAS software (version 9.2; SAS Institute Inc., Cary, NC, USA), and a two-sided significance level of 5% was used. Results: PM10 levels averaged over 24 hours were significantly and positively associated with continuous IL-6 and TNF-α levels, in the whole study population both in unadjusted and adjusted analyses. For each cytokine, there was a similar seasonal pattern, with wider confidence intervals in summer than during the other seasons, which might partly be due to the smaller number of participants examined in summer. The associations of PM10 with IL-6 and TNF-α were also found after having dichotomized these cytokines into high versus low levels, which suggests that the associations of PM10 with the continuous cytokine levels are very robust to any distributional assumption and to potential outlier values. In contrast with what we observed for continuous IL-1β levels, high PM10 levels were significantly associated with high IL-1β. PM10 was significantly associated with IL-6 and TNF-α in men, but with TNF-α only in women. However, there was no significant statistical interaction between PM10 and sex. For IL-6 and TNF-α, the associations tended to be stronger in younger people, with a significant interaction between PM10 and age groups for IL-6. PM10 was significantly associated with IL-6 and TNF-α in the healthy group and also in the "non-healthy" group, although the statistical interaction between healthy status and PM10 was not significant. Conclusion: In summary, we found significant independent positive associations of short-term exposure to PM10 with circulating levels of IL-6 and TNF-α in the adult population of Lausanne. Our findings strongly support the idea that short-term exposure to PM10 is sufficient to induce systemic inflammation on a broad scale in the general population. From a public health perspective, the reported association of elevated inflammatory cytokines with short-term exposure to PM10 in a city with relatively clean air such as Lausanne supports the importance of limiting urban air pollution levels.