A new method to estimate the infilling of alluvial sediment of glacial valleys using a sloping local base level

A new method is used to estimate the volumes of sediments of glacial valleys. This method is based on the concept of sloping local base level and requires only a digital terrain model and the limits of the alluvial valleys as input data. The bedrock surface of the glacial valley is estimated by a progressive excavation of the digital elevation model (DEM) of the filled valley area. This is performed using an iterative routine that replaces the altitude of a point of the DEM by the mean value of its neighbors minus a fixed value. The result is a curved surface, quadratic in 2D. The bedrock surface of the Rhone Valley in Switzerland was estimated by this method using the free digital terrain model Shuttle Radar Topography Mission (SRTM) (~92 m resolution). The results obtained are in good agreement with the previous estimations based on seismic profiles and gravimetric modeling, with the exceptions of some particular locations. The results from the present method and those from the seismic interpretation are slightly different from the results of the gravimetric data. This discrepancy may result from the presence of large buried landslides in the bottom of the Rhone Valley.

Investigation of the Reproductibility of Third-Level Characteristics

The process of comparing a fingermark recovered from a crime scene with the fingerprint taken from a known individual involves the characterization and comparison of different ridge details on both the mark and the print. Fingerprints examiners commonly classify these characteristics into three different groups, depending on their level of discriminating power. It is commonly considered that the general pattern of the ridge flow constitutes first-level detail, specific ridge flow and minutiaes (e.g. ending ridges, bifurcations) constitutes second-level detail, and fine ridge details (e. g. pore positions and shapes) are described as third-level details.In this study, the reproducibility of a selection of third-level characteristics is investigated. The reproducibility of these features is examined on serveral recordings of a same finger, first acquired using only optical visualization techniques and second on impressions developed using common firngermark development techniques. Prior to the evaluation of the reproducibility of the considered characteristics, digital images of the fingerprints were recorded at two different resolutions (1000 and 2000 ppi). This allowed the study to also examine the influence of higher resolution on the considered characteristics. It was observed that the increase in the resolution did not result in better feature detection or comparison between images.The examination of the reproducibility of a selection of third-level characteristics showed that the most reproducible features observed were minutiae shapes and pore positions along the ridges.

Variations of the carcinoembryonic antigen level in the plasma of patients with gynecologie cancers during therapy

In 63 patients with histologically proved gynecologie carcinoma, circulating carcinoembryonic antigen (CEA) was determined by radioimmunoassay before and at two intervals after treatment. Thirty-one patients of 63 had CEA values over 2.5 ng. per milliliter before treatment. In general, the CEA levels were low compared to those found in endodermal carcinoma. The percentage of elevated CEA values was slightly higher in cases of carcinoma of the cervix and corpus uteri than in those of carcinoma of the ovary. All patients with CEA levels greater than 2.5 ng. per milliliter treated by complete surgical resection of tumor showed a drop of CEA levels to below 2.5 ng. per milliliter seven weeks after operation. In contrast, patients with palliative therapy showed no change in CEA values. About half of the patients treated with a complete course of internal and external radiotherapy showed a drop of CEA levels to below 2.5 ng. per milliliter, whereas the other patients showed fluctuating CEA values. No correlation between clinical status and evolution of CEA levels in these patients could be drawn at the present time. The CEA test seems to be of little value for the earl of diagnosis of gynecologie carcinoma but appears to be interesting for the evaluation of therapy and the follow-up of patients with diagnosed cases.

Coagulation Factor Xa Activates Thrombin and Signals Ischemic Neuronal Death Via Par-1 and JNK in Ischemic Neural Tissue

Background: The coagulation factor thrombin mediates ischemic neuronal deathand, at a low concentration, induces tolerance to ischemia.We investigated its modeof activation in ischemic neural tissue using an in vitro approach to distinguish therole of circulating coagulation factors from endogenous cerebral mechanisms. Wealso studied the signalling pathway downstream of thrombin in ischemia and afterthrombin preconditioning.Methods: Rat organotypic hippocampal slice cultures to 30 minute oxygen (5%)and glucose (1 mmol/L) deprivation (OGD).Results: Selective factor Xa (FXa) inhibition by fondaparinux during and afterOGD significantly reduced neuronal death in the CA1 after 48 hours. Thrombinactivity was increased in the medium 24 hours after OGD and this increasewas prevented by fondaparinux suggesting that FXa catalyzes the conversion ofprothrombin to thrombin in neural tissue after ischemia in vitro. Treatment withSCH79797, a selective antagonist of the thrombin receptor protease activatedreceptor-1 (PAR-1), significantly decreased neuronal cell death indicating thatthrombin signals ischemic damage via PAR-1. The JNK pathway plays an importantrole in cerebral ischemia and we observed activation of the JNK substrate,c-Jun in our model. Both the FXa inhibitor, fondaparinux and the PAR-1 antagonistSCH79797, decreased the level of phospho-c-Jun Ser73. After thrombin preconditioningc-Jun was activated by phosphorylation in the nuclei of neurons of the CA1.Treatment with a synthetic thrombin receptor agonist resulted in the same c-Junactivation profile and protection against subsequent OGD indicating that thrombinalso signals via PAR-1 and c-Jun in cell protection.Conclusion: These results indicate that FXa activates thrombin in cerebral ischemia,leading via PAR-1 to the activation of the JNK pathway resulting in neuronal death.Thrombin induced tolerance also involves PAR-1 and JNK, revealing commonfeatures in cell death and survival signalling.

Estrogen receptor level determines sex-specific in vitro transcription from the Xenopus vitellogenin promoter.

Female-specific expression of the Xenopus laevis vitellogenin gene was reconstituted in vitro by addition of recombinant vaccinia-virus-produced estrogen receptor to nuclear extracts from male livers, in which this gene is silent. Transcription enhancement was at least 30 times and was selectively restricted to vitellogenin templates containing the estrogen-responsive unit. Thus, in male hepatocytes, estrogen receptor is the limiting regulatory factor that in the female liver controls efficient and accurate sex-specific expression of the vitellogenin gene. Furthermore, the Xenopus liver factor B, which is essential in addition to the estrogen receptor for the activation of this gene, was successfully replaced in the Xenopus extract by purified human nuclear factor I, identifying factor B of Xenopus as a functional homolog of this well-characterized human transcription factor.

SDF 1-alpha (CXCL12) triggers glutamate exocytosis from astrocytes on a millisecond time scale: Imaging analysis at the single-vesicle level with TIRF microscopy

Chemokines are small chemotactic molecules widely expressed throughout the central nervous system. A number of papers, during the past few years, have suggested that they have physiological functions in addition to their roles in neuroinflammatory diseases. In this context, the best evidence concerns the CXC-chemokine stromal cell-derived factor (SDF-1alpha or CXCL12) and its receptor CXCR4, whose signalling cascade is also implicated in the glutamate release process from astrocytes. Recently, astrocytic synaptic like microvesicles (SLMVs) that express vesicular glutamate transporters (VGLUTs) and are able to release glutamate by Ca(2+)-dependent regulated exocytosis, have been described both in tissue and in cultured astrocytes. Here, in order to elucidate whether SDF-1alpha/CXCR4 system can participate to the brain fast communication systems, we investigated whether the activation of CXCR4 receptor triggers glutamate exocytosis in astrocytes. By using total internal reflection (TIRF) microscopy and the membrane-fluorescent styryl dye FM4-64, we adapted an imaging methodology recently developed to measure exocytosis and recycling in synaptic terminals, and monitored the CXCR4-mediated exocytosis of SLMVs in astrocytes. We analyzed the co-localization of VGLUT with the FM dye at single-vesicle level, and observed the kinetics of the FM dye release during single fusion events. We found that the activation of CXCR4 receptors triggered a burst of exocytosis on a millisecond time scale that involved the release of Ca(2+) from internal stores. These results support the idea that astrocytes can respond to external stimuli and communicate with the neighboring cells via fast release of glutamate.

ConnectomeViewer - Multi-Modal Multi-Level Network Visualization and Analysis.

Introduction: The field of Connectomic research is growing rapidly, resulting from methodological advances in structural neuroimaging on many spatial scales. Especially progress in Diffusion MRI data acquisition and processing made available macroscopic structural connectivity maps in vivo through Connectome Mapping Pipelines (Hagmann et al, 2008) into so-called Connectomes (Hagmann 2005, Sporns et al, 2005). They exhibit both spatial and topological information that constrain functional imaging studies and are relevant in their interpretation. The need for a special-purpose software tool for both clinical researchers and neuroscientists to support investigations of such connectome data has grown. Methods: We developed the ConnectomeViewer, a powerful, extensible software tool for visualization and analysis in connectomic research. It uses the novel defined container-like Connectome File Format, specifying networks (GraphML), surfaces (Gifti), volumes (Nifti), track data (TrackVis) and metadata. Usage of Python as programming language allows it to by cross-platform and have access to a multitude of scientific libraries. Results: Using a flexible plugin architecture, it is possible to enhance functionality for specific purposes easily. Following features are already implemented: * Ready usage of libraries, e.g. for complex network analysis (NetworkX) and data plotting (Matplotlib). More brain connectivity measures will be implemented in a future release (Rubinov et al, 2009). * 3D View of networks with node positioning based on corresponding ROI surface patch. Other layouts possible. * Picking functionality to select nodes, select edges, get more node information (ConnectomeWiki), toggle surface representations * Interactive thresholding and modality selection of edge properties using filters * Arbitrary metadata can be stored for networks, thereby allowing e.g. group-based analysis or meta-analysis. * Python Shell for scripting. Application data is exposed and can be modified or used for further post-processing. * Visualization pipelines using filters and modules can be composed with Mayavi (Ramachandran et al, 2008). * Interface to TrackVis to visualize track data. Selected nodes are converted to ROIs for fiber filtering The Connectome Mapping Pipeline (Hagmann et al, 2008) processed 20 healthy subjects into an average Connectome dataset. The Figures show the ConnectomeViewer user interface using this dataset. Connections are shown that occur in all 20 subjects. The dataset is freely available from the homepage (connectomeviewer.org). Conclusions: The ConnectomeViewer is a cross-platform, open-source software tool that provides extensive visualization and analysis capabilities for connectomic research. It has a modular architecture, integrates relevant datatypes and is completely scriptable. Visit www.connectomics.org to get involved as user or developer.

Des services adaptés aux adolescents, à quel prix. [What services do we adapt to adolescents and at what price?].

http://rms.medhyg.ch/numero-253-page-1227.htm

HIV rebounds from latently infected cells, rather than from continuing low-level replication.

Rapid rebound of plasma viremia in patients after interruption of long-term combination antiretroviral therapy (cART) suggests persistence of low-level replicating cells or rapid reactivation of latently infected cells. To further characterize rebounding virus, we performed extensive longitudinal clonal evolutionary studies of HIV env C2-V3-C3 regions and exploited the temporal relationships of rebounding plasma viruses with regard to pretreatment sequences in 20 chronically HIV-1-infected patients having undergone multiple 2-week structured treatment interruptions (STI). Rebounding virus during the short STI was homogeneous, suggesting mono- or oligoclonal origin during reactivation. No evidence for a temporal structure of rebounding virus in regard to pretreatment sequences was found. Furthermore, expansion of distinct lineages at different STI cycles emerged. Together, these findings imply stochastic reactivation of different clones from long-lived latently infected cells rather than expansion of viral populations replicating at low levels. After treatment was stopped, diversity increased steadily, but pretreatment diversity was, on average, achieved only >2.5 years after the start of STI when marked divergence from preexisting quasispecies also emerged. In summary, our results argue against persistence of ongoing low-level replication in patients on suppressive cART. Furthermore, a prolonged delay in restoration of pretreatment viral diversity after treatment interruption demonstrates a surprisingly sustained evolutionary bottleneck induced by punctuated antiretroviral therapy.

Behavioural queueing : cellular automata and a laboratory experiment

Dans cette thèse, nous étudions les aspects comportementaux d'agents qui interagissent dans des systèmes de files d'attente à l'aide de modèles de simulation et de méthodologies expérimentales. Chaque période les clients doivent choisir un prestataire de servivce. L'objectif est d'analyser l'impact des décisions des clients et des prestataires sur la formation des files d'attente. Dans un premier cas nous considérons des clients ayant un certain degré d'aversion au risque. Sur la base de leur perception de l'attente moyenne et de la variabilité de cette attente, ils forment une estimation de la limite supérieure de l'attente chez chacun des prestataires. Chaque période, ils choisissent le prestataire pour lequel cette estimation est la plus basse. Nos résultats indiquent qu'il n'y a pas de relation monotone entre le degré d'aversion au risque et la performance globale. En effet, une population de clients ayant un degré d'aversion au risque intermédiaire encoure généralement une attente moyenne plus élevée qu'une population d'agents indifférents au risque ou très averses au risque. Ensuite, nous incorporons les décisions des prestataires en leur permettant d'ajuster leur capacité de service sur la base de leur perception de la fréquence moyenne d'arrivées. Les résultats montrent que le comportement des clients et les décisions des prestataires présentent une forte "dépendance au sentier". En outre, nous montrons que les décisions des prestataires font converger l'attente moyenne pondérée vers l'attente de référence du marché. Finalement, une expérience de laboratoire dans laquelle des sujets jouent le rôle de prestataire de service nous a permis de conclure que les délais d'installation et de démantèlement de capacité affectent de manière significative la performance et les décisions des sujets. En particulier, les décisions du prestataire, sont influencées par ses commandes en carnet, sa capacité de service actuellement disponible et les décisions d'ajustement de capacité qu'il a prises, mais pas encore implémentées. - Queuing is a fact of life that we witness daily. We all have had the experience of waiting in line for some reason and we also know that it is an annoying situation. As the adage says "time is money"; this is perhaps the best way of stating what queuing problems mean for customers. Human beings are not very tolerant, but they are even less so when having to wait in line for service. Banks, roads, post offices and restaurants are just some examples where people must wait for service. Studies of queuing phenomena have typically addressed the optimisation of performance measures (e.g. average waiting time, queue length and server utilisation rates) and the analysis of equilibrium solutions. The individual behaviour of the agents involved in queueing systems and their decision making process have received little attention. Although this work has been useful to improve the efficiency of many queueing systems, or to design new processes in social and physical systems, it has only provided us with a limited ability to explain the behaviour observed in many real queues. In this dissertation we differ from this traditional research by analysing how the agents involved in the system make decisions instead of focusing on optimising performance measures or analysing an equilibrium solution. This dissertation builds on and extends the framework proposed by van Ackere and Larsen (2004) and van Ackere et al. (2010). We focus on studying behavioural aspects in queueing systems and incorporate this still underdeveloped framework into the operations management field. In the first chapter of this thesis we provide a general introduction to the area, as well as an overview of the results. In Chapters 2 and 3, we use Cellular Automata (CA) to model service systems where captive interacting customers must decide each period which facility to join for service. They base this decision on their expectations of sojourn times. Each period, customers use new information (their most recent experience and that of their best performing neighbour) to form expectations of sojourn time at the different facilities. Customers update their expectations using an adaptive expectations process to combine their memory and their new information. We label "conservative" those customers who give more weight to their memory than to the xiv Summary new information. In contrast, when they give more weight to new information, we call them "reactive". In Chapter 2, we consider customers with different degree of risk-aversion who take into account uncertainty. They choose which facility to join based on an estimated upper-bound of the sojourn time which they compute using their perceptions of the average sojourn time and the level of uncertainty. We assume the same exogenous service capacity for all facilities, which remains constant throughout. We first analyse the collective behaviour generated by the customers' decisions. We show that the system achieves low weighted average sojourn times when the collective behaviour results in neighbourhoods of customers loyal to a facility and the customers are approximately equally split among all facilities. The lowest weighted average sojourn time is achieved when exactly the same number of customers patronises each facility, implying that they do not wish to switch facility. In this case, the system has achieved the Nash equilibrium. We show that there is a non-monotonic relationship between the degree of risk-aversion and system performance. Customers with an intermediate degree of riskaversion typically achieve higher sojourn times; in particular they rarely achieve the Nash equilibrium. Risk-neutral customers have the highest probability of achieving the Nash Equilibrium. Chapter 3 considers a service system similar to the previous one but with risk-neutral customers, and relaxes the assumption of exogenous service rates. In this sense, we model a queueing system with endogenous service rates by enabling managers to adjust the service capacity of the facilities. We assume that managers do so based on their perceptions of the arrival rates and use the same principle of adaptive expectations to model these perceptions. We consider service systems in which the managers' decisions take time to be implemented. Managers are characterised by a profile which is determined by the speed at which they update their perceptions, the speed at which they take decisions, and how coherent they are when accounting for their previous decisions still to be implemented when taking their next decision. We find that the managers' decisions exhibit a strong path-dependence: owing to the initial conditions of the model, the facilities of managers with identical profiles can evolve completely differently. In some cases the system becomes "locked-in" into a monopoly or duopoly situation. The competition between managers causes the weighted average sojourn time of the system to converge to the exogenous benchmark value which they use to estimate their desired capacity. Concerning the managers' profile, we found that the more conservative Summary xv a manager is regarding new information, the larger the market share his facility achieves. Additionally, the faster he takes decisions, the higher the probability that he achieves a monopoly position. In Chapter 4 we consider a one-server queueing system with non-captive customers. We carry out an experiment aimed at analysing the way human subjects, taking on the role of the manager, take decisions in a laboratory regarding the capacity of a service facility. We adapt the model proposed by van Ackere et al (2010). This model relaxes the assumption of a captive market and allows current customers to decide whether or not to use the facility. Additionally the facility also has potential customers who currently do not patronise it, but might consider doing so in the future. We identify three groups of subjects whose decisions cause similar behavioural patterns. These groups are labelled: gradual investors, lumpy investors, and random investor. Using an autocorrelation analysis of the subjects' decisions, we illustrate that these decisions are positively correlated to the decisions taken one period early. Subsequently we formulate a heuristic to model the decision rule considered by subjects in the laboratory. We found that this decision rule fits very well for those subjects who gradually adjust capacity, but it does not capture the behaviour of the subjects of the other two groups. In Chapter 5 we summarise the results and provide suggestions for further work. Our main contribution is the use of simulation and experimental methodologies to explain the collective behaviour generated by customers' and managers' decisions in queueing systems as well as the analysis of the individual behaviour of these agents. In this way, we differ from the typical literature related to queueing systems which focuses on optimising performance measures and the analysis of equilibrium solutions. Our work can be seen as a first step towards understanding the interaction between customer behaviour and the capacity adjustment process in queueing systems. This framework is still in its early stages and accordingly there is a large potential for further work that spans several research topics. Interesting extensions to this work include incorporating other characteristics of queueing systems which affect the customers' experience (e.g. balking, reneging and jockeying); providing customers and managers with additional information to take their decisions (e.g. service price, quality, customers' profile); analysing different decision rules and studying other characteristics which determine the profile of customers and managers.

Enhanced compressed sensing recovery with level set normals.

We propose a compressive sensing algorithm that exploits geometric properties of images to recover images of high quality from few measurements. The image reconstruction is done by iterating the two following steps: 1) estimation of normal vectors of the image level curves, and 2) reconstruction of an image fitting the normal vectors, the compressed sensing measurements, and the sparsity constraint. The proposed technique can naturally extend to nonlocal operators and graphs to exploit the repetitive nature of textured images to recover fine detail structures. In both cases, the problem is reduced to a series of convex minimization problems that can be efficiently solved with a combination of variable splitting and augmented Lagrangian methods, leading to fast and easy-to-code algorithms. Extended experiments show a clear improvement over related state-of-the-art algorithms in the quality of the reconstructed images and the robustness of the proposed method to noise, different kind of images, and reduced measurements.