Assessment Of The Sensitivity Of GompitZ

Decision support for sewer rehabilitation programs is dependent on reliable information about the asset conditions. Inference about the condition development can be made by combining condition observations with deterioration forecasting models. GompitZ is a Non-Homogenous Markov Chain model, which enables waste water utilities to predict the sewer deterioration at a network segment level, based on closed-circuit TV (CCTV) inspection and normalized condition grading. The predictions can be used to assess investment needs for the sewer systems. Successful calibration and prediction is however dependent on the validity of the model assumptions, sufficient amounts of CCTV observations, and that the condition grading system used is capable of describing the actual sewer conditions. In this work, Monte Carlo simulations are used to assess the sensitivity of GompitZ calibration results with respect to available input data. The simulations are performed by starting with a full dataset of observations, and randomly selecting a subset from the full dataset. By repeating the calibration process many times for random subsets of equal size, one can assess the distribution of the model parameters and the uncertainty in the output from GompitZ. The sensitivity analysis is performed both on a real (Oslo municipality) and a virtual dataset. GompitZ uses a simplified Mixed Generalized Linear Regression technique, and the sensitivity results can be used to draw several conclusions about this calibration method and possible ways to improve it, as well as about the predictive capabilities of the model. Practical learnt lessons are expected, as for assessing: The inherent uncertainty in sewer conditions; i.e. at what point increased amounts of CCTV observations does not help to reduce the prediction uncertainty How the uncertainty in the predictions develops as the amount of data reduces The critical number of observations needed in order to achieve a successful calibration with Gompit

Interactions between groundwater and surface water at river banks and the confluence of rivers

Riparian vegetation depends on hydrological resources and has to adapt to changes in water levels and soil moisture conditions. The origin and mixing of water in the streamside corridor were studied in detail. The development of riparian woodland often reflects the evolution of hydrological events. River water levels and topography are certainly the main causes of the exchange between groundwater and river water through the riverbank. Stable isotopes, such as 18O, are useful tools that allow water movement to be traced. Two main water sources are typically present: (i) river water, depleted of heavy isotopes, originating upstream, and (ii) groundwater, which comes mainly from the local rainfall. On the Garonne River bank field site downstream of Toulouse, the mixing of these two waters is variable, and depends mainly on the river level and the geographical position. The output of the groundwater into the river water is not diffuse on a large scale, but localised at few places. At the confluence of two rivers, the water-mixing area is more complex because of the presence of a third source of water. In this situation, groundwater supports the hydrologic pressure of both rivers until they merge, this pressure could influence its outflow. Two cases will be presented. The first is the confluence of the Garonne and the Ariège Rivers in the south-west of France, both rivers coming from the slopes of the Pyrénées mountains. Localised groundwater outputs have been detected about 200 m before the confluence. The second case presented is the confluence of the Ganges and the Yamuna Rivers in the north of India, downstream of the city of Allahabad. These rivers are the two main tributaries of the Ganges, and both originate in the Himalayas. A strong stream of groundwater output was measured at the point of confluence

Understanding the leakage process for multi-scale water infrastructure asset management: necessity for a dialogue between sociological and data sciences

Reducing water losses is one of the most pressing issues for modern water utilities. To that end, improving the efficiency of the pipe leakage and repair process and aiding the selection of the pipes that are to be renewed or rehabilitated are essential. To help addressing these tasks, in this work, we develop a model predicting the probability of a pipe to be leaking. This work is set the context of a multidisciplinary project with Soci{\'e}t{\'e} Wallone des Eaux and it is aligned with their goal to improve their Infrastructure Asset Management in the short and the long terms. Developing and feeding this leakage probability model relies on an intense data processing phase, mobilizing data and water engineering sciences, since the raw data from SWDE is not ready to be used in the model. Complementarily, we thus employ techniques from sociology (e.g., interviews, analyses of the human/non-human actors and of the tools, sociotechnical translations) in order to complete the data, to improve our understanding of its production, and to increase its value and its availability for the prediction of the pipe leakage probability. This model will be implemented in SWDE's information system and used for strategies to reduce water losses

Muon spin relaxation studies of incommensurate magnetism and superconductivity in stage-4 La2_{2}CuO4.11_{4.11} and La1.88_{1.88}Sr0.12_{0.12}CuO4_{4}

This paper reports muon spin relaxation (MuSR) measurements of two single crystals of the title high-Tc cuprate systems where static incommensurate magnetism and superconductivity coexist. By zero-field MuSR measurements and subsequent analyses with simulations, we show that (1) the maximum ordered Cu moment size (0.36 Bohr magneton) and local spin structure are identical to those in prototypical stripe spin systems with the 1/8 hole concentration; (2) the static magnetism is confined to less than a half of the volume of the sample, and (3) regions with static magnetism form nano-scale islands with the size comparable to the in-plane superconducting coherence length. By transverse-field MuSR measurements, we show that Tc of these systems is related to the superfluid density, in the same way as observed in cuprate systems without static magnetism. We discuss a heuristic model involving percolation of these nanoscale islands with static magnetism as a possible picture to reconcile heterogeneity found by the present MuSR study and long-range spin correlations found by neutron scattering.Comment: 19 pages, 15 figures, submitted to Phys. Rev. B. E-mail: [email protected]

Particles and fields in fluid turbulence

The understanding of fluid turbulence has considerably progressed in recent years. The application of the methods of statistical mechanics to the description of the motion of fluid particles, i.e. to the Lagrangian dynamics, has led to a new quantitative theory of intermittency in turbulent transport. The first analytical description of anomalous scaling laws in turbulence has been obtained. The underlying physical mechanism reveals the role of statistical integrals of motion in non-equilibrium systems. For turbulent transport, the statistical conservation laws are hidden in the evolution of groups of fluid particles and arise from the competition between the expansion of a group and the change of its geometry. By breaking the scale-invariance symmetry, the statistically conserved quantities lead to the observed anomalous scaling of transported fields. Lagrangian methods also shed new light on some practical issues, such as mixing and turbulent magnetic dynamo.Comment: 165 pages, review article for Rev. Mod. Phy

Quantum Field Theory in the Large N Limit: a review

We review the solutions of O(N) and U(N) quantum field theories in the large $N$ limit and as 1/N expansions, in the case of vector representations. Since invariant composite fields have small fluctuations for large $N$, the method relies on constructing effective field theories for composite fields after integration over the original degrees of freedom. We first solve a general scalar U(\phib^2) field theory for $N$ large and discuss various non-perturbative physical issues such as critical behaviour. We show how large $N$ results can also be obtained from variational calculations.We illustrate these ideas by showing that the large $N$ expansion allows to relate the (\phib^2)^2 theory and the non-linear $\sigma$-model, models which are renormalizable in different dimensions. Similarly, a relation between $CP(N-1)$ and abelian Higgs models is exhibited. Large $N$ techniques also allow solving self-interacting fermion models. A relation between the Gross--Neveu, a theory with a four-fermi self-interaction, and a Yukawa-type theory renormalizable in four dimensions then follows. We discuss dissipative dynamics, which is relevant to the approach to equilibrium, and which in some formulation exhibits quantum mechanics supersymmetry. This also serves as an introduction to the study of the 3D supersymmetric quantum field theory. Large $N$ methods are useful in problems that involve a crossover between different dimensions. We thus briefly discuss finite size effects, finite temperature scalar and supersymmetric field theories. We also use large $N$ methods to investigate the weakly interacting Bose gas. The solution of the general scalar U(\phib^2) field theory is then applied to other issues like tricritical behaviour and double scaling limit.Comment: Review paper: 200 pages, 13 figure

Illuminating hydrological processes at the soil-vegetation-atmosphere interface with water stable isotopes

Funded by DFG research project “From Catchments as Organised Systems to Models based on Functional Units” (FOR 1Peer reviewedPublisher PDFPublisher PD

Genetic regulation of pituitary gland development in human and mouse

Normal hypothalamopituitary development is closely related to that of the forebrain and is dependent upon a complex genetic cascade of transcription factors and signaling molecules that may be either intrinsic or extrinsic to the developing Rathke’s pouch. These factors dictate organ commitment, cell differentiation, and cell proliferation within the anterior pituitary. Abnormalities in these processes are associated with congenital hypopituitarism, a spectrum of disorders that includes syndromic disorders such as septo-optic dysplasia, combined pituitary hormone deficiencies, and isolated hormone deficiencies, of which the commonest is GH deficiency. The highly variable clinical phenotypes can now in part be explained due to research performed over the last 20 yr, based mainly on naturally occurring and transgenic animal models. Mutations in genes encoding both signaling molecules and transcription factors have been implicated in the etiology of hypopituitarism, with or without other syndromic features, in mice and humans. To date, mutations in known genes account for a small proportion of cases of hypopituitarism in humans. However, these mutations have led to a greater understanding of the genetic interactions that lead to normal pituitary development. This review attempts to describe the complexity of pituitary development in the rodent, with particular emphasis on those factors that, when mutated, are associated with hypopituitarism in humans

The Vitamin D Receptor Is a Wnt Effector that Controls Hair Follicle Differentiation and Specifies Tumor Type in Adult Epidermis

We have investigated how Wnt and vitamin D receptor signals regulate epidermal differentiation. Many epidermal genes induced by β-catenin, including the stem cell marker keratin 15, contain vitamin D response elements (VDREs) and several are induced independently of TCF/Lef. The VDR is required for β-catenin induced hair follicle formation in adult epidermis, and the vitamin D analog EB1089 synergises with β-catenin to stimulate hair differentiation. Human trichofolliculomas (hair follicle tumours) are characterized by high nuclear β-catenin and VDR, whereas infiltrative basal cell carcinomas (BCCs) have high β-catenin and low VDR levels. In mice, EB1089 prevents β-catenin induced trichofolliculomas, while in the absence of VDR β-catenin induces tumours resembling BCCs. We conclude that VDR is a TCF/Lef-independent transcriptional effector of the Wnt pathway and that vitamin D analogues have therapeutic potential in tumors with inappropriate activation of Wnt signalling