Simultaneous 3D measurement of the translation and rotation of finite size particles and the flow field in a fully developed turbulent water flow

We report a novel experimental technique that measures simultaneously in three dimensions the trajectories, the translation, and the rotation of finite size inertial particles together with the turbulent flow. The flow field is analyzed by tracking the temporal evolution of small fluorescent tracer particles. The inertial particles consist of a super-absorbent polymer that renders them index and density matched with water and thus invisible. The particles are marked by inserting at various locations tracer particles into the polymer. Translation and rotation, as well as the flow field around the particle are recovered dynamically from the analysis of the marker and tracer particle trajectories. We apply this technique to study the dynamics of inertial particles much larger in size (Rp/{\eta} \approx 100) than the Kolmogorov length scale {\eta} in a von K\'arm\'an swirling water flow (R{\lambda} \approx 400). We show, using the mixed (particle/fluid) Eulerian second order velocity structure function, that the interaction zone between the particle and the flow develops in a spherical shell of width 2Rp around the particle of radius Rp. This we interpret as an indication of a wake induced by the particle. This measurement technique has many additional advantages that will make it useful to address other problems such as particle collisions, dynamics of non-spherical solid objects, or even of wet granular matter.Comment: 18 pages, 7 figures, submitted to "Measurement Science and Technology" special issue on "Advances in 3D velocimetry

Optical spectroscopy and the nature of the insulating state of rare-earth nickelates

Using a combination of spectroscopic ellipsometry and DC transport measurements, we determine the temperature dependence of the optical conductivity of NdNiO$_3$ and SmNiO$_{3}$ films. The optical spectra show the appearance of a characteristic two-peak structure in the near-infrared when the material passes from the metal to the insulator phase. Dynamical mean-field theory calculations confirm this two-peak structure, and allow to identify these spectral changes and the associated changes in the electronic structure. We demonstrate that the insulating phase in these compounds and the associated characteristic two-peak structure are due to the combined effect of bond-disproportionation and Mott physics associated with half of the disproportionated sites. We also provide insights into the structure of excited states above the gap.Comment: 12 pages, 13 figure

Impressions de Toreros : suite de récits

Copia digital. Valladolid : Junta de Castilla y León. Consejería de Cultura y Turismo, 201

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support

<p>Abstract</p> <p>Background</p> <p>Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved.</p> <p>Method</p> <p>This paper introduces a new hybrid methodology <it>Expert-based Cooperative Analysis </it>(EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by <it>EbCA-Data Envelopment Analysis (EbCA-DEA)</it>, and 2) Case-mix of schizophrenia based on functional dependency using <it>Clustering Based on Rules (ClBR)</it>. In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases.</p> <p>Results</p> <p>EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here <it>Implicit Knowledg </it>-IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases.</p> <p>Discussion</p> <p>This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research.</p

Markov property of Lagrangian turbulence

Based on direct numerical simulations with point-like inertial particles transported by homogeneous and isotropic turbulent flows, we present evidence for the existence of Markov property in Lagrangian turbulence. We show that the Markov property is valid for a finite step size larger than a Stokes number-dependent Einstein-Markov memory length. This enables the description of multi-scale statistics of Lagrangian particles by Fokker-Planck equations, which can be embedded in an interdisciplinary approach linking the statistical description of turbulence with fluctuation theorems of non-equilibrium stochastic thermodynamics and fluctuation theorems, and local flow structures.Comment: submitted to PRL, 5 pages, 4 figure

Impacts of changes in groundwater recharge on the isotopic composition and geochemistry of seasonally ice-covered lakes: insights for sustainable management

Lakes are under increasing pressure due to widespread anthropogenic impacts related to rapid development and population growth. Accordingly, many lakes are currently undergoing a systematic decline in water quality. Recent studies have highlighted that global warming and the subsequent changes in water use may further exacerbate eutrophication in lakes. Lake evolution depends strongly on hydrologic balance, and therefore on groundwater connectivity. Groundwater also influences the sensitivity of lacustrine ecosystems to climate and environmental changes, and governs their resilience. Improved characterization of groundwater exchange with lakes is needed today for lake preservation, lake restoration, and sustainable management of lake water quality into the future. In this context, the aim of the present paper is to determine if the future evolution of the climate, the population, and the recharge could modify the geochemistry of lakes (mainly isotopic signature and quality via phosphorous load) and if the isotopic monitoring of lakes could be an efficient tool to highlight the variability of the water budget and quality. Small groundwater-connected lakes were chosen to simulate changes in water balance and water quality expected under future climate change scenarios, namely representative concentration pathways (RCPs) 4.5 and 8.5. Contemporary baseline conditions, including isotope mass balance and geochemical characteristics, were determined through an intensive field-based research program prior to the simulations. Results highlight that future lake geochemistry and isotopic composition trends will depend on four main parameters: location (and therefore climate conditions), lake catchment size (which impacts the intensity of the flux change), lake volume (which impacts the range of variation), and lake G index (i.e., the percentage of groundwater that makes up total lake inflows), the latter being the dominant control on water balance conditions, as revealed by the sensitivity of lake isotopic composition. Based on these model simulations, stable isotopes appear to be especially useful for detecting changes in recharge to lakes with a G index of between 50 and 80 %, but response is non-linear. Simulated monthly trends reveal that evolution of annual lake isotopic composition can be dampened by opposing monthly recharge fluctuations. It is also shown that changes in water quality in groundwater-connected lakes depend significantly on lake location and on the intensity of recharge change

Studies on muon tomography for archaeological internal structures scanning

International audienceMuon tomography is a potential non-invasive technique for internal structure scanning. It has already interesting applications in geophysics and can be used for archaeological purposes. Muon tomography is based on the measurement of the muon flux after crossing the structure studied. Differences on the mean density of these structures imply differences on the detected muon rate for a given direction. Based on this principle, Monte Carlo simulations represent a useful tool to provide a model of the expected muon rate and angular distribution depending on the composition of the studied object, being useful to estimate the expected detected muons and to better understand the experimental results. These simulations are mainly dependent on the geometry and composition of the studied object and on the modelling of the initial muon flux at surface. In this work, the potential of muon tomography in archaeology is presented and evaluated with Monte Carlo simulations by estimating the differences on the muon rate due to the presence of internal structures and its composition. The influence of the chosen muon model at surface in terms of energy and angular distributions in the final result has been also studied. 1. Introduction Among the different applications that muon tomography can have, the scanning of archaeological structures is one of the most innovative one. The principle of the method is straightforward. By detecting the muons that cross the studied object and reconstructing their directions, it is possible to identify the existence of significant differences in the muon rate for a given direction. These differences, consequence of a variation of the mean density of the object traversed by the muons, indicate the possible existence of an internal structure inside the object. The reconstruction of these internal structures by the analysis of the directions of the registered muons is frequently called inverse method. Some features of muon tomography are specially interesting for archaeology. It is a passive method since it is based on the detection of the atmospheric muons, which are naturally produced. Moreover, it is a non-invasive technique since the detector would be placed outside the object to study or, if possible, inside it if internal corridors and halls already exist, as i

The LISA PathFinder DMU and Radiation Monitor

The LISA PathFinder DMU (Data Management Unit) flight model was formally accepted by ESA and ASD on 11 February 2010, after all hardware and software tests had been successfully completed. The diagnostics items are scheduled to be delivered by the end of 2010. In this paper we review the requirements and performance of this instrumentation, specially focusing on the Radiation Monitor and the DMU, as well as the status of their programmed use during mission operations, on which work is ongoing at the time of writing.Comment: 11 pages, 7 figures, prepared for the Proceedings of the 8th International LISA Symposium, Classical and Quantum Gravit

The combined effects of reactant kinetics and enzyme stability explain the temperature dependence of metabolic rates

A mechanistic understanding of the response of metabolic rate to temperature is essential for understanding thermal ecology and metabolic adaptation. Although the Arrhenius equation has been used to describe the effects of temperature on reaction rates and metabolic traits, it does not adequately describe two aspects of the thermal performance curve (TPC) for metabolic rate—that metabolic rate is a unimodal function of temperature often with maximal values in the biologically relevant temperature range and that activation energies are temperature dependent. We show that the temperature dependence of metabolic rate in ectotherms is well described by an enzyme-assisted Arrhenius (EAAR) model that accounts for the temperature-dependent contribution of enzymes to decreasing the activation energy required for reactions to occur. The model is mechanistically derived using the thermodynamic rules that govern protein stability. We contrast our model with other unimodal functions that also can be used to describe the temperature dependence of metabolic rate to show how the EAAR model provides an important advance over previous work. We fit the EAAR model to metabolic rate data for a variety of taxa to demonstrate the model’s utility in describing metabolic rate TPCs while revealing significant differences in thermodynamic properties across species and acclimation temperatures. Our model advances our ability to understand the metabolic and ecological consequences of increases in the mean and variance of temperature associated with global climate change. In addition, the model suggests avenues by which organisms can acclimate and adapt to changing thermal environments. Furthermore, the parameters in the EAAR model generate links between organismal level performance and underlying molecular processes that can be tested for in future work

Probing quantum and classical turbulence analogy through global bifurcations in a von K\'arm\'an liquid Helium experiment

We report measurements of the dissipation in the Superfluid Helium high REynold number von Karman flow (SHREK) experiment for different forcing conditions, through a regime of global hysteretic bifurcation. Our macroscopical measurements indicate no noticeable difference between the classical fluid and the superfluid regimes, thereby providing evidence of the same dissipative anomaly and response to asymmetry in fluid and superfluid regime. %In the latter case, A detailed study of the variations of the hysteretic cycle with Reynolds number supports the idea that (i) the stability of the bifurcated states of classical turbulence in this closed flow is partly governed by the dissipative scales and (ii) the normal and the superfluid component at these temperatures (1.6K) are locked down to the dissipative length scale.Comment: 5 pages, 5 figure