Sensitivity and identifiability of hydraulic and geophysical parameters from streaming potential signals in unsaturated porous media

Fluid flow in a charged porous medium generates electric potentials called streaming potential (SP). The SP signal is related to both hydraulic and electrical properties of the soil. In this work, global sensitivity analysis (GSA) and parameter estimation procedures are performed to assess the influence of hydraulic and geophysical parameters on the SP signals and to investigate the identifiability of these parameters from SP measurements. Both procedures are applied to a synthetic column experiment involving a falling head infiltration phase followed by a drainage phase.GSA is used through variance-based sensitivity indices, calculated using sparse polynomial chaos expansion (PCE). To allow high PCE orders, we use an efficient sparse PCE algorithm which selects the best sparse PCE from a given data set using the Kashyap information criterion (KIC). Parameter identifiability is performed using two approaches: the Bayesian approach based on the Markov chain Monte Carlo (MCMC) method and the first-order approximation (FOA) approach based on the Levenberg–Marquardt algorithm. The comparison between both approaches allows us to check whether FOA can provide a reliable estimation of parameters and associated uncertainties for the highly nonlinear hydrogeophysical problem investigated.GSA results show that in short time periods, the saturated hydraulic conductivity (Ks) and the voltage coupling coefficient at saturation Csat are the most influential parameters, whereas in long time periods, the residual water content (θs), the Mualem–van Genuchten parameter n and the Archie saturation exponent na become influential, with strong interactions between them. The Mualem–van Genuchten parameter α has a very weak influence on the SP signals during the whole experiment.Results of parameter estimation show that although the studied problem is highly nonlinear, when several SP data collected at different altitudes inside the column are used to calibrate the model, all hydraulic (Ks, θs, α, n) and geophysical parameters (na, Csat) can be reasonably estimated from the SP measurements. Further, in this case, the FOA approach provides accurate estimations of both mean parameter values and uncertainty regions. Conversely, when the number of SP measurements used for the calibration is strongly reduced, the FOA approach yields accurate mean parameter values (in agreement with MCMC results) but inaccurate and even unphysical confidence intervals for parameters with large uncertainty regions.</p

Bilateral stellate neuroretinitis revealing a pheochromocytoma

Neuroretinitis (NR) is an inflammatory disorder characterized by optic disc  edema and subsequent formation of a macular star. We present a case of a 33 year old woman patient admitted for a progressive bilateral visual loss since two weeks. Fundus examination showed bilateral stellate neuroretinitis. Physical examination revealed a malignant hypertension of 210/150mmHg. Magnetic resonance imaging identified a left suprarenal mass, whereas urinary catecholamine level was abnormally high which supported a diagnosis of pheochromocytoma.The patient underwent a laparoscopic left suprarenal adrenalectomy after successful control of blood pressure. histopathologic examination confirmed the diagnosis of pheochromocytoma. Visual acuity was restored and the retinal alterations disappeared 7 months after surgery

Isocyanurate transformation induced healing of isocyanurate–oxazolidone polymers

Isocyanurate–oxazolidone (ISOX) polymers have been reported as a novel, intrinsically self‐healable thermoset, and their healing mechanism under the effect of nucleophiles, such as tertiary amines and pyridines during polymerization, is thoroughly investigated in this study. This work provides evidence that the healing behavior of the polymers results part from the transformation of isocyanurate to oxazolidone on the fracture surfaces of the ISOX polymers at elevated temperatures. The isocyanurate transformation is characterized by chemical composition of the ISOX polymers before and after a predetermined healing procedure, through a combination characterization of Fourier transform infrared spectroscopy and carbon nuclear magnetic resonance spectroscopy. From the chemical composition of the ISOX polymers, an increased oxazolidone fraction is observed after the healing event, which verifies the hypothesized healing mechanism. By correlating the change in oxazolidone fraction in the polymers during the healing event, with the corresponding healing performance of the polymers, healing efficiencies of the polymers are shown to be inversely proportional to the ratio of oxazolidone to isocyanurate in the polymers. The transformation to oxazolidone is also shown to be dependent on two variables, nucleophilicity of the polymerization catalyst and duration of the postcure. The isocyanate and epoxide polymerization mechanism in the presence of nucleophiles is also investigated to explain the effect of the catalyst nucleophilicity on the chemical composition as well as the healing performance of the ISOX polymers. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019, 137, 48698.Isocyanurate‐to‐oxazolidone transformation within the polymers for healing.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154270/1/app48695-sup-0001-FigureS1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154270/2/app48698_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154270/3/app48698.pd

Un-reduction

This paper provides a full geometric development of a new technique called un-reduction, for dealing with dynamics and optimal control problems posed on spaces that are unwieldy for numerical implementation. The technique, which was originally concieved for an application to image dynamics, uses Lagrangian reduction by symmetry in reverse. A deeper understanding of un-reduction leads to new developments in image matching which serve to illustrate the mathematical power of the technique.Comment: 25 pages, revised versio

Metabolic Alterations in Obstructive Jaundice: Effect of Duration of Jaundice and Bile-Duct Decompression

We examined the effect of prolonged bile duct obstruction, and subsequent biliary decompression, on biochemical and metabolic parameters, using a reversible jaundice model in male Fischer 344 rats. The animals were studied after biliary obstruction for varying periods (4 days, one week, and two weeks) and following decompression. They were sacrificed one or two weeks following decompression. All the rats were compared to sham operated, pair-fed, controls. Obstructive jaundice rapidly increased bilirubin, liver enzymes, serum free fatty acid, and triglyceride levels. Glucose levels were significantly decreased in the jaundice rats compared to their pair-fed controls. Only after two weeks of jaundice was significant hypoalbuminemia observed. Following decompression, all biochemical and metabolic values gradually returned to normal levels, except for albumin. Hypoalbuminemia was not reversed within the two-week post-decompression period. The rats jaundiced for two weeks had significantly higher mortality, compared to the other groups. We conclude that prolonged jaundice adversely affects the metabolic capacity of the rats, with albumin concentration being markedly decreased, and that biliary decompression could not reverse completely all the alterations seen with cholestasis, especially following two weeks of bile duct obstruction

Should We Learn Probabilistic Models for Model Checking? A New Approach and An Empirical Study

Many automated system analysis techniques (e.g., model checking, model-based testing) rely on first obtaining a model of the system under analysis. System modeling is often done manually, which is often considered as a hindrance to adopt model-based system analysis and development techniques. To overcome this problem, researchers have proposed to automatically "learn" models based on sample system executions and shown that the learned models can be useful sometimes. There are however many questions to be answered. For instance, how much shall we generalize from the observed samples and how fast would learning converge? Or, would the analysis result based on the learned model be more accurate than the estimation we could have obtained by sampling many system executions within the same amount of time? In this work, we investigate existing algorithms for learning probabilistic models for model checking, propose an evolution-based approach for better controlling the degree of generalization and conduct an empirical study in order to answer the questions. One of our findings is that the effectiveness of learning may sometimes be limited.Comment: 15 pages, plus 2 reference pages, accepted by FASE 2017 in ETAP

High-Resolution X-Ray Spectroscopy of the Bursting Pulsar GRO J1744-28

The bursting pulsar GRO J1744-28 is a Galactic low-mass X-ray binary that distinguishes itself by displaying type-II X-ray bursts: brief, bright flashes of X-ray emission that likely arise from spasmodic accretion. Combined with its coherent 2.1 Hz X-ray pulsations and relatively high estimated magnetic field, it is a particularly interesting source to study the physics of accretion flows around neutron stars. Here we report on Chandra/HETG observations obtained near the peak of its bright 2014 accretion outburst. Spectral analysis suggests the presence of a broad iron emission line centered at E_l ~ 6.7 keV. Fits with a disk reflection model yield an inclination angle of i ~ 52 degrees and an inner disk radius of R_in ~ 85 GM/c^2, which is much further out than typically found for neutron star low-mass X-ray binaries. Assuming that the disk is truncated at the magnetospheric radius of the neutron star, we estimate a magnetic field strength of B ~ (2-6)E10 G. Furthermore, we identify an absorption feature near ~6.85 keV could correspond to blue-shifted Fe xxv and point to a fast disk wind with an outflow velocity of v_out ~ (7.5-8.2)E3 km/s (~0.025c-0.027c). If the covering fraction and filling factor are large, this wind could be energetically important and perhaps account for the fact that the companion star lost significant mass while the magnetic field of the neutron star remained strong.Comment: Accepted for publication in ApJ Letters, 6 pages, 4 figures, 1 tabl

Statistical properties of 243^{243}Pu, and 242^{242}Pu(n,γ\gamma) cross section calculation

The level density and gamma-ray strength function (gammaSF) of 243Pu have been measured in the quasi-continuum using the Oslo method. Excited states in 243Pu were populated using the 242Pu(d,p) reaction. The level density closely follows the constant-temperature level density formula for excitation energies above the pairing gap. The gammaSF displays a double-humped resonance at low energy as also seen in previous investigations of actinide isotopes. The structure is interpreted as the scissors resonance and has a centroid of omega_{SR}=2.42(5)MeV and a total strength of B_{SR}=10.1(15)mu_N^2, which is in excellent agreement with sum-rule estimates. The measured level density and gammaSF were used to calculate the 242Pu(n,gamma) cross section in a neutron energy range for which there were previously no measured data.Comment: 9 pages, 8 figure