Hanging bladder calculi secondary to misplaced surgical suture

Bladder calculi, a rare condition in the pediatric population, occur most commonly as a result of either migration from the kidney or urinary stasis in the bladder. We report the case of a 3-year-old boy with recurrent urinary tract infections (UTI) secondary to bladder calculi formation on the sutures from a previous herniorrhaphy.A 3-year-old boy with previous history of herniorrhaphy presented with recurrent episodes of urinary tract infection, resistant to antibiotic therapy. Physical examination was unremarkable. Ultrasonography (US) showed an echogenic fixed intra-luminal lesion in the bladder. Cystoscopic evaluation was performed and confirmed presence of calculi forming around several permanent silk sutures fixed to the bladder wall. The patient undergone cystotomy and the calculi were resected. The stone analysis revealed 80 uric acid calculi. The final diagnosis was of bladder calculi due to remnant suture from past herniorrhaphy. © 2015, Tehran University of Medical Sciences and Iranian Society of Radiology

XMM-Newton and Gemini Observations of Eight RASSCALS Galaxy Groups

We study the distribution of gas pressure and entropy in eight groups of galaxies belonging to the ROSAT All-Sky Survey / Center for Astrophysics Loose Systems (RASSCALS). We use archival and proprietary XMM-Newton observations, supplementing the X-ray data with redshifts derived from the literature; we also list 127 new redshifts measured with the Gemini North telescope. The groups show remarkable self-similarity in their azimuthally averaged entropy and temperature profiles. The entropy increases with radius; the behavior of the entropy profiles is consistent with an increasing broken power law with inner and outer slope 0.92+0.04-0.05 and 0.42+0.05-0.04 (68% confidence), respectively. There is no evidence of a central, isentropic core, and the entropy distribution in most of the groups is flatter at large radii than in the inner region, challenging earlier reports as well as theoretical models predicting large isentropic cores or asymptotic slopes of 1.1 at large radii. The pressure profiles are consistent with a self-similar decreasing broken power law in radius; the inner and outer slopes are -0.78+0.04-0.03 and -1.7+0.1-0.3, respectively. The results suggest that the larger scatter in the entropy distribution reflects the varied gasdynamical histories of the groups; the regularity and self-similarity of the pressure profiles is a sign of a similarity in the underlying dark matter distributions.Comment: Accepted for publication in the Astrophysical Journa

Joint Analysis of Cluster Observations: II. Chandra/XMM-Newton X-ray and Weak Lensing Scaling Relations for a Sample of 50 Rich Clusters of Galaxies

We present a study of multiwavelength X-ray and weak lensing scaling relations for a sample of 50 clusters of galaxies. Our analysis combines Chandra and XMM-Newton data using an energy-dependent cross-calibration. After considering a number of scaling relations, we find that gas mass is the most robust estimator of weak lensing mass, yielding 15 +/- 6% intrinsic scatter at r500 (the pseudo-pressure YX has a consistent scatter of 22%+/-5%). The scatter does not change when measured within a fixed physical radius of 1 Mpc. Clusters with small BCG to X-ray peak offsets constitute a very regular population whose members have the same gas mass fractions and whose even smaller <10% deviations from regularity can be ascribed to line of sight geometrical effects alone. Cool-core clusters, while a somewhat different population, also show the same (<10%) scatter in the gas mass-lensing mass relation. There is a good correlation and a hint of bimodality in the plane defined by BCG offset and central entropy (or central cooling time). The pseudo-pressure YX does not discriminate between the more relaxed and less relaxed populations, making it perhaps the more even-handed mass proxy for surveys. Overall, hydrostatic masses underestimate weak lensing masses by 10% on the average at r500; but cool-core clusters are consistent with no bias, while non-cool-core clusters have a large and constant 15-20% bias between r2500 and r500, in agreement with N-body simulations incorporating unthermalized gas. For non-cool-core clusters, the bias correlates well with BCG ellipticity. We also examine centroid shift variance and and power ratios to quantify substructure; these quantities do not correlate with residuals in the scaling relations. Individual clusters have for the most part forgotten the source of their departures from self-similarity.Comment: Corrects an error in the X-ray luminosities (erratum submitted)---none of the other results are affected. Go to http://sfstar.sfsu.edu/jaco for an electronic fitter and updated quick data download link

The Orbital Structure of Dark Matter Halos with Gas

With the success of the Chandra and XMM missions and the maturation of gravitational lensing techniques, powerful constraints on the orbital structure of cluster dark matter halos are possible. I show that the X-ray emissivity and mass of a galaxy cluster uniquely specify the anisotropy and velocity dispersion profiles of its dark matter halo. I consider hydrostatic as well as cooling flow scenarios, and apply the formalism to the lensing cluster CL0024+16 and the cooling flow cluster Abell 2199. In both cases, the model predicts a parameter-free velocity dispersion profile that is consistent with independent optical redshift surveys of the clusters.Comment: 17 pages, 12 figures; to appear in the Astrophysical Journa

Iodination of Alcohols over Keggin-type Heteropoly Compounds: A Simple, Selective and Expedient Method for the Synthesis of Alkyl Iodides

Different catalysts derived from Keggin-type heteropoly compounds were prepared and their catalytic activities have been compared in the iodination of benzyl alcohol with KI under mild reaction conditions. A high catalytic activity was found over tungstophosphoric acid supported on silica and titania. The effect of catalyst loading, iodine source and the nature of substituents on the aromatic ring of benzyl alcohol were investigated. Finally, several competitive reactions were studied between structurally diverse alcohols. This protocol provides a mild and expedient way for the conversion of various alcohols to their corresponding alkyl iodides with high selectivity.Keywords: Keggin-type Heteropoly Compounds, Supported Catalyst, Alcohols, Alkyl Iodides, Potassium Iodid

Analysis of agile canine gait characteristics using accelerometry

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. The high rate of severe injuries associated with racing greyhounds poses a significant problem for both animal welfare and the racing industry. Using accelerometry to develop a better understanding of the complex gait of these agile canines may help to eliminate injury contributing factors. This study used a single Inertial Measurement Unit (IMU) equipped with a tri-axial accelerometer to characterise the galloping of thirty-one greyhounds on five different race tracks. The dorsal-ventral and anterior-posterior accelerations were analysed in both the time and frequency domains. The fast Fourier transform (FFT) and Morlet wavelet transform were applied to signals. The time-domain signals were synced with the corresponding high frame rate videos of the race. It is observed that the acceleration peaks in the dorsal-ventral accelerations correspond to the hind-leg strikes which were noted to be fifteen times the greyhound’s weight. The FFT analysis showed that the stride frequencies in all tracks were around 3.5 Hz. The Morlet wavelet analysis also showed a reduction in both the frequency and magnitude of signals, which suggests a speed reduction throughout the race. Also, by detecting abrupt changes along the track, the wavelet analysis highlighted potentially hazardous locations on the track. In conclusion, the methods applied in this research contribute to animal safety and welfare by eliminating the factors leading to injuries through optimising the track design and surface type

Robust Dynamic Operating Envelopes with Uncertain Demands and Impedances in Unbalanced Distribution Networks

Dynamic operating envelopes (DOEs), as a key enabler to facilitate DER integration, have attracted increasing attention in the past years. However, uncertainties, which may come from load forecast errors or inaccurate network parameters, have been rarely discussed in DOE calculation, leading to compromised quality of the hosting capacity allocation strategy. This letter studies how to calculate DOEs that are immune to such uncertainties based on a linearised unbalanced three-phase optimal power flow (UTOPF) model. With uncertain parameters constrained by norm balls, formulations for calculating Robust DOEs (RDOEs) are presented along with discussions on their tractability. Two cases, including a 2-bus illustrative network and a representative Australian network, have been tested to demonstrate the effectiveness and efficiency of the proposed approach.Comment: Under review by Journal of Modern Power Systems and Clean Energ

Comparison of Coupled Flow-deformation and Drained Analyses for Road Embankments on CMC Improved Ground

© 2016 The Authors. Published by Elsevier B.V. The use of controlled modulus columns (CMC) is gaining increased popularity in the support of rail and road bridge approach embankments on soft soils. The further columns are driven into the competent firm soils, the further the design will rely on the inclusions to take the bulk of the vertical loads, as they become rigid inclusions. The advantage of this design approach is that it produces increased control over the settlement, but as a result the columns will attract greater loads, including bending moment and shear force in situations where non-uniform loading or ground conditions exist. The load on the composite soil-CMC is uniformly distributed by the upper layer of granular load transfer platform (LTP), which also includes a layer of reinforcement. Finite difference program FLAC3D has been used to numerically simulate an embankment on the improved ground with end-bearing CMC. A geosynthetic reinforcement layer has been simulated using the inbuilt FLAC3D geogrid element. In this paper, a comparison has been made between the drained and coupled flow-deformation analyses. The force in the reinforcement layer, in particular, has been compared for the two analysis approaches. It was found that according to the numerical simulation, the drained analysis provides lower estimates of the settlement, lateral displacement; and therefore, predicts less tension in the geosynthetic layer

Main Determinants of Supplementary Health Insurance Demand: (Case of Iran)

INTRODUCTION: In the majority of developing countries, the volume of medical insurance services, provided by social insurance organizations is inadequate. Thus, supplementary medical insurance is proposed as a means to address inadequacy of medical insurance. Accordingly, in this article, we attempted to provide the context for expansion of this important branch of insurance through identification of essential factors affecting demand for supplementary medical insurance. METHOD: In this study, two methods were used to identify essential factors affecting choice of supplementary medical insurance including Classification and Regression Trees (CART) and Bayesian logit. To this end, Excel® software was used to refine data and R® software for estimation. The present study was conducted during 2012, covering all provinces in Iran. Sample size included 18,541 urban households, selected by Statistical Center of Iran using 3-stage cluster sampling approach. In this study, all data required were collected from the Statistical Center of Iran. RESULTS: In 2012, an overall 8.04 of the Iranian population benefited from supplementary medical insurance. Demand for supplementary insurance is a concave function of age of the household head, and peaks in middle-age when savings and income are highest. The present study results showed greater likelihood of demand for supplementary medical insurance in households with better economic status, higher educated heads, female heads, and smaller households with greater expected medical expenses, and household income is the most important factor affecting demand for supplementary medical insurance. CONCLUSION: Since demand for supplementary medical insurance is hugely influenced by households' economic status, policy-makers in the health sector should devise measures to improve households' economic or financial access to supplementary insurance services, by identifying households in the lower economic deciles, and increasing their financial ability to pay. Moreover, insurance companies should adjust their insurance policy according to clients' needs, household characteristics, and their incomes

Investigation of inverse design of multilayer thin-films with conditional invertible Neural Networks

The task of designing optical multilayer thin-films regarding a given target is currently solved using gradient-based optimization in conjunction with methods that can introduce additional thin-film layers. Recently, Deep Learning and Reinforcement Learning have been been introduced to the task of designing thin-films with great success, however a trained network is usually only able to become proficient for a single target and must be retrained if the optical targets are varied. In this work, we apply conditional Invertible Neural Networks (cINN) to inversely designing multilayer thin-films given an optical target. Since the cINN learns the energy landscape of all thin-film configurations within the training dataset, we show that cINNs can generate a stochastic ensemble of proposals for thin-film configurations that that are reasonably close to the desired target depending only on random variables. By refining the proposed configurations further by a local optimization, we show that the generated thin-films reach the target with significantly greater precision than comparable state-of-the art approaches. Furthermore, we tested the generative capabilities on samples which are outside the training data distribution and found that the cINN was able to predict thin-films for out-of-distribution targets, too. The results suggest that in order to improve the generative design of thin-films, it is instructive to use established and new machine learning methods in conjunction in order to obtain the most favorable results