63 research outputs found

    Ultrasound diagnosis of anterior iliopsoas impingement in total hip replacement.

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    Iliopsoas impingement syndrome, an infrequent complication of total hip replacement, has been rarely reported in the radiological literature. It follows chronic friction of the posterior aspect of the iliopsoas muscle and tendon against the acetabular cup, a piece of cement, or cup fixation screws. Clinical findings are non-specific and an imaging modality is required to diagnose the condition. Computed tomography (CT) is considered the gold standard imaging modality in evaluating iliopsoas impingement. We report a case of a patient in which the diagnosis was made by ultrasound and later confirmed by CT

    (Rezig 1989)

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    Dagger: A Data (not code) Debugger

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    With the democratization of data science libraries and frame- works, most data scientists manage and generate their data analytics pipelines using a collection of scripts (e.g., Python, R). This marks a shift from traditional applications that communicate back and forth with a DBMS that stores and manages the application data. While code debuggers have reached impressive maturity over the past decades, they fall short in assisting users to explore data-driven what-if sce- narios (e.g., split the training set into two and build two ML models). Those scenarios, while doable programmati- cally, are a substantial burden for users to manage them- selves. Dagger (Data Debugger) is an end-to-end data de- bugger that abstracts key data-centric primitives to enable users to quickly identify and mitigate data-related problems in a given pipeline. Dagger was motivated by a series of interviews we conducted with data scientists across several organizations. A preliminary version of Dagger has been in- corporated into Data Civilizer 2.0 to help physicians at the Massachusetts General Hospital process complex pipelines

    Influence of corrosion damage on the initiation of fatigue cracks in high strength stainless steels

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    This research project investigates the influence of corrosion flaws on the initiation of fatigue cracks in high strength stainless steels, and more particularly in 15-5 precipitation hardening high strength stainless steel. Susceptibility of 15-5PH to localised corrosion was examined and pit-like corrosion flaws produced by pitting and crevice corrosion were introduced in fatigue specimens in order to measure the influence of these surface flaws on fatigue crack initiation. From the results and observations made during the experiments, models of crevice corrosion propagation and initial stage of fatigue were developed. Experimental testing revealed that 15-5 precipitation hardening stainless steel is more prone to crevice corrosion than pitting, and that crevice corrosion is thought to be the most likely cause of any pit-like flaws in this material. The first results of the modelling of the propagation of crevice corrosion in 15-5PH stainless steel showed that the initial growth across the metal surface was proportional t3/ 8 . It follows that the depth growth rate in that initial stage was proportional t5/ 8 . All pre-corroded fatigue specimens failed from fatigue cracks which initiated from crevice corrosion flaws during fatigue testing. After failure the shape and size of corrosion flaws where the cracks initiated were measured and their largest Kt values determined by finite element analysis. No general pattern linking total fatigue life and stress concentration factor value was found. However, it was shown that stress concentration factor Kt has an influence on the initiation and early crack growth behaviour, but has no effect on the life of longer cracks. In addition, it appeared that not considering the small excursions found at the bottom of corrosion flaws in the assessment of the stress concentration factor Kt underestimates the values of Kt.Airbus U

    Development of a knowledge model for managing schedule disturbance in steel-making

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    The development of a knowledge model, which describes the reasoning process in managing schedule disturbance in steel-making, is presented. A literature review shows the lack of research in developing a knowledge model for decision-making in steel-making. The knowledge model distinguishes three knowledge categories: task, inference and domain. Knowledge is captured for the ten most common types of disturbances in steel-making. A common inference model exists for disturbance management. A knowledge elicitation methodology called eXpert Process Knowledge Analysis Technique (XPat) combined with a CommonKADS approach was used to capture process knowledge for managing schedule disturbance in steel-making. Finally, the knowledge model is validated through paper-based simulations of three common disturbance scenarios. The validation process consisted of three components: accuracy, completeness and consistency

    Growth and optimization by post-annealing of chalcopyrite CuAlS

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    The chalcopyrite CuAlS2 compound was grown from stoichiometric melt by horizontal Bridgman method. The obtained ingots were crushed finely and annealed at different temperatures from 800 °C to 1100 °C under a gas mixture of 5% N2/H2 atmosphere. X-ray diffraction and Raman spectroscopy were used to investigate the layer microstructures, as well as their lattice vibration spectra. The layers were characterized by scanning electron microscopy (SEM) and the compositional analyses were done by energy dispersive X-ray microanalysis (EDX). Raman measurements of the as made powder indicated seven prominent peaks at 205, 250, 290, 340, 369, 418 and 457 cm−1 with large intensity at 457 cm−1. The peaks at 205, 250, 340 and 457 cm−1 were ascribed to B2 modes while the peaks 369 and 418 cm−1 were ascribed to E modes. The peak at 290 cm−1 may be assigned to the A1 mode. After annealing, the Raman features become better and phonon mode at 290 cm−1 looks more distinct. The stoichiometric CuAlS2 compound was obtained when the sample was annealed at 900 °C
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