174 research outputs found

    De onderwijsovereenkomst in het onderwijs

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    Opschortingsbevoegdheid uit Boek 6 BW toegepast in verhouding onderwijsinstelling en leerling

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    Rb. Noord-NederlandCoherent privaatrech

    De opschortingsbevoegdheid in het onderwijs

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    Intraoperative cone beam computed tomography for detecting residual stones in percutaneous nephrolithotomy:a feasibility study

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    Cone beam computed tomography (CBCT) provides multiplanar cross-sectional imaging and three-dimensional reconstructions and can be used intraoperatively in a hybrid operating room. In this study, we investigated the feasibility of using a CBCT-scanner for detecting residual stones during percutaneous nephrolithotomy (PCNL). Intraoperative CBCT-scans were made during PCNL procedures from November 2018 until March 2019 in a university hospital. At the point where the urologist would have otherwise ended the procedure, a CBCT-scan was made to image any residual fragments that could not be detected by either nephroscopy or conventional C-arm fluoroscopy. Residual fragments that were visualized on the CBCT-scan were attempted to be extracted additionally. To evaluate the effect of this additional extraction, each CBCT-scan was compared with a regular follow-up CT-scan that was made 4 weeks postoperatively. A total of 19 procedures were analyzed in this study. The mean duration of performing the CBCT-scan, including preparation and interpretation, was 8 min. Additional stone extraction, if applicable, had a mean duration of 11 min. The mean effective dose per CBCT-scan was 7.25 mSv. Additional extraction of residual fragments as imaged on the CBCT-scan occurred in nine procedures (47%). Of the follow-up CT-scans, 63% showed a stone-free status as compared to 47% of the intraoperative CBCT-scans. We conclude that the use of CBCT for the detection of residual stones in PCNL is meaningful, safe, and feasible

    Automatic hoof-on and -off detection in horses using hoof-mounted inertial measurement unit sensors

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    For gait classification, hoof-on and hoof-off events are fundamental locomotion characteristics of interest. These events can be measured with inertial measurement units (IMUs) which measure the acceleration and angular velocity in three directions. The aim of this study was to present two algorithms for automatic detection of hoof-events from the acceleration and angular velocity signals measured by hoof-mounted IMUs in walk and trot on a hard surface. Seven Warmblood horses were equipped with two wireless IMUs, which were attached to the lateral wall of the right front (RF) and hind (RH) hooves. Horses were walked and trotted on a lead over a force plate for internal validation. The agreement between the algorithms for the acceleration and angular velocity signals with the force plate was evaluated by Bland Altman analysis and linear mixed model analysis. These analyses were performed for both hoof-on and hoof-off detection and for both algorithms separately. For the hoof-on detection, the angular velocity algorithm was the most accurate with an accuracy between 2.39 and 12.22 ms and a precision of around 13.80 ms, depending on gait and hoof. For hoof-off detection, the acceleration algorithm was the most accurate with an accuracy of 3.20 ms and precision of 6.39 ms, independent of gait and hoof. These algorithms look highly promising for gait classification purposes although the applicability of these algorithms should be investigated under different circumstances, such as different surfaces and different hoof trimming conditions
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