RESUMO
A robust impurity detection and tracking code, able to generate large sets of dust tracks from tokamak camera footage, is presented. This machine learning-based code is tested with cameras from the Joint European Torus, Doublet-III-D, and Magnum-PSI and is able to generate dust tracks with a 65-100% classification accuracy. Moreover, the number dust particles detected from a single camera shot can be up to the order of 1000. Several areas of improvement for the code are highlighted, such as generating more significant training data sets and accounting for selection biases. Although the code is tested with dust in single two-dimensional camera views, it could easily be applied to multiple-camera stereoscopic reconstruction or nondust impurities.
RESUMO
The impact of edge localized modes (ELMs) carrying energies of up to 450 kJ on carbon erosion in the JET inner divertor is assessed by means of time resolved measurements using an in situ quartz microbalance diagnostic. The inner target erosion is strongly nonlinearly dependent on the ELM energy: a single 400 kJ ELM produces the same carbon erosion as ten 150 kJ events. The ELM-induced enhanced erosion is attributed to the presence of codeposited carbon-deuterium layers on the inner divertor target, which are thermally decomposed under the impact of ELMs.
RESUMO
Nine hundred and twenty-three smears covered by 40 x 22 mm size coverslips were examined inside and outside the coverslip area to determine whether this coverslip size could be responsible for missed dyskaryotic cells in conventional cervical cancer screening. There was no instance when abnormal cells seen outside the coverslip were not also present within the coverslipped area.
