RESUMEN
Material clusters of different sizes are known to exist in high-temperature plasmas due to plasma-wall interactions. The facts that these clusters, ranging from sub-microns to above mm in size, can move from one location to another quickly and that there are a lot of them make high-speed imaging and tracking one of the best, effective, and sometimes only diagnostic. An unsupervised machine learning technique based on deconvolutional neural networks is developed to analyze two-camera videos of high-temperature microparticles generated from exploding wires. The neural network utilizes a locally competitive algorithm to infer representations and optimize a dictionary composed of kernels, or basis vectors, for image analysis. Our primary goal is to use this method for feature recognition and prediction of the time-dependent three-dimensional (or "4D") microparticle motion. Features equivalent to local velocity vectors have been identified as the dictionary kernels or "building blocks" of the scene. The dictionary elements from the left and right camera views are found to be strongly correlated and satisfy the projection geometrical constraints. The results show that unsupervised machine learning techniques are promising approaches to process large sets of images for high-temperature plasmas and other scientific experiments. Machine learning techniques can be useful to handle the large amount of data and therefore aid the understanding of plasma-wall interaction.
RESUMEN
1. Growth hormone-deficient hypopituitary adults often complain of weakness and fatigue. The cause of the fatigue is unknown but could be an increased proportion of fast, fatiguable, type 2 fibres in the muscle. The aim of this study was to examine the contractile properties of the quadriceps muscle in a group of these patients compared with healthy controls. Changes in these properties were also examined in a small subset of the patients following growth hormone replacement. 2. Isometric strength, half-relaxation time from a twitch (t1/2) and the force-frequency relationship were measured using electrically evoked contractions in 14 growth hormone-deficient patients and 14 age- and sex-matched controls. Six patients were restudied following 6-24 month's replacement therapy with growth hormone (daily dose 0.04 +/- 0.01 i.u./kg). 3. The growth hormone-deficient patients had a significantly lower t1/2 than the controls (46.1 +/- 6.1 ms versus 56.1 +/- 10.5 ms respectively; P = 0.0072; mean +/- SD). The 10/100% ratio was also significantly lower in growth-hormone-deficient patients (38.6 +/- 9.9% versus 52.3 +/- 8.0%; P = 0.0005), as was muscle strength (349 +/- 99 N versus 493 +/- 215 N; P = 0.036). Following growth hormone replacement, muscle strength increased significantly (P < 0.05). The 10/100% ratio also increased towards control values, but this change was not significant. 4. These results demonstrate that the relaxation times of the quadriceps are significantly shorter and that the force-frequency relationship shifted to the right in growth hormone-deficient patients, which is consistent with a greater proportion of type 2 fibres within the muscles.(ABSTRACT TRUNCATED AT 250 WORDS)