The prompt-gamma neutron activation facility at Brookhaven National Laboratory was upgraded to improve both the precision and accuracy of its in vivo determinations of total body nitrogen. The upgrade, guided by Monte Carlo simulations, involved elongating and modifying the source collimator and its shielding, repositioning the system's two NaI(Tl) detectors, and improving the neutron and gamma shielding of these detectors. The new source collimator has a graphite reflector around the 238PuBe neutron source to enhance the low-energy region of the neutron spectrum incident on the patient. The gamma detectors have been relocated from positions close to the upward-emerging collimated neutron beam to positions close to and at the sides of the patient. These modifications substantially reduced spurious counts resulting from the capture of small-angle scattered neutrons in the NaI detectors. The pile-up background under the 10.8 MeV 14N(n, gamma)15N spectral peak has been reduced so that the nitrogen peak-to-background ratio has been increased by a factor of 2.8. The resulting reduction in the coefficient of variation of the total body nitrogen measurements from 3% to 2.2% has improved the statistical significance of the results possible for any given number of patient measurements. The new system also has a more uniform composite sensitivity.

A: Convolutional neural networks (CNNs) have found applications in many image processing tasks, such as feature extraction, image classification, and object recognition. It has also been shown that the inverse of CNNs, so-called deconvolutional neural networks, can be used for inverse problems such as plasma tomography. In essence, plasma tomography consists in reconstructing the 2D plasma profile on a poloidal cross-section of a fusion device, based on line-integrated measurements from multiple radiation detectors. Since the reconstruction process is computationally intensive, a deconvolutional neural network trained to produce the same results will yield a significant computational speedup, at the expense of a small error which can be assessed using different metrics. In this work, we discuss the design principles behind such networks, including the use of multiple layers, how they can be stacked, and how their dimensions can be tuned according to the number of detectors and the desired tomographic resolution for a given fusion device. We describe the application of such networks at JET and COMPASS, where at JET we use the bolometer system, and at COMPASS we use the soft X-ray diagnostic based on photodiode arrays. K : Computerized Tomography (CT) and Computed Radiography (CR); Plasma diagnostics -interferometry, spectroscopy and imaging 1Corresponding author. 2See the author list of Overview of the JET preparation for Deuterium-Tritium Operation by E. Joffrin et al. in Nucl.

The present work is concerned with the optimization of the sapphire fast neutron filter thickness used in neutron diffraction instruments. The optimization is based on maximization of the slow neutron transmission, minimization of the fast neutron transmission, and also taking into consideration the neutron background at the vicinity of an instrument. Scattering properties of the sapphire in the fast and slow neutron regions are discussed.

The design, calibration, dosimetry and performance evaluation of a prompt-gamma neutron activation analysis facility for in vivo body composition studies in small animals (i.e. rats or rabbits) is discussed. The system design was guided by Monte Carlo transport calculations using MCNP-4C code. A system was built and performance evaluation was made using a 185-GBq Pu-Be neutron source. Prompt-gamma rays produced by neutron capture reactions were detected by a combination of a NaI(Tl) scintillation and a HPGe semiconductor detectors. Nitrogen and chlorine were quantified by analysis of the 10.83-MeV and 6.11-MeV peaks, respectively. Appropriate corrections for the animal body size were determined. The facility described allows the in vivo determination of protein and extracellular space in sets of experimental animals.

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