Abstract: The spectroscopic performances of the new integrated ASIC (Application-Specific Integrated Circuit) preamplifiers for highly segmented silicon detectors have been evaluated with an early silicon detector prototype of the TRacking Array for light Charged Ejectiles (TRACE). The ASICS were mounted on a custom-designed PCB (Printed Circuit Board) and the detector plugged on it. Energy resolution tests, performed on the same detector before and after irradiation, yielded a resolution of 21 keV and 33 keV FWHM respectively. The output signals were acquired with an array of commercial 100-MHz 14-bit digitizers. The preamplifier chip is equipped with an innovative Fast-Reset device that has two functions: it reduces dramatically the dead time of the preamplifier in case of saturation (from milliseconds to microseconds) and extends the spectroscopic dynamic range of the preamplifier by more than one order of magnitude. Other key points of the device are the low noise and the wide bandwidth.

Abstract: In this work we present a comparison between the two liquid scintillators BC-501A and BC-537 in terms of their performance regarding the pulse-shape discrimination between neutrons and gamma rays. Special emphasis is put on the application of artificial neural networks. The results show a systematically higher gamma-ray rejection ratio for BC-501A compared to BC-537 applying the commonly used charge comparison method. Using the artificial neural network approach the discrimination quality was improved to more than 95% rejection efficiency of gamma rays over the energy range 150 to 1000 keV for both BC-501A and BC-537. However, due to the larger light output of BC-501A compared to BC-537, neutrons could be identified in BC-501A using artificial neural networks down to a recoil proton energy of 800 keV compared to a recoil deuteron energy of 1200 keV for BC-537. We conclude that using artificial neural networks it is possible to obtain the same gamma-ray rejection quality from both BC-501A and BC-537 for neutrons above a low-energy threshold. This threshold is, however, lower for BC-501A, which is important for nuclear structure spectroscopy experiments of rare reaction channels where low-energy interactions dominates.

Abstract: This work investigates the capability of TMA ((CH3)(3)N) molecules to shift the wavelength of Xe VUV emission (160-188 nm) to a longer, more manageable, wavelength (260-350 nm). Light emitted from a Xe lamp was passed through a gas chamber filled with Xe-TMA mixtures at 800 Torr and detected with a photomultiplier tube. Using bandpass filters in the proper transmission ranges, no reemitted light was observed experimentally. Considering the detection limit of the experimental system, if reemission by TMA molecules occurs, it is below 0.3% of the scintillation absorbed in the 160-188 nm range. An absorption coefficient value for xenon VUV light by TMA of 0.43 +/- 0.03 cm(-1) Torr(-1) was also obtained. These results can be especially important for experiments considering TMA as a molecular additive to Xe in large volume optical time projection chambers.

Abstract: We present a compilation and evaluation of experimental beta-delayed neutron emission probabilities (P-n) and half-lives (T-1/2) for known or potential beta-delayed neutron precursors with atomic number Z > 28 (Cu-73 – Fr-233). This article includes the recommended values of both of these quantities, together with a compilation of experimental measurements when available. Some notable cases, as well as proposed standards for beta-delayed neutron measurements are also discussed. Evaluated data has also been compared to systematics using three different approaches. The literature cut-off date for this work is August 15, 2020.

Abstract: Patient Trajectories (PTs) are a method of representing the temporal evolution of patients. They can include information from different sources and be used in socio-medical or clinical domains. PTs have generally been used to generate and study the most common trajectories in, for instance, the development of a disease. On the other hand, healthcare predictive models generally rely on static snapshots of patient information. Only a few works about prediction in healthcare have been found that use PTs, and therefore benefit from their temporal dimension. All of them, however, have used PTs created from single-source information. Therefore, the use of longitudinal multi-scale data to build PTs and use them to obtain predictions about health conditions is yet to be explored. Our hypothesis is that local similarities on small chunks of PTs can identify similar patients concerning their future morbidities. The objectives of this work are (1) to develop a methodology to identify local similarities between PTs before the occurrence of morbidities to predict these on new query individuals; and (2) to validate this methodology on risk prediction of cardiovascular diseases (CVD) occurrence in patients with diabetes. We have proposed a novel formal definition of PTs based on sequences of longitudinal multi-scale data. Moreover, a dynamic programming methodology to identify local alignments on PTs for predicting future morbidities is proposed. Both the proposed methodology for PT definition and the alignment algorithm are generic to be applied on any clinical domain. We validated this solution for predicting CVD in patients with diabetes and we achieved a precision of 0.33, a recall of 0.72 and a specificity of 0.38. Therefore, the proposed solution in the diabetes use case can result of utmost utility to secondary screening.