Reflection Efficiency and Spectra Resolutions Ray-Tracing Simulations for the VOXES HAPG Crystal Based Von Hamos Spectrometer

The VOXES collaboration at INFN National Laboratories of Frascati developed a prototype of a high resolution Von Hamos X-ray spectrometer using HAPG (Highly Annealed Pyrolytic Graphite) mosaic crystals. This technology allows the employment of extended isotropic sources and could find application in several physics fields. The capability of the spectrometer to reach energy precision and resolution below 1 and 10 eV, respectively, when used with wide sources, has been already demonstrated. Recently, the response of this device, for a ρ = 206.7 mm cylindrically bent HAPG crystal using CuKα1,2 and FeKα1,2 XRF lines, has been investigated in terms of reflection efficiency by a dedicated ray-tracing simulation. Details of the simulation procedure and the comparison with the experimental results are presented. This study is crucial in order to retrieve information on the spectrometer signal collection efficiency, especially in the energy range in which the standard calibration procedures cannot be applied.

Soft and Hard Iron Compensation for the Compasses of an Operational Towed Hydrophone Array without Sensor Motion by a Helmholtz Coil

Usually, towed hydrophone arrays are instrumented with a set of compasses. Data from these sensors are utilized while beamforming the acoustic signal for target bearing estimation. However, elements of the hydrophone array mounted in the neighborhood of a compass can affect the Earth’s magnetic field detection. The effects depend upon the materials and magnetic environment present in the vicinity of the platform hosting the compass. If the disturbances are constant in time, they can be compensated for by means of a magnetic calibration procedure. This process is commonly known as soft and hard iron compensation. In this paper, a solution is presented for carrying out the magnetic calibration of a COTS (Commercial Off the Shelf) digital compass without sensor motion. This approach is particularly suited in applications where a physical rotation of the platform that hosts the sensor is unfeasible. In our case, the platform consists in an assembled and operational towed hydrophone array. A standard calibration process relies on physical rotation of the platform and thus on the use of the geomagnetic field as a reference during the compensation. As a variation on this approach, we generate an artificial reference magnetic field to simulate the impractical physical rotation. We obtain this by using a tri-axial Helmholtz coil, which enables programmability of the reference magnetic field and assures the required field uniformity. In our work, the simulated geomagnetic field is characterized in terms of its uncertainty. The analysis indicates that our method and experimental set-up represent a suitably accurate approach for the soft and hard iron compensation of the compasses equipped in the hydrophone array under test.

A machine learning approach to Bayesian parameter estimation

Bayesian estimation is a powerful theoretical paradigm for the operation of the approach to parameter estimation. However, the Bayesian method for statistical inference generally suffers from demanding calibration requirements that have so far restricted its use to systems that can be explicitly modeled. In this theoretical study, we formulate parameter estimation as a classification task and use artificial neural networks to efficiently perform Bayesian estimation. We show that the network’s posterior distribution is centered at the true (unknown) value of the parameter within an uncertainty given by the inverse Fisher information, representing the ultimate sensitivity limit for the given apparatus. When only a limited number of calibration measurements are available, our machine-learning-based procedure outperforms standard calibration methods. Our machine-learning-based procedure is model independent, and is thus well suited to “black-box sensors”, which lack simple explicit fitting models. Thus, our work paves the way for Bayesian quantum sensors that can take advantage of complex nonclassical quantum states and/or adaptive protocols. These capabilities can significantly enhance the sensitivity of future devices.

Reducing Calibration Time in PET Systems Based on Monolithic Crystals

In the past years, the gamma-ray detector designs based on the monolithic crystals have demonstrated to be excellent candidates for the design of high-performance PET systems. The monolithic crystals allow to achieve the intrinsic detector resolutions well below state-of-the-art; to increase packing fraction thus, increasing the system sensitivity; and to improve lesion detectability at the edges of the scanner field of view (FOV) because of their intrinsic depth of interaction (DOI) capabilities. The bottleneck to translate to the clinical PET systems based on a large number of monolithic detectors is eventually the requirement of mechanically complex and time-consuming calibration processes. To mitigate this drawback, several methods have been already proposed, such as using non-physically collimated radioactive sources or implementing the neuronal networks (NN) algorithms trained with simulated data. In this work, we aimed to simplify and fasten a calibration process of the monolithic based systems. The Normal procedure consists of individually acquiring a 11 × 11 22Na source array for all the detectors composing the PET system and obtaining the calibration map for each module using a method based on the Voronoi diagrams. Two reducing time methodologies are presented: (i) TEST1, where the calibration map of one detector is estimated and shared among all others, and (ii) TEST2, where the calibration map is slightly modified for each module as a function of their detector uniformity map. The experimental data from a dedicated prostate PET system was used to compare the standard calibration procedure with both the proposed methods. A greater similarity was exhibited between the TEST2 methodology and the Normal procedure; obtaining spatial resolution variances within 0.1 mm error bars and count rate deviations as small as 0.2%. Moreover, the negligible reconstructed image differences (13% deviation at most in the contrast-to-noise ratio) and almost identical contrast values were reported. Therefore, this proposed method allows us to calibrate the PET systems based on the monolithic crystals reducing the calibration time by approximately 80% compared with the Normal procedure.

PSVI-27 Relationship of volatile compounds and consumer sensory traits from New Zealand grass-fed and American grain-fed beef strip loins varying in marbling level and wet aging time

Cattle diet, marbling and wet aging can affect eating quality and consumer preference of beef. The objective of this study was to assess the relationship of cooked volatile compounds and consumer sensory traits of New Zealand grass-fed strip loin steaks in comparison to US grain-fed strip loin steaks from five different USDA quality grades, wet-aged for 7, 21 and 42 days. Beef strip loins (n = 200; 20 per USDA quality grade/fed cattle type) representing five USDA quality grades (USDA Prime, Top Choice, Low Choice, Select and Standard) and two fed cattle types (New Zealand grass-finished and US grain-finished) were used. Steaks were cooked to a target internal temperature of 71°C and served to consumer panelists (n = 600; 120 per five different cities in the US). Volatile analysis (n = 600) was performed on cooked samples, and quantitation was conducted by an internal standard calibration with authentic standards. Statistical analyses were conducted using the FACTOR procedure of SAS. A principle component analysis (PCA) showed relationships of volatile compounds, treatments, and consumer ratings. PC1 explained 17.17% of the variation and PC2 explained 10.96% of the variation. Consumer flavor liking was most closely associated with ethanol and treatments grass and grain Prime aged 42d. The majority of the alcohols and n-aldehydes were associated with the 7d grain treatments including grain Top Choice, Low Choice and Select. The Maillard derived compounds were grouped together and most associated with grass Top Choice 42d and the consumer attributes. Methional was closest to many grass treatments including grass Top Choice 7d, Low Choice 7d, Standard 7d, Prime 7d and Standard 21d. Although associations were evident between volatile compounds and consumer sensory attributes, they were not strongly related.

Lead Assays with Smartphone Detection Using a Monolithic Rod with 4-(2-Pyridylazo) Resorcinol

A monolithic rod of polyurethane foam–[4-(2-pyridylazo) resorcinol] (PUF–PAR) as a simple chemical sensor for lead assays with smartphone detection and image processing was developed. With readily available simple apparatus such as a plastic cup and a stirrer rod, the monolithic PUF rod was synthesized in a glass tube. The monolithic PUF–PAR rod could be directly loaded by standard/sample solution without sample preparation. A one-shot image in G/B value from a profile plot in ImageJ for a sample with triplicate results via a single standard calibration approach was obtained. A linear single standard calibration was: [G/B value] = −0.038[µg Pb2+] + 2.827, R2 = 0.95 for 10–30 µg Pb2+ with a limit of quantitation (LOQ) of 33 µg L−1. The precision was lower than 15% RSD. The proposed method was tested by an assay for Pb2+ contents in drinking water samples from Bangkok. The results obtained by the proposed method agree with those of ICP-OES and with 100–120% recovery, demonstrating that the method is useful for screening on-site water monitoring.

Soft and Hard Iron Compensation for the Compasses of an Operational Towed Hydrophone Array without Sensor Motion by a Helmholtz Coil

Usually, towed hydrophone arrays are instrumented with a set of compasses. Data from these sensors are utilized while beamforming the acoustic signal for target bearing estimation. However, elements of the hydrophone array mounted in the neighborhood of a compass can affect the Earth’s magnetic field detection. The effects depend upon the kind of elements present in the platform hosting the compass. If the disturbances are constant in time, they can be compensated for by means of a magnetic calibration. This process is commonly known as soft and hard iron compensation. In this paper, a solution is presented to carry out the magnetic calibration of a COTS (Commercial Off The Shelf) digital compass without unattainable sensor motion. This approach is particularly suited in applications where a physical rotation of the platform that hosts the sensor is unfeasible. In our case, the platform consists in an assembled and operational towed hydrophone array. A standard calibration process relies on physical rotation of the platform and thus on the use of the geomagnetic field as a reference during the compensation. As a variation on this approach, we provide to the sensor an artificial reference magnetic field to simulate the unfeasible physical rotation. We obtain this by using a tri-axial Helmholtz coil, which enables programmability of the reference magnetic field and assures the required field uniformity. In our work, the simulated geomagnetic field is characterized in terms of its uncertainty. The analysis indicates that our method and experimental set-up represent a suitably accurate approach for the soft and hard iron compensation of the compasses equipped in the hydrophone array under test.