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n_TOF Collaboration(Massimi, C. et al), Domingo-Pardo, C., & Tain, J. L. (2010). Au-197(n,gamma) cross section in the resonance region. Phys. Rev. C, 81(4), 044616–22pp.
Abstract: The (n,gamma) cross section of Au-197 has been measured at nTOF in the resolved resonance region, up to 5 keV, with the aim of improving the accuracy in an energy range where it is not yet considered standard. The measurements were performed with two different experimental setup and detection techniques, the total energy method based on C6D6 detectors, and the total absorption calorimetry based on a 4 pi BaF2 array. By comparing the data collected with the two techniques, two accurate sets of neutron-capture yields have been obtained, which could be the basis for a new evaluation leading to an extended cross-section standard. Overall good agreement is found between the n_TOF results and evaluated cross sections, with some significant exceptions for small resonances. A few resonances not included in the existing databases have also been observed.
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n_TOF Collaboration(Lederer, C. et al), Domingo-Pardo, C., & Tain, J. L. (2011). Au-197(n,gamma) cross section in the unresolved resonance region. Phys. Rev. C, 83(3), 034608–11pp.
Abstract: The cross section of the reaction Au-197(n,gamma) was measured with the time-of-flight technique at the n_TOF (neutron time-of-flight) facility in the unresolved resonance region between 5 and 400 keV using a pair of C6D6 (where D denotes H-2) liquid scintillators for the detection of prompt capture gamma rays. The results with a total uncertainty of 3.9%-6.7% for a resolution of 20 bins per energy decade show fair agreement with the Evaluated Nuclear Data File Version B-VII.0 (ENDF/B-VII.0), which contains the standard evaluation. The Maxwellian-averaged cross section (MACS) at 30 keV is in excellent agreement with the one according to the ENDF/B-VII.0 evaluation and 4.7% higher than the MACS measured independently by activation technique. Structures in the cross section, which had also been reported earlier, have been interpreted as being due to clusters of resonances.
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Albiol, A., Corbi, A., & Albiol, F. (2017). Automatic intensity windowing of mammographic images based on a perceptual metric. Med. Phys., 44(4), 1369–1378.
Abstract: Purpose: Initial auto-adjustment of the window level WL and width WW applied to mammographic images. The proposed intensity windowing (IW) method is based on the maximization of the mutual information (MI) between a perceptual decomposition of the original 12-bit sources and their screen displayed 8-bit version. Besides zoom, color inversion and panning operations, IW is the most commonly performed task in daily screening and has a direct impact on diagnosis and the time involved in the process. Methods: The authors present a human visual system and perception-based algorithm named GRAIL (Gabor-relying adjustment of image levels). GRAIL initially measures a mammogram's quality based on the MI between the original instance and its Gabor-filtered derivations. From this point on, the algorithm performs an automatic intensity windowing process that outputs the WL/WW that best displays each mammogram for screening. GRAIL starts with the default, high contrast, wide dynamic range 12-bit data, and then maximizes the graphical information presented in ordinary 8-bit displays. Tests have been carried out with several mammogram databases. They comprise correlations and an ANOVA analysis with the manual IW levels established by a group of radiologists. A complete MATLAB implementation of GRAIL is available at . Results: Auto-leveled images show superior quality both perceptually and objectively compared to their full intensity range and compared to the application of other common methods like global contrast stretching (GCS). The correlations between the human determined intensity values and the ones estimated by our method surpass that of GCS. The ANOVA analysis with the upper intensity thresholds also reveals a similar outcome. GRAIL has also proven to specially perform better with images that contain micro-calcifications and/or foreign X-ray-opaque elements and with healthy BI-RADS A-type mammograms. It can also speed up the initial screening time by a mean of 4.5 s per image. Conclusions: A novel methodology is introduced that enables a quality-driven balancing of the WL/WW of mammographic images. This correction seeks the representation that maximizes the amount of graphical information contained in each image. The presented technique can contribute to the diagnosis and the overall efficiency of the breast screening session by suggesting, at the beginning, an optimal and customized windowing setting for each mammogram.
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Stoppa, F., Bhattacharyya, S., Ruiz de Austri, R., Vreeswijk, P., Caron, S., Zaharijas, G., et al. (2023). AutoSourceID-Classifier Star-galaxy classification using a convolutional neural network with spatial information. Astron. Astrophys., 680, A109–16pp.
Abstract: Aims. Traditional star-galaxy classification techniques often rely on feature estimation from catalogs, a process susceptible to introducing inaccuracies, thereby potentially jeopardizing the classification's reliability. Certain galaxies, especially those not manifesting as extended sources, can be misclassified when their shape parameters and flux solely drive the inference. We aim to create a robust and accurate classification network for identifying stars and galaxies directly from astronomical images.Methods. The AutoSourceID-Classifier (ASID-C) algorithm developed for this work uses 32x32 pixel single filter band source cutouts generated by the previously developed AutoSourceID-Light (ASID-L) code. By leveraging convolutional neural networks (CNN) and additional information about the source position within the full-field image, ASID-C aims to accurately classify all stars and galaxies within a survey. Subsequently, we employed a modified Platt scaling calibration for the output of the CNN, ensuring that the derived probabilities were effectively calibrated, delivering precise and reliable results.Results. We show that ASID-C, trained on MeerLICHT telescope images and using the Dark Energy Camera Legacy Survey (DECaLS) morphological classification, is a robust classifier and outperforms similar codes such as SourceExtractor. To facilitate a rigorous comparison, we also trained an eXtreme Gradient Boosting (XGBoost) model on tabular features extracted by SourceExtractor. While this XGBoost model approaches ASID-C in performance metrics, it does not offer the computational efficiency and reduced error propagation inherent in ASID-C's direct image-based classification approach. ASID-C excels in low signal-to-noise ratio and crowded scenarios, potentially aiding in transient host identification and advancing deep-sky astronomy.
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Stoppa, F., Ruiz de Austri, R., Vreeswijk, P., Bhattacharyya, S., Caron, S., Bloemen, S., et al. (2023). AutoSourceID-FeatureExtractor Optical image analysis using a two-step mean variance estimation network for feature estimation and uncertainty characterisation. Astron. Astrophys., 680, A108–14pp.
Abstract: Aims. In astronomy, machine learning has been successful in various tasks such as source localisation, classification, anomaly detection, and segmentation. However, feature regression remains an area with room for improvement. We aim to design a network that can accurately estimate sources' features and their uncertainties from single-band image cutouts, given the approximated locations of the sources provided by the previously developed code AutoSourceID-Light (ASID-L) or other external catalogues. This work serves as a proof of concept, showing the potential of machine learning in estimating astronomical features when trained on meticulously crafted synthetic images and subsequently applied to real astronomical data.Methods. The algorithm presented here, AutoSourceID-FeatureExtractor (ASID-FE), uses single-band cutouts of 32x32 pixels around the localised sources to estimate flux, sub-pixel centre coordinates, and their uncertainties. ASID-FE employs a two-step mean variance estimation (TS-MVE) approach to first estimate the features and then their uncertainties without the need for additional information, for example the point spread function (PSF). For this proof of concept, we generated a synthetic dataset comprising only point sources directly derived from real images, ensuring a controlled yet authentic testing environment.Results. We show that ASID-FE, trained on synthetic images derived from the MeerLICHT telescope, can predict more accurate features with respect to similar codes such as SourceExtractor and that the two-step method can estimate well-calibrated uncertainties that are better behaved compared to similar methods that use deep ensembles of simple MVE networks. Finally, we evaluate the model on real images from the MeerLICHT telescope and the Zwicky Transient Facility (ZTF) to test its transfer learning abilities.
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Stoppa, F., Vreeswijk, P., Bloemen, S., Bhattacharyya, S., Caron, S., Johannesson, G., et al. (2022). AutoSourceID-Light Fast optical source localization via U-Net and Laplacian of Gaussian. Astron. Astrophys., 662, A109–8pp.
Abstract: Aims. With the ever-increasing survey speed of optical wide-field telescopes and the importance of discovering transients when they are still young, rapid and reliable source localization is paramount. We present AutoSourceID-Light (ASID-L), an innovative framework that uses computer vision techniques that can naturally deal with large amounts of data and rapidly localize sources in optical images. Methods. We show that the ASID-L algorithm based on U-shaped networks and enhanced with a Laplacian of Gaussian filter provides outstanding performance in the localization of sources. A U-Net network discerns the sources in the images from many different artifacts and passes the result to a Laplacian of Gaussian filter that then estimates the exact location. Results. Using ASID-L on the optical images of the MeerLICHT telescope demonstrates the great speed and localization power of the method. We compare the results with SExtractor and show that our method outperforms this more widely used method. ASID-L rapidly detects more sources not only in low- and mid-density fields, but particularly in areas with more than 150 sources per square arcminute. The training set and code used in this paper are publicly available.
Keywords: astronomical databases; miscellaneous; methods; data analysis; stars; imaging; techniques; image processing
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Heavy Flavor Averaging Group(Amhis, Y. et al), & Oyanguren, A. (2017). Averages of b-hadron, c-hadron, and tau-lepton properties as of summer 2016. Eur. Phys. J. C, 77(12), 895–335pp.
Abstract: This article reports world averages of measurements of b-hadron, c-hadron, and tau-lepton properties obtained by the Heavy Flavor Averaging Group using results available through summer 2016. For the averaging, common input parameters used in the various analyses are adjusted (rescaled) to common values, and known correlations are taken into account. The averages include branching fractions, lifetimes, neutral meson mixing parameters, CP violation parameters, parameters of semileptonic decays, and Cabbibo-Kobayashi-Maskawa matrix elements.
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Heavy Flavor Averaging Group(Amhis, Y. et al), & Oyanguren, A. (2023). Averages of b-hadron, c-handron, and t-lepton properties as of 2021. Phys. Rev. D, 107(5), 052008–365pp.
Abstract: This paper reports world averages of measurements of b-hadron, c-hadron, and τ-lepton properties obtained by the Heavy Flavor Averaging Group using results available before April 2021. In rare cases, significant results obtained several months later are also used. For the averaging, common input parameters used in the various analyses are adjusted (rescaled) to common values, and known correlations are taken into account. The averages include branching fractions, lifetimes, neutral meson mixing parameters, CP violation parameters, parameters of semileptonic decays, and Cabibbo-Kobayashi-Maskawa matrix elements.
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Bolle, E., Casella, C., Chesi, E., De Leo, R., Dissertori, G., Fanti, V., et al. (2012). AX-PET: A novel PET concept with G-APD readout. Nucl. Instrum. Methods Phys. Res. A, 695, 129–134.
Abstract: The AX-PET collaboration has developed a novel concept for high resolution PET imaging to overcome some of the performance limitations of classical PET cameras, in particular the compromise between spatial resolution and sensitivity introduced by the parallax error. The detector consists of an arrangement of long LYSO scintillating crystals axially oriented around the field of view together with arrays of wave length shifter strips orthogonal to the crystals. This matrix allows a precise 3D measurement of the photon interaction point. This is valid both for photoelectric absorption at 511 key and for Compton scattering down to deposited energies of about 100 keV. Crystals and WLS strips are individually read out using Geiger-mode Avalanche Photo Diodes (G-APDs). The sensitivity of such a detector can be adjusted by changing the number of layers and the resolution is defined by the crystal and strip dimensions. Two AX-PET modules were built and fully characterized in dedicated test set-ups at CERN, with point-like Na-22 sources. Their performance in terms of energy (Renew approximate to 11.8% (FWMH) at 511 key) and spatial resolution was assessed (sigma(axial) approximate to 0.65 mm), both individually and for the two modules in coincidence. Test campaigns at ETH Zurich and at the company AAA allowed the tomographic reconstructions of more complex phantoms validating the 3D reconstruction algorithms. The concept of the AX-PET modules will be presented together with some characterization results. We describe a count rate model which allows to optimize the planing of the tomographic scans.
Keywords: PET; Axial geometry; Geiger-mode Avalanche Photo Diodes (G-APD); SiPM
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Di Valentino, E., Giusarma, E., Lattanzi, M., Melchiorri, A., & Mena, O. (2014). Axion cold dark matter: Status after Planck and BICEP2. Phys. Rev. D, 90(4), 043534–11pp.
Abstract: We investigate the axion dark matter scenario (ADM), in which axions account for all of the dark matter in the Universe, in light of the most recent cosmological data. In particular, we use the Planck temperature data, complemented by WMAP E-polarization measurements, as well as the recent BICEP2 observations of B-modes. Baryon acoustic oscillation data, including those from the baryon oscillation spectroscopic survey, are also considered in the numerical analyses. We find that, in the minimal ADM scenario and for Delta(QCD) = 200 MeV, the full data set implies that the axion mass m(a) = 82.2 +/- 1.1 μeV [corresponding to the Peccei-Quinn symmetry being broken at a scale f(a) = (7.54 +/- 0.10) x 10(10) GeV], or m(a) = 76.6 +/- 2.6 μeV [f(a) = (8.08 +/- 0.27) x 10(10) GeV] when we allow for a nonstandard effective number of relativistic species N-eff. We also find a 2 sigma preference for N-eff > 3.046. The limit on the sum of neutrino masses is Sigma m(v) < 0.25 eV at 95% C.L. for N-eff = 3.046, or Sigma m(v) < 0.47 eV when N-eff is a free parameter. Considering extended scenarios where either the dark energy equation-of-state parameter w, the tensor spectral index n(t), or the running of the scalar index dn(s)/d ln k is allowed to vary does not change significantly the axion mass-energy density constraints. However, in the case of the full data set exploited here, there is a preference for a nonzero tensor index or scalar running, driven by the different tensor amplitudes implied by the Planck and BICEP2 observations. We also study the effect on our estimates of theoretical uncertainties, in particular the imprecise knowledge of the QCD scale Delta(QCD), in the calculation of the temperature-dependent axion mass. We find that in the simplest ADM scenario the Planck + WP data set implies that the axion mass m(a) = 63.7 +/- 1.2 μeV for Delta(QCD) = 400 MeV. We also comment on the possibility that axions do not make up for all the dark matter, or that the contribution of string-produced axions has been grossly underestimated; in that case, the values that we find for the mass can conservatively be considered as lower limits. Dark matter axions with mass in the 60-80 μeV (corresponding to an axion-photon coupling G(a gamma gamma) similar to 10(-14) GeV-1) range can, in principle, be detected by looking for axion-to-photon conversion occurring inside a tunable microwave cavity permeated by a high-intensity magnetic field, and operating at a frequency nu similar or equal to 15-20 GHz. This is out of the reach of current experiments like the axion dark matter experiment (limited to a maximum frequency of a few GHzs), but is, on the other hand, within the reach of the upcoming axion dark matter experiment-high frequency experiment that will explore the 4-40 GHz frequency range and then be sensitive to axion masses up to similar to 160 μeV.
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