Abstract
This paper presents a novel approach for fragmented solid object classification exploiting neural networks based on point clouds. This work is the initial step of a project in collaboration ...with the Institution of ‘Ente Parco Archeologico del Colosseo’ in Rome, which aims to reconstruct ancient artifacts from their fragments. We built from scratch a synthetic dataset (DS) of fragments of different 3D objects including aging effects. We used this DS to train deep learning models for the task of classifying internal and external fragments. As model architectures, we adopted PointNet and dynamical graph convolutional neural network, which take as input a point cloud representing the spatial geometry of a fragment, and we optimized model performance by adding additional features sensitive to local geometry characteristics. We tested the approach by performing several experiments to check the robustness and generalization capabilities of the models. Finally, we test the models on a real case using a 3D scan of artifacts preserved in different museums, artificially fragmented, obtaining good performance.
The COVID-19 disease causes pneumonia in many patients that in the most serious cases evolves into the Acute Distress Respiratory Syndrome (ARDS), requiring assisted ventilation and intensive care. ...In this context, identification of patients at high risk of developing ARDS is a key point for early clinical management, better clinical outcome and optimization in using the limited resources available in the intensive care units. We propose an AI-based prognostic system that makes predictions of oxygen exchange with arterial blood by using as input lung Computed Tomography (CT), the air flux in lungs obtained from biomechanical simulations and Arterial Blood Gas (ABG) analysis. We developed and investigated the feasibility of this system on a small clinical database of proven COVID-19 cases where the initial CT and various ABG reports were available for each patient. We studied the time evolution of the ABG parameters and found correlation with the morphological information extracted from CT scans and disease outcome. Promising results of a preliminary version of the prognostic algorithm are presented. The ability to predict the evolution of patients’ respiratory efficiency would be of crucial importance for disease management.
•Nuclear reactions are fundamental for Ion-therapy simulations.•Theoretical models running time are too long for medical applications.•We are proposing the idea of using a Deep Learning algorithm to ...emulate the model.•We obtained promising preliminary results.
A reliable model to simulate nuclear interactions is fundamental for Ion-therapy. We already showed how BLOB (“Boltzmann-Langevin One Body”), a model developed to simulate heavy ion interactions up to few hundreds of MeV/u, could simulate also 12C reactions in the same energy domain. However, its computation time is too long for any medical application. For this reason we present the possibility of emulating it with a Deep Learning algorithm.
The BLOB final state is a Probability Density Function (PDF) of finding a nucleon in a position of the phase space. We discretised this PDF and trained a Variational Auto-Encoder (VAE) to reproduce such a discrete PDF. As a proof of concept, we developed and trained a VAE to emulate BLOB in simulating the interactions of 12C with 12C at 62 MeV/u. To have more control on the generation, we forced the VAE latent space to be organised with respect to the impact parameter (b) training a classifier of b jointly with the VAE.
The distributions obtained from the VAE are similar to the input ones and the computation time needed to use the VAE as a generator is negligible.
We show that it is possible to use a Deep Learning approach to emulate a model developed to simulate nuclear reactions in the energy range of interest for Ion-therapy. We foresee the implementation of the generation part in C++ and to interface it with the most used Monte Carlo toolkit: Geant4.
We examine the sensitivity of a large scale two-phase liquid argon detector to the directionality of the dark matter signal. This study was performed under the assumption that, above 50 keV of recoil ...energy, one can determine (with some resolution) the direction of the recoil nucleus without head-tail discrimination, as suggested by past studies that proposed to exploit the dependence of columnar recombination on the angle between the recoil nucleus direction and the electric field. In this paper we study the differential interaction recoil rate as a function of the recoil direction angle with respect to the zenith for a detector located at the Laboratori Nazionali del Gran Sasso and we determine its diurnal and seasonal modulation. Using a likelihood-ratio based approach we show that, with the angular information alone, 100 (250) events are enough to reject the isotropic hypothesis at three standard deviation level, for a perfect (400 mrad) angular resolution. For an exposure of 100 tonne years this would correspond to a spin independent WIMP-nucleon cross section of about 10−46cm2 at 200 GeV WIMP mass. The results presented in this paper provide strong motivation for the experimental determination of directional recoil effects in two-phase liquid argon detectors.
Graphics Processing Units for HEP trigger systems Ammendola, R.; Bauce, M.; Biagioni, A. ...
Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment,
07/2016, Letnik:
824
Journal Article
Recenzirano
General-purpose computing on GPUs (Graphics Processing Units) is emerging as a new paradigm in several fields of science, although so far applications have been tailored to the specific strengths of ...such devices as accelerator in offline computation. With the steady reduction of GPU latencies, and the increase in link and memory throughput, the use of such devices for real-time applications in high-energy physics data acquisition and trigger systems is becoming ripe. We will discuss the use of online parallel computing on GPU for synchronous low level trigger, focusing on CERN NA62 experiment trigger system. The use of GPU in higher level trigger system is also briefly considered.
We describe a pilot project for the use of Graphics Processing Units (GPUs) for online triggering applications in High Energy Physics (HEP) experiments. Two major trends can be identified in the ...development of trigger and DAQ systems for HEP experiments: the massive use of general-purpose commodity systems such as commercial multicore PC farms for data acquisition, and the reduction of trigger levels implemented in hardware, towards a pure software selection system (trigger-less). The very innovative approach presented here aims at exploiting the parallel computing power of commercial GPUs to perform fast computations in software both at low- and high-level trigger stages. General-purpose computing on GPUs is emerging as a new paradigm in several fields of science, although so far applications have been tailored to the specific strengths of such devices as accelerator in offline computation. With the steady reduction of GPU latencies, and the increase in link and memory throughputs, the use of such devices for real-time applications in high-energy physics data acquisition and trigger systems is becoming very attractive. We discuss in details the use of online parallel computing on GPUs for synchronous low-level trigger with fixed latency. In particular we show preliminary results on a first test in the NA62 experiment at CERN. The use of GPUs in high-level triggers is also considered, the ATLAS experiment (and in particular the muon trigger) at CERN will be taken as a study case of possible applications.
We present the results of a search for dark matter weakly interacting massive particles (WIMPs) in the mass range below 20 GeV/c^{2} using a target of low-radioactivity argon with a 6786.0 kg d ...exposure. The data were obtained using the DarkSide-50 apparatus at Laboratori Nazionali del Gran Sasso. The analysis is based on the ionization signal, for which the DarkSide-50 time projection chamber is fully efficient at 0.1 keVee. The observed rate in the detector at 0.5 keVee is about 1.5 event/keVee/kg/d and is almost entirely accounted for by known background sources. We obtain a 90% C.L. exclusion limit above 1.8 GeV/c^{2} for the spin-independent cross section of dark matter WIMPs on nucleons, extending the exclusion region for dark matter below previous limits in the range 1.8-6 GeV/c^{2}.
We present new constraints on sub-GeV dark-matter particles scattering off electrons based on 6780.0 kg d of data collected with the DarkSide-50 dual-phase argon time projection chamber. This ...analysis uses electroluminescence signals due to ionized electrons extracted from the liquid argon target. The detector has a very high trigger probability for these signals, allowing for an analysis threshold of three extracted electrons, or approximately 0.05 keVee. We calculate the expected recoil spectra for dark matter-electron scattering in argon and, under the assumption of momentum-independent scattering, improve upon existing limits from XENON10 for dark-matter particles with masses between 30 and 100 MeV/c^{2}.
.
Building on the successful experience in operating the DarkSide-50 detector, the DarkSide Collaboration is going to construct DarkSide-20k, a direct WIMP search detector using a two-phase Liquid ...Argon Time Projection Chamber (LAr TPC) with an active (fiducial) mass of 23 t (20 t). This paper describes a preliminary design for the experiment, in which the DarkSide-20k LAr TPC is deployed within a shield/veto with a spherical Liquid Scintillator Veto (LSV) inside a cylindrical Water Cherenkov Veto (WCV). This preliminary design provides a baseline for the experiment to achieve its physics goals, while further development work will lead to the final optimization of the detector parameters and an eventual technical design. Operation of DarkSide-50 demonstrated a major reduction in the dominant
39
Ar background when using argon extracted from an underground source, before applying pulse shape analysis. Data from DarkSide-50, in combination with MC simulation and analytical modeling, shows that a rejection factor for discrimination between electron and nuclear recoils of
>
3
×
10
9
is achievable. This, along with the use of the veto system and utilizing silicon photomultipliers in the LAr TPC, are the keys to unlocking the path to large LAr TPC detector masses, while maintaining an experiment in which less than
<
0
.
1
events (other than
ν
-induced nuclear recoils) is expected to occur within the WIMP search region during the planned exposure. DarkSide-20k will have ultra-low backgrounds than can be measured
in situ
, giving sensitivity to WIMP-nucleon cross sections of
1
.
2
×
10
-
47
cm
2
(
1
.
1
×
10
-
46
cm
2
) for WIMPs of 1 TeV/c
2
(10 TeV/c
2
) mass, to be achieved during a 5 yr run producing an exposure of 100 t yr free from any instrumental background.
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