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Mapping neutrino nuclei interactions using electrons
Get PDFNext-generation neutrino facilities, such as DUNE, rely on precise modelling of neutrino-induced hadron knockout processes from nuclei in the detector medium (e.g, argon) to determine the initial (untagged) neutrino beam energy and
determine the neutrino flux. However, uncertainty in the modelling of these nuclear interactions constitutes the largest systematic uncertainty in extracting key physics,
including the neutrino oscillation parameters. Within the e4nu Collaboration at the Thomas Jefferson National Laboratory (JLab), we address this by studying the same
knockout reactions exploited at neutrino facilities, but using incident electron beams of precisely determined energy (up to 12 GeV). A range of hadron knockout reactions
from light to heavy nuclear targets are determined utilising the nearly complete acceptance of the CLAS12 spectrometer. This expansive data set will be used to benchmark nuclear calculations (GiBUU and GENIE) in the poorly constrained
kinematic regime of DUNE and will directly affect the achievable accuracy for the key physics outputs of DUNE. Our current results, the first from e4nu at CLAS12, are presented and implications for neutrino facilities discussed
Heavy-flavour hadronization in ultra-relativistic heavy-ion collisions: From AA to pp
Get PDFThe Λc/D0 ratio observed in AA collisions at RHIC and LHC
energies have a value of the order of the unity. On the other hand, the recent experimental measurements in pp collisions at both √s = 5.02 TeV and √s = 13 TeV have shown ratios for charm baryons/mesons Λc/D0 and Ξc/D0 larger than those measured and expected in elementary e+e− collisions. We present a hadronization mechanism based on the coalescence and fragmentation processes and we show that this model gives a consistent description of several observables involving heavy flavour hadrons from AA collisions to pp collisions. The results obtained within this approach suggest that a description of charmed hadron production in pp collisions require the assumption of the formation of a hot QCD matter at finite temperature.
Finally, extending this approach to study the production of hadrons containing multiple charm quarks, Ξcc, Ωcc and Ωccc we provide the predictions of multi-charmed hadrons in different collision systems, like Pb+Pb, Kr+Kr, Ar+Ar and O+O
A crystallographic method to investigate the presence of cluster configurations in 12C
Get PDFThis work presents a crystallographic approach for the investigation of the existence of cluster structures in the ground state of 12C, with some forecasts on its extension to other nuclei, such as 16O. The model is based on outstanding
analogies between the world of molecules and that of atomic nuclei: diffractive studies are indeed used to determine molecular structures and properties, and a similar approach was developed in the present work for atomic nuclei, under the assumption of the presence of regular α-cluster structures. In this work we analyzed a large database of literature data for the elastic scattering angular distributions of protons colliding on 12C and 4He target nuclei in the bombarding energy range Ep = 30–80 MeV, for which the de Broglie wavelength associated with the proton
beam is comparable with the distance existing between the assumed α-clusters inside the nucleus
Observations on the rotational seismic wavefield recorded in the Campi Flegrei volcanic area
Get PDFThe present work describes preliminary results of the analisys carried out on the signals provided by a rotational seismometer installed in the Campi Flegrei volcanic area. Starting from January 2021, a rotational seismometer (Lu
nitek Tellus R2) was installed in the area. The analyzed data consists of 20 local earthquakes occurred in Campi Flegrei from February 2021. The local seismicity is composed by low magnitude volcano tectonic earthquakes (MDmax =3.6) located at depth between 0.3 and 4 km b.s.l. For the strongest earthquake, we observed a maximum rotational velocity equal to 6 mrad/s. The joint use of the rotational
sensor and the accelerometer confirms the possibility of estimating the azimuth and the apparent velocity of the incoming wavefront and highlighted some more correlated phases in the coda of seismograms that could provide useful indications about the diffuse wave field recorded in the investigated area
External beam radiotherapy with electrons of low (IOeRT) and high (VHEE) energies: Status and prospects for conventional and FLASH irradiations
Get PDFThe field of cancer treatment is continuously evolving with the goal of enhancing tumor control probability, minimizing complications in normal tissues, and improving the life expectancy and quality of life for patients. Currently, there is a renewed focus on both low (Intra Operative electron Radio Therapy applications) and Very-High Energy Electron (VHEE) beams, particularly due to their potential to be delivered at FLASH intensities. The unique characteristics of electron interactions with matter can be leveraged to offer effective alternatives to standard
Radiotherapy (RT) and Proton Therapy (PT) treatments, with electron technology being the most adaptable for FLASH treatment deliveries among the three. In this study, we explore the achievable efficiency in IOeRT and VHEE treatments at both conventional and FLASH regimes using a GPU-based fast Monte Carlo (MC) simulation as a tool for dose calculation and treatment optimization. The results
obtained for partial breast irradiations and the treatment of pancreatic cancer will be compared with the latest technologies in RT and PT
A novel database of 90Y voxel S-Values including Internal Bremsstrahlung and an analytical model extending the calculation to any voxel size
Get PDFIn this paper we summarize our work aimed at producing via Monte Carlo (MC) simulations an updated database of Voxel S-Values (VSVs) for the radioisotope 90Y, widely used in nuclear medicine therapies. The usually neglected
contribution due to Internal Bremsstrahlung accompanying β-decay was included in the computation of the VSVs, increasing their accuracy with respect to pre-existing
databases. An analytical model enabling to extend the VSVs calculation to any voxel size of interest was additionally developed, to overcome the limitation due to the finite number of sizes directly evaluable via MC
Investigating the structure of cluster galaxies with combined strong lensing and stellar kinematics
Get PDFStrong lensing (SL) is a powerful probe of the dark matter (DM)
mass distribution in the cores of galaxy clusters, providing us with stringent tests of the cold DM (CDM) paradigm. SL models predict an excess of galaxy-galaxy SL events for observed galaxy clusters compared to simulated data based on cosmological simulations: this is reflected by a higher compactness for the observed cluster galaxies with respect to their simulated counterparts. We address this discrepancy by building improved SL models of cluster galaxies. We describe a SL model of the massive cluster Abell S1063, where the properties of the cluster galaxies are described more accurately than in previous studies using a parametrisation based on the Fundamental Plane relation, which we calibrated based on the observed kinematic properties of the members. We present new SL models for three galaxy lenses within the clusters MACS J0416.1−2403 and MACS J1206.2−0847; we have measured their truncation radius and their stellar-to-total mass fraction, extending
current studies on lens galaxies to lower mass limits. We compare our results with a suite of cosmological hydrodynamical simulations, testing the effects of the resolution and of the feedback set-up, and confirming the lower compactness predicted for simulated cluster galaxies. This persistent mismatch could point towards new physics beyond CDM
Biodiversity Change in the Anthropocene: Priorities for research. Book of Abstract. April 10th, 11th 2024
Get PDFWe are happy to present the Book of Abstracts for the Symposium entitled "Biodiversity Change in the Anthropocene: Priorities for Research" a national meeting organized by the
CNR-Istituto per le Risorse Biologiche e le Biotecnologie Marine (IRBIM) and CNR-Istituto di Ricerca sugli
Ecosistemi Terrestri (IRET), in collaboration with the Fano Marine Center, Lifewatch Italy and the National
Biodiversity Future Center. This Symposium was conceived, ideated and scientifically supported by the
Working Group Biodiversity of CNR, which was formally established in May 2021 as a network of
researchers aimed at enhancing Italian research on biodiversity
P-wave polarity determination via ensemble deep learning models
Get PDFP-wave first-motion polarities play a central role in understanding earth dynamics. Manual or classical automated procedures for determining polarities face several challenges. To address these issues, recent advanced studies leverage deep learning techniques, particularly Convolutional Neural Networks (CNNs). This paper explores the efficacy of ensemble deep learning approach, combining predictions from multiple CNN models. Ensemble methods exhibit improved overall performance and enhanced capabilities in managing waveforms showing no polarity.
Additionally, a specific augmentation procedure known as time-shift, enhances the ability to evaluate the uncertainty on noise-only waveforms
Artificial Intelligence-assisted thyroid cancer diagnosis from Raman spectra of histological samples
Get PDFRaman spectroscopy emerges as a highly promising diagnostic tool for thyroid cancer due to its capacity to discern biochemical alterations during cancer progression. This non-invasive and label/dye-free technique exhibits superior
efficacy in discriminating malignant features compared to traditional molecular tests, thereby minimizing unnecessary surgeries. Nevertheless, a key challenge in adopting Raman spectroscopy lies in identifying significant patterns and peaks. This study proposes an artificial intelligence approach for distinguishing healthy/benign from malignant nodules, ensuring interpretable outcomes. Raman spectra from histological samples are collected, and a set of peaks is selected using a data-driven, label-independent approach. Machine Learning algorithms are trained based on the relative prominence of these peaks, achieving performance metrics with an area under the receiver operating characteristic curve exceeding 0.9. To enhance inter
pretability, eXplainable Artificial Intelligence (XAI) is employed to compute each feature’s contribution to sample prediction