Scientific Open-access Literature Archive and Repository
Not a member yet
16397 research outputs found
Sort by
Fits of unpolarized proton and pion TMDs at N3LL accuracy
Get PDFWe present the most recent global extraction of unpolarized proton Transverse Momentum Dependent Parton Distribution Functions (TMD PDFs) and Fragmentation Functions from experimental data sets of Semi-Inclusive Deep Inelastic Scattering, Drell-Yan and Z-boson production. We also present an extraction of the pion TMD PDFs from all available data of unpolarized pion-nucleus Drell–Yan processes. Both fits are performed at next-to-next-to-next-to-leading log arithmic (N3LL) accuracy
Noise-enhanced stability of sine-Gordon breathers
Get PDFA noise-induced enhancement of the breather stability in a lossy, stochastic sine-Gordon system is discussed. The numerical solutions indicate that a spatially uniform noisy source enables a stationary breather to survive way beyond
its deterministic lifetime. An average characteristic time for the breather is defined, whose values vary nonmonotonically as a function of the noise strength, while being almost unaffected by the mode’s initial phase
The ReD experiment for the directional sensitivity of a double phase Ar TPC
Get PDFIn the research framework of Weakly Interacting Massive Particle as a Dark Matter candidate, directionality could be a key aspect to flag a signal nuclear recoil event. It could also be a crucial tool to reject isotropic background
sources coming from the irreducible neutrino scattering. The Recoil Directionality project within the Global Argon Dark Matter Collaboration aims to characterize the light and charge response of a liquid Argon dual-phase time projection chamber to neutron-induced nuclear recoils to probe the directional sensitivity of the detector in the energy range of interest of 20–100keV. In this work, such a possibility is investigated with a data-driven analysis involving a Machine Learning algorithm
BAO from HI intensity mapping: The role of multipoles and cross-correlations
Get PDFA standard ruler akin in application to standard candles, Baryon Acoustic Oscillations (BAO) are a main feature of the matter power spectrum, depending on fundamental quantities cosmologists are striving to measure. The SKA Observatory (SKAO) will look for their signal in the post-reionisation universe via neutral hydrogen Intensity Mapping, a task made challenging by astrophysical foregrounds and resolution limitations. To tackle these issues, we investigate the results emerging from the multipole expansion approach as a mitigation of such limitations and we showcase the gains made from cross-correlating the HI intensity mapping with spectroscopic galaxy observations. This is to be intended as an anticipation of future synergies between the SKAO Project and LSS Stage 4- or DESI-like instruments. Adding then the information from the quadrupole term allows for a detection of the BAO feature up to 4.5–6 σ at the lowest redshifts, providing robust constraints on the radial Alcock-Paczy´nski parameter (a proxy for the Hubble parameter). On the other hand, the corresponding perpendicular parameter remains
unconstrained and prior dominated due to beam effects
Decoupling of radionuclide production cumulative cross-sections and TTY: Application to the process natDy(d,x)155Ho → 155Dy → 155Tb
Get PDFNuclear reaction cross-sections are sometimes presented as cumulative, in the sense that not all production is due to direct reactions, but the decay of a co-produced isomeric state or radioactive father contributes to the total yield of the reaction. In this paper, we discuss one of the scenarios that occur more frequently. Moreover, the results are employed to discuss one of the production routes of the
medically relevant 155Tb
Robustness and predictivity of MRI-based radiomic features in glioma grade discrimination
Get PDFAnalysis pipelines based on Radiomics are widely used exploration tools in medical imaging. This study aims to define a robust processing pipeline based on the computation of radiomic features on multiparametric Magnetic Reso
nance Imaging data to make a Machine Learning classification between two diagnostic categories. As a case study, we considered the discrimination between high-grade and low-grade gliomas. The impact of intensity normalization techniques and different settings in image discretization on classification performances was studied. A set of MRI-reliable features was defined by selecting the most appropriate normalization and discretization settings. The results in glioma grade classification showed that the use of MRI-reliable features improves discrimination performances
The SHERPA project: Bent crystal-assisted beam extraction simulations
Get PDFIn this article, we report on the SHERPA project, aiming at de- veloping an efficient technique to extract a positron beam from one of the rings of the LNF DAΦNE collider, creating O(ms) long pulses. The most common slow ex- traction method is the resonant technique: after having created an unstable region in phase space, particles are gradually extracted from the circulating beam using a combination of electrostatic and magnetic septa. Instead, SHERPA proposes to use coherent processes in bent crystals, a cheaper and less complex alternative. This non-resonant technique, already used in hadron accelerators, will provide contin- uous multi-turn extraction with high efficiency. Various Geant4 simulations were carried out to study the channeling properties of positrons below GeV, in prepara- tion for the first beam tests of the crystals produced for SHERPA. For positrons in this energy region, no experimental data exist on crystal channeling. Validation of the Geant4 simulations was obtained using a combination of analytical theoretical equations and other Monte Carlo simulations
The GEMMAE project: A multidisciplinary study of Roman glass-gems
Get PDFAquileia, in northeastern Italy, is one of the most important ancient Roman archaeological sites worldwide. Its museum, among the other cultural her- itage materials, holds one of the most important and rich collections of gemstones, counting more than 6000 gems, dated between the 2nd century BC and the 2nd century AD and mainly discovered both in the ancient city and in its cemeteries. In other words, the collection principally counts stones with a known archaeological origin. Unfortunately, this is not true for all the gems. Due to this peculiarity, the chance to study this amazing collection represents a scientific privilege. In the present paper, the characterization project focused on the Roman glass-gems study, and a case study of the expected results will be preliminarily reported
Tear-based vibrational spectroscopy for non-invasive biomarker discovery in Amyotrophic Lateral Sclerosis
Get PDFIn recent literature, tear’s biomarkers analysis through spectroscopic techniques is emerging as a reliable tool to identify neurodegenerative diseases such as Alzheimer’s and Parkinson’s syndromes. The focus of this work is to discuss the results of the application of Raman Spectroscopy on tears collected from patients affected by Amyotrophic Lateral Sclerosis (ALS), comparing to healthy controls. Showing high specificity and sensitivity, both differential and multivariate analysis have reported differences in spectral components, principally identified in two peaks related to Phenylalanine and Amide I. Furthermore, as distinctive for the neurode- generative diseases, protein and lipids alterations have been found. The results, being confirmed by a parallel study conducted by infrared (IR) spectroscopy on the same samples, lead to the prospect of defining the technique supportive in the diagnosis of ALS, exploiting tears as a source of biomarkers
Capturing correlations in vision parameters by artificial neural networks
Get PDFUnderstanding the correlations between different visual functions is fundamental to ensure the right intervention to solve refractive problems. Existing studies are based on complex procedures, where it is possible to address analysis through empirical models. A different approach that has shown great functionality are neural networks, since they are able to find correlations within large collections of data with little assistance from the user. The present study stems from the desire to develop a prediction algorithm through Neural Networks by adopting a black-box approach. The objective is to design a network able to predict the values of visual acuity from the refractive errors and take into account correlation between the two quantities. For the construction of the network in questions, 136 eyes (68 subjects) were included, and, even using commercial, unsophisticated tools, the predictions for visual acuity remain close to the actual one. Our results give hope for the wide diffusion of this contact between optometry and neural networks