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In this work we provide a model-independent experimental evaluation of the degree of isospin equilibration taking place in $^{58,64}$Ni+$^{58,64}$Ni collisions at 32 MeV/nucleon across varying reaction centralities. This result has been obtained by combining the complementary information provided by two different datasets, sharing common characteristics. The first dataset has been acquired with the INDRA setup and has been used to implement a model-independent reconstruction of the impact parameter. The second dataset has been acquired in the first experimental campaign of the coupled INDRA-FAZIA apparatus at GANIL. The neutron-to-proton content of the quasiprojectile remnant measured by FAZIA has been employed as isospin observable. The effect of isospin diffusion has been evidenced by means of the isospin transport ratio, reported as a function of the impact parameter of the collision. The evolution towards isospin equilibration from semiperipheral to more central collisions is clearly extracted. This experimental result, expanding our previous works (Phys. Rev. C 106, 024603 (2022) and Phys. Rev. C 108, 054611 (2023)), can be compared with the predictions of any transport model, and can thus be used to set constraints on the behavior of the symmetry energy term of the nuclear Equation of State at sub- to saturation densities.

We propose a novel two-stage semi-supervised learning approach for training downsampling-upsampling semantic segmentation architectures. The first stage does not use backpropagation. Rather, it exploits the bio-inspired Hebbian principle "fire together, wire together" as a local learning rule for updating the weights of both convolutional and transpose-convolutional layers, allowing unsupervised discovery of data features. In the second stage, the model is fine-tuned with standard backpropagation on a small subset of labeled data. We evaluate our methodology through experiments conducted on several widely used biomedical datasets, deeming that this domain is paramount in computer vision and is notably impacted by data scarcity. Results show that our proposed method outperforms SOTA approaches across different levels of label availability. Furthermore, we show that using our unsupervised stage to initialize the SOTA approaches leads to performance improvements. The code to replicate our experiments can be found at: https://github.com/ciampluca/hebbian-medical-image-segmentation

Characterization of the participant-zone (PZ) in the $^{129,124}$Xe + $^{112,124}$Sn reaction at the energy range 65-150 MeV/nucleon reveals copious cluster production. A detailed study of the chemical composition as a function of the impact parameter shows that heavier clusters ($^6$He, $^{6-8}$Li, $^{7-10}$Be...) are most likely produced for central collisions. A hierarchy of the cluster production with the neutron-richness of the total system is observed, suggesting a full mixing of the projectile and target in the PZ. An estimate of the maximum density in central collisions has been deduced from the kinetic energy of the emitted fragments, reaching almost 2 time the normal density (2$\rho_0$) at 150 MeV/nucleon., Comment: 5 pages, 3 figures, nn2024 conference

Recently, object counting has shifted towards class-agnostic counting (CAC), which counts instances of arbitrary object classes never seen during model training. With advancements in robust vision-and-language foundation models, there is a growing interest in prompt-based CAC, where object categories are specified using natural language. However, we identify significant limitations in current benchmarks for evaluating this task, which hinder both accurate assessment and the development of more effective solutions. Specifically, we argue that the current evaluation protocols do not measure the ability of the model to understand which object has to be counted. This is due to two main factors: (i) the shortcomings of CAC datasets, which primarily consist of images containing objects from a single class, and (ii) the limitations of current counting performance evaluators, which are based on traditional class-specific counting and focus solely on counting errors. To fill this gap, we introduce the Prompt-Aware Counting (PrACo) benchmark. It comprises two targeted tests coupled with evaluation metrics specifically designed to quantitatively measure the robustness and trustworthiness of existing prompt-based CAC models. We evaluate state-of-the-art methods and demonstrate that, although some achieve impressive results on standard class-specific counting metrics, they exhibit a significant deficiency in understanding the input prompt, indicating the need for more careful training procedures or revised designs. The code for reproducing our results is available at https://github.com/ciampluca/PrACo., Comment: Accepted at WACV 2025 Conference

The emission of the pre-equilibrium particles during nuclear collisions at moderate beam energies is still an open question. This influences the properties of the compound nucleus but also changes the interpretation of the quasi-fission process. A systematic analysis of the data obtained by the FAZIA collaboration during a recent experiment with a neutron rich projectile is presented. The full range of charged particles detected in the experiment is within the limit of isotopic resolution of the FAZIA detector. Quasi-projectile (QP) fragments were detected in majority thanks to the forward angular acceptance of the experimental setup which was confirmed by introducing cuts based on the HIPSE event generator calculations. The main goal was to compare the experimental results with the HIPSE simulations after introducing these cuts to investigate the influence of the n-rich entrance channel on the QP fragment properties. More specifically, the lowering of N/Z of QP fragments with beam energy was found to be present since the initial phase of the reaction. Thus, pre-equilibrium emissions might be a possible candidate to explain such an effect., Comment: 10 pages, 10 figures

A detailed knowledge of the decay properties of the so called Hoyle state in the $^{12}$C nucleus ($E_x=7.654$ MeV, $0^+$) is required to calculate the rate at which carbon is forged in typical red-giant stars. This paper reports on a new almost background-free measurement of the radiative decay branching ratio of the Hoyle state using advanced charged particle coincidence techniques. The exploitation, for the first time in a similar experiment, of a bidimensional map of the coincidence efficiency allows to reach an unitary value and, consequently, to strongly reduce sources of systematic uncertainties. The present results suggest a value of the radiative branching ratio of $\Gamma_{rad}/\Gamma_{tot}=4.2(6)\cdot10^{-4}$. This finding helps to resolve the tension between recent data published in the literature.

This article presents an investigation of isospin equilibration in cross-bombarding $^{40,48}$Ca$+^{40,48}$Ca reactions at 35 MeV/nucleon, by comparing experimental data with filtered transport model calculations. Isospin diffusion is studied using the evolution of the isospin transport ratio with centrality. The asymmetry parameter $\delta=(N-Z)/A$ of the quasiprojectile (QP) residue is used as isospin-sensitive observable, while a recent method for impact parameter reconstruction is used for centrality sorting. A benchmark of global observables is proposed to assess the relevance of the antisymmetrized molecular dynamics (AMD) model, coupled to GEMINI++, in the study of dissipative collisions. Our results demonstrate the importance of considering cluster formation to reproduce observables used for isospin transport and centrality studies. Within the AMD model, we prove the applicability of the impact parameter reconstruction method, enabling a direct comparison to the experimental data for the investigation of isospin diffusion. For both, we evidence a tendency to isospin equilibration with an impact parameter decreasing from 9 to 3 fm, while the full equilibration is not reached. A weak sensitivity to the stiffness of the equation of state employed in the model is also observed, with a better reproduction of the experimental trend for the neutron-rich reactions.

Heavy-ion collisions are a good tool to explore hot nuclear matter below saturation density. It has been established that if a nuclear system reaches the thermal and chemical equilibrium, this leads to scaling properties in the isotope production when comparing two systems which differ in proton fraction. This article presents a study of the isoscaling properties of an expanding gas source exploring different thermodynamic states (density, temperature, proton fraction). This experimental work highlights the existence of an isoscaling relationship for hydrogen and 3He, 4He helium isotopes which agrees with the hypothesis of thermal and chemical equilibrium. Moreover, this work reveals the limitations of isoscaling when the two systems differ slightly in total mass and temperature. Also, a discrepancy has been observed for the 6He isotope, which could be explained by finite size effects or by the specific halo nature of this cluster.

Fusion enhancement for neutron-rich isotopes of oxygen on carbon nuclei was probed. To measure the fusion cross-section a $^{20}$O beam accelerated to E$_{lab}$/A=2.7 MeV bombarded the active-target detector MuSIC@Indiana with a fill gas of CH$_4$. Examination of the average fusion cross-section over the interval 12 MeV $\leq$E$_{c.m.}$$\leq$ 17 MeV for $^{16-20}$O + $^{12}$C reveals that while even isotopes of oxygen exhibit essentially the same cross-section, the cross-section for odd isotopes can be either enhanced or suppressed relative to the even A members of the isotopic chain. Theoretical models fail to explain the observed experimental results., Comment: 6 pages, 4 figures

An investigation of the quasiprojectile breakup channel in semiperipheral and peripheral collisions of $^{58,64}$Ni+$^{58,64}$Ni at 32 and 52 MeV/nucleon is presented. Data have been acquired in the first experimental campaign of the INDRA-FAZIA apparatus in GANIL. The effect of isospin diffusion between projectile and target in the two asymmetric reactions has been highlighted by means of the isospin transport ratio technique, exploiting the neutron-to-proton ratio of the quasiprojectile reconstructed from the two breakup fragments. We found evidence that, for the same reaction centrality, a higher degree of relaxation of the initial isospin imbalance is achieved in the breakup channel with respect to the more populated binary output, possibly indicating the indirect selection of specific dynamical features. We have proposed an interpretation based on different average projectile-target contact times related to the two exit channels under investigation, with a longer interaction for the breakup channel. The time information has been extracted from AMD simulations of the studied systems coupled to GEMINI++: the model calculations support the hypothesis hereby presented.

Generally, crowd datasets can be collected or generated from real or synthetic sources. Real data is generated by using infrastructure-based sensors (such as static cameras or other sensors). The use of simulation tools can significantly reduce the time required to generate scenario-specific crowd datasets, facilitate data-driven research, and next build functional machine learning models. The main goal of this work was to develop an extension of crowd simulation (named CrowdSim2) and prove its usability in the application of people-tracking algorithms. The simulator is developed using the very popular Unity 3D engine with particular emphasis on the aspects of realism in the environment, weather conditions, traffic, and the movement and models of individual agents. Finally, three methods of tracking were used to validate generated dataset: IOU-Tracker, Deep-Sort, and Deep-TAMA.

Data scarcity has become one of the main obstacles to developing supervised models based on Artificial Intelligence in Computer Vision. Indeed, Deep Learning-based models systematically struggle when applied in new scenarios never seen during training and may not be adequately tested in non-ordinary yet crucial real-world situations. This paper presents and publicly releases CrowdSim2, a new synthetic collection of images suitable for people and vehicle detection gathered from a simulator based on the Unity graphical engine. It consists of thousands of images gathered from various synthetic scenarios resembling the real world, where we varied some factors of interest, such as the weather conditions and the number of objects in the scenes. The labels are automatically collected and consist of bounding boxes that precisely localize objects belonging to the two object classes, leaving out humans from the annotation pipeline. We exploited this new benchmark as a testing ground for some state-of-the-art detectors, showing that our simulated scenarios can be a valuable tool for measuring their performances in a controlled environment., Comment: Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 2023

Four different reactions, $^{32}$S+$^{12}$C and $^{20}$Ne+$^{12}$C at 25 and 50 MeV/nucleon, have been measured with the FAZIA detector capable of full isotopic identification of most forward emitted reaction products. Fragment multiplicities, angular distributions and energy spectra have been measured and compared with Monte Carlo simulations, i.e. the antisymmetrized molecular dynamics (AMD) and the heavy-ion phase space exploration (HIPSE) models. These models are combined with two different afterburner codes (HF$l$ and SIMON) to describe the decay of the excited primary fragments. In the case of AMD, the effect of including the clustering and inter-clustering processes to form bound particles and fragments is discussed. A clear confirmation of the role of cluster aggregation in the reaction dynamics and particle production for these light systems, for which the importance of the clustering process increases with bombarding energy, is obtained., Comment: 15 pages, 14 PDF figures

An analysis of the asymmetric reactions $^{40,48}$Ca+$^{12}$C at 25 and 40 MeV/nucleon is presented. Data have been collected with six modules of the FAZIA array. The analysis is focused on the breakup channel of sources produced in dissipative collisions, partially corresponding to incomplete fusion processes. The study has been performed both on detected fragments and on some resonances reconstructed by means of particle-fragment correlations, with a focus on the evolution of the breakup channel with the beam energy and the neutron content of the system, looking in particular at the relative velocity between the breakup fragments. Results show that also Carbon fragments reconstructed by means of particle correlations can be in large part interpreted as the light partner of a scission.

Automatic people counting from images has recently drawn attention for urban monitoring in modern Smart Cities due to the ubiquity of surveillance camera networks. Current computer vision techniques rely on deep learning-based algorithms that estimate pedestrian densities in still, individual images. Only a bunch of works take advantage of temporal consistency in video sequences. In this work, we propose a spatio-temporal attentive neural network to estimate the number of pedestrians from surveillance videos. By taking advantage of the temporal correlation between consecutive frames, we lowered state-of-the-art count error by 5% and localization error by 7.5% on the widely-used FDST benchmark., Comment: Accepted at IEEE ISCC 2022

In this dissertation, we investigated and enhanced Deep Learning (DL) techniques for counting objects, like pedestrians, cells or vehicles, in still images or video frames. In particular, we tackled the challenge related to the lack of data needed for training current DL-based solutions. Given that the budget for labeling is limited, data scarcity still represents an open problem that prevents the scalability of existing solutions based on the supervised learning of neural networks and that is responsible for a significant drop in performance at inference time when new scenarios are presented to these algorithms. We introduced solutions addressing this issue from several complementary sides, collecting datasets gathered from virtual environments automatically labeled, proposing Domain Adaptation strategies aiming at mitigating the domain gap existing between the training and test data distributions, and presenting a counting strategy in a weakly labeled data scenario, i.e., in the presence of non-negligible disagreement between multiple annotators. Moreover, we tackled the non-trivial engineering challenges coming out of the adoption of Convolutional Neural Network-based techniques in environments with limited power resources, introducing solutions for counting vehicles and pedestrians directly onboard embedded vision systems, i.e., devices equipped with constrained computational capabilities that can capture images and elaborate them., Comment: Version with high-quality images can be found at https://etd.adm.unipi.it/theses/available/etd-04262022-163702/. arXiv admin note: text overlap with arXiv:1802.03601, arXiv:1707.01202, arXiv:1809.02165, arXiv:1901.06026, arXiv:1808.01244 by other authors

An investigation of the isospin equilibration process in the reactions $^{58,64}$Ni+$^{58,64}$Ni at two bombarding energies in the Fermi regime ($32\,$MeV/nucleon and $52\,$MeV/nucleon) is presented. Data have been acquired during the first experimental campaign of the coupled INDRA-FAZIA apparatus in GANIL. Selecting from peripheral to semi-central collisions, both the neutron content of the quasiprojectile residue and that of the light ejectiles coming from the quasiprojectile evaporation have been used as probes of the dynamical process of isospin diffusion between projectile and target for the asymmetric systems. The isospin transport ratio technique has been employed. The relaxation of the initial isospin imbalance with increasing centrality has been clearly evidenced. The isospin equilibration appears stronger for the reactions at $32\,$MeV/nucleon, as expected due to the longer projectile-target interaction time than at $52\,$MeV/nucleon. Coherent indications of isospin equilibration come from the quasiprojectile residue characteristics and from particles ascribed to the quasiprojectile decay.

Modern Unmanned Aerial Vehicles (UAV) equipped with cameras can play an essential role in speeding up the identification and rescue of people who have fallen overboard, i.e., man overboard (MOB). To this end, Artificial Intelligence techniques can be leveraged for the automatic understanding of visual data acquired from drones. However, detecting people at sea in aerial imagery is challenging primarily due to the lack of specialized annotated datasets for training and testing detectors for this task. To fill this gap, we introduce and publicly release the MOBDrone benchmark, a collection of more than 125K drone-view images in a marine environment under several conditions, such as different altitudes, camera shooting angles, and illumination. We manually annotated more than 180K objects, of which about 113K man overboard, precisely localizing them with bounding boxes. Moreover, we conduct a thorough performance analysis of several state-of-the-art object detectors on the MOBDrone data, serving as baselines for further research., Comment: Accepted at ICIAP 2021

Integrated technologies greatly enhance the prospects for practical quantum information processing and sensing devices based on trapped ions. High-speed and high-fidelity ion state readout is critical for any such application. Integrated detectors offer significant advantages for system portability and can also greatly facilitate parallel operations if a separate detector can be incorporated at each ion-trapping location. Here we demonstrate ion quantum state detection at room temperature utilizing single-photon avalanche diodes (SPADs) integrated directly into the substrate of silicon ion trapping chips. We detect the state of a trapped $^{88}\text{Sr}^{+}$ ion via fluorescence collection with the SPAD, achieving $99.92(1)\%$ average fidelity in 450 $\mu$s, opening the door to the application of integrated state detection to quantum computing and sensing utilizing arrays of trapped ions., Comment: 7 pages, 5 figures

This study is the first to provide a systematic review of the literature focused on the relationship between digitalization and organizational agility (OA). It applies the bibliographic coupling method to 171 peer-reviewed contributions published by 30 June 2021. It uses the digitalization perspective to investigate the enablers, barriers and benefits of processes aimed at providing firms with the agility required to effectively face increasingly turbulent environments. Three different, though interconnected, thematic clusters are discovered and analysed, respectively focusing on big-data analytic capabilities as crucial drivers of OA, the relationship between digitalization and agility at a supply chain level, and the role of information technology capabilities in improving OA. By adopting a dynamic capabilities perspective, this study overcomes the traditional view, which mainly considers digital capabilities enablers of OA, rather than as possible outcomes. Our findings reveal that, in addition to being complex, the relationship between digitalization and OA has a bidirectional character. This study also identifies extant research gaps and develops 13 original research propositions on possible future research pathways and new managerial solutions.

A multi-layer trigger system, based on programmable logic devices hosted on VME boards, has been implemented. It is completely scalable and suitable for handling from a few up to a few hundred channels. Custom software for monitoring and controlling the trigger system has been developed., Comment: 23 pages, 4 figures, Published on Nuclear Instruments and Methods in Physics Research A. For associated software/firmware package see https://github.com/NUCLEX-Fi/FTBOX.git

This paper presents a novel solution to automatically count vehicles in a parking lot using images captured by smart cameras. Unlike most of the literature on this task, which focuses on the analysis of single images, this paper proposes the use of multiple visual sources to monitor a wider parking area from different perspectives. The proposed multi-camera system is capable of automatically estimate the number of cars present in the entire parking lot directly on board the edge devices. It comprises an on-device deep learning-based detector that locates and counts the vehicles from the captured images and a decentralized geometric-based approach that can analyze the inter-camera shared areas and merge the data acquired by all the devices. We conduct the experimental evaluation on an extended version of the CNRPark-EXT dataset, a collection of images taken from the parking lot on the campus of the National Research Council (CNR) in Pisa, Italy. We show that our system is robust and takes advantage of the redundant information deriving from the different cameras, improving the overall performance without requiring any extra geometrical information of the monitored scene., Comment: Submitted to Expert Systems With Applications

The neutron-proton equilibration process in 48 Ca+ 40 Ca at 35 MeV/nucleon bombarding energy has been experimentally estimated by means of the isospin transport ratio. Experimental data have been collected with a subset of the FAZIA telescope array, which permitted to determine Z and N of detected fragments. For the first time, the QP evaporative channel has been compared with the QP break-up one in a homogeneous and consistent way, pointing out to a comparable n-p equilibration which suggests close interaction time between projectile and target independently of the exit channel. Moreover, in the QP evaporative channel n-p equilibration has been compared with the prediction of the Antisymmetrized Molecular Dynamics (AMD) model coupled to the GEMINI statistical model as an afterburner, showing a larger probability of proton and neutron transfers in the simulation with respect to the experimental data.

Secure two-party computation considers the problem of two parties computing a joint function of their private inputs without revealing anything beyond the output. In this work, we consider the setting where the two parties (a classical Alice and a quantum Bob) can communicate only via a classical channel. Our first result shows that it is in general impossible to realize a two-party quantum functionality with black-box simulation in the case of malicious quantum adversaries. In particular, we show that the existence of a secure quantum computing protocol that relies only on classical channels would contradict the quantum no-cloning argument. We circumvent this impossibility following three different approaches. The first is by considering a weaker security notion called one-sided simulation security. This notion protects the input of one party (the quantum Bob) in the standard simulation-based sense and protects the privacy of the other party's input (the classical Alice). We show how to realize a protocol that satisfies this notion relying on the learning with errors assumption. The second way to circumvent the impossibility result, while at the same time providing standard simulation-based security also against a malicious Bob, is by assuming that the quantum input has an efficient classical representation. Finally, we focus our attention on the class of zero-knowledge functionalities and provide a compiler that takes as input a classical proof of quantum knowledge (PoQK) protocol for a QMA relation R and outputs a zero-knowledge PoQK for R that can be verified by classical parties. The direct implication of our result is that Mahadev's protocol for classical verification of quantum computations (FOCS'18) can be turned into a zero-knowledge proof of quantum knowledge with classical verifiers. To the best of our knowledge, we are the first to instantiate such a primitive., Comment: (v2) changed the title, added new results, and improved readability. 55 pages

Isospin transport ratio is a powerful method to estimate the neutron-proton (n-p) equilibration in heavy-ion collisions, and extensively used to obtain information on the asy-stiffness of the nuclear Equation of State. In fact such a ratio is expected to bypass any perturbations introducing a linear transformation of the chosen observable. In particular, it is supposed to overcome contributions due to emission, either of dynamical or statistical nature, from the primary fragments formed during the collisions. In this paper we explore the validity of this assumption, looking at the quasi-projectile n-p ratio ($N/Z$) in peripheral and semi-peripheral events for Ca+Ca reactions at 35\amev{}, simulated via the Antisymmetrized Molecular Dynamics transport model, coupled to different statistical decay codes. The statistical de-excitation of the primary fragments introduces a linear transformation at relatively high excitation energies (above 2\amev{}) when the residue approaches the Evaporation Attractor Line, while some effect is produced at lower excitation energies due to the occurrence of some non-linearities. As for fast emissions after the end of the projectile-target interaction it is shown that they introduce a non-linear transformation too.

Monitoring vehicle flows in cities is crucial to improve the urban environment and quality of life of citizens. Images are the best sensing modality to perceive and assess the flow of vehicles in large areas. Current technologies for vehicle counting in images hinge on large quantities of annotated data, preventing their scalability to city-scale as new cameras are added to the system. This is a recurrent problem when dealing with physical systems and a key research area in Machine Learning and AI. We propose and discuss a new methodology to design image-based vehicle density estimators with few labeled data via multiple camera domain adaptations., Comment: 1st International Workshop on New Foundations for Human-Centered AI (NeHuAI) at ECAI-2020