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From photoelectrons to bytes: development and integration of photosensors and data acquisition for the DarkSide-20k experiment
No full textThe search for Dark Matter (DM) remains one of the most compelling challenges in contemporary physics.
The DarkSide-20k experiment, a dual-phase liquid argon Time Projection Chamber (TPC) under construction
at the Laboratori Nazionali del Gran Sasso (LNGS), aims to directly detect Weakly Interacting Massive Particles (WIMPs) with unprecedented sensitivity. This thesis presents the development, integration, and characterisation of the
photodetector and the data acquisition system that form the backbone of DarkSide-20k.
The first part of the work focuses on the design, production, and characterisation of cryogenic Silicon Photo-Multipliers (SiPMs), integrated into objects called \textit{Tiles}. A large-scale quality assurance and control program was established to certify thousands of
photodetector Tiles, ensuring uniform performance in terms of optical properties and noise characteristics.
The implementation of automated testing procedures, a centralised production database, and real-time monitoring tools enabled
consistent tracking and validation across multiple assembly sites.
The second part of the thesis describes the architecture and implementation of the DarkSide-20k Data Acquisition (DAQ)
system. A triggerless acquisition, segmented into fixed-length time slices, is envisaged to manage the high data throughput of the detector, combining waveform digitisation, real-time data processing, and online data reduction. Extensive simulation studies and prototype validation through the \textit{Quadrant} DAQ prototype were conducted to assess system performance, understand busy logic, and ensure scalability
to the full detector.
The final part of the thesis presents results from \textsc{Proto-0}, the first operational prototype of the DarkSide-20k TPC.
The prototype provided a crucial testbed for the DarkSide-20k photosensors and DAQ system, enabling a thorough detector characterisation, studies of scintillation (S1) and electroluminescence (S2) signals, and validation of the triggerless data acquisition system envisaged for DarkSide-20k.
A dedicated reconstruction framework was developed for \textsc{Proto-0}, providing a valuable platform for testing and benchmarking event reconstruction algorithms.
Together, these developments demonstrate the readiness of the DarkSide-20k technologies and methodologies, marking
essential milestones toward the next generation of liquid argon Dark Matter detectors. The results reported herein contribute directly
to the realisation of a multi-ton experiment capable of probing WIMP-nucleon cross sections below
, advancing the frontier of direct Dark Matter searches
TIMESAFE. Timing interruption monitoring and security assessment for fronthaul environments
No full text5G and beyond cellular systems embrace the disaggregation of Radio Access Network (RAN) components, exemplified by the evolution of the fronthaul (FH) connection between cellular baseband and radio unit equipment. Crucially, synchronization over the FH is pivotal for reliable 5G services. In recent years, there has been a push to move these links to an Ethernet-based packet network topology, leveraging existing standards and ongoing research for Time-Sensitive Networking (TSN). However, TSN standards, such as Precision Time Protocol (PTP), focus on performance with little to no concern for security. This increases the exposure of the open FH to security risks. Attacks targeting synchronization mechanisms pose significant threats, potentially disrupting 5G networks and impairing connectivity.
In this article, we demonstrate the impact of successful spoofing and replay attacks against PTP synchronization. We show how a spoofing attack is able to cause a production-ready O-RAN and 5G-compliant private cellular base station to catastrophically fail within 2 seconds of the attack, necessitating manual intervention to restore full network operations. To counter this, we design a Machine Learning (ML)-based monitoring solution capable of detecting various malicious attacks with over 97.5% accuracy
Sapienza University of Rome and Sudan: Recent activities between archives and digital communication
No full textThe contribution offers an overview of the latest research initiatives of University of Rome “La Sapienza” activated before and after the crisis. The fieldwork at Hujair Gubli and Magal, recently established in collaboration with NCAM but interrupted by the outbreak of the war, is first presented. The prolonged conflict has forced a re-definition and re-calibration of efforts, which have shifted toward archival research and digital communication. Significant material related to the Italian archaeological work conducted in Sudan in the last century has been recovered, digitised, and is currently under review. Its study deepens our understanding of past archaeological practices, adds valuable pieces of information on the preservation and transformation of Sudanese cultural heritage, plays a crucial role in disseminating the multifaceted histories of such heritage. The ongoing documentation, archival and museum activities, will be thus discussed and reflected upon in the context of present situation and future challenge
A Machine Learning Approach to Passivity-Preserving Safety-Critical Control
No full textPassivity-Based Control enables to constructively synthetize controllers with guarantees on the stability of the overall system. Although safety-critical control based on Control Barrier Functions is able to synthetize controllers that effectively cope with state constraints, passivity and input bounds are not addressed in general. This paper proposes a novel model-based Machine Learning methodology aimed at synthesizing Control Barrier Functions such that passivity of the closed loop system is preserved under safety-critical control and input saturation. Numerical simulations on a cart-pole system and on a 2R robot validate the effectiveness of the proposed control strategy in terms of performances and passivity preservation
The influence of the Mediterranean dietary pattern on male and female sexual dysfunctions: an updated review
No full textBackground: Sexual dysfunctions affect a large percentage of men and women worldwide. Dietary patterns, such as the Mediterranean diet (MeD), may play a role in the protection of sexual dysfunction. The aim of the present narrative review was to investigate the influence of MeD dietary patterns on male and female sexual dysfunctions. We aimed to evaluate potential mechanisms and clinical implications that could prompt further research and dietary recommendations. Methods: An electronic database search was performed to identify and retrieve peer-reviewed articles that examined the association of the MeD with sexual function in adults. Results: Although the included studies were heterogeneous in design and outcome measures, most reported a positive association between increased adherence to a MeD pattern and better sexual function for both sexes. Higher adherence in men results in improved erectile performance and reduced frequency of erectile dysfunction. The results pointed to a possible improvement in all domains of overall sexual satisfaction for women who adhere to the MeD. Potential underlying mechanisms include improvements in vascular health, anti-inflammatory actions, and healthier metabolic profiles, which collectively may exert favorable effects on sexual function. Conclusions: Preliminary evidence supports a beneficial role of the MeD patterns on sexual health in both genders. While the findings are encouraging, confirmation of causality, together with more detailed practical recommendations, will require larger-scale, longitudinal, and interventional studies with standardized measures. Future work should focus on the identification of specific components of the MeD that promote the benefits described and explore personalized interventions to optimize sexual function
Investigating brain morphometry in prodromal dementia with Lewy bodies. A preliminary MRI-based cortical thickness analysis
No full textObjectives: Prodromal dementia with Lewy bodies (pro-DLB) has gained attention in the field of dementia prevention. However, identifying reliable biomarkers remains a challenge. This ongoing study aims to characterize brain alterations in prodromal DLB (pro-DLB) relative to the healthy population and prodromal Alzheimer’s disease (AD), with a focus on pro-DLB phenotypical onsets: mild cognitive impairment (MCI-DLB) and psychiatric (PSY).
Methods: We recruited 54 patients (20 MCI-DLB, 20 MCI-AD, 14 PSY) and 15 healthy controls (HC). Participants underwent structural and functional MRI. A preliminary Voxel-Based Morphometry (VBM) analysis was performed using CAT12 within SPM12. Gray matter volume (GMV) differences among groups were compared via one-way ANOVA.
Results: VBM revealed structural damage in both MCI-DLB and PSY patients relative to HC. Frontal atrophy affected the superior frontal gyrus, supplementary motor area, and anterior/middle cingulum. Parietal damage involved the precuneus, with additional atrophy in posterior parietal areas in PSY and the posterior cingulum in MCI-DLB. Temporal atrophy was limited to inferior temporal and fusiform gyri, although PSY patients also exhibited reductions in the left medial temporal lobe. Occipital atrophy was observed in the cuneus, with additional bilateral damage in the early visual cortex in MCI-DLB and middle occipital gyrus in PSY. Subcortical atrophy involved the caudate and olfactory area. No significant GMV differences emerged between pro-DLB subgroups, both showing relative hippocampal preservation compared to MCI-AD.
Conclusions: Pro-DLB is characterized by atrophy in frontal, parietal, and occipital areas, aligning with core clinical and neuropsychological features of overt DLB. Structural MRI may aid in distinguishing pro-DLB from healthy aging and prodromal stages of other neurodegenerative disorders, like AD. Lastly, differences between pro-DLB phenotypes might be associated with functional rather than macro-structural alterations
Structure and function of persulfide dioxygenase from Pseudomonas aeruginosa: Implications on H2S homeostasis and interplay with nitric oxide
No full textHydrogen sulfide is an important signaling molecule, beneficial at physiological concentrations but harmful at higher levels, due to which a tight control of its bioavailability is essential. Here, we investigated persulfide dioxygenase, an enzyme involved in H2S catabolism, from the pathogen Pseudomonas aeruginosa (PaPDO). Deletion of the gene pdo led to a 4-fold increase in H2S concentration, confirming its physiological role. The recombinant enzyme was structurally characterized at 2.06 Å resolution and assigned to the metallo-β-lactamase superfamily. Compared with its human homolog, PaPDO displayed a different dimerization area and a larger active site, suggesting different substrate preferences. Functionally, PaPDO catalyzed glutathione persulfide dioxygenation with a high turnover rate, and its activity was enhanced by reduced glutathione. Interestingly, the results show that PaPDO binds to nitric oxide, which reversibly inhibits its catalytic activity. These findings reveal a novel mechanism of crosstalk between hydrogen sulfide and nitric oxide signaling and provide insights into redox regulation in a multidrug-resistant pathogen
Data Fusion and change detection techniques based on optical and Synthetic Aperture Radar satellite imagery for damage mapping and multi-temporal assessment of the recovery and reconstruction process after natural disasters
No full textThis doctoral research aims to evaluate the potential of Earth Observation (EO) and Geographic Information Systems (GIS) for monitoring long-term recovery and resilience in disaster-prone environments. While remote sensing is a well-established means for damage assessment during emergencies and the scientific literature has focused on developing new algorithms and improving the accuracy of the existing ones, very few studies have shown how satellite imagery can be used by technical officers of affected countries to provide crucial, up-to-date information to monitor the reconstruction progress and natural restoration.
Two case studies were developed in Haiti after Hurricane Matthew and in La Mojana, Colombia, to assess recovery after a series of catastrophic floods. By integrating freely available optical and Synthetic Aperture Radar (SAR) satellite imagery—primarily Sentinel-1 and Sentinel-2—and, in the case of La Mojana, machine learning techniques such as Random Forest classification, the study demonstrates cost-effective methodologies capable of operating under data and resource constraints. In Haiti, the analysis following Hurricane Matthew operationalized EO-based recovery monitoring at a national scale, enabling the detection of affected areas, reconstruction patterns, and settlement dynamics even in inaccessible regions. In La Mojana, the fusion of SAR and optical data enhanced flood impact assessments, revealing the spatial and temporal complexity of recovery processes.
The comparative analysis highlights the need for methodological accessibility and scalability in developing and low-income countries, where technical capacity and data availability are limited. It underscores that recovery is neither linear nor homogeneous, requiring temporally adaptive monitoring frameworks aligned with local hazard cycles. The research also emphasizes the critical role of multi-sensor validation, demonstrating that analytical reliability depends on the integration of diverse datasets and ground-truth verification. Beyond methodological advances, the thesis argues that EO technologies are strategic enablers for resilience governance, bridging short-term response and long-term development planning. The findings reveal how open-access satellite data can democratize disaster monitoring, empower local institutions, and support risk-informed reconstruction policies. Ultimately, this work proposes a paradigm shift from reactive crisis management toward proactive, geospatially informed recovery systems, offering a scalable and inclusive framework to operationalize resilience in the face of escalating climate-related hazards
The Lax–Wendroff theorem for Patankar-type methods applied to hyperbolic conservation laws
No full textFor hyperbolic conservation laws, the famous Lax–Wendroff theorem delivers sufficient conditions for the limit of a convergent numerical method to be a weak (entropy) solution. This theorem is a fundamental result, and many investigations have been done to verify its validity for finite difference, finite volume, and finite element schemes, using either explicit or implicit linear time-integration methods. Recently, the use of modified Patankar (MP) schemes as time-integration methods for the discretization of hyperbolic conservation laws has gained increasing interest. These schemes are unconditionally conservative and positivity-preserving and only require the solution of a linear system. However, MP schemes are by construction nonlinear, which is why the theoretical investigation of these schemes is more involved. We prove an extension of the Lax–Wendroff theorem for the class of MP methods. This is the first extension of the Lax–Wendroff theorem to nonlinear time integration methods with just an additional hypothesis on the total time variation boundedness of the numerical solutions. We provide some numerical simulations that validate the theoretical observations