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Predicting Information Diffusion on Social Media Using an Epidemiological Approach
No full textRecent decades have been characterized by deep changes in our way of communicating thanks to powerful new tools e.g., social networks, that allow a fast spread of information with very limited costs and control. In this paper, we will show the importance of analyzing information diffusion on social media in the first phases of the news spread, using a mathematical epidemiological approach. We will highlight the importance of predicting the evolution of the news trend over time before a loss of interest from social media users is observed. For this reason, firstly, we will analyze the characteristics of several kinds of mathematical models from literature to choose the most appropriate for our purposes, showing that a possible choice consists of a model of Ignorant - Spreader - Exposed - Skeptic (IESZ) type. Then, we will describe a possible strategy to compute optimized parameters for the chosen model starting from a dataset of real data. Finally, by exploiting several case studies regarding both true and fake news shared on X (Twitter) in the last years, we will show that the proposed strategy is truly applicable to reality
Prosocial Activities as a Tool for Organizational Well-Being
No full textThis chapter analyzes prosociality as a strategic lever for organizational well-being and as an evolutionary principle of sustainability in contemporary organizations. Drawing on contributions from social psychology, Organizational Citizenship Behavior, and Positive Organizational Scholarship, the text interprets prosocial activities not as simple individual altruistic behaviors, but as systemic dynamics capable of generating relational capital, trust, and collective resilience. Prosociality is examined in relation to psychological well-being, intrinsic motivation, stress regulation, and the construction of organizational identity, highlighting its role as a key resource in complex and highly uncertain contexts. The chapter also explores the cultural and leadership dimensions of prosociality, linking it to ethical, transformational, and servant leadership models, as well as to the ethics of care and theories of complexity. In conclusion, prosociality is proposed as a cultural and design paradigm capable of integrating performance and ethics, efficiency and humanity, contributing to the construction of sustainable, resilient organizations oriented toward shared well-being
Integrating Visual and Audio Cues for Emotion and Gender Recognition: a Multi modal and Multi task approach
No full textMultivariate anomaly detection and root cause analysis of energy issues in microservice-based systems
No full textContext: Microservice-based systems have become the architecture style of choice for modern applications, offering scalability, flexibility, and resilience. However, their distributed nature leads to increased resource consumption and energy inefficiencies, posing challenges for maintaining sustainable operations. Accurate anomaly detection (AD) and root cause analysis (RCA) tools are critical for diagnosing energy consumption issues in these systems, yet existing solutions often lack focus on energy metrics. Goal: This study aims to evaluate the effectiveness of AD and RCA algorithms in identifying and diagnosing performance-related energy consumption anomalies in microservice-based systems. Method: Two representative systems, Sock Shop and Train Ticket, are deployed under controlled environments. Then, anomalies are deliberately introduced by stressing at the same time CPU, memory, and disk resources. The data collection is conducted using Prometheus for performance metrics and Scaphandre for energy metrics. Once normal and anomalous datasets are constructed for each system, the study evaluates five AD algorithms (Birch, iForest, KNN, LOF, and SVM) and four RCA algorithms (MicroRCA, CausalRCA, CIRCA, and RCD) based on their precision, recall, and scalability across varied scenarios and workloads. Results: The experiment reveals that overall, iForest is the most effective AD algorithms in detecting energy anomalies (0.59 F-Score in Sock Shop and 0.634 F-Score in Train Ticket). In particular, iForest performs better in precision when the user load is high (1000 concurrent users). For RCA, CIRCA performs well in identifying root causes in smaller systems, while RCD is more scalable for larger and more complex systems. Conclusions: The findings of this study provide insights for both researchers and practitioners. In the context of our experiment, AD algorithms tend to perform relatively well, whereas RCA algorithms tend to be imprecise in localizing energy issues
AI-integrated didactic systems: positioning dynamics and identity transformations in mathematics education
No full textThis chapter examines how Generative AI integration fundamentally reshapes mathematical identities by introducing a fourth actor into the traditional didactic triangle of teacher-student-knowledge. Drawing on positioning theory and empirical studies involving 50 undergraduate topology students and 30 prospective mathematics teachers in Italy, we analyse how AI participation reconfigures positioning dynamics at both learning and teaching levels. At the learning level, students engaged in structured three-phase activities where AI intervened as a "peer participant" after autonomous problem-solving, triggering an alternating discussion dynamic that fostered metacognitive awareness and critical evaluation competencies. Interview data reveals students repositioning themselves from passive knowledge recipients to critical evaluators who view AI neither as authority nor threat but as a "provocative companion of thought" requiring constant epistemic vigilance. At the teaching level, covariational instructions structured through Taxicab geometry exploration activated three distinct AI participation modes within the Mathematical Working Space framework: Social (AI as collaborative problem-solver), Weak Instrumental (AI as critical friend), and Instrumental (AI as design partner). Prospective teachers developed professional identities balancing pedagogical authority with strategic AI collaboration. These identity transformations occur across cognitive, metacognitive, and affective dimensions, fundamentally altering how actors position themselves within mathematical discourse communities and demanding theoretical reconceptualization of the didactic system itself
Reverse Mortgages: Exploring the Impact of Risk Factors by Source
No full textIn recent years, reverse mortgages have gained attention as suitable financial instruments for individuals of retirement age, particularly those classified as “house-rich but cash-poor.” Despite growing interest in countries such as the US, the UK, and Australia, the Italian market remains underdeveloped in this area. From a lender’s perspective, these contracts are perceived as complex, mainly due to the management of various risk components: longevity risk, financial risk, and house price risk. Our goal is to provide lenders with insights into the impact of each risk factor through a time-dependent profit/loss function. This approach aids in identifying the most critical sources of risk, enabling lenders to take appropriate measures to mitigate potential financial threats. We conduct Monte Carlo simulations of the chosen stochastic risk models and apply a single-component VaR assessment procedure. Our findings indicate that house price risk is the most significant risk factor of a Reverse Mortgage portfolio. Moreover, the lender can control the financial risk through the analysis of the risk premium values. The results also highlight that, beyond a certain time horizon, the lender’s exposure stabilizes, with profitability emerging in the long run
Topology-enhanced superconducting qubit networks for in-sensor quantum information processing
No full textWe investigate the influence of topology on the magnetic response of inductively coupled superconducting flux-qubit networks. Using exact diagonalization methods and linear response theory, we compare the magnetic response of linear and cross-shaped array geometries, used as paradigmatic examples. We find that the peculiar coupling matrix in cross-shaped arrays yields a significant enhancement of the magnetic flux response compared to linear arrays, this network-topology effect arising from cooperative coupling among the central and the peripheral qubits. These results establish quantitative design criteria for function-oriented superconducting quantum circuits, with direct implications for advancing performance in both quantum sensing and quantum information processing applications. Concerning the latter, by exploiting the non-linear and high-dimensional dynamics of such arrays, we demonstrate their suitability for quantum reservoir computing technology. This dual functionality suggests a novel platform in which the same device serves both as a quantum-limited electromagnetic sensor and as a reservoir capable of signal processing, enabling integrated quantum sensing and processing architectures
Emerging Therapeutic Approaches for Modulating the Intestinal Microbiota
No full textBackground/Objectives: The gut microbiota is increasingly recognized as a key determinant of human health, playing a vital role in metabolism, immunity, and disease susceptibility. Dysbiosis, or microbial imbalance, is associated with gastrointestinal disorders such as irritable bowel syndrome (IBS), inflammatory bowel disease (IBD), and Clostridioides difficile infection (CDI), as well as extraintestinal conditions, including obesity, cardiovascular disease, and neuropsychiatric disorders. This review aims to provide an updated overview of emerging therapeutic strategies to modulate the gut microbiota to restore eubiosis and improve health outcomes. Methods: A narrative review of recent literature was conducted, focusing on preclinical and clinical studies investigating microbiota-targeted therapies. The review primarily covers innovative interventional approaches, including fecal microbiota transplantation (FMT), bacterial consortium transplantation (BCT), bacteriophage therapy and outer membrane vesicles (OMVs). Results: Evidence supports the role of probiotics, prebiotics, and synbiotics in remodeling microbial communities and improving host health, although their effects may be strain- and context-dependent. FMT has demonstrated high efficacy in the treatment of recurrent Clostridium difficile infections and is being studied for IBD, IBS and extraintestinal diseases, following the recent Food and Drug Administration approval of the first commercial FMT products. BCT offers a standardized alternative to donor-derived material, with early clinical successes such as FDA-approved SER-109. Phage therapy and OMVs represent promising frontiers, offering targeted microbial modulation and interactions with the immune system, although clinical data remain limited. Conclusions: Emerging gut microbiota modulation strategies offer new perspectives for precision medicine and could transform the prevention and treatment of many diseases, but further studies are needed to ensure their safety, standardization, and clinical application
Surface-localized magnetic order in RuO2 thin films revealed by low-energy muon probes
No full textRuthenium dioxide (RuO2) has recently emerged as an altermagnetic candidate, but its intrinsic magnetic ground state in thin films remains widely debated. This study aims to clarify the nature and spatial extent of the magnetic order in RuO(2 )thin films grown under different conditions. Thin films of RuO2 with thicknesses of 30 and 33 nm are deposited by pulsed laser deposition and sputtering onto TiO2(110) and Al2O3( 1102) substrates, respectively. Low-energy muon spin rotation/relaxation (LE- mu SR) with depth-resolved sensitivity measurements is performed in transverse magnetic fields (TF) from 4 K to 290 K. The mu SR data collected with a muon implantation energy of 1 keV reveal that magnetic signals originate from the near-surface region of the film ( less than or similar to 10 nm), and the affected volume fraction is approximately 8.5%. The localized magnetic response is consistent across different substrates, growth techniques, and parameter sets, suggesting a common origin related to surface defects and dimensionality effects. The combined use of TF- mu SR and the study of depth-dependent implantation with low-energy muons provides direct evidence for surface-confined, inhomogeneous static magnetic order in RuO2 thin films, helping reconcile discrepancies. These findings underscore the importance of considering reduced-dimensional contributions and motivate further investigation into the role of defects, strain, and stoichiometry on the magnetic properties of RuO2, especially at the surface
The ecosystemic governance for impact (EGI) framework: coordinating innovation across actors, tools and value trajectories
No full textPurpose
This paper aims to propose the ecosystemic governance for impact (EGI) framework to help innovation ecosystems generate lasting, stakeholder-aligned impact. By combining service-dominant logic (S-D logic), digitalization and Industry 4.0 (D&I4), project management (PM) and benefit realization management (BRM), the framework balances rigor with flexibility to coordinate actors, tools and value co-creation processes.
Design/methodology/approach
The study employs an abductive, qualitative case study design drawing on a national R&D project (Ditron-C). The analysis integrates data from interviews, project documents, field observations and co-design artifacts, interpreted through four innovation management approaches.
Findings
The EGI framework structures innovation governance around four phases: co-visioning, co-design, co-realization and co-evolution. Each phase supports structured planning and adaptive coordination among actors, helping translate project outputs into sustained impact.
Research limitations/implications
Findings are based on a retail innovation project and validated through a cross-sector application. While these cases support the transferability of the framework, further research could examine the applicability of the framework across different ecosystems and in conditions of extreme power asymmetries.
Practical implications
In practice, EGI helps managers move beyond checklists and dashboards, providing a scaffold that keeps negotiations open and makes impact visible over time.
Social implications
The framework promotes inclusive governance and participatory alignment among ecosystem actors, enabling innovation processes to support lasting and mutually negotiated impact.
Originality/value
This paper proposes a mid-range theoretical framework that reframes innovation governance as a reflexive and ecosystemic process