Archivio istituzionale della ricerca - Alma Mater Studiorum Università di Bologna
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Navigating fear: how the pandemic moral regulation affected social control with adverse impacts on Italian society
No full textThis chapter will present the management of the SarsCov-2 pandemic emergency in Italy in the first phase of the phenomenon and how the moral panic generated led to the rise of substantial moral regulation in the population. The question is thus posed: how does moral regulation in response to an epoch-making event, albeit the consequence of a “good” moral panic, impact society and what perverse effects can it lead to? In order to try to give a partial answer to the question, an attempt was made to interpret the substantial moral regulation resulting from the “good panic” – that it to say the governmental protective response and its impact on the population in light of the extraordinary event of the pandemic – by exploring some of the negative effects it brings with it, which will be exposed, including a tightening of police surveillance and consequences on domestic violence against women during the lockdown period
A Human-Centric AutomationML Framework for Adaptive UX-Driven Automation
No full textThe transition to Industry 5.0 emphasizes human-centric automation, prioritizing ergonomics, cognitive adaptability, and real-time collaboration between humans and machines. Traditional automation strategies have focused primarily on efficiency and standardization, often overlooking human operators’ cognitive and physiological workload. This paper presents an AutomationML-based (AML) digital framework that integrates user experience (UX) approaches and human-in-the-loop methodologies to optimize human task design by harmonizing human cognitive states, physiological data, and real-time behavioral insights from industrial digital assets and the physical factory. The presented approach extends the recently defined AML standard by introducing a structured human taxonomy, a UX database architecture, and an enhanced task modeling and adaptation strategy based on the operators’ feedback. An industrial use case about quality inspection is presented to validate the proposed framework, where an assisted inspection system integrates augmented reality visualization with human physiological monitoring using a sensorized wristband. This framework enables real-time task adaptation based on the estimate of the operator’s workload, reducing cognitive overload and optimizing task allocation between humans and machines. Results on the use case suggest how UX-driven automation improves both process performance and workers’ well-being, as well as the overall system flexibility. This research contributes to the development of ergonomic and cognitive-aware automation solutions that enhance collaboration between humans and machines
Bayesian network model for assessing hydrogen ignition probability
No full textThe global energy transition is accelerating the adoption of hydrogen as a clean, versatile fuel. Hydrogen offers environmental benefits but introduces safety challenges due to its high flammability. Accurate estimation of hydrogen ignition probability is crucial for effective safety management, especially in environments where ignition sources cannot be fully controlled. Existing approaches often rely on surrogate models, such as methane-based models, which may not adequately capture hydrogen behavior. Computational fluid dynamics simulations can provide detailed ignition assessments. They are, however, computationally expensive and impractical for multi-scenario analyses. This paper presents a novel quantitative Bayesian network-based ignition probability model aimed at delivering hydrogen-specific ignition probability estimates with improved accuracy and efficiency. Case studies involving hydrogen electrolyzers demonstrate the model’s practicality and effectiveness for rapid, scenario-based risk assessments. For a 1 MW PEM electrolyzer operating at 30 bar, the probability of immediate ignition was 0.068 for a leak (1 % of pipe cross-section) and 0.091 for a rupture (100 % of pipe cross-section). The probability of delayed ignition was 0.115 for a leak and 0.167 for a rupture. This model provides a valuable tool to enhance hydrogen safety evaluations and supports the safer deployment of hydrogen technologies
The Dual Role of Subaerial Biofilms Through the Lens of AI: The Case for Causal Networks and Targeted Learning
No full textSubaerial biofilms (SABs) are microbial communities that form on surfaces exposed to both air and periodic moisture and that can adapt to harsh environmental conditions like UV radiation, and fluctuating temperatures. On the one hand they can protect built surfaces by forming a barrier against environmental stressors, on the other they can also cause deterioration through biological weathering. The balance is complex and depend on a large number of factors. Unfortunately, only a small part of the complex multiscale network of physical, chemical and biological processes is captured by existing mechanistic model; this prompts for the involvement of phenomenological models. In this work we point at the modeling advantages offered by Bayesian Networks (BNs), Causal Networks and Targeted Learning (TL) in the study of the dual role of SABs
La valorizzazione delle sepolture ed altro: archeologia funeraria, museologia ed etica (alcune proposte mai realizzate?). Una riflessione.
No full textLa questione etica del percorso di valorizzazione delle sepolture di epoche che vanno dall'età del Bronzo al Rinascimento, in percorsi museali diversificati anche cronologicamente e in relazione alle società che hanno diversamente interpretato la morte e la sopravvivenza al di là di questa, costituisce un tema che si è rivelato molto sensibile. Attraverso l'analisi di sistemi espositivi ottocenteschi, fino a comprendere le sistemazioni dei Musei all'aperto o la valorizzazione in area urbana di luoghi deputati alle sepolture ma attualmente non più visibili, vengono presentate proposte e progetti fattibili, in connessione con le realtà già consolidate
Swarm intelligence-driven performance optimization of multi-shaft stirrer reactors: leader shaft control strategy
No full textThe growing gap between production demand and capacity has placed increasing pressure on the efficiency and automation of chemical production processes. However, multi-shaft stirred reactors, inspired by the swarm intelligence of geese, have emerged as a promising solution. This work first addresses the critical issue of the “leader shaft” and determines its optimal position. Using high-precision simulations of the flow field at multiple scales, revealing that improving mixing performance depends on understanding the variation of flow dynamics and energy demands. Additionally, the torque attractor fractal dimension is identified as a key metric linking operational conditions to energy demands. Building on this, a multi-agent intelligent control system, focused on the leader shaft, is developed and validated through Belousov-Zhabotinsky reaction experiment. Results demonstrate a 46.7% increase in reaction rate compared to conventional optimal operating conditions. This control strategy significantly enhances reactor automation and has the potential to substantially improve industrial production capacity
Dynamic characteristics of multilayer graphene considering nonlinear higher-order strain gradient
No full textThis study adopts a higher-order simulation framework to investigate wave propagation in
two-dimensionaldefect-freemultilayergraphene, incorporatinggeometricnonlinearitythrough
second strain gradient elasticity. To accomplish this, the strong and weak forms governing
π-bonds associated with van der Waals interactions and σ-bonds are derived using continuum
beammodels. Thedynamicpropertiesofmultilayergraphene, includingbandstructures, slow-
ness surfaces, and energy flow, are analyzed using the theory of periodic structures. Numerical
results reveal that accounting for nonlinearity predicts higher frequency values, indicating a
stiffness hardening effect in graphene. At high frequencies, energy is predominantly confined
to a single direction, and the nonlinear model demonstrates a strong wave-controlling capa-
bility compared to the linear model. This innovative study advances our understanding of
graphene’s dynamic behavior and offers significant insights for engineering applications in-
volving graphene-based nanocomposites
Logistics facilities location choice modeling: Effects of environmental constraints
No full textThe selection of logistics facility locations is a critical decision that influences supply chain efficiency, cost structures and operational resilience. While previous studies have extensively examined the role of transport accessibility in location choices, the interplay between socio-demographic, transport-related and environmental constraints remain partially underexplored. This study addresses this gap by developing a conditional logit model to assess the impact of these factors on logistics facility location decisions, using the Emilia-Romagna region (Italy) as a case study. The model incorporates key determinants of location choice, including proximity to transport infrastructure (highways, freight terminals, rail stations), population density, environmental risks (flooding and seismic hazards) and land-use restrictions (protected natural areas). Results confirm that transport accessibility is the primary driver of logistics location choices and that socio-demographic factors, particularly
population, also influence location preferences. Conversely, environmental constraints exert a negative effect on site selection, reducing the likelihood of a location being chosen. These findings bring significant policy implications.
Investments in logistics-oriented transport infrastructure – such as enhanced highway connectivity, intermodal terminals and advanced congestion management systems – remains essential for strengthening regional logistics competitiveness. Moreover, implementing risk mitigation measures in location choice process analysis, including flood-resilient warehousing and seismic-resistant facilities, can enable firms to operate in moderate-risk areas without undermining operational resilience. Finally, integrated transport and land-use
planning that harmonizes industrial expansion with environmental sustainability, through initiatives like ecoindustria parks, can support the development of resilient and efficient logistics systems
Realism
No full textThe sciences develop theories that rely on both observable and unobservable entities—i.e., entities accessible only through instruments—to describe and explain the world. Furthermore, unobservables have been changing over time, with new theoretical entities entering scientific discourse in various fields, and others disappearing. What are scientific theories ultimately aimed at: truth, empirical adequacy, predictive success, ...? Can our epistemic justification for observable and unobservable entities be the same? Do theoretical entities genuinely refer, or are they merely formal devices? And how can the scientific success achieved through unobservables be reconciled with theoretical change? These are the central issues addressed in the scientific realism/antirealism debate. While tackling the relationship between pure and instrumentally mediated observation and theory, the debate also affects our broader conception of science, its focus and goals. In what follows, we consider some core arguments in this philosophical discussion and their relevance for psychology
ARMS in ports: monitoring non-indigenous species through Autonomous Reef Monitoring Structures
No full textHarbors and marinas are considered Non-Indigenous Species (NIS) hotspots, being departure and arrival points for numerous vessels and providing environments with less complex artificial substrates that promote NIS colonization. Monitoring changes in the structure of benthic communities allows to early detect the arrival of new NIS. In this study, we used Autonomous Reef Monitoring Structures, ARMS, 3D standardized passive collectors of benthic organisms, to monitor NIS presence and abundance in ports with different uses, a commercial harbor, and a touristic marina, in the northern Adriatic Sea, over one year. The sessile organisms growing on each ARMS plate were identify by photo analysis while the motile ones were morphologically recognized and counted using stereomicroscope. Benthic communities grown on ARMS were characterized by many taxa typical of coastal urbanized areas and showed high seasonal variability, being richer in spring and summer than in winter. Distinct benthic and NIS communities were found in the harbor and marina, with the marina hosting
higher numbers of both native and NIS. This is likely due to the different environmental conditions, port structural complexity, and performed economic activities. Of the 86 macrofaunal taxa detected, nearly 19 % were NIS, mostly belonging to crustaceans, polychaetes, bivalves, and ascidians. Our results indicate that ARMS represent an efficient tool for monitoring NIS and suggest that they should be deployed in the spring season and in environments with different levels of urbanization to capture higher NIS diversity and enable their early detection