Archivio istituzionale della ricerca - Alma Mater Studiorum Università di Bologna
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The role of thermo-poro-elastic effects in the interpretation of gravity data
No full textThe study of gravity changes induced by magma chambers in volcanic environments has long been used to
monitor unrest phases and to estimate the volumes and masses of magma intrusions. However, magma is not the
sole driver of the observed deformation and gravity changes. Hydrothermal systems within the volcanic structure
can also play a significant role. Recent advances in Thermo-Poro-Elastic (TPE) inclusion models have made it
possible to efficiently and accurately simulate the mechanical effects caused by an increase of temperature and
pore-pressure of fluids in a reservoir. In this work, we calculate the gravity variations induced by a disk-shaped
inclusion. We model gravity variations induced by increments of pore-pressure and temperature within different
fluid phases. We also consider the superposition of the effects of a TPE inclusion with a deeper magma chamber.
The comparison with the data measured at the Campi Flegrei caldera (Italy) allows us to draw some suggestions
on the use and interpretation of these results. Our findings demonstrate that these effects are significant and
cannot be overlooked when interpreting gravimetric data during unrest phases and to assess geohazard levels
Towards IT/OT integration in industry digitalization: A comprehensive survey
Full text linkAccording to both academic and industry perspectives, the Fourth Industrial Revolution has brought about a paradigm shift in the manufacturing sector enabling companies to enhance their competitiveness in the global market. To achieve this goal, manufacturing companies will need to undertake a deep digital transformation, primarily by introducing advanced Information Technology into traditionally less digitalized departments, such as shop floors, where Operational Technology currently dominate. For the full achievement of Industry 4.0 revolution objectives, practitioners believe in the strong requirement of a progressive and tight integration between IT and OT departments.
In the depicted scenario, communication technologies are expected to play a pivotal role in facilitating the integration process, but other more recent and advanced IT have also proven helpful.
In particular, the topic of IT/OT integration has attracted significant attention from various research communities that have sought to identify both the opportunities and challenges associated with its implementation. Although some good surveys of those works have appeared in the literature, to the best of our knowledge, no comprehensive review has yet been conducted that is fully dedicated to the topic of IT/OT convergence. In this paper, we propose a holistic approach to examine the various dimensions of IT/OT integration, which we classify into five interconnected realms, Communication, IT-Driven Support to OT, Human Centricity, Advanced Industrial Control Systems, and cybersecurity. Furthermore, we develop a realm-oriented taxonomy to organize the surveyed works in a structured manner, offering readers a clear overview of the current state of the literature, along with insights into unexplored opportunities and future directions for IT/OT integration
Taxon-specific responses to temperature, landscape, and local management challenge common strategies for pest control in vineyards
No full textGrape is among the most pesticide treated crops in Europe. To reduce pesticide use, it is increasingly important to enhance pest control by natural enemies. However, the provision of biological control in vineyards is highly
context- and taxa-dependent. Here, we selected 60 vineyards across Italy in order to explicitly explore the effect of vineyard management, temperature and landscape composition on arthropod predators, grapevine pests, dummy caterpillar predation, and seed predation. We found that plant cover in the inter-row was lower in dry-warm climates, and it positively affected only the abundance of hoverflies, while the abundance of carabids, ladybugs, harvest spiders and spiders was affected by temperature and the surrounding landscape. Organic management did not affect predators but supported more abundant populations of the pest Erasmoneura vulnerata. Overall, most leafhopper pests showed species specific responses to local management, temperature and the landscape. The abundance of two leafhopper species decreased with increasing semi-natural areas. By contrast, pest control rate and grape damage did not respond to any of the selected drivers. In conclusion, our findings suggest that local vineyard management significantly influences biocontrol and pests, but the effects are taxon specific and shaped by the surrounding landscape and by the temperature, challenging universal strategies
Federated Data Modelling for Heritage Building Performance Management
No full textThe fragmentation of knowledge across multiple sources and players, coupled with limited access to information, is one of the main challenges for the performance-based management of heritage buildings. Despite recent research efforts in the field of Heritage Building Information Modelling (HBIM), this technology alone is insufficient for managing the variety of data related to building performance and is challenging for stakeholders without digital expertise to adopt. These limitations, along with advancements in knowledge technologies, have led to the emergence of federated data modelling approaches as a core strategy for managing the complexity of buildings’ operational information. To address data fragmentation, this research proposes a methodology for linking heterogeneous data on historic building performance. The approach structures heterogeneous data, gathered from multiple sources—HBIM models, sensors, and energy bills—into knowledge graphs that enable semantic integration, cross-domain queries and support interactive visualisation. As part of the BeTwin research project, the methodology is validated through its application to a case study in the Appia Antica Archaeological Park (Rome, Italy)
Targeting ferroptosis in Pyricularia Oryzae to suppress rice blast (INFIRE)
No full textRice blast fungus (Pyricularia oryzae) destroys enough rice annually to feed 60 million people, representing a critical threat to global food security as 551 million tons of milled rice will be needed by 2030. The pathogen undergoes iron-dependent cell death (ferroptosis) during infection, which paradoxically enhances its virulence, making this process a novel and unexplored therapeutic target.
INFIRE aims to develop new antifungal compounds that disrupt ferroptosis through three complementary approaches: suppressing lipid peroxidation using natural and synthetic antioxidants, modulating iron availability with chelators, and inhibiting iron-dependent NOX enzymes involved in the ferroptosis pathway. The project will initially screen natural compounds, then synthesize optimized analogs and design hybrid molecules that combine multiple mechanisms of action.
The expected outcome is identification of new chemical classes for rice blast management, advancing both fundamental understanding of fungal ferroptosis and practical agrochemical applications. This represents a paradigm shift from traditional fungicides toward targeting the pathogen's own regulated cell death mechanisms, offering potential for more effective and sustainable disease control strategies
Systems The special issue of Systems (ISSN 2079-8954): Circular Economy for Food Systemic Design.
No full textSystems is an international, peer-reviewed, open access journal on systems theory in practice, including fields such as systems engineering management, systems based project planning in urban settings, health systems, environmental management and complex social systems, published monthly online by MDPI. The International Society for the Systems Sciences (ISSS) is affiliated with Systems and its members receive a discount on the article processing charges
Temperature-dependent toughening of carbon/epoxy composites using rubbery NBR/PCL nanofibers: Mode I fracture and damage mechanisms
No full textThis study evaluates the temperature-dependent toughening effect of rubbery NBR/PCL nanofibers in carbon/epoxy composites under mode I loading. Double Cantilever Beam (DCB) tests at six temperatures (−30 °C to 120 °C) measured interlaminar fracture toughness in non-modified and nano-modified laminates. At 30 °C, modified specimens achieved 164 % higher initiation toughness and 394 % higher propagation toughness than non-modified ones, driven by nano-modified interactions that enhanced energy dissipation through plastic deformation and fiber bridging. However, at elevated temperatures (90 °C and 120 °C), toughness declined sharply due to modified matrix softening above the rubber’s glass transition temperature (Tg) and PCL melting point, impairing crack-bridging efficacy. Fractographic analysis revealed contrasting failure modes: non-modified specimens exhibited matrix cracking (cusps) and fiber–matrix debonding, with cusp height reduction at higher temperatures. Nano-modified specimens showed hole-rich fracture surfaces and robust fiber–matrix adhesion at lower temperatures, confirming nanofiber-mediated toughening. This effect diminished at higher temperatures as nanofibers softened, reducing energy absorption. The results underscore the temperature sensitivity of NBR/PCL nanofibers in enhancing fracture resistance, with peak performance at lower temperatures. These findings provide critical insights for optimizing composite designs for applications exposed to varying thermal conditions, balancing toughening benefits against temperature-induced limitations
Predicting Multidimensional Cubes Through Intentional Analytics
No full textIn an attempt to streamline exploratory data analysis of multidimensional cubes, the Intentional Analytics Model has been proposed as a way to unite OLAP and analytics by allowing users to indicate their analysis intentions and returning cubes enhanced with models. Five intention operators were envisioned to this end; in this work we focus on the predict operator, whose goal is to estimate the missing values of a cube measure starting from known values of the same measure or other measures using different regression models. Although prediction tasks such as forecasting and imputation are routinary for analysts, the added value of our approach is (i) to encapsulate them in a declarative, concise, natural language-like syntax; (ii) to automate the selection of the best measures to be used and the computation of the models, and (iii) to automate the evaluation of the interest of the models computed. First we propose a syntax and a semantics for predict and discuss how enhanced cubes are built by (i) predicting the missing values for a measure based on the available information via one or more models and (ii) highlighting the most interesting prediction. Then we test the operator implementation, proving that its performance is in line with the interactivity requirement of OLAP session and that accurate predictions can be returned