Archivio Istituzionale della Ricerca - Università degli Studi di Pavia
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Seed priming con biostimolanti per migliorare la crescita delle colture foraggere e la tolleranza alla siccità
No full textIl cambiamento climatico esercita una profonda pressione sui sistemi agricoli, spingendo verso la necessità di strategie innovative e sostenibili per garantire la produttività delle colture e la sicurezza alimentare in condizioni ambientali sempre più variabili. La siccità e altri stress abiotici rappresentano gravi minacce per la germinazione dei semi, la crescita delle piante e la resa, mentre l’uso eccessivo di fertilizzanti chimici e regolatori della crescita ha intensificato le preoccupazioni di natura ecologica ed economica. In questo contesto, l’esplorazione di soluzioni naturali basate sulla bioeconomia circolare è diventata un obiettivo centrale della ricerca agronomica moderna. Tra queste, i biostimolanti di origine vegetale (PBs), derivati da scarti agroalimentari, rappresentano un approccio ambientalmente sostenibile in grado di migliorare il vigore delle piante, mitigare lo stress ossidativo e ridurre la dipendenza da input sintetici. Complementarmente, il seed priming, una tecnica di pretrattamento dei semi prima della semina che migliora la germinazione e la tolleranza agli stress, offre una via pratica per tradurre questi principi in un’agricoltura resiliente ai cambiamenti climatici. Comprendere la diversità chimica e metabolica del germoplasma vegetale, inclusi i composti organici volatili (VOC), può rivelare tratti adattativi naturali e guidare l’identificazione di varietà resilienti adatte a sistemi colturali sostenibili.
Questo lavoro ha combinato analisi fisiologiche, biochimiche e molecolari per indagare come i biostimolanti di origine vegetale e la diversità genetica intrinseca contribuiscano alle prestazioni dei semi e all’adattamento agli stress in colture leguminose e cerealicole. Utilizzando soia e mais come specie agronomiche di grande rilevanza, estratti vegetali ottenuti da scarti di radicchio rosso, colza e cavolfiore sono stati applicati come agenti di seed priming biostimolante per valutare i loro effetti sulla dinamica di germinazione, le risposte agli stress e il metabolismo ossidativo. Il lavoro svolto si è basato sull’integrazione di valutazioni quantitative dell’efficienza di germinazione e della regolazione delle specie reattive dell’ossigeno (ROS) con analisi molecolari di geni chiave associati alla segnalazione e all’omeostasi dello stress. L’analisi avanzata del profilo volatilomico di genotipi italiani di mais, condotta mediante nuove tecniche basate sulla spettrometria di massa a reazione di trasferimento di protoni, ha permesso di mettere in luce la diversità chimica e i potenziali marcatori legati alla qualità del seme.
Complessivamente, i risultati ottenuti hanno permesso di: (1) dimostrare che il seed priming con biostimolanti di origine vegetale consente di mitigare la risposta allo stress in modo dipendente dal genotipo e dal trattamento; (2) caratterizzare il profilo volatilomico in vista dell’identificazione dei determinanti della qualità del seme. Nel loro insieme, questi risultati forniscono nuove prospettive sulle diverse sfaccettature dell’adattamento metabolico e aprono la strada verso approcci agricoli più sostenibili e resilienti, in linea con gli obiettivi di una bioeconomia circolare.Climate change is exerting profound pressure on agricultural systems, driving the need for innovative and sustainable strategies to ensure crop productivity and food security under increasingly variable environmental conditions. Drought and other abiotic stresses represent major threats to seed germination, plant growth, and yield, while excessive use of chemical fertilizers and growth regulators has intensified ecological and economic concerns. In this context, the exploration of natural, circular bioeconomy-based solutions has become a central goal in modern agronomic research. Among these, plant-based biostimulants (PBs) derived from agri-food waste represent an environmentally sustainable approach capable of enhancing plant vigor, mitigating oxidative stress, and reducing reliance on synthetic inputs. Complementarily, seed priming, a pre-sowing technique that improves germination performance and stress tolerance, provides a practical avenue to translate these principles into climate-resilient agriculture. Understanding the chemical and metabolic diversity of plant germplasm, including volatile organic compounds (VOCs), can reveal natural adaptive traits and guide the identification of resilient varieties suitable for sustainable cropping systems.
This work combined physiological, biochemical, and molecular analyses to investigate how plant-based biostimulants and intrinsic genetic diversity contribute to seed performance and stress adaptation in legume and cereal crops. Using soybean and maize as highly relevant agronomic species, plant waste extracts from red chicory, canola, and cauliflower were applied as biostimulant seed priming agents to evaluate their effects on germination dynamics, stress responses, and oxidative metabolism. The work performed was based on integrating quantitative assessments of germination efficiency and reactive oxygen species (ROS) regulation with molecular analyses of key genes associated with stress signalling and homeostasis. Advanced volatilome profiling of Italian maize genotypes, using novel approaches based on proton-transfer-reaction mass spectrometry, allowed to uncover the chemical diversity and potential markers linked to seed quality.
Overall, the obtained results allowed to: (1) demonstrate that seed priming with plant-based biostimulants enabled the mitigation of stress response in a genotype and treatments dependent manner; (2) and characterize the volatilome profiling in view of identifying determinants of seed quality. Taken together, this work provide novel into the different facets of metabolic adaptation and paves the way toward more sustainable and resilient agricultural approaches, consistent with the goals of a circular bioeconomy
Dynamic field testing of a 15-year-old friction pendulum base-isolated residential building
No full textThis paper presents a landmark full-scale experimental program aimed at advancing the understanding of long-term performance of seismic base isolation for buildings in real service conditions. A three-story residential structure in Arischia (L'Aquila, Italy), base-isolated with Friction Pendulum (FP) bearings in service for over 15 years, was subjected to in-situ dynamic testing. Using custom-designed self-reacting frames and the EUCENTRE's mobile laboratory, displacement-controlled sinusoidal loading histories were applied, covering a range of amplitudes and peak velocities. This paper details the test specimen, experimental setup, loading protocols, and instrumentation. It presents preliminary findings on key isolation system properties, including post-elastic stiffness, static and dynamic friction coefficients, and equivalent damping ratio. These results provide rare field-based insight into the effects of aging on FP isolators and offer critical validation data for models used in performance-based assessment of base-isolated structures. In addition, the study demonstrates the feasibility and value of in-situ testing, which can serve as a model for future full-scale investigations of base-isolated buildings
Subjective Cognitive Decline in Brazilian Adults: Prevalence and Associated Social, Lifestyle, and Health-Related Factors: A Nationally Representative Cross-Sectional Analysis from the ELSI-Brazil Cohort
No full textPathology of the self: a network analysis of personality functioning, narcissistic vulnerability, mentalizing, and epistemic trust across trauma profiles
No full textModeling and Control of Macroscopic Freeway Traffic Systems with Integrated Service Stations
No full textMacroscopic traffic modeling and control are fundamental to the effective operation of modern freeway networks, with direct implications for congestion mitigation, travel time reliability, and energy efficiency. Traditionally, Service Stations (STs) have been treated as passive roadside elements. However, their increasingly dynamic interaction with traffic, due to changing driver behavior and growing network complexity, demands a shift in perspective. This thesis proposes a comprehensive, infrastructure-aware modeling and control framework that explicitly incorporates the dynamics of STs into freeway traffic management.
Chapter 2 introduces METANET with service station (METANET-s), a novel second-order macroscopic traffic model that extends the classical METANET model to account for ST dynamics via a dedicated Service Area Facility modeled by a Store-and-forward (saf) link. The model enforces physical capacity constraints at STs and simulates critical behaviors such as queue
formation, dwell times, and re-entry effects.
Chapter 3 presents the Infrastructure-Dependent ramp-metering Control (IDC) strategy designed for METANET-s. This two-tier control scheme combines ALINEA ramp-metering at the ST exit with route guidance mechanisms that manage vehicle entry into the ST during peak congestion. The IDC scheme enables the active use of STs as traffic regulators, improving flow distribution and reducing congestion-induced delays along freeway segments.
Building on this foundation, Chapter 4 introduces the Service Station-Enhanced Mainstream Traffic Flow Control (ST-MTFC) architecture, which integrates Variable Speed Limit (VSL) and IDC scheme including ramp-metering, and route guidance within a unified feedback control framework. By treating STs as dynamic storage actuators, ST-MTFC enhances classical
Mainstream Traffic Feedback Control (MTFC) strategies, improves bottleneck throughput, protects ramp accessibility, and mitigates upstream queuing. The effectiveness of this integrated approach is validated through microsimulation in AIMSUN Next using a real-world freeway segment.
Chapter 5 proposes a refined segment-aware speed-density relationship, Road Segment Proximity to Service Stations (RSP2S), that incorporates ST-related perturbations into the speed estimation function. The formulation embeds anticipatory terms for upstream slowdown and correction terms for downstream merging effects, making it responsive to local dynamics induced
by ST operations. The RSP2S model is calibrated and validated against AIMSUN data, showing improved behavioral fidelity and empirical accuracy over classical formulations.
Overall, this thesis advances a new generation of infrastructure-aware traffic flow models and control strategies by repositioning service stations as active elements within macroscopic frameworks. The proposed methods offer increased flexibility, improved congestion management, and a deeper integration of roadside infrastructure into traffic control design.Macroscopic traffic modeling and control are fundamental to the effective operation of modern freeway networks, with direct implications for congestion mitigation, travel time reliability, and energy efficiency. Traditionally, Service Stations (STs) have been treated as passive roadside elements. However, their increasingly dynamic interaction with traffic, due to changing driver behavior and growing network complexity, demands a shift in perspective. This thesis proposes a comprehensive, infrastructure-aware modeling and control framework that explicitly incorporates the dynamics of STs into freeway traffic management.
Chapter 2 introduces METANET with service station (METANET-s), a novel second-order macroscopic traffic model that extends the classical METANET model to account for ST dynamics via a dedicated Service Area Facility modeled by a Store-and-forward (saf) link. The model enforces physical capacity constraints at STs and simulates critical behaviors such as queue
formation, dwell times, and re-entry effects.
Chapter 3 presents the Infrastructure-Dependent ramp-metering Control (IDC) strategy designed for METANET-s. This two-tier control scheme combines ALINEA ramp-metering at the ST exit with route guidance mechanisms that manage vehicle entry into the ST during peak congestion. The IDC scheme enables the active use of STs as traffic regulators, improving flow distribution and reducing congestion-induced delays along freeway segments.
Building on this foundation, Chapter 4 introduces the Service Station-Enhanced Mainstream Traffic Flow Control (ST-MTFC) architecture, which integrates Variable Speed Limit (VSL) and IDC scheme including ramp-metering, and route guidance within a unified feedback control framework. By treating STs as dynamic storage actuators, ST-MTFC enhances classical
Mainstream Traffic Feedback Control (MTFC) strategies, improves bottleneck throughput, protects ramp accessibility, and mitigates upstream queuing. The effectiveness of this integrated approach is validated through microsimulation in AIMSUN Next using a real-world freeway segment.
Chapter 5 proposes a refined segment-aware speed-density relationship, Road Segment Proximity to Service Stations (RSP2S), that incorporates ST-related perturbations into the speed estimation function. The formulation embeds anticipatory terms for upstream slowdown and correction terms for downstream merging effects, making it responsive to local dynamics induced
by ST operations. The RSP2S model is calibrated and validated against AIMSUN data, showing improved behavioral fidelity and empirical accuracy over classical formulations.
Overall, this thesis advances a new generation of infrastructure-aware traffic flow models and control strategies by repositioning service stations as active elements within macroscopic frameworks. The proposed methods offer increased flexibility, improved congestion management, and a deeper integration of roadside infrastructure into traffic control design
Rethinking the Role of the Cerebellum in Mediating Human Behavior Through TMS: From Socio-Emotional Processing to Clinical Applications
No full textHistorically, the cerebellum has been primarily associated with motor control, while its contribution to higher-order cognition has only more recently been explored. The cerebellum supports a wide spectrum of functions, including emotional and social processing. Despite this growing body of evidence, relevant questions regarding its temporal and intrinsic dynamics, topographic characteristics, and clinical relevance remain unanswered. Transcranial magnetic stimulation (TMS) allows for testing causal evidence about cerebellar involvement in socioemotional processing and investigating novel therapeutic applications. In the present thesis, the involvement of the cerebellum in socio-emotional processing was investigated by employing TMS in four distinct experiments, testing for hypotheses concerning cerebellar chronometry and topography, and eventual intra-cerebellar functional dependencies. Furthermore, a systematic review was conducted to evaluate the effectiveness of multisession cerebellar TMS in treating motor and non-motor clinical conditions. Results showed that the posterior cerebellum recruits medial and lateral areas for emotional processing and social cognition (precisely, mentalizing) respectively, that medial and lateral areas are functionally independent of each other, and that it displays a specific chronometric pattern in emotional processing. Additionally, multisession cerebellar TMS was proven to be effective, safe, and tolerable in the treatment of symptoms of several motor and non-motor clinical conditions. Overall, this thesis provides causal evidence for the posterior cerebellum’s involvement in socio-emotional processing and for its central contribution to a wider social neural network, and supports the implementation of cerebellar TMS as a protocol for clinical treatment.Historically, the cerebellum has been primarily associated with motor control, while its contribution to higher-order cognition has only more recently been explored. The cerebellum supports a wide spectrum of functions, including emotional and social processing. Despite this growing body of evidence, relevant questions regarding its temporal and intrinsic dynamics, topographic characteristics, and clinical relevance remain unanswered. Transcranial magnetic stimulation (TMS) allows for testing causal evidence about cerebellar involvement in socioemotional
processing and investigating novel therapeutic applications. In the present thesis, the involvement of the cerebellum in socio-emotional processing was investigated by employing TMS in four distinct experiments, testing for hypotheses concerning cerebellar chronometry and topography, and eventual intra-cerebellar functional dependencies. Furthermore, a systematic review was conducted to evaluate the effectiveness of multisession cerebellar TMS in treating motor and non-motor clinical conditions. Results showed that the posterior cerebellum recruits medial and lateral areas for emotional processing and social cognition (precisely, mentalizing) respectively, that medial and lateral areas are functionally independent of each other, and that it displays a specific chronometric pattern in emotional processing. Additionally, multisession cerebellar TMS was proven to be effective, safe, and tolerable in the treatment of symptoms of several motor and non-motor clinical conditions. Overall, this thesis provides causal evidence for the posterior cerebellum’s involvement in socio-emotional processing and for its central contribution to a wider social neural network, and supports the implementation of cerebellar TMS as a protocol for clinical treatment
Substance-Based Medical Device in Wound Care: Bridging Regulatory Clarity and Therapeutic Innovation
No full textSubstance-based medical devices (SBMDs) are increasingly used in wound care due to their favorable safety profile, physicochemical mechanisms of action, and therapeutic effectiveness. These products often incorporate biopolymers such as hyaluronic acid or chitosan, alone or in combination with antimicrobial agents like silver nanoparticles (AgNPs) or silver sulfadiazine (SSD), offering hydration, tissue protection, and control of microbial burden in both acute and chronic wounds. Despite their widespread clinical use, the regulatory classification of SBMDs under Regulation (EU) 2017/745 (MDR) remains one of the most challenging and debated areas within the current European framework. This review analyzes the scientific and regulatory context of topical SBMDs, with particular emphasis on borderline products that share similarities with medicinal products in terms of formulation, composition, or claimed effects. The discussion focuses on the application of MDR Annex VIII, specifically Rule 21 for substance-based devices and Rule 14 for devices incorporating medicinal substances with ancillary action, together with interpretative guidance provided by MDCG 2022-5 Rev.1 and the Association of the European Self-Care Industry (AESGP) Position Paper. Particular attention is given to the identification of the critical role of the primary mode of action (MoA) as the determining criterion for regulatory qualification, especially for products containing antimicrobial substances. Through selected examples and case analyses, the review highlights inconsistencies in classification across Member States and underscores the need for a more harmonized, evidence-based, and proportionate regulatory approach. Overall, SBMDs challenge traditional regulatory boundaries and call for a framework capable of accommodating complex, multifunctional products while ensuring patient safety and regulatory coherence
Open-oriented algorithmic approach for BIM modelling of complex historic water infrastructure
No full textThe management of water resources has underpinned the history of settlement systems for centuries. The introduction of railways often led to neglect the previously fundamental hydraulic infrastructures that characterised the landscape. The “Naviglio” of the city of Pavia (Italy), an artificial water channel built to allow uphill navigation from Pavia to Milan, is the perfect example of a relevant historic infrastructure worth of management and refurbishment interventions. To this end, monitoring strategies and a digital ecosystem to implement them are required. Namely, the proposed methodological workflow integrates semi-automated modelling procedures for the fast development of a LOD 200 GeoBIM model of the “Naviglio” starting just from 2D cartographic data and literature information. The objective is indeed to set up a digital ecosystem, taking advantage of the strength of the BIM methodologies, optimised for implementing monitoring strategies both at architectural and urban scales. Furthermore, the approach seeks to employ open tools when possible, relying on a transferable parametrisation algorithm so as not to constrain further researchers to a specific BIM authoring tool