Politecnio die Bari - Catalogo di prodotti della Ricerca
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Monitoring Landslide Dynamics Using PSInSAR and Historical Geotechnical Data in the Pianello Slope, Bovino, Italy
No full textMeasurement of the inclusive cross sections for W and Z boson production in proton-proton collisions at = 5.02 and 13 TeV
No full textGellan gum/tannic acid hydrogels for cartilage repair: the versatile role of tannic acid as green crosslinker conferring antibacterial and anti-inflammatory properties
No full textA novel hydrogel, containing two gellan gums with different acyl content crosslinked with tannic acid and magnesium ions, was proposed as cartilage substitute. In addition to crosslinking, tannic acid was employed as an anti-inflammatory and antioxidant compound. The analytical characterization of the hydrogel revealed that the interaction between carbohydrates and tannic acid consisted of hydrogen bonds. The hydrogel showed satisfactory mechanical performances (compressive Young's modulus up to 188 ± 12 kPa, and strain at break up to 55.3 ± 1.5 %). The biological results demonstrated that tannic acid-loaded hydrogels were cytocompatible and significantly enhanced the genetic expression of key chondrogenic markers (Collagen type 2 and SRY-Box Transcription Factor 9), showing up-regulation of ∼30- and 14-fold under physiological conditions, and ∼6- and 3-fold under pro-inflammatory conditions of oxidative stress, compared to the unloaded hydrogels. Moreover, the intrinsic ability of tannic acid to bind pro-inflammatory active species under oxidative stress imparted the scaffold with immunomodulatory properties, as shown by the upregulation of the anti-inflammatory genes Interlukin-10 and Interferon-γ. Finally, tannic acid reported bactericidal and anti-biofilm activity, achieving a bacterial load reduction of over 90 % when hydrogels were infected with Staphylococcus aureus. Thus, this research highlights the multiple bioactivity of the gellan gum/tannic acid hydrogel for cartilage regeneration
Geographically Distributed Real-Time Simulation of a Hierarchical Control Architecture for Isolated Microgrids
No full textIn the energy transition scenario, the security of small isolated electrical networks is challenged by the pervasive Renewable Energy Sources (RES) penetration. This paper presents a hierarchical control architecture designed within the framework of an Italian industrial research project. The proposed control architecture aims to allocate adequate operating reserve during the operation of isolated microgrids in the presence of high RES penetration. To validate its performances under realistic conditions, the architecture was implemented and tested in a Hardware-in-the-Loop simulation environment, which employed Geographically Distributed Real-Time Simulation to exploit the software and hardware facilities of two separate laboratories. The set-up serves as a cyber-physical demonstrator, enabling the assessment of the readiness level and effectiveness of the proposed control architecture in ensuring the secure operation of the isolated electrical network of a real Italian small island under vulnerable operating conditions
Innovative digital systems for the diagnosis of built heritage
No full textThe conservation and enhancement of historical architectural heritage play a crucial role in preserving the cultural memory and the social role of communities. Diagnosis and monitoring activities aimed at planning restoration and maintenance of the built heritage, which is often characterised by deterioration and structural instability, require time-consuming and costly manual labour. In recent years, the advent of advanced digital technologies has brought transformative changes to the field of architectural conservation. Techniques such as laser scanning, photogrammetry, Artificial Intelligence (AI), Internet of Things (IoT) systems and Historic Building Information Modeling (HBIM) environments offer effective solutions for documenting, analysing and monitoring the conditions and deterioration of historic buildings. Nevertheless, despite these technological advances, significant challenges remain, including the absence of standardised protocols, limited data interoperability, and the complexity of conducting interdisciplinary analyses. In this context, the research aims to establish an innovative methodological framework for the diagnosis and monitoring of the built heritage, with particular focus on reverse engineering techniques, Artificial Intelligence and IoT systems. The proposed approach aims to optimise the processes of data collection, analysis, and management of diagnostic information by leveraging reality-based three-dimensional models (point clouds and textured meshes), to conduct visual assessments of artefact’s state of conservation, including periodic monitoring over time. The methodology adopted involves data acquisition through photogrammetric surveys to generate high-resolution three-dimensional models, followed by the automatic classification of degradation pathologies by means of AI techniques, through the development ofmachine learning and deep learning algorithms designed to analyse image-based data derived from digital surveys (textures, UV maps, orthoimages). In this way, the threedimensional models are not merely a geometric reference for the 3D modelling phase, serving instead as intrinsic containers of both colorimetric and geometric information that also spill over into the two-dimensional data derived from them. In this way, the extraction of geometric and metric data allows for qualitative and quantitative analyses of the state of preservation in order to provide consistent and reliable diagnostic information, both in terms of the extent and the severity of degradation pathologies. Furthermore, integrating this information, along with sensor data from IoT systems, into interoperable and shareable HBIM-based environments allows for a complete and dynamic digital representation of the building. These representations support ongoing monitoring and evaluation phases of decay progression over time, enabling the planning of targeted and shared interventions. The research aims to establish a standardised and efficient methodological-operational workflow for the diagnosis of built heritage, promoting the replicability and scalability of the approach. Validation has been conducted through significant case studies about the historical cultural heritage of the Italian and Spanish territories. Based on the materials and structural characteristics, as well as the current conditions of the studied sites, different techniques of automatic classification of the pathologies have been validated and tested. The results have been integrated into semantically enriched digital environments, offering a solid basis for future technological and methodological advancements in the field of digitisation and architectural conservation
On the Solutions for the Conserved Kuramoto–Sivashinsky Equation
No full textThe conserved Kuramoto–Sivashinsky equation has been derived in the context of crystal growth. In this paper, we study the existence, uniqueness, and stability with respect to the initial data of the initial value problem
MAGIC: Multi-User Advanced Graphic Immersive Configurator for Sustainable Customization of Complex Design Products—A Sailing Yacht Case Study
No full textModern design products are increasingly complex and emotionally significant, demanding versatile and collaborative customization. However, a literature and commercial review reveals a limited availability of flexible, multi-user, photorealistic Virtual Reality (VR) systems for product configuration. We introduce MAGIC (Multi-user Advanced Graphic Immersive Configurator), a collaborative platform combining realistic graphics with ergonomic validation using digital avatars, addressing the limitations of 2D visualization and existing tools. MAGIC is evaluated in a yacht design case study involving 30 participants in an immersive, co-located configuration of a sailing yacht to assess the system’s usability and the potential of VR for customizing complex products. Results show MAGIC’s feasibility in supporting multi-user configuration (100% success rate) and achieving a strong usability score (SUS = 80.83). User feedback highlights that high-quality graphics and additional content significantly enhance immersion and user engagement. However, encountered challenges with navigation methods and spatial perception indicate areas for improvement. MAGIC’s collaborative and immersive capabilities can be extended to other industries demanding proactive customer engagement in the customization of large, heavy products and ergonomic design. Moreover, by promoting prototype dematerialization and providing an interactive remote tool for end users, MAGIC offers potential environmental and economic benefits to boost the competitiveness of small and medium enterprises (SMEs)
Enhanced Segmentation of Glioma Subregions via Modality-Aware Encoding and Channel-Wise Attention in Multimodal MRI
No full textAccurate segmentation of key tumor subregions in adult gliomas from Magnetic Resonance Imaging (MRI) is of critical importance for brain tumor diagnosis, treatment planning, and prognosis. However, this task remains poorly investigated and highly challenging due to the considerable variability in shape and appearance of these areas across patients. This study proposes a novel Deep Learning architecture leveraging modality-specific encoding and attention-based refinement for the segmentation of glioma subregions, including peritumoral edema (ED), necrotic core (NCR), and enhancing tissue (ET). The model is trained and validated on the Brain Tumor Segmentation (BraTS) 2023 challenge dataset and benchmarked against a state-of-the-art transformer-based approach. Our architecture achieves promising results, with Dice scores of 0.78, 0.86, and 0.88 for NCR, ED, and ET, respectively, outperforming SegFormer3D while maintaining comparable model complexity. To ensure a comprehensive evaluation, performance was also assessed on standard composite tumor regions, i.e., tumor core (TC) and whole tumor (WT). The statistically significant improvements obtained on all regions highlight the effectiveness of integrating complementary modality-specific information and applying channel-wise feature recalibration in the proposed model
Resilient and Flexible Electrohydrodynamics Pumps for Human–Machine Interfaces
No full textSoft fluidic systems can be a versatile tool to design human–machine interfaces such as hydraulic actuators, liquid displays, and thermal haptics. Yet the bulkiness, noise, and rigidity of pumps and valves required for fluid circulation prevent their use in flexible and portable devices. This study introduces an electrohydrodynamic (EHD) driven flexible pump with resilience against dielectric breakdown. Previous EHD pumps, despite their excellent features such as quietness and high power density, suffer from dielectric breakdowns and subsequent permanent failures. This pump with novel electrode construction has the passive resilience to recover the insulation essential for EHD without any external input in the event of dielectric breakdown. The passive resilience of our pump is demonstrated in various scenarios. Notably, this pump withstands 100 dielectric breakdowns and maintains 90% of its performance. An active resilient system is also configured to enable continuous pumping. This system automatically removes bubbles and other impurities to recover flow generation. This pumps drive various soft fluid-driven human-machine interfaces like soft actuators, prosthetic hands, and tube-format displays. The combination of passive resilience inherent in the pump and active resilience configured by the system ensures adaptability and robustness, setting the stage for the next generation of human–machine interfaces