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Conceptual eco-physical reframing for immovable cultural heritage assets in the context of sustainable cities
No full textUrban sustainability research increasingly recognizes cities as social-ecological systems shaped through the long-term construction of the human niche to which cities belong. However, immovable cultural heritage assets remain largely absent from ecological models of urban resources functioning and management. This article advances a theoretical reframing of built cultural heritage as components and regulators of urban systems, arguing that their material persistence contributes to environmental modulation and supports the provision of ecosystem services. In particular, we hypothesize that built heritage participates in urban metabolism not only through material flows, but also through the transmission of environmental information and the generation of non-material ecosystem services such as identity, spatial coherence, and perceptual intelligibility, operating as long-term regulators of human–environment interactions, while anchoring collective memory within the urban landscape. Thus, the ecological agency of heritage produces also systemic co-benefits that align with the integrative principles of One Health, not as health-driven outcomes, but as emergent effects of ecological continuity and informational stability. The framework presented here positions immovable cultural heritage as a material–sensory–informational infrastructure embedded within the metabolism of the city and outlines a set of testable hypotheses for future interdisciplinary research aimed at integrating heritage into sustainable urban systems
Sul fondamento umanistico della relazione di cura nell’ambito educativo: Prerequisiti per lo sviluppo degli atteggiamenti metacognitivi e l’uso di tecnologie assistive
No full textExploring the role of residential surrounding greenness in global and domain-specific cognitive function among community-dwelling mature and older adults from Southern Italy
No full textObjectivesRecent evidence suggests residential surrounding greenness may benefit cognitive functioning. Although benefits have been widely studied in children and young adults, research involving mature and older adults, especially studies using objective greenness measures and comprehensive cognitive assessments, remains limited and shows mixed results. This study examines the effect of residential surrounding greenness on global and domain-specific cognition (memory, attention, language, executive functions) in community-dwelling mature and older adults. Also, moderating factors (age, gender, and education) are investigated.MethodSatellite-based Normalized Difference Vegetation Index (NDVI) was measured at 100, 300, and 500 m buffers around residences, considering short-term (1-year) and long-term (20-year) exposure. Cognitive functioning was assessed using standardized neuropsychological tests. Linear and moderated regression models tested hypotheses.ResultsFindings reveal differentiated effects of residential greenness on cognition. Short- and long-term exposure were positively associated with language performance in subgroups, such as older participants and those with lower schooling. Conversely, greenness exposure was negatively associated with memory, particularly in males.ConclusionThese findings highlight the complex relationship between residential greenness and cognition. Effects vary across cognitive domains and socioeconomic factors, underscoring the need for further investigation of mechanisms linking greenness exposure to cognitive functioning in aging populations
Socio-ecological resilience and technology-driven value creation for humanitarian emergencies. An exploratory case study
No full textThe purpose of this paper is to explore, assuming the service ecosystem perspective, the humanitarian domain, and the multi-level dynamics that ensure service continuity even in emergencies. In doing so, the enhancing role of digital technologies has been investigated, pointing out the way they support actors in enacting specific practices able to make a humanitarian service ecosystem (HSE) resilient over time. The study was based on an
exploratory qualitative analysis, conducted by administering some semi-structured interviews to humanitarian service ecosystem key informants. Results were analyzed and presented by implementing an interpretative data analysis process. An HSE was conceptualized by grasping its main characteristics, also pointing out the role that digital technologies play in ensuring service continuity and the main mechanisms that make it resilient and, therefore, able to function and evolve by creating new and renovated value. The research theoretically contributes to the nascent literature on the humanitarian service ecosystem, offering a new understanding of the role
that socio-technical actors can have in ensuring the continuity of humanitarian service in emergency contexts. Particularly, the study advances the literature on service ecosystems in the humanitarian domain, providing a multilevel framework that explains the mechanisms linking humanitarian ecosystem emergency management to resilient outcomes. Practically, the study offers interesting insights for humanitarian organizations, policy-makers, and technology developers seeking to enhance preparedness and response strategies by leveraging digital innovations
Non-thermal dielectric barrier discharge plasma for the degradation of microplastics suspended in water: Evidence from CO2 quantification and spectroscopic analysis
No full textThe persistence of microplastics (MPs) in aquatic environments poses a significant challenge due to their resistance to conventional remediation strategies. In this study, the direct application of atmospheric dielectric barrier discharge (DBD) non-thermal plasma (NTP) was investigated for the mineralization of polyvinyl chloride (PVC), polystyrene (PS), and polypropylene (PP) microplastics suspended in water. Treatments were carried out using air or pure oxygen as process gases, and degradation efficiency was quantitatively assessed by continuous COQ monitoring via in-line mass spectrometry. A key innovation of this work lies in the direct plasma treatment of MP-contaminated water combined with real-time COQ evolution tracking and internal temperature measurement using a fiber optic probe. Although temperature increases during the treatment, this approach enables the evaluation of the relative contributions of thermal effects and plasma-induced chemical degradation mechanisms. Results show that using oxygen as the process gas significantly enhances degradation performance compared to air, with PVC exhibiting the highest COQ release due to dehydrochlorination followed by oxidation. PS showed intermediate reactivity, whereas PP was the least responsive under plasma treatment. Structural and morphological changes were characterized by SEM, FTIR, and Raman spectroscopy, revealing polymer-specific surface modifications induced by plasma treatment. These findings provide new insights into selective microplastic degradation mechanisms and highlight non-thermal plasma as a promising tool for advanced oxidation processes under mild operating conditions
ANN-based prediction of photosynthetically active radiation (PAR) in an agrivoltaic greenhouse system
No full textAgrivoltaics represents an innovative approach that mitigates land-use conflicts between the energy and agricultural sectors. The integration of semi-transparent photovoltaic modules into agriculture is a valid strategy for increasing the availability of solar radiation incident on crops. These modules modify the spectral distribution of solar radiation and the amount of Photosynthetically Active Radiation (PAR) available for photosynthesis. However, direct PAR measurement is limited worldwide, making it necessary to use empirical models for its prediction. The aim of this paper is to fill this gap by presenting a Multi-Layer Perceptron (MLP) Artificial Neural Network (ANN) model developed to predict PAR in semi-transparent agrivoltaic greenhouses. The network was trained using experimental data collected at the University of Ja ́en on two agrivoltaic greenhouses: a control unit with transmissivity of 92% and a semi-transparent configuration with transmissivity of 20%. Specifically, the input variables considered for this study are global radiation on the array plane (G poa ), angle of incidence (AOI), air mass (AM) and transmittance coefficient (CT) of the modules. The model shows excellent convergence between the predicted and target values for both greenhouse configurations, with an average correlation coefficient (R) of 0.99 and a Normalized Mean Squared Error (nMSE) equal to 0.0135
Organizational Sustainability in Environmental Complexity: Linking to the 2030 Agendas
No full textThis chapter examines the concept of organizational sustainability in light of the growing environmental complexity that characterizes the contemporary global context, marked by interconnected ecological, social, economic, and technological crises. Drawing on contributions from complexity theory, the Anthropocene, and resilience studies, the text proposes a reinterpretation of sustainability not as an ancillary practice or reputational tool, but as a systemic, transformative, and ethically grounded principle. Particular attention is paid to the role of organizations as co-constitutive actors in socio-ecological dynamics, called upon to integrate sustainability into governance models, strategies, and organizational cultures. The chapter also analyzes the relevance of the 2030 Agenda and the Sustainable Development Goals as a regulatory and strategic framework of reference, while highlighting their critical issues and operational potential. In conclusion, it is argued that worker well-being is a key, albeit often underestimated, dimension of organizational sustainability, contributing decisively to the resilience, innovation, and legitimacy of organizations in complex contexts
La raccolta e l’analisi dei dati di rete per lo studio dell’effetto dei pari in ambito scolastico
No full textIl volume presenta i principali risultati del Progetto PRIN 2022 PEERUP From high school to university: Assessing peers’ influence in educational inequalities and performances che ha coinvolto le Università di Cagliari, Firenze e Salerno. Esso analizza i percorsi educativi dalla scuola superiore all’università, con particolare attenzione all’ultimo anno della scuola e alla fase di transizione verso l’istruzione terziaria. Lo studio si concentra sul ruolo delle disuguaglianze educative e sull’influenza esercitata dal genere, dalle condizioni socioeconomiche della famiglia, dal contesto dei pari e dalla tipologia di istituto frequentato sulle scelte formative e sulle performance accademiche.
Gli obiettivi del progetto sono stati perseguiti mediante l’uso integrato di dati amministrativi e di indagini nazionali sulla valutazione del sistema educativo e attraverso la raccolta di dati primari con la realizzazione di due indagini. La prima, comune alle tre unità di ricerca e realizzata in Campania, Sardegna e Toscana, analizza i fattori che influenzano la decisione di proseguire gli studi universitari dopo il diploma, con riferimento all’ambito disciplinare, alle intenzioni di mobilità, al ruolo delle cerchie sociali e alle motivazioni individuali. La seconda indagine approfondisce l’influenza della struttura e della composizione delle reti personali, delle reti amicali e di supporto sociale tra compagni di classe sulle scelte educative di studenti e studentesse in un campione di scuole campane
Agrivoltaics Across Crops and Technologies: A Systematic Review of Experimental Tests on Yield, Microclimate, and Energy Performance
No full textAgrivoltaics is a rapidly expanding technology thanks to its energy, agronomic, and microclimatic benefits, which have been demonstrated in a variety of climatic contexts around the world. This study presents the first systematic review exclusively focused on experimental agrivoltaics field studies, based on the analysis of 82 peer-reviewed articles. The aim is to provide a cross-study comparable synthesis of how shading from different photovoltaic (PV) technologies affects microclimate, crop yield, and crop quality. The reviewed systems include four main categories of PV modules: conventional, bifacial, semi-transparent/transparent, including spectrally selectivity modules and concentrating photovoltaic systems (CPV). To handle heterogeneity and improve comparability, results were normalised against open-field controls as relative percentage variations. The analysis reveals a high variability in results, strongly influenced by crop type, climate, level of shading, and reduction in PAR (Photosynthetically Active Radiation). Studies conducted with the same shade intensity but under different climatic conditions show contrasting results, suggesting that there is no universally optimal agrivoltaics configuration. Nevertheless, the review allows us to identify recurring patterns of compatibility between crops and photovoltaic technologies, providing useful guidance for choosing the most suitable technology based on climate, crop physiology, and production objectives
SUPPORTING DOMAIN EXPERTS IN DATA-DRIVEN PROCESSES WITHIN THE MEDICAL CONTEXT
No full textLA CRESCENTE DIGITALIZZAZIONE DEI SISTEMI SANITARI E LA CONSEGUENTE DISPONIBILITÀ DI BIG DATA BIOMEDICI HANNO TRASFORMATO IL MODO IN CUI LE INFORMAZIONI VENGONO ACQUISITE, GESTITE E SFRUTTATE IN AMBITO CLINICO E DI RICERCA. TUTTAVIA, L'ETEROGENEITÀ DELLE FONTI DI DATI, L'INCOMPLETEZZA DELLE CARTELLE CLINICHE, LA VARIABILITÀ SEMANTICA DELLA TERMINOLOGIA DI DOMINIO E LA RICHIESTA DI RISULTATI INTERPRETABILI PONGONO SFIDE SIGNIFICATIVE ALLA PROGETTAZIONE DI PROCESSI BIOMEDICI AFFIDABILI BASATI SUI DATI. QUESTE SFIDE INFLUISCONO DIRETTAMENTE SULLA CAPACITÀ DEGLI ESPERTI DI DOMINIO DI ESPLORARE, COMPRENDERE E FIDARSI DELLE INFORMAZIONI PRODOTTE DA TALI PROCESSI. IN QUESTA TESI, L'INTERA PIPELINE BIOMEDICA BASATA SUI DATI VIENE ESAMINATA END-TO-END, CON PARTICOLARE ATTENZIONE A COME DIVERSE TIPOLOGIE DI METADATI (DOCUMENTALI E DI PROFILAZIONE) POSSANO MIGLIORARE OGNI FASE E SUPPORTARE GLI ESPERTI DI DOMINIO NEL PRENDERE DECISIONI INFORMATE E INTERPRETABILI.
IL PRIMO CONTRIBUTO RIGUARDA LA FASE DI ACCESSO ALLE INFORMAZIONI. VIENE PROPOSTO UN MOTORE DI RICERCA SEMANTICO PER LA LETTERATURA BIOMEDICA, SFRUTTANDO METADATI DOCUMENTALI, RAPPRESENTAZIONI BASATE SU GRAFICI E TECNICHE DI ANALISI SEMANTICA PER SUPERARE I LIMITI DEL RECUPERO BASATO SU PAROLE CHIAVE. IL SISTEMA SCOPRE RELAZIONI CONCETTUALI TRA I TERMINI, MITIGANDO L'IMPATTO DELLA VARIABILITÀ TERMINOLOGICA TIPICA DEL DOMINIO E MIGLIORANDO LA QUALITÀ DEL RECUPERO, CON BENEFICI PER LE FASI SUCCESSIVE DELLA PIPELINE. PER MIGLIORARE LA QUALITÀ DEI DATI ALL'INTERNO DI DATASET BIOMEDICI, LA TESI INDAGA L'INTERAZIONE TRA LA SCOPERTA DI PROFILING METADATA E L'IMPUTAZIONE DEI DATI IN SCENARI INCREMENTALI. ATTRAVERSO DUE PIPELINE COMPLEMENTARI, MOSTRA COME LA SCOPERTA PROGRESSIVA DI DIPENDENZE FUNZIONALI RILASSATE (RFD) POSSA GUIDARE PROCESSI DI IMPUTAZIONE PIÙ EFFICACI E, VICEVERSA, COME L'IMPUTAZIONE CONTRIBUISCA ALLA STABILITÀ E ALLA COMPLETEZZA DELLE DIPENDENZE SCOPERTE. INOLTRE, LA TESI PRESENTA UN ALGORITMO DI DATA AUGMENTATION BASATO SU RFD, VOLTO A CORREGGERE LO SQUILIBRIO DI CLASSE PRESERVANDO AL CONTEMPO I VINCOLI STRUTTURALI E SEMANTICI DEI DATI ORIGINALI, MIGLIORANDO ULTERIORMENTE LA QUALITÀ DEI DATI PRIMA DELLE ATTIVITÀ ANALITICHE. NELL'AMBITO PIÙ AMPIO DELLA SCOPERTA DI METADATI, LA TESI PRESENTA UN ALGORITMO PER LA SCOPERTA DI PROPERTY GRAPH KEY (PG KEY), UN NUOVO TIPO DI METADATI STRUTTURALI CHE IDENTIFICA VINCOLI DI UNICITÀ E PATTERN RELAZIONALI NELLE RAPPRESENTAZIONI BASATE SU GRAFI. QUESTO CONTRIBUTO MIGLIORA LA COERENZA, L'INTERPRETABILITÀ E LA INTERROGABILITÀ DEI GRAFI BIOMEDICI, RAFFORZANDO L'ORGANIZZAZIONE E LA QUALITÀ DELLE INFORMAZIONI LUNGO L'INTERA PIPELINE. A SUPPORTO DELLA FASE FINALE DI INTERPRETAZIONE E SPIEGABILITÀ, LA TESI INTRODUCE UNO STRUMENTO PER L'ANALISI DELL'EVOLUZIONE TEMPORALE DEGLI RFD. INTEGRANDO L'ANALISI DEI METADATI CON I MODELLI LINGUISTICI, LO STRUMENTO FORNISCE INFORMAZIONI SU COME E PERCHÉ LE DIPENDENZE CAMBIANO NEL TEMPO, FACILITANDO LA CONVALIDA DEL MODELLO E L'INTERPRETAZIONE DEI FENOMENI SOTTOSTANTI. INFINE, LA TESI PROPONE UN FRAMEWORK COMPLETO PER LA VALUTAZIONE DI SET DI DATI SINTETICI LUNGO DIVERSE DIMENSIONI DI QUALITÀ, SUPPORTATO DA UNA PIATTAFORMA WEB INTERATTIVA CHE GARANTISCE INTERPRETABILITÀ E RIPRODUCIBILITÀ.THE GROWING DIGITALIZATION OF HEALTHCARE SYSTEMS AND THE RESULTING AVAILABILITY OF BIOMEDICAL BIG DATA HAVE PROFOUNDLY TRANSFORMED THE WAY INFORMATION IS ACQUIRED, MANAGED, AND EXPLOITED IN CLINICAL AND RESEARCH SETTINGS. YET THE HETEROGENEITY OF DATA SOURCES, THE INCOMPLETENESS OF BIOMEDICAL RECORDS, THE SEMANTIC VARIABILITY OF DOMAIN TERMINOLOGY, AND THE DEMAND FOR INTERPRETABLE RESULTS POSE SIGNIFICANT CHALLENGES TO THE DESIGN OF RELIABLE DATA-DRIVEN BIOMEDICAL PROCESSES. THESE CHALLENGES DIRECTLY AFFECT THE ABILITY OF DOMAIN EXPERTS TO EXPLORE, UNDERSTAND, AND TRUST THE INFORMATION PRODUCED BY SUCH PROCESSES. IN THIS THESIS, THE ENTIRE DATA-DRIVEN BIOMEDICAL PIPELINE IS EXAMINED END-TO-END, WITH A PARTICULAR FOCUS ON HOW DIFFERENT TYPES OF METADATA (DOCUMENTARY AND PROFILING) CAN ENHANCE EACH STAGE AND SUPPORT DOMAIN EXPERTS IN MAKING INFORMED AND INTERPRETABLE DECISIONS. THE FIRST CONTRIBUTION CONCERNS THE INFORMATION ACCESS PHASE. A SEMANTIC SEARCH ENGINE FOR BIOMEDICAL LITERATURE IS DEVELOPED, LEVERAGING DOCUMENTARY METADATA, GRAPH-BASED REPRESENTATIONS AND SEMANTIC ANALYSIS TECHNIQUES TO OVERCOME THE LIMITATIONS OF KEYWORD-BASED RETRIEVAL. THE SYSTEM UNCOVERS CONCEPTUAL RELATIONSHIPS BETWEEN TERMS, MITIGATING THE IMPACT OF TERMINOLOGICAL VARIABILITY TYPICAL OF THE DOMAIN AND ENHANCING THE QUALITY OF RETRIEVAL, WITH DIRECT BENEFITS FOR SUBSEQUENT PIPELINE STAGES. TO IMPROVE DATA QUALITY WITHIN BIOMEDICAL DATASETS, THE THESIS INVESTIGATES THE INTERPLAY BETWEEN PROFILING METADATA DISCOVERY AND DATA IMPUTATION IN INCREMENTAL SCENARIOS. THROUGH TWO COMPLEMENTARY PIPELINES, IT SHOWS HOW THE PROGRESSIVE DISCOVERY OF RELAXED FUNCTIONAL DEPENDENCIES (RFDS) CAN GUIDE MORE EFFECTIVE IMPUTATION PROCESSES AND, CONVERSELY, HOW INCREMENTAL IMPUTATION CONTRIBUTES TO THE STABILITY AND COMPLETENESS OF THE DISCOVERED DEPENDENCIES. IN ADDITION TO THIS, THE THESIS PRESENTS AN RFD-BASED DATA AUGMENTATION ALGORITHM AIMED AT ADDRESSING CLASS IMBALANCE WHILE PRESERVING THE STRUCTURAL AND SEMANTIC CONSTRAINTS OF THE ORIGINAL DATA, THEREBY FURTHER ENHANCING DATA QUALITY BEFORE ANALYTICAL TASKS. WITHIN THE BROADER AREA OF METADATA DISCOVERY, THE THESIS PRESENTS AN ALGORITHM FOR THE DISCOVERY OF PROPERTY GRAPH KEYS (PG KEY), A NEW TYPE OF STRUCTURAL METADATA THAT IDENTIFIES UNIQUENESS CONSTRAINTS AND RELATIONAL PATTERNS IN GRAPH-BASED REPRESENTATIONS. THIS CONTRIBUTION ENHANCES THE CONSISTENCY, INTERPRETABILITY, AND QUERYABILITY OF BIOMEDICAL GRAPHS, REINFORCING THE ORGANIZATION AND QUALITY OF INFORMATION THROUGHOUT THE ENTIRE PIPELINE. TO SUPPORT THE FINAL STAGE OF INTERPRETATION AND EXPLAINABILITY, THE THESIS INTRODUCES A TOOL FOR ANALYZING THE TEMPORAL EVOLUTION OF RFDS. BY INTEGRATING METADATA ANALYSIS WITH LANGUAGE MODELS, THE TOOL PROVIDES INSIGHTS INTO HOW AND WHY DEPENDENCIES CHANGE OVER TIME, FACILITATING MODEL VALIDATION AND THE INTERPRETATION OF UNDERLYING PHENOMENA. FINALLY, THE THESIS PROPOSES A COMPREHENSIVE FRAMEWORK FOR EVALUATING SYNTHETIC DATASETS ALONG DIFFERENT QUALITY DIMENSIONS, SUPPORTED BY AN INTERACTIVE WEB PLATFORM THAT ENSURES INTERPRETABILITY AND REPRODUCIBILITY