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Esperienza scolastica, orientamento e aspettative per il lavoro: le percezioni di studenti e studentesse
No full textIl capitolo analizza come l’esperienza scolastica, la funzione orientativa delle istituzioni educative e le aspettative rispetto al lavoro contribuiscano a modellare le scelte post-diploma degli studenti. Inserito nel quadro teorico della sociologia dell’esperienza, il contributo interpreta la vita scolastica attraverso tre logiche – integrazione, strategia e soggettivazione – mostrando come esse influenzino la percezione di utilità, coinvolgimento e autoefficacia. Parallelamente, il capitolo approfondisce il ruolo delle aspettative e delle aspirazioni lavorative, evidenziando come esse derivino da un intreccio di risorse culturali, riconoscimento sociale, capitale informativo e pratiche orientative scolastiche.
Attraverso l’analisi dei dati dell’indagine Esperienze scolastiche e scelte educative, gli autori ricostruiscono due dimensioni dell’esperienza scolastica (strumentalità e coinvolgimento) e due dimensioni delle aspettative lavorative (strutturate/non strutturate e vocazionali/strumentali), ottenute tramite Analisi delle Corrispondenze Multiple. Le differenze emergono in relazione a genere, classe sociale, background migratorio, indirizzo scolastico e rendimento percepito, mostrando come tali caratteristiche influenzino sia la percezione della scuola sia l’orientamento verso il futuro lavorativo.
Il capitolo evidenzia infine il ruolo cruciale della scuola come mediatore tra vissuto educativo e costruzione delle aspettative, sottolineando come pratiche orientative efficaci possano ampliare gli orizzonti di scelta e ridurre i costi informativi, contribuendo a contrastare la riproduzione delle disuguaglianze
From intellectual to influencer. Populist mediation in the citizenship referendum debate.
No full textThe emergence of the internet has often been associated with an egalitarian communicative ideal: the shift from a one-to-many to a many-to-many model, the supposed end of the audience, and the rise of participatory culture (Jenkins, 2006) were interpreted as evidence of the disappearance of gatekeepers. Rather than producing a flat and inclusive communicative space, however, digital environments have fostered new forms of concentration of power, visibility, and influence.
This study explores the crisis of traditional cultural mediators - the emergence of a society "without intellectuals" (Caravale, 2023) - within the broader framework of a profound transformation in the Habermasian public sphere (Habermas, 2023; Schlesinger, 2024) and a parallel crisis of politics (Kirchheimer, 2015; Gerbaudo, 2019) marked by the rise of populism and anti-elitist rhetoric (Merkley, 2020). The research argues that the promise of disintermediation has resulted in a "re-intermediation" based on algorithmic visibility and the attention economy (Terranova, 2012), where visibility capital increasingly replaces symbolic and cultural capital (Bourdieu, 1996).
This theoretical framework is empirically explored through a case study of the online debate surrounding the Italian citizenship referendum held on 8–9 June 2025. The analysis is based on a dataset of 2,246 posts collected over a ten-week period on X and Bluesky. Using engagement-based rankings, the Gini concentration index, and sentiment analysis (NRC Emotion Lexicon), the study addresses whether digital debate promotes re-intermediation, identifies the central actors, and examines how emotional dynamics drive centrality across different platforms.
Findings show a high concentration of engagement, suggesting that the digital public sphere remains far from egalitarian. On X, the debate is dominated by hyper-visible political actors employing populist and emotionally charged strategies - most notably the "Hyperleader" Roberto Vannacci. Emotional analysis reveals high levels of negative affect (anger and fear), indicating a polarized environment. In contrast, Bluesky displays lower emotional intensity and a more heterogeneous composition of engaged users.
Rather than enabling new critical voices, the debate was dominated by figures able to ride the wave of digital consensus through self-branding and populist strategies. This suggests that the myth of disintermediation conceals an opposite process: the concentration of attention around a few powerful actors who act as new cultural mediators. Furthermore, this algorithmically-driven populist form of intermediation has profound consequences for the future of democratic deliberation
Impact of frailty on infection risk in non-transplant eligible multiple myeloma patients: a systematic review and meta-analysis
No full textDynamics of the Kac Ring Model with switching scatterers
No full textWe introduce a generalized version of the Kac ring model in which particles are of two types, black and white. Black particles modify the environment through which all particles move, thereby inducing indirect and potentially long-range interactions among them. Unlike the inert scatterers of Kac's original model, the scatterers in our setting possess internal states that change upon interaction with black particles and can be interpreted as energy levels of the environment. This makes the model self-consistent, as it incorporates a form of particle interactions, mediated by the environment, that drives the system toward some kind of stationary state. Although indirect and long-range interactions do not typically promote thermodynamic states, interactions are necessary for energy to play a role and be shared among the elementary constituents of matter. Therefore, the inclusion of interactions in our model constitutes a step forward in the description of a macroscopic system in terms of its microscopic constituents. We find that any initial state of the system converges to a time periodic state (i.e. a phase space orbit) and describe basins of attraction for some of such asymptotic periodic states
Artificial intelligence-assisted reading of non-contrast prostate MRI: application and concordance with expert interpretation in a screening population within the PROSA trial
No full textObjectives: Non-contrast MRI (bi-parametric MRI-bpMRI) has been investigated as a potential tool to be integrated in clinically significant prostate cancer (csPCa) screening. Moreover, artificial intelligence (AI) is emerging too as a potential support, especially for less-experienced radiologists. Therefore, the aim of this study was to evaluate the effectiveness of an AI-based software in csPCa screening using bpMRI, with a focus on supporting less-experienced radiologists. Material and methods: A retrospective analysis was conducted within the PROSA-trial, a randomized, single-center study involving 759 men eligible for PCa screening. BpMRI were acquired using prostate imaging reporting and data system (PI-RADS) v2.1-compliant protocols and evaluated independently by an expert radiologist, a less-experienced reader, AI-based software, and the less-experienced reader with AI support. Diagnostic performance was assessed using ROC curves and inter-reader agreement (Cohen's kappa), using expert interpretation as the reference standard. Results: Four hundred ninety-nine bpMRI were analyzed. The AI-assisted less-experienced reader achieved the highest diagnostic performance (sensitivity 76.5%, specificity 97.2%, accuracy 95.8%, AUC 0.969), surpassing both AI-alone (sensitivity 58.8%, specificity 96.6%, accuracy 94.0%, AUC 0.952) and unaided less-experienced reader (sensitivity 67.6%, specificity 95.1%, accuracy 93.2%, AUC 0.932). Inter-reader agreement improved with AI assistance (from κ = 0.64 to 0.84). AI assistance reduced equivocal PI-RADS 3 cases (from 77 to 53) and improved exact agreement with the expert from 32.5% to 54.5%, while also reducing diagnostic discordance. Conclusions: AI can support less experienced radiologists and enhance consistency in bpMRI interpretation, especially considering equivocal cases. Moreover, integrating AI into radiology workflows can alleviate reporting burden and help prioritize suspicious cases, offering critical advantages in high-volume PCa screening settings. Key points: Question Can AI improve the diagnostic performance and consistency of less experienced radiologists interpreting non-contrast prostate MRI in a screening setting? Findings AI assistance significantly improved effectiveness and inter-reader agreement in prostate MRI interpretation, particularly for less experienced radiologists within a screening population. Clinical relevance Integrating AI into prostate MRI workflows may enhance screening efficiency, reduce variability, and support equitable early detection of csPCa, with a positive impact on prioritization of reporting
Liguria e Piemonte nei dialoghi mediterranei della pittura del Tre e Quattrocento (1340-1480 circa)
No full textLa ricerca ha indagato i rapporti tra l'arte della Liguria e del Piemonte nei secoli del basso Medioevo (con particolare riferimento al Trecento e al Quattrocento) e le coeve manifestazioni sviluppatesi in altre regioni del Mediterraneo occidentale, specie la Spagna e l'Italia meridionale, ovvero quei territori che per buona parte del periodo esaminato furono inclusi nella Corona d'Aragona. Si sono prese in considerazione sia le relazioni dirette documentate, sia le affinità o tangenze stilistiche, nell'ambito della pittura, con qualche richiamo anche alle altre arti, come la scultura
Coping strategies and corrective actions to address digital consumer vulnerability: a multistakeholder perspective
No full textIn the digital environment, consumers are increasingly exposed to
deceptive marketing practices that increase their vulnerability and
create challenges for consumer protection. This study investigates
the consumer coping strategies adopted in situations of digital
deception and analyses how these interact with companies’ and
public institutions’ corrective actions at different stages of the
customer journey. A systematic literature review, conducted using
the PRISMA protocol and the snowballing technique, led to the
identification of 44 relevant articles. The analysis mapped the main
coping strategies (e.g. disengagement) and corrective actions that
companies (e.g. technological support) and institutions (e.g. regulatory support) could adopt during the customer journey. The
results highlight both areas of alignment and significant asymmetries between consumer coping strategies and the corrective
actions of other stakeholders. In particular, there is a prevalence
of reactive interventions by companies and a concentration of
institutional policies in the preventive phases, with less attention
paid to managing vulnerability in the post-deception phase. These
discrepancies contribute to amplifying consumers’ coping strategies and hindering the restoration of trust. Overall, the study contributes significantly to advancing the literature on consumer
vulnerability in digital environments, highlighting the need for a
multistakeholder approach in which companies and institutions
operate in a coordinated, targeted and complementary manner
throughout the entire customer journey. From a managerial perspective, the results highlight the importance of developing integrated and proactive protection systems that are capable not only
of mitigating the consequences of digital deception, but also of
preventing its occurrence and limiting the use of coping strategies
Evaluating ChatGPT-generated psychoeducation for mood disorders: comparative insights from patients and mental health professionals
No full textIntroduction: Psychoeducation is a key intervention in mood disorders. With the rise of artificial intelligence (AI) conversational agents, tools like ChatGPT are increasingly consulted by patients. Yet, empirical data on how AIgenerated psychoeducational content is perceived by patients and professionals remain limited.
Methods: In this cross-sectional study, 30 depressed inpatients submitted five open-ended questions to ChatGPT-4o. Responses were rated by patients using 5-point Likert scales for relevance, comprehensibility, usefulness, empathy, and acceptance. Independent safety checks were applied to all outputs. The same responses were later blindly evaluated, in randomized order, by three psychiatrists and three psychiatric rehabilitation technicians (PRTs).
Results: All outputs passed safety review. Patients assigned higher total scores (mean ± SD = 22.43 ± 2.64) than PRTs (17.63 ± 3.39) and psychiatrists (15.42 ± 2.02). The largest gaps involved empathy and acceptance, whereas relevance, usefulness, and comprehensibility differed less. PRT ratings were intermediate: closer to patients on relevance, comprehensibility, and usefulness, but closer to psychiatrists on empathy and acceptance. Within patients, no associations emerged with age, education, depression severity, or prior psychoeducation.
Conclusions: Patients with mood disorders perceived ChatGPT-generated responses as more relevant, comprehensible, useful, accepting, and empathetic than health professionals did. With conversational agents entering psychoeducation, clinicians must develop strategies to critically integrate such tools, ensuring safety and quality while guiding patient use. The challenge is not resisting AI adoption, but framing it within safe, effective, and ethically sound psychoeducational care
Soil Moisture Estimation from Multi-Frequency Synthetic Aperture Radar (SAR) data. Towards an Integrated Agricultural Drought Monitoring Framework
No full textOver the last fifty years, microwave remote sensing has established itself as a key tool for
soil moisture retrieval. In particular, Synthetic Aperture Radar (SAR) is capable of obtaining
high-resolution measurements, which are required by several applications, such as precision
agriculture, hydrological and flood monitoring, and drought forecasting. However, the SAR
backscattered signal is influenced not only by variations in the soil’s dielectric properties, but
also by a range of bio-geophysical factors, including soil roughness, canopy structure, vegetation
biomass, and water content. Presently, SAR-based soil moisture retrievals exhibit higher
uncertainty under dense canopies, steep terrain, and no sensitivity in forest ecosystems. The
use of longer wavelengths is expected to improve soil moisture retrieval on vegetated areas, due
to their penetration capability and thus greater sensitivity to soil properties, yet their limited
availability has so far constrained their application. A new generation of L-band missions, including
NISAR (2025) and ROSE-L (2028), has been designed with soil moisture monitoring as
one of the primary objectives. These will accomplish a global C-band and L-band coverage of
the Earth, posing the challenge of combining asynchronous acquisition in a System-of-Systems
approach, dealing with different configurations and geometries.
The main goal of this thesis is to advance soil moisture retrieval from SAR time series by exploiting
the synergy between C- and L-band observations. The resulting soil moisture estimates
are integrated with eco-hydrological indices to support applications related to drought monitoring
and vegetation productivity. The research is structured around the following topics: (i)
assessing the sensitivity of C- and L-band data for soil moisture monitoring through regressions
and change detection methods; (ii) developing a roughness mitigation approach based on polarimetric
entropy; (iii) quantifying the impact of incidence and azimuth angles on multi-frequency
data; (iv) evaluating the effects of radiometric terrain flattening, masking, and downsampling
on anisotropy effects; (v) developing a framework to integrate C- and L-band soil moisture estimates,
together with Solar-Induced Chlorophyll Fluorescence (SIF) for empirical vegetation
correction; and (vi) assessing eco-hydrological responses to drought with retrieved SM, meteorological
and vegetation indices. The long-term change detection method provided the basis for
these analyses, which were conducted employing SAOCOM and Sentinel-1 SAR systems. The
test areas comprised a region in Spain, characterized by the availability of in-situ soil moisture
data, and the Po Basin, for the variety of land cover and topography conditions, as well as for its
sensitivity to drought events. Overall, the thesis demonstrates that integrated multi-frequency
approaches can advance operational soil moisture retrieval and support applications in water
management, early warning systems, and food security
