Archivio della ricerca della Scuola Superiore Sant'Anna
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Lateralized courtship behavior in Ostrinia furnacalis (Lepidoptera: Crambidae): influence of gender, sexual experience, and its effects on mating success
No full textIn suo esse perseverare: la posizione costituzionale del Re sabaudo fra atrofizzazione e riappropriazione delle prerogative
No full text
Soddisfazione degli infermieri: un'analisi basata sulle evidenze
No full textPer analizzare la soddisfazione degli infermieri in Italia abbiamo condotto una scoping review,
o revisione esplorativa. Questa metodologia è stata scelta per fornire una mappatura
esaustiva della letteratura esistente sui temi della soddisfazione lavorativa, della motivazione,
dell’intenzione di lasciare il lavoro e dell’empowerment tra gli infermieri italiani, identificando
le lacune di ricerca e sintetizzando le evidenze attuali.
La raccolta delle evidenze si è basata sugli studi pubblicati fra il 2020 e 2024 su riveste referate
attraverso la banca dati Scopus. A questi studi sono stati aggiunti altri studi individuati
dagli esperti in management sanitario, e ritenuti rilevanti da rappresentanti FNOPI, sia per
l’ampiezza del campione che per la rilevanza dello studio.
I criteri di individuazione degli studi da letteratura sono stati i seguenti:
• Ambito geografico: Studi condotti in Italia o che includono infermieri che lavorano in
Italia (l’obiettivo è quello di avere evidenze sulla situazione italiana).
• Tipo di pubblicazione: Articoli di ricerca originali pubblicati in riviste peer-review
(sono esclusi editoriali o lettere alle riviste per includere solo evidenze recenti derivanti da
studi descritti nell’articolo).
• Periodo di pubblicazione: Studi pubblicati tra il 2020 e il 2024 (per limitare gli studi
ai dati più recenti, a cui si sono aggiunti articoli, paper e capitoli segnalati da esperti o rappresentanti
FNOPI)
• Popolazione: Infermieri impiegati in strutture sanitarie italiane
• Lingua: Articoli in inglese o italiano.
• Temi: Studi che trattano la soddisfazione lavorativa, la motivazione, l’intenzione di
lasciare il lavoro o la ritenzione degli infermieri che riportino evidenze quantitative.
La revisione integrata da ulteriori studi offre una panoramica sui livelli di soddisfazione e
intenzione di cambiare lavoro. Collateralmente alle informazioni quantitative vengono riportate
le sintesi sui fattori indagati negli studi che influenzano la soddisfazione lavorativa e il
benessere degli infermieri.
Le analisi qui riportate sono esplorative e hanno l’obiettivo di fornire una prima panoramica
di quanto risulta dai dati pubblicati che riguardano le condizioni di lavoro degli infermieri in
Italia. Di 19 studi
Statistical Model Checking of Python Agent-Based Models: An Integration of MultiVeStA and Mesa
Full text linkAgent-based models (ABM) consist of several heterogeneous agents interacting in a complex way, possibly mediated by spatial constraints or other aspects, giving rise to emergent behavior not directly expressed in the model itself. These aspects made ABMs widespread in several areas, including the social sciences. These models are typically too complex to be solved analytically, requiring to use simulation-based analyses. Often, especially in the social sciences, these simulation-based analyses are not automatic, and the number of performed simulations or simulation steps might be arbitrary. This might lead to replicability issues, to low statistical accuracy of the results, or just to wrong results. In computer science, simulation-based analyses can be automated, e.g., using statistical model checking. We present an integration of the statistical model checker MultiVeStA with Mesa, a python-based framework for modeling and analysing ABMs. We validate the integration by using two seminal ABMs from the social sciences. We analyze the famous Boids flock model, able to generate flocking behaviors of birds, with the transient and counterfactual analysis capabilities of MultiVeStA. We analyze the well-known Schelling model, able to generate social segregation behaviors, with the steady-state and ergodicity diagnostics capabilities of MultiVeStA. The contribution of this paper is not methodological. Rather, this is on the one hand a case study paper presenting an application of MultiVeStA. On the other hand, it is a step towards automating and making more reliable the simulation-based analysis of models written in the popular Mesa framework
On the effect of the attention mechanism for automatic welding defects detection based on deep learning
No full textCharacterization of EAF and LF Slags Through an Upgraded Stationary Flowsheet Model of the Electric Steelmaking Route
Full text linkThe current, continuous increase in attention toward preservation of the environment and natural resources is forcing resource-intensive industries like steelworks to investigate new solutions to improve resource efficiency and promote the growth of a circular economy. In this context, electric steelworks, which inherently implement circularity principles, are spending efforts to enhance valorization of their main by-product, namely slags. A reliable characterization of the slag’s composition is crucial for the identification of the best valorization pathway, but, currently, slag monitoring is often discontinuous. Furthermore, in the current period of transformation of steel production, preliminary knowledge of the effect of modifications of operating practices on slags composition is crucial to assessing the viability of these modifications. In this paper, a stationary flowsheet model of the electric steelmaking route is presented; this model enables joint monitoring of
key variables related to process, steel and slags. For the estimation of the content of most compounds in slags, the average relative percentage error is below 20% for most of the considered steel families. Thus, the tool can be considered suitable for scenario analyses supporting slag valorization. Higher performance is achievable by exploiting more reliable data for model tuning. These data can be obtained via novel devices that gather more numerous and representative data on the amount and composition of slags
Socio-geographical factors associated with cardiac rehabilitation participation after percutaneous coronary intervention: a registry-based cohort study from France
No full textAims: Cardiac rehabilitation (CR) after percutaneous coronary intervention (PCI) for acute (ACS) or chronic (CCS) coronary syndrome is underutilised worldwide. The determinants of underuse are not fully understood. Using real-world data, this study explored the effect of socio-geographical factors on CR participation. Methods: Patients from the Aquitaine region (France) who underwent PCI between 2017 and 2019 were selected from a regional PCI register. Their 1-year CR participation was tracked using the French hospital database. Associations between CR participation and socio-geographical factors, (social deprivation, general practitioner accessibility, and distance to the nearest CR centre) were assessed through logistic regression mixed models at 1 and 3 months in ACS, and at 3 and 6 months in CCS. Results: Among the 19,002 patients, 5,073 (26.7%) participated in CR (ACS: 4,071, 33.0%; CCS: 1,002, 15.0%). A CR centre distance >25 km reduced participation at 3 months in ACS patients (OR = 0.83, 95% CI: 0.70-0.99, p = 0,023), but not at 1 month after PCI. CCS patients from most advantaged areas were more likely to participate in CR at 3 (OR = 0.62, 95% CI: 0.44-0.88, p = 0.002) and 6 months (OR = 0.59, 95% CI: 0.42-0.82, p < 0.001). General practitioner accessibility did not affect participation. Conclusion: Post-PCI CR participation was low. Proximity to CR centres promoted participation for ACS patients, while CR usage correlated with higher socio-economic status for CCS patients. These findings highlight socio-geographical inequalities in CR access, providing a basis for targeted interventions, such as telerehabilitation or expanded coverage
Laser‐Induced Graphene from Commercial Inks and Dyes
Full text linkLaser-induced graphene (LIG) has been so far obtained from polymer precursors and proposed for numerous applications, including various types of sensors and energy storage solutions. This study examines a radically different class of new precursors for LIG, distinct from polymers: inks and dyes. The identification of specific organic dyes present in commercial markers demonstrates that the aromatic structure, in conjunction with high thermal stability (residual weight > 20% at 800°C), are key factors for laser-induced pyrolysis. Eosin Y is identified as an excellent LIG precursor, comparable with well-known polyimide. The unique properties of dyes allow for dispersion in various media, such as acrylic binder. A dye concentration of 0.75 mol L−1 in acrylic binder results in a conductivity of 34 ± 20 S cm−1 for LIG. The composition and microstructure of LIG from dyes are thoroughly characterized, revealing peculiar features. A versatile “Paint & Scribe” methodology is introduced, enabling to integrate LIG tracks onto any wettable surface, and in particular onto printed and flexible electronics. A process for obtaining freestanding and transferrable LIG is demonstrated by dissolving acrylic paint in acetone and floating LIG in water. This advancement offers novel avenues for diverse applications that necessitate a transfer process of LIG