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Durante il XV e XVI secolo il plurilinguismo diventa un tema rilevante nei manoscritti che circolano tra le corti e le botteghe di scrittura europee. Il contatto interlinguistico si articola nelle molteplici varietà italo-romanze diffuse nell’Italia e nella Francia medievale e rinascimentale.
Il manoscritto Mscr.Dresd.Oc.56, conservato a Dresda e da collocare nel dibattito cinquecentesco, ospita la traduzione francese del Libro del Cortegiano (1528) di Baldassare Castiglione (1478-1529). Si tratta di una delle più antiche traduzioni francesi dell’opera, realizzata ancora prima della versione a stampa (1537). Nel manoscritto il presunto autore, Jacques Colin (scomparso nel 1547), non funge soltanto da mero traduttore, ma propone anche riflessioni sulla corretta resa di alcuni passi della traduzione, ad esempio a proposito di giochi di parole e modi di dire italiani e francesi.
L’articolo, che prende in esame una selezione di passi tratti dal testo di partenza italiano e dalla sua traduzione francese, adotta una prospettiva filologica e linguistica contrastiva. Il contributo offre inoltre alcune considerazioni sulla riflessione linguistica svolta dal traduttore nell’ambito del processo di produzione del Mscr.Dresd.Oc.56.
Additive Manufacturing (AM), also known as rapid prototyping or 3D printing, is widely used across various industries, including medical products and automotive spare parts. The COVID-19 pandemic has further accelerated its adoption to address supply chain disruptions caused by shortages in production resources and logistics constraints. However, as AM integrates into supply chains, structural changes in nodes and data flows create new challenges in information sharing and data standardization. Ontologies have proven effective in enhancing data interoperability and improving information quality through semantic modeling. Despite this, a comprehensive approach that combines AM and logistics ontologies to address cross-domain challenges remains underexplored. This study develops an ontology-based supply chain model for AM by integrating existing AM and logistics ontologies. Using the Design Science Research Methodology (DSRM), the proposed ontology is constructed and instantiated with a sample dataset for validation. The results provide a foundational framework for improving data management and coordination in AM supply chains.
Additive manufacturing (AM) revolutionises traditional manufacturing by enabling localised, on-demand production, reducing waste, and enhancing design flexibility. The adoption of the AM method also transforms supply chains (SCs) in several perspectives due to, removing and adding some nodes and arcs. While this transformation offers numerous benefits, it also presents significant challenges in configuring an optimal network for AM SCs, especially when a decentralization network is preferable. In this regard, this study investigates using the network optimisation modelling (NOM) method to optimise decentralised AM SCs. Utilising AnyLogistix software, the study models an AM SC to determine the optimal network configuration that minimises costs while ensuring timely deliveries. It explores the advantages of decentralised production, such as reduced lead times and costs. This study contributes to the growing body of literature by addressing gaps related to NOM in AM contexts, providing valuable insights for practical applications in SC management.
Smoking remains a prominent preventable health risk in Germany, creating a need for effective cessation interventions. Digital smoking cessation interventions (DSCIs) present promising support for individuals aiming to quit, yet their utilization and acceptance are not thoroughly understood. This study analyzes usage patterns and acceptance levels of DSCIs among smokers, occasional smokers, and former smokers in Germany, focusing on user behavior, acceptance determinants, and the influence of prescription and reimbursement status. An online questionnaire based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model was administered to participants. Data were collected through recruitment via social media, email lists, counseling groups, and public postings. The responses were analyzed using SPSS. The study included 173 participants (61.85% female, 37.57% male, 0.58% diverse) with an average age of 35.28 years. They reported smoking for an average of 18.21 years and attempting cessation 3.42 times. Among respondents, 41.62% had used DSCIs, predominantly former smokers (54.17%) and women (79.17%), with the “Smoke Free” app being the most utilized intervention. Although 73.05% expressed willingness to (re)use DSCIs, actual usage showed moderate acceptance levels. Significant predictors of acceptance included willingness to pay (p = 0.013), self-efficacy (p = 0.018), and physician prescription with clinical evidence (p = 0.019). The results highlight a rising demand for digital solutions focused on long-term smoking cessation, particularly among middle-aged women, emphasizing the need for a deeper understanding of acceptance drivers and model expansions to address healthcare dynamics.
The digital transformation of healthcare education has accelerated significantly due to the COVID-19 pandemic, shifting traditional, practice-oriented teaching towards digital methodologies. Before the pandemic, digital teaching was minimally adopted and lacked systematic strategies, especially in Germany’s higher education institutions. This study comprised two cross-sectional online surveys among university faculty in public health, nursing, and medicine—conducted in 2020 and 2021—with a total of 238 participants. The surveys explored the use of digital tools, satisfaction with digital teaching, perceived challenges, and expectations for future teaching practices. Digital platforms such as Zoom, Moodle and MS Teams emerged as the most widely used tools, primarily for content delivery rather than interactive or collaborative activities. Faculty reported generally positive experiences and increasing adaptation to digital teaching, though concerns persisted regarding its time demands and limited support for personalized learning and student engagement. Satisfaction with digital teaching grew between the two survey phases, yet remained moderate regarding didactic support and student outcomes. Educational videos and learning management systems were highlighted as favored methodologies. Nonetheless, reservations about reducing attrition rates and supporting disadvantaged learners indicate unresolved challenges. While digital methodologies in healthcare education have gained acceptance, their integration remains shaped by technical considerations rather than didactic innovation. To optimize digital teaching, institutions must provide targeted professional development, define clear frameworks for digital competencies, and implement systematic evaluation processes. The adoption of emerging technologies, including artificial intelligence, necessitates further investment in faculty training and attention to ethical and legal considerations. Comprehensive pedagogical reforms are essential for the sustainable advancement of digital education in healthcare.
