Parthenope University of Naples
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Digital Tactility and Embodied Learning: Rethinking Educational Interfaces in the Post-Digital Classroom
No full textResponsabilità sostenibile e qualità della prestazione professionale. Evoluzione del sistema e attualità della funzione notarile
No full textObservation of Collider Neutrinos without Final State Muons with the SND@LHC Experiment
No full textWe report the observation of neutrino interactions without final state muons at the LHC, with a significance of 6.4σ. A dataset of proton-proton collisions at sqrt[s]=13.6 TeV collected by SND@LHC in 2022 and 2023 is used, corresponding to an integrated luminosity of 68.6 fb^{-1}. Neutrino interactions without a reconstructed muon are selected, resulting in an event sample consisting mainly of neutral-current and electron neutrino charged-current interactions in the detector. After selection cuts, 9 neutrino interaction candidate events are observed with an estimated background of 0.32 events
Review of Knisely & Russell (2024): Redoing Linguistic Worlds: Unmaking Gender Binaries, Remaking Gender Pluralities
No full textPrefazione a "Sperimentare percorsi di educazione sentimentale per l’affettività, la sessualità ed il genere. Una raccolta di buone prassi da esperienze vissute"
No full textL’oggetto di indagine sono gli studi sul Genere e sull’Orientamento sessuale
ma con modalità decisamente inedite o quantomeno non adeguatamente utilizzate in ricerca educativa. Il testo si nutre di storie, analisi di casi di letteratura e cronaca, dati di ricerca raccolti in numerose esperienze formative e di territorio sul tema. L’obiettivo dell’autore è utilizzare i dati raccolti per inferire, raccontare, esplorare la trama più significativa della dimensione formativa degli studi sul genere, anche con riferimento all’educazione affettivo-sentimentale a scuola, recentemente oggetto di numerosi dibattiti, anche estremamente divisivi, nell’ambito delle “Nuove Indicazioni Nazionali per la Scuola 2025”
A GPU-CUDA Numerical Algorithm for Solving a Biological Model
No full textTumor angiogenesis models based on coupled nonlinear parabolic partial differential equations require solving stiff systems where explicit time-stepping methods impose severe stability constraints on the time step size. Implicit–Explicit (IMEX) schemes relax this constraint by treating diffusion terms implicitly and reaction–chemotaxis terms explicitly, reducing each time step to a single linear system solution. However, standard Gaussian elimination with partial pivoting exhibits cubic complexity in the number of spatial grid points, dominating computational cost for realistic discretizations in the range of 400–800 grid points. This work presents a CUDA-based parallel algorithm that accelerates the IMEX scheme through GPU implementation of three core computational kernels: pivot finding via atomic operations on double-precision floating-point values, row swapping with coalesced memory access patterns, and elimination updates using optimized two-dimensional thread grids. Performance measurements on an NVIDIA H100 GPU demonstrate speedup factors, achieving speedup factors from 3.5× to 113× across spatial discretizations spanning (Formula presented.) grid points relative to sequential CPU execution, approaching 94.2% of the theoretical maximum speedup predicted by Amdahl’s law. Numerical validation confirms that GPU and CPU solutions agree to within twelve digits of precision over extended time integration, with conservation properties preserved to machine precision. Performance analysis reveals that the elimination kernel accounts for nearly 90% of total execution time, justifying the focus on GPU parallelization of this component. The method enables parameter studies requiring (Formula presented.) PDE solves, previously computationally prohibitive, facilitating model-driven investigation of anti-angiogenic therapy design
Investigating Neophobia Towards New Food Technologies in Italy: The CoNF&TTI Cross-Sectional Study
No full text: Background/Objectives: Food technology neophobia (FTN), defined as the reluctance to accept or consume foods produced with novel or emerging food technologies, represents a psychological barrier to the adoption of sustainable and innovative dietary practices. This cross-sectional study investigated the prevalence of food technology neophobia and its associated factors among Italian university students. Methods: A total of 1788 undergraduates from 13 universities completed a validated online questionnaire between February and October 2024. The instrument included the Food Technology Neophobia Scale (FTNS), environmental attitude items, and demographic and dietary questions. Results: The mean FTNS score was 51.2 ± 14.0, suggesting moderate levels of neophobia. Multivariate logistic regression identified several factors inversely associated with neophobia: male gender (OR = 0.73, p = 0.003), paternal university education (OR = 0.73, p = 0.024), studying in Northern Italy (OR = 0.64, p < 0.001), dietary supplement use (OR = 0.74, p = 0.003), and pro-environmental attitudes (OR = 0.97, p < 0.001). Conversely, being a commuter student was associated with increased neophobia (OR = 1.29, p = 0.031). Conclusions: These findings highlight the influence of socio-demographic, behavioral, and attitudinal factors on the acceptance of new food technologies. Tailored strategies are recommended to address FTN in specific subgroups, particularly among female, commuter, and Southern Italian students, to enhance receptivity to food innovation and support sustainable dietary transitions
