This paper applies Roland Barthes' theory of myth to overtourism, arguing that the term naturalizes historically contingent tourism problems. Without denying the reality of congestion, environmental degradation, or resident dissatisfaction, it traces how overtourism is constructed through media discourse, governance, and tourism development. Drawing on Barthesian semiology, the paper shows how complex political and economic processes are reframed as the apparently self-evident problem of “too much tourism,” whether excess is identified through destination indicators or residents' and tourists’ perceptions. It argues that overtourism can obscure competing explanations and interests while shaping what is measured, blamed, and governed. The paper concludes by treating overtourism itself as an object of critical inquiry rather than a self-evident analytical category.
While cost-benefit frameworks have dominated resident support research, they struggle to explain why governance quality increasingly shapes acceptance. This Research Note introduces the conditional support framework (CSF), which treats resident support as a contingent, revisable stance: granted, withheld, or withdrawn depending on perceived governance quality. Drawing on 74 semi-structured interviews and 14 focus groups (N = 146) with young residents aged 18 to 30 years in Lombardy, Italy, this study examines perceptions of the Milano-Cortina 2026 Winter Olympic Games. Findings reveal that support is contingent on four governance-related conditions: (a) transport readiness, (b) housing fairness, (c) sustainability credibility, and (d) local inclusion. Economic and reputational benefits were widely acknowledged, yet proved insufficient to secure endorsement when governance performance was questioned. By reframing resident support as governance-dependent rather than purely impact-driven, the CSF extends resident attitude research and offers a transferable lens for future research on tourism legitimacy.
We solve the L^p-regularity problem of the Bergman projection of two-dimensional Rudin ball quotients.
Colorimetric solid-state sensors for saline media must retain their chromophores within the sensing phase, remain optically readable, and operate reliably in high-ionic-strength matrices. In this work, PU–DTZ, a polyurethane (PU) coating containing dithizone (DTZ), was deposited on glass slides and coupled to a low-power RGB light-to-frequency (L2F) optoelectronic module housed in a simulated buoy configuration. Rheological analysis showed that DTZ incorporation did not substantially impair the processability of the waterborne PU formulation. Spectroscopic and morphological characterization collectively supported DTZ incorporation and optical activity within the polymer matrix but provided no evidence of covalent bonding between DTZ and PU. In ASTM D1141–98 synthetic seawater, separate single-metal exposures were performed at nominal total concentrations ranging from 5 × 10−8 M to 5 × 10−4 M. After the fixed 24 h exposure period, the lowest tested concentrations showing apparent discrimination from the matrix blank were 5 × 10−6 M for Hg2+ and 5 × 10−5 M for Pb2+, Cd2+, and Ni2+. These values represent protocol-specific operational discrimination thresholds and should not be interpreted as analytically validated LODs. Exploratory PCA was used only to visualize condition-level RGB response patterns and not for predictive classification. The prototype demonstrates the feasibility of coupling a DTZ-loaded PU coating with a compact RGB L2F reader for alarm-level screening in saline media. However, dye leaching, long-term coating stability, response kinetics, mixed-ion selectivity, and ion-specific matrix effects were not assessed. Further work should address lower operational thresholds, replicate-level statistics, calibration, coating reproducibility, and validation in real seawater against reference elemental analysis before quantitative applications.
This work proposes a physiologically interpretable, control-oriented model of glucose–insulin dynamics that explicitly accounts for time-varying insulin sensitivity. The proposed model combines a single-compartment glucose subsystem, two-compartment insulin pharmacokinetics, two-compartment meal absorption, and a dynamic state for insulin sensitivity driven by circadian modulation. Under basal, fasting conditions, the model predicts two basal operating regimes: (i) one in which a constant basal insulin infusion leads to a periodic glucose trajectory, and (ii) one in which a periodic basal insulin infusion is used to maintain a constant basal glucose level. Structural identifiability and sensitivity analyses are used to define a practically estimable parameter subset for personalization. The model is validated both in silico on the commercial UVA/Padova adult cohort and on free-living data from thirteen subjects of the TAILOR/3 study. Compared with a previous control-oriented linear formulation, the proposed model provides improved prediction accuracy, with higher goodness of fit and lower root mean squared error. On clinical data, the improvement holds for every subject over the identification period, while over a two-day open-loop validation horizon the proposed model yields a positive fit on eleven subjects out of thirteen, against nine for the linear benchmark and without ever failing on a subject on which the benchmark remains usable, with performance markedly lower than in silico, as expected given real-life uncertainties. These results indicate that explicitly modeling dynamic insulin sensitivity can improve physiological fidelity and prediction performance, supporting the development of more personalized model-based strategies for automated insulin delivery.
