Search Results (9,590)

Tsunami fragility modeling plays a central role in probabilistic coastal risk assessment; however, representing structural vulnerability under near-field tsunami conditions remains challenging due to complex hydrodynamic loading, strong spatial variability, and the presence of pre-existing earthquake damage. This paper advances near-field tsunami fragility modeling through three specific contributions, each bridging simulation-based methods and empirical damage survey observations. First, it demonstrates how a successive earthquake–tsunami simulation framework can generate conditional fragility surfaces that explicitly account for pre-existing seismic damage without relying on statistically intractable probabilistic decompositions. Second, it develops and validates a distance-dependent intensity-shifting approach—derived from analysis of the 2011 Great East Japan tsunami survey dataset—that adapts baseline fragility curves to near-field and near-coast conditions in a physically interpretable and practically deployable manner. Third, it establishes an explicit cross-validation pathway between simulation-derived fragility surfaces and empirical damage observations through machine-learning-assisted feature importance analysis, a connection largely absent from prior literature. Together, these contributions provide a physically consistent and data-informed foundation for near-field tsunami fragility modeling that is directly applicable—as a methodological framework—to loss and resilience estimation platforms such as IN-CORE and HAZUS and to risk-informed coastal infrastructure design in subduction-zone regions, subject to typology-specific calibration; the simulation results are demonstrated for a US Reinforced Concrete (RC) moment-frame archetype and the empirical results for Japanese wood-frame construction, so direct quantitative application to other structural typologies requires recalibration of the respective model components. Full article

Reliable rainfall information is fundamental for climate-risk analysis and operational monitoring in Mediterranean regions such as Apulia (Southern Italy), one of the areas most affected by climate change-driven shifts in rainfall patterns. Recent evaluations across Italy and comparable Mediterranean settings consistently show that gridded precipitation performance is highly dependent on orography and dataset typology: reanalyses often provide the best overall agreement with gauges, while satellite and blended products can exhibit larger biases, with persistent challenges in complex terrain and for high-intensity events. In this context—and given the documented spatial heterogeneity of rainfall extremes within Apulia—validation of such gridded datasets with respect to ground observations remains essential for early warning and climatological applications. In the present work, we evaluate four widely used precipitation products—CHIRPS-v2, the newly released CHIRPS-v3, IMERG, and ERA5—benchmarking them against the Apulia region Civil Protection rain-gauge network. We provide diagnostics aligned with early warning and climate monitoring: bias and error statistics, rainfall intensity distributions, and dry spell duration. A key contribution is, to our knowledge, the first dedicated validation of CHIRPS-v3 in Apulia, which is timely given that CHIRPS-v3 was explicitly developed to address shortcomings such as underestimated temporal variance and to leverage expanded station inputs. The results indicate that CHIRPS-v3 yields systematic improvements over CHIRPS-v2 across multiple metrics, while ERA5 generally shows the strongest overall agreement with gauges—consistent with broader Italian evidence. Full article

The resurgence of trade policy interventions in the global economy has renewed interest in the long-run macroeconomic implications of commercial barriers. While previous research has largely focused on the short-term effects of tariff reforms and trade liberalization, relatively less attention has been paid to the persistence of trade policy regimes over time. This study addresses this gap by analysing the relationship between trade policy persistence—proxied by the trajectory of the Nominal Average Tariff (NAT)—and Peru’s real GDP during the period 1980–2025. Using a Johansen cointegration framework combined with a Vector Error Correction Model (VECM), the study evaluates both the existence of a long-run equilibrium relationship and the dynamics of adjustment following deviations from that equilibrium. The econometric evidence confirms the existence of a stable long-run relationship between the NAT and aggregate GDP. The normalized cointegrating vector suggests that higher and persistent levels of tariff protection are associated with lower levels of real GDP in the long run. The estimated error-correction mechanism further indicates that deviations from equilibrium are gradually corrected through adjustments in the trajectory of real GDP, whereas the tariff equation does not exhibit a statistically significant adjustment process at conventional levels. This asymmetric structure suggests that trade policy persistence operates as a relatively stable macroeconomic condition, while aggregate GDP gradually adjusts to long-run disequilibria. By framing tariffs not only as policy instruments but also as indicators of persistent policy orientations, the study contributes to the trade and growth literature from a persistence-based perspective. The findings additionally highlight the potential relevance of policy consistency and predictability in small open economies characterized by high external dependence and prolonged processes of trade liberalization. Full article

The operational integration of renewable energy into contemporary power systems requires accurate and dependable wind power forecasting, particularly in multi-site settings with nonlinear temporal dynamics, inter-site dependence, and forecast uncertainty. Static site conditioning, conditional variable selection, dynamic graph learning, encoder–decoder temporal fusion, interpretable temporal attention, quantile regression, and post hoc split conformal calibration are all combined in this work to create DG-TFT-CQR, a global multi-site historical-power-based probabilistic forecasting framework. A representative eight-site subset of the AEMO 5 Minute Wind Power benchmark was used to evaluate the model under four different forecasting settings: H1, H3, H6, and H12. The proposed model demonstrated the most balanced probabilistic behavior and the strongest overall point-forecasting performance over these horizons among the compared baselines. The MAE/RMSE/R² values for the point-forecasting results were 0.025490/0.043186/0.980096 at H1, 0.037241/0.062569/0.958221 at H3, 0.047917/0.079747/0.932133 at H6, and 0.062891/0.102751/0.887340 at H12. Additionally, the model preserved competitive interval sharpness while maintaining empirical coverage near the nominal 90% target. DG-TFT-CQR is the most robust balanced framework, with particularly evident advantages at H1 and H12, according to ablation, site-wise, daily case, statistical, and complexity analyses. In pairwise comparisons, H3 and H6 correspond to more mixed regimes. All things considered, the suggested approach offers a reliable and practically significant solution for multi-site wind power forecasting that takes uncertainty into account. Full article

Vertebral fractures are among the most common skeletal injuries and present significant clinical and biomechanical challenges, particularly in older adults and individuals with low bone density. Accurate prediction of vertebral mechanical response and failure under varying loading conditions is essential for improving understanding of spinal injury mechanisms. This study develops a density-dependent viscoelastic analytical model to predict the stiffness and fracture force of human vertebral specimens subjected to different compression rates. The vertebral body is represented as a composite structure consisting of a cortical shell and a trabecular core. Cortical bone is modeled as a linear elastic material, whereas trabecular bone is described using a Kelvin–Voigt viscoelastic formulation. Density-dependent constitutive relationships are incorporated for the elastic modulus and viscous coefficient of trabecular bone. Unknown material parameters are identified through optimization using the Nelder–Mead algorithm, based on experimental compression data from cadaveric vertebral specimens tested under quasi-static and dynamic loading conditions. The calibrated model reproduced the overall trend of specimen-to-specimen mechanical variation observed experimentally. Predicted stiffness values were in reasonable agreement with measured data. Fracture force predictions showed moderate agreement for dynamically tested specimens (R² = 0.60), which improved to R² = 0.88 after exclusion of one statistically identified outlier. Compared with a purely linear elastic formulation, the proposed viscoelastic model demonstrated modest improvement in stiffness prediction and more substantial improvement in fracture force prediction. These findings indicate that incorporating density-dependent viscoelastic effects improves representation of vertebral mechanical behavior, particularly at higher loading rates. Owing to its simplicity and computational efficiency, the proposed model requires only limited imaging input and may be useful for future biomechanical investigations, rapid screening, and injury risk prediction. Full article

This study examines the relationship between financial inclusion and economic development in the European Union by analyzing its macroeconomic determinants across 26 countries over the period of 2004–2023. Using a balanced panel dataset, the empirical analysis employs econometric techniques that account for heterogeneity, autocorrelation, and cross-sectional dependence, leading to the estimation of a Panel-Corrected Standard Errors (PCSE) model. Financial inclusion is proxied by the number of automated teller machines per 100,000 adults, while the explanatory variables include GDP per capita, personal remittances, inflation, years of schooling, unemployment, and foreign direct investment. The results show that GDP per capita, remittances, inflation, and unemployment have a positive and statistically significant effect on financial inclusion, whereas education and foreign direct investment exhibit a negative and significant relationship. These findings suggest that financial inclusion in the European Union is shaped by a complex interplay of economic development, labor market conditions, and external financial flows, rather than by structural factors alone. Notably, the results reveal counterintuitive relationships that challenge conventional assumptions about the roles of education and foreign investment in promoting financial access. This study contributes to the literature by providing updated panel evidence for advanced economies and by emphasizing the multidimensional nature of financial inclusion in a context of increasing digitalization and economic integration. The findings also offer relevant policy implications, suggesting that strategies to enhance financial inclusion should go beyond expanding financial infrastructure and instead focus on improving the effective use of financial services, strengthening financial capabilities, and reducing structural disparities across countries. Full article

Synthetic food dyes represent an important category of chemical contaminants with potential phytotoxic, genotoxic, and ecotoxic effects on living organisms and natural ecosystems. The present study aimed to evaluate the physiological effects induced by three commercial food dyes on the model organism Allium cepa, using the Allium test under hydroponic conditions. A total of 105 bulbs were exposed for 48 h to two different concentrations of each dye, for which gravimetric and physiological parameters, such as biomass, water content, mineral and organic composition, growth inhibition index, tolerance index, and relative growth rate, were subsequently analyzed. Statistical analyses revealed significant differences between batches for all evaluated parameters, indicating effects mainly dependent on the type of dye applied. The results suggest that exposure to synthetic food dyes causes disturbances in water balance, biomass accumulation and mineral homeostasis, confirming the phytotoxic potential of these compounds and the utility of the Allium test in the biomonitoring of chemical contaminants. Full article

This research examines the impact of multiple-choice question (MCQ) sequencing—forward (instructional order) versus randomized—on undergraduate student performance in education courses. Grounded in cognitive perspectives on memory organization and retrieval, the study investigates whether question order influences test outcomes. Using a 2 × 2 mixed repeated-measures design across four courses at an Arab Gulf university, data were collected from 212 students who completed two MCQ-based assessments administered under alternating sequencing conditions. Repeated-measures Analysis of Variance (ANOVA) and Analysis of Covariance (ANCOVA) were employed to analyze performance differences while controlling for testing phase and academic achievement (GPA). Results indicated no statistically significant main effects of question order or testing phase, nor any significant interaction between sequencing and testing phase. GPA did not moderate the relationship between sequencing format and performance. However, descriptive trends suggested slightly higher performance under forward sequencing conditions, pointing to the possibility of small or context-dependent sequencing influences. Overall, the study findings indicate that undergraduate students perform similarly across forward and randomized MCQ formats under typical classroom conditions. By integrating within- and between-subject analyses and controlling for individual academic achievement, the study strengthens the methodological evidence base on MCQ sequencing. The findings provide cautious support for the use of randomized sequencing as a fairness-oriented assessment strategy, highlighting the importance of test design features and contextual factors. Future research should examine sequencing effects in high-stakes settings, assessments targeting higher-order cognitive skills, and diverse disciplinary contexts. Full article

Large language models and vision–language models already achieve strong results on reasoning tasks, but their reliability under controlled assessment-style conditions remains insufficiently characterized. This paper presents a benchmark study of multimodal multiple-choice mathematical reasoning using 324 Austrian Mathematical Kangaroo competition problems (2022–2024), including both text-only and diagram-dependent items. We evaluate five state-of-the-art models under a controlled protocol that isolates two factors: input modality and prompt format. We compare a strict short-answer condition requiring a single option label (one_liner) with a structured condition eliciting step-by-step reasoning and an explicit final answer (full) while enforcing deterministic decoding and rule-based answer extraction. Performance is assessed using accuracy, abstention rates, and contest-style scoring, supported by paired and unpaired statistical analyses and a structured error taxonomy. The results show that prompt format is the primary driver of performance: structured prompting yields substantial gains across all the models, particularly on text-only items. In contrast, visual-text problems remain consistently harder, with a robust performance gap that persists across prompting conditions, indicating persistent limitations in visual grounding. Model comparisons are additionally influenced by response strategies, especially abstention behavior under strict output constraints. An error analysis reveals systematic failure modes, including constraint violations, inappropriate strategy selection, and diagram misinterpretation, alongside structured biases in multiple-choice selection under constrained prompting. Overall, the findings demonstrate that measured performance is highly sensitive to the interaction between prompt format and input modality. This underscores the importance of treating prompting, decoding, and answer extraction as integral components of evaluation in assessment-oriented settings, where reliability and reproducibility are central. Full article

Background: Linear growth during childhood is a key indicator of health status and child development, and liquid cow’s milk has been proposed as a potentially relevant dietary component for this outcome. In this systematic review, we aimed to synthesize the available evidence on the association between liquid cow’s milk consumption and linear growth outcomes in infants and children aged 6 months to 12 years. Methods: A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Observational and experimental studies published in peer-reviewed journals, with no language restrictions, were included if they assessed habitual liquid cow’s milk consumption as the main exposure and reported linear growth outcomes such as height, growth velocity, or height-for-age z-scores. Searches were performed in PubMed (MEDLINE) and Scopus from database inception to 15 January 2026. Study selection, data extraction, and risk-of-bias assessment were carried out systematically. Due to methodological heterogeneity among the included studies, results were synthesized narratively. Results: Twelve studies conducted across diverse geographic and socioeconomic contexts were included. Most studies reported positive associations between liquid cow’s milk consumption and indicators of linear growth, including greater height, higher growth velocity, or improved height-for-age z-scores. Experimental studies showed significant increases in linear growth among children who received milk regularly, whereas some observational studies reported non-significant associations or results dependent on statistical adjustment. One study assessing complete cow’s milk exclusion observed deceleration in linear growth. Overall, the risk of bias was predominantly moderate. Conclusions: Habitual consumption of liquid cow’s milk during childhood appears to be predominantly associated with favorable linear growth outcomes, although variability exists according to study design, age at exposure, milk type, and exposure assessment. Further research using more robust designs is warranted to clarify the magnitude of the association, potential mechanisms, and implications for weight-related outcomes. Full article

Air entrainment in self-compacting concrete (SCC) is governed by coupled interactions between chemical admixtures, empirical workability behaviour, aggregate-skeleton geometry and early air-bubble stability. In highly flowable mixtures, the hardened air-void system cannot be assessed reliably from total air content alone because bubble escape, redistribution and coalescence in the fresh state may change the final pore structure. This study evaluates the link between early fresh-air retention and hardened air-void characteristics in 25 SCC mixtures arranged according to a five-level Graeco-Latin square design. The analysed factors were air-entraining admixture (AEA) dosage (0.00–0.20% by mass of cement), binder type, water-to-binder ratio (0.29–0.41) and the volumetric paste-to-aggregate filling parameter φ (1.1–1.5). The aggregate skeleton was kept constant to separate paste-composition and volumetric-filling effects from aggregate grading. Fresh concrete was characterised by slump-flow diameter, T₅₀ flow time, density and air content after 5 and 15 min; these quantities were treated as empirical workability and early-retention indicators, not as direct rheological parameters. Hardened concrete was examined after 28 days according to EN 480-11 using total hardened air content A, spacing factor L, micropore content A₃₀₀ and specific surface α. The slump-flow diameter ranged from 50 to 79 cm, fresh air content after 5 min from 1.6% to 8.6%, air loss between 5 and 15 min from 0.41 to 1.12 percentage points, hardened air content from 1.20% to 8.59%, and spacing factor from 0.13 to 0.44 mm. Strong correlations were obtained between fresh and hardened air contents (A₅ vs. A: r = 0.920, R² = 0.846, p < 0.001, 95% CI for r: 0.824–0.964; A₁₅ vs. A: r = 0.922, R² = 0.849, p < 0.001, 95% CI for r: 0.828–0.965), while hardened air content was strongly and inversely related to spacing factor (A vs. L: r = −0.907, R² = 0.822, p < 0.001, 95% CI for r: −0.958 to −0.797). The recalculated ANOVA showed that statistical significance was response-dependent: w/b was significant for early air loss ΔA (F = 4.190, p = 0.040, partial η² = 0.677) and micropore content A₃₀₀ (F = 4.058, p = 0.044, partial η² = 0.670), whereas binder type showed near-threshold tendencies for fresh and hardened air contents. No single factor was statistically significant for all air-void descriptors. The SDI-based approach is therefore presented as a bounded explanatory framework, not as an externally validated prediction model. Direct durability claims, including freeze–thaw resistance, require separate experimental verification. Full article

We present a novel method for deriving radially resolved dynamical chronometers from galaxy rotation curves, allowing galaxy assembly histories to be reconstructed directly from kinematic data. In the Nexus Paradigm, the baryonic Tully–Fisher relation is used to estimate the dynamical mass profile. We compare this profile with independently derived intrinsic baryonic mass distributions obtained from stellar Sérsic fits and gas surface-density measurement yields. This yields a radial ratio that maps to formation redshift with radial resolution. Inverting this ratio within a standard cosmological framework produces a radial lookback-time profile, representing the time since each radial shell last experienced dynamical reconfiguration. Applying the method to a pilot sample of seven SPARC galaxies, including both high- and low-surface-brightness systems as well as the Milky Way, reveals diverse age structures: stratified profiles associated with inside-out growth and flatter profiles consistent with coherent disk assembly. The method requires no dark-matter halo fitting and offers a kinematic chronometer that complements stellar population and chemical evolution approaches. The NP rotation-curve parameters were determined by minimizing the chi-squared statistic between the observed and predicted velocities using a two-stage optimization consisting of a global differential-evolution search followed by nonlinear least-squares refinement. Observational uncertainties were taken from the published rotation-curve data, supplemented by a 5 km s⁻¹ systematic error floor added in quadrature to account for non-circular motions and other unresolved systematics. We also show that the governing dynamical equation admits a gravitoelectromagnetic interpretation, in which a velocity-dependent term generates disk-wide torques that regulate angular momentum transport. This leads to a unified stability framework in which galaxy morphology emerges from a single parameter regime: balanced conditions favor a coherent spiral structure, whereas dynamically hot regimes naturally produce diffuse and ultra-faint systems. The cosmological scaling of the effective gravitomagnetic field further suggests that the spiral structure is partly regulated by cosmic time. Although the inferred ages depend on the accuracy of the baryonic mass reconstruction and on the local validity of the evolving baryonic Tully–Fisher relation, our results show that rotation curves encode time-resolved dynamical information. This establishes the radial dynamical chronometer as a new observable for studying galaxy evolution and testing gravitational frameworks. Full article

The increasing adoption of virtual reality for industrial tasks such as virtual assembly, inspection, and operator training necessitates a standardized approach for evaluating and selecting appropriate hardware. This paper addresses this need by introducing a comprehensive methodology to assess the usability of commercially widespread virtual reality headsets specifically for industrial applications with hand-held controllers. We conducted a large-scale comparative study involving five leading headsets (HTC VIVE Pro 1 and 2, HTC VIVE XR Elite, Meta Quest Pro, and Meta Quest 3) and 60 demographically balanced participants. The evaluation was based on a protocol of 15 distinct tasks designed to measure performance in near and far-field object manipulation, interaction fidelity, visual clarity, ergonomics, and long-term comfort. By combining quantitative Key Performance Indicators with subjective user feedback and rigorous inferential statistical analysis, our findings reveal significant performance disparities among the devices. The results demonstrate that, while certain headsets excel in high-precision tracking for assembly tasks, others offer superior comfort, visual quality, and ease of use for inspection and prolonged sessions. Ultimately, this study concludes that no single headset is universally superior; the optimal choice is highly task-dependent. The proposed methodology provides a robust, evidence-based framework to guide industries in making informed virtual reality hardware selections tailored to their specific needs. Full article

Sodium hypochlorite (NaOCl) remains the gold standard irrigant in endodontics due to its proteolytic and antimicrobial properties, whereas hydrogen peroxide (HP) is widely used for internal bleaching because of its oxidative capacity. Both agents have been associated with chemical and structural alterations in dentin; however, the impact of their sequential application on the organic–mineral balance has not been fully elucidated. Objective: To evaluate whether the isolated and sequential application of 5.25% NaOCl and 37.5% HP induces chemical alterations in dentin by analyzing changes in the organic matrix and mineral phase using Fourier-transform infrared spectroscopy (FTIR) and Energy-dispersive X-ray spectroscopy (EDX). Methods: Twenty-four independent dentin sections (n = 6 per group) from six human third molars were distributed using a tooth-balanced allocation into four groups: Control, NaOCl (5.25%, 15 min), HP (37.5%, 30 min), and sequential NaOCl+HP. FTIR assessed organic (amide I, II, III, CH₂) and inorganic (phosphate, carbonate) components through baseline-corrected integrated areas, Full Width at Half Maximum (FWHM), and molecular ratios. Surface elemental composition and the calculated Ca/P atomic ratio were determined by EDX. Multiple sub-measurements per specimen were averaged before statistical analysis. Data were analyzed using Kruskal–Wallis and Mann–Whitney U tests with Bonferroni correction (p < 0.05). Results: FTIR revealed treatment-dependent modifications. NaOCl reduced absorbance in organic-associated bands, indicating collagen degradation, whereas HP altered the mineral phase. The NaOCl+HP group exhibited increased numerical values for integrated band areas, with differences detected in carbonate, phosphate, and amide III bands (p < 0.05), reflecting structural disorganization and modified spectral signal rather than tissue preservation. No differences were detected across the calculated infrared ratios (p > 0.05). EDX showed decreased absolute atomic percentages of Ca, P, and O in the NaOCl+HP group (p < 0.05), indicating structural demineralization, while its stoichiometric Ca/P ratio remained at 1.56. Isolated HP shifted the mineral stoichiometry to the highest numerical Ca/P ratio (1.69; range 1.58–1.80). Fluorine decreased across all treated groups (p < 0.001). Conclusions: Sequential NaOCl and HP application triggers distinct chemical alterations compared to individual treatments, inducing severe structural disorganization of the organic network and absolute mineral depletion of Ca and P. This multi-agent sequence alters dentin stoichiometry, which may compromise the biomechanical integrity of the tissue. Full article

Background/Objectives: Nabiximols, a standardized extract of Cannabis sativa, has been approved as an add-on therapy for patients with moderate to severe spasticity associated with multiple sclerosis (MS). Moreover, current Italian treatment algorithms suggest that cannabis-based therapies may have further relevance in the management of MS. The aim of our systematic review and meta-analysis was to assess the effectiveness of nabiximols in relieving symptoms other than spasticity in adult MS patients. Methods: A systematic search was conducted in Web of Science, MEDLINE (via PubMed), Cochrane CENTRAL and Embase on September 10, 2025. Study selection was performed according to the predefined PROSPERO protocol (CRD42022329952). Data were combined into a common denominator and examined using a random-effects model with meta-regression expressed as mean difference (MD) and a 95% confidence interval (CI). Risk of bias was assessed using the Cochrane risk of bias instrument (RoB2) and the Risk Of Bias In Non-randomized Studies of Interventions (ROBINS-I) tool. Results: Of the 49 eligible articles, 25 were included in the statistical analysis (2949 patients). Significant improvements in spasm quality (MD = −16.87; 95% CI = (−29.75)–(−3.99)), bladder function (MD = −16.38; 95% CI = (−22.18)–(−10.58)), sleep disruption (MD = −15.75; 95% CI = (−22.02)–(−9.49)) and gait function (timed walk MD(s) = −5.31; 95% CI(s) = (−9.88)–(−0.74)) were observed. Time-dependency was not significant. The subject global impression of change (SGIC) improved significantly after the first month (odds ratio (OR) = 1.69; 95% CI = (1.30)–(2.18)). Conclusion: Beyond spasticity, nabiximols may represent a signal of benefit for bladder function, sleep disruption, spasm quality, and gait function in MS, in line with the “spasticity-plus” concept. However, the evidence certainty was low to very low, and these findings should be considered exploratory. Full article