Search Results (1,254)

Island ecosystems are highly sensitive to climate change and intensive human activities. However, most existing assessments rely on subjective weighting and linear assumptions, which may not capture nonlinear temporal evolution and can be distorted by spatial-scale effects, including extreme density outliers on micro-islands. Focusing on five representative islands in Jiangsu Province, China (2014–2024), this study applies a data-driven evaluation framework. First, we constructed an Island Ecological Quality Index (IEQI) using principal component analysis (PCA) to integrate multidimensional ecological-state variables. Second, to reduce sensitivity to selected scale-related extremes in spatially restricted units, we employed a geographical detector model to identify explanatory factors and characterize interactive associations. The IEQI showed a nonlinear temporal trajectory, with fluctuations followed by recovery and stabilization after 2021. Under the robust adaptive Jenks classification, the factor detector showed high relative explanatory power for Artificial Shoreline Ratio (q = 0.8457), Population Density (q = 0.8339), Terrain Index (q = 0.8135), Tourist Density (q = 0.6282), and Built-up Ratio (q = 0.3189). Interaction analysis identified bi-factor enhancement between Terrain Index and Population Density (q = 0.8364) and nonlinear enhancement between Policy Count and Built-up Ratio (q = 0.6424). These q statistics describe spatial explanatory associations rather than causal effects. These findings challenge linear and generalized coastal management paradigms. We propose a “one island, one policy” framework that explicitly distinguishes micro-islands by their topographic buffering capacity and anthropogenic pressure profiles, enabling spatially targeted conservation and restoration strategies. Full article

The stable boundary layer (SBL) over land exhibits pronounced vertical decoupling and structural heterogeneity that remain challenging to diagnose using routine operational monitoring. Here, we utilize a three-year continuous multi-level tower dataset ($N=\mathrm{40,630}$ quality-controlled 15-min records at 2, 10, 20, and 50 m) over the Horqin Grassland to characterize stability-dependent modifications of surface-layer wind structure and near-surface kinetic energy. Using the bulk Richardson number ($R{i}_b$) and raw thermal gradients ($\Delta T_v/\Delta z$), we identify a stability-driven reduction in vertical wind coupling, with a statistical change-point cluster centered near $R{i}_b\approx 0.30$ (95% CI: 0.09–0.52). Cross-level correlation analysis empirically localizes a structural transition zone to the 10–20 m interval, separating a faster, shear-driven upper layer from a dynamically suppressed near-surface flow under strong stability. Concurrently, near-surface horizontal kinetic energy ($HK{E}_{02}$) undergoes a 47% (nighttime) to 55% (full-record) median reduction, while horizontal wind-direction variability (${\sigma }_{\theta \_02}$) broadens due to low-wind meandering, and sub-hourly vertical velocity variance (${\sigma }_{w,\mathrm{LF}}^2$) is suppressed by 57–72% across all heights. Multidimensional scaling (MDS) reveals a statistically significant phase-space compaction under high stability (${\tilde{d}}_{\mathrm{high}}=2.13$ vs. ${\tilde{d}}_{\mathrm{low}}=2.67$, $p<0.001$), with adjusted odds ratios highlighting thermal gradient ($\mathrm{OR}=5.80$), wind shear ($\mathrm{OR}=1.52$), and directional variability ($\mathrm{OR}=1.34$) as dominant positive predictors. These empirical patterns remain robust under temporal-holdout validation (Year-1 calibration vs. Years 2–3 validation; consensus breakpoint $R{i}_b=0.161$ vs. $0.156$) and seasonal/wind-speed stratifications. The results demonstrate that routine 15-min multi-level tower networks provide valuable observational constraints on surface-layer structural transitions, informing boundary-layer parameterizations in numerical weather prediction models and near-surface dispersion assessments. Full article

Situated between the Altyn Tagh and Eastern Kunlun ranges, the western Qaidam Basin records Cenozoic sediment-routing changes associated with the growth of the northern Tibetan Plateau. However, the provenance of post-Miocene strata in this region remains debated, and the role of sediment recycling has not yet been quantitatively constrained. Here, we integrate field observations, sandstone petrography, quantitative detrital zircon U-Pb analysis, and inverse Monte Carlo modeling to compare Late Cenozoic strata in the Qigequan area with nearby Mesozoic strata and basement sources in the Altyn Tagh and Eastern Kunlun ranges, thereby assessing direct versus recycled sediment supply. Sandstones of the Qigequan and Shizigou formations are poorly sorted and contain angular to subangular quartz and feldspar grains and identifiable sandstone and mudstone lithic fragments, indicating erosion of pre-existing sedimentary rocks. Their detrital zircon age spectra are dominated by 300–600 Ma grains (57.9%–69.0%), followed by subordinate < 300 Ma grains (18.4%–21.1%) and minor 600–1000 Ma (6.9%–13.2%), 1000–1500 Ma (1.3%–3.9%), and >1500 Ma (1.3%–3.9%) components. Similarity metrics and multidimensional scaling (MDS) analyses show that the Cenozoic age distributions are substantially more similar to the composite Mesozoic proxy than to the Altyn Tagh or Eastern Kunlun basement endmembers. Inverse Monte Carlo modeling further shows that a three-endmember model incorporating the composite Mesozoic proxy provides a better fit than the two-endmember Altyn Tagh–Eastern Kunlun model. Across the three optimization metrics, the composite Mesozoic proxy contributes approximately 36%–68% and 61%–72% to the modeled detrital zircon age distributions of the Shizigou and Qigequan formations, respectively. Together, these results support a substantial role for recycled Mesozoic material in the Late Cenozoic sediment-routing system of the western Qaidam Basin, providing new provenance constraints on basin–range coupling along the northwestern margin of the Tibetan Plateau. Full article

Background: Prostate cancer is one of the most commonly diagnosed cancers in men. Robot-assisted radical prostatectomy (RARP) is one of the recommended surgical treatment options; however, knowledge regarding changes in illness acceptance, psychological adjustment, and quality of life after surgery remains limited. Objective: To evaluate changes in illness acceptance, psychological adjustment, and quality of life in patients undergoing RARP. Materials and Methods: A total of 150 patients diagnosed with prostate cancer and scheduled for RARP were enrolled. Longitudinal analysis was performed in 93 patients who completed both study assessments. Evaluations were conducted before surgery and 3–4 months postoperatively using a self-developed questionnaire, the Acceptance of Illness Scale (AIS), the Mini-Mental Adjustment to Cancer (Mini-MAC), the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30), and the prostate cancer-specific module (EORTC QLQ-PR25). Results: Following RARP, illness acceptance did not change significantly after Holm adjustment (p_Holm = 0.465). Psychological adjustment showed an adverse postoperative pattern, characterised by increased anxious preoccupation, helplessness–hopelessness, and destructive style, together with reduced fighting spirit and constructive style. After adjustment across 25 paired outcome comparisons, significant increases remained in emotional and cognitive functioning scores, while constipation and diarrhoea decreased significantly. Sexual activity also decreased significantly after surgery. Among participants who completed both assessments, incontinence-aid use increased from 15/93 (16.1%) before surgery to 38/93 (40.9%) at follow-up (exact two-sided McNemar test, p < 0.001). Conclusions: During the early postoperative period following RARP, favourable changes were observed in selected quality-of-life scores, whereas illness acceptance did not change significantly after adjustment for multiple comparisons. At the same time, psychological adjustment showed an adverse pattern, characterised by reduced fighting spirit and constructive style together with increased anxious preoccupation, helplessness–hopelessness, and destructive style. Decreased sexual activity and increased incontinence-aid use further illustrate the multidimensional nature of early postoperative recovery. These exploratory findings indicate that favourable changes in selected quality-of-life outcomes do not necessarily coincide with improved psychological adaptation and support the inclusion of psycho-oncological assessment and support in postoperative care. Full article

Hearing aid technology adaptation and user satisfaction are influenced by multiple interacting demographic, clinical, and behavioral factors, making reliable prediction of outcomes challenging with conventional statistical approaches alone. This study proposes an explainable machine learning framework to investigate the multidimensional determinants of hearing aid satisfaction by integrating demographic characteristics, hearing aid-related variables, and patient-reported outcomes obtained from the Hearing Aid Technology Adaptation and Satisfaction Scale (HATASS). Five regression algorithms—Linear Regression, Decision Tree Regression (DTR), Random Forest Regression (RFR), Support Vector Regression, and Gradient Boosting Regression (GBR)—were comparatively evaluated using a five-fold cross-validation strategy. Predictive performance was assessed using the root mean square error (RMSE), mean absolute error (MAE), and the coefficient of determination ($R^2$), while model interpretability was investigated through cross-validated out-of-bag permutation feature importance analysis. Among the evaluated algorithms, Random Forest Regression achieved the most consistent predictive performance, yielding the lowest average RMSE (14.225) and the highest average $R^2$ (0.146) under the adopted validation framework. Although the overall predictive performance remained modest, the explainability analysis consistently identified age as the most influential predictor, followed by onset year, education level, hearing aid usage duration, and daily hearing aid use. In contrast, gender, battery type, tinnitus, and vertigo contributed comparatively less to model predictions. These findings indicate that hearing aid adaptation and satisfaction arise from complex nonlinear interactions among demographic, behavioral, clinical, and device-related characteristics rather than isolated linear associations. The proposed framework provides an interpretable, internally validated analytical approach for investigating hearing aid technology adaptation and satisfaction and establishes a foundation for future studies that integrate comprehensive audiological measurements, longitudinal follow-up data, and independent external validation to support the development of more transparent and personalized hearing healthcare systems. Full article

Background/Objectives: The emotional impact of a cancer diagnosis may become particularly salient during survivorship, as survivors continue to face fears and concerns related to recurrence. Fear of cancer recurrence (FCR) is one of the most prevalent psychological challenges and significant unmet need among women with female cancer. The aim of this study was to assess the presence of FCR in predominantly breast cancer survivors, and to examine its relationship with certain demographic, clinical, and psychosocial factors. Methods: This cross-sectional study was conducted with a convenience sample of 120 women with a history of breast or gynecological cancer who were recruited over a two-month period through several cancer support associations across Croatia. Data were collected in person using a questionnaire comprising sociodemographic and clinical variables, as well as four self-reported instruments: the Fear of Cancer Recurrence Inventory–Short Form, Impact of Event Scale, Cancer Behavior Inventory–Brief Version, and Multidimensional Scale of Perceived Social Support. Data were analyzed using descriptive statistics, Pearson’s correlation coefficient and hierarchical regression analysis. Results: In the final sample of 110 women, FCR levels were moderate, with 66.4% of participants reporting clinically significant levels. FCR was positively associated with chemotherapy (r = 0.22, p < 0.05), intrusive thoughts (r = 0.56, p < 0.01) and avoidance tendencies (r = 0.39, p < 0.01), and negatively associated with age (r = −0.26, p < 0.01) and self-efficacy for coping (r = −0.41, p < 0.01). In the final regression model, intrusive thoughts, coping self-efficacy, and chemotherapy were the only variables independently associated with fear of cancer recurrence. Conclusions: These findings indicate the presence of FCR in the period after primary treatment, particularly among breast cancer survivors, and highlight cognitive processing of cancer-related experiences and self-efficacy as potentially relevant areas for further research. Full article

Artificial intelligence (AI) is now woven into university communication, learning, and administration, exposing students, faculty, and professional staff to scalable cybercrime, social engineering, and personal-data risks. This study tested a Compliance Architecture–Legality–Trust–Vigilance (CALT–V) model in which legal literacy and AI-enabled risk perception act as upstream orientations, trust as a calibration mechanism, vigilance as the proximal behavioral-translation layer, and digital safety behaviors as the outcome. A cross-sectional, role-stratified, non-probability survey of 710 UAE higher-education stakeholders (300 students, 200 faculty members, and 210 administrative/professional staff) measured self-reported legal literacy, objective legal knowledge, AI risk perception, institutional and technology/AI trust, vigilance, digital safety behaviors, and perceived governance conditions. Respondents reported moderate objective legal knowledge alongside moderate-to-high self-reported literacy, risk awareness, trust, vigilance, and safety behavior. Confirmatory factor analysis and structural equation modeling were estimated with subscale-level indicators in IBM SPSS AMOS 29.0 (IBM Corp., Armonk, NY, USA), using maximum-likelihood estimation, complete scale-level cases, and 5000-sample bias-corrected bootstrapping for indirect and total effects. Because the model is multidimensional and the sample is role-balanced but non-probability, the results are read as cautious model-based evidence rather than definitive population evidence. AI risk perception was associated with digital safety behaviors both directly and indirectly through trust and vigilance, whereas trust was linked to safety mainly through vigilance. Legal literacy was associated with trust, but its total association with digital safety behavior was not statistically reliable. Rather than claiming that human oversight is a new idea, the findings specify how trust-with-verification can be operationalized in UAE university cyber-governance through concrete verification, reporting, and incident-escalation routines. Full article

To effectively address the challenges of complex spatiotemporal conflicts, dynamic obstacle avoidance, and coordinated multi-objective optimization in preemptive multi-UAV logistics delivery within complex airspace, this study proposes a Hybrid Improved Multi-Objective Cuckoo Search algorithm (HI-MOCS) for preemptive multi-UAV cooperative logistics scheduling and planning. To overcome the limitations of conventional MOCS, including a low proportion of feasible solutions under complex constraints, susceptibility to local optima, and uneven distribution of multi-objective solution sets, a multi-constraint physical model and a multidimensional evaluation framework are established for preemptive scheduling. A positive knowledge-transfer mechanism based on the co-evolution of primary and auxiliary populations is developed, in which constraint-violation information is used to guide infeasible solutions toward the feasible region. A hybrid heuristic population initialization strategy combining emergency-order priority and spatial scanning rules is introduced to increase the proportion of high-quality feasible solutions in the initial population. In addition, a nonlinear dynamic adaptive parameter-adjustment strategy is designed to balance global exploration and local exploitation, while an iterative truncation-based environmental selection mechanism using the shortest-distance criterion is employed to improve the distribution quality of the Pareto solution set. The experimental results show that, in the benchmark scenario, HI-MOCS achieves an average increase of 33.26% in the total order completion rate and an average reduction of 15.34% in emergency response time compared with 11 multi-objective optimization algorithms, while also exhibiting favorable performance in terms of flight distance per completed order. The fleet-size analysis shows that the 15-UAV configuration achieves the lowest best mean fitness. The safety-distance analysis indicates that, compared with the other safety-distance settings, the 30 m setting increases the total order completion rate by an average of 26.55%, while reducing emergency response time and flight distance per completed order by 27.36% and 33.72%, respectively. The task-scale analysis shows that the 50-order scenario achieves the lowest best mean fitness. Further ablation experiments demonstrate that, compared with the average performance of MOCS and the four single-strategy variants, the complete HI-MOCS improves the total order completion rate by 20.27%, while reducing emergency response time and flight distance per completed order by 20.71% and 36.18%, respectively. The HV, IGD, and Pareto-front results further confirm that the synergistic effects of the four improvement mechanisms effectively enhance the multi-objective optimization performance and the quality of the nondominated solution set. The current study is still validated under simulation conditions assuming reliable GNSS positioning and communication links, without explicitly considering communication delays. Full article

Short ordinal self-report scales are widely used to study children’s digital lives, yet their measurement properties can distort conclusions about nonlinear relationships. We introduced an integrated diagnostic workflow for such scales—covering range, structure, reliability, method variance and functional form—and applied it to the TIMSS 2023 Digital Self-Efficacy scale across all 63 Grade 4 and 47 Grade 8 education-system and benchmarking samples (source database N = 719,881 children; 630,461 with complete seven-item measurement data). The scale was endpoint-concentrated, markedly at Grade 8, losing 83% and 95% of its test information between the mean and two standard deviations above it; an exact marginal calculation from a testlet model gave 80% and 89%. The apparent multidimensionality was better represented as localized covariance among three similarly worded items than as a separable second dimension, and omega hierarchical of 0.79 and 0.83 supported using the total score. In a factorial simulation evaluating the population projection coefficient on the analysis scale, endpoint concentration raised rejection of no curvature from 5.4% to 16.7% with raw summed scores, while latent scoring returned it to 5.5% and raised power from 71% to 88%, whether the item parameters were known or, in a smaller supporting condition, estimated in the analysis sample. Applied to cybervictimization, the quadratic association was attenuated but did not reverse sign once covariates were matched, and its prediction interval included zero. The range and reliability diagnostics behaved similarly on a second scale from the same assessment; broader applicability of the full workflow is proposed on theoretical grounds rather than established here. Full article

Background/Objectives: Multiple chronic conditions (MCCs) are highly prevalent among older adults and require effective collaboration between the patient and caregiver. Mutuality, reflecting the quality of the dyadic relationship, is associated with better self-care and health outcomes. However, the Mutuality Scale (MS) has not been validated on patient–caregiver dyads managing MCCs living in a low–middle-income country (LMIC). Aim: This study seeks to evaluate the structural and convergent validity and reliability of the MS among patient–caregiver dyads managing MCCs living in a LMIC. Methods: A cross-sectional study was conducted on MCC patients and their caregiver recruited from community and outpatient settings. The MS, Self-care of Chronic Illness Inventory (SC-CII) and Caregiver Contribution to self-care Inventory (CC-SCCII) were used for measuring mutuality, patient self-care, and Caregiver Contribution (CC) to patient self-care, respectively. Confirmatory factor analysis (CFA) was performed separately for patients and caregivers to evaluate the original four-factor structure of the MS. Convergent validity was examined through correlations with self-care and CC to patient self-care. Reliability was evaluated using composite reliability and the Global Reliability Index for multidimensional scale. Results: A sample of 406 patient–caregiver dyads was examined. Patients had a mean age of 73.9 (±6.2) years. Caregivers had a mean age of 47.8 (±15.5) years. The four-factor structure was supported in both samples, with acceptable model fit (patients: Comparative Fit Index (CFI) = 0.953 and Root Mean Square Error of Approximation (RMSEA) = 0.078; caregiver CFI = 0.945 and RMSEA = 0.085. The second-order CFA supported a hierarchical structure. Patient and caregiver mutuality scores were strongly correlated (r = 0.778, p < 0.01). Higher mutuality was associated with better patient self-care (r = 0.276–0.479) and CC to self-care (r = 0.174–0.556). Reliability indices ranged from 0.70 to 0.91 for patients and 0.66 to 0.89 for caregivers. Conclusions: The findings support the validity and reliability of the MS for assessing mutuality in patients and their caregivers managing MCCs in an LMIC characterized by limited healthcare resources and formal support. Its use provides empirical support for assessing relationship quality and facilitating dyadic care within this vulnerable population. Future longitudinal studies should evaluate its predictive validity, responsiveness, and measurement invariance across different groups and between patient and caregiver. Full article

Emerging industrial agglomeration drives green transformation through knowledge spillovers and economies of scale. However, its effects exhibit pronounced nonlinearity and heterogeneity, shaped by spatial externalities and development stages. This paper investigates 19 Chinese urban agglomerations over the period 2014 to 2023. Kernel density estimation based on enterprise-level Point-of-Interest (POI) data is used to characterize spatial agglomeration patterns across eight emerging sectors. A two-stage dynamic network super-efficiency SBM model decomposes Green Transition Efficiency (GTE) into resource utilization and pollution control sub-stages. An XGBoost-SHAP-GEO analytical framework, combined with partial dependence analysis, then identifies nonlinear driving mechanisms. The main findings are as follows: First, emerging industrial agglomeration intensifies and polarizes toward the eastern coast, whereas GTE displays a “high-west, low-east” pattern. This produces a significant spatial mismatch, rooted in the near-saturation of environmental carrying capacity in eastern regions, where congestion effects exceed knowledge spillover dividends. Second, geographic characteristics constitute the primary factor shaping GTE and operate through nonlinear interactions with industrial agglomeration and R&D investment. Notably, their moderation direction is reversible, suggesting that geographic endowments should be understood as “conditional assets” rather than fixed advantages. Third, nonlinear patterns across sectors are highly heterogeneous. The bio-industry is the only sector to achieve a J-shaped positive breakthrough. Information technology and new materials exhibit persistent inhibition, while related services display an extremely narrow threshold window with the deepest negative reversal. Thus, “moderate agglomeration” is a multidimensional concept that shifts dynamically with industry type and regional endowment. Fourth, driving mechanisms display stage-dependent evolution. The incubation stage relies on natural endowments and basic industrial pull, with the green bottleneck residing in resource utilization efficiency. The growth stage faces multiple tensions from coexisting positive and negative effects. The optimization stage shifts toward R&D innovation and industrial greening, marking a qualitative transformation from MAR externalities to Jacobs externalities. In addition, the non-significant linear coefficient in the 2SLS instrumental variable test is consistent with the inverted U-shaped nonlinear finding, further validating the necessity of a nonlinear analytical framework. These findings provide differentiated governance evidence for balancing industrial agglomeration with green sustainable development. Full article

Background/Objectives: The transition toward healthier and more sustainable diets has increased the need for reformulated bakery and confectionery products formulated with alternative ingredients. However, validated instruments for assessing consumer acceptance of these products remain limited. This study aimed to develop and psychometrically validate a multidimensional assessment framework integrating food choice motives, green (environmental) values, health consciousness, perceived nutritional value, willingness to pay a premium, and purchase intention. Methods: A cross-sectional survey was conducted among 504 consumers in Romania using an online questionnaire. The instrument was developed by adapting established scales and by developing a new Perceived Nutritional Value scale. Dimensionality was evaluated using exploratory (EFA) and confirmatory (CFA) factor analyses. Temporal stability was assessed in an independent test–retest subsample (n = 30; 14-day interval), and the proposed conceptual model was evaluated using Partial Least Squares Structural Equation Modeling (PLS-SEM) with 5000 bootstrap resamples. Robustness was examined through a sensitivity analysis excluding respondents younger than 18 years (N = 441). Results: EFA (KMO = 0.933) and CFA (CFI = 0.965, TLI = 0.959, RMSEA = 0.061, SRMR = 0.033) supported the proposed six-factor structure. All constructs demonstrated excellent internal consistency (Cronbach’s α: 0.898–0.938), convergent validity (AVE: 0.790–0.889), discriminant validity (HTMT < 0.77), and good-to-excellent test–retest reliability (ICC: 0.82–0.91). Perceived nutritional value was positively and significantly associated with both willingness to pay and purchase intention, and willingness to pay partially mediated the association between perceived nutritional value and purchase intention. The structural model explained 46.1% of the variance in purchase intention; all hypothesized relationships were supported, and the findings remained stable in the sensitivity analysis. Conclusions: The proposed framework demonstrated good psychometric performance and provides a theory-informed measurement framework for assessing consumer acceptance of reformulated bakery and confectionery products. It may support future nutrition research, consumer studies, and the evaluation of food reformulation strategies aimed at promoting healthier and more sustainable dietary choices. Full article

Life skills are cognitive, emotional and social competencies that help adolescents manage everyday demands and participate in school and social contexts. This study aimed to translate, culturally adapt and examine the psychometric properties of the European Portuguese Life Skills Scale (LSS). A cross-sectional methodological study included a convenience sample of 1807 Portuguese adolescents aged 13–19 years from public secondary schools in Central Portugal. The sample was randomly split for exploratory factor analysis (EFA; n = 903) and confirmatory factor analysis (CFA; n = 904). EFA supported an interpretable eight-factor solution explaining 50.7% of the variance. CFA compared the original ten-factor model with the EFA-derived eight-factor model. The ten-factor model showed significant standardised loadings (λ = 0.444–0.849) and comparatively better fit, with acceptable root mean square error of approximation (RMSEA = 0.045) and standardised root mean square residual (SRMR = 0.062), although the comparative fit index (CFI = 0.855) and Tucker–Lewis index (TLI = 0.849) remained below preferred thresholds. Internal consistency was satisfactory to excellent (α = 0.782–0.963; ω = 0.783–0.964). Average variance extracted (AVE) and heterotrait–monotrait ratio (HTMT) analyses provided partial evidence of convergent validity and additional support for discriminant validity. Supplementary multi-group CFA provided preliminary support for measurement invariance across female and male adolescents. Findings provide initial support for the European Portuguese LSS as a multidimensional measure of adolescent life skills. Full article

The rule of law can be considered as a multidimensional institutional phenomenon, which emerges through interplay between legal, governance and administrative institutions. The paper offers an exploratory statistical modeling approach to find empirical patterns in national rule-of-law profiles according to the 2024 World Justice Project (WJP) Rule of Law Index. Eight dimensions of the index are considered to identify differences between countries and similarities of their multidimensional institutional performance. Principal Component Analysis reveals strong associations between eight dimensions, which are structured along the same performance institutional scale; the first principal component explains 85.7% of the overall variation and two principal components explain 92.5% of it. K-Means, hierarchical and DBSCAN clustering methods are then used to examine the empirical similarities between countries. While the six-cluster solution of K-Means offers distinct group descriptions, low bootstrap stability of this solution suggests that these groups cannot be regarded as fixed rule-of-law regimes. In addition, the Random Forest analysis reveals Regulatory Enforcement, Absence of Corruption, and Criminal Justice as the three dimensions, which contribute to the empirical differentiation of the described profiles the most. In general, the results imply that international variations in rule-of-law performance are viewed as heterogeneous locations in a multidimensional institution space, rather than as stable and distinct legal systems. The above-presented methodology allows for an exploratory approach to analyze international variations in rule-of-law performance that considers the limitations of cross-section data and instability of clusters. Full article

This study was conducted to examine the perceptions and attitudes of final-year veterinary students regarding the Official Minimum Fee Schedule established for veterinarians in Türkiye, within a multidimensional framework. The research was conducted with a total of 216 final-year students enrolled in veterinary faculties in Türkiye. Data were collected using a questionnaire consisting of Likert-type items. The construct validity of the scale was assessed using Exploratory Factor Analysis (EFA), and its reliability was measured using Cronbach’s alpha coefficients. The study found that the majority of students considered providing services below the official minimum fee schedule to be ethically inappropriate and reported that professional organizations play an important regulatory and supervisory role in this regard. In terms of demographic variables, no statistically significant differences were found in factor scores based on gender, income level, university, level of education, or internship experience. However, significant differences were identified in the dimensions of regulatory–deontological attitudes and price transparency based on place of residence. In conclusion, attitudes toward the minimum fee schedule in veterinary medicine are shaped not only by legal knowledge but also by ethical values, professional socialization processes, and institutional norms. These findings highlight the importance of addressing fee policies in veterinary education together with their ethical and professional dimensions, as well as strengthening the awareness-raising role of professional organizations. Full article