Search Results (2,069)

Background/Objectives: The growing population of cancer survivors has increased the need for reliable, culturally appropriate instruments to identify unmet supportive care needs. The Cancer Survivors’ Unmet Needs Measure (CaSUN) is a survivorship-specific assessment tool, but validated Russian and Kazakh versions have not previously been available. This study aimed to translate and culturally adapt CaSUN, evaluate its psychometric properties in cancer survivors in Kazakhstan, and examine unmet needs relevant to survivorship care. Methods: This cross-sectional psychometric validation study included 404 cancer survivors (Russian version, n = 201; Kazakh version, n = 203). Translation and cultural adaptation involved forward- and back-translation, expert review, cognitive debriefing, and pilot testing. Internal consistency was assessed using Cronbach’s alpha. Construct validity was evaluated using exploratory (EFA) and confirmatory factor analysis (CFA), with measurement invariance examined across language versions. Unmet needs and associated demographic and clinical factors were also examined. Results: Both versions demonstrated excellent internal consistency (Cronbach’s alpha: Russian = 0.966; Kazakh = 0.978). KMO values were 0.920 and 0.940, respectively (Bartlett’s tests, p < 0.001). EFA yielded a five-factor solution explaining 68.1% and 64.2% of the variance in the Russian and Kazakh versions, respectively; however, parallel analysis supported five factors in the Russian sample but suggested three in the Kazakh sample, indicating greater structural uncertainty for the Kazakh version. CFA demonstrated good incremental fit in both language groups (Russian: CFI = 0.975, TLI = 0.973; Kazakh: CFI = 0.973, TLI = 0.971), although RMSEA (0.096 and 0.102, respectively) and SRMR (0.116 and 0.099, respectively) indicated residual model misfit. Metric invariance was supported, while scalar invariance was supported by conventional fit index criteria but should be regarded as provisional. The most frequent unmet needs concerned medical care, up-to-date information, and involvement in health management. Younger age, male sex, urban residence, a history of cancer recurrence, and Kazakh language completion were independently associated with more unmet needs. Conclusions: The Russian and Kazakh CaSUN versions demonstrated high internal consistency and evidence supporting construct validity and cross-language comparability. These culturally adapted versions may support systematic needs assessment and patient-centered survivorship care in multilingual oncology services in Kazakhstan. Full article

The fatigue of an SBS asphalt mixture with physical gel structures under repeated loading is a variable-rate mechanical process. However, there is a lack of a mechanical characterization mechanism to accurately quantify this process. This study aims to propose a method for mechanically characterizing the variable-rate fatigue process of the SBS asphalt mixture based on kinetics theory. First, indirect tensile monotonic and repeated-loading tests with advantages of easy specimen fabrication, good test repeatability, and widespread use in pavement fatigue evaluation were conducted at 15 °C, 20 °C, and 25 °C to obtain the mechanical response of SBS asphalt mixtures. Then, a permanent strain model accounting for damage of the SBS asphalt mixture was established based on viscoelastic damage theory. Finally, a fatigue damage kinetic model was developed. The parameters, represented in terms of lumped damage sensitivity exponent (β) and fatigue activation energy (E_a), were determined to quantitatively characterize the variable-rate fatigue behavior of the SBS asphalt mixture. The results show that the established permanent strain model accounting for damage can accurately capture the nonlinear evolution of fatigue damage and permanent strain in SBS asphalt mixtures. The parameter β can serve as a reliable mechanical indicator for quantifying the fatigue process rate. The fitted kinetic parameter E_a can reasonably characterize the magnitude of the energy barrier governing the temperature-dependent variable-rate fatigue process. Macroscopically, the SBS asphalt mixture presents an elevated fatigue damage energy threshold compared with the base mixture. According to existing literature, this difference may be associated with three-dimensional physical gel structures from the SBS polymer. Within the scope of the present test conditions, kinetics theory shows potential as a theoretical framework for quantifying and characterizing the variable-rate fatigue behavior observed for SBS asphalt mixtures. Full article

The deep-sea tunnels at the Sanshan Island Gold Mine are subjected to extreme conditions characterized by high stress and complex erosion resulting from high mineralization. Under these conditions, conventional shotcrete is prone to performance degradation and insufficient durability, posing a threat to the long-term safety of the tunnels. At the same time, mine water is difficult to recycle on-site. To address these engineering challenges, this study utilized fly ash (FA), S105-grade ground granulated blast furnace slag (GGBS), polypropylene coarse fiber (PPCF), and hydroxypropyl methylcellulose (HPMC) as modifying components and employed the response surface method (RSM) to optimize the mix design of mine water-blended shotcrete. The study selected compressive strength, direct shear strength, and chloride ion electrical flux at 6 h as response indicators and constructed a quadratic polynomial regression model. Analysis of variance and goodness-of-fit tests indicated that the model possessed good significance and reliability of fit. Based on this model, the optimal mix design was determined: an FA/GGBS blend ratio of 3:7, a cement replacement rate of 20%, a PPCF content of 3.3%, and an HPMC content of 0.18%. Performance testing showed that the optimal mixture achieved a compressive strength of 25.24 MPa, a direct shear strength of 8.08 MPa, and a chloride ion electrical flux of 778 C after 6 h. Compared to the control group, its peak compressive strength decreased by only 9.98%, while its residual strength increased significantly; direct shear strength increased by 18.1%, and electrical flux decreased by 33.8%. This indicates that the material’s mechanical load-bearing capacity, deformation coordination, and corrosion resistance have been enhanced in a synergistic manner. Field industrial trials have verified that this modified concrete possesses excellent ductile yield characteristics, can effectively suppress water seepage in mine tunnels, is capable of withstanding extreme underground operating conditions, and enables the efficient reuse of mine water resources. Full article

This study presents an integrated green analytical strategy combining deep eutectic solvent (DES) screening, Fourier transform infrared spectroscopy (FTIR), principal component analysis (PCA), and Box–Behnken response surface optimization for the valorization of pineapple crowns, an underexplored agro-industrial by-product. An ultrasound-assisted extraction (UAE) method was developed using DESs to obtain phenolic-rich extracts from pineapple (Ananas comosus) crowns. Five DES formulations were characterized by FTIR to evaluate their characteristic vibrational features, while extraction performance was assessed using total phenolic content (TPC) and antioxidant activity determined by the DPPH assay. Among the tested solvents, glycerol/urea (1:1, molar ratio) exhibited the highest extraction performance based on TPC and antioxidant activity measurements. PCA was used as a complementary tool to visualize the relationships among the DES formulations. Following preliminary temperature screening, 50 °C was selected for the optimization experiments. The extraction conditions were optimized using a Box–Behnken design coupled with response surface methodology (BBD–RSM), while desirability function analysis was applied to identify the optimum extraction conditions. The predicted optimum conditions were a sample mass of 1.09 g, an extraction time of 24.75 min, and a water content of 38.21%, yielding predicted responses of 34.66 mg GAE/g air-dried sample (ADS) for TPC and 12.30 mg Trolox equivalent antioxidant capacity (TEAC)/g-ADS for antioxidant activity. Experimental confirmation at the optimum showed deviations below 2% between predicted and observed responses, supporting the adequacy of the models. The quadratic models showed high goodness of fit (R² = 0.9871 for TPC, and R² = 0.9906 for antioxidant activity). Overall, the integration of DES-based UAE, FTIR characterization, PCA, and chemometric optimization provides a sustainable analytical approach for producing phenolic-rich extracts from pineapple crown biomass. Full article

Traditional goodness-of-fit tests for binary longitudinal data can perform poorly when response-pattern tables are sparse. Concordant information-based tests mitigate this issue by using lower-dimensional marginal information, but their performance under second-order serial dependence has not been systematically examined. Building on this framework, we first discuss a third-order concordant marginal formulation and identify an important limitation in the binary setting: for binary responses, we show that each third-order concordance residual is exactly one half of the sum of the three corresponding pairwise concordance residuals. Thus, the third-order concordance formulation contains no additional information beyond the pairwise concordance residuals, and its rank deficiency in larger binary designs follows from this redundancy. We therefore focus on the second-order concordance statistic and related limited-information diagnostics under AR(2) and MA(2) error structures. Specifically, the AR(2) simulations cover all parameter pairs on the specified grid that satisfy the stationarity conditions, whereas the MA(2) simulations include all 162 grid points satisfying $|{\varphi }_1|+|{\varphi }_2|\le 0.9$ and ${\varphi }_2\ne 0$, which form a symmetric subset of the invertible parameter region. We assess Type I error rates and empirical power across different sample sizes and dependence configurations. The results show that second-order serial dependence, especially negative dependence patterns, can substantially affect test performance. These findings clarify the relative performance of concordance-based diagnostics under the AR(2) and MA(2) parameter settings examined in this study. Full article

Perceived safety determines whether urban greenways are used in everyday life, yet it is rarely measurable at the boundary scale where design decisions are made. Existing street-view models split into black-box networks whose predictions cannot be traced to design elements and pixel-ratio regressions whose interpretability rests on weak, unstructured representations, while greenspace studies lean on GIS proximity variables that confound design with context. We present the CPTED-Guided Perception Network (CGPN), which fuses a visual branch with a masked, learnable projection of segmentation ratios onto five CPTED dimensions. Because the mask confines learning to a theory-defined support, the prior regularizes the representation while every coordinate of the model remains tied to a named CPTED dimension, whose directional effect on the prediction we verify by perturbation. On 110,633 street-view images, CGPN is statistically equivalent to the strongest black-box baseline in pairwise ranking accuracy (0.649 vs. 0.652; equivalence test within a 1.5-point margin, $p=0.006$, attains the best $R^2$ (0.192), and improves on its unconstrained variant in goodness of fit across three seeds ($\mathrm{\Delta }{R}^2=+0.031$, $p=0.042$). Applied to 218 greenway-adjacent residential boundaries in Boston and New York, it uncovers a threshold-like negative association for barrier-dominated access control and an inverted-U distance profile whose weakest segment lies within 100 m of the greenway edge ($p=0.007$). Full article

The Mediterranean Basin ranks among the region’s most vulnerable to climate change, yet little evidence exists as to whether the scientific literature emphasises strategic planning or operational implementation. This study measures the thematic distribution of adaptation strategies in the Mediterranean adaptation literature and identifies which categories of measures remain comparatively under-researched. A systematic review following PRISMA 2020 was conducted on peer-reviewed articles indexed in the Web of Science Core Collection and published between 2015 and 2024, retrieved through a thematic query built on regional and landscape planning vocabulary. Of 89 articles retained in the qualitative synthesis, 64 reported at least one codable adaptation measure and entered the quantitative analysis, yielding 123 coded occurrences across twelve thematic categories; the remaining 25 returned a null coding vector. Chi-square goodness-of-fit testing against a maximum-entropy benchmark, with residuals corrected for article-level dependence by cluster bootstrap and for multiplicity by the Benjamini–Hochberg procedure, shows an uneven distribution (χ² (11, N = 123) = 56.02, p < 0.001; Cramér’s V = 0.20; Pielou’s evenness J = 0.90). Sustainable development and adaptation policy are over-represented; green spaces, cultivation and hydrological interventions are under-represented. An article-level analysis of register co-occurrence finds no segregation between policy-oriented and technical categories: 34.4% of coded articles engage both registers, and the two are statistically independent across the corpus (odds ratio 2.02, p = 0.17). The imbalance is therefore one of volume rather than of community structure. Because the unit of observation is the published article rather than the implemented intervention, and because the corpus is restricted to planning-oriented, English-language, indexed literature dominated by northern-rim EU member states, these findings characterise the orientation of a defined body of literature and cannot establish a gap in adaptation practice. The study provides a reproducible method for measuring thematic emphasis and an empirical basis for identifying under-researched categories of operational adaptation measures. Full article

Collaboration networks are frequently studied as empirical instances of complex social systems, yet standardized methodological frameworks for consistently identifying heterogeneous mesoscopic structural regimes remain limited. This study proposes an integrated multi-criteria classification framework and demonstrates its application to the structural characterization of communities extracted from a large-scale scientific collaboration network. The framework combines community detection, classical network metrics, statistical modeling of weighted degree tails, small-world diagnostics, information-entropy measures, and fractal analysis based on the Song–Havlin–Makse box-covering renormalization framework. As an empirical application, the methodology is applied to the giant coauthorship component of Embrapa’s scientific production (1974–2024), derived from the Brazilian Agricultural Research Database (BDPA), comprising 60,636 nodes. The weighted Louvain algorithm partitions the network into 25 major communities, which are evaluated through an integrated classification protocol combining the Akaike Information Criterion model selection, Kolmogorov–Smirnov goodness-of-fit tests, small-worldness diagnostics, and fractal scaling analysis. The proposed framework identifies three network families, namely Barabási–Albert (BA-like)/scale-free small-world, scale-free fractal (non-BA) and small-world (non-scale-free), while explicitly distinguishing supported and ambiguous classifications according to the overall consistency of the statistical and structural evidence. The results demonstrate that distinct mesoscopic structural regimes coexist within the same connected collaboration system, highlighting the usefulness of the proposed reproducible multi-criteria framework for comparative topological characterization across complex collaboration networks. Full article

When many binary items are analyzed, most cells in the complete response table are empty. Full-table statistics may then be unreliable, and an omnibus result does not locate the misfit. This paper develops a local goodness-of-fit testing method for binary item response models by extending the weighted sequential sums-of-squares construction to pairwise concordance margins. The construction gives ordered one-degree-of-freedom components for individual item pairs. They are compared with Cholesky components and four local diagnostics under zero and wide symmetric intercepts. Omnibus statistics are examined separately under symmetric slopes. The sequential components have an empirical Type I error close to the nominal levels. With zero intercepts, all methods show substantial power for the target pairs, although pair order moves some shared discrepancy into non-target components. Cholesky gives higher target-pair power and broader moderate elevations across non-target pairs, whereas the sequential components show more concentrated, order-dependent peaks. With wide symmetric intercepts, power differs greatly among target pairs, and the Lagrange multiplier statistic is particularly sensitive to intercept distance. The main qualitative patterns persist across three nominal levels. Lower-order omnibus statistics generally maintain an empirical Type I error close to the nominal levels and detect the slope alternatives, whereas Pearson–Fisher is liberal in the sparse full table. A symmetric parameter vector therefore need not give uniform local diagnostic results. Full article

Open workforce datasets can help to extend research on artificial intelligence (AI) only if they are sufficiently provenance-traceable, have good measurement quality, and have a relational structure suitable for behavioral inference. This study examines a benchmark dataset comprising 12,000 linked records across 15 industry categories and 47,206 AI tool-use records. Sampling, recruitment, questionnaire wording, respondent authentication, ethics procedures, and whether the records are real or synthetic are not documented, so the dataset is treated as a tabular source rather than verified workforce evidence. Analyses are limited to indicators that have been observed directly, including job satisfaction, work–life balance, career outlook, trust in AI, weekly learning hours, AI-use intensity, and employer-provided AI training. Assessment of behavioral interpretation of the data was conducted using Spearman correlations, HC3-robust regressions, false discovery rate adjustment, secondary industry interaction checks, and a relational-realism diagnostic. Concerns about AI replacing jobs were negligible and non-significant on a five-point scale, with an average of 2.745. Training also showed no robust association when evaluated against outcomes that did not contain training. The median absolute Spearman correlation across conceptually related observed variables was 0.0064, with the 95th percentile at 0.0180, which is very low. These estimates reflect the characteristics of the supplied documents rather than employee actions, and do not assess conservation of resources processes or tourism worker outcomes. Results from the analysis demonstrate the importance of checking open workforce data for construct validity, relational validity, sector fit and provenance before testing behavioral theories. Research for regenerative tourism requires reliable sector-specific samples, reliable multi-item measures, longitudinal design, and direct measures of social and destination outcomes. Full article

Background/Objectives: HLA class II molecules play a pivotal role in maternal–fetal immune tolerance; however, their contribution to recurrent pregnancy loss (RPL) appears population-specific. This study investigated associations between HLA-DRB1, HLA-DQA1, and HLA-DQB1 alleles and idiopathic RPL in Azerbaijani women. Methods: A case–control study included 125 women with idiopathic RPL and 138 ethnically matched fertile controls. All participants had normal karyotypes and no identifiable anatomical, endocrine, or other established causes of pregnancy loss. HLA class II genotyping was performed using SSP-PCR. Allele frequencies were compared using chi-square or Fisher’s exact tests, as appropriate. Hardy–Weinberg equilibrium was assessed in controls using the chi-square goodness-of-fit test. Benjamini–Hochberg FDR correction was applied across all 25 allele-level comparisons. Results: Several alleles showed nominal associations with RPL before multiple-testing correction, including HLA-DRB1*04, DRB1*11, DRB1*15, HLA-DQB1*03, DQB1*05, HLA-DQA1*01, DQA1*05, and DQA1*06. After FDR correction, HLA-DQB1*05 (p = 0.004, q = 0.050; OR = 1.95, 95% CI: 1.24–3.07) showed a borderline association with increased RPL susceptibility, whereas HLA-DQB1*02 (p = 0.004, q = 0.050; OR = 0.54, 95% CI: 0.35–0.82) showed a borderline protective association. The remaining nominal associations did not remain significant (q > 0.05). Conclusions: HLA-DQB1*05 and DQB1*02 showed borderline associations with idiopathic RPL in Azerbaijani women after FDR correction. These findings should be interpreted cautiously and validated in larger, independent, multi-ethnic cohorts. Full article

We propose a two-stage joint estimation method combining a multi-physics-constrained physics-informed neural network (PINN) with an adaptive extended Kalman filter (AEKF) for lithium-ion battery state-of-charge (SOC) estimation. Three constraints—an RC polarization dynamics ODE residual, discharge voltage–SOC monotonicity, and terminal-voltage physical bounds—are embedded into the PINN loss function; the converged network then serves as the nonlinear observation model within the AEKF. On LG 18650HG2 cells across six temperatures (−20 to 40 °C) under a strict cross-condition setup (training on LA92/UDDS; testing on US06 and two mixed profiles), the method maintains a temperature-averaged SOC mean absolute error (MAE) of 2.33% (1.54–4.48%, three random seeds), whereas the MAE for the equivalent circuit model with the AEKF (ECM-AEKF) degrades to 9.46% and 11.66% at −20 °C and −10 °C, and remains 1.5–4.6× worse with the per-temperature re-identified parameters; an end-to-end long short-term memory (LSTM) baseline averages 1.90% but degrades to a per-condition maxima of 22.6% at low temperatures. Multi-seed ablations locate the constraints’ value in providing low-temperature stability and physical consistency, with the RC-ODE constraint contributing most. The study further reveals that goodness of terminal-voltage fit does not imply SOC accuracy; the controlled comparisons trace this to the model structure rather than parameter settings, exposing the risk of voltage-fitting-based evaluation over wide temperature ranges. Full article

Background/Objective: The measurement properties of the Arabic Fear-Avoidance Beliefs Questionnaire (FABQ) have not been examined using the Rasch measurement model. This study evaluated the Physical Activity (FABQ-PA) and Work (FABQ-W) subscales of the Arabic FABQ in individuals with low back pain (LBP). Methods: This cross-sectional study included 113 individuals with LBP who completed the Arabic FABQ. The FABQ-PA and FABQ-W were evaluated separately using RUMM2030. Likelihood-ratio tests supported use of the partial credit model for both subscales. Rasch analysis examined overall and individual item fit, person misfit, response-category threshold ordering, local item dependency, differential item functioning (DIF), person separation, unidimensionality, and targeting. DIF was investigated by sex, age, and LBP duration. Unidimensionality was evaluated by comparing person estimates derived from item subsets defined by principal component analysis of residuals. Targeting was examined using person–item threshold distributions. A previously proposed four-category rescoring structure was additionally explored because of disordered thresholds. Results: Following removal of participants with substantial person misfit, both FABQ-PA (n = 105) and FABQ-W (n = 106) demonstrated satisfactory overall Rasch model fit, and all individual items showed satisfactory fit. Both subscales supported unidimensionality, with no evidence of local item dependency or DIF by sex, age, or LBP duration. Targeting was generally adequate, although coverage was less optimal at the higher end of FABQ-PA and lower end of FABQ-W. Person separation was limited for FABQ-PA (PSI = 0.60) but good for FABQ-W (PSI = 0.80). All items demonstrated disordered thresholds using the original seven-category response scale. A previously proposed four-category rescoring structure improved, but did not completely resolve, threshold disordering. Conclusions: The Arabic FABQ-PA and FABQ-W demonstrated satisfactory final model and item fit and supported unidimensional measurement; however, important limitations were identified. Limited person separation for FABQ-PA and persistent threshold disordering across both subscales indicate that scores should be interpreted cautiously and that further refinement of the FABQ response format is warranted. Full article

Extreme financial events are usually defined by loss magnitude alone, which quantifies severity but leaves open whether tail losses arrive in isolation or in temporally concentrated patterns. This paper develops a fractional tail-event timing diagnostic combining peaks-over-threshold (POT) generalized Pareto distribution (GPD) severity with Mittag-Leffler recurrence of interarrival times. We show that when exceedance times are driven by a stationary and ergodic latent intensity, the log-moment recurrence estimator has an explicit probability limit below the Poisson boundary that depends on the intensity only through its marginal log-variance, so volatility-driven dispersion of the arrival rate suffices to produce sub-Poisson estimates. In six daily series through 2026, the estimator is calibrated against a permutation null preserving the marginal loss distribution and the integer-gap discretization. That null sits near 1.05 rather than at unity, so the nominal Poisson boundary is not the correct reference for trading-day gaps. Against the calibrated null, the Deutscher Aktienindex (DAX), Nasdaq Composite, Nikkei 225, platinum, and the Standard & Poor’s 500 (S&P 500) display significant temporal concentration and coffee does not, whereas the monotone decline of the estimator across thresholds proves to be mechanical. Once goodness-of-fit tests are bootstrap-calibrated, no waiting-time law survives for four assets. The Mittag-Leffler parameter is therefore used only as an interpretable diagnostic index of temporal concentration; it is not a fitted-law claim and should not be interpreted as evidence of structural long memory or of a fractional data-generating mechanism. Full article

This study aimed to determine the apparent metabolizable energy (AME), nitrogen-corrected AME (AMEn), and net energy (NE) values of corn for Arbor Acres (AA) broilers aged 12–14 and 26–28 days and to develop prediction equations. Ten corn samples with varying chemical compositions were selected. Test diets were formulated using the substitution method, in which corn replaced 40% of the energy-supplying components in a basal diet. A total of 396 male AA broilers at 9 days of age and another 396 at 23 days of age were used across the two metabolism trials. AME, AMEn and NE were determined using the substitution method combined with respiratory calorimetry. Correlations between energy values and chemical components were analyzed. Multiple linear stepwise regression in SPSS was used to establish prediction equations for AME, AMEn, and NE. The results showed that for 12–14-day-old broilers, AME, AMEn, and NE ranged from 13.84–15.66 MJ/kg, 13.39–15.35 MJ/kg, and 8.61–12.56 MJ/kg, respectively. For 26–28-day-old broilers, the corresponding values ranged from 14.62–16.30 MJ/kg, 14.42–16.05 MJ/kg, and 10.42–13.06 MJ/kg. Notably, NE values and AME/GE (gross energy) ratios were significantly higher in 26–28-day-old broilers than in 12–14-day-old broilers (p < 0.05), which increased by 9.33% and 3.96%, respectively. Correlation analysis showed that phytic acid (PA) was significantly negatively correlated with AME, AMEn, NE, AME/GE, and AMEn/GE in the younger group, whereas ash content was significantly negatively correlated with AME and AMEn in the older group. The prediction equations exhibited good fit, with the coefficient of determination (R²) of the best equation reached 0.97. These findings support the precise application of corn in feed formulation and provide a scientific basis for its efficient utilization in poultry production. Full article