Search Results (496)

Ecological security pattern (ESP) planning typically emphasizes ecological structure and connectivity, but may provide limited information on long-term functional degradation occurring within ecologically important areas. To address this gap, this study develops a baseline-referenced framework for diagnosing ecological resilience degradation (ERD) by integrating ecosystem service value (ESV) dynamics, minimum cumulative resistance (MCR) modeling, and explainable machine learning (XGBoost–SHAP). Using the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) as a case study, ERD was operationally defined as long-term functional degradation within ecologically important components of the 2000 baseline network, with net ESV decline from 2000 to 2020 used as the functional-degradation signal. Two complementary ERD patterns were distinguished: source erosion and corridor interruption. The results showed that ERD exhibited a pronounced core–periphery pattern, with higher degradation intensity concentrated along the Guangzhou–Foshan–Dongguan–Shenzhen urban development corridor. Integrated ERD covered 5452.69 km², of which source erosion accounted for 4238.32 km² (77.73%) and corridor interruption for 1214.37 km² (22.27%). Source erosion represented the dominant ERD pattern in terms of spatial extent. The XGBoost model showed moderate predictive performance under spatial block cross-validation (mean validation R² = 0.638 ± 0.043), and SHAP analysis indicated that vegetation condition, proximity to water bodies, nighttime light, and elevation were among the most influential factors associated with spatial variation in ERD intensity. NDVI contributions shifted from positive to negative around 0.65, while the distance-to-water response changed most rapidly within 200–300 m. These values are interpreted as empirical transition ranges in the model response. Overall, the proposed framework links long-term ecosystem functional degradation with baseline ecological network position and provides a spatially explicit basis for identifying functionally degraded ecological areas and supporting differentiated spatial prioritization and ecological management. Full article

Objective: We aimed to investigate whether ultrasound-based texture analysis can differentiate liver metastases according to the histopathological origin of the primary tumor and to evaluate the quantitative texture characteristics of metastases originating from colorectal, pancreatic, and breast cancer. Materials and Methods: This prospective study included 75 patients with biopsy-proven liver metastases, comprising 25 colorectal adenocarcinoma, 25 pancreatic ductal adenocarcinoma, and 25 invasive ductal breast carcinoma metastases. Conventional B-mode ultrasound images were obtained prior to treatment. The largest metastatic lesion in each patient was manually segmented using a whole-lesion two-dimensional region of interest (ROI). Histogram-based texture analysis was performed using an in-house MATLAB-based software package (version R2021a; MathWorks, Natick, MA, USA). Extracted parameters included intensity-based metrics, dispersion measures, entropy, uniformity, and percentile values. Texture features were compared among the three groups using appropriate statistical tests. Results: Significant differences were observed among metastatic lesions according to their primary tumor origin. Significant differences were observed in the mean, median, minimum, maximum, most frequent gray-level values, root-mean-square level, root-sum-of-squares level, entropy, and all evaluated percentile parameters among groups (all p < 0.05). Pancreatic cancer metastases consistently demonstrated the highest intensity-related histogram values and percentiles, whereas breast cancer metastases exhibited the lowest values. Colorectal metastases were generally of intermediate intensity. Entropy values were significantly higher in colorectal and pancreatic metastases than in breast cancer metastases (p < 0.05), suggesting greater structural heterogeneity. No significant differences were observed for kurtosis, skewness, uniformity, or size distribution parameters (all p > 0.05). Conclusions: Ultrasound-based tissue analysis revealed distinct quantitative features among liver metastases originating from colorectal, pancreatic, and breast cancer. Density-related parameters, percentiles, and entropy show the potential to differentiate metastatic lesions based on their primary tumor origin, thus serving as a non-invasive biomarker. Full article

Hydrolates are aqueous co-products of aromatic-plant distillation whose composition and functionality differ from those of the corresponding essential oils. This critical review links botanical source, distillation conditions, chemical composition, quantitative biological performance, food or agricultural application, and readiness for nano-enabled formulation. Direct hydrolate studies show marked heterogeneity: reported antimicrobial performance ranges from minimum inhibitory concentrations of 5.69–500 μL mL⁻¹ to approximately 1–3.5 log reductions in food models, while antioxidant results depend strongly on the assay and reporting unit. Evidence in foods is most developed for fresh produce, seafood, dairy, meat, and beverages, but direct bakery validation remains a gap. Hydrolates offer aqueous compatibility and generally lower sensory intensity than essential oils, yet low active-compound concentrations, batch variability, microbiological susceptibility, and limited shelf stability restrict reproducible use. Among nano-enabled solutions, one direct lavender-hydrolate nanoemulsion study reported a diameter of 225.4 ± 3.2 nm and a polydispersity index of 0.098 ± 0.011, together with improved antibacterial activity; however, hydrolate-specific encapsulation efficiencies, release kinetics, long-term stability, food validation, and field trials are largely unreported. Liposomes, polymeric nanoparticles, nanogels, and active films therefore remain mostly transferable concepts supported by essential-oil, extract, or isolated-compound studies rather than established hydrolate technologies. Future work should use standardized production and quality markers, free-hydrolate and unloaded-carrier controls, realistic matrices, safety and non-target testing, scale-up analysis, and quantitative sustainability assessment. Hydrolates are promising sustainable phytochemical resources, but claims of nano-enabled advantage require direct comparative evidence. Full article

This study presents a data-driven framework for determining the optimal gear tooth surface modification (crowning) to improve tolerance to angular misalignment (in-plane and out-of-plane). A nonlinear tooth contact analysis (TCA) model was employed to accurately predict the contact path evolution of meshing gears under different combinations of tooth modification amounts and misalignment angles. An accurate dataset consisting of 530 simulated helical gear meshing configurations was generated. Based on these simulation results, a Gaussian Process Regression (Kriging) surrogate model was developed to establish the relationship between tooth modification, misalignment parameters, and contact behavior. The validated surrogate model enables rapid prediction of gear contact characteristics and interpolation within the design space, thereby supporting efficient surrogate-assisted design exploration without requiring repeated computationally intensive TCA simulations. The proposed framework identifies the minimum modification required to maintain acceptable contact conditions, and provides an efficient tool for improving misalignment tolerance and supporting robust gear design. Full article

This study investigates the atmospheric and upper-ocean responses associated with Super Typhoon (TY) Lekima (2019) during 4–12 August, including its landfall over Zhejiang Province, China. Variations in sea surface temperature (SST), latent heat flux (LHF), water vapor flux (WVF), total column water vapor (TCWV), vertical integral moisture divergence (VIMD), mean sea level pressure (MSLP), wind circulation, precipitation, subsurface temperature and salinity, and Ekman pumping velocity (W_E) were analyzed throughout the typhoon life cycle. Before intensification, SSTs of 29.5–31.0 °C indicated favorable ocean-surface conditions. During and after the storm passage, SST decreased to approximately 26.0–27.5 °C along portions of the track and below 25.0 °C near the Zhejiang coast, with stronger cooling on the right-hand side of the track. Surface salinity decreased by approximately 0.3–0.8 PSU during 8–10 August, with freshening extending through the upper 30–40 m. The Ekman pumping field identified regions where wind-stress curl favored upwelling and downwelling, with stronger positive signals occurring on the right side of the track. During the active maritime stage, LHF values of approximately −300 to −200 W m⁻² indicated enhanced upward latent heat transfer. WVF reached 1800–2200 kg m⁻¹ s⁻¹, TCWV exceeded 70 kg m⁻², and VIMD decreased below approximately −100 × 10⁻⁵ kg m⁻² s⁻¹, indicating enhanced moisture transport and convergence. These conditions coincided with daily precipitation exceeding 120 mm and locally reaching approximately 160 mm over northern and northwestern coastal Zhejiang. The minimum daily mean MSLP decreased from 1000 to 972–976 hPa during peak intensity and subsequently increased as Lekima approached landfall and weakened inland. While these responses are qualitatively consistent with previous TY case studies, our study provides new quantitative benchmarks and process attribution through heat budget analysis. This integrated, stage-based analysis provides a comprehensive quantitative reference for model validation and future comparative studies of landfalling typhoons in the western North Pacific. Full article

Understanding intra-urban spatial interaction is essential for context-sensitive urban planning. While classical spatial interaction theories provide strong conceptual foundations, systematically translating these theoretical concepts into quantifiable indicators remains a significant methodological challenge. Furthermore, capturing the complex, non-linear dynamics driving urban mobility requires analytical approaches that balance predictive power with interpretability. To address this gap, this study develops a feasible, theory-informed analytical framework that bridges classical spatial interaction theory with interpretable machine learning to quantify the predictive patterns underlying intra-urban mobility. In a case study of Changchun, China, Ullman’s three core concepts, together with fundamental measures of urban scale, were systematically operationalized as a set of quantitative proxy variables based on multi-source geospatial big data. XGBoost was then used to model grid-level origin-destination flows at multiple spatial resolutions, and the SHapley Additive exPlanations (SHAP) was used to assess the contributions and dependence patterns of the theory-driven indicators. The results demonstrate the framework’s predictive robustness, with the XGBoost model consistently outperforms the traditional parametric benchmark across all evaluated spatial resolutions. The 1000 m resolution provided the best balance between predictive performance and spatial detail, yielding an R² of 0.696, compared with 0.611 for the benchmark. The explanatory analysis indicates that functional complementarity is the most critical predictive dimension overall. It also identifies distinct nonlinear patterns, including negative associations between transfer impedance and predicted mobility flows beyond critical thresholds, positive associations between built-environment scale indicators and predicted flows only above minimum intensity thresholds, and diminishing marginal associations between intervening opportunities and predicted flows. This study provides a scalable and transferable approach for diagnosing spatial interactions in data-rich urban contexts, providing an empirical basis for calibrating future micro-level urban simulations. Full article

This study investigates the effect of high-temperature hydrogen exposure on the structure and properties of Cr₂O₃/Al₂O₃-based detonation coatings deposited on AISI 316L stainless steel. Bilayer and gradient coatings were exposed to hydrogen at 1000 °C for 3, 4, and 5 h and subsequently characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDS), surface profilometry, and thermal desorption spectroscopy (TDS). One independent specimen was examined for each combination of coating architecture and hydrogen exposure duration. Therefore, the present study was designed as an exploratory comparative investigation rather than a statistically powered study. The principal α-Al₂O₃ and Cr₂O₃ phases remained detectable after all exposure durations, indicating preservation of the main oxide phases. SEM/EDS analysis revealed microcracks, local defects, and heterogeneous surface regions, with more pronounced localized damage in the bilayer coatings. The Ra values of the bilayer coatings were 1.385, 0.833, and 1.207 μm after 3, 4, and 5 h, respectively, whereas the corresponding values for the gradient coatings were 1.049, 1.337, and 1.049 μm. The minimum Ra of 0.833 μm after 4 h in the bilayer coating coincided with SEM/EDS evidence suggesting local coating damage and possible thinning. TDS showed the most intense hydrogen desorption for the gradient coating after 3 h. Overall, the observed results suggest that coating architecture influences surface evolution and hydrogen-retention behavior under the investigated high-temperature hydrogen exposure conditions. Full article

Warsaw experiences significant urban heat island (UHI) effects driven by low-albedo surfaces and urban geometry, which pose ongoing challenges for public health and climate adaptation. This study evaluates daytime SUHI intensity at satellite acquisition time across the entire city to provide a comparison of two acquisition dates during heatwaves. Utilizing Landsat 7 and Landsat 9 satellite imagery from July 2015 and July 2022, the research compares six distinct SUHII calculation methods, including spectral indices, statistical normalizations, and area-based temperature differences, as minimum SUHII values differed significantly between the two observations (shifting from approximately −13.8 °C to −7.7 °C). This indicates that suburban areas can become thermally similar to the city due to rapid land conversion and decreased evaporative cooling of vegetation during severe heat. Average intensities calculated via the SUHII 4 method reached 5.80 °C in 2015 and 2.07 °C in 2022. Under the criteria considered in this case study—interpretability, explicit physical units, treatment of water bodies, data requirements, and spatial consistency—SUHII 4 was the most suitable of the six tested formulations for the Warsaw analysis. Conversely, dimensionless spectral indices and purely statistical approaches are not recommended due to interpretative limitations. Full article

This study presents a parametric optimization model for the friction disc of a combined friction face milling cutter operating under intensive contact friction, high clamping forces, and cyclic thermomechanical loading. The computational framework integrates ANSYS Workbench, the Static Structural module, Design of Experiments (DOE), Kriging surrogate modeling, and Multi-Objective Genetic Algorithm (MOGA) optimization. The friction disc geometry is defined by two design variables: the radial depth of the relief groove, a (3–6 mm), and its axial width, b (3–8 mm). Structural performance is evaluated using the von Mises equivalent stress and axial displacement of the cutting zone. Heat-treated 65G spring steel, with a yield strength of 640 MPa, is selected as the material. Using a safety factor of four, the allowable stress is limited to 160 MPa, while the permissible axial displacement is 0.05 mm to satisfy axial runout requirements for face milling cutters. Finite element analysis and response surface modeling show that parameter a predominantly affects axial deformation, whereas the combined influence of a and b governs the acceptable stress region. Multi-Objective Genetic Algorithm (MOGA) optimization identifies design solutions satisfying both strength and stiffness constraints. The proposed approach enables the determination of the minimum admissible values of the geometric parameters a and b while satisfying the prescribed strength, stiffness, and axial displacement constraints. Full article

Reliable rainfall regionalization underpins hydrological design and the transfer of rainfall information to ungauged or short-record sites, yet it is especially difficult in arid regions with strong spatial and temporal variability and short, uneven records. This study develops a multivariate, stability-validated framework for classifying rain gauges into candidate homogeneous rainfall regions across Saudi Arabia. A national database of 274 stations was screened for 2015–2023, and 202 stations were retained. Ten descriptors representing annual rainfall, interannual variability, L-skewness of annual maxima, within-day rainfall concentration, short-duration intensity, elevation, and distance from the coast were constructed from 5 min records; correlated concentration and intensity descriptors were compressed by block-wise principal component analysis into a seven-variable, robustly scaled feature matrix. Partitions from K = 2 to 10 were evaluated using internal-validity indices, the gap statistic, minimum cluster size, repeated-subsample stability, cross-algorithm agreement, and sensitivity to alternative feature representations. The diagnostics supported several low-order structures: the four-region K-means solution showed the highest subsample stability (median adjusted Rand index: 0.977) and best consensus rank, whereas Ward clustering and Gaussian mixture modeling favored a parsimonious three-region solution. At four regions, cross-algorithm agreement was moderate (adjusted Rand index: 0.526–0.663) and the partition was strongly reproduced under the robust original-variable and global principal component analysis-(PCA)PCA representations (0.804). The regions comprised a widespread arid interior, a small near-coastal group, a wetter western–southwestern group, and a coastal-foothill group, with distance from the coast, elevation, and short-duration intensity providing the strongest contrasts. The framework offers a reproducible basis for regional rainfall-frequency analysis, station pooling, and hydrological transfer, pending verified completeness data and formal homogeneity testing. Full article

Conservation interventions in historic buildings require quantitative assessment to balance preservation needs and minimal intervention principles. This study presents a quantitative framework for minimum intervention assessment of heritage conservation, based on 133 documented interventions at Caishen Temple in Xinzhou across four periods: 1992, 2006, 2016, and 2017. Four dimensions were defined: Extent of Intervention (EI), Reversibility (RE), Information Loss (IL), and Necessity (NE). Expert scoring on a five-point Likert scale yielded high inter-rater reliability (ICC: 0.79–0.88). The entropy weight method was then used to derive data-driven weights from the expert-scoring matrix, $\mathit{IL}=0.3149$, $\mathit{EI}=0.3025$, $\mathit{NE}=0.2572$, $\mathit{RE}=0.1253$, and the Intervention Intensity Index ($\mathit{III}$) was calculated for each intervention. A random forest model was further developed as an exploratory cross-check, with 19 problematic interventions labelled as $\mathit{y}=1$ and 114 normal interventions as $\mathit{y}=0$. Target labels were defined through a dual-source procedure combining SSIM- and HSV-based image-similarity assessment for interventions with paired pre- and post-restoration photographs and explicit textual evidence from conservation records for interventions without paired photographs. Feature importance and SHAP analyses indicated that reversibility and necessity had the greatest discriminative importance for distinguishing problematic from normal interventions in this dataset, whereas the entropy-based ranking assigned higher weights to information loss and extent of intervention. This descriptive contrast, based on only four dimensions, highlights the distinction between data dispersion and discriminative capacity. Spatiotemporal analysis indicated that roof and rafter components exhibited the highest intervention intensity, while 1992 interventions contained the largest proportion of problematic practices. This study combines entropy-derived weighting with a machine-learning-based exploratory cross-check, providing a transparent, case-based framework for evidence-based conservation decision-making at historic heritage sites. Full article

Parcel area sits at the intersection of urban planning, land administration and land surveying. It underpins development intensity, floor area allocation, minimum lot thresholds, land readjustment and value capture mechanisms. Yet discrepancies between modern measurements and ownership titles are usually evaluated through fixed tolerance formulas rather than quantified confidence intervals. While coordinate precision is routinely specified, the uncertainty of the derived parcel area is seldom expressed explicitly, limiting the traceability of planning calculations based on cadastral geometry. This paper presents a variance-based formulation for estimating parcel area uncertainty from boundary coordinates. Using the Gauss area function and first-order propagation, vertex precision is translated into parcel-level confidence intervals based on horizontal RMS parameters commonly reported in cadastral practice, including documented transformation accuracy. The Greek cadastre provides an illustrative case combining a national GNSS infrastructure, a unified reference system and formula-based area screening embedded in statutory workflows. Illustrative examples show how area uncertainty varies with parcel geometry and measurement origin. Absolute uncertainty increases with parcel size and boundary elongation, while relative uncertainty decreases with parcel size. A Monte Carlo analysis of the error-correlation structure shows that the diagonal, independent model is not a universal bound: depending on the structure of the transformation error and on parcel geometry it may either overstate or understate the true area uncertainty, by factors between about 0.4 and 3.5 in the cases examined. The results clarify how coordinate precision propagates into regulatory-relevant area values and support more transparent interpretation of area discrepancies in planning and land administration contexts. Full article

Background: The timing of perceived exertion assessment within a resistance training set may influence physiological adaptation; this study aimed to directly compare first-repetition (RPE-1) and last-repetition (RPE-last) monitoring strategies applied to functional, neuromuscular, body composition, and cardiometabolic adaptations during elastic band resistance training in older adults. Methods: Forty sedentary older adults (n = twenty per group, sex-balanced) were randomly assigned to RPE-1 or RPE-last using the OMNI-RES elastic band scale during a 16-week, open-label high-intensity elastic band resistance training program, with blinded outcome assessment and data analysis; three withdrew during the intervention (RPE-1, n = 2; RPE-last, n = 1), and all forty randomized participants were retained in the intention-to-treat analysis via baseline carry-forward. Functional capacity, isokinetic knee and elbow strength (60 and 180°/s), DXA-assessed body composition, and fasting cardiometabolic biomarkers were evaluated pre- and post-intervention. Between-group effects were analyzed using ANCOVA with Benjamini–Hochberg false discovery rate (FDR) correction, whereas functional equivalence was assessed using Welch-corrected two one-sided tests (TOST) with percentile bootstrap against published minimum clinically important difference (MCID) margins. Results: Both groups improved significantly across most outcomes. For the primary outcomes, RPE-1 was associated with greater improvements across all eight isokinetic strength conditions after FDR correction, with adjusted between-group differences ranging from +7.86 to +18.38 Nm in favor of RPE-1, and all 95% CIs excluding zero (ηp² = 0.14–0.37). The Welch-corrected TOST demonstrated functional equivalence between monitoring strategies for all four functional outcomes in the primary intention-to-treat analysis. However, the pre-specified complete-case sensitivity did not confirm equivalence in the 30-Second Chair Stand Test, indicating that this outcome was sensitive to the handling of missing data. Among secondary exploratory outcomes, RPE-1 also was associated with greater improvements in DXA-assessed fat mass (adjusted difference—−1.33 kg; 95% CI—−2.02 to −0.63; ηp² = 0.29) and lean mass (+0.42 kg; 95% CI—0.02 to 0.83; ηp² = 0.11), high-density lipoprotein cholesterol (+5.11 mg/dL; 95% CI—1.52 to 8.69; ηp² = 0.18), and low-density lipoprotein cholesterol (−16.99 mg/dL; 95% CI—−23.22 to −10.76; ηp² = 0.45). Conclusion: RPE-1 appeared to confer greater benefits for maximizing neuromuscular strength, whereas RPE-last provides an equally valid alternative when preserving physical independence is the primary objective. Full article

Microalgae represent a promising raw material for the bioeconomy and biotechnology. One of the key factors regulating their metabolism is light. However, the traditional approach to cultivation, aimed at maximising biomass productivity due to high lighting intensity, contradicts the principles of energy efficiency. In addition, the responses of soil microalgae to the spectral composition of light remain poorly understood, which creates a gap in fundamental knowledge. The Pleurastrum insigne CAMU MZ–Ch4 soil strain is a potent producer of valuable compounds. Physico-chemical and instrumental analysis, including spectrophotometric, chromatographic and gravimetric techniques, were used to determine the productive and biochemical parameters of the strain. It was shown that blue and red light with intensities of 90 and 150 µmol m⁻² s⁻¹ are optimal in absolute terms for the growth and CO₂ biofixation, green light for the accumulation of pigments and antioxidants, and low-intensity red light is the most energy efficient for the synthesis of lipids and other metabolites. Based on calculations of product-specific energy intensity, it was demonstrated that the “more light = more product” strategy increases metabolite energy intensity. Maximum bioeconomic efficiency (the minimum cost of electricity to produce a unit of a metabolite) is achieved with low intensity of red and blue light. Full article

Karst river basins require restoration approaches that identify vulnerable connections while distinguishing ecological constraints from governance implementation conditions. This study developed a sequential Structure–Resistance–Connectivity–Governance (SRCG) framework for the Chengjiang River Basin, Guangxi, China. Ecological sources were identified from vegetation vitality, habitat quality, landscape integrity, and hydrological proximity. Natural landscape resistance and anthropogenic disturbance were integrated to delineate potential source-pair corridors. Bottleneck Intensity combined corridor load, minimum corridor width, and high-resistance overlap, and was integrated with ecological movement resistance to delineate Ecological Restoration Priority Zones (ERPZs). Governance Mismatch Index and Administrative Boundary Proximity Index values were applied only after ERPZ delineation. The analysis identified 28 ecological sources covering 312.4 km², 76 potential connections, three principal bottleneck clusters, and six ERPZs covering 118.5 km². The upper basin retained a relatively continuous network; whereas, the middle and lower reaches were increasingly constrained by roads, settlements, quarry disturbance, fragmented cropland, and discontinuous riparian vegetation. ERPZ-A, D, E, and F were resistance-dominated, ERPZ-B was bottleneck-dominated, and ERPZ-C was compound-priority. Governance assessment differentiated four implementation contexts. Overall land-cover accuracy was 0.896, Cohen’s kappa was 0.874, and 14 of 16 field sections were concordant with mapped landscape conditions; sensitivity tests retained the principal sources, bottlenecks, and ERPZ cores. The framework separates ecological restoration urgency from implementation difficulty, while its outputs represent potential structural rather than confirmed functional connectivity. Full article