Search Results (5,313)

This study aimed to use intact mineral trioxide aggregate (MTA) as a root canal sealer by hydrophilizing the gutta-percha (GP) surface. The GP specimens were treated with atmospheric air plasma, cetylpyridinium chloride (CPC), or a combination of both. The wettability and surface chemical properties were evaluated using contact angle measurements and X-ray photoelectron spectroscopy (XPS). The physicochemical properties of MTA mixed with water or 100 mM of CPC solution were evaluated using setting time, flowability, compressive strength, and X-ray diffraction (XRD) analyses. Sealing ability was assessed by evaluating the dye penetration in obturated single-rooted teeth. Combined plasma and CPC treatment significantly decreased the contact angle of GP compared to that of the untreated group (p < 0.05) and showed the least hydrophobic recovery after 8 weeks. The XPS analysis confirmed the adsorption of CPC onto the GP surface. The XRD and compressive strength results indicated that the CPC did not interfere with the setting reaction of intact MTA, although the setting time was prolonged (p < 0.05). Dye penetration was significantly reduced in the plasma- and CPC-treated GP groups compared to the untreated GP group (p < 0.05), with a sealing ability comparable to that of the zinc oxide-based sealer. Full article

Zinc oxide (ZnO) nanoparticles have attracted increasing attention in wood science due to their multifunctional properties, including antimicrobial activity, UV absorption, and photocatalytic behavior. Water-based deposition protocols offer clear advantages yet typically struggle with nanoparticle aggregation and limited adhesion to lignocellulosic substrates. This work introduces a rapid and scalable waterborne protocol combining catalyst-free aqueous seeding with microwave-assisted (MWA) growth under mild conditions. Pinus pinaster veneer samples were treated via dip-coating and spraying, with single and double seeding cycles, followed by MWA growth. Protocol efficiency was assessed through ZnO retention, SEM, and EDS analysis, while the impact of the substrate was assessed via mechanical testing, ATR-FTIR spectroscopy, and colorimetry. Dip-coating achieves significantly higher precursor uptake than spraying, while repeated seeding cycles further increase ZnO loading. Results suggest that incorporation may proceed through zinc–carboxylate bonds within the wood matrix, followed by localized ZnO nanostructures development. The effective integration did not weaken the mechanical properties, while color changes were significant for dip-coated samples and noticeable for sprayed ones. Overall, this methodology provides a fast, water-based, and minimally invasive route for ZnO incorporation into wood and a scalable pathway with retained mechanical and chemical properties and limited visual impact. Full article

Background: Rare diseases are associated with chronic progression, functional impairment, and complex care needs, requiring long-term and coordinated rehabilitation. Physical and Rehabilitation Medicine (PRM) plays a key role in maintaining functional capacity and improving quality of life; however, access to rehabilitation services remains uneven across regions. Aim: This study aims to assess the regional structural availability of PRM services across Bulgaria and to identify territorial differences in the organizational profile of rehabilitation services that may influence the potential availability of rehabilitation care for patients with rare diseases. Methods: A descriptive cross-sectional study was conducted using publicly available aggregated data from the NHIF and the National Statistical Institute as of 31 December 2024. Structural indicators included the number of outpatient and inpatient PRM healthcare facilities and PRM specialists, standardized per 100,000 population, as well as the outpatient-to-inpatient facility ratio (OFs/IFs). Hierarchical cluster analysis (Ward’s method, Euclidean distance) was applied as an exploratory tool to identify similarities in regional service availability profiles. Results: Substantial regional differences in the structural availability of PRM services were identified. Outpatient facilities ranged from 4.46 to 6.74 per 100,000 population, while inpatient facilities ranged from 2.30 to 3.42 per 100,000 population. The OFs/IFs ratio varied between 1.30 and 2.26, indicating different organizational profiles of PRM service provision. Exploratory hierarchical clustering suggested two broad regional service profiles: one characterized by a relatively balanced distribution of outpatient and inpatient structures and another characterized by a predominance of outpatient-oriented rehabilitation services. Conclusion: The findings reveal substantial regional differences in the organization of PRM services in Bulgaria. Regions with a predominance of outpatient structures may demonstrate different capacities for delivering comprehensive rehabilitation services, particularly for patients with complex long-term needs, including rare diseases. The results highlight the need for targeted regional planning, improved integration of rehabilitation services, and policy measures aimed at ensuring equitable access to care. Full article

Highway–rail grade crossing (HRGC) incidents remain a persistent safety concern due to repeated interactions between roadway users and rail operations under varying environmental and operational conditions. Existing studies rely on raw incident counts or partial exposure measures that can be influenced by differences in infrastructure exposure and do not account for spatial dependence, limiting consistent comparison across locations. This study developed an exposure-normalized framework to model incident intensity at the county level using accumulated incidents per crossing (AIPC), which normalizes cumulative incidents by crossing exposure. The analysis integrated statistical distribution modeling, spatial clustering, and supervised machine learning. The study combined county-level HRGC data for the contiguous United States from 1975 to 2025 with infrastructure, traffic, environmental, and accessibility variables. Results showed that AIPC was consistent with a gamma distribution, indicating a continuous representation of incident intensity without discrete risk regimes. Local Moran’s I identified statistically significant high-intensity clusters in specific regions, confirming spatial dependence in incident intensity. Machine learning models achieved strong predictive performance, with the extra trees model reaching AUC = 0.907 (F1 = 0.528) and ensemble methods consistently outperforming linear and kernel approaches. SHAP and permutation-based feature importance analysis identified temperature, train frequency, and accessibility measures as the most influential predictors, while aggregate density measures contributed the least. The results provided consistent evidence that incident intensity was associated with environmental conditions, operational exposure, and network structure. The proposed framework supports exposure-based risk assessment and enables identification of high-intensity counties for targeted intervention. This approach provides a transparent and transferable method for improving HRGC safety analysis and prioritizing resource allocation across large geographic areas. Full article

The preparation of high-performance cadmium zinc telluride (CZT) radiation detector materials requires efficient ingot-level quality assessment before full downstream wafer testing. This study proposes a machine learning framework that predicts the product-level yield of test wafers from IV and double-sided spectral measurements of a limited number of standardized evaluation wafers from the same ingot. To address the small number of ingots and wafer-level variability, ingot-level aggregate, A/B-side consistency, threshold-ratio, and distributional features were combined with intra-ingot bootstrap augmentation. Among the evaluated regression models, Random Forest achieved the best held-out test performance under a leakage-safe protocol, with an MSE of 0.021, an MAE of 0.125, and a Pearson correlation coefficient of 0.646; XGBoost showed comparable performance, with an MSE of 0.023, an MAE of 0.128, and a Pearson correlation coefficient of 0.601. In a top-22% screening experiment, the average true yield of ingots selected by Random Forest and XGBoost reached 63.71% and 60.40%, respectively, exceeding the empirical Rule_IV_Abs baseline of 59.08%. These results indicate that the proposed framework can provide useful ranking and prioritization support for early CZT ingot screening, while remaining a decision-support tool rather than a replacement for wafer-level inspection. Full article

Environmental disasters demand structured monitoring systems capable of linking ecological responses to adaptive governance. This study proposes an integrated indicator framework designed to support ecosystem preservation and environmental risk mitigation following large-scale contamination events. The proposed framework combines multi-source environmental data, intrinsic risk classification, multivariate statistical validation, and a dashboard-based decision-support architecture. When the model was applied to Restinga ecosystems impacted by mining tailings deposition, the results revealed significant spatial heterogeneity between the monitoring stations, with ~33% of sites classified under high or critical ecological risk during at least one monitoring period. Of the metals evaluated, 46.15% were above the reference levels, while for biological response indicators such as primary productivity, a 23.53% reduction in danger alerts was observed in 2019 across the evaluated sites when comparing the rainy and dry seasons. The composite “Danger Alert” indicator was triggered in all sampling campaigns during the evaluated period, demonstrating persistent ecological pressure throughout seasonal cycles. Sensitivity analyses confirmed the robustness of the risk classifications under alternative baseline and aggregation scenarios, and an uncertainty assessment indicated stable trends across temporal variability ranges. The proposed framework enhances the interpretability of complex environmental datasets by structuring inferential ecological associations between environmental pressures and biological responses, which can then be translated into actionable governance outputs. Beyond the case study, the architecture is structurally transferable to other ecosystems, provided that ecological indicators and thresholds are contextually recalibrated. The proposed approach contributes to sustainability-oriented environmental governance by integrating statistical validation, adaptive risk thresholds, and decision-support visualization within a unified monitoring system. Full article

Engineered nanomaterials are widely used in environmental remediation, agriculture, and industrial applications owing to their large specific surface area, high reactivity, and tunable physicochemical properties. However, their release into aquatic environments has raised increasing concerns regarding potential risks to primary producers. Microalgae are highly sensitive to environmental stressors and play essential roles in photosynthesis, nutrient cycling, carbon fixation, and aquatic food-web stability, making them important model organisms for assessing the toxicity of engineered nanomaterials. This review summarizes the toxic effects and mechanisms of representative engineered nanomaterials, including metal and metal oxide nanoparticles, nanoplastics, and carbon-based nanomaterials, on microalgae. Major toxic pathways include nanoparticle attachment and aggregation on algal surfaces, shading effects, membrane damage, altered permeability, cellular internalization, toxic ion release, reactive oxygen species overproduction, photosynthetic inhibition, and metabolic disturbance. The review further discusses how particle size, morphology, surface coating, dissolution, aging, light, pH, and natural organic matter regulate nanomaterial bioavailability and toxicity. Combined toxicity caused by coexisting nanoparticles or emerging pollutants is also considered, with emphasis on synergistic, antagonistic, and concentration-dependent effects. Finally, recent methodological advances, such as near-native imaging, Raman-based spectroscopy, particle-specific elemental analysis, and multi-omics approaches, are highlighted. This review provides an integrated perspective for understanding nanomaterial toxicity to microalgae and supports future ecological risk assessment in aquatic environments. Full article

Rice monoculture systems, often involving double- or triple-cropping cycles annually, require intensive agricultural practices that can lead to land degradation. This study evaluates land degradation within the long-term rice monoculture systems of Nakhon Sawan, Thailand, using the Sustainable Development Goal 15.3.1 framework. By focusing exclusively on persistent rice-growing areas, the study minimized the confounding signals of land-use conversion, allowing for an evaluation of the trajectories driven by combined agricultural management and climatic factors. The assessment integrated land use and land cover (LULC), soil organic carbon (SOC) stocks, and land productivity. Findings indicate that 83% of the original paddy area remained long-term monoculture, with LULC-related degradation limited to 4% of the original paddy cultivation area. While SOC depletion was observed in a few districts, a broader potential carbon accretion trend was identified across the province, likely driven by sustainable post-harvest practices such as stubble retention and organic amendments. Land productivity analysis revealed partial stress only in a few districts. The study demonstrated that long-term rice cultivation did not result in widespread deterioration of soil health on an aggregate provincial scale; however, district-localized degradation hotspots suffering from soil organic carbon depletion and climate-induced productivity stress were identified, demanding targeted regional management. Full article

Background: Whether the fatal and non-fatal composition of aggregate pancreatitis burden has changed over time remains unclear. We assessed long-term changes in the fatal-to-non-fatal composition of aggregate pancreatitis burden using Global Burden of Disease (GBD) 2023 estimates. Methods: We conducted a systematic descriptive and trend analysis using publicly available estimates from the GBD 2023 Results Tool for incidence, prevalence, deaths, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) across 204 countries and territories from 1990 to 2023. Because GBD reports pancreatitis as an aggregate cause category, the analysis could not distinguish acute pancreatitis, recurrent acute pancreatitis, chronic pancreatitis, or acute exacerbations of chronic pancreatitis. Primary analyses used age-standardised rates per 100,000 population. Four burden–composition metrics were derived within each location–year stratum: the YLL:YLD ratio, YLD:DALY proportion, deaths-to-incidence ratio, and prevalence-to-incidence ratio. Temporal trends were modelled in R version 4.5, using segmented regression, with up to three joinpoints selected by a Bayesian information criterion. Results: Globally, all six age-standardised native GBD measures declined between 1990 and 2023. The age-standardised incidence rate decreased from 37.62 (95% UI 32.20–43.11) to 32.91 (28.84–37.17) per 100,000, prevalence from 93.78 (69.26–126.25) to 68.92 (52.53–90.32), deaths from 1.76 (1.49–2.16) to 1.40 (1.21–1.66), YLDs from 5.70 (2.75–9.45) to 4.34 (2.18–7.04), YLLs from 55.96 (46.50–69.72) to 43.60 (36.89–53.53), and DALYs from 61.66 (50.62–75.61) to 47.94 (40.57–58.16). However, the fatal-to-non-fatal composition changed little: the global YLL:YLD ratio was 9.82 in 1990 and 10.04 in 2023, while the YLD share of DALYs was 0.092 and 0.091, respectively. Joinpoint modelling showed fluctuation rather than a sustained shift toward disability-dominant burden: the global YLL:YLD ratio was stable until 1998, increased from 1998 to 2002 (annual percent change [APC] 1.38%, 95% CI 0.42 to 2.36), and then declined modestly thereafter (APC −0.13%, −0.20 to −0.06). Burden remained higher in males, whereas females had a greater non-fatal share of total burden (YLD:DALY in 2023: 0.134 vs. 0.073). All sociodemographic index strata remained mortality-dominant in both 1990 and 2023; low-SDI settings had the greatest fatal dominance (YLL:YLD 34.94 in 1990; 24.72 in 2023). Using a descriptive YLD:DALY ≥ 0.50 benchmark, 203 of 204 countries and territories remained below the disability-dominant threshold in both years, no country crossed from below to above this benchmark, and only Georgia moved from above to below the benchmark. Conclusions: Despite declines in global incidence, mortality, and DALY rates, the aggregate GBD pancreatitis burden remained overwhelmingly mortality-dominant from 1990 to 2023. Because GBD pancreatitis combines acute and chronic pancreatitis, this finding should be interpreted as describing the modelled aggregate pancreatitis cause category rather than proving subtype-specific mortality dominance. The intensity of fatal dominance varied by sex, SDI, region, age, and country, but a structural shift toward disability-dominant aggregate burden was not observed. Full article

This paper examines the drivers of house price cycles across EU countries between 2005 and 2024 and measures their synchronicity. We used panel data methods—fixed effects, dynamic panel models (Arellano–Bond GMM), and a pooled VAR framework—to capture static and dynamic relationships between house price growth and key macroeconomic variables. The results show that the dynamics of house prices are highly persistent. GDP growth has a clear positive effect, while higher unemployment and interest rates push prices down. Migration flows, however, are not statistically significant at the EU aggregate level. Property taxation shows a positive coefficient, which probably reflects structural and institutional differences rather than a direct dampening effect on prices. Dynamic analysis suggests that macroeconomic shocks have persistent and economically meaningful impacts on house price growth. Hierarchical cluster analysis revealed three distinct groups of countries, meaning that house price cycles are only partially synchronized across the EU. Unlike previous studies that typically examine individual determinants or synchronization separately, this study integrates panel econometric methods, dynamic VAR analysis, and hierarchical clustering within a unified framework to jointly assess macroeconomic drivers, dynamic interactions, and structural heterogeneity of house price cycles across EU countries. In general, common macroeconomic drivers and structural heterogeneity coexist—this is important for the stability of the housing market and sustainable development. Full article

Gold-mine tailings have attracted increasing interest as alternative constituents in cement-based materials, yet their use in structural concrete remains limited by the lack of multivariable approaches capable of capturing the interaction between tailing fractions with different functional roles. In this study, a tailing-derived fine aggregate and a fine tailing sludge from the Cisneros Project (Santo Domingo, Antioquia, Colombia) were jointly incorporated into structural concrete and evaluated through a response surface methodology based on a central composite design. The tailings were characterized by physical, chemical, mineralogical, and morphological analyses, while concrete mixtures proportioned according to ACI 211 were assessed in terms of 28-day compressive strength. The statistical model revealed a significant quadratic response and a strong interaction between both incorporation variables. The most favorable strength region, based solely on 28-day compressive strength, was identified at sludge contents below 20% and tailing aggregate replacement below 90%, with the latter interpreted as a preliminary mechanical threshold rather than as a practical recommendation for field application. Higher incorporation levels led to strength losses associated with the increasing fineness of the system and greater water demand. This study demonstrates that the performance of tailing-modified structural concrete depends on the coordinated dosage of fractions with distinct roles and provides preliminary mechanical incorporation limits based solely on 28-day compressive strength. Since durability and environmental safety tests, including heavy metal/cyanide leaching, permeability, shrinkage, and chemical resistance, were not conducted, these limits should not be interpreted as definitive recommendations for long-term structural application. Full article

Renal cell carcinoma (RCC) comprises histologic subtypes with distinct prognosis and treatment implications. This single-cohort study evaluated slide-level weakly supervised subtype classification for clear cell RCC (ccRCC), papillary RCC (pRCC), and chromophobe RCC (chRCC) using 928 diagnostic H&E whole-slide images (WSIs) from 928 patients in TCGA-RCC. We propose Swin-CLAM, a controlled modification of CLAM in which the conventional CNN patch encoder is replaced by an ImageNet-pretrained Swin-Tiny Transformer, while the CLAM-SB bag-level aggregation module is kept unchanged. WSIs were segmented, tiled into non-overlapping $256\times 256$ patches at an effective $20\times$ magnification, encoded offline, and classified using slide-level labels only. In five-fold patient-level cross-validation on TCGA-RCC, Swin-CLAM achieved a macro-averaged AUC of $0.976\pm 0.008$, an accuracy of $94.8\pm 1.0\%$, and a macro-F1 of $0.940\pm 0.012$, with the largest gain observed for chRCC. Attention heatmaps and t-SNE plots were used as qualitative, exploratory analyses rather than formal evidence of interpretability. These results suggest that stronger patch-level representation can improve CLAM-based RCC subtype classification under a fixed MIL aggregator. However, the study does not establish clinical readiness, and external validation, calibration, domain-shift analysis, and expert region-level assessment are needed before practical deployment. Full article

Aggregates comprise up to 95% of flexible pavement composition, critically influencing performance based on geological source and processing methods. In Pakistan, where approximately 264,175 km of roads carry 96% of inland freight, premium Margalla aggregates face increasing demand and depleting reserves, necessitating sustainable alternatives. This study comprehensively evaluates aggregates from five key quarries (Margalla, Malakand, Kohat, Swabi, and Besai) for highway suitability. Rigorous laboratory testing encompassed macro-level physical and mechanical properties and micro-characterization using Scanning Electron Microscopy (SEM), Energy Dispersive Spectroscopy (EDS), and Fourier Transform Infrared Spectroscopy (FTIR), alongside performance tests including Indirect Tensile Strength (ITS), rutting resistance, and fatigue analysis. Overall, Margalla aggregates exhibited the best performance, showing the lowest abrasion value (21%), highest Tensile Strength ratio (TSR) (82%), highest conditioned ITS (433.7 kPa), highest dynamic modulus (2120 MPa at 25 Hz), and the lowest rut depth (7.8 mm at 10,000 cycles). These superior properties are attributed to their favorable physical characteristics and high calcium content. Malakand and Kohat aggregates also demonstrated satisfactory performance, with TSR values of 79% and 76%, conditioned ITS values of 408.7 and 377.7 kPa, and rut depths of approximately 8.8 and 10.5 mm, respectively, indicating their suitability for medium-traffic pavements. In contrast, Swabi and Besai aggregates exhibited lower moisture resistance (TSR = 77% and 75%), lower conditioned ITS (355.7 and 337.7 kPa), and higher rut depths (~13.0 and 14.2 mm), making them less suitable for high-stress pavement layers. These findings support Malakand and Kohat aggregates as viable regional alternatives to Margalla. Full article

In the face of the raw materials crisis and environmental concerns, sustainable waste management has become a priority for current and future generations. Recycling waste from wastewater treatment plants in a closed loop protects natural resources, reduces landfill volumes, and lowers disposal costs. This paper presents the results of tests on the physical, filtration, and mechanical properties of mixtures of washed mineral waste (WMW) from grit chambers with fly ash from the thermal treatment of municipal sewage sludge (SSA) in a fluidized bed furnace. Additionally, radiological tests of the mixture components were conducted. Based on the conducted tests, the possibility of sustainable use in civil engineering, such as soil backfills and embankment construction materials, was assessed. The possibility of safely using waste materials in the indicated construction solutions was demonstrated for mixtures with dominant WMW content (90% and 70% by total weight). The waste mixtures correspond to poorly or medium-grade sands with a small amount of silt (uniformity coefficients of 3.33, 3.50, and 8.00). They are characterized by maximum dry densities of 1.542, 1.770, and 1.780 g/cm³; optimal moisture contents of 12.54, 12.86, and 20.25%; permeability coefficients of 0.08, 0.22, and 0.39 m/d; and internal friction angles of 38.4, 39.5, and 40.1°. The values of the determined parameters of some mixtures are similar to those of natural sands used as construction aggregates. All mixtures meet the geotechnical criteria for use in road embankments, below frost depth, and in flood embankment bodies. Mixtures with a 90% mass fraction of WMW were also approved for application as backfill for installation trenches. However, none of the mixtures met the hydraulic conductivity threshold required for the upper layers of embankments nor for backfill of abutments and retaining structures without the use of an additional binder (cement or lime), which is considered a prerequisite for these applications. Full article

This study proposes an integrated terrestrial laser scanning (TLS)-based workflow for quantitatively and spatially assessing the relative geometric condition of exterior wall surfaces. The workflow consists of point-cloud acquisition, ROI definition, reference-plane estimation, signed-depth computation, grid-based spatial aggregation, specimen-based validation, and real exterior wall application. Rather than introducing a fundamentally new point-cloud processing algorithm, the main contribution lies in integrating established processing steps into a consistent surface-based assessment procedure and extending deviation evaluation from simple numerical summaries to spatial interpretation. A 3D-printed validation specimen with designed defect depths of 1, 3, 5, and 7 mm was used for quantitative validation. Among 136 designed defects, 123 ground-truth-mapped ROIs were evaluated, resulting in an MAE of 0.795 mm, RMSE of 1.168 mm, and P95 error of 2.511 mm. A RANSAC threshold-based sensitivity analysis confirmed that the final refined reference plane and major signed-depth statistics remained stable within the tested threshold range. The workflow was further applied to a real exterior wall dataset with 29,933,332 strict-ROI points, yielding a mean signed depth of 2.448 mm, median of 2.691 mm, RMSE of 9.956 mm, P95 of 17.121 mm, and maximum value of 90.827 mm. High-deviation regions with an absolute centered signed depth of 15 mm or greater occupied 28.218 m², corresponding to 10.62% of the valid analysis area, and were distributed across 57 connected clusters. These results indicate that the proposed workflow can support both quantitative deviation assessment and spatial interpretation of high-deviation regions, while the real exterior wall results should be interpreted as a relative geometric assessment and feasibility demonstration rather than absolute accuracy validation or structural damage assessment. Full article