Search Results (18,454)

Background/Objectives: This study aimed to evaluate the gingival crevicular fluid (GCF) levels of fractalkine/CX3CL1 and CX3CR1 in patients with gingivitis and periodontitis before and after non-surgical periodontal therapy. Methods: A total of 90 individuals comprising 30 with stage 3 periodontitis, 30 with gingivitis, and 30 periodontally healthy, were enrolled in the study. Gingivitis and periodontitis patients underwent non-surgical periodontal treatment. GCF samples were collected at baseline and at 1 and 3 months after treatment. CX3CL1 and CX3CR1 were measured by an ELISA analysis. Results: GCF CX3CL1 and CX3CR1 were significantly elevated in patients with periodontitis and gingivitis compared to healthy controls (p < 0.001). The periodontitis patients also showed higher GCF levels of CX3CL1 and CX3CR1 than those with gingivitis (p < 0.001). Significant decreases in GCF CX3CL1 and CX3CR1 were detected at 1 month after periodontal treatment compared to baseline values in both the gingivitis and periodontitis patients (p < 0.001). Moreover, the periodontitis patients exhibited significant decreases in both CX3CL1 and CX3CR1 levels at 3 months post-treatment compared to 1 month (p < 0.001), whereas no significant changes were observed between the two time points in the gingivitis patients (p > 0.05). Conclusions: Our findings suggest that the CX3CL1–CX3CR1 axis might contribute to the inflammatory processes of periodontal diseases and may represent a treatment-responsive component of the local host response. Full article

Traditional Mediterranean grapevine landraces represent irreplaceable reservoirs of adaptive diversity, yet many regional germplasm pools remain poorly characterized, limiting conservation strategies and climate-resilient breeding. This study presents the first comparative genetic assessment of 154 local Vitis accessions from three historically interconnected but genomically underrepresented Mediterranean regions: Greece, Morocco, and Slovenia. Using 12 highly polymorphic nuclear SSR markers, we detected substantial genetic diversity (168 alleles; mean heterozygosity He = 0.881) with distinct regional signatures. Moroccan accessions exhibited the highest allelic richness and 11 private alleles, reflecting diverse agroecological adaptation. Slovenian germplasm formed a cohesive, genetically stable cluster with high effective allele numbers. Greek accessions exhibited the highest observed heterozygosity and 14 private alleles, consistent with the Aegean’s role as a major diversification hotspot. Despite >90% of variance occurring within individuals, AMOVA and pairwise FST (0.050–0.061) revealed low to moderate but significant geographic differentiation. Multivariate analyses (PCA, UPGMA) and Bayesian clustering (sNMF, K = 3) consistently resolved three regional genetic groups with varying admixture levels, consistent with a mosaic domestication model, as previously proposed for the Mediterranean basin, shaped by recurrent introductions, wild introgression, and region-specific selection. Our results show that peripheral Mediterranean germplasm harbors meaningful, regionally distinctive, substantial, non-redundant diversity not fully represented in surveys focused on climate adaptation, disease resistance breeding, and long-term genetic resource conservation. These findings challenge simplistic diffusion models and emphasize the strategic importance of geographically comprehensive sampling in grapevine conservation programs. Full article

Photoacoustic spectroscopy (PAS) is a highly sensitive and non-destructive technique widely used for trace gas detection; however, the simultaneous quantification of methane (CH₄), ethane (C₂H₆), and ethylene (C₂H₄) remains challenging due to severe spectral cross-interference and non-linear responses across broad concentration ranges. In this work, we propose a high-precision, end-to-end detection framework based on a Deep Kernel Extreme Learning Machine (DKELM) optimized using a Mutation–Chaotic Particle Swarm Optimization (MCPSO) algorithm. To enhance diagnostic information in the photoacoustic signals, a multi-scale wavelet transform based on a db4 wavelet basis with 5-layer decomposition and a Heursure soft threshold strategy is first employed for denoising and enhancing absorption features. To address the hyperparameter sensitivity and local-optimum trapping inherent in deep models, the MCPSO algorithm integrates hybrid chaotic initialization, adaptive mutation probability control, Cauchy-based perturbation, temperature-controlled mutation amplitude, and elite-guided population updating. The proposed MCPSO-DKELM model is evaluated on an expanded dataset of 470 mixed-gas spectra and benchmarked against other frameworks, including the previously reported SVM-CPSO-KELM architecture. The experimental results demonstrate that MCPSO-DKELM achieves stable, segmentation-free quantification across the full dynamic range, with an average detection error below 3.5% and the maximum relative error constrained to under 15%, which represents a substantial improvement over existing approaches. Thus, the combination of deep kernel feature extraction and mutation–chaotic global optimization provides a robust and reliable solution for simultaneous multi-component hydrocarbon gas analysis in complex industrial environments. Full article

This paper presents a three-dimensional generalization of the M-integral, formulated as an interaction integral based on a bilinear strain energy density, for the mixed-mode decoupling of crack front energies in finite structural components. The proposed $M_{\theta }^{3D}$ integral combines real and virtual mechanical fields within a local spherical reference frame, enabling the separate evaluation of mode I (opening), mode II (in-plane shear) and mode III (out-of-plane shear) energy release rates along arbitrary crack front lines. The theoretical framework, derived from Noether’s theorem and the virtual work principle, is implemented in the Cast3M finite element code using a toroidal integration domain with a local theta weighting function. Numerical validations are conducted on the Mixed-Mode Crack Growth (MMCG) specimen, a geometry representative of structural components subjected to combined tension and shear. Three key findings are demonstrated: (i) practical domain independence is achieved for all three fracture modes; (ii) the three-dimensional approach converges to the plane-stress solution for thin specimens and reveals significant deviations from plane-strain assumptions; (iii) even under nominally mode I + II loading, a non-negligible mode III component emerges due to Poisson-induced out-of-plane effects, with magnitude increasing at free surfaces and for thicker geometries. These results indicate that finite-thickness and out-of-plane effects can significantly affect the partition of fracture energy between modes. For the MMCG configuration investigated here, the three-dimensional formulation shows the limitations of two-dimensional assumptions and provides an energetic basis for the analysis of mixed-mode fracture in finite-thickness components. Full article

The Probability Hypothesis Density (PHD) filter based on the Track-Before-Detect (TBD) approach is a key technique for detecting weak targets whose numbers are unknown and time-varying. To overcome the limitations of existing algorithms, such as high computational cost, poor real-time performance, and low tracking efficiency in dense clutter, this paper proposes a fast non-sequential particle PHD filter for TBD. Specifically, an adaptive particle generation method based on differential localization is introduced in the prediction stage, allowing newly generated particles to quickly concentrate around potential target locations. In the update stage, particles are divided into three groups to simplify weight calculation and improve efficiency. Furthermore, a parallel resampling strategy is adopted to further enhance real-time performance. Numerical experiments demonstrate that the proposed method maintains tracking accuracy with only a small number of particles, thereby significantly reducing computational complexity and improving real-time capability. This work offers a practical reference for the engineering deployment of TBD algorithms. Full article

Surface-enhanced Raman spectroscopy (SERS) has emerged as a transformative tool in biomedical diagnostics, offering a highly sensitive and non-invasive method for detecting molecular biomarkers at exceptionally low concentrations. This approach takes advantage of the plasmonic characteristics of customized metallic nanostructures that produce intense localized electromagnetic fields via localized surface plasmon resonance and facilitate electron transfer reactions that notoriously enhance the intrinsically weak Raman scattering signals of molecular entities which reside on or next to their surfaces. SERS-based assays have shown remarkable potential in detecting cancer biomarkers, circulating tumor DNA (ctDNA), and proteins at early stages, enabling timely and targeted intervention. Additionally, the combination of SERS with AI-driven data analysis has facilitated real-time diagnostics, enhancing the precision and efficiency of point-of-care testing. Despite its promising capabilities, challenges such as substrate fouling, signal degradation, and the need for better biocompatibility remain. Nevertheless, ongoing research in substrate development, coupled with advances in AI, positions SERS as a leading technology for future diagnostic tools. This paper explores the current state of SERS in biomedical applications, highlighting its potential to revolutionize diagnostics and personalized medicine while addressing the existing limitations and future research directions. Full article

The southeastern flank of Mt. Etna is affected by the presence of active faults capable of adapting to deformation through both seismic slip and aseismic creep, posing challenges for seismic microzonation and for land-use planning. Structural surveys in the urban area of San Gregorio di Catania revealed a ~1 km long, N–S trending secondary fracture zone with an extensional component, inducing progressive damage to buildings and infrastructure. To characterize this scarcely visible structure, passive seismic single-station surveys processed with Horizontal-to-Vertical Spectral Ratio (HVSR) tecnique were integrated with Multichannel Analysis of Surface Waves (MASW). The HVSR data enabled the mapping of the spatial distribution of resonance frequencies, tracking an anomalous trend in the seismic bedrock geometry and depth directly correlatable with the presence of the secondary fracture zone. Directional analyses exhibit systematic preferential orientations of resonance peaks near the fracture corridor, confirming a rigorous structural control and a tectonic origin for the recorded anomalies. Furthermore, reconstructed 2D impedance contrast sections show distinct discontinuities and a local westward dislocation of the main seismo-stratigraphic interface across the deformation zone. The lack of correlated instrumental seismicity supports the interpretation that the displacement is primary accommodated via aseismic fault creep. Methodologically, these findings demonstrate that the passive seismic method provides a highly effective, non-invasive approach for identifying hard-to-detect tectonic structures that remain unobliterated by dense urbanization. Ultimately, these results offer critical, actionable constraints for seismic microzonation and urban land-use setback zoning. Full article

Mastitis remains the most economically damaging disease of dairy production, and recent molecular work has converged on the NLRP3 inflammasome as a key integrative node of its pathogenesis. This narrative review integrates evidence published largely between 2015 and 2026 to show how diverse triggers—Staphylococcus aureus and Escherichia coli, lipopolysaccharide (LPS) and lipoteichoic acid (LTA), non-esterified fatty acids (NEFA), heat stress, environmental xenobiotics including nanoplastics, and microbiota-derived signals—may funnel into a common NLRP3–ASC–caspase-1–GSDMD axis that drives pyroptosis, blood–milk barrier disruption, and clinical disease. The review examines the potential obligatory role of reactive oxygen species (ROS), mitochondrial dysfunction, and selenoprotein-mediated redox control in licensing inflammasome assembly. It further evaluates the emerging gut–mammary and rumen–mammary axes that operate upstream of local epithelial activation. We survey a structurally diverse therapeutic landscape encompassing dietary selenium, probiotics, microbial metabolites, plant-derived nanovesicles, polyphenols, ginsenosides, and small-molecule NLRP3 antagonists, identifying recurring mechanistic motifs that suggest combinatorial regimens may yield additive benefit. Importantly, much of the evidence derives from in vitro and murine models, and we highlight the translational gaps that must be bridged before clinical application in dairy cattle. Finally, we map outstanding research gaps and propose priorities for translational work aimed at sustainable, antibiotic-sparing management of bovine mastitis. Full article

Millimeter-wave radar enables non-contact monitoring of cardiac activity and therefore has the potential to reconstruct electrocardiogram signals without surface electrodes. However, existing radar-based electrocardiogram reconstruction methods still suffer from incomplete extraction of heartbeat-related information and insufficient modeling of electrocardiogram-related features, which limits reconstruction accuracy. To address these issues, this study proposes a millimeter-wave radar-based electrocardiogram reconstruction method that integrates a respiratory-harmonic-suppressed multi-channel signal-processing frontend with the proposed CA-WTBNet deep reconstruction network. First, based on maximal overlap discrete wavelet transform-based multi-resolution analysis, respiratory harmonics mixed into heartbeat-related components are suppressed by combining respiratory harmonic detection with a heart-rate frequency protection strategy, while cardiac-related information is preserved as much as possible. A multi-channel input representation is then constructed. Meanwhile, the proposed deep reconstruction network is developed to jointly model complementary channel-wise features, local waveform morphology, and temporal dependencies by integrating channel-attention mechanisms, convolutional residual modules, window-based Transformer blocks, and bidirectional long short-term memory. Experiments conducted on the public dataset show that our method achieves an average Pearson correlation coefficient of 0.9641, a mean normalized root mean square error of 0.0458, an average R-peak F1 score of 0.9956, and an average R-peak timing error of 3.13 ms on the test set. In comparison with related studies on the same public Resting dataset, the proposed method achieves the best overall performance among the compared methods, with a 0.53% improvement in Pearson correlation coefficient and a 10.20% reduction in normalized root mean square error over the best-performing compared method. Full article

The efficiency of airport resource allocation is improved through the establishment of a scientific multi-granularity configuration scheme for flight slot coordination parameters. In this study, a collaborative configuration method for hourly and 15 min coordination parameters is proposed, with Beijing Capital International Airport serving as a case study. Short-term traffic clusters are frequently omitted by traditional hourly parameters, thereby leading to sudden delay surges. First, local delays were extracted from March 2024 Automatic Dependent Surveillance-Broadcast (ADS-B) trajectory data. Subsequently, a delay prediction model was constructed through the integration of a non-stationary queuing model and a gradient boosting regression tree. Second, simulated timetables were generated via a Monte Carlo method under various parameter combinations. With a constant daily flight volume utilized as the experimental baseline, a mapping relationship was established between parameter combinations and expected local delays. Finally, feasible delay regions were delineated and interpretable configuration rules were extracted via a decision tree to maximize schedule flexibility. It was indicated by the results that at an hourly parameter of 70 flights, the target delay is maintained below 8 min by tightening the 15 min parameter to 19 flights. The findings suggest that average load is controlled by hourly parameters, while traffic clustering in high-load scenarios is effectively suppressed by 15 min parameters. A quantitative reference is provided by this method for the configuration of multi-granularity time parameters at hub airports. Full article

Smart cities increasingly rely on distributed sensing and edge intelligence to support urban planning, mobility management, environmental monitoring, and critical infrastructure operation. However, large-scale urban Internet-of-Things deployments are constrained by heterogeneous device capabilities, limited energy availability, variable communication conditions, and data-governance requirements. Federated learning offers a data-locality-preserving alternative to centralized model training, but conventional federated learning strategies often assume full, random, or fixed client participation, which can lead to unnecessary energy consumption, communication overhead, or client starvation in resource-constrained urban environments. This paper proposes an Energy- and Communication-Aware Federated Learning strategy, termed ECA-FL, for smart city sensing systems. The main novelty of the work lies in the joint use of residual device energy and communication conditions to guide adaptive client participation and local training effort, providing a tunable resource–performance trade-off rather than an accuracy-maximizing strategy alone. The framework is evaluated through a controlled simulation-based study using a synthetic multi-class urban sensing proxy task distributed across 100 federated clients under strongly non-IID conditions. Compared with full-participation FedAvg, ECA-FL reduces cumulative energy consumption by 82.9% and communication overhead by 64.7%, while maintaining a final accuracy of 0.8124 compared with 0.8319 for FedAvg-full. Compared with rigid fixed-participation strategies, ECA-FL avoids severe learning degradation by adapting participation dynamically instead of excluding clients according to a static rule. A sensitivity analysis further shows that the trade-off parameter controls the balance between learning performance and resource conservation, allowing the framework to be adjusted according to different deployment priorities. The results support the hypothesis that adaptive energy- and communication-aware participation can substantially reduce operational cost while preserving acceptable learning performance within the adopted simulation setting. The study provides practical design insights for sustainable, communication-conscious, and data-locality-preserving federated learning in smart city sensing infrastructures. Full article

The present contribution provides a systematic review of the international scientific literature on the relationship between contaminated sites and real estate market dynamics. The objective is to investigate whether and to what extent the presence of environmental risk sources—both active or decommissioned—affects the value of surrounding residential properties. In particular, the review is focused on an examination of the methods commonly used in relevant studies to measure, interpret, and represent this impact across different geographical contexts, identifying the main magnitude ranges found in the selected contributions. Several studies consistently confirm a statistically significant negative relationship between proximity to polluting sites and real estate values, although the relevance of this effect varies considerably across case studies. Other records highlight non-notable impacts or even positive effects following remediation and redevelopment interventions. The evidence suggests that this relationship is complex and influenced by factors such as site type, contamination severity, specificities of the local urban context and community perception. Moreover, the findings underscore regional variations in the extent and nature of price impacts, reflecting diverse regulatory frameworks and remediation efforts. The outcomes of the literature review provide a robust foundation for developing more effective evaluation tools able to support decision-making processes, enabling policymakers, planners, and investors to promote sustainable urban regeneration, improve environmental justice, and reduce spatial inequalities. Ultimately, this study highlights the critical need for integrating environmental, social, and economic dimensions to fully capture the multifaceted effects of contaminated sites on property markets, thereby orienting more informed and equitable urban development strategies worldwide. Full article

This study proposes a practical framework for estimating instantaneous stay-cable tension in cable-stayed bridges based on the first-order frequency moment (FFM). The proposed framework combines cepstrum-guided modal decomposition, FFM-based instantaneous frequency estimation, windowed cepstrum-based consistency assessment, and energy-weighted multi-modal averaging to estimate instantaneous cable tension from measured vibration responses. Unlike conventional time–frequency analysis methods that rely on local peak extraction in the time–frequency domain, the proposed approach directly estimates instantaneous frequency from the local time–frequency energy distribution, thereby improving tracking robustness while maintaining computational efficiency under operational conditions. Numerical validation demonstrates reliable instantaneous frequency tracking under noisy and non-stationary vibration conditions while maintaining low computational cost. Field validation using acceleration- and displacement-based measurements from an in-service bridge further confirms the capability of the proposed framework to capture vehicle-induced transient tension variations. The results indicate that the framework provides reliable and physically consistent cable tension information under real operational conditions. These characteristics, together with computational efficiency and compatibility with existing monitoring systems, indicate strong potential for near-real-time structural health monitoring applications. Full article

Floodplain wetlands are globally important ecosystems, yet altered hydrological regimes increasingly disrupt the balance between woody and non-woody vegetation. In Australia’s regulated Murray–Darling Basin, it remains unclear whether woody plant encroachment represents a persistent shift toward terrestrialisation or a dynamic process that can be periodically reversed by flooding. This study quantified long-term patterns of woody-vegetation encroachment and retreat across 32,000 ha of mapped wetlands in the mid-Murrumbidgee River floodplain from 1988 to 2023, and assessed how hydrological variability and floodplain connectivity mediate these dynamics. Using open, analysis-ready Earth observation data from Digital Earth Australia (DEA) within the Open Data Cube (ODC) framework, we combined DEA Land Cover for transition mapping, Water Observations for hydrological masking, Landsat surface reflectance for Enhanced Vegetation Index (EVI)-based spectral plausibility testing, and the Wetlands Insight Tool for qualitative temporal context. Woody-vegetation dynamics were strongly non-linear and closely linked to alternating drought and flood phases. During the Millennium Drought (2001–2009), mapped woody-cover decline exceeded 50% of wetland area in some sub-regions, whereas the post-drought recovery interval (2008–2013) produced encroachment exceeding 40% in the most affected areas. Across the full 35-year record, mean encroachment rates ranged from 85 to 250 ha yr⁻¹ among sub-regions, summing to approximately 865 ha yr⁻¹ of woody expansion across the floodplain, while retreat rates were lower overall (approximately 634 ha yr⁻¹), resulting in a net expansion of woody cover. Local hydrological connectivity strongly mediated these responses: infrequently inundated wetlands showed persistent terrestrialisation, whereas more frequently inundated, better-connected wetlands experienced periodic flood-driven retreat. Landsat-derived EVI broadly supported the mapped transitions, indicating general consistency with canopy greening and canopy decline, supporting the ecological plausibility of the detected changes. This open DEA–ODC workflow provides a transparent, transferable framework for operational wetland monitoring and demonstrates that maintaining natural flood frequency, duration, and connectivity is essential for sustaining the resilience of regulated floodplain systems. Full article

Background: Odontogenic keratocysts are developmental cysts of the jaws that often remain asymptomatic until they reach considerable size and are most frequently located in the mandibular angle and ramus regions. Due to their high recurrence potential, the optimal treatment approach remains controversial. The aim of this study was to evaluate treatment modalities associated with lower recurrence rates in odontogenic keratocysts. Material and Methods: Patients diagnosed with odontogenic keratocyst between 2000 and 2024 at the Department of Oral and Maxillofacial Surgery, Gazi University, were retrospectively evaluated. Associations between gender, age, lesion localization, histological subtype, treatment modality, and recurrence were analyzed. Statistical analyses were performed using SPSS for Windows (version 27). Results: A total of 291 cases were included, with an overall recurrence rate of 16.2%. The highest recurrence rate was observed in patients treated with enucleation (19.2%), whereas a lower recurrence rate was found in cases treated with marsupialization (5%). No recurrence was observed in patients who underwent resection. A statistically significant association was found between treatment modality and recurrence (p = 0.014). Conclusions: Treatment selection for odontogenic keratocysts should be carefully planned. In the present study, marsupialization was associated with a lower recurrence rate than enucleation in selected cases. However, because of the retrospective design and non-randomized treatment allocation, these findings should be interpreted with caution and should not be considered evidence of a causal relationship. Long-term clinical and radiological follow-up remains essential because of the potential for late recurrence. Full article