Search Results (20,639)

In this study, a comprehensive mathematical method for modeling the operational reliability of mine hoisting equipment under conditions of incomplete and heavily censored data is developed. The analyzed dataset includes 259 observations collected over a five-year period for six critical components, with the overall level of censoring reaching 62% and exceeding 70% for long life mechanical subsystems. Considering right, left, and interval censoring, the paper proposes a unified statistical procedure that combines empirical estimation of failure rates with parametric identification using Weibull, exponential, normal, and lognormal distributions. Model parameters are estimated using censored data–aware fitting procedures, while model selection is performed based on likelihood-based criteria, supplemented by correlation analysis to assess agreement between empirical and fitted reliability curves. The methodology is implemented computationally in the Mathcad Prime environment and is supplemented with mathematical tools for reconstructing survival curves, analyzing parameter sensitivity, and evaluating robustness at different censoring levels. In addition, an economic optimization model is formulated to determine cost-effective maintenance intervals by minimizing an integral functional that accounts for preventive maintenance, repair, and downtime costs. The results demonstrate that the proposed approach provides stable reliability estimates and reliable forecast intervals, enabling the construction of generalized life cycle curves for individual subsystems. The study establishes a rigorous mathematical basis for the transition from fixed-interval maintenance to adaptive, reliability-oriented maintenance strategies in industrial mine hoisting systems. Full article

Floods are natural disasters that cause significant socioeconomic and environmental losses in both urban and rural areas. Within the framework of spatial planning, precautionary measures against flood hazards can be developed using analytical approaches based on different modeling techniques. In this study, flood-prone areas in the Melen Basin, Türkiye, were identified and mapped using five statistical methods, namely Frequency Ratio (FR), Shannon Entropy (SE), Evidential Belief Function (EBF), and the hybrid models EBF–SE and EBF–FR. The analysis was conducted using a flood inventory and environmental datasets covering the period 2019–2024, including elevation, slope, aspect, land use, plan and profile curvature, drainage density, distance to river, curve number, long-term average precipitation, geological formation, soil depth, topographic wetness index, sediment transport, and stream power index. Model performances were evaluated using the Receiver Operating Characteristic (ROC) curve and the Area Under the Curve (AUC). The results indicate that the SE method achieved the highest predictive performance (AUC = 0.979), followed by FR (0.974), EBF–SE (0.972), EBF–FR (0.968), and EBF (0.966). According to the FR and SE models, elevation, lithology, and slope were identified as the most influential factors in flood occurrence. In the evaluation of the success index of the models, the following values were determined according to their size: EBF–SE (96.0), SE (94.4), EBF (91.8), FR (81.9), and EBF–FR (79.4). In the classification of flood sensitivity maps, Natural Breaks (Jenks) is the most successful method according to the success index. The findings demonstrate that data-driven and hybrid models can effectively support flood risk assessment and provide valuable input for land-use planning and flood risk management. Full article

Identity-based communities that share common characteristics, beliefs, and experiences (e.g., Black LGBTQ+ communities) have historically been conceptualized as protective bubbles that buffer Black LGBTQ+ individuals against the deleterious effects of systemic racism and cisheterosexism. However, this monolithic narrative often masks the internal power dynamics that divide belonging. This study explores the exclusionary dynamics embedded within these safe spaces, examining how internal hierarchies of skin tone, socioeconomic status, and gender performance function as proximal stressors. Guided by a critical constructivist paradigm, this study utilized Reflexive Thematic Analysis to analyze open-ended survey responses from 74 Black LGBTQ+ adults. Data were drawn from a larger mixed-methods study and analyzed using a six-phase recursive process to identify latent patterns of intragroup gatekeeping. The analysis revealed that the sanctuary of the community is restricted. Three primary themes emerged: (1) Phenotypic Capital and the Politics of Authenticity, where lighter skin tone triggered authenticity scrutiny and darker skin tone faced rejection based on physical appearance; (2) Socioeconomic Gatekeeping, where belonging was stratified by the cost of participation and protective insularity within working-class spaces; and (3) Policing the Binary, where rigid adherence to gender archetypes created a landscape of performance surveillance. Access to community resilience is not a universal right but a negotiated status contingent upon the payment of a resilience tax. To promote genuine health equity, researchers and practitioners working with this population must move beyond the uncritical referral to “community” and actively dismantle the internalized systems of oppression that fracture collective survival. Full article

Accurate monitoring of aboveground biomass (AGB) is essential for forest carbon accounting and climate change mitigation, yet signal saturation and the treatment of forest landscapes as biophysically homogeneous entities remain significant barriers to high-fidelity mapping. This study implements an ecologically integrated model that leverages forest-type specific (coniferous vs. broadleaf) to enhance regional AGB retrieval. By refining established data fusion techniques with structural and compositional parameters, this approach seeks to mitigate systematic biases often found in generic regional assessments. Compared with 360 geo-referenced subplots, our stratified Support Vector Regression (SVR) model significantly outperformed non-classified counterparts, achieving an R² of 0.76 and a reduced RMSE of 18.48 Mg/ha. This refined precision enabled a nuanced time-series analysis (2013–2020), revealing that while regional AGB increased from 157.13 to 192.23 Mg/ha, this trajectory was punctuated by a distinct sub-regional growth plateau between 2016 and 2018. By correlating these trends with disturbance data, we identified a 11.27% biomass decline in southwestern sectors linked to a tripling of burned area, pinpointing intensified fire regimes as the primary driver overriding recovery-driven carbon gains. These findings demonstrate that harmonizing multi-sensor signals with functional forest differentiation provides the necessary sensitivity to track carbon resilience, offering a scalable and robust tool for operational forest management and global carbon cycle research. Full article

Background/Objectives: Accumulating evidence and clinical observations suggest that the gut microbiome plays a crucial role in functional dyspepsia (FD). However, the precise characterization of this relationship is unclear. This systematic review and meta-analysis aimed to elucidate the potential role of the gut microbiome in FD based on evidence from published clinical studies. Methods: A comprehensive search of three databases (PubMed, Google Scholar, and Web of Science) was conducted, and 17 relevant clinical studies, including 8 observational studies and 9 interventional studies, published up to September 2025, were identified. Data on the gut microbiome and FD were extracted and subjected to meta-analysis. Results: Meta-analysis revealed no significant differences in gut microbiota α- or β-diversity between patients with FD and healthy controls (Shannon index: standardized mean difference [SMD] = −0.12, 95% confidence interval [CI] −0.90 to 0.67, I² = 88%). In contrast, effective interventions induced notable shifts in the microbial community structure (pooled SMD = 0.27, 95% CI −0.28 to −0.83, I² = 58%). These shifts were accompanied by increased short-chain fatty acid (SCFA) production and intestinal tight-junction protein levels, which coincided with improved FD symptoms. Conclusions: Although no significant differences in the gut microbiota were detected between patients with FD and healthy controls, interventions in patients with FD induced marked changes in the microbial community. Modulation of gut microbiota-related metabolites, such as SCFAs, may represent a promising therapeutic strategy for the management of FD. Full article

Phages, the most abundant entities on Earth, exhibit a complex interplay with bacteria, especially within environmental biofilms, resulting in an ecological arms race. This study investigates the interaction between phages and bacteria in the drains of beef-processing plants using high-throughput sequencing and metagenomic analysis. Metagenomic data collected from 75 drain samples from beef-processing plants were analyzed to investigate phage–bacterial interactions. First, assembled contigs were screened to identify viral sequences, which were then taxonomically annotated to determine the viral composition, including phages. Functional annotation of these viral sequences provided information about the viral genes and their roles in bacterial interactions specifically associated with attack and counterattack of bacteria. In parallel, bacterial contigs were examined to identify genes associated with antiphage defense systems, providing insights into the strategies adapted by bacteria to resist phage infection. Taxonomic annotation of viral sequences from the bulk metagenomic data revealed the presence of phages targeting Pseudomonas, Klebsiella, and Enterococcus. The higher abundance of Pseudomonas phages aligns with our previous study, where Pseudomonas was identified as the dominant bacterial genus, suggesting potential copersistence of phages and their hosts. Functional annotation of phage contigs revealed infective and lysis-related genes, highlighting their potential role in bacterial attack. Conversely, bacterial contigs encoded antiphage defense systems, including CRISPR-Cas, restriction–modification, and other defense-related genes. The study also uncovered the presence of anti-CRISPR proteins in phages, suggesting a counterattack on the bacterial defense. These findings provide evidence for phage attack, bacterial defense, and phage counterattack and may showcase the ongoing coevolutionary arms race between phages and bacteria. While this evidence looks promising, these results remain preliminary and further studies are needed to validate these findings. Still, this study provides a foundational understanding of bacteria–phage coexistence in beef-processing plant drains and paves the way for further explorations of these intricate interactions and their possible applications in controlling pathogenic microorganisms within biofilms. Full article

Civil registration of births and deaths underpins people’s legal identity, access to essential services, and evidence-based policy. Over the last two decades, the expansion of the National Health Mission (NHM) and the dramatic increase in institutional deliveries have created new opportunities to link maternal healthcare with critical event documentation. Primary health centres (PHCs) and community health centres (CHCs), which are frequently the initial point of contact for rural households, are emerging as important places for birthing and registration. Despite their expanding importance, the particular role of these grassroots facilities in birth registration results has not been thoroughly investigated. This study addresses that gap by assessing their role in increasing registration coverage among children under the age of five. We analyzed nationally representative data from the National Family Health Survey rounds 4 (2015–2016) and 5 (2019–2021). This study focused on children under five, examining the association between place of delivery and registration status. Descriptive analysis and multivariable logistic regression estimated the odds of registration across delivery settings. Pooled data from both survey rounds captured temporal shifts, and predicted probabilities were calculated for institutional deliveries, adjusting for socio-demographic covariates. The proportion of institutional births occurring in PHCs and CHCs rose from 30.5% to 34.7% between the two survey rounds. Registration among children delivered in these facilities increased from 80.8% to 90.2%, the highest gain among all delivery settings. Regression analysis showed that births in PHCs/CHCs were associated with 38% higher odds of being registered compared to private facilities. States designating PHCs and CHCs as official registrars, such as Delhi, Rajasthan, and Uttar Pradesh, reported the greatest improvements. Lower-level government health facilities are not only advancing safe delivery but also acting as pivotal nodes for civil registration. Their dual function creates a scalable model for integrating healthcare with legal identity creation, supporting equity and accelerating progress toward Sustainable Development Goal 16.9. Full article

High-dimensional structured datasets are common in fields such as semiconductor manufacturing, healthcare, and finance, where redundant and irrelevant features often increase computational cost and reduce predictive accuracy. Feature selection mitigates these issues by identifying a compact, informative subset of features, enhancing model efficiency, performance, and interpretability. This study proposes Maximal Information Coefficient–Simplified Swarm Optimization (MIC-SSO), a two-stage hybrid feature selection method that combines the MIC as a filter with SSO as a wrapper. In Stage 1, MIC ranks feature relevance and removes low-contribution features; in Stage 2, SSO searches for an optimal subset from the reduced feature space using a fitness function that integrates the Matthews Correlation Coefficient (MCC) and feature reduction rate to balance accuracy and compactness. Experiments on five public datasets compare MIC-SSO with multiple hybrid, heuristic, and literature-reported methods, with results showing superior predictive accuracy and feature compression. The method’s ability to outperform existing approaches in terms of predictive accuracy and feature compression underscores its broader significance, offering a powerful tool for data analysis in fields like healthcare, finance, and semiconductor manufacturing. Statistical tests further confirm significant improvements over competing approaches, demonstrating the method’s effectiveness in integrating the efficiency of filters with the precision of wrappers for high-dimensional tabular data analysis. Full article

Thermal conductivity is a crucial parameter for heat transfer in asphalt pavements, especially in cold regions where electrically heated snow-melting systems are used. Steel slag, an industrial by-product with high thermal conductivity, holds significant potential to enhance the thermal performance of asphalt mixtures. However, its thermal behavior is influenced by various factors. This study established a thermal conductivity database consisting of 200 samples from published experimental studies, incorporating data collection, graphical digitization, and physically constrained expansion. Mixture composition, volumetric structure, and steel slag properties were used as input variables, with thermal conductivity as the output. Five machine learning models including k-nearest neighbors regression, decision tree, random forest, support vector regression, and gradient boosting were developed. Among them, random forest and gradient boosting showed the highest accuracy and robustness. Feature importance analysis revealed that steel slag content is the primary factor affecting thermal conductivity, while material properties and gradation parameters play secondary roles. This data-driven framework facilitates the efficient prediction and design of thermal conductivity in steel slag asphalt mixtures, supporting the engineering application of functional asphalt pavements. Full article

This study examines the vocal directivity of singing in Greek across three stylistically diverse genres—operatic/classical, modern/pop, and Byzantine chant—performed under realistic, unconstrained conditions. Directivity data was captured in a hemi-anechoic environment using a 29-microphone hemispherical array, in a setup that allowed singers to make natural, performance-related micro-movements. The applied analysis framework combined sound projection (magnitude of radiated energy across space and frequency) and radiation patterns (normalized spatial distribution) with three established directivity metrics: Horizontal Directivity Index, Front-to-Back Ratio, and Upward-to-Downward Ratio. Results show that while directional shape remains largely consistent across styles and sexes, projection intensity varies systematically as a function of both. Male pop singers exhibit the strongest low-frequency output (125–500 Hz), while female classical and male pop/Byzantine singers display greater frontal focus in the 1–2 kHz range. Classical singers tend toward more balanced projection profiles. Beyond the release of publicly available datasets—including the first directivity measurements of Byzantine chant—this study introduces a structured analysis framework and offers comparative findings that inform vocal science, pedagogy, and spatial audio applications. Full article

Maize is a globally significant cereal crop, while Albic soils in Northeast China are characterized by low available phosphorus (P), poor humus (HS) quality, and constrained maize yield. The synergistic effects of P fertilization on maize yield and HS quality in these soils remain poorly understood. This three-year field experiment was conducted to determine the optimal P application rate for concurrently enhancing crop productivity and HS quality. Four P application rates were established: 0 kg P₂O₅ ha⁻¹ (no P application, P0), 40 kg P₂O₅ ha⁻¹ (low P application, LP), 80 kg P₂O₅ ha⁻¹ (moderate P application, MP), and 120 kg P₂O₅ ha⁻¹ (high P application, HP). Soil nutrients status, HS fractions, dissolved organic matter (DOM) fluorescence characteristics, and structural properties of humic acid (HA) were systematically analyzed following standard analytical procedures. Principal component analysis (PCA) and Pearson correlation analysis were integrated to facilitate comprehensive data interpretation. Results indicated that the MP treatment achieved the highest maize yield (12,257.1 kg ha⁻¹) and soil organic matter (SOM, 14.8 g kg⁻¹) content, with no further yield improvement observed under HP. The MP treatment significantly increased DOM carbon content (C_DOM, 0.350 mg L⁻¹) and its humification index (HIX, 6.80), promoting the transformation of labile DOM into stable HS. HA under MP treatment exhibited enhanced structural stability, as evidenced by a lower H/C ratio (1.72), a higher O/C ratio (0.880), and a reduced E₄/E₆ ratio, reflecting increased aromatic condensation and a greater abundance of oxygen-containing functional groups. Fourier transform infrared (FTIR) spectroscopy and differential thermal analysis (DTA) confirmed that MP improved the structural complexity and thermal stability of HA. In contrast, P0 and LP restricted nutrient availability and HS formation, whereas HP induced soil acidification (pH 5.68) and disrupted HS equilibrium. Principal component analysis (PCA) and correlation analysis revealed significant positive associations between the MP treatment and SOM, C_DOM, and maize yield. This implied that moderate P input promoted stable soil organic carbon accumulation and nutrient availability, synergistically enhancing maize productivity—consistent with the study’s core goal of optimizing P management for concurrent yield and HS quality improvement in Albic soils. Accordingly, this study concluded that moderate P application (80 kg P₂O₅ ha⁻¹) was optimal for Albic soils, synergistically enhancing both maize productivity and HS quality. These findings provided theoretical support for precise P management in sustainable agricultural systems within the Albic soil regions of Northeast China. Full article

This study examines how environmental management systems (EMSs) function as information-based organizational capabilities that drive circular product innovation in manufacturing SMEs operating in an emerging economy. Grounded in the resource-based view (RBV) and institutional theory, the study develops and empirically tests a model linking EMSs to circular-oriented product innovation through the mediating role of green transition, while assessing the moderating influence of policy support. Data were collected through a cross-sectional survey administered in two temporally separated phases to mitigate common method bias, targeting senior managers of ISO 14001-certified manufacturing SMEs registered in the Turkish Trade Register Gazette. A total of 511 valid responses were analyzed. Measurement reliability and validity were established using confirmatory factor analysis, and hypotheses were tested via Hayes’ PROCESS macro. The results indicate that an EMS significantly enhances circular product innovation both directly and indirectly. Green transition emerges as a strong partial mediator, explaining a substantial share of the total effect, highlighting its critical role in translating environmental information, routines, and capabilities into product-level circular outcomes. While organizational sustainability policy does not moderate the EMS–green transition relationship, policy support significantly strengthens the impact of green transition on circular product innovation. Firms operating within more supportive policy environments achieve substantially higher levels of circular innovation. Overall, the study advances the understanding of how information system-enabled capabilities and supportive institutional conditions jointly shape sustainability transitions, offering insights for managers and policymakers seeking to foster circular innovation in manufacturing SMEs. Full article

This study compared the bioenergetic profiles of immature and in vitro–matured bovine cumulus–oocyte complexes (COCs) using Seahorse extracellular flux technology, with the aim of establishing standardized conditions for real-time metabolic assessment during in vitro maturation (IVM). Groups of five COCs were analysed prior to maturation and after 22 h of IVM using the Seahorse XFp Analyzer to measure oxygen consumption rate (OCR, pmoL/min) and extracellular acidification rate (ECAR, mpH/min), providing dynamic readouts of oxidative phosphorylation and glycolysis that extend beyond conventional endpoint assays. To optimize assay performance, three media were first evaluated: TCM199, DMEM/F12, and HEPES-buffered synthetic oviductal fluid (HSOF). HSOF yielded the most reliable readings for immature COCs, whereas TCM199 provided superior conditions for mature COCs. Adhesion strategies were then tested by comparing uncoated wells with wells coated with fibronectin, concanavalin A, or Matrigel^®. Sequential injections of oligomycin and rotenone plus antimycin A enabled partitioning of mitochondrial and glycolytic contributions to ATP production. COC maturation was associated with a clear metabolic shift from glycolysis toward oxidative metabolism. Immature COCs displayed a predominantly glycolytic phenotype, while mature COCs showed increased active mitochondrial ATP production. Adhesion conditions markedly affected the detected metabolic profile: concanavalin A and fibronectin supported effective attachment and were associated with robust energy metabolism, whereas Matrigel^® and poor adhesion were linked to quiescent profiles with low OCR and ECAR signals. Together, these data define practical assay parameters for extracellular flux analysis of COCs and highlight the increasing reliance on mitochondrial function as a hallmark of oocyte maturation, supporting improved metabolic phenotyping for IVM optimization. Full article

Ground-nesting shorebirds face growing pressure from recreational activities in coastal urban areas. We monitored the breeding success of Kentish Plover (Charadrius alexandrinus) and Little Ringed Plover (Charadrius dubius) over six consecutive years (2020–2025) at the Promenade of Sablettes, a heavily visited waterfront in Algiers, Algeria. We combined field surveys with multi-sensor remote sensing analysis using Sentinel-1, Sentinel-2, and Dynamic World data to quantify habitat change. A total of 105 nests were recorded across both species. Breeding success reached 70% during the COVID-19 lockdown period (2020–2021), when human visitation dropped sharply. In contrast, complete reproductive failure occurred in 2022 and 2023, coinciding with resumed tourism and unplanned construction activities. Remote sensing revealed that 80–85% of the study area experienced severe habitat degradation between 2020 and 2025, while suitable refuge zones shrank to less than 10% of the total surface. Fledged chicks consistently moved toward a less disturbed vegetated zone, highlighting its functional importance for brood survival. Our results show that human disturbance is the primary factor limiting breeding success at this site, operating through two pathways: direct disturbance of nesting birds and progressive habitat degradation driven by recreational use and unplanned construction. When disturbance was reduced during the pandemic, the habitat proved fully functional for both species. These findings suggest that simple management measures such as seasonal access restrictions and symbolic fencing during the April–July breeding period could restore breeding conditions without major habitat engineering. This study provides one of the first integrations of long-term field breeding data with landscape-scale remote sensing to document the effects of the anthropause and subsequent recovery on urban shorebird populations. Full article

Left dorsal displacement of the large colon (LDDLC) is a common cause of colic in horses and it is frequently associated with recurrent episodes, with significant implications for horse management, athletic performance, and owner satisfaction. Laparoscopic nephrosplenic space (NSS) ablation is a preventive surgical technique aimed at reducing recurrence in horses with a history of medically or surgically treated LDDLC. This retrospective study evaluated 48 horses that underwent laparoscopic NSS ablation in two Italian Veterinary Teaching Hospitals between 2016 and 2024. Short-term outcomes, including immediate postoperative complications and discharge status, were assessed. Long-term follow-up data were collected via owner questionnaires, focusing on survival, recurrence of colic, post-surgical complications, return to athletic or breeding activity, and owner satisfaction. Most horses were discharged without complications (91.7%), while postoperative colic occurred in 8.3%. Kaplan–Meier estimated one-year post-discharge survival was 83.3%, and 81.3% of horses were alive at last follow-up (range 0.7 months to 8.8 years). Post-discharge complications were reported in 31.2% of horses, most commonly recurrent LDDLC. Return to preoperative athletic or breeding activity was reported in 70.8% of cases, and owner satisfaction was high (83.3%). Time-to-event analysis indicated markedly reduced survival in horses requiring laparotomy during follow-up. Bayesian logistic models suggested lower mortality and fewer post-discharge complications in horses with prior colic surgery, whereas a history of recurrent colic and laparotomy during follow-up was associated with higher mortality and complications. These results indicate that laparoscopic NSS ablation is an effective and safe procedure for long-term management of horses at risk of LDDLC, allowing a high rate of survival, functional recovery, and owner satisfaction, despite the persistence of occasional colic episodes. Full article