Search Results (599)

The growing use of PET strapping in packaging has increased plastic waste, prompting interest in its reuse in cement-based materials. This study evaluates waste PET strapping powder as a partial replacement for natural sand in cement mortar. Mortars were prepared with three water–cement ratios (0.4, 0.5, and 0.6) and four replacement levels (0%, 5%, 10%, and 15%). Slump, flow, compressive strength, flexural strength, ultrasonic pulse velocity (UPV), four-point resistivity, and sulphate resistance were examined at different curing ages. Increasing PET content reduced slump and flow, indicating lower workability. It also decreased compressive and flexural strengths, with flexural strength showing a greater reduction. UPV declined as PET replacement increased, which was attributed to the combined effects of acoustic-property contrast between PET and the cementitious matrix, interfacial wave scattering, and local microstructural defects. However, PET increased electrical resistivity and reduced sulphate-related weight loss, indicating lower continuity of ion-conducting pathways and potentially improved resistance to the transport of aggressive ions under the adopted test conditions. SEM observations showed limited interfacial defects at 5% PET, whereas higher contents produced a more porous interfacial transition zone. Overall, the mix with 5% PET and W/C = 0.5 showed the best balance of properties, supporting the reuse of PET strapping powder as a sustainable sand replacement. Full article

Fracture in concrete is inherently a multi-stage process, yet traditional three-stage frameworks do not explicitly distinguish between micro-crack development and macro-crack propagation, particularly under varying ligament length conditions. The influence of ligament length (notch-to-depth ratios of 0.0, 0.2, 0.3, 0.4, and 0.5) on the crack propagation characteristics in notched concrete beams under three-point bending is investigated. Three-dimensional digital image correlation (3D DIC) was employed to monitor full-field displacement and strain, enabling the evaluation of key fracture parameters including horizontal displacement, crack mouth opening displacement (CMOD), horizontal strain, fracture process zone (FPZ) length, macro-crack length, and total fracture zone length. A high-magnification industrial camera (100×) was simultaneously used for real-time observation of the notch tip. Based on the evolution of these parameters, the fracture process was divided into four distinct stages: linear elastic stage, micro-crack initiation and propagation stage, macro-crack initiation and propagation stage, and complete failure stage. The industrial camera observations confirmed macro-crack initiation at approximately 60% of the post-peak load, validating the proposed four-stage division. Quantitative results show that increasing the notch depth ratio from 0.0 to 0.5 reduces the peak load by approximately 30–40% and decreases the nominal stress proportionally. The FPZ was found to be fully developed at the 60% post-peak load threshold, after which it diminished as macro-crack propagation dominated. Aggregate bridging, crack deflection, and crack branching were consistently identified as the primary toughening mechanisms governing the ligament effect. The crack propagation mechanisms in the four stages are controlled by the combined effects of front free boundary effect, stress concentration effect, ligament effect, and back free boundary effect. These findings provide a refined understanding of concrete fracture that can inform the safety assessment and design of concrete bending members in infrastructure construction. Full article

External corrosion of buried ferrous water mains remains the dominant driver of structural failure in aging water distribution networks, yet the mechanisms linking soil physical and chemical heterogeneity to corrosion kinetics and product phase evolution have not previously been synthesized into a unified critical framework. This review evaluates three partially competing accounts of electrochemical degradation—anodic dissolution coupled to oxygen reduction within porous rust layers, redox cycling of iron oxide phases driven by seasonal soil moisture fluctuations, and microbially influenced corrosion (MIC) mediated by direct extracellular electron transfer (EMIC) and chemical metabolite pathways (M-MIC)—and assesses the weight of evidence for each. We demonstrate that corrosion products retain electrochemical activity long after formation, functioning as dynamic redox mediators that continue the reactions responsible for their own growth: the reduction of lepidocrocite under anoxic conditions regenerates Fe²⁺ ions that sustain anodic dissolution and catalyze oxygen reduction, while repeated soil moisture cycles drive the irreversible transformation of γ-FeOOH to Fe₃O₄, which fundamentally alters the conductivity and cathodic capacity of the rust layer. The widely cited universal critical-moisture threshold of 65% water-holding capacity (WHC) is evaluated and found to be a single-point approximation contradicted by texture-resolved experimental data that show the critical degree of saturation ranges from S_r ≈ 0.5 in sand to S_r ≈ 0.8 in clay. Modern machine learning analyses of field corrosion databases confirm that chloride content, pH, pipe-to-soil potential, and water content are the four highest-ranked predictors of maximum pit depth, consistent with the mechanistic framework developed here. The classical cathodic depolarization model of SRB-driven corrosion is evaluated against EMIC evidence and found insufficient: measured pure-culture SRB corrosion current densities range from 14 to 135 µA cm⁻², not the milliampere-level values reported in some earlier reviews. An explicit research agenda is proposed to address the five most consequential unresolved mechanistic questions. Full article

Rapid and accurate identification of mine water inrush sources is critical for hazard control in underground coal mining. Conventional Fisher discriminant analysis is often limited by feature redundancy and multicollinearity when applied to small-sample, high-dimensional hydrochemical data. To address this, we propose GWO–Fisher, a hybrid model integrating the Grey Wolf Optimizer (GWO) with Fisher discriminant analysis. The model employs correlation-based pre-screening followed by global optimization, using a fitness function that combines Fisher accuracy with a feature-size penalty, to achieve a compact and interpretable feature set. Trained on data from the Xiegou Coal Mine (Shanxi, China), it reduced 17 hydrochemical indicators to 12 key features, achieving 92.98% training accuracy and 86.21% test accuracy—an improvement of 10.35 percentage points over conventional Fisher. When independently validated across four mines in three spring domains, the model maintained over 83% accuracy, consistently selecting TDS, K⁺, and HCO₃⁻ as core features. Misclassification patterns were cross-domain consistent and linked to hydrogeological conditions. The proposed GWO–Fisher model balances predictive accuracy with hydrogeological interpretability, demonstrating reliable performance across both single-mine and cross-spring-domain scenarios. Full article

Agricultural steel pipelines are essential components of pressurized irrigation systems, yet localized corrosion-induced pinholes severely compromise their structural integrity by creating critical stress concentrations. To address the lack of performance-based maintenance guidelines, this study experimentally evaluates three repair techniques—a multi-joint hinge clamp, a GFRP composite sleeve, and overlay welding—applied to steel pipes containing simulated pinhole defects representing 6% and 10% circumferential damage. Four-point bending and uniaxial tensile tests were conducted to simulate transverse overburden and longitudinal axial loading encountered in buried pipelines. Results reveal that repair effectiveness strongly depends on both loading mode and damage severity. At 6% damage, all methods effectively restored bending capacity, with the GFRP sleeve achieving near-complete recovery. Under tensile loading, however, external-confinement methods provided limited ductility improvement because they lack a direct axial load-transfer path. In contrast, overlay welding consistently achieved substantial structural restoration by eliminating stress concentrations and shifting fracture to the parent pipe material. Furthermore, a significant transition in repair performance was observed near the 6% damage level, beyond which confinement-based repairs exhibited reduced efficacy. These findings demonstrate that repair performance cannot be reliably assessed from bending behavior alone and highlight the importance of considering both loading conditions and damage severity in rehabilitation design. The study provides a quantitative framework for load-specific pipeline rehabilitation strategies. Full article

Background/Objectives: Early handwriting and motor skills underpin later academic success, yet robust evidence for psychomotor programs in preschoolers is limited. This study examined whether participation in a six-week psychomotor intervention was associated with changes in graphomotor performance, writing proficiency, and motor competence in preschool children. Methods: This non-randomized quasi-experimental study included pre- and post-intervention assessments and a control group. Thirty-four preschoolers were assigned by class to an intervention group (n = 19) or a control group (n = 15). For six weeks, the intervention group completed three 50 min psychomotor sessions per week targeting fine- and gross-motor abilities, whereas the control group continued its usual school routine. Graphomotor performance (Pascual Graphomotor Test), writing proficiency (seven-item teacher scale) and motor competence (Movement Assessment Battery for Children-2) were assessed one week before and after the program. Results: The intervention group showed significant improvements in graphomotor performance and all motor-skill tasks assessed. Between-group comparisons of pre–post change favored the intervention group for the total graphomotor score (mean difference = −3.14 points, 95% CI [−4.59, −1.68]; p < 0.001; Hedges’ g = −1.48) and for all four motor-skill tasks (p ≤ 0.019). At post-intervention, pencil grip was the only writing proficiency item showing a significant between-group difference (p = 0.002; Cramér’s V = 0.617), whereas no significant differences were observed for the remaining items. Conclusions: A psychomotor intervention was associated with greater improvements in motor competence and graphomotor performance compared with the control condition. However, evidence for broader improvements in writing proficiency, including handwriting legibility, was limited. Although pencil grip differed between groups at post-intervention, this finding should be interpreted cautiously because the groups already differed at baseline. Full article

Climate change has become one of the most urgent challenges of the 21st century, shaping environmental, economic, and social dynamics on a global scale. In the Mediterranean basin, temperatures have risen by 1.5 °C, with projections suggesting a further increase of 5.6 °C by 2100. The building sector represents a critical intervention point, accounting for 30% of final energy consumption and 27% of global carbon dioxide emissions. While passive strategies mitigate these impacts, current energy policies fail to consider future variations in heating and cooling demand due to climate change. Using OpenStudio and EnergyPlus, three reference models (small office, residential building, and hospital) were simulated across five Spanish climatic areas (Almería, Córdoba, Cáceres, Lleida, León). Current conditions were compared against 2050 projections under four Shared Socioeconomic Pathways (SSP1-2.6 to SSP5-8.5) utilizing the morphing method. The results revealed a systemic shift toward cooling-dominated profiles. Small office heating demand drops by 18–34%, while cooling demand increases by 80–274%. Residential heating decreases by 19–36%, while cooling increases by 85–706%. Hospitals show milder relative variations, yet cooling demand rises 64–114%. These findings, based on thermal energy demand (kWh/m²), emphasize the need for climate-responsive design and efficient retrofitting. Conclusions regarding peak power grid stress, carbon emissions, or energy poverty are indirect implications; translating thermal demand to final energy, primary energy, or emissions requires accounting for HVAC system efficiency, energy source mix, and emission factors, which are outside the scope of this study. Full article

Ammonium nitrogen (NH₄⁺-N) contamination in groundwater beneath chemical industrial parks exhibits extreme spatial heterogeneity, yet the comparative effectiveness of spatial prediction methods under such conditions remains poorly understood. At a chemical industrial park in a region of Shanxi Province, northern China, we analyzed 133 monitoring wells sampled across four campaigns (April–October 2024) at two aquifer depths. Global Moran’s I (0.040–0.118) and variogram nugget ratios (>75%) indicated weak spatial autocorrelation. Consequently, on the raw concentration scale, all six geostatistical methods yielded near-zero or negative leave-one-out cross-validation (LOO-CV) R². Evaluated on the log₁₀ scale, machine learning (ML) models achieved positive predictive skills, with Extreme Gradient Boosting (XGBoost) performing best (R² ≈ 0.75). Three hybrid ML–kriging methods produced physically coherent plume surfaces while retaining their predictive skills; the April upper-layer result (R² ≈ 0.67)—the only campaign without retained within-well information—best represents spatial generalization, whereas the higher later-campaign values (R² > 0.97) are optimistic. Exceedance probability mapping based on XGBoost (area under the ROC curve, AUC = 0.959) revealed a persistent high-risk zone. Because the geostatistical and ML metrics span different response scales and validation schemes, their comparison is indicative rather than a direct ranking. Spatial autocorrelation diagnostics should precede method selection at point-source-dominated industrial sites. Full article

Service-Based Architectures (SBAs) in 5G core and cloud-native deployments require differentiated treatment for service classes with heterogeneous latency, reliability, and throughput expectations. Although HTTP/3 over QUIC is an important evolution of the HTTP ecosystem, HTTP/2 remains operationally relevant in SBA environments where TCP/TLS-based infrastructures and 3GPP service-based interfaces continue to rely on HTTP/2 communication. This paper therefore focuses on HTTP/2 priority signaling and the problem of translating application-level Service Level Agreement (SLA) policies into protocol-level priority metadata. To address this problem, the paper presents an SLA-aware priority management system built around the RFC 9218 extensible prioritization scheme, specifically its urgency and incremental parameters. The system integrates three coordinated subsystems: a rule-based Priority Classification Engine (PCE), a feedback-driven Dynamic Priority Mapping Algorithm (DPMA), and a runtime priority-update manager that applies bounded priority adjustments under changing network and load conditions. The revised evaluation reports a 7200-observation baseline campaign covering four operating modes, ten service classes, nine network profiles, and twenty repetitions per service–profile–mode combination, together with a 14,880-observation scalability and overhead campaign across increasing concurrent-stream levels. Compared with the unmanaged HTTP/2 baseline, DPMA reduced mean latency by 24.8%, P95 latency by 35.1%, P99 latency by 38.0%, and SLA violations by 19.9 percentage points. Compared with the legacy RFC 7540 baseline, DPMA reduced mean latency by 39.0%, P95 latency by 49.3%, P99 latency by 49.9%, and SLA violations by 21.1 percentage points. Compared with the static RFC 9218 baseline, DPMA reduced mean latency by 38.7%, P95 latency by 48.1%, P99 latency by 50.6%, and SLA violations by 21.4 percentage points. The scalability analysis shows that DPMA maintained P95 latency between 126.8 ms and 128.2 ms over the tested 1–100 concurrent-stream range, with priority-update decision overhead below 0.004 ms per request. The results indicate that SLA-aware use of RFC 9218 priority metadata can improve latency and SLA-compliance behavior in controlled SBA-like HTTP/2 environments while preserving a transparent and auditable prioritization policy. Full article

In this paper, we introduce a general class of quadrilateral total pairwise $\phi$-contractions and investigate fixed-point results for such mappings in metric and semimetric spaces endowed with multiple distinct metrics. We establish several fixed-point theorems for these contractions and show that the obtained results extend beyond classical metric spaces to encompass ultrametric spaces and distance spaces equipped with power-type triangle functions. Furthermore, within the framework of metric spaces, we study the existence of solutions to fractional boundary-value problems with prescribed boundary conditions by employing mappings satisfying the quadrilateral total pairwise contraction condition. Several well-known results, including the Banach contraction principle, the Boyd–Wong fixed-point theorem, and various related three-point and four-point contraction results, are recovered as particular cases of our theorems. Full article

Background: Obesity is a chronic condition that compromises health and quality of life, with physical exercise representing a relevant therapeutic strategy in its management. Functional training (FT) has been adopted as a modality that integrates neuromuscular and cardiorespiratory stimuli, promoting both physical and psychosocial benefits. However, gaps remain in the literature regarding the effects of FT on body composition in individuals with excess weight. In this context, a systematic review was conducted to analyze the current state of scientific knowledge on this approach. Methods: Randomized controlled clinical trials investigating FT were selected, including interventions classified as high-intensity functional training (HIIT-F), multicomponent programs, and CrossFit-like interventions when they fulfilled the predefined FT eligibility criteria. Participants were required to be between 18 and 65 years of age, physically independent, and in generally good health. The systematic search was conducted in the PubMed/MEDLINE, Embase, Web of Science, Cochrane Library, PEDro, and LILACS databases. The risk of bias (RoB 2.0) and the certainty of the evidence (GRADE) were assessed. Results: A total of 2,972 records were identified. Seven studies met the eligibility criteria, comprising 296 participants. Two randomized controlled trials (61 participants) were eligible for meta-analysis. The pooled analysis demonstrated a significant reduction in body fat percentage (%BF) in favor of FT/HIIT-F compared with non-exercising controls (mean difference = −4.44 percentage points; 95% confidence interval −7.08 to −1.80; p = 0.001). Risk of bias assessment showed moderate methodological limitations across studies. None were classified as low risk. Three had high risk due to missing outcome data and deviations from intended interventions, whereas four showed some concerns related to allocation concealment and analysis reporting. Bias in outcome measurement was consistently low. Conclusions: Current evidence suggests that FT/HIIT-F may be associated with reductions in %BF among adults with overweight or obesity. However, these findings should be interpreted with caution because the certainty of the evidence was rated as very low according to the GRADE approach, the quantitative synthesis included only two studies, and important methodological limitations were identified. As the available data are predominantly derived from female participants, the applicability of these findings to men remains uncertain. Full article

Courtyard enclosure form and façade orientation are associated with near-wall microclimatic fluctuation and autumn façade-greening dynamics. This exploratory study monitored Boston ivy at six sample points in two-sided, three-sided, and four-sided enclosures with south-, west-, and north-facing façades. Near-wall temperature and relative humidity were recorded every 5 min, and fixed-ROI time-series imagery quantified leaf color change and defoliation. Mean thermal–humidity conditions varied modestly; daily temperature range varied from 8.79 ± 2.35 to 17.90 ± 7.21 °C and daily relative humidity range from 18.46 ± 4.59% to 29.81 ± 7.38%. DI50 occurred from 20 October to 1 November and DI80 from 6 to 25 November. Spearman analysis of 60 matched daily observations showed stronger associations of mean thermal–humidity indicators than fluctuation indicators with phenological indicators. RMedian correlated positively with LCR (ρ = 0.70), while DI correlated negatively with RMedian and Color Index (ρ = −0.50 and −0.53). Because enclosure form and façade orientation were partly coupled, their effects could not be separated. Overall, sample points differed more clearly in thermal–humidity fluctuation than in mean conditions, while phenological differences reflected enclosure form, façade orientation, near-wall thermal–humidity conditions, and exposure conditions. Full article

Gas concentration in coal mine return-air corners is affected by ventilation, mining disturbance and gas drainage conditions, and it shows strong nonstationarity, local fluctuation and dynamic multi-point correlations. To improve frequency information separation, monitoring point relationship modeling, and short-term prediction accuracy, a variational mode decomposition (VMD)-based dual-branch spatiotemporal graph method is proposed. Gas concentrations from four key monitoring points are used as inputs, and the return-air corner gas concentration is taken as the output. First, the raw series are decomposed by VMD and reconstructed into low- and high-frequency components. Then, two branches are built for different frequency components. The low-frequency branch combines adaptive graph learning, graph convolution and gated recurrent units to extract global variation features, while the high-frequency branch combines graph attention and gated recurrent units to capture local disturbance features. Finally, a feature-fusion module generates multi-step predictions, and a lightweight short-term warning strategy is developed based on the predicted values. The proposed model achieves MAE, RMSE and R² values of 0.0338, 0.0471 and 0.9499 in one-step prediction, respectively, and outperforms GRU, LSTM, GCN-GRU, GAT-GRU, VMD-GRU, Informer and STGCN under three-step and six-step conditions. Cross-dataset validation and inference time analysis indicate good adaptability and online prediction potential. Full article

Traffic simulation models require calibration to capture local driving behavior, particularly in developing countries where conditions differ from Western defaults. This study calibrates three car-following models—Krauss, Wiedemann 99 (W99), and Intelligent Driver Model (IDM)—with lane-change parameters for heterogeneous traffic on six two-lane two-way roads in Egypt’s Nile Delta. A sensitivity analysis reduced eight lane-change parameters to three critical ones: lcOpposite, lcSpeedGain, and lcStrategic. A Genetic Algorithm then optimized car-following and lane-change parameters jointly across multiple seeds and generations. The best configurations achieved mean absolute percentage errors of 8.79% (IDM), 8.94% (W99), and 10.56% (Krauss), indicating that IDM and W99 performed similarly under the original four-metric validation, while Krauss was less accurate overall and exceeded the overtaking-rate threshold. suggesting calibration methodology matters more than model choice. Minimum standstill gap (minGap) treatment varied by model: freeing it improved IDM and Krauss performance, while fixing it at 1.50 m benefited W99. Constraining minGap in IDM increased error by 2.06 percentage points and altered parameter sensitivity, with lcStrategic becoming dominant and tau showing reduced sensitivity. Notably, SUMO’s uncalibrated Krauss defaults achieved 10.11% error under understaturated conditions, though this should not extend to congested scenarios. Simulated standard deviations underestimated observed variability, primarily due to aggregation mismatches rather than model inadequacy. Full article

With the continuous embedding of small- and medium-sized manufacturing enterprises (SMMEs) into manufacturing platform ecosystems, selecting the optimal resource reconstruction model has become a critical decision for both platforms and SMMEs. However, the existing literature provides limited insight into how different resource types compare in terms of their efficiency in enabling capability reconstruction. Addressing this gap, this paper constructs asymmetric Stackelberg game-theoretic models for the platform–SMME collaborative system and systematically investigates efficiency differentiation and strategy selection under three resource models: the fund resource model, the knowledge resource model, and the fund and knowledge hybrid model. Drawing on dynamic capability theory, the models formalize the transmission paths through which heterogeneous resources affect SMMEs’ capability reconstruction, and derive the equilibrium conditions governing resource input, pricing, revenue-sharing, and payoff outcomes. The findings reveal three key insights. (1) As dynamic capability matures and price sensitivity rises, the platform’s optimal strategy shifts systematically from fund resource model through hybrid model to knowledge resource model, requiring dynamic model switching aligned with the SMME’s capability path and market conditions. (2) Fund-driven improvement operates through two paths, while knowledge-driven improvement operates through four paths and the upstream paths, creating a win-win zone and downstream paths generating diverging interests. (3) Dynamic capability, particularly conversion efficiency of “information-management,” reduces resource input while increasing both parties’ payoffs, shifting the strategy from a fund resource model to a knowledge resource model. The findings point to a shift from resource provision to capability-driven collaboration, requiring dynamic model switching by platforms, precision matching by SMMEs, and shared investment in dynamic capabilities for sustainable mutual benefit. Full article