Search Results (1,226)

In lateral-joint-widening projects of multi-span continuous concrete box girder bridges, significant discrepancies in longitudinal shrinkage, creep deformation, and vertical displacement between the existing and newly added bridge sections can lead to stress concentration and subsequent concrete cracking. Notably, such incompatibility often results in pronounced overall lateral bending deformation, which compromises the structural safety and service reliability of the widened bridge. To address these challenges, this study proposes a novel sliding-type transverse connection structure. This innovative connection enables the independent development of longitudinal shrinkage and creep deformation in the new bridge superstructure relative to the old one through a sliding mechanism, thereby effectively mitigating stress concentration and minimizing overall bending deformation caused by differential deformations. To validate the feasibility and elucidate the load transfer mechanism of the proposed structure, both scaled model tests and finite element simulations were conducted. The results indicate that the connection not only effectively coordinates longitudinal deformation differences and accommodates vertical deformation between the flange plates of the new and old bridges, but also ensures efficient transverse load transfer through shear force transmission. The structural behavior is primarily governed by shear stress distribution. These findings demonstrate that the sliding-type transverse connection significantly improves deformation compatibility in bridge widening applications, thereby enhancing the mechanical performance and safety reliability of the overall structure. Full article

Background and Objectives: Urinary tract infections (UTIs) are a major cause of emergency department (ED) visits and hospital admissions among older adults. Although most seniors present hemodynamically stable, a sizeable fraction deteriorate during hospitalization, and no ED-specific tool exists to identify those at greatest risk. We sought to determine risk factors for in-hospital mortality in this population and to develop a predictive model. Materials and Methods: We analyzed the MIMIC-IV-ED database (2011–2019) and enrolled culture-confirmed UTI patients aged ≥ 65 years who were hemodynamically stable—defined as a systolic blood pressure ≥ 100 mm Hg without vasopressor support. Demographics, comorbidities, triage vital signs, and initial laboratory tests were extracted. Least Absolute Shrinkage and Selection Operator (LASSO) regression with 10-fold cross-validation was performed for variable selection. Discrimination was quantified with the C-statistic, calibration with the Hosmer–Lemeshow test, and clinical utility with decision curve analysis. Internal validation was assessed via 1000-sample bootstrap resampling. Results: Among 1571 eligible encounters (median age 79 years, 33% male), in-hospital mortality was 4.5%. LASSO selected eight variables; six remained significant in multivariable analysis: age, systolic blood pressure, oxygen saturation, white blood cell count, red cell distribution width, and blood urea nitrogen. The predictive nomogram demonstrated a C-statistic of 0.73 (95% CI 0.66–0.79) and outperformed traditional early warning scores. Conclusions: A six-variable nomogram may stratify mortality risk in hemodynamically stable older adults with UTI. Because the model was developed in a single U.S. tertiary-care ED, it remains hypothesis-generating until validated in external, multicenter cohorts to confirm generalizability. Full article

Poly(N-isopropylacrylamide) (PNIPAAm) hydrogels exhibit temperature-responsive volume changes near physiological temperature, but their low mechanical strength in the swollen state limits use in structurally demanding biomedical applications. In this study, we systematically investigated poly(NIPAAm-co-acrylamide), P(NIPAAm-co-AAm), hydrogels with varying AAm-to-NIPAAm ratios to explore the compositional trade-offs between thermal responsiveness and mechanical performance. Hydrogels were synthesized under fixed crosslinker and water content conditions, and evaluated through compressive mechanical testing, thermal swelling analysis, and crosslinking density estimation. Our results show that increasing AAm content enhances mechanical strength and stiffness but reduces the magnitude of temperature-induced volumetric shrinkage. An intermediate comonomer formulation demonstrated an optimal balance, maintaining both sufficient mechanical integrity for transdermal microneedle insertion and a reversible volume transition. This study highlights the potential of compositional tuning in hydrogel systems to meet the competing demands of responsiveness and durability in advanced biomedical applications. Full article

Microbial Induced Carbonate Precipitation (MICP) is regarded as a promising eco-friendly alternative to traditional Portland cement for soil stabilization. However, the feasibility of applying bio-cemented soil as a road base material remains inadequately studied, particularly in terms of the relationships between MICP treatment parameters—such as solution content, curing age, and the ratio of bacterial solution (BS) to cementation solution (CS) —and key mechanical and durability properties under realistic road conditions. In this study, an optimal curing condition for bio-cemented sand was first determined through unconfined compression strength (UCS) tests and calcium carbonate content (CCC) determination. Subsequently, dynamic triaxial tests were conducted to evaluate its resistance to cyclic loading. Further road performance tests, including splitting tensile strength, freeze-thaw resistance, temperature shrinkage, and arch expansion assessments, were carried out to comprehensively evaluate the material’s applicability. Scanning electron microscopy (SEM) was employed to elucidate the microstructural mechanisms underlying strength development. The results show that the strength (4.28 MPa) of bio-cemented sand cured under optimal conditions (12% bio-cured solution content, a BS-to-CS ratio of 1:4 and 7-d curing age) satisfies the criteria for road base applications. MICP treatment significantly improved the dynamic properties of aeolian sand (AS), reducing the cumulative plastic axial strain (ε_p) by nearly 11–46% and increasing the dynamic elastic modulus (E_d) by approximately 7–31% compared to untreated sand. The material also demonstrates satisfactory performance across all four road performance metrics. Microstructural analysis reveals enhanced interparticle bonding due to calcium carbonate precipitation, with samples prepared near the optimum moisture content exhibiting superior integrity and strength. Overall, bio-cemented sand demonstrates excellent potential as a sustainable road base material. These findings provide a theoretical foundation for practical applications of similar bio-cemented soils in road engineering. Full article

The selection of tree species for afforestation in Mediterranean environments involves challenges related to adaptability, impact on soil properties, and overall environmental quality. Cupressus lusitanica has been recognized for its rapid growth, environmental resilience, and versatile applications, positioning it as a promising candidate for these regions. Although it has been used for afforestation in Northeast Portugal since the 1990s, no comprehensive studies have evaluated its performance under local conditions. To address this knowledge gap, this study assessed a 14-year-old C. lusitanica stand in Northeast Portugal. The wood’s anatomical, physical, chemical, and mechanical properties, as well as biomass production, were evaluated. The species showed superior radial growth and adaptability compared with other species under similar environmental conditions. Despite exhibiting lower fiber length (1.6 mm) and basic wood density (404 kg/m³), shrinkage values fell within the typical range for softwoods. Nevertheless, a marked tendency for warping was observed. The extractive content was relatively high (5.1%), with the ethanol-soluble fraction being predominant (3.6%). Mechanical tests revealed low values for both Modulus of Elasticity (MOE) (3592.5–3617.1 MPa) and Modulus of Rupture (MOR) (57.7–68.9 MPa), with both properties significantly influenced by knot presence. Given the results obtained, the species C. lusitanica, despite its low wood density and potential limitations in use, exhibits remarkable growth and adaptability, which confer a high potential for biomass production and carbon sequestration, as well as potential applications of its wood in reconstituted panels and fiber- or particle-based boards. Full article

This study prepared alkali-activated cementitious composites using high-whiteness kaolin, sodium water glass, and NaOH as the main raw materials. Multiple methods, including FE-SEM, XRD, whiteness/light transmittance tests, shrinkage rate measurements, DSC-TG, flexural strength testing, and hydrolysis resistance testing, were used to investigate the effects of curing temperature and time on material properties. The optimal parameters were determined as kaolin calcined at 1100 °C, activator modulus 1.25, calcined kaolin-to-activator ratio 1:1, and 2.5% deionized water added for molding. The optimal sample achieved a flexural strength of 23.81 MPa, with the bonding strength to porcelain 60.17 times that of gypsum and 1.90 times that of kaolin-bonded materials. Curing below 100 °C slowed polymerization, while temperatures exceeding 100 °C accelerated it, with violent reaction at 120 °C. Curing beyond 10 h reduced flexural strength. A large number of cage-like, ‘zeolite-like’ structures formed, closely relating to material properties. This study provides references for ceramic restoration materials. Full article

Injection molding is widely used for mass-producing plastic components, demanding precise thermal control to optimize cycle times and part quality. Traditional CNC-machined molds limit design flexibility and restrict advanced cooling features like conformal cooling channels (CCCs). Integrating CCCs improves cooling performance, reduces cycle times, and offers more efficient, cost-effective designs. Additive manufacturing (AM), especially Metal-Fused Filament Fabrication (Metal-FFF), offers geometries unattainable by machining. While most mold research focuses on Laser Powder Bed Fusion (LPBF), the feasibility of Metal-FFF molds remains underexplored. This study presents the design, fabrication, and experimental evaluation of an injection mold produced via Metal-FFF with integrated CCCs. The process included computational design, resistance simulations, fabrication, debinding, sintering, and post-processing, followed by testing under injection molding conditions. Results show that Metal-FFF molds with CCCs boost cooling efficiency, cutting cycle times by about 30% compared to conventional molds, while offering greater design freedom and economic benefits. Nonetheless, issues such as porosity and shrinkage need further refinement to fully leverage this technology for industrial use. Full article

Canvases and preparation layers consist of diverse materials that respond differently to mechanical stress. In a canvas painting, elongations and shrinkages can cause deformations—either recoverable or permanent—as well as shear stresses and potential cracks, which may weaken the overall structure. This study aims to better understand the interaction between the canvas and preparatory strata in terms of mechanical behavior. To achieve this, a set of canvases and the same types of canvases with preparation layers were selected. Two types of linen and two types of polycotton were chosen to represent contemporary materials currently available in fine-art stores. Additionally, an accelerated aging process was applied to the samples to compare their mechanical response before and after aging. By examining the mechanical behavior of both primed and unprimed canvases through dynamometric tests, a method to evaluate the mechanical degradation attributable to the ground layer has been developed and explained in detail. This method is applicable to cases with similar characteristics. Analysis of the force/elongation graphs for the ground layer allows for the calculation of how this layer evolves with increasing elongation and how the mechanical degradation worsens. The results highlight the differing mechanical behaviors among the analyzed canvas types in both the warp and weft directions, as well as the degradation values resulting from both the aging process and the dynamometric testing of the canvases and ground layers. Full article

The technological potential and sustainability of red clays from the Taveiro region (Coimbra, Portugal) for structural ceramic applications have been investigated. Thirteen representative samples granulometric, mineralogical, chemical analysis, and technological characterization were conducted to determine the suitability for extrusion-based ceramics, aligned with circular economy and climate goals (e.g., PNEC2030, RNC2050). The samples exhibited a high fine fraction content (<0.002 mm up to 76%) and plasticity index (PI; up to 41%), associated with significant smectite, illite, and kaolinite content. Bulk mineralogy was dominated by Σ phyllosilicates (up to 77%) and quartz (12%–29%), while chemical analyses showed high SiO₂ and Al₂O₃ content, moderate Fe₂O₃, and low CaO/MgO, typical of aluminosilicate clays for red ceramics. High cation exchange capacity (CEC; up to 49 meq/100 g) and specific surface area (SSA; up to 83 m²/g) reflected smectite-rich samples. Firing tests at 900 and 1000 °C demonstrated decreasing water absorption and shrinkage with increased temperature, with some samples yielding lower porosity and higher strength (~12 MPa), confirming suitability for bricks and tiles. Two samples showed higher plasticity but greater shrinkage and porosity, suggesting applicability in porous ceramics or blends. This work highlights the role of mineralogical and technological indicators in guiding the eco-efficient use of georesources for ceramic manufacturing. Full article

Objective: Sarcopenic obesity (SO) is a combination of depleted skeletal muscle mass and obesity, with a high prevalence, undetected onset, challenging diagnosis, and poor prognosis. However, studies on SO in cancer settings are limited. We aimed to explore the association between SO and mortality and to investigate potential predictors involved in the development of SO, with a further objective of constructing a model to detect its occurrence in cancer patients. Methods: The data of 1432 cancer patients from the National Health and Nutrition Examination Survey (NHANES) from the years 1999 to 2006 and 2011 to 2016 were included. For survival analysis, univariable and multivariable Cox proportional hazard models were used to examine the associations of SO with overall survival, adjusting for potential confounders. For machine learning, six algorithms, including logistic regression, stepwise logistic regression, least absolute shrinkage and selection operator (LASSO), support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost), were utilized to build models to predict the presence of SO. The predictive performances of each model were evaluated. Results: From six machine learning algorithms, cancer patients with SO were significantly associated with a higher risk of all-cause mortality (adjusted HR 1.368, 95%CI 1.107–1.690) compared with individuals without SO. Among the six machine learning algorithms, the optimal LASSO model achieved the highest area under the curve (AUC) of 0.891 on the training set and 0.873 on the test set, outperforming the other five machine learning algorithms. Conclusions: SO is a significant risk factor for the prognosis of cancer patients. Our constructed LASSO model to predict the presence of SO is an effective tool for clinical practice. This study is the first to utilize machine learning to explore the predictors of SO among cancer populations, providing valuable insights for future research. Full article

Background: Pan-drug-resistant (PDR) Acinetobacterinfections are an escalating ICU threat, demanding both patient-level triage and facility-wide forecasting. Objective: The aim of this study was to build a dual-scale AI framework that (i) predicts PDR status at infection onset and (ii) forecasts hospital-level PDR burden through 2027. Methods: We retrospectively analyzed 270 Acinetobacter infection episodes (2020–2024) with 65 predictors spanning demographics, timelines, infection type, resistance-class flags, and a 25-drug antibiogram. TabTransformer and XGBoost were trained on 2020–2023 episodes (n = 210), evaluated by stratified 5-fold CV, and externally tested on 2024 episodes (n = 60). Metrics included AUROC, AUPRC, accuracy, and recall at 90% specificity; AUROC was optimism-corrected via 0.632 + bootstrap and DeLong-tested for drift. SHAP values quantified feature impact. Weekly PDR incidence was forecast with an attention–LSTM model retrained monthly (200 weekly origins, 4-week horizon) and benchmarked against seasonal-naïve, Prophet, and SARIMA models (MAPE and RMSE). Quarterly projections (TFT-lite) extended forecasts to 2027. Results: The CV AUROC was 0.924 (optimism-corrected 0.874); an ensemble of TabTransformer + XGBoost reached 0.958. The 2024 AUROC fell to 0.586 (p < 0.001), coinciding with a PDR prevalence drop (75→38%) and three covariates with PSIs > 1.0. Isotonic recalibration improved the Brier score from 0.326 to 0.207 and yielded a net benefit equivalent to 26 unnecessary isolation-days averted per 100 ICU admissions at a 0.20 threshold. SHAP highlighted Ampicillin/Sulbactam resistance, unknown acquisition mode, and device-related infection as dominant drivers. The attention–LSTM achieved a median weekly MAE of 0.10 (IQR: 0.028–0.985) vs. 1.00 for the seasonal-naïve rule, outperforming it on 48.5% of weeks and surpassing Prophet and SARIMA (MAPE = 6.2%, RMSE = 0.032). TFT-lite projected a ≥ 25% PDR tipping point in 2025 Q1 with a sustained rise in 2027. Conclusions: The proposed framework delivers explainable patient-level PDR risk scores and competitive 4-week and multi-year incidence forecasts despite temporal drift, supporting antimicrobial stewardship and ICU capacity planning. Shrinkage and bootstrap correction were applied to address the small sample size (EPV = 2.1), which poses an overfitting risk. Continuous recalibration and multi-center validation remain priorities. Full article

Banana (Musa paradisiaca) is among Ecuador’s most important export commodities, globally recognized for its high nutritional value. To extend shelf life and reduce physiological and microbiological deterioration, bananas are typically harvested at the green stage and stored under controlled conditions using plastic packaging. This study evaluated the combined effect of an antifungal coating based on cinnamon essential oil and polyethylene bags of different densities (LDPE and HDPE) over a 28-day storage period. Eight treatments were tested, including various coating–packaging combinations from three producers, as well as plastic-only and unpackaged controls. Physicochemical results showed that the antifungal coating combined with LDPE significantly reduced weight loss, peel and length shrinkage, and firmness decline. Color retention (ΔL*, Δa*, Δb*) and soluble solids were better preserved in samples coated with antifungal agent. Sensory evaluation revealed the highest acceptance scores for coated and packaged fruit. Microbiological analyses confirmed that coated bananas had the lowest counts of mesophilic aerobes and yeasts and molds, while total coliforms remained below detection limits in all treatments. These results highlight the effectiveness of integrating antifungal coatings with polyethylene packaging to enhance banana quality during postharvest storage. Full article

The accurate assessment of soil fertility is critical for guiding nutrient management and promoting sustainable agriculture in semi-arid agroecosystems. In this study, a machine learning-based Soil Fertility Index (SFI) model was developed using regularized regression techniques to evaluate fertility across a dryland maize-growing region in southeastern Türkiye. A total of 64 composite soil samples were collected from the Batman Plain, characterized by alkaline and salinity-prone conditions. Five soil chemical indicators, electrical conductivity (EC), pH, organic matter (OM), zinc (Zn), and iron (Fe), were selected for SFI estimation using a standardized rating approach. The dataset was randomly split into training (80%) and test (20%) subsets to calibrate and validate the models. Ridge, Lasso, and Elastic Net regression models were employed to predict SFI and assess variable importance. Among these, the Lasso model achieved the highest predictive accuracy on test data (R² = 0.746, RMSE = 0.060), retaining only EC and Zn as significant predictors. Ridge and Elastic Net captured OM and pH, though their contributions were minimal (|β| < 0.01). Spatial predictions showed moderate alignment with observed SFI values (range: 0.48–0.76), but all models underestimated high-fertility zones (>0.69), likely due to coefficient shrinkage. Despite its simplicity, the Lasso model offered superior interpretability and spatial resolution. The results reveal the potential of interpretable machine learning for supporting sustainable, site-specific fertility assessment and informed nutrient management in data-scarce and environmentally vulnerable regions. Full article

This investigation examines the impact of machine-made sand methylene blue (MB) values on mortar properties and microstructure through controlled clay type and content testing, encompassing macro-performances, microstructures, and mechanisms measuring compressive strength, flexural strength, drying shrinkage, frost resistance, impermeability, pore structure, microstructure, interfacial transition zones (ITZs), and hydration products. MB testing demonstrates that montmorillonite and illite exhibit a significant sensitivity divergence, where 1% montmorillonite achieves an MB value of 1.42, exceeding 1.40, while illite requires a 5% content to attain an MB of 1.50, complying with SL/T 352-2020 specifications. Increasing MB values induce an initial rise followed by a decline in 7d compressive strength yet a persistent increase in flexural strength for montmorillonite mortars, with both strength parameters decreasing at 28d and 90d. Illite mortars exhibit progressive declines in compressive and flexural strength across all curing ages (7d, 28d, and 90d) with rising MB values. SEM-EDS analyses reveal a deteriorating mortar microstructure, reduced paste compactness, and thickened ITZ under identical clay types as MB values increase. Combined XRD and TG-DTA analyses demonstrate a diminishing hydration degree and decreased hydration products in mortars with ascending MB values. Given a constant clay mineralogy, elevated MB values inhibit hydration-product formation, causing incomplete cement hydration reactions and deteriorated ITZ microstructures, consequently impairing mortar macro-performances. Full article

This study presents an extended dataset on educational quality covering 101 countries, from 1970 to 2023. While existing international assessments, such as the Programme for International Student Assessment (PISA) and Trends in International Mathematics and Science Study (TIMSS), offer valuable snapshots of student performance, their limited coverage across countries and years constrains broader analyses. To address this limitation, we harmonized observed test scores across assessments and imputed missing values using both linear interpolation and machine learning (Least Absolute Shrinkage and Selection Operator (LASSO) regression). The dataset included (i) harmonized test scores for 15 year olds, (ii) annual educational quality indicators for the 15–19 age group, and (iii) educational quality indexes for the working-age population (15–64). These measures are provided in machine-readable formats and support empirical research on human capital, economic development, and global education inequalities across economies. Full article