Search Results (27,409)

Background: This study aims to investigate the potential modifying effects of lifestyle behavior on the association between drinking water micronutrients and body mass index (BMI) in a large population of children and adolescents. Methods: Data of the present analysis came from a comprehensive regional large-scale surveillance study in 2022, involving 172,880 children and adolescents (50.71% boys vs. 49.29% girls) aged seven to seventeen. A restricted cubic spline (RCS) analysis was utilized to examine the exposure-response association of regular drinking water indices (including fluoride, nitrate nitrogen, pH, chloride, sulfates, and total dissolved solids (TDS), total hardness (TH), and chemical oxygen demand (COD)) with BMI. Generalized linear model and logistic regression were conducted to relate BMI and quartiles of drinking water micronutrients. Results: Our findings reveal a nonlinear association between nitrate nitrogen (P for nonlinear < 0.001) and pH (P for nonlinear < 0.001) with BMI. High TH and COD levels significantly increase BMI. Notably, fluoride and chloride were associated with BMI Z-scores but not with overweight and obesity (OB). The BMI Z-score showed a more pronounced association with low and high pH levels in girls. For urban participants, increased TH levels were associated with a higher risk of OB. This study also found that adopting healthy lifestyles could mitigate the negative effects of fluoride, chloride, and sulfate on BMI Z-scores. Conclusions: This large surveillance study provides new insights into the complex interplay between drinking water micronutrients and BMI in children and adolescents. The association of various drinking water parameters on BMI varies, necessitating ongoing focus on their effects, particularly among girls and urban individuals. Healthy lifestyle behavior could mitigate the effects of fluoride, chloride, and sulfate on BMI Z-score. Full article

In this study, the crystallization behavior, microstructure, and mechanical and physical properties of CaO-Al₂O₃-SiO₂ (CAS)-based glass-ceramics prepared from eggshell waste, zeolite, and pumice were investigated using X-ray diffraction (XRD), differential thermal analysis (DTA), scanning electron microscopy (SEM), a nanoindentation tester, and the Archimedes method. XRD analysis revealed that anorthite and wollastonite crystalline phases precipitated in the glass-ceramic samples after sintering at temperatures of 1000 °C and 1100 °C. However, diffraction peaks belonging to the wollastonite phase disappeared after sintering at 1200 °C, while peaks representing the pseudowollastonite phase were detected together with anorthite in the samples. SEM images showed that the crystals become coarser as the sintering temperature increased, with the crystal morphology transitioning from needle-like to rod-like. The crystallization activation energy (E_a) and Avrami parameter (n), both kinetic parameters, were calculated from DTA curves plotted at different heating rates using the Kissinger, Ozawa, and Matusita approaches. The results indicated that the crystallization activation energy of the CASZ glass ranged from 406 to 428 kJ mol⁻¹, while that of the CASP glass varied from 356 to 378 kJ mol⁻¹, depending on the method used. Additionally, the Avrami constant (n) was calculated to be 3.33 for CASZ and 2.89 for CASP. The hardness and bulk density of the glass-ceramic samples were significantly affected by the porosity present in the structure, with the highest hardness and bulk density values achieved for the CASZ glass-ceramic sample at the initial sintering temperature of 1000 °C. Full article

This study examines the static performances of a graphene platelet (GPL)-reinforced ethylene tetrafluoroethylene (ETFE) composite membrane under wind loadings. The wind pressure distribution on a periodic tensile membrane unit was analyzed by using CFD simulations, which considered various wind velocities and directions. A one-way fluid–structure interaction (FSI) analysis incorporating geometric nonlinearity was performed in ANSYS to evaluate the static performances of the composite membrane. The novelty of this research lies in the integration of graphene platelets (GPLs) into ETFE membranes to enhance their static performance under wind loading and the combination of micromechanical modelling for obtaining material properties of the composites and finite element simulation for examining structural behaviors, which is not commonly explored in the existing literature. The elastic properties required for the structural analysis were determined using effective medium theory (EMT), while Poisson’s ratio and mass density were evaluated using rule of mixtures. Parametric studies were carried out to explore the effects of a number of influencing factors, including pre-strain, attributes of wind, and GPL reinforcement. It is demonstrated that higher initial strain effectively reduced deformation under wind loads at the cost of increased stress level. The deformation and stress significantly increased with the increase in wind velocity. The deflection and stress level vary with the wind direction, and the maximum values were observed when the wind comes at 15° and 45°, respectively. Introducing GPLs with a larger surface area into membrane material has proven to be an effective way to control membrane deformation, though it also results in a higher stress level, indicating a trade-off between deformation management and stress management. Full article

The current study focused on the synthesis of doped silver nanoparticles (doped AgNPs) with yttrium (Y), gadolinium (Gd), and chromium (Cr) from pine needle leaf extract (PNLE). X-ray diffraction (XRD) was performed to assess the phase formation, detecting 61.83% from Ag and 38.17% for secondary phases of AgCl, AgO, Y, Cr-, and Gd phases. The size and shape of the NPs were determined by transmission electron microscopy (TEM), showing a spherical shape with an average particle size of 26.43 nm. X-ray photoelectron spectroscopy (XPS) detected the oxidation state of the presented elements. The scanning electron microscope (SEM) and the energy-dispersive X-ray analysis (EDX) determined the morphology and elemental composition of the NPs, respectively. Fourier transform infrared spectroscopy (FTIR) determined the different functional groups indicating the presence of Ag, Y, Gd, Cr, and other groups. Photoluminescence (PL) spectroscopy showed the optical properties of the NPs. A vibrating sample magnetometer (VSM) revealed the ferromagnetic behavior of the doped AgNPs. The antibacterial activity of the doped AgNPs was tested against six uro-pathogenic bacteria (Staphylococcus aureus, Staphylococcus haemolyticus, Enterococcus faecalis, Escherichia coli, Klebsiella pneumonia, and Pseudomonas aeruginosa) using the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) microdilution assays, agar well diffusion assay, time–kill test, and antibiofilm screening assays, revealing significant activity, with MICs ranging between 0.0625 and 0.5 mg/mL and antibiofilm activity between 40 and 85%. The antioxidant activity was determined by the 1,1, diphenyl 1-2 picrylhydrazyl (DPPH) radical scavenging assay with a potential of 61.3%. The docking studies showed that the doped AgNPs had the potential to predict the inhibition of crucial enzymes such as penicillin-binding proteins, LasR-binding proteins, carbapenemase, DNA gyrase, and dihydropteroate synthase. The results suggest that the doped AgNPs can be applied in different medical domains. Full article

This article examines the role of computer science in enhancing laser processing techniques, emphasizing the transformative potential of their integration into manufacturing. It discusses key areas where computational methods enhance the precision, adaptability, and performance of laser operations. Through advanced modeling and simulation techniques, a deeper understanding of material behavior under laser irradiation was achieved, enabling the optimization of processing parameters and a reduction in defects. The role of intelligent control systems, driven by machine learning and artificial intelligence, was examined, showcasing how a real-time data analysis and adjustments lead to improved process reliability and quality. The utilization of computer-generated diffractive optical elements (DOEs) was emphasized as a means to precisely control laser beam characteristics, thus broadening the application opportunities across various industries. Additionally, the significance of predictive modeling and data analyses in enhancing manufacturing effectiveness and sustainability is discussed. While challenges such as the need for specialized expertise and investment in new technologies persist, this article underscores the considerable advantages of integrating computer science with laser processing. Future research should aim to address these challenges, further improving the quality, adaptability, and sustainability of manufacturing processes. Full article

In the context of China’s promotion of green buildings and resilient urban development, new reinforcement technologies offer significant development prospects, while traditional methods have limited effectiveness in enhancing structural resilience. To address this latter issue, this study proposes a novel reinforcement method that involves enlarging the structural cross-section and adding external self-resetting components to improve seismic performance. While this method has been validated through quasi-static tests, limitations in terms of sample size and experimental conditions necessitate further research into the seismic performance and dynamic behavior of the reinforced framework. Consequently, this study uses finite element analysis to explore the influencing factors and dynamic characteristics of the reinforcement method. The results show that finite element modeling effectively simulates the stress characteristics of reinforced frameworks. Installing prefabricated beams significantly enhances the load-bearing capacity by 18% and reduces the residual deformation rates after earthquakes by 26%. Increased pre-tensioning of the steel strands further improves seismic resilience. This reinforcement method enables older structures lacking self-resetting capabilities to achieve some degree of self-resetting ability, and it performs well under various earthquake conditions. Full article

Background: In northern countries, spring requires the removal of large volumes of abrasive materials used in winter road maintenance. This sweeping process, crucial for safety and environmental protection, has traditionally relied on conventional mechanical brooms. Recent technological innovations, however, have introduced more efficient and environmentally friendly sweeping solutions; Methods: This study provides a comprehensive comparative analysis of the environmental and operational performance of these innovative sweeping systems versus conventional methods. Using simulation models based on real-world data and integrating fuel consumption models, the analysis replicates sweeping behaviors to assess both operational and environmental performance. A sensitivity analysis was conducted using these models, focusing on key parameters such as the collection rate, the number of trucks, the payload capacity, and the truck unloading duration; Results: The results show that the innovative sweeping system achieves an average 45% reduction in GHG emissions per kilometer compared to the conventional system, consistently demonstrating superior environmental efficiency across all resources configurations; Conclusions: These insights offer valuable guidance for service providers by identifying effective resource configurations that align with both environmental and operational objectives. The approach adopted in this study demonstrates the potential to develop decision-making support tools that balance operational and environmental pillars of sustainability, encouraging policy decision-makers to adopt greener procurement policies. Future research should explore the integration of advanced technologies such as IoT, AI-driven analytics, and digital twin systems, along with life cycle assessments, to further support sustainable logistics in road maintenance. Full article

Biodegradable composites combining thermoplastic polymers and natural fibers could originate materials with synergetic mechanical and thermal properties, keeping their biodegradability. This paper describes biodegradable polymers’ mechanical and thermal properties, such as polylactic acid (PLA) and polyhydroxybutyrate (PHB) reinforced with curaua fibers. To improve the interface between matrix and reinforcement, the curaua fibers were treated by two routes: (1) treatment with hot water and subsequent mercerization with NaOH; (2) treatment with chlorite and subsequent mercerization with NaOH. The composites of PLA and PHB reinforced with natural or modified fibers (10 and 20 wt%) were obtained by extrusion and injection molding. The influence of fiber content and treatment on composite properties was studied by tensile and flexural tests, scanning electron microscopy (SEM), X-ray diffraction (XRD), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC). The results showed the removal of hemicellulose and lignin from the fibers, increasing their crystallinity and slightly decreasing their thermal stability after chemical treatments. Also, the DSC technique showed that the insertion of the curaua fibers increased the crystallinity index of all composites/PLA. The mercerized-curaua (20 wt%)/PLA composite showed the best result in the mechanical behavior, both in tensile and bending tests. The PHB composite, reinforced with curaua fibers and treated with hot water and mercerization (20 wt%), showed the best result regarding mechanic performance. To conclude, all composites improved mechanical properties compared to pure polymers. Full article

The aim of this work was to perform a simulation analysis of the dynamics of a freight wagon with a variant vibration damping: dry friction and viscous damping. The following mathematical models of the damping characteristics are presented: the Maxwell model and the Kolsch model. The differences among the types of damping were first analyzed based on the dynamic responses of the 1 DOF model. Simulation studies were then carried out in a VI-Rail environment with the use of S-curved track models comprising short straight sections connecting the curves. The track models differed in the values of curve radii, cant, and length, which made it possible to run at different speeds. The multibody model of the vehicle represents a typical two-axle freight wagon. The dynamics of the wagon model were investigated for two states: empty and laden. Standard kinematic and dynamic values were compared in order to investigate if the nature of the damping has a significant impact on the dynamic properties of a freight wagon. The analysis of the simulation study showed that replacing dry friction damping with the viscous one can generally reduce forces acting on the wheel–rail contact, which, in turn, can be related to improving the running behavior of wagons while reducing the negative impact on the track. Full article

The development of sustainable infrastructure is essential to address the challenges of climate change and reduce CO₂ emissions. The use of alternative materials, such as agro-industrial ashes and silica fume, emerges as a promising option to enhance the durability of concrete and diminish its environmental impact. These materials can partially replace conventional cement, contributing to the construction of more sustainable infrastructure without compromising performance, even under adverse environmental conditions. In this study, we present an analysis of the use of sugarcane bagasse ash (SBA) and silica fume (SF) as a 15% cement replacement. The behavior of these materials was investigated under coastal conditions, analyzing climatic variables and degrading gases such as CO₂, CH₄, and N₂O. Electrochemical techniques were employed to measure corrosion rate and potential, in addition to conducting carbonation and compressive strength tests. The mixtures with a 15% addition of SBA and SF showed improvements compared to conventional mixes. SBA reduced the corrosion rate by 25% and increased compressive strength by 12% after 150 days, while SF enhanced carbonation resistance by 20% and compressive strength by 25%. The incorporation of SBA and SF provides significant durability in coastal environments, contributing to the sustainability of infrastructure exposed to adverse weather conditions. Full article

Background/Objectives: A favorable attitude towards suicidal behavior is associated with an increased risk of suicidal behavior in youth populations. Hence, the aim of the present study was to analyze attitudinal beliefs about suicidal behavior among Mexican medical and nursing students. We also compared attitudinal beliefs about suicidal behavior according to the religious affiliation of the participants. Methods: This is a cross-sectional observational study. Attitudinal beliefs about suicidal behavior were assessed using the Attitudinal Beliefs Questionnaire about Suicide Behavior (CCCS-18). We evaluated personal and family histories of suicide using the Spanish version of the MINI International Neuropsychiatric Interview. Comparative analysis between nursing and medical students was performed, using Chi-square tests for categorical variables and Student t-tests for continuous variables. Results: A total of 195 (52.2%) medical students and 178 (47.8%) nursing students participated. Medicine students reported a higher prevalence of a family history of suicide attempts and knowing someone who had tried to die by suicide compared to nursing students (p = 0.001). Regarding attitudinal beliefs—specifically, suicide in terminal patients—medical students reported higher scores than nursing students (9.50 ± 5.91 vs. 11.23 ± 6.38, p < 0.001), while the latter exhibited higher scores in attitudinal beliefs related to suicide itself (9.55 ± 4.45 vs. 7.28 ± 4.09, p < 0.001). Both groups display similar scores when compared by religious affiliation. Conclusions: Our findings show differences in attitudinal beliefs about suicidal behavior between medical and nursing students. Medical students exhibited more positive responses toward suicide in terminal patients, while nursing students had higher values for attitudinal beliefs related to suicide itself. These results could be considered in the planning of health sciences curricula in order to positively impact future suicide prevention efforts. This study was retrospectively registered at the Universidad Juarez Autónoma de Tabasco, with the registration number 20240063 on 8 June 2024. Full article

For improving the adaptability of a tracked vehicle equipped with a symmetrical suspension system on complex hilly terrain, based on the coupling method of multi-body dynamics (MBD) and discrete element method (DEM), an MBD-DEM coupling model was built and verified to explore its dynamic behaviors on soil. Firstly, according to the basic parameters of the tracked vehicle equipped with a symmetrical suspension system, a corresponding MBD model was built in Recurdyn V9R4 software. Based on the Euler–Lagrange method, the mathematical structure of the symmetrical suspension system was analyzed, and a corresponding mathematical simulation model was built in Matlab2016/Simulink to verify the MBD model. Secondly, based on the DEM theory and the parameter of the soil in a hilly area, a granular pavement model was built. Then, based on the coupling method of MBD and DEM, the corresponding MBD-DEM coupling model was built. Finally, using the MBD-DEM coupling model, the dynamic behaviors of the tracked vehicle equipped with a symmetrical suspension system under horizontal condition, the climbing condition and the obstacle crossing condition were obtained and discussed. The study results show that the proposed MBD-DEM coupling model could be used effectively to analyze the dynamic characteristics of the tracked vehicle. In addition, according to the analysis of the dynamic characteristics of the proposed tracked vehicle, the tracked vehicle equipped with a symmetrical suspension presents good adaptabilities under various working conditions. Full article

Although the rapid development of Artificial Intelligence (AI) in recent years has brought increasing academic attention to the intelligent transformation of physical education, the core knowledge structure of this field, such as its primary research topics, has yet to be systematically explored. The LDA (latent Dirichlet allocation) topic model can identify latent themes in large-scale textual data, helping researchers extract key research directions and development trends from extensive literature. This study is based on data from the Web of Science Core Collection and employs a systematic literature screening process, utilizing the LDA topic model for in-depth analysis of relevant literature to reveal the current status and trends of AI technology in physical education. The findings indicate that AI applications in this field primarily focus on three areas: “AI and data-driven optimization of physical education and training”, “computer vision and AI-based movement behavior recognition and training optimization”, and “AI and virtual technology-driven innovation and assessment in physical education”. An in-depth analysis of existing research shows that the intelligentization of physical education, particularly in school and athletic training contexts, not only promotes sustainable development in the field but also significantly enhances teaching quality and safety, allowing educators to utilize data more precisely to optimize teaching strategies. However, current research remains relatively broad and lacks more precise and robust data support. Therefore, this study critically examines the limitations of current research in the field and proposes key research directions for further advancing the intelligent transformation of physical education, providing a solid theoretical framework and guidance for future research. Full article

This study conducts a simulation analysis of the stability of tall and collapse-prone stopes at the Dongguashan copper mine, using the FLAC3D-3.0 software to investigate the stress distribution and deformation behavior of geological materials under different working conditions, providing an effective means of addressing complex mechanical issues in geotechnical engineering. In this paper, the stability of the tall stopes in the Dongguashan mining area was analyzed through numerical simulations using the FLAC3D finite difference method. First, a three-dimensional numerical model of the tall stopes was established based on the actual conditions of the mining area, simulating the mining conditions and environment. Next, the stress distribution, displacement variation, and potential instability zones under different mining schemes were studied, with a comparative analysis conducted between traditional mining methods and optimized schemes to clarify their respective advantages and disadvantages. Finally, based on the simulation results, the most suitable mining scheme for the area was identified, aimed at reducing the risk of stope collapse and improving the overall stability and safety of the mine. The findings provide technical support for the design and support of tall stopes in deep deposits and offer important reference points for mine safety management. Full article

Steel T-profiles with the spot-welding manufacturing process are extensively used in various sectors such as construction, automotive, renewable energy, etc., due to their versatility and reliability. These profiles are exposed to various loading modes during their service life, which include axial, bending, shear, torsional, or combinations thereof. This paper investigates the fatigue performance of a spot-welded T-profile assembly subjected to torsional cyclic loading. The extended finite element method (XFEM) analysis was performed to simulate the intricate behavior of spot welds under the loading, elucidating critical areas prone to fatigue initiation and propagation especially around the spot welds. The simulation results were compared with previously obtained experimental results. Both results are consistent. The effects of various parameters, including the spot-weld diameters, the amount of torque applied, thickness of the profile parts, and the presence of base part, on the fatigue performance of the assembly were studied critically. Full article