Search Results (7,693)

Relying on an engineering case, this study establishes an analysis model using PLAXIS 3D and GeoStudio, and compares and analyzes the slope deformation and internal force of the supporting structure with different slope grades and different platform widths at the same height. The results show that the greatest displacement manifests in the lower segments of the slope, which is 12.99 mm, and the maximum anchoring force manifests in the mid-level and lower segments of the slope, which is 288.1 kN. A close correlation is observed between the simulated horizontal displacement of the slope, the maximum axial force of the anchor cable, and the corresponding field measurement results, indicating that the model parameters are satisfactory and that the resulting calculations are reliable. In consideration of the comprehensive stability of the slope, the stability coefficient increased by approximately 1.42% with two-stage slope support and by about 3.48% with four-stage slope support. The axial force of anchor cables was reduced by around 9.5% under two-stage grading, while four-stage grading decreased the maximum axial force of the middle–lower anchors by nearly 27%. The distance between the entrance and exit of the overall sliding surface and the slope surface also decreases with the increase in slope grading and platform width. This study systematically evaluates the combined effects of slope grading, platform width, and frame prestressed anchors. When site conditions permit, slope grading should be prioritized over simply widening the platform, as grading more effectively enhances slope stability and reduces anchor cable loads. Full article

To explore the application of precast concrete construction methods in underground stations, a combined precast and cast in situ construction method was adopted for a long-span column-free underground subway station. To study the stability of large-span underground arch structures under asymmetric loading, a full-scale test was conducted using the displacement-force control method. Steel blocks were used to simulate the overlying soil and additional loads on the upper surface of the arch, while the displacement of the arch foot was applied by adjusting the tension of the cables. The maximum tensile stress and maximum compressive stress of the steel bars appeared at the midpoints of the left and right arches, which were less than the yield stress of the steel bars. The results show that the structural stability meets the design requirements and provides a considerable safety margin. A comprehensive analysis of the arch structure under asymmetric loading was carried out through on-site monitoring, numerical simulation, and analytical solutions. The results are in good agreement: compared with the experimental results, the calculated values increase the maximum deflection of the arch by 13.67%, which verifies the reliability of the numerical simulation and analytical solution methods under the same boundary conditions. However, restricted by test conditions, the loading in this study was only applied on one side of the arch crown, which differs from the actual working condition involving full loading first followed by unloading on one side. Full article

The integration of solar generation into national energy balances is associated with a wide range of technical, economic, and organizational challenges, the solution of which requires the adoption of innovative strategies for energy system management. The inherent variability of electricity production, driven by fluctuating climatic conditions, complicates system balancing processes and necessitates the reservation of capacities from conventional energy sources to ensure reliability. Under modern market conditions, the pricing of generated electricity is commonly based on day-ahead forecasts of day energy yield, which significantly affects the economic performance of solar power plants. Consequently, achieving high accuracy in day-ahead electricity production forecasting is a critical and highly relevant task. To address this challenge, a physico-statistical model has been developed, in which the analytical approximation of daily electricity generation is represented as a function of a random variable—cloud cover—modeled by a β-distribution. Analytical expressions were derived for calculating the mathematical expectation and variance of daily electricity generation as functions of the β-distribution parameters of cloudiness. The analytical approximation of daily generation deviates from the exact value, obtained through hourly integration, by an average of 3.9%. The relative forecasting error of electricity production, when using the mathematical expectation of cloudiness compared to the analytical approximation of daily generation, reaches 15.2%. The proposed forecasting method, based on a β-parametric cloudiness model, enhances the accuracy of day-ahead production forecasts, improves the economic efficiency of solar power plants, and contributes to strengthening the stability and reliability of power systems with a substantial share of solar generation. Full article

In this study, NiO nanoparticle–reinforced PMMA nanocomposites were fabricated by melt blending, and the influence of extrusion mixing time on structural and thermal properties was examined. Mixing durations of 6 and 12 min were applied, and the materials were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM). These analyses confirmed the presence of NiO within the PMMA matrix and indicated that prolonged mixing promoted particle agglomeration. Thermal behavior was assessed by thermogravimetric analysis (TGA) at heating rates of 5, 10, 15, and 20 K·min⁻¹, and activation energies of decomposition were calculated using the Kissinger, Takhor, and Augis–Bennett methods. The results showed that extended mixing reduced composite homogeneity and adversely affected thermal stability. Incorporation of NiO nanoparticles decreased both the onset decomposition temperature and the activation energy compared to pure PMMA, facilitating earlier degradation. At 620 K, pure PMMA exhibited ~8% mass loss, whereas the 12 min blend showed ~12% loss. These findings highlight the importance of nanoparticle dispersion and processing parameters in governing the degradation behavior of PMMA/NiO nanocomposites. Full article

YKL-40 is a glycoprotein that may be present at elevated levels in many cancers and neurodegenerative diseases. It has been investigated in numerous studies as a potential biomarker for several conditions, including Alzheimer’s Disease (AD). In this study, a biosensor with Surface Plasmon Resonance imaging (SPRi) detection, sensitive to YKL-40, was constructed for the detection of this analyte in the blood plasma of AD patients. Extensive validation of the biosensor was performed. This included the determination of analytical parameters such as the biosensor’s response characteristics, detection and quantification limits, precision, accuracy, repeatability, selectivity, stability, and performance in natural samples. Validation parameters were primarily tested using standard solutions, while natural samples were employed to evaluate repeatability, stability, and assay accuracy in three groups of samples from different patients. A YKL-40-specific antibody was used as the receptor layer, immobilized on a gold plate using the EDC/NHS protocol on thiol 11-MUA. The biosensor exhibited a wide operating range (1–200 ng/mL), a low detection limit (LOD) of 2 pg/mL, and a quantification limit (LOQ) of 7 pg/mL. High precision and accuracy were confirmed by the calculated standard deviations (SD) and coefficients of variation (CV), which ranged from 0.0009 to 7.02 ng/mL and from 0.12% to 9.24%, respectively. The sensor also demonstrated good repeatability (CV = 4.995%) and was capable of detecting the analyte of interest in complex biological matrices. Its applicability was confirmed in a study using plasma from AD patients and two selected control groups: plasma from smokers and patients with prostatitis. This allowed the assessment of YKL-40 levels across different groups. The results were consistent with literature values, and statistical analysis confirmed the significance of concentration differences between groups. Furthermore, ROC curve analysis confirmed the diagnostic usefulness of the constructed YKL-40 test in the context of Alzheimer’s disease. Full article

Local livestock genetic resources are crucial for sustainable agriculture and biodiversity conservation. Dengchuan cattle, a nationally protected dairy breed in China, are esteemed for their high milk fat content and cultural significance. However, they have been threatened by crossbreeding with exotic high-yielding breeds, resulting in a decline in purebred resources. In this study, we evaluated the genetic diversity and structure of a conserved population using 100K SNP microarray data from 74 individuals. After implementing strict quality control measures, 78,460 loci were retained for principal component analysis (PCA), which identified 100 SNPs most associated with PC1. After calculating high-consistency loci using PLINK, based on allelic consistency, we selected 61 high-stability markers to represent 60 individuals for further analysis. Genetic diversity parameters indicated moderate polymorphism, with an effective population size (Ne) of 2.293, observed heterozygosity (Ho) of 0.300, expected heterozygosity (He) of 0.326, and an average polymorphic information content (PIC) of 0.261. A paired t-test confirmed a highly significant difference between Ho and He (p < 0.001). Runs of homozygosity (ROH) revealed a moderate level of inbreeding (F_ROH = 0.0928), with bulls exhibiting slightly higher values than females. Neighbor-joining (NJ) clustering further indicated clear lineage distinctions among bulls, but lower kinship among females. Overall, Dengchuan cattle exhibit moderate genetic diversity but face risks due to a small Ne and an unbalanced family structure. Targeted breeding strategies and genetic monitoring are recommended to ensure sustainable conservation and utilization. Full article

The stability of rubble mound breakwaters is highly affected by extreme wave loading. While extensive research has been devoted to wave-induced scour and liquefaction around breakwaters, comprehensive stability evaluations of the rubble mound breakwater core remain limited. This study develops a numerical framework to investigate the stability of rubble mound breakwaters subjected to solitary wave loading. Wave motion is modeled using the Navier–Stokes equations, wave-induced pore pressure is computed based on Darcy’s law, and soil behavior is represented through the Mohr–Coulomb constitutive model. The numerical model is validated against experimental data. To assess structural stability, the strength reduction method is employed to calculate the Factor of Safety (FOS) during wave propagation, with the minimum FOS serving as the stability criterion. Furthermore, the influence of key parameters, including wave height, soil shear strength, wave–current interaction, berm dimensions, and slope gradient, on breakwater stability is systematically analyzed. Full article

This study used density functional theory (DFT)-based first-principles calculations to investigate the desolvation effect of single-walled carbon nanotubes (SWCNTs) modified with hydroxyl (-OH), carbonyl (-C=O), and carboxyl (-COOH) groups. SWCNTs have great potential as supercapacitor electrode materials due to their unique structural and electronic properties, but their practical application is limited by poor solvation-induced dispersibility and low ion transport efficiency. To solve this, this study constructed functionalized SWCNT models, simulated their interaction with lithium ion (Li⁺) complexes in acetonitrile (AN) solvent, and analyzed Li⁺ desolvation behavior, relative capacitance, and post-desolvation density of states (DOSs). The key research results are as follows: [Li(AN)]⁺ complete desolvation sizes differed: 5.91 Å (pristine SWCNTs), 6.26 Å (hydroxylated SWCNTs, HCNT), 6.11 Å (carbonylated SWCNTs, CNCNT; carboxylated SWCNTs, CXCNT). HCNT showed the largest relative capacitance enhancement (max 1.4× pristine), while CNCNT and CXCNT both had a max 1.3× improvement. Post-desolvation DOS analysis revealed distinct electronic property changes: HCNT-Li⁺ enhanced metallicity and conductivity; CNCNT-Li⁺ increased metallicity but reduced conductivity; and CXCNT-Li⁺ decreased metallicity with nearly unchanged conductivity. This study provides an atomic-scale theoretical basis for optimizing the properties of SWCNT solutions, supporting their application in high-performance supercapacitors, particularly in enhancing device energy density and cycle stability. Full article

Conventional ridging and mulching machines struggle to perform effectively in yellow sand substrates due to their loose texture, high collapsibility, and strong fluidity, which compromise ridge stability and operational quality. To address these challenges, this study proposes the development of an integrated rotary tillage, ridging, and film-mulching machine specifically designed to meet the agronomic requirements of tomato cultivation in greenhouse environments with yellow sand substrate. Based on theoretical analysis and parameter calculations, a soil transportation model was established, and the key structural parameters—such as blade arrangement and helical shaft geometry—were determined. A discrete element method (DEM) simulation was employed to construct a contact model for the yellow sand–slag mixed substrate. A combination of single-factor experiments and Box–Behnken response surface methodology was used to investigate the effects of forward speed, shaft rotational speed, and tillage depth on ridge stability and operational performance. The simulation results indicated that a forward speed of 0.82 m·s⁻¹, shaft speed of 260 rpm, and tillage depth of 150 mm yielded the highest ridge stability, with an average of 95.7%. Field trials demonstrated that the ridge top width, base width, height, and spacing were 598.6 mm, 802.3 mm, 202.4 mm, and 1002.8 mm, respectively, with an average ridge stability of 94.3%, differing by only 1.4 percentage points from the simulated results. However, a quantitative traction/energy comparison with conventional equipment was not collected in this study, and we report this as a limitation. The energy consumption is estimated based on power usage and effective field capacity (EFC) under similar operating conditions. Soil firmness reached 152.1 kPa, fully satisfying the agronomic requirements for tomato cultivation. The proposed machine significantly improves operational adaptability and ridge stability in yellow sand substrate conditions, providing robust equipment support for efficient greenhouse farming. Full article

In this study, beans aquafaba was used as the emulsifying agent for oil-in-water (o/w) emulsions with sunflower oil concentrations of 30% and 60%. The primary approach to stabilizing such emulsions is by increasing their viscosity through the incorporation of selected polysaccharides. For this purpose, xanthan gum or pregelatinized corn starch were added as stabilizers. The effects of oil content and different stabilizers on the microstructure and rheological properties were evaluated using laser diffraction and rotational viscometry. A pre-optimized seed-to-water ratio of 1:1.5 yielded beans aquafaba with a protein concentration of 0.5%. Further evaporation was used to increase the protein content to 0.8%. The aquafaba-based emulsion samples exhibited a bimodal particle size distribution. An increase in both oil and xanthan gum content had minimal impact on the mean volume diameter of emulsion particles, whereas the addition of pregelatinized corn starch significantly increased this value. All emulsions exhibited pseudoplastic flow behavior. The flow curves were approximated using the power-law and Herschel–Bulkley models. The calculated dynamic yield shear stresses consistently increased with increasing content of both oil and stabilizer in the range from 0.3 to 5.0 Pa. It is worth noting that in emulsions with an oil content of 30%, the addition of xanthan gum had a significant impact on this indicator, while in emulsions with an oil content of 60%, the addition of pregelatinized corn starch had a greater impact. Consequently, higher concentrations of the selected polysaccharides led to the formation of more viscous systems exhibiting enhanced stability. The developed food emulsions based on beans aquafaba are a promising technology in the development of vegetarian products. Full article

The development of efficient and sustainable advanced oxidation processes (AOPs) for organic pollutant removal is of great significance for water purification. In this study, a CoFeNi-layered double hydroxide (CoFeNi-LDH) catalyst was synthesized and applied for the simultaneous activation of peroxymonosulfate (PMS) and ozone to degrade rhodamine B (RhB) in aqueous solution. The CoFeNi-LDH/PMS/ozone system achieved a remarkable RhB removal efficiency of 95.2 ± 1.2% within 8 min under neutral pH conditions. Systematic parametric studies revealed that synergistic interactions among CoFeNi-LDH, PMS, and ozone contributed to the generation of reactive oxygen species (ROS), primarily sulfate radicals (SO₄^•−) and singlet oxygen (¹O₂), as confirmed by EPR and quenching experiments. Density functional theory (DFT) calculations demonstrated that ozone enhanced PMS adsorption and activation at CoFeNi catalytic sites. The catalyst exhibited robust magnetic recyclability and structural stability after repeated use. This work highlights a synergistic catalytic strategy for PMS/ozone activation, offering an effective and environmentally friendly platform for dye wastewater remediation. Full article

Integration of renewable energy into modern power grids remains limited by intermittency and the need for reliable energy storage. Redox flow batteries (RFBs) are promising for large-scale energy storage, yet their widespread adoption is hindered by the high cost. In this study, we investigate isopropanol as a redox-active species with Pt-Cu alloy electrocatalysts for aqueous-organic RFBs. A series of Pt_xCu catalysts with varying Pt:Cu ratios were synthesized and studied for isopropanol electro-oxidation reaction (IPAOR) performance. Among them, PtCu demonstrated the best performance, achieving a low activation energy of 14.4 kJ/mol at 0.45 V vs. RHE and excellent stability at 1 M isopropanol (IPA) concentration. Kinetic analysis and in situ attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy revealed significantly reduced acetone accumulation on PtCu compared to pure Pt, indicating enhanced resistance to catalyst poisoning. Density functional theory (DFT) calculations further identified the first proton-coupled electron transfer (PCET) as the rate-determining step (RDS) with C-H bond scission as the preferred pathway on PtCu. A proof-of-concept PtCu-catalyzed H-cell demonstrated stable cycling over 200 cycles, validating the feasibility of IPA as a low-cost, regenerable redox couple. These findings highlight PtCu-catalyzed IPA/acetone(ACE) chemistry as a promising platform for next-generation aqueous-organic RFBs. Full article

With the rapid development of cybersecurity technologies, cybersecurity testing has played an increasingly critical role in scientific research, new technology validation, system performance evaluation, and talent development. A central challenge in this domain lies in efficiently and rapidly constructing testing environments while ensuring the reliability and reproducibility of test results. To address this issue, this paper proposes an integrated evaluation method specifically designed for cybersecurity testing, combining anomaly detection and predictive analysis techniques. The method first employs an autoencoder (AE) to perform dimensionality reduction on the raw data collected from a testbed environment, followed by anomaly detection using the Isolation Forest (IF) algorithm. To assess the impact of cyberattacks on the stability of the testbed system, the steady-state data of the environment was treated as the ideal reference. The degree of disruption was then quantified by calculating the Euclidean distance between the dimensionally reduced experimental data and the reference state. Finally, a specific case study was conducted to validate the feasibility and effectiveness of the proposed method, and a percentage-based scoring mechanism was introduced to quantitatively evaluate the security level of the system. Full article

This article presents an innovative approach to optimizing the seismic modeling and analysis of high-rise buildings by automating the process with Python 3.13 and the ETABS 22.1.0 API. The process begins with the collection of information on the base building, a structure of seventeen regular levels, which includes data from structural elements, material properties, geometric configuration, and seismic and gravitational loads. These data are organized in an Excel file for further processing. From this information, a code is developed in Python that automates the structural modeling in ETABS through its API. This code defines the sections, materials, edge conditions, and loads and models the elements according to their coordinates. The resulting base model is used as a starting point to generate an optimal solution using a genetic algorithm. The genetic algorithm adjusts column and beam sections using an approach that includes crossover and controlled mutation operations. Each solution is evaluated by the maximum displacement of the structure, calculating the fitness as the inverse of this displacement, favoring solutions with less deformation. The process is repeated across generations, selecting and crossing the best solutions. Finally, the model that generates the smallest displacement is saved as the optimal solution. Once the optimal solution has been obtained, it is implemented a second code in Python is implemented to perform static and dynamic seismic analysis. The key results, such as displacements, drifts, internal and basal shear forces, are processed and verified in accordance with the Peruvian Technical Standard E.030. The automated model with API shows a significant improvement in accuracy and efficiency compared to traditional methods, highlighting an R² = 0.995 in the static analysis, indicating an almost perfect fit, and an RMSE = 1.93261 × 10⁻⁵, reflecting a near-zero error. In the dynamic drift analysis, the automated model reaches an R² = 0.9385 and an RMSE = 5.21742 × 10⁻⁵, demonstrating its high precision. As for the lead time, the model automated completed the process in 13.2 min, which means a 99.5% reduction in comparison with the traditional method, which takes 3 h. On the other hand, the genetic algorithm had a run time of 191 min due to its stochastic nature and iterative process. The performance of the genetic algorithm shows that although the improvement is significant between Generation 1 and Generation 2, is stabilized in the following generations, with a slight decrease in Generation 5, suggesting that the algorithm has reached its level has reached a point of convergence. Full article

The Nile, Indus, and Yellow River deltas are historically significant and have experienced extensive shoreline changes over the past 50 years, yet the roles of human interventions and natural events remain unclear. In this study, the Net Shoreline Movement and End Point Rate (EPR) were calculated to quantify the erosion and accretion of the shoreline, respectively. Subsequently, linear trend analysis was employed to identify potential directional shifts in shoreline behavior. These measures are combined with segment-scale cumulative area and the EPR trend to reveal where erosion or accretion intensifies, weakens, or reverses through time. Results show distinct, system-specific trajectories, the Nile lost ~27 km² from 1972 to1997 as a result of the dam construction and sediment reduction, and lost only ~3 km² more from 1997 to 2022, with local stabilization. The Indus switched from intermittent gains before 1990s to sustained loss after that, totaling ~300 km² of cumulative land loss mainly due to upstream dam constructions and storm events. The Yellow River gained ~500 km² from 1973 to 1996 then lost ~200 km² after main-channel relocation and reduced sediment supply despite active-mouth management. These outcomes indicate that deltas are very vulnerable to system wide human activities and natural events. Combined, satellite-derived metrics can help prioritize locations, guide feasible interventions, establish annual monitoring and trigger action. A major caveat of this study is that yearly shoreline rates and 5–10-yearaverages can mask short-lived or very local shifts. Targeted field surveys and finer-scale modeling (hydrodynamics, subsidence monitoring, bathymetry) are therefore needed to refine the design and inform better policy choices. Full article