Search Results (8,115)

This study developed a new magnetic adsorbent from waste coconut shells using high-temperature carbonization, EDTA-2Na chelation, and Fe₃O₄ magnetic loading. Response surface methodology optimized the preparation conditions to a mass ratio of activated carbon: EDTA-2Na:Fe₃O₄ = 2:0.6:0.2. Characterization (SEM, XRD, FT-IR, and EDS) showed that EDTA-2Na increased the surface carboxyl and amino group density, while Fe₃O₄ loading (Fe concentration 6.83%) provided superior magnetic separation performance. The optimal adsorption conditions of Cu²⁺ by EDTA-2Na-Fe₃O₄-activated carbon composite material are as follows: when pH = 5.0 and the initial concentration is 180 mg/L, the equilibrium adsorption capacity reaches 174.96 mg/g, and the removal rate reaches 97.2%. The optimal adsorption conditions for Pb²⁺ are as follows: when pH = 6.0 and the initial concentration is 160 mg/L, the equilibrium adsorption capacity reaches 157.60 mg/g, and the removal rate reaches 98.5%. The optimal adsorption conditions for Cd²⁺ are pH = 8.0 and an initial concentration of 20 mg/L. The equilibrium adsorption capacity reaches 18.76 mg/g, and the removal rate reaches 93.8%. The adsorption followed the pseudo-second-order kinetics (R² > 0.95) and Langmuir/Freundlich isotherm models, indicating chemisorption dominance. Desorption experiments using 0.1 mol/L HCl and EDTA-2Na achieved efficient desorption (>85%), and the material retained over 80% of its adsorption capacity after five cycles. This cost-effective and sustainable adsorbent offers a promising solution for heavy metal wastewater treatment. Full article

The shear characteristics of the frozen soil–concrete interface are core parameters in frost heave resistance design in cold-region engineering, and the influence mechanism of interface roughness on these characteristics is not clear. In this study, the regulatory effect of different roughness levels (R-0 to R-4) on the interfacial freezing strength was quantitatively analyzed for the first time through direct shear tests, and the evolution characteristics of the contribution ratio of the ice cementation strength were revealed. The results show that the peak shear strength of the interface increases significantly with the roughness (when the normal stress is 400 kPa and the water content is 14%, the increase in R-4 is 47.7% compared with R-0); the ice cementation strength increases synchronously and its contribution ratio increases with the increase in roughness. Although the absolute value of the residual strength increase is small, the relative amplitude is larger (178.5% increase under the same working conditions). The peak cohesion increased significantly with the roughness (R-0 to R-4 increased by 268.6%), while the residual cohesion decreased. The peak and residual internal friction angle increased slightly with the roughness. The study clarifies the differential influence mechanism of roughness on the interface’s shear parameters and provides a key quantitative basis for the anti-frost heave design of engineering interfaces in cold regions. Full article

Foam cement, as a building insulation material, encounters a major problem in practical application, which is the difficulty in achieving a balance between its strength and insulation performance. To achieve multi-objective optimization of foamed cement mix design, this study first determined the optimal ranges of nano-silica aerogel (NSA), foaming agent, and polypropylene (PP) fiber dosage through single-factor experiments. Then, response surface methodology (RSM) was employed to construct a quadratic polynomial regression model, systematically investigating the influence of different NSA contents, foaming agent contents, and PP fibers contents on the thermal conductivity and compressive strength of foamed cement. Finally, the optimal mix ratio was further predicted and experimentally validated. The results demonstrate that the regression model developed using RSM exhibits high accuracy and reliability. The correlation coefficients R² of the regression models established by the response surface method are 0.9756 and 0.9684, respectively, indicating good prediction accuracy. The optimized mix ratio was determined as follows: NSA content, 9.548%; foaming agent content, 0.533%; and PP fiber content, 0.1%. Under this mix, the model predicted a thermal conductivity of 0.123 W/(m·K) and a 28-day compressive strength of 1.081 MPa. Experimental verification confirmed that the errors between predicted and measured values for all performance indicators were within 5%, demonstrating the high reliability of the predictive model. This study provides support for the practical application of foam cement as a thermal insulation material in construction projects and offers guidance for optimizing its mixture composition. Full article

This study examines the hydrodynamic and acoustic performance of plain NACA0018 hydrofoil and modified NACA0018 hydrofoils (foil with a cavity on suction surface) at a Reynolds number ($Re$) of $40,000$, which is indicative of small-scale turbines and marine applications. A cavity was created on suction side surface at 40–50% of the chord length, which is chosen for its efficacy in cavitation control. The present analysis examines the impact of the cavity on lift-to-drag-ratio ($L/D$) and cavity length at three cavitation numbers ($1.7$, $1.2$, and $0.93$) for plain and modified hydrofoils. Simulations demonstrate a significant enhancement of 7% in the lift-to-drag ratio relative to traditional designed foils. Contrary to earlier observations, the cavity length increases instead of decreasing for the modified hydrofoil. Both periodic steady and turbulent inflow conditions are captured that simulate the complex cavity dynamics and flow–acoustic interactions. It is found that a reduction in RMS velocity with modified blade suggests flow stabilization. Spectral analysis using Mel-frequency techniques confirms the cavity’s potential to reduce low-frequency flow-induced noise. These findings offer new insights for designing quieter and more efficient hydrofoils and turbine blades. Full article

To address the issue that existing raisin foreign object removal equipment cannot eliminate surface contaminants adhered to raisins through non-washing methods, this paper proposes an adhesive foreign object removal method based on “rapid freezing–rolling extrusion separation-airflow screening”. A raisin adhesive foreign object removal device was designed based on this method. The separation and removal processes of adhesive foreign objects were analyzed and optimized through simulation, followed by device fabrication and performance testing. Starting from the separation process of raisins and adhesive foreign objects, we conducted experimental studies on quick-freezing separation, determined the most suitable separation method based on experimental results, and performed structural design of the equipment accordingly. To conduct simulation analysis and optimization, material parameters were calibrated. The working process of foreign object separation was simulated and optimized using discrete element method (DEM) simulation, verifying the equipment’s separation capability for different adhesive foreign objects while determining the optimal rotational speed of 600 r/min. Through EDEM-Fluent coupled simulation, the working process of foreign object removal was analyzed and optimized, validating the influence of flow field on foreign object removal and determining the optimal air velocity of 11 m/s. The equipment was ultimately fabricated, with further parameter optimization and comprehensive performance testing conducted. The final optimal rotational speed and air velocity were determined as 650 r/min and 11 m/s, respectively. In terms of comprehensive performance, the equipment achieved a separation rate of 93.76%, damage rate of 3.05%, residue rate of 4.28%, removal rate of 94.52%, carry-over ratio of 71:1, and processing capacity of 120 kg/h. Full article

Constipation is a prevalent gastrointestinal disorder that significantly impairs quality of life. While pharmacological agents such as loperamide are widely used to induce constipation in experimental models, there is increasing interest in natural alternatives for alleviating intestinal dysfunction. In this study, we investigated the laxative effects of soybean powder fermented by Bacillus subtilis DKU_09 in a loperamide-induced rat model of constipation. The probiotic strain was isolated from cheonggukjang, a traditional Korean fermented soybean paste, and its identity was confirmed through 16S rRNA sequencing. Fermented soybean powder was characterized morphologically via scanning electron microscopy and chemically via HPLC to assess its isoflavone content. Rats were administered loperamide (5 mg/kg) for four days to induce constipation and were then treated with fermented soybean powder at doses of 100, 200, or 300 mg/kg. No pharmacological laxatives (e.g., PEG) were used as a positive control; instead, values from the treatment groups were compared with those from the loperamide-only constipation group. Key outcomes of fecal output, water content, colonic fecal retention, and gastrointestinal transit ratio were measured. The fermented product significantly improved stool frequency and moisture content, reduced colonic fecal retention, and restored gastrointestinal transit in a dose-dependent manner. Notably, the 300 mg/kg group demonstrated nearly complete recovery of fecal parameters without affecting body weight. Statistical analysis was performed using one-way ANOVA followed by Tukey’s post hoc test. These findings suggest that Bacillus subtilis-fermented soybean powder exerts synergistic laxative effects through the combined action of probiotic viability and fermentation-enhanced bioactive compounds such as aglycone isoflavones. This study supports the potential use of fermented soybean-based nutraceuticals as a natural and safe intervention for constipation and gastrointestinal dysregulation. Full article

Background and Objectives: The cytokine IL-6, methyltransferase NSD2, pro-protein convertase Furin, and growth factor receptor IGF-1R are essential factors in the proliferation of cancer cells. These proteins are involved in the tumor process by generating several cell-signaling pathways. However, the interactions of these oncogenic biomarkers, Furin, IL-6, and NSD2, and their links with the inhibitor SERPINA-1 remain largely unknown. Materials and Methods: Cell proliferation is measured by colorimetric and enzymatic methods. The genetic expressions of SERPINA-1, Furin, IL-6, and NSD2 are measured by qRT-PCR, while the expression of IGF-1R on the cell surface is measured by flow cytometry. Results: The proliferation of cells overexpressing SERPINA-1 (JP7pSer+) is decreased by more than 90% compared to control cells (JP7pSer-). The kinetics of the gene expression ratios of Furin, IL-6, and NSD2 show an increase for 48 h, followed by a decrease after 72 h for the three biomarkers in JP7pSer+ cells compared to JP7pSer- cells. The expression of IGF-1R on the cell surface in both cell lines is low, with JP7pSer- cells expressing 1.33 times more IGF-1R than JP7pSer+ cells. Conclusions: These results suggest gene correlations of SERPINA-1 overexpression with decreased cell proliferation and modulation of gene expression of Furin, IL-6, and NSD2. This study should be complemented by molecular transcriptomic and proteomic experiments to better understand the interaction of SERPINA-1 with IL-6, Furin, and NSD2, and their effect on tumor progression. Full article

It is imperative to comprehend the cyclical variations inherent in liquid methane engines (LMEs) across both design and operational domains. The theoretical thermal efficiency of LMEs is high at higher compression ratios, but the combustion instability also increases. Obtaining relevant metrics from bench experiments is difficult and time-consuming; therefore, in this study, we model tabular data using Conditional GAN (CTGAN) to model the tabular data and generated more virtual samples based on the experimental results of the key metrics (peak pressure, maximum pressure rise rate, and average effective pressure). Through this, a machine learning model was proposed that couples a random forest (RF) model with a Bayesian optimization machine learning model for predicting cyclic variation. The findings indicate that the Bayesian-optimized RF model demonstrates superiority in predicting the metrics with greater accuracy and reliability compared to the gradient boosting (XGBoost) and support vector machine (SVM) models. The R² value of the former model is consistently greater than 0.75, and the root mean square error (RMSE) is typically lower than 0.3. This paper highlights the promising potential of the Bayesian-optimized RF model in predicting unknown cyclic parameters. Full article

Aiming at the lightweight design of a bridge-shed integration structure, this paper presents a three-layered absorbing system in which a part of the sand cushion is replaced by expanded polystyrene (EPS) geofoam and the reinforced concrete (RC) protective slab is arranged above the sand cushion to enhance the composite system’s safety. A three-dimensional Smoothed Particle Hydrodynamics–Finite Element Method (SPH-FEM) coupled numerical model is developed in LS-DYNA (Livermore Software Technology Corporation, Livermore, CA, USA, version R13.1.1), with its validity rigorously verified. The dynamic response of rockfall impacts on the shed slab with composite cushions of various thicknesses is analyzed by varying the thickness of sand and EPS materials. To optimize the cushion design, a specific energy dissipation ratio (SEDR), defined as the energy dissipation rate per unit mass (η/M), is introduced as a key performance metric. Furthermore, the complicated interactional mechanism between the rockfall and the optimum-thickness composite system is rationally interpreted, and the energy dissipation mechanism of the composite cushion is revealed. Using logistic regression, the ultimate stress state of the reactive powder concrete (RPC) slab is methodically analyzed, accounting for the speed and mass of the rockfall. The results are indicative of the fact that the composite cushion not only has less dead weight but also exhibits superior impact resistance compared to the 90 cm sand cushions; the impact resistance performance index SEDR of the three-layered absorbing system reaches 2.5, showing a remarkable 55% enhancement compared to the sand cushion (SEDR = 1.61). Additionally, both the sand cushion and the RC protective slab effectively dissipate most of the impact energy, while the EPS material experiences relatively little internal energy build-up in comparison. This feature overcomes the traditional vulnerability of EPS subjected to impact loads. One of the highlights of the present investigation is the development of an identification model specifically designed to accurately assess the stress state of RPC slabs under various rockfall impact conditions. Full article

Accurate parameter estimation is essential for gravitational wave data analysis. In extreme mass-ratio inspiral binary systems, orbital eccentricity is a critical parameter for parameter estimation. However, the current software for the parameter estimation of the gravitational wave often neglects the direct estimation of orbital eccentricity. To fill this gap, we have developed the MatBYIB, a MATLAB-based software (Version 1.0) package for the parameter estimation of the gravitational wave with arbitrary eccentricity. The MatBYIB employs the Analytical Kludge waveform as a computationally efficient signal generator and computes parameter uncertainties via the Fisher Information Matrix and the Markov Chain Monte Carlo. For Bayesian inference, we implement the Metropolis–Hastings algorithm to derive posterior distributions. To guarantee convergence, the Gelman–Rubin convergence criterion (the Potential Scale Reduction Factor $\widehat{R}$) is used to determine sampling adequacy, with MatBYIB dynamically increasing the sample size until $\widehat{R}<1.05$ for all parameters. Our results demonstrate strong agreement between predictions based on the Fisher Information Matrix and full MCMC sampling. This program is user-friendly and allows for the estimation of the gravitational wave parameters with arbitrary eccentricity on standard personal computers. Full article

Introduction: This study evaluated the performance of automated dual-energy computed tomography (DECT)-based quantification of perfusion defects (PDs) in acute pulmonary embolism and examined its correlation with clinical parameters. Methods: We retrospectively analyzed data from 171 patients treated for moderate-to-severe acute pulmonary embolism, who underwent DECT imaging at two separate time points. PDs were quantified using a fully automated AI-based segmentation method that relied exclusively on iodine perfusion maps. This was compared with a semi-automatic clinician-guided segmentation, where radiologists manually adjusted thresholds to eliminate artifacts. Clinical variables including the Miller obstruction score, right-to-left ventricular diameter ratio, oxygen saturation, and patient-reported symptoms were also collected. Results: The semiautomatic method demonstrated stronger correlations with embolic burden (Miller score; r = 0.4, p < 0.001 at follow-up) and a negative correlation with oxygen saturation (r = −0.2, p = 0.04). In contrast, the fully automated AI-based quantification consistently produced lower PD values and demonstrated weaker associations with clinical parameters. Conclusions: Semiautomatic quantification of PDs currently provides superior accuracy and clinical relevance for evaluating lung PDs in acute pulmonary embolism. Future multimodal AI models that incorporate both anatomical and clinical data may further enhance diagnostic precision. Full article

This study investigates the influence of façade-design parameters on daylighting performance in hot arid climates, with a particular focus on Egypt. A total of nine façade configurations of a residential building were modeled and simulated using Autodesk Revit and Insight 360, varying three critical variables: glazing type (clear, blue, and dark), Window-to-Wall Ratio (WWR) of 15%, 50%, 75%, and indoor wall finish (light, moderate, dark) colors. These were compared to the Leadership in Energy and Environmental Design (LEED) daylighting quality thresholds. The results revealed that clear glazing paired with high WWR (75%) achieved the highest Spatial Daylight Autonomy (sDA), reaching up to 92% in living spaces. However, this also led to elevated Annual Sunlight Exposure (ASE), with peak values of 53%, exceeding the LEED discomfort threshold of 10%. Blue and dark glazing types successfully reduced ASE to as low as 0–13%, yet often resulted in underlit spaces, especially in private rooms such as bedrooms and bathrooms, with sDA values falling below 20%. A 50% WWR emerged as the optimal balance, providing consistent daylight distribution while maintaining ASE within acceptable limits (≤33%). Similarly, moderate color wall finishes delivered the most balanced lighting performance, enhancing sDA by up to 30% while controlling reflective glare. Statistical analysis using Pearson correlation revealed a strong positive relationship between sDA and ASE (r = 0.84) in highly glazed, clear glass scenarios. Sensitivity analysis further indicated that low WWR configurations of 15% were highly influenced by glazing and finishing types, leading to variability in daylight metrics reaching ±40%. The study concludes that moderate glazing (blue), medium WWR (50%), and moderate color indoor finishes provide the most robust daylighting performance across diverse room types. These findings support an evidence-based approach to façade design, promoting visual comfort, daylight quality, and sustainable building practices. Full article

This study evaluates the potential use of reclaimed sand from municipal wastewater treatment plants (WWTP), categorized as waste under code 19 08 02, as a full substitute for natural sand in cement mortars. The sand was subjected to alkaline pretreatment using sodium hydroxide (NaOH) at concentrations of 0.5%, 1% and 2% to reduce organic impurities and improve surface cleanliness. All mortar mixes were prepared using CEM I 42.5 R as the binder, maintaining a constant water-to-cement ratio of 0.5. Mechanical testing revealed that mortars produced with 100% WWTP-derived sand, pretreated with 0.5% NaOH, achieved a mean compressive strength of 51.9 MPa and flexural strength of 5.63 MPa after 28 days, nearly equivalent to reference mortars with standardized construction sand (52.7 MPa and 6.64 MPa, respectively). In contrast, untreated WWTP sand resulted in a significant performance reduction, with compressive strength averaging 30.0 MPa and flexural strength ranging from 2.55 to 2.93 MPa. The results demonstrate that low-alkaline pretreatment—particularly with 0.5% NaOH—allows for the effective reuse of WWTP waste sand (code 19 08 02) in cement mortars based on CEM I 42.5 R, achieving performance comparable to conventional materials. Although higher concentrations, such as 2% NaOH, are commonly recommended or required by standards for the removal of organic matter from fine aggregates, the results suggest that lower concentrations (e.g., 0.5%) may offer a better balance between cleaning effectiveness and mechanical performance. Nevertheless, 2% NaOH remains the obligatory reference level in some standard testing protocols for fine aggregate purification. Full article

We consider the problem of privately updating a message out of K messages from N replicated and non-colluding databases where a user has an outdated version of the message ${\hat{W}}_{\theta }$ of length L bits that differ from the current version $W_{\theta }$ in at most f bits. The user also has a cache containing coded combinations of the K messages (with a pre-specified structure), which are unknown to the N databases (unknown prefetching). The cache Z contains ℓ linear combinations from all K messages in the databases with $r=\frac{\mathcal{l}}{L}$ being the caching ratio. The user needs to retrieve $W_{\theta }$ correctly using a private information retrieval (PIR) scheme without leaking information about the message index $\theta$ to any individual database. Our objective is to jointly design the prefetching (i.e., the structure of said linear combinations) and the PIR strategies to achieve the least download cost. We propose a novel achievable scheme based on syndrome decoding where the cached linear combinations in Z are designed to be bits pertaining to the syndrome of $W_{\theta }$ according to a specific linear block code. We derive a general lower bound on the optimal download cost for $0\le r\le 1$, in addition to achievable upper bounds. The upper and lower bounds match for the cases when r is exceptionally low or high, or when $K=3$ messages for arbitrary r. Such bounds are derived by developing novel cache-aided arbitrary message length PIR schemes. Our results show a significant reduction in the download cost if $f<{\displaystyle \frac{L}{2}}$ when compared with downloading $W_{\theta }$ directly using typical cached-aided PIR approaches. Full article

CT scanners are essential tools in modern medical imaging. Sudden failures of their X-ray tubes can lead to equipment downtime, affecting healthcare services and patient diagnosis. However, existing prediction methods based on a single model struggle to adapt to the multi-stage variation characteristics of tube lifespan and have limited modeling capabilities for temporal features. To address these issues, this paper proposes an intelligent prediction architecture for CT tubes’ remaining useful life based on a dual-branch neural network. This architecture consists of two specialized branches: a residual self-attention BiLSTM (RSA-BiLSTM) and a multi-layer dilation temporal convolutional network (D-TCN). The RSA-BiLSTM branch extracts multi-scale features and also enhances the long-term dependency modeling capability for temporal data. The D-TCN branch captures multi-scale temporal features through multi-layer dilated convolutions, effectively handling non-linear changes in the degradation phase. Furthermore, a dynamic phase detector is applied to integrate the prediction results from both branches. In terms of optimization strategy, a dynamically weighted triplet mixed loss function is designed to adjust the weight ratios of different prediction tasks, effectively solving the problems of sample imbalance and uneven prediction accuracy. Experimental results using leave-one-out cross-validation (LOOCV) on six different CT tube datasets show that the proposed method achieved significant advantages over five comparison models, with an average MSE of 2.92, MAE of 0.46, and R² of 0.77. The LOOCV strategy ensures robust evaluation by testing each tube dataset independently while training on the remaining five, providing reliable generalization assessment across different CT equipment. Ablation experiments further confirmed that the collaborative design of multiple components is significant for improving the accuracy of X-ray tubes remaining life prediction. Full article