Search

Particle size is a critical parameter for calculating the solid phase holdup and settling velocity in pipeline suspensions. However, accurately determining solid holdup remains challenging due to the complexity and variability in multiphase suspensions, especially when the physical size of the suspended particles is unknown. We have developed a novel multi-frequency particle size measurement system that utilizes acoustic backscatter techniques. Furthermore, we propose a new particle size inversion algorithm that integrates Empirical Mode Decomposition (EMD) and the Pearson Correlation Coefficient (PCC) with traditional algorithms. By applying EMD, the raw echo signal is decomposed into Intrinsic Mode Functions (IMFs), allowing for effective noise separation. The PCC is subsequently used to determine correlations between IMFs, improving signal reconstruction accuracy. The minimum concentration gradient continuous inversion algorithm we proposed effectively solves the multi-solution problem of the energy ratio algorithm through the minimum concentration difference method. This algorithm innovatively employs sliding window technology to accurately assess the optimal particle size range of suspended particles in the ultrasonic measurement path. Experimental results indicate that the Mean Absolute Percentage Error (MAPE) for particle diameters in the ranges of 280–350 μm, 450–550 μm, and 760–880 μm are 7.16 %, 3.87 %, and 4.66 %, respectively. This method provides a precise and efficient solution for measuring particle size distribution in underground pipelines, with broad applications in pipeline maintenance, sediment transport modeling, and drainage system design. • A multi-frequency acoustic system was developed for real-time assessment of particle size in urban rainwater pipelines. • EMD and PCC techniques were applied to decouple flow noise, significantly improving echo signal reconstruction accuracy. • A novel algorithm was proposed for particle size assessment in low-concentration suspensions, achieving MAPE below 10%. • The new algorithm reduces particle size inversion time by 67% compared to traditional methods without compromising accuracy. • Ultrasonic measurement reduces MAPE by 13% compared to image recognition techniques in particle size assessment. [ABSTRACT FROM AUTHOR]

• An efficient reverse approximation frequency adaptive conductivity test circuit is realized by using full-wave rectification design. • A new frequency adaptive conductivity measurement model is proposed. • The complex problem of solving the time constant τ is avoided. • Effectively improve the detection accuracy of two-electrode conductivity equipment. Accurately measuring the solution conductivity is important both for environmental assessment and process monitoring. A reverse approximation frequency adaptive conductivity test method is proposed in this paper. This method avoids the complex calculation of the time constant τ of the first-order resistance-capacitance network and eliminates the influence of the accessory capacitance on the measurement results to the greatest extent. Through 9 groups of optimal frequency selection experiments, the optimal measurement frequency of R 1 and R x fixed ratio in a certain range is obtained. The optimal measurement frequency and dimensionless relationship model constitute a complete frequency adaptive solution conductivity measurement method.Through comparative analysis, the mean absolute percentage error of the measurement results is 2.65%, which not only improves the measurement accuracy of the existing self-developed equipment but also provides a new solution to solve the influence of additional capacitance in the conductivity measurement process. [ABSTRACT FROM AUTHOR]

Abstract: Aims: To investigate whether ischemia/reperfusion (I/R)-induced apoptosis in the bile duct epithelium could be mediated by tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) receptors in biliary epithelial cells, we examined the effects of hypoxia/reoxygenation (H/R) on TRAIL cytotoxicity. Main methods: Using an H/R model, normal primary human intrahepatic biliary epithelial cells were exposed to hypoxia for 1 h, and then reoxygenated. Expressions of death receptor 4 (DR4) and DR5 mRNA and protein were measured. After 1 h of hypoxia, biliary epithelial cells were treated with TRAIL in different concentrations for 4 h. The death of biliary epithelial cells was confirmed by analysis of apoptosis and methylthiazolyl tetrazolium. The activities of caspase-3 and caspase-8 were determined by fluorometric assay. Key findings: Compared with normoxic-cultured cells, the mRNA expressions of DR4 and DR5 were up-regulated from 0 min after reoxygenation, reaching a peak value at 60 min after reoxygenation. The protein expression of DR4 was most intense at 90 min after reoxygenation; the most intense expression of DR5 came at 120 min after reoxygenation. The apoptosis rate increased in the TRAIL treatment group and further increased in the TRAIL plus H/R group, and the effect of concentration-dependent TRAIL-mediated cell killing was more pronounced. Caspase-3 and caspase-8 enzymatic activities after H/R also increased with increased TRAIL concentration. Significance: H/R up-regulated the expression of DR4 and DR5, and enhanced TRAIL-mediated apoptosis in normal human intrahepatic biliary epithelial cells. [Copyright &y& Elsevier]

[Display omitted] • An improved SSA-based wavelet threshold denoising method was proposed by introducing two adjustable factors. • The Hilbert Huang transform was used to decompose the infrasound signal, and the signal was preliminarily filtered based on Pearson correlation coefficient. • Three wavelet threshold parameters were determined in the infrasound simulation. • Experiments on debris flows with different volumes and velocities were conducted in Jiangjia Gully, and the effectiveness of the method was verified. The measurement and analysis of infrasound are widely utilized in debris flow monitoring and early warning. However, the infrasound signals are often contaminated by noise across various frequencies, posing significant challenges for feature extraction. The current methods for infrasound denoising are somewhat rudimentary and face several constraints. This study introduces a novel method for enhancing infrasound signals through denoising. This approach integrates empirical mode decomposition with an enhanced wavelet threshold algorithm, and improves the conventional wavelet threshold function. This study uses the Signal-to-Noise ratio, smoothness and correlation coefficient to fine-tune the wavelet parameters. Experiments in flumes with varying speeds and volumes were conducted to test the effectiveness of the denoising method. The results demonstrate that, compared to traditional methods, the proposed method improves the SNR by averages of 69.56%, 60.91%, and 55.63%. It offers a new alternative for the noise reduction of debris flow infrasound signals. [ABSTRACT FROM AUTHOR]

• The nonlinear and temperature drift characteristics for silicon piezoresistive pressure sensor are tested and analyzed. • The adjustable nonlinearity convergence factor, the weight vector and weight adjustment coefficient are proposed and established. • The comprehensive compensation method based on surface fitting and improved grey wolf algorithm is established. • The full range is better than 0.03 %, and the local range is less than 0.02 % with reducing fitting data. • The proposed method is easy to be used for piezoresistive pressure sensor without adding the additional hardware and software code. The optimized surface fitting method base on improved gray wolf algorithm (IGWO) is proposed to overcome the nonlinearity and temperature drift of piezoresistive pressure sensor. To improve the convergence rate and search ability of gray wolf optimization algorithm (GWO), the adjustable nonlinearity convergence factor is established. The weight vector and weight adjustment coefficient are integrated into the residual function of the least square method. Employing the maximum full range error as the fitness function, the least square method is continuously optimized by IGWO to establish the high-performance comprehensive compensation mathematical formula. The simulation and practical test results indicate that the maximum full-scale error in the full range is better than 0.03 %, and the maximum full-scale error in the local range is less than 0.02 % especially. The proposed method proposed method is very suitable for the application and production of industrial pressure sensor with many advantages. [ABSTRACT FROM AUTHOR]

Zygotic gene activation (ZGA) is one of the most important events after mouse fertilization, but the mechanisms underpinning it are still unclear. Estrogen receptor alpha (ERα) is a versatile player in animal development. Our preliminary studies showed that ERα-specific antagonists blocked mouse 2-cell development and inhibited ZGA related gene expression, indicating an indispensable role of maternal ERα in early mouse preimplantation embryo development (PED). Here, we performed immunostaining detection to investigate the cell cycle specific subcellular localization of ERα, and serine 118 phosphorylated ERα (pERα-S118), during the first two cleavages of mouse PED. Our results showed that ERα nuclear localization appeared at 1-cell S-phase, disappeared at metaphase, and reappeared since the G1 phase of 2-cell embryos. Nuclear expression of pERα-S118 started at the 1-cell S-phase, but was absent at the G1 phase of 2-cell embryos, and reappeared since the 2-cell S-phase. Interestingly, pERα-S118 showed a dynamic expression pattern among nuclear, nuclear surface, cytoplasm and cell membrane. These results indicate that maternal derived ERα might still function in the first two cleavages of mouse PED, during which ZGA occurs. [ABSTRACT FROM AUTHOR]