Search

Copyright of China Pulp & Paper is the property of China Pulp & Paper Magazines Publisher and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Automobile Technology is the property of Automobile Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of the Chinese Society of Agricultural Engineering is the property of Chinese Society of Agricultural Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Forest Engineering is the property of Forest Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper established a high performance liquid chromatography (HPLC) method for the determination of ultraviolet absorber UV-P in an light resistant thermoplastic polyurethane infusion device, and to carry out the research on the dissolution of ultraviolet absorber UV-P from disposable TPU infusion device. Six different types of injections were used to simulate the clinical application conditions, and after infusion with a light resistant TPU infusion device, they were analyzed by high-performance liquid chromatography. Kromasil C18 column was adopted, the mobile phase consisted of methanol-water (90:10), the detection wavelength was 339 nm. The results show that calibration curves of UV-P are linear over the range of 0.061 4~1.638 0 mg/L (r=0.999 9), the average recoveries are both between 97.91% and 101.10%, the relative standard deviation is less than 2%, the signal-to-noise ratio is greater than 3, and the values of quantitation limit is 0.020 48 mg/L. The method is sensitive and good repeatability, which is suitable for the detection of UV-P dissolution in TPU infusion device. [ABSTRACT FROM AUTHOR]

Ellipticity is an important indicator for measuring the deformation of subway shield tunnel segments. The key to ellipticity analysis is the points on the inner wall of the tunnel. Because there are rail beds and pipelines in the subway tunnel, there are many non-inner wall points in the tunnel point cloud with varying distances from the inner wall, which will affect the analysis of ellipticity. Currently, the commonly used method is to use a straight-through filter to process rail beds, but the effect is not good when there is a large clearance between the rails and the bed. For other attachments, the distance threshold method is used, but there is a difficulty in accurately determining the threshold in advance. This paper proposed a distance threshold elimination method for rail bed points and a grading weighting elimination algorithm for attachment points, based on the distribution characteristics of the shield tunnel point cloud. The method ensured that the points used in ellipticity calculation were all inner wall points, improving the accuracy of subway shield tunnel ellipticity analysis. Simulation data shows that the MAE of ellipticity obtained by the algorithm proposed in this paper is 0.085‰, which is better than the direct least squares method and RANSAC algorithm. Based on laser point clouds of 56 single-ring subway tunnels, the performance of the algorithm is tested, with the average MAE of ellipticity for each ring being 0.174‰ and the average standard deviation of ellipticity for each ring being 0.216‰, which is respectively 19.1% and 19.7% higher than the RANSAC algorithm. This demonstrates that the proposed method can effectively eliminate the influence of non-inner wall points in subway tunnel point clouds, and the ellipticity calculation results are robust. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Mining Magazine is the property of China Mining Magazine Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Chongqing University of Technology (Natural Science) is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Geomatics & Information Science of Wuhan University is the property of Geomatics & Information Science of Wuhan University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Because the thermal conductivity of freezing soil is hard to measure, in order to clarify the influence of temperature on thermal conductivity, a hyperbolic model with three parameters was proposed to describe the relationship between thermal conductivity and negative temperature in this paper. Then, the performance of the new hyperbolic model was verified by the measured thermal conductivity coefficients and three widely used models, and a sensitivity analysis of model parameters was performed. The results show that the hyperbolic model can accurately predict the change pattern of soil thermal conductivity during the freezing process. Among these four models, the proposed hyperbolic model has the smallest root mean square error and relative error. The model parameters are closely related to the fine particle content and decrease as the initial volume moisture content increases. Considering the new model can accurately simulate the variation of thermal conductivity with subzero temperature, it can provide a basis for coupled heat and mass transfer in cold regions. [ABSTRACT FROM AUTHOR]

An accurate runoff prediction is the prerequisite for the optimal allocation and efficient utilization of water resources, and the basis for making flood control and disaster reduction decisions. However, due to the influence of human activities, environment, climate and other actors, runoff series show nonlinear, unsteady and multi-scale changes, which increases the difficulty of accurate runoff prediction. In order to improve the accuracy and credibility of runoff prediction, this paper combines the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) method. Quantum Particle Swarm Optimization (QPSO), Broad Learning System (BLS) model, a combined runoff prediction model based on CEEEDAN-QPSO-BLS is proposed. Firstly, CEEMDAN method is used to decompose the original runoff signal to obtain several relatively stationary intrinsic mode components. Secondly, the QPSO algorithm is used to optimize the number of node groups in the feature layer, the number of node groups in the enhancement layer and the number of nodes in the group of BLS model, and the optimal topology structure of the width learning network is obtained. Then, the optimal QPSO-BLS is used to predict multiple steady-state components, and the prediction components are reconstructed so as to obtain higher prediction accuracy. In this model, the daily runoff value of Xiaolangdi Reservoir in the Yellow River Basin is used as the experimental data, and EMD-QPSO-BLS and QPSO-BLS are used as the comparison model of CEEMDAN-QPSO-BLS. Nash-Sutcliffe efficiency coefficient (NSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Per centage Error (MAPE) are used to evaluate the reliability and accuracy of the model prediction. The experimental results show that, compared with QPSO-BLS with EMD-QPSO-BLS models, the prediction accuracy of CEEMDAN-QPSO-BLS is improved by 79.87% and 19.80%, and the credibility is improved by 131.2% and 10.98%, respectively. This paper provides decision-making support for flood control and drought relief to protect people s lives and property and sustainable development. [ABSTRACT FROM AUTHOR]

To enhance the efficiency of RMFS and reduce operating costs, this paper proposed a double-layer planning model for AGV task allocation considering load balancing, following an analysis of key factors causing congestion in RMFS. The upper layer sought to minimize the total cost, while the lower layer addressed the minimization of the system load standard deviation and AGV idle rate through a multi-objective function. It introduced a modified adaptive genetic algorithm(SAGA) to overcome the challenges of low efficiency and susceptibility to local optima in solving task allocation problems using traditional GA. It integrated the sigmoid function was to transform fitness values and participates in the adaptive adjustment of cross-mutation operators. Additionally, it incorporated catastrophic strategies to prevent premature convergence of the algorithm. Finally, it simulated the proposed algorithm on different scale cases, and the results demonstrate that, in comparison to the genetic algorithm, adaptive genetic algorithm, adaptive disaster genetic algorithm, and ant colony algorithm, the improved algorithm exhibits substantial optimization in the experimental results of various scale cases. This suggests that the enhanced algorithm effectively avoids premature convergence, enhances solution quality and convergence stability, actively balances road network load, and reduces total operating costs. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central China Normal University is the property of Huazhong Normal University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Chongqing University of Technology (Natural Science) is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to use the acceleration of the train body vibration to accurately inverse the track longitudinal irregularity value of railroads, this paper proposes a model (GWO--CNN--LSTM)based on Gray Wolf Optimization algorithm (GWO), Convolutional Neural Network (CNN) and Long Short Term Memory Network (LSTM) to construct the relationship between vehicle body vibration acceleration and track longitudinal irregularity value. Firstly, the measured data of the track inspection vehicle are pre-processed according to the characteristics of the data using the PauTa criterion for outlier rejection, and then the processed data are used with the vehicle vibration acceleration as the input of the model in which the track longitudinal irregularity is the output. The CNN is used to learn the waveform information of the vehicle body vibration acceleration, and the features learned by the CNN are input to the LSTM. Finally the key parameters of the LSTM model is optimized with GWO, then the inverse perform of the track longitudinal irregularity value is made. To highlight the adaptability of the model, additional zones are randomly selected for inversion. Three performance metrics are used to evaluate the model and compare with other classical methods. The results show that the root mean square error, the mean absolute error and the goodness of fit of the GWO-CNN-LSTM model are 0.141, 0.107 and 0.977 respectively, and the GWO-CNN combined with LSTM can improve the goodness of fit by 20.1% compared with a single LSTM; compared with recurrent neural network, BP neural network and support vector regression, the proposed GWO--CNN--LSTM model has 68.1%~79.1% lower root mean square error, 60.4%~68.3% lower mean absolute error, and 27.7%~44.9% higher goodness of fit, which verifies the GWO--CNN--LSTM model for inversion of track longitudinal irregularity values validity. The model provides a new idea for the study of railroad track longitudinal irregularity value inversion. [ABSTRACT FROM AUTHOR]

In this paper, the inactivation kinetics of potassium sorbate-assisted high pressure thermal sterilization (HPTS) on Bacillus subtilis spores were studied. First-order kinetics model, Weibull and Log-logistic kinetics models were used to fit the inactivation curve of B. subtilis spores by potassium sorbate-assisted HPTS. By analysis of precision factor (Df), bias factor (Bf), root mean square error (RMSE), coefficient of determination (R²), In the three models, Log- logistic Kinetic model fitted best the spore sterilization effect of potassium sorbate-assisted HPTS (R² =0.986). When potassium sorbate (0.2g/100mL) assisted HPTS (600 MPa, 75 25min), the inactivation effect was the best, and the spore inactivation was 6.10 lg (CFU/mL). Potassium sorbate assisted HPTS treatment was applied to the inactivation of spores in muskmelon juice, it was found that the browning degree was significantly reduced, after 28 days of storage, the absorbance of potassium sorbate (0.1g/100mL) assisted HPTS (600 MPa, 75 25 min) at 420 mn reached 0.093, The absorbance of the HPTS-treated control sample was 0.058. Scanning electron microscope was used to observe the microstructure of Bacillus subtilis spores in muskmelon juice before and after treatment, and it was found that the morphological structure of the spores changed after treatment. In conclusion, potassium sorbate assisted HPTS has significant application value. [ABSTRACT FROM AUTHOR]

There are sufficient illumination resources and strong solar radiation in Shiyang River Basin. It is of great significance to estimate the total solar radiation accurately for agricultural production in Shiyang River Basin. In order to evaluate the simulation accuracy of common total solar radiation models in the Shiyang River Basin and determine the model suitable for the estimation of total solar radiation in the Shiyang River Basin, this paper selects 5 types of total solar radiation models based on the meteorological data of Shiyang River Experimental Station of China Agricultural University from 2014 to 2018. Five indexes, namely determination coefficient R2, mean absolute error MAE, root mean square error RMSE, consistency index d and overall evaluation index GPI are used to evaluate the suitability of the solar total radiation model based on different weather types. The results show that the comprehensive model based on percentage of sunshine, average daily temperature and relative humidity has the best simulation effect. In sunny weather, the cubic function A-P model has the best simulation effect. In cloudy weather, the comprehensive model has the best simulation effect, and the estimation model of total solar radiation in Shiyang River Basin based on weather combination is proposed, which provides a further model support for the estimation of total solar radiation in Shiyang River Basin. [ABSTRACT FROM AUTHOR]

Copyright of Food & Fermentation Industries is the property of Food & Fermentation Industries and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A rapid and simultaneous lateral flow immunochromatography (LFIC) method was established based on colloidal gold (CG) for testing three addictive drugs in milk tea, including methamphetamine (MET), ketamine (KET), and cocaine (COC).After optimizing the key parameters, such as the concentration of coated antigen, the combination position of the three analytes, and the immunoreaction time, the developed method could be used for the simultaneous identification of three target addictive drays in a milk tea sample with a lower concentration could be tested.The limits of detection of MET, KET, and COC were 1.60, 1.59, and 1.39 ng/mL, respectively.In milk tea samples, the mean recoveries of the three types of mixed reference analytes ranged from 90% to 109% with a relative standard deviation of less than 5%.Briefly, the multiple CG-LFIC method had the advantages of easy operation, fast analysis, high sensitivity, and good specificity.It can be an effective method for simultaneous screening addictive drugs in milk tea and provides promising applications in the bio-detection field. [ABSTRACT FROM AUTHOR]