Description: The aim of this study was to investigate the possible protective role of sodium selenite on aflatoxin B1-induced oxidative stress and apoptosis in spleen of broilers. Two hundred one-day-old male broilers, divided into five groups, were fed with basal diet (control group), 0.3 mg/kg AFB1 (AFB1 group), 0.3 mg/kg AFB1 + 0.2 mg/kg Se (+Se group I), 0.3 mg/kg AFB1 + 0.4 mg/kg Se (+Se group II) and 0.3 mg/kg AFB1 + 0.6 mg/kg Se (+Se group III), respectively. According to biochemical assays, AFB1 significantly decreased the activities of glutathione peroxidase, total superoxide dismutase, glutathione reductase, catalase and the level of glutathione hormone, while it increased the level of malondialdehyde. Moreover, AFB1 increased the percentage of apoptosis cells by flow cytometry and the occurrence of apoptotic cells by TUNEL assay. Simultaneous supplementation with sodium selenite restored these parameters to be close to those in control group. In conclusion, sodium selenite exhibited protective effects on AFB1-induced splenic toxicity in broilers by inhibiting oxidative stress and excessive apoptosis.

Description: Nowadays, sensor development focuses on miniaturization and non-contact measurement. According to the D-dot principle, a D-dot voltage sensor with a new structure was designed based on the differential D-dot sensor with a symmetrical structure, called an asymmetric open D-dot voltage sensor. It is easier to install. The electric field distribution of the sensor was analyzed through Ansoft Maxwell and an open D-dot voltage sensor was designed. This open D-voltage sensor is characteristic of accessible insulating strength and small electric field distortion. The steady and transient performance test under 10 kV-voltage reported satisfying performances of the designed open D-dot voltage sensor. It conforms to requirements for a smart grid measuring sensor in intelligence, miniaturization and facilitation.

Description: In line with the wider application of non-contact voltage transducers in the engineering field, transducers are required to have better performance for different measuring environments. In the present study, the D-dot voltage transducer is further improved based on previous research in order to meet the requirements for long-distance measurement of electric transmission lines. When measuring three-phase electric transmission lines, problems such as synchronous data collection and composite electric field need to be resolved. A decomposition method is proposed with respect to the superimposed electric field generated between neighboring phases. The charge simulation method is utilized to deduce the decomposition equation of the composite electric field and the validity of the proposed method is verified by simulation calculation software. With the deduced equation as the algorithm foundation, this paper improves hardware circuits, establishes a measuring system and constructs an experimental platform for examination. Under experimental conditions, a 10 kV electric transmission line was tested for steady-state errors, and the measuring results of the transducer and the high-voltage detection head were compared. Ansoft Maxwell Stimulation Software was adopted to obtain the electric field intensity in different positions under transmission lines; its values and the measuring values of the transducer were also compared. Experimental results show that the three-phase transducer is characterized by a relatively good synchronization for data measurement, measuring results with high precision, and an error ratio within a prescribed limit. Therefore, the proposed three-phase transducer can be broadly applied and popularized in the engineering field.

Description: An easy, but effective, method has been proposed to detect and quantify the Pb(II) in the presence of Cd(II) based on a Bi/glassy carbon electrode (Bi/GCE) with the combination of a back propagation artificial neural network (BP-ANN) and square wave anodic stripping voltammetry (SWASV) without further electrode modification. The effects of Cd(II) in different concentrations on stripping responses of Pb(II) was studied. The results indicate that the presence of Cd(II) will reduce the prediction precision of a direct calibration model. Therefore, a two-input and one-output BP-ANN was built for the optimization of a stripping voltammetric sensor, which considering the combined effects of Cd(II) and Pb(II) on the SWASV detection of Pb(II) and establishing the nonlinear relationship between the stripping peak currents of Pb(II) and Cd(II) and the concentration of Pb(II). The key parameters of the BP-ANN and the factors affecting the SWASV detection of Pb(II) were optimized. The prediction performance of direct calibration model and BP-ANN model were tested with regard to the mean absolute error (MAE), root mean square error (RMSE), average relative error (ARE), and correlation coefficient. The results proved that the BP-ANN model exhibited higher prediction accuracy than the direct calibration model. Finally, a real samples analysis was performed to determine trace Pb(II) in some soil specimens with satisfactory results.

Description: Energies, Vol. 10, Pages 2050: Investigation of the Ampacity of a Prefabricated Straight-Through Joint of High Voltage Cable Energies doi: 10.3390/en10122050 Authors: Pengyu Wang Gang Liu Hui Ma Yigang Liu Tao Xu This paper presents a theoretical and experimental study on the ampacity of the prefabricated straight-through joint of a 110 kV high voltage cable. Thermal modelling revealed that the critical spot limiting the ampacity of this type of cable joint is located on its crosslinked polyethylene (XLPE) insulation section. The axial distribution of the thermal field in this type of cable joint was also determined. An algorithm for assessing ampacity in this type of cable joint was developed. Experiments were conducted on a real cable system with a prefabricated straight-through joint under different loading conditions. The experiments show a good agreement with the thermal modelling results.

Description: Water, Vol. 9, Pages 947: Measurement and Simulation of Soil Water Contents in an Experimental Field in Delta Plain Water doi: 10.3390/w9120947 Authors: Wenjuan Hua Chuanhai Wang Gang Chen Hai Yang Yue Zhai Variation in soil water content in the delta plain has its own particularity and is significant for agricultural improvement, the utilization of water resources and flood risk mitigation. In this study, experimental data collected from a plot of farmland located in the Taihu Basin were used to investigate the temporal and vertical variation of soil water content, as well as the effects of individual rainfall on soil water and shallow groundwater and their interaction. The results showed that the variation of soil water content is dependent on the comprehensive influence of soil hydraulic properties, meteorological factors and shallow groundwater and the correlation to the groundwater table is the strongest due to the significant capillary action in the delta plain. A saturated-unsaturated three-dimensional soil water numerical model was developed for the study area in response to rainfall and evapotranspiration. Scenario simulations were performed with different soil depths for soil water content and the error source was analyzed to improve the model. The average RMSE, RE and R2 values of the soil water content at the five depths between the measured and simulated results were 0.0192 cm3·cm−3, 2.09% and 0.8119, respectively. The results indicated that the developed model could estimate vertical soil water content and its dynamics over time at the study site at an acceptable level. Moreover, further research and application to other sites in delta plains are necessary to verify and improve the model.

Description: Energies, Vol. 10, Pages 1541: Techniques for Reduction of the Cogging Torque in Claw Pole Machines with SMC Cores Energies doi: 10.3390/en10101541 Authors: Chengcheng Liu Jiawei Lu Youhua Wang Gang Lei Jianguo Zhu Youguang Guo As one of the main parasitic parameters in permanent magnet (PM) synchronous machines (PMSMs), cogging torque is the main component of the torque ripple, which has always been the handicap in the high-performance, low-speed drive systems. Over the last two decades, various methods have been proposed to decrease the cogging torque in both radial-flux and axial-flux PMSMs. Among these methods, stator slot skewing, stator tooth notching, permanent magnet (PM) skewing, PM shifting, and pole pairing are extensively investigated. However, little work has been done on reducing the cogging torque of the claw pole machine (CPM), whose cogging torque cannot be ignored. In this paper, the general methods that have been used to reduce the cogging torque in radial-flux and axial-flux PMSMs are developed and verified in a CPM with a soft magnetic composite (SMC) core. The 3-D finite element method (FEM) is used to calculate the cogging torque and PM flux linkage per turn. By comparing different cogging torque reduction technologies, it can be found that the magnet step skewing and unequal claw pole width are very suitable for CPM.

Description: Remote Sensing, Vol. 9, Pages 1215: Preliminary Analysis of Chinese GF-3 SAR Quad-Polarization Measurements to Extract Winds in Each Polarization Remote Sensing doi: 10.3390/rs9121215 Authors: Lin Ren Jingsong Yang Alexis Mouche He Wang Juan Wang Gang Zheng Huaguo Zhang This study analyzed the noise equivalent sigma zero (NESZ) and ocean wind sensitivity for Chinese C-band Gaofen-3 (GF-3) quad-polarization synthetic aperture radar (SAR) measurements to facilitate further operational wind extraction from GF-3 data. Data from the GF-3 quad-polarization SAR and collocated winds from both NOAA/NCEP Global Forecast System (GFS) atmospheric model and National Data Buoy Center (NDBC) buoys were used in the analysis. For NESZ, the co-polarization was slightly higher compared to the cross-polarization. Regarding co-polarization and cross-polarization, NESZ was close to RadarSAT-2 and Sentinel-1 A. Wind sensitivity was analyzed by evaluating the dependence on winds in terms of normalized radar cross-sections (NRCS) and polarization combinations. The closest geophysical model function (GMF) and the polarization ratio (PR) model to GF-3 data were determined by comparing data and the model results. The dependence of co-polarized NRCS on wind speed and azimuth angle was consistent with the proposed GMF models. The combination of CMOD5 and CMOD5.N was considered to be the closest GMF in co-polarization. The cross-polarized NRCS exhibited a strong linear relationship with moderate wind speeds higher than 4 m·s−1, but a weak correlation with the azimuth angle. The proposed model was considered as the closest GMF in cross-polarization. For polarization combinations, PR and polarization difference (PD) were considered. PR increased only with the incidence angle, whereas PD increased with wind speed and varied with azimuth angle. There were three very close PR models and each can be considered as the closest. Preliminary results indicate that GF-3 quad-polarization data are valid and have the ability to extract winds in each polarization.

Description: This paper documents the condition-based maintenance (CBM) of power transformers, the analysis of which relies on two basic data groups: structured (e.g., numeric and categorical) and unstructured (e.g., natural language text narratives) which accounts for 80% of data required. However, unstructured data comprised of malfunction inspection reports, as recorded by operation and maintenance of the power grid, constitutes an abundant untapped source of power insights. This paper proposes a method for malfunction inspection report processing by deep learning, which combines the text data mining–oriented recurrent neural networks (RNN) with long short-term memory (LSTM). In this paper, the effectiveness of the RNN-LSTM network for modeling inspection data is established with a straightforward training strategy in which we replicate targets at each sequence step. Then, the corresponding fault labels are given in datasets, in order to calculate the accuracy of fault classification by comparison with the original data labels and output samples. Experimental results can reflect how key parameters may be selected in the configuration of the key variables to achieve optimal results. The accuracy of the fault recognition demonstrates that the method we proposed can provide a more effective way for grid inspection personnel to deal with unstructured data.

Description: IJGI, Vol. 7, Pages 193: Implementation of a Parallel GPU-Based Space-Time Kriging Framework ISPRS International Journal of Geo-Information doi: 10.3390/ijgi7050193 Authors: Yueheng Zhang Xinqi Zheng Zhenhua Wang Gang Ai Qing Huang In the study of spatiotemporal geographical phenomena, the space–time interpolation method is widely applied, and the demands for computing speed and accuracy are increasing. For nonprofessional modelers, utilizing the space–time interpolation method quickly is a challenge. To solve this problem, the classical ordinary kriging algorithm was selected and expanded to a spatiotemporal kriging algorithm. Using the OpenCL framework to integrate central processing unit (CPU) and graphic processing unit (GPU) computing resources, a parallel spatiotemporal kriging algorithm was implemented, and three experiments were conducted in this work to verify the results. The results indicated the following: (1) when the size of the prediction point dataset is consistent, the performance of the method is robust with the increasing size of the observation point dataset; (2) the acceleration effect of the parallel method increases with an increased number of predicted points. Compared with the original sequential program, the implementation of the improved parallel framework showed a 3.23 speedup, which obviously shortens the interpolation time; (3) when cross-validating the temperature data in the Beijing Tianjin Hebei region, the space–time acceleration model provides a better fit than traditional pure space interpolation.