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High calcium fly ash slurry has a high pH value, which is prone to contaminating groundwater when it is directly used for fire prevention and extinguishing in gob. To study the reaction characteristics of carbon fixation and alkali reduction in the production of underground fire extinguishing materials using fly ash by CO2 mineralization, the fly ash from a coal and electricity integrated enterprise in northern Shaanxi is used to analyze its composition and phase structure through XRF and XRD. At the same time, using a mixture of N2 and CO2, laboratory experiments on CO2 mineralization is conducted to analyze the variation law of pH value during the carbon fixation and alkali reduction reaction process of fly ash, and the influence of key parameters such as CO2 concentration, gas flow rate, solid-liquid ratio, temperature and stirring method on the mineralization reaction process. Also, the key technologies that need to be addressed for a large-scale underground application are proposed from the characteristics of fly ash carbon fixation and alkali reduction, development of mineralization reaction equipment, diffusion law of slurry in gob, and the entire preparation process. The research results indicate that fly ash is rich in alkali metal elements such as Ca2+, Mg2+, K+, Al3+, with CaO content of up to 17.8%, belonging to high calcium ash. CO2 can be reacted with Ca2+, Mg2+ in the fly ash and CO2 is attached to the surface of spherical particles of fly ash with calcium carbonate type after the reaction, indicating the feasibility of carbon sequestration and alkali reduction of high calcium fly ash. During the mineralization reaction process, the pH value of the slurry decreases in three stages: slow−fast−slow. When the pH value of the fly ash slurry drops to 7.0−7.5, the pH value return will not exceed 9, meeting the requirements for fire prevention and extinguishing materials for coal mine gob. The optimal mineralization reaction parameters are that CO2 concentration being of 10%−15%, solid-liquid ratio being of 300 g/L, gas flow rate being of 1.0 L/min per liter of slurry, and temperature being not higher than 55 ℃. Taking into account factors such as carbon sequestration, alkali reduction and return rate, and reaction scale, a two-stage coupled reaction system consisting of a vortex reactor and a propeller reactor is proposed.

In order to realize the effective development of shale oil with low maturity in continental faulted basins in Jiyang Depression， systematic evaluations have been carried out simultaneously in Boxing， Niuzhuang， and Minfeng sags since 2019， based on the 10 000 meters of systematic coring and more than 100 000 core tests. Significant breakthroughs have been made in single well evaluation and stereoscopic development of well groups. A pilot test of eight wells in three layers was conducted in Boxing Sag， and the first 100 000-ton shale oil development well group of SINOPEC was built. A large-platform stereoscopic development test of well groups was carried out with 20 wells in five layers， and all wells were put into production in Niuzhuang Sag. A comprehensive overall evaluation and stereoscopic development test was launched in Minfeng Sag， following the mode of “overall deployment of a large platform and step-by-step implementation of a small well group.” Peak daily oil production exceeded one hundred tons in 28 wells， including Wells FYP1 and FY1-1HF ternary-element （storage， fracture， and pressure） storage and flow theory of shale oil in Jiyang Depression was proposed. The technologies of shale oil development， stereoscopic fine evaluation of development sweet spots， integrated modeling and numerical simulation， and stereoscopic development optimization were developed. A theoretical and technical system of stereoscopic development of shale oil in continental faulted basins with Shengli characteristics was initially constructed. It effectively supported the construction of the shale oil national demonstration area in Jiyang Depression， Shengli Oilfield.

Objectives: In the refrigeration industry, thin-walled copper tubes are crucial heat exchange devices, and during their drawing production process, the floating core head plays a significant role in the quality of the copper tubes. With the rapid development of chemical vapor deposition(CVD) diamond coating technology and its wide application in the field of molds, the DC arc plasma injection method is used to produce diamond-coated floating core heads to improve the quality of copper tube drawing and extend the service life of floating core heads. Methods: Using a deposition method and a rotating device design, the diamond coating was uniformly deposited on the surface of cemented carbide floating core heads by the DC arc plasma injection method. The surface roughness, morphology, mass uniformity, and film-base adhesion of the coating were tested and analyzed using a white light interferometer, scanning electron microscope, Raman spectrometer, and indentation method. The prepared diamond-coated floating core head was applied to a high-precision copper pipe production line, and the application effect was compared with that of a traditional cemented carbide floating core head. Results: SEM and Raman spectrum analysis showed that the diamond coating quality at each position of the floating core head was superior. The average thickness of the diamond in the cylindrical section of the floating core head was 13.3 μm, and in the fixed diameter section, it was 13.7 μm. At a room temperature of 20 ℃ and a relative humidity of 40%, with a filtering cutoff wavelength of 250 μm and a scanning area of 100 μm × 100 μm, the average surface roughness (Ra) of the polished diamond coating was 76.4 nm. Under the indentation test condition of loading to 1 000 N and holding constant force for 3 seconds at a fixed loading rate of 20.0 N/s, the average distance from the diamond coating shedding position to the indentation center was 287.9 μm. The prepared diamond-coated floating core head was then applied to the high-precision copper pipe production line. Compared with the cemented carbide floating core head, the following findings were observed: (1) Due to the excellent finish and self-lubrication characteristics of the diamond coating, the maintenance frequency of the floating core head decreased from once per frame to once every 20 frames, reducing labor intensity significantly. (2) Due to the excellent wear resistance of the diamond coating, the size of the fixed diameter section of the core head remained constant, ensuring that the wall thickness of the copper tube did not vary, therefore improving product consistency. (3) The service life of the diamond-coated floating core head was about 15 times that of the cemented carbide core head. Conclusions: The DC arc plasma injection method can uniformly deposit high quality diamond coating on the surface of cemented carbide floating core heads, reducing labor intensity effectively, ensuring consistency in copper tube production, and extending the service life of the core head in practical applications. Others: With the continuous progress of DC arc plasma jet deposition diamond coating technology, the quality of diamond-coated floating core heads will further improve. Diamond coatings can gradually be applied to various internal molds, such as fixed core heads and threaded cores. When used with diamond coated outer molds, these internal molds can replace traditional cemented carbide molds, reducing mold costs and labor costs, and improving the drawing quality of pipes significantly. This approach will help achieve the goal of reducing costs and increasing the efficiency in the copper, aluminum, stainless steel and other related industries.

To evaluate the degree of unsaturation of different varieties of Camellia oil, it was necessary to establish a rapid evaluation method with a narrow iodine value range (iodine value difference less than 10). In this study, a rapid quantitative prediction model for iodine value of oil in high-resolution Raman spectroscopy based on linear regression and gradient descent method was established. The Raman signals (785 nm) about 39 group of Camellia oil samples and 10 group of commercially oils were firstly collected. Then, the intensity ratio of peaks of 1656 cm−1 and 1440 cm−1 (I1656/1440) were selected through smoothing algorithm least squares smoothing filter (Savitzky-Golay), polynomial fitting and deconvolution algorithm Lorentzian. A credible model was obtained through correlation analysis with the iodine value of corresponding oil samples. The coefficient of determination (R2) of the test set of the constructed quantitative model was >0.82, the mean square error (MSE) was

Lithium–sulfur battery is cost-effective and has a theoretical specific energy density of up to 2600 W·h·kg−1; moreover, the earth is rich in sulfur resources; therefore, it is considered a promising candidate for next-generation high-energy-density batteries. However, a few obstacles still persist in the process of commercialization, including the insulation of charge and discharge products, huge volume changes, flammable electrolytes, polysulfide “Shuttle Effect”, and unstable lithium metal anode. Among these challenges, safety is a main concern in the process of commercialization. Batteries using sulfurized polyacrylonitrile (PAN/S) as positive electrode active material have substantial advantages in terms of lifespan and a wider selection of electrolytes. As lithium polysulfide dissolution has not been considered, phosphate-based electrolytes can be used in this system because they also have good nonflammable properties. Phosphate-based flame retardants or nonflammable solvents can capture combustion free radicals and have excellent flame retardant effects as main solvents and flame retardant additives. This study explores the application of high-concentration triethyl phosphate (TEP) and tri (2,2,2-trifluoroethyl) phosphate (TFP) electrolytes in Li-PAN/S batteries to improve battery safety for next-generation high-energy-density secondary batteries. We investigate the effect of TEP and TFP-based electrolytes on the stability of lithium metal negative and sulfur positive electrodes as well as interfacial reactions during battery cycling. Charge–discharge and Li deposition/stripping tests were conducted using a high-concentration electrolyte with a molar ratio of 1∶2 between LiFSI and TEP. The results reveal that the electrolyte can achieve a 99.6% S utilization at 0.1 Cand stable Li deposition/stripping performance. However, the high viscosity and limited ionic conductivity of electrolyte limit its battery performance under high-loading electrode and high-rate conditions. By conducting electrochemical tests on TEP and TFP-based electrolytes with different TTE dilution ratios, we found that the charge–discharge overpotential of TFP-based electrolytes was higher, making it difficult to stably cycle in Li/Cu half cells. Furthermore, TFP molecules formed an unstable interface layer on the Li metal surface, which deteriorates the cell performance. After diluting TEP-based electrolyte with TTE at a volume fraction of 1∶2, excellent rate performance was achieved, with stable cycling of over 200 cycles at a rate of 1C and ultimately maintaining a discharge specific capacity of 1038.1 mA·h·g−1. These results highlight the potential of high-concentration TEP as a promising candidate for safer and higher-performing Li–S batteries.

A method based on graph transformation and transfer learning is proposed to further enhance the accuracy of household-transformer relationships and phase identification in low-voltage distribution networks. Firstly， a graph transformation method based on Gramian angular field （GAF） is introduced to convert electricity consumption data into a two-dimensional representation， facilitating the identification of differences in one-dimensional time-series electricity consumption data. Next， to address challenges such as sparse user data in low-voltage distribution networks， limited data acquisition methods， and a scarcity of samples， a deep learning model suitable for household-transformer relationship and phase identification is constructed using transfer learning and leveraging pre-trained parameter weights. Experimental validation demonstrates that the proposed model outperforms mainstream methods in both household-transformer relationship and phase identification， exhibiting improved accuracy and stability.

Brassica oleracea is one of the important vegetable crops in China. Its seeds are primarily imported. Hence, developing innovative varieties belonging to China is an urgent requirement. Since broccoli is a cross-pollinated crop systematic selection and cross-breeding are challenging, and the application of radiation mutagenesis breeding in broccoli has not been reported. In this study, the seeds of Brassica oleracea were irradiated using carbon ion beams to investigate the biological effects of these beams on broccoli. The growth indices, antioxidant enzyme activity, photosynthetic indices, and chlorophyll fluorescence were detected at the seedling stage. The results revealed that irradiation with 100–500 Gy exhibited no significant effect on the germination of Brassica oleracea, while the germination of seeds was significantly inhibited at 600 Gy. After irradiation with 100–600 Gy, the root length, shoot length, seedling height, and leaf area decreased with the increase in irradiation dose. The Median lethal dose (LD50) of Brassica oleracea irradiated using a carbon ion beam was 415.89 Gy, and the dose that halved the root length was 495.12 Gy. After irradiation, the activities of superoxide dismutase (SOD) and peroxidase (POD) were higher than that of the control plants, while the activity of catalase (CAT) was lower than that of the control plants. The content of malondialdehyde (MDA) increased significantly at a dose of 400 Gy. The photosynthetic pigments (chlorophyll a, chlorophyll b, and carotenoids) showed an increasing trend initially, and then a decreasing trend with an increasing irradiation dose, and the highest value was detected at a dose of 300 Gy. Net photosynthesis, transpiration rate, and stomatal conductance exhibited a negative correlation with irradiation dose, while the non-photosynthetic quenching coefficient exhibited a significant increase after irradiation. The findings indicated that heavy ion beam radiation inhibited the growth of broccoli plants and affected the activity of antioxidant enzymes and photosynthesis. The study provided basic data for the radiation mutation breeding of Brassica oleracea.

In order to realize the real-time interaction between virtual space and real space, the digital twin system of nuclear reactor was built according to the actual nuclear reactor, with a large number of sensor devices and a large amount of data, resulting in problems of large storage space demand, low transmission efficiency and high complexity of data analysis. To solve the above problems, it is necessary to optimize the sensor arrangement and achieve efficient data storage, transmission and analysis. Few studies have been made to find feature parameters while obtaining their physical meaning and maintaining high efficiency simultaneously, which is the purpose of this paper. In this study, a parameter inversion model was built for the digital twin system of space thermionic reactors by combining clustering algorithm and artificial neural network based on random search optimization, so as to realize the inversion of core temperature data under heat pipe failure conditions. The main process of the model can be grouped into two parts, feature parameter extraction and parameter inversion. In the part of feature extraction, data were reduced from high dimension to low dimension, which constituted a data reduction. The temperature data were extracted from four areas of the space thermionic reactors core from the inside out, which were fuel, emitter, receiving pole and coolant, under 20% heat pipe failure condition. Temperature parameters can be regarded as numerical vectors with the same dimension as the number of time nodes, so the clustering method can divide these temperature parameters into different categories, and the parameter closest to the center of each category was taken as the parameter with typical change characteristics. Silhouette Score is usually used for evaluating the effect of clustering, which can be used to find the proper number of clusters. Therefore, K-means clustering algorithm and Silhouette Score were used as evaluation indicators to select the feature parameters of different regions of the core. In the second part, the feature parameters were inverted to other parameters by a fully connected artificial neural network, its hyper parameters optimized by random search configuration. The optimizing process was executed by setting a range for different hyper parameters like the number of hidden layers, the nodes of each layer and the learning rate, and then choosing a combination that had the smallest loss. Then the feature parameters were used as input and inverted to the rest as output. The inversion model was then verified with the temperature data of 15% heat pipe failure condition. The results show that by using the parameter inversion of fuel, emitter, receiving pole and coolant, the relative error of temperature inversion value is 0.55%, 0.41%, 0.19% and 0.18% respectively, and the feature parameters used for inversion are no more than 8% of the total parameters. Therefore, the parameter inversion model established in this study can obtain the physical meaning of the feature parameters and reverse the space reactor core temperature parameters with high accuracy, therefore resisting the influence of probe damage and data loss. The application of this method in the digital twin system of nuclear reactor can also provide an evaluation basis for the future installation of detectors in small nuclear reactors.

The oxidation of almonds during the storage and processing would seriously affect their nutrition and quality. The purpose of this study was to establish a sensitive and reliable method for rapid detection of the oxidation of almonds. A rapid and simple phase-transfer of gold nanoparticles (AuNPs) from aqueous solution to toluene was achieved via a strategy of surface ligand exchange. The results of UV-Vis and transmission electron microscopy showed that the morphology of AuNPs after phase-transfer changed no obvious. The AuNPs in toluene could be successfully used as an efficient SERS substrate for detecting the oxidation of almond oil. The characteristic Raman signal of the cis-double bond at 1655 cm−1 of almonds oil gradually decreased during oxidation. Raman signal at 1747 cm−1 of the ester bond was selected as the reference, and the relative intensity of I1655/I1747 showed a good linear relationship with the time of accelerated ageing of almonds (R2=0.98). By virtue of principal component analysis, the developed method was able to quickly and accurately distinguish the almonds with different oxidation levels. This study also provided a new strategy for the preparation and application of SERS substrates for fatty foods.

[Introduction] With the emphasis and promotion of the electricity market system construction by the government, the electricity market is constantly growing towards a deeper and more unified direction. In order to promote the electricity market construction, the influence factors of the electricity market risk and its evaluation remain to be studied further. [Method] Based on the consideration of the whole cycle of electricity market trading, this paper took pre-trade risk, during-trade risk, and post-trade riskas the entry points, integrated the existing risks in each stage of electricity market, and established the risk evaluation index system for electricity market. Based on the thought of subjective and objective weighting, analytic hierarchy process (AHP) and entropy weight method were used to assign weights to the index system respectively, and fuzzy comprehensive evaluation (FCE) was adopted to evaluate the comprehensive risk level of the electricity market. [Result] The rationality, comprehensiveness and validity of the proposed model are verified through the analysis of the calculation examples of different electricity markets. [Conclusion] The model eatablished in this paper can conduct a comprehensive risk evaluation for the electricity market, and provide a theoretical reference for the construction of the risk system of the electricity market and its future development direction.

The development of big data era makes the application of clustering algorithms more and more widespread, but most current clustering algorithms are sensitive to noisy data and cannot identify datasets with complex structures such as non-convex shapes. To address this problem, a clustering algorithm for constructing connected graph with reverse nearest neighbor is proposed. Firstly, a density calculation is designed to obtain the density of data points, and a dynamic noise discriminator is constructed to denoise the data so as to weaken the effect of noise on the clustering process. Secondly, considering that reverse neighbors better reflect the connection between data points and surrounding points, a clustering method is designed to construct reverse nearest neighbor connectivity graphs for the denoised data to identify data structure information within clusters, and to merge clusters using a given number of clusters. Finally, when classifying the noise points into clusters, considering that only classifying them into the closest clusters may lead to inaccurate classification results, a noise classification method is designed to take the density information into account to obtain the final clustering results. To verify the effectiveness of the proposed method, the clustering results of proposed algorithm are compared with those of five other clustering algorithms, and the external evaluation metrics Acc (cluster accuracy) and NMI (normalized mutual information) are used to evaluate the clustering results. Experimental results show that the clustering results of the proposed algorithm are better than those of comparison algorithms on the noisy datasets with complex structures such as non-convex shapes.

ObjectiveWheat, as one of the major global food crops, plays a key role in food production and food supply. Different influencing factors can lead to different types of wheat lodging, e.g., root lodging may be due to improper use of fertilizers. While stem lodging is mostly due to harsh environments, different types of wheat lodging can have different impacts on yield and quality. The aim of this study was to categorize the types of wheat lodging by unmanned aerial vehicle (UAV) image detection and to investigate the effect of UAV flight altitude on the classification performance.MethodsThree UAV flight altitudes (15, 45, and 91 m) were set to acquire images of wheat test fields. The main research methods contained three parts: an automatic segmentation algorithm, wheat classification model selection, and an improved classification model based on EfficientNetV2-C. In the first part, the automatic segmentation algorithm was used to segment the UAV to acquire the wheat test field at three different heights and made it into the training dataset needed for the classification model. The main steps were first to preprocess the original wheat test field images acquired by the UAV through scaling, skew correction, and other methods to save computation time and improve segmentation accuracy. Subsequently, the pre-processed image information was analyzed, and the green part of the image was extracted using the super green algorithm, which was binarized and combined with the edge contour extraction algorithm to remove the redundant part of the image to extract the region of interest, so that the image was segmented for the first time. Finally, the idea of accumulating pixels to find sudden value added was used to find the segmentation coordinates of two different sizes of wheat test field in the image, and the region of interest of the wheat test field was segmented into a long rectangle and a short rectangle test field twice, so as to obtain the structural parameters of different sizes of wheat test field and then to generate the dataset of different heights. In the second part, four machine learning classification models of support vector machine (SVM), K nearest neighbor (KNN), decision tree (DT), and naive bayes (NB), and two deep learning classification models (ResNet101 and EfficientNetV2) were selected. Under the unimproved condition, six classification models were utilized to classify the images collected from three UAVs at different flight altitudes, respectively, and the optimal classification model was selected for improvement. In the third part, an improved model, EfficientNetV2-C, with EfficientNetV2 as the base model, was proposed to classify and recognized the lodging type of wheat in test field images. The main improvement points were attention mechanism improvement and loss function improvement. The attention mechanism was to replace the original model squeeze and excitation (SE) with coordinate attention (CA), which was able to embed the position information into the channel attention, aggregate the features along the width and height directions, respectively, during feature extraction, and capture the long-distance correlation in the width direction while retaining the long-distance correlation in the length direction, accurate location information, enhancing the feature extraction capability of the network in space. The loss function was replaced by class-balanced focal loss (CB-Focal Loss), which could assign different loss weights according to the number of valid samples in each class when targeting unbalanced datasets, effectively solving the impact of data imbalance on the classification accuracy of the model.Results and DiscussionsFour machine learning classification results: SVM average classification accuracy was 81.95%, DT average classification accuracy was 79.56%, KNN average classification accuracy was 59.32%, and NB average classification accuracy was 59.48%. The average classification accuracy of the two deep learning models, ResNet101 and EfficientNetV2, was 78.04%, and the average classification accuracy of ResNet101 was 81.61%. Comparing the above six classification models, the EfficientNetV2 classification model performed optimally at all heights. And the improved EfficientNetV2-C had an average accuracy of 90.59%, which was 8.98% higher compared to the average accuracy of EfficientNetV2. The SVM classification accuracies of UAVs at three flight altitudes of 15, 45, and 91 m were 81.33%, 83.57%, and 81.00%, respectively, in which the accuracy was the highest when the altitude was 45 m, and the classification results of the SVM model values were similar to each other, which indicated that the imbalance of the input data categories would not affect the model's classification effect, and the SVM classification model was able to solve the problem of high dimensionality of the data efficiently and had a good performance for small and medium-sized data sets. The SVM classification model could effectively solve the problem of the high dimensionality of data and had a better classification effect on small and medium-sized datasets. For the deep learning classification model, however, as the flight altitude increases from 15 to 91 m, the classification performance of the deep learning model decreased due to the loss of image feature information. Among them, the classification accuracy of ResNet101 decreased from 81.57% to 78.04%, the classification accuracy of EfficientNetV2 decreased from 84.40% to 81.61%, and the classification accuracy of EfficientNetV2-C decreased from 97.65% to 90.59%. The classification accuracy of EfficientNetV2-C at each of the three altitudes. The difference between the values of precision, recall, and F1-Score results of classification was small, which indicated that the improved model in this study could effectively solve the problems of unbalanced model classification results and poor classification effect caused by data imbalance.ConclusionsThe improved EfficientNetV2-C achieved high accuracy in wheat lodging type detection, which provides a new solution for wheat lodging early warning and crop management and is of great significance for improving wheat production efficiency and sustainable agricultural development.

This experiment mainly studied the effect of shiitake stipe powder on the quality and nutritional composition of eggs from Hy-Line brown hens. 112 healthy 40-week-old Hy-Line brown hens in the same batch were selected and were randomly divided into 4 groups. The control group was fed the basic diet and the experimental groups were supplemented with 5%, 10% and 15% of mushroom stalk powder, respectively. After 20 weeks of feeding, the egg quality was measured. The results showed that the average egg weight and size of the experimental groups were significantly higher than those of the control group (P

【Objective】 The purpose of this paper is to investigate the evolution of water resource vulnerability in the southern wet mountain regions in China. 【Method】 We took Xiangxi Tujiazu & Miaozu Autonomous Prefecture as an example, and developed a VSD model to calculate their water resource vulnerability evaluation index by considering exposure, sensitivity and adaptation. It included three hierarchies and 15 indicators. The evaluation model was developed based on the projection pursuit-cloud model. 【Result】 The trend of water resources vulnerability in Xiangxi Autonomous Prefecture can be divided into four categories including good category, category in continuous improvement, continuously worsening category, and category in fluctuation. The good category includes water consumptions by agriculture, industry, domestic use and water quality compliance rate; the continuous improvement category includes eco-environmental water demand, forest coverage rate, water storage of large and medium-sized reservoirs, sewage recovery rate, and length of embankments; continuously worsening category includes tourism revenue, effective irrigation area; the fluctuation category includes water yield coefficient, water resources per capita, annual rainfall, and groundwater water exploitation. The comprehensive evaluation changed from moderate vulnerability to weak vulnerability since the work for aquatic ecological civilization, the system for the river-leader and model river have been carried out. 【Conclusion】 The enhancement of the water resources system in Xiangxi Prefecture is related to its eco-civilization of water, river chief system, but it should also develop ecological tourism and water infrastructure construction. The method we developed in this paper can be used to evaluate and analyze water resource vulnerability in the other wet mountainous regions.

A plasma torch with split anode and rotating arc was developed. The diamond was coated on the inner wall of large diameter annular workpiece by the torch. The umbrella-like arc formed by the movable anode makes the axial working gas blow vertically to the inner wall of the annular workpiece. The parameters of arc under different anode diameters were tested, and the arc shap was taken by camera. High quality diamond coatings were successfully deposited on the inner surface of cemented carbide drawing die with inner diameter of 180 mm and graphite with inner diameter of 100 mm. The composition and surface morphologies of the coating were analyzed by Raman spectroscopy and scanning electron microscopy. The diamond coating cemented carbide die has been successfully applied in the drawing equipment of aluminum sheath of extra-high voltage cable.

The static headspace(HS) combined with gas chromatography-mass spectrometry(GC-MS) was used to analyze the volatile flavor compounds of Zanthoxylum bungeanum from 45 producing areas in Shanxi, Shandong, Sichuan and Gansu. Using automatic mass spectrometry deconvolution qualitative system(AMDIS) and Kováts Retention index(RI) analysis, a total of 99 volatile compounds were obtained. 79, 69, 68 and 63 volatile compounds were identified in Zanthoxylum bungeanum from Shanxi, Gansu, Shandong and Sichuan province. A variety of mathematical models were established to identify the origin. Among them, the Orthogonal partial least squares(OPLS-DA) model could accurately distinguish Zanthoxylum bungeanum samples from 4 provinces, the model fitting parameter Q2 was 0.84, and the 6 key difference substances(VIP>2) were piperonone, pinene, terpinene, 3-carene, ocirene and α-phellandrene. Further application of GC-MS full-spectrum data combined with Random Forest(RF) model for origin identification could successfully distinguish Zanthoxylum bungeanum from Shanxi, Gansu, Shandong and Sichuan provinces, with an accuracy rate of 100%.

Aiming at the real-time detection and classification of the growth period of crops in the current digital cultivation and regulation technology of facility agriculture, an improved YOLOv4 method for identifying the growth period of strawberries in a greenhouse environment was proposed. The attention mechanism into the Cross Stage Partial Residual (CSPRes) module of the YOLOv4 backbone network was introduced, and the target feature information of different growth periods of strawberries while reducing the interference of complex backgrounds was integrated, the detection accuracy while ensured real-time detection efficiency was improved. Took the smart facility strawberry in Yunnan province as the test object, the results showed that the detection accuracy (AP) of the YOLOv4-CBAM model during flowering, fruit expansion, green and mature period were 92.38%, 82.45%, 68.01% and 92.31%, respectively, the mean average precision (mAP) was 83.78%, the mean inetersection over union (mIoU) was 77.88%, and the detection time for a single image was 26.13 ms. Compared with the YOLOv4-SC model, mAP and mIoU were increased by 1.62% and 2.73%, respectively. Compared with the YOLOv4-SE model, mAP and mIOU increased by 4.81% and 3.46%, respectively. Compared with the YOLOv4 model, mAP and mIOU increased by 8.69% and 5.53%, respectively. As the attention mechanism was added to the improved YOLOv4 model, the amount of parameters increased, but the detection time of improved YOLOv4 models only slightly increased. At the same time, the number of fruit expansion period recognized by YOLOv4 was less than that of YOLOv4-CBAM, YOLOv4-SC and YOLOv4-SE, because the color characteristics of fruit expansion period were similar to those of leaf background, which made YOLOv4 recognition susceptible to leaf background interference, and added attention mechanism could reduce background information interference. YOLOv4-CBAM had higher confidence and number of identifications in identifying strawberry growth stages than YOLOv4-SC, YOLOv4-SE and YOLOv4 models, indicated that YOLOv4-CBAM model can extract more comprehensive and rich features and focus more on identifying targets, thereby improved detection accuracy. YOLOv4-CBAM model can meet the demand for real-time detection of strawberry growth period status.

Irrigation is an important factor that affects crop yield. In order to control irrigation of facility crops more effectively and accurately, this study took "Zhangji" strawberry as an example, introduced crop real-time growth characteristics into irrigation decision-making, and combined Penman-Monteith (P-M) model and knowledge reasoning to study the irrigation of strawberry. In the first step, the influencing factors and expert experience in identifying strawberry growth period of "Zhangji" strawberry irrigation were standardized, and the strawberry irrigation data structure based on Resource Description Framework (RDF) was established. The second step was to collect expert experience of strawberry irrigation according to the standardized knowledge structure model. Firstly, all data were unified into structured data, and then were stored in *.csv format together with expert experience, and strawberry irrigation knowledge map based on Neo4j was constructed. The third step was to collect the environmental data and plant data of strawberry in each growth period. The fourth step was using P-M model to calculate the initial irrigation value of strawberry, and then adjusted the initial irrigation value by knowledge reasoning.The fifth step was to conduct experimental planting and evaluate the sampled fruits. In knowledge reasoning, irrigation adjustment strategies of each expert was different. In strawberry irrigation experiment based on P-M model and path sorting algorithm, a group of irrigation reasoning values with the highest probability value were selected to adjust irrigation with the goal of maximizing strawberry yield. The experimental results showed that under the condition of harvesting at a specified time, The total fruit yield, average fruit yield per plant and average fruit weight percentage increased by 2478.5 g, 20.65 g and 12.15% (average fruit weight increased by 1.65 g per fruit) based on P-M model and path sorting algorithm compared with traditional P-M model, respectively. First, on the basis of P-M model, the yield-first irrigation adjustment strategy was adopted. Based on knowledge reasoning, the irrigation frequency and amount were adjusted timely according to the crop growth situation, which improved the yield. Second, under the condition of harvesting and recording yield at a specified time, the experiment accurately controlled the growth period to ensure early fruit ripening, while the other three groups of fruits were not fully mature and the yield of immature fruits were not calculated. Under the method of strawberry irrigation based on Penman-Monteith model and path sorting algorithm, the fruit was picked within a fixed time and reached 0.39 kg/cm2, which increased by 0.1 kg/cm2. Because the planting goal of this study was yield first, only the influence of irrigation on yield was considered. The experimental resulted show that the irrigation method based on model and knowledge reasoning could improve the yield of strawberry, and can provide a new idea for precise irrigation.

The metallic molybdenum disulfide exhibits large interlayer spacing, high electrical conductivity and abundant active sites, which shows wildly application prospects in the field of energy storage and conversion. The recent progress of metallic molybdenum disulfide in energy storage and conversion was reviewed. Firstly, the crystal and electronic structure of the metallic molybdenum disulfide were introduced, and the synthesis methods such as top-down (lithium intercalation stripping) and bottom-up (solvent/hydrothermal) were included. Then, the progress of metallic molybdenum disulfide and its composites in the fields such as hydrogen evolution reaction, lithium (sodium) ion batteries and supercapacitors were summarized. Finally, it is pointed out that the current challenges of metallic molybdenum disulfide are uncontrollable synthesis process and poor structural stability. The in-depth study on the structure and properties of metallic molybdenum disulfide is expected to fundamentally improve its performance and practical application in the field of energy storage and conversion.

Objective To explore the impact of venous thromboembolism (VTE) on the diagnosis and treatment of lung cancer patients. Methods We retrospectively analyzed the clinical data of lung cancer patients with VTE treated in Peking University Cancer Hospital. The incidence of VTE was calculated and the relation between VTE and lung cancer was analyzed. Results Among 1766 patients with lung cancer, VTE occurred in 115(6.5%) patients. Among 115 VTE cases, there were 78(67.8%) males patients; 82(71.3%) cases were deep venous thrombosis, 21(18.3%) cases were pulmonary embolism, 12(10.4%) cases were deep venous thrombosis with pulmonary embolism; 74(64.3%) cases were symptomatic VTE; 102(88.7%) patients received antithrombotic therapy. Among the patients who received antithrombotic therapy, 97(95.1%) cases chose drug therapy. In drug treatment, 65(67.0%) cases used adequate/standard dose. Among 115 VTE cases, 52(45.2%) patients had improvement or disappearance of thrombus, 32(27.8%) patients had no improvement, and 31(27.0%) patients with unknown results; 11(9.6%) patients had adverse reactions such as bleeding during antithrombotic therapy; 30(26.1%) patients changed antineoplastic treatment plan due to VTE. Conclusion VTE is a common complication of lung cancer patients. Antithrombotic therapy for lung cancer patients with VTE is complex, the treatment effect is not ideal and the risk of adverse reactions such as bleeding is high. VTE has a great impact on the implementation of anti-cancer treatment.

Lithium-air batteries(LABs) are among the most promising electrochemical energy storage technologies in the future due to extremely high theoretical energy density. The performance of LABs is mainly governed by the electrochemical reactions that occur on the surface of the cathode. Therefore, the rational design of a cathode with high stability and reversibility is the key to commercially viable LABs. However, the side reactions are caused by the instability of traditional carbon-based electrodes can limit capacity and cycle performance of LABs, therefore, alternative carbon-based electrode materials are required. Based on the structure and the principle of cathode reaction of LABs, the current challenges of LABs were presented. Then based on the analysis of the instability of carbon-based cathode, the design of a stable and reversible cathode for LABs was summarized. Finally, a perspective that the rational design of the cathode catalyst and the in-depth understanding of the catalytic mechanism play a decisive role in the performance improvement of LABS was provided.

Objective To explore the predictive value of neutrophil-to-lymphocyte ratio(NLR) and platelet-to-lymphocyte ratio (PLR) in the prognosis and curative effect of locally advanced nasopharyngeal carcinoma(NPC) patients. Methods We collected the clinical information of locally advanced NPC patients from a randomized prospective clinical trial in Guizhou cancer hospital from July 2015 to December 2016. The patients were treated with two cycles of TPF induction chemotherapy and cisplatin-based concurrent chemoradiotherapy. The relationship between NLR, PLR before treatment and the therapeutic effect of patients was analyzed. We compared the curative effect between chrono-chemotherapy group and routine group. Results The mean values of NLR and PLR in stage Ⅳa/b patients were higher than those in stage Ⅲ patients (P=0.010); the immediate effect of metastatic lymph nodes in low PLR group was better than that in high PLR group (P=0.029), and the curative effect of primary lesion and overall curative effect three months after radiotherapy were better in low PLR group (P=0.012, P=0.027); there was no significant difference in immediate effect or overall curative effect three months after radiotherapy between conventional group and chronological group (P > 0.05). Conclusion NLR and PLR are related to the clinical staging of nasopharyngeal carcinoma. The later tumor stage is, the higher NLR and PLR values are. The predictive value of NLR for the patients' short-term efficacy is not well. PLR may be a predictor for recent outcomes of patients with locally advanced nasopharyngeal carcinoma, and high PLR may predict poor short-term efficacy.

The application background of Co-Ni-Al composite binder phase in cemented carbide was introduced. The latest research results of Co-based superalloy and the properties of cemented carbide with binder strengthened by ordered phase were briefly described. The application of integrated computational material engineering in the research and development of Co-Ni-Al composite binder was introduced. The progress in the preparation, microstructure characterization and performance of WC-Co-Ni-Al cemented carbides were summarized. The results show that the composition of Co-Ni-Al composite binder has obvious influence on the solid-liquid interface energy and the liquid-phase nucleation driving force of the alloy. Accordingly, the grain size of the binder phase and the grain morphology of WC are affected. Ultimately these factors affect the performance of the alloy. It is pointed out that the performance of cemented carbide strengthened by ordered γ′ phase precipitation can be improved significantly. It is expected to obtain high-performance cemented carbide materials with excellent high-temperature resistance, corrosion resistance and oxidation resistance. It is proposed that the interfacial microstructure, the relationship between C content and precipitation phase and the anti-wear mechanism of cemented carbide with Co-Ni-Al composite binder phase should be emphasized in future.

Objective To investigate the effect of miRNA-101 (miR-101) on the invasion and Wnt/β-catenin pathway activation in colon cancer cells through targeting CDK8. Methods qRT-PCR and Western blot were used to detect the expression of miR-101 and CDK8 in colon cancer tissues, adjacent normal tissues and five colon cancer cell lines. Dual luciferase reporter assay was used to determine whether miR-101 could directly bind to the 3'UTR region of CDK8. CDK8 expression was regulated through miR-101 mimic and/or pBabe-CDK8 transfection, and its effects on tumor cell invasion and Wnt/β-catenin activation were detected. Results Compared with adjacent normal tissues, the expression level of miR-101 in colon cancer tissues was significantly decreased, while the expression of CDK8 increased significantly. Dual luciferase reporter assay confirmed that miR-101 could bind directly to the 3'UTR region of CDK8 and regulate its expression. The invasion ability of colon cancer cells transfected with miR-101 mimic was significantly lower than those in negative control group and CDK8 overexpression group. The transfection of miR-101 mimic resulted in a significant decrease of TOP/FOP luciferase activity and β-catenin protein expression. However, CDK8 overexpression vector transfection could significantly inhibit the effect of miR-101 mimic. Conclusion miRNA-101 could regulate colon cancer cell invasion and Wnt/β-catenin pathway activation through targeting CDK8.

In order to solve problems of poor reliability and lacking of visual and effective early-warning signal of traditional fault protection system of belt conveyor in coal mine, the paper proposed a design scheme of underground early-warning system of belt conveyor. The system adopts technologies of explosion-proof and intrinsic safety PLC and industrial field bus and realizes functions of linkage control of multi belt conveyors, fault monitoring and early-warning in forms of words and sound. The application result showed that the system is stable in running and strong in reliability, which improves efficiency of fault early-warning and treatment of belt conveyor.

The paper analyzed problems of voltage level, heat dissipation, EMC and conversion efficiency of inverter existed in using process of explosion-proof frequency converter in coal mine underground, and introduced methods of solving these problems in details, namely using technologies of flameproof and intrinsic safety and heat dissipation with heat pipes to solve problems of explosion-proof and heat dissipation of frequency converter, which can make explosion-proof frequency converter has characteristics of high performance, strong functions and low noise; using technical means of changing circuit topology and improving control strategy of frequency converter to solve problems of EMC and energy consumption of frequency converter, which can make explosion-proof frequency converter meet with requirements of modernization of coal mine production.

In view of problems of inconvenient observations, bigger error and poor data real-time performance existed in monitoring for coal mine roadway roof separation with mechanical device, the paper designed a structure health monitoring system for coal mine roadway roof separation. The system uses optical fiber displacement sensor to measure displacement condition of roadway roof separation automatically, adopts computer control program to monitor strain and displacement of coal mine roadway roof separation, and evaluates security of structure, thus safeguards the health of the structure. The practical application shows that the system has advantages such as real-time observation, small error and high efficiency.

Objective: To evaluate the effects of laser in situ keratomileusis (LASIK) and laser-assisted subepithelial keratomileusis (LASEK) on wavefront aberration for treatment of myopia., Methods: Eighteen right eyes with LASIK and 18 right eyes with LASEK were included in this study. The patients were selected randomly for evaluation of the wavefront aberration using a WFA1000 subjective aberrometer before and 10 days, 1 and 3 months after treatment. The coefficient of 35 terms of zenike was obtained by aberrometer, and root mean square (RMS) of each and total high order aberration was calculated by Matlab5.3. SPSS10.0 was used for statistical analysis., Results: Uncorrected visual acuity in all eyes after operation achieved or exceeded preoperative best corrected visual acuity; no serious complication occurred to threaten visual acuity. RMS of each and total high order aberration was increased at 10 days after LASIK, and then decreased at 1 and 3 months, during which period the changes after LASEK were the same as those after LASIK, only smaller than that of the preoperative data except order 3. Statistical difference of order 3, 4 and total high order before and 10 days after LASIK was significant, while that 1 and 3 months was insignificant. There was statistically significant difference of each and total high order before and after LASEK, whereas, the results of LASEK showed no significant difference when compared with that of LASIK., Conclusions: RMS of wavefront aberration increased rapidly at 10 days after LASIK and LASEK and decreased gradually at 1 and 3 months. There was no statistically significant difference in RMS at 1 and 3 months after treatment. The degree of crease after LASEK is smaller than that after LASIK.

Objective: To study the influence of cornea flap and residual cornea bed on cornea intensity after laser in situ keratomileusis (LASIK)., Methods: The established mature cats animal model of LASIK was used. In Group A, a 160 micro m cornea flap was made, followed by performing ablation on the stroma by excimer laser to preserve the residual bed for 300 micro m, and then the cornea flap was repositioned. The cornea flap was removed with the residual bed 300 micro m remaining in Group B, while in Group C, a 160 micro m cornea flap was made with the residual bed 180 micro m, and followed reposition of the cornea flap. In Group D, the cornea flap was cut off and a 180 micro m the residual bed was remained. Measurements included central cornea pachymetry, anterior chamber depth (ACD) and analysis of the posterior best fit sphere in cornea Topography before operation and 1 week, 1 month, 2 months and 3 months after operation. The results were analyzed statistically. 3 months after operation, the changes of cornea structures were observed by histopathological analysis and transmission electron microscope., Results: Increase of ACD 3 months after operation: Group A, (0.16 +/- 0.08) mm; group B, (0.21 +/- 0.16) mm; group C, (0.33 +/- 0.09) mm; group D, (0.41 +/- 0.10) mm. There was no statistical difference between group A and group B (t = 0.685, P > 0.05) and between group C and group D (t = 1.457, P > 0.05). There was a statistical difference between group A and group C (t = 3.458, P < 0.05) and between group B and group D (t = 2.597, P < 0.05). Increase of posterior cornea prominence 3 months after operation: Group A, (27.78 +/- 9.52) micro m; group B, (39.57 +/- 7.68) micro m; group C, (58.57 +/- 8.66) micro m; group D, (68.14 +/- 19.69) micro m. No statistical difference was found between group A and group B (t = 2.361, P > 0.05) and group C and group D (t = 1.090, P > 0.05). There was a statistical difference between group A and group C (t = 5.860, P < 0.05) and between group B and group D (t = 3.310, P < 0.05). Light microscopy and transmission electronic microscopy showed that the arrangements of collagen fiber in the interface were disordered with no apparent cross arrangement. There was no significant increase of rough endoplasmic reticulum in fibroblast., Conclusions: The residual cornea bed is the main factor to influence corneal intensity. After LASIK, the wound healing of the interface is different from scar. This may be the main reason for cornea flap's no apparent influence on cornea intensity.