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According to the boundary information of the coal wall and roof in the 3D laser scanning model of fully mechanized working face, the shearer can automatically adjust the cutting height of the drum to realize the coal precise mining. The existing technology realizes the automatic extraction of the roof line of coal cutting based on the laser point cloud of the working face. But the extraction results cannot be directly applied to the digital automatic coal cutting. In order to solve this problem, the overall scheme of 3D laser scanning modeling for fully mechanized working face is proposed. The key technologies such as boundary extraction of coal wall and roof, target ball detection, point cloud registration and coordinate transformation are studied. The near real-time acquisition of boundary information of coal wall and roof under 3D geological coordinate system is realized. The information can be directly sent to the shearer drum to provide data reference for the next cutting of the shearer. The scanning of the working surface is realized through an inspection robot to obtain the inspection point cloud. Based on the curvature characteristics of the boundary of the coal wall and roof, the string and normal vector method is used to extract the boundary of the coal wall and roof roughly. The angle information between the normal vector of data points and the normal vector of adjacent points is introduced. The obvious intersection points of non coal wall and roof are eliminated through the threshold. As the inspection point cloud and the extracted boundary information are both located in a local coordinate system, the head and tail point clouds and the inspection point cloud are registered through the detection and registration of the positioning target ball. The working face combined point cloud is obtained. According to the 3D geological coordinate and the local coordinate of the positioning target ball, the transformation relation between the coordinates is obtained. The combined point cloud is transformed into the 3D geological coordinate system through coordinate transformation. Therefore, the boundary information of the coal wall and the roof under the 3D geological coordinate system is obtained. The underground industrial test results show that the error of the boundary between the coal wall and roof extracted by 3D laser scanning technology in fully mechanized working face is less than 10 cm. The sampling points with error less than 4 cm account for 50%. The sampling points with error less than 8 cm account for 96.67%.

For the current stateful network protocol fuzzing technology, the auxiliary type message repeated interaction affects the test efficiency and ensures the validity of the test case by inputting the corresponding test case according to the state of the protocol entity, so that the message abnormality input sequence test cannot be performed. In this paper, a stateful network protocol fuzzing method is designed based on Q-learning algorithm. The auxiliary message of the boot state is not required, and the message abnormality input sequence test can be performed under the premise of ensuring the validity of the test case. Experimental results show that this fuzzing method can significantly improve test efficiency and vulnerability mining capabilities.

Correct non-standard protocol format recognition is the foundation of protocol security analysis, which is an important part of industrial control system(ICS) information security content. Due to current situation of ICS and protocol features of structure determination, transmission repeat and semantic limited, a method based on net-trace is proposed. The formats of protocol are gotten by single message processing for a preliminary clustering, packet processing for sequence alignment, key fields to infer semantics. Verification results show that the method can reverse recognition non-standard ICS protocol format.

Using bisphenol A paraformaldehyde phenolic resin (BPA-PA phenolic resin) and epcchiorohydrin as raw materials, BPA-PA phenolic epoxy resin is obtained through nucleophilic substitution reaction. FTIR and ¹HNMR are used to confirm the structure. The optimal synthesis process conditions of BPA-PA novo! epoxy resin are obtained through single factor and orthogonal experiments: the amount of epichiorohydrin of 80 g, the amount of catalyst of 0.5 g, the reaction temperature of 80 °C and the reaction lime of 3 h. When the amount of 10 wt% NaOH is 15 g, the epoxy value reaches 0.565. Then combined nonisothermal DSC, T-β extrapolation line and FTIR analysis, the best curing process conditions are studied. Finality, the BPA-PA phenolic epoxy resin is used as the matrix resin, and conductive fillers and additives are added to prepare a medium-temperature conducive adhesive. Tensile shear strength, volume resistivity, thermogravimetry and scanning electron m- croscopy test are conducted for its conductive adhesive. The results show that the self-made BPA-PA phenolic epoxy resin conductive adhesive has a tensile shear strength of 17.04 MPa, a volume resistivity of 8.65 x 10-4 Ω • cm, and a residual carbon content of 65.28%. Compared with the commercially available conductive adhesive made of E-51 epoxy resin, the self-made BPA-PA phenolic epoxy resin conductive adhesive has increased tensile shear strength by 2.59 MPa, reduced volume resistivity by 2.65 x 10-4 Ω • cm, and increased carbon residue by 3.88%. [ABSTRACT FROM AUTHOR]

In order to improve the effective utilization of features in remote sensing image scene classification and achieve the purpose of improving the accuracy of remote sensing image classification, a remote sensing image classification method based on dual-channel depth-dense feature fusion was used for theoretical analysis and experimental verification. First, the image convolution layer features and fully connected layer features was separated extracted by constructing a composite dense convolutional network model. In order to exploit the deep information of the image, the deep convolutional layer features extracted by the model were recombined and encoded by the bag of visual words to capture the deep local features of the image. Finally the linear and weighted methods were used to fuse local and global features and then classify them. The results show that using the datasets UC Merced Land-Use and NWPU-RESISC45 for experiments, the classification accuracy obtained is 93.81% and 92.62%, respectively. This method makes full use of the complementarity of local features and global features to achieve the full expression of deep image information. [ABSTRACT FROM AUTHOR]

Unsteady shock/boundary layer interaction generated by 2-D compression corner under movement conditions is studied by numerical calculating the unsteady Reynolds averaged N-S equations, and the unsteady characteristics of separation zone during the process of pitching up, pitching down and periodically oscillating are analyzed. The numerical results show that when the model pitches up, the size of separation region becomes smaller, and when the model pitches down, the size of separation region becomes larger. The positions of separation points, reattachment points and shock oscillate periodically as the oscillation of the compression corner and the frequency of the oscillation agrees with each other. When the amplitude of model increases, the change of separation region becomes wider. When the frequency of model increases, the position of the maximal and minimal separation region is distinctly changed during the oscillation of compression corner. Furthermore, the results are compared to those calculated at static conditions, and conclusion is achieved that the variation of separation region is dominated by both of the pitching angle and the unsteady movement effects. Changing of pitching angel leads to the change of free stream Mach number, which have influence on the separation flow. [ABSTRACT FROM AUTHOR]

Isovaleric acidemia is a type of organic acidemia for which the earliest definite diagnosis was attained. It features an autosomal recessive inheritance, with the onset of age varying from newborn to adulthood. The clinical manifestations are complex and variable, which include feeding difficulty, vomiting, lethargy, coma, metabolic acidosis, sweaty feet odor and mental retardation. The mortality and mobility rates of isovaleric acidemia are quite high, and early diagnosis and rational treatment can significantly improve the prognosis. This article has provided a summary for the current understanding and research progress on isovaleric acidemia.

Objective: To investigate the incidence,clinical,biochemical and genetic characteristics of isovaleric acidemia (IVA) in Zhejiang province., Methods: Between January 2009 and December 2019, a total of 3 510 004 newborns were screened for IVA using tandem mass spectrometry. Patients of IVA were confirmed by urine organic acid and IVD gene detection. IVA patients were given diet and life management, supplemented with L-carnitine and glycine treatment, long-term followed up to observe and evaluate the growth and intellectual development., Results: A total of 15 patients with IVA were diagnosed, with an incidence of 1/234 000. Three patients had acute neonatal IVA, and the rest were asymptomatic. The isovalerylcarnitine (C5) levels were increased in all patients. Twelve children underwent urinary organic acid analysis, of which 11 cases had elevated isovalerylglycine levels, 4 cases with 3-hydroxyisovalerate increased simultaneously. Eleven IVA patients underwent genetic testing, 9 patients were compound heterozygous variants in IVD gene, one with homozygous variants in IVD gene, and one harbored one IVD variant. Nineteen IVD variants (14 missense mutations, 3 intron mutations, 1 code shift mutation, and 1 synonymous mutation) were identified, 11 of which were not reported. Among the 15 IVA patients, one patient died and two patients were followed up locally. The remaining patients had no obvious clinical symptoms during the follow-up (2-79 months). Three patients presented with growth and development delay, the remaining had normal physical and mental development., Conclusions: The clinical manifestations of IVA are non-specific, and the gene spectrum is scattered. Newborn patients screened by tandem mass spectrometry can receive early diagnosis and treatment, so as to correct metabolic defects and pathophysiological changes.