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This study focuses on the research of spray-pump type unmanned surface vehicles (USVs). Based on the analysis of the dynamics and motion characteristics of USVs, a method combining Dubins curves and the particle swarm optimization algorithm is proposed to find the optimal or suboptimal solution for the formation path. The research goal is to switch multiple USVs from an unordered state to a formation state, taking the speed of USVs and the formation endpoint as dynamic variables and integrating Dubins curve theory into the particle swarm optimization algorithm. A theoretical framework for the formation of spray-pump type USVs is proposed. Finally, the formation of three USVs is realized in a simulation platform.

Distribution of landslide is controlled by various causative factors that have different impacts on the occurrence of landslide in different regions. Using one single model to build the hazard assessment is not enough to fully reflect the spatial differences of landslide controlling factors especially for large area. Landslide hazard assessment based on zonation was therefore proposed in this study with an attempt to take effective measures to address this problem. The China–Pakistan Economic Corridor was taken as the study area where landslide hazard assessment was carried out. Based on the features of geological structure, topography, and climate, the study area was divided into three zones. The controlling factors were further analyzed by the geographical detectors method. It was found that the main controlling factors for landslides in these three zones were related to the site’s topography (altitude, slope gradient, and relief amplitude), land use, and distance to an earthquake epicenter. Furthermore, different factors for landslide hazard assessment were selected based on the result of a controlling factor analysis. An artificial neural network model was employed to build the hazard assessment models, and hazard assessment maps were generated. Validations were conducted, showing that the accuracy of hazard assessment maps by zones was higher than that by the whole study area, despite there was no significant difference during the modeling process.

To monitor the health of rolling bearing, the vibration signals are always used for fault diagnosis. However, the non-linear and non-stationary characteristics of vibration signals have not been solved in current methods. In this work, an intelligent fault diagnosis method is proposed, which is a sequential combinations of variational mode decomposition（VMD）, Kurtogram, and artificial fish algorithm（AFSA）. To begin, original vibration signals are decomposed into intrinsic mode functions（IMFs） using VMD, among which the most effective fault information is selected based on the Kurtogram algorithm and the rules of maximum correlation coefficients. Then the feature vectors are identified using the morphological entropy and energy entropy of the above IMFs. Next, two crucial tunable parameters, penalty coefficient C and Gaussian kernel width coefficient σ are optimized through AFSA algorithm. At last, the fault diagnosis model is developed based on AFSA-SVM algorithm, in which the extracted fault features are employed as inputs. The experimental results show that the proposed method accurately identifies fault features of the original signal. It has also improved model learning efficiency and classification accuracy.

Highly pathogenic avian influenza (HPAI) viruses pose a threat to wild birds and poultry globally, and HPAI H5N1 viruses are of even greater concern because of their frequent spillover into [...]

Objective To explore the influence of CD151 inhibition by RNA interference on invasion and metastasis of Xuanwei lung adenocarcinoma XWLC-05 cells, as well as lung metastasis in nude mice given tail veins injection of XWLC-05 cells. Methods Recombinant plasmid aimed to interfere CD151 gene was constructed and transfected into XWLC-05 cells. MTT, wound-healing assay and Transwell assay were applied to detect cell proliferation and migration abilities. Stably-expressed XWLC-05-shRNA, XWLC-05-shNC and XWLC-05-Blank cell lines were injected into the tail veins of BALB/c nude mice. Lung metastasis was measured by naked eye and microscope after HE staining. Results Inhibition of CD151 gene expression could reduce the migration and invasion abilities of XWLC-05 cells in vitro(P < 0.05). The proportion and number of lung metastasis were 75%(6/8) and (5.2±1.2), 100%(8/8) and (9.8±1.6), 75%(7/8) and (9.1±1.2) in XWLC-05-shRNA, XWLC-05-shNC and XWLC-05-Blank groups, respectively. There was no differences in XWLC-05-shNC vs. XWLC-05-Blank group(P=0.423). There were significant differences in XWLC-05-shRNA vs. XWLC-05-shNC group(P=0.000) and XWLC-05-shRNA vs. XWLC-05-Blank group(P=0.000). Conclusion Inhibition of CD151 gene expression could reduce lung metastasis in nude mice given tail veins injection of XWLC-05 cells. CD151 may become one of the potential therapeutic targets for inhibiting the invasion and metastasis of Xuanwei lung adenocarcinoma.

The boundary mesh of the casting model was determined by direct calculation on the triangular facets extracted from the STL file of the 3D model. Then the inner and outer grids of the model were identified by the algorithm in which we named Inner Seed Grid Method. Finally, a program to automatically generate a 3D FDM mesh was compiled. In the paper, a method named Triangle Contraction Search Method (TCSM) was put forward to ensure not losing the boundary grids; while an algorithm to search inner seed grids to identify inner/outer grids of the casting model was also brought forward. Our algorithm was simple, clear and easy to construct program. Three examples for the casting mesh generation testified the validity of the program.