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In view of the low stability of conventional insulator detection technology and the inability to realize insulator detection in complex working environment, a composite insulator detection technology based on optical field sensing and Fourier spectrum combined detection is proposed. Optical field and spectral data of insulators are collected by optical sensor probe and interferometer. The relationship between light intensity and electric field intensity is obtained by processing the optical electric field data of insulator. Fourier transform is carried out on the insulator spectral image, and the full Fourier spectrum of the normal insulator is taken as a reference. Combined with the analysis of the optical electric field data of the insulator, the fault location and fault cause of the composite insulator are located and detected, so as to realize the joint detection of the insulator. Compared with the conventional detection technology, the proposed joint detection technology has better stability and is more suitable for complex working environment.

Background The polysaccharide hyaluronan (HA) is abundant in pancreatic cancer (PC) tissue and promotes pancreatic cancer cell (PCC) motility in vitro. However, it is controversial as to whether high-molecular-weight HA (HMW-HA) or low-molecular weight HA(LMW-HA) is present in the pancreatic cancer stroma and whether PCC or pancreatic stellate cell (PSC) in PC tissue produces HA. We thereby aim to characterize the molecular weight and source of HA in PC tissue that promotes cancer cell motility. Methods We analyzed the expression of hyaluronan synthase 2 (HAS2) and the hydrolyzing enzyme hyaluronidase 1 (HYAL1) in PCC lines and pancreatic stellate cells (PSCs) using real-time PCR. HA production in the supernatant of PCC lines and PSCs and in PC tissues was quantitatively and qualitatively examined. Finally, we knocked down HYAL1 expression in one of the PCC line PANC-1 cells and analyzed the impact on cell migration. Results HAS2 was abundantly expressed in activated PSCs (aPSCs) but less so in quiescent PSCs (qPSCs) and PCC lines. The baseline expression of HYAL1 did not differ among the cell types. The concentration of HMW-HA was higher in the supernatant of aPSCs than in that of PCC lines. Treatment with exogenous HMW-HA promoted PANC-1 cell motility. Knockdown of HYAL1 decreased HMW-HA-promoted PANC-1 cell migration, which was accompanied by a decrease in intracellular HA levels. Conclusion aPSCs are an important source of stromal HMW-HA, which promotes PCC migration in an HYAL1-dependent manner in PC.

Recent works show that deep neural networks trained on image classification dataset bias towards textures. Those models are easily fooled by applying small high-frequency perturbations to clean images. In this paper, we learn robust image classification models by removing high-frequency components. Specifically, we develop a differentiable high-frequency suppression module based on discrete Fourier transform (DFT). Combining with adversarial training, we won the 5th place in the IJCAI-2019 Alibaba Adversarial AI Challenge. Our code is available online., Comment: 3 pages. This paper is a technical report of the 5th place solution in the IJCAI-2019 Alibaba Adversarial AI Challenge. This paper has been accepted by the corresponding workshop

Four-rotor UAV is widely used in reconnaissance missions, UAV usually needs to adjust the yaw angle before reconnaissance aerial photography. To improve the speed of the four-rotor uav at the adjustment of yaw angle, this paper presents a variable-domain fuzzy PID controller. First, we established the nonlinear dynamic model of four-rotor UAV. Then, we fuzzed the corresponding variables in the governing equation, formulated fuzzy rules and introduced variable theory to adjust domain of discourse. Finally, we used simulink software to carry out experiments. The experiment result shows that variable-domain fuzzy PID controller has some undoubtedly advantages in performance evaluation compared to traditional PID controller, which including dynamic property and steady state error, and can be used to improve the quality of the adjustment of yaw angle.

Radar deployment is of great importance for airborne radar network performance. An efficient deployment required a good detection performance and energy consumption. This paper focuses on the detection of directional stealth target using UAV swarms equipped with active and passive radars. Based on calculated bistatic radar cross section (RCS) of stealth targets and Cassini oval sensing region, the optimum geometrical structures are analyzed with bistatic radars (BRs) using multiple mobile adaptive forward receivers to extend the dynamic detection range and coverage. Multi-objective optimization model is introduced and many critical constraints have been identified. Grid partition method and wolf pack algorithm (WPA) are applied to search the optimal deployments. In particular, we consider the problem of deploying an airborne network of BRs in the surveillance region to maximize the worst-case intrusion detectability as well as the vulnerability of active radar. Our findings provide valuable and practical insights into deployment of UAVs for stealth target tracking and the efficiency of the proposed algorithm is also validated by our simulation results.

This paper focuses on the settlement of loess high-fill ground. The settlement characteristics of the loess filled ground in the gully were studied by centrifuge model tests. The results indicate that those factors, i.e. the boundary condition, fill height, valley shape, compaction degree, and humidification, have significant effect on the settlement of filled ground. Settlement occurs mainly in the construction stage, and the post-construction settlement linearly increases with increasing filled height. The narrow valley tectonic has obvious deformation confinement effect on the filled soil. The full compaction of filled loess during the construction phase can reduce the post-construction settlement, and the improvement of compaction degree will be more obvious for the settlement control of large thickness filled ground. Due to the water-sensitive characteristics of loess, a significant settlement caused by wetting exists as long as the filling material being humidified, even though the post-construction settlement tends to be stable.

Asphalt pavements subject to solar radiation and air temperature can reach high temperatures causing not only environmental problems such as the heat island effect on cities but also structural damage due to rutting or hardening as a result of thermal cycles. This paper established a finite element model to analyze the temperature distribution in asphalt pavement due to thermal environmental conditions. By considering the continuous solar radiation, air temperature and wind velocity, pavement temperature was calculated in the heat transfer module in Comsol Multiphysics. It is found that the amplitude of the pavement temperature is mainly dependent on air temperature and solar radiation. Another 3-D model was established to test the high temperature distribution of asphalt pavement in Nanjing, China. Then the simulation result was compared to SHRP and LTPP prediction, and pavement temperature could agree well with SHRP model in certain depth. The model could predict the maximum, minimum, and amplitude of the pavement temperature with good accuracy, which could provide guide for asphalt pavement design and to develop cool pavements.

More than 90% of the highway pavements in China use cement treated base or semi-rigid base. Due to the relatively high stiffness of this type of base layer, its structural capacity plays a vital role for the stability, integrity, performance and durability of the pavement structure. However, there are little studies on the long-term structural capacity of in-service semi-rigid base and the influence of other pavement or non-pavement related factors. This paper evaluated the long-term structural capacity of the base layer by investigating the deflection basin data of a typical section of highways. The deflection basin parameters (DBPs) measured by falling weight deflectometer (FWD), such as the D20–D60, were investigated by simulation and used to characterize the structural capacity of the semi-rigid base. Data mining methods including decision tree and multiple linear regression were adopted to identify and quantify the influence of factors including base material properties, traffic level, upper layer thickness and materials. Findings from this study can be used to evaluate the structural performance of in-service semi-rigid base and to help design pavement structural preservation treatments.