Abstract:With the development of marine economy, the demand for underwater observation and prospecting equipment is increasing accordingly. Conventional underwater vision system can only provide image but lack of 3D information. To realize 3D measurement for various underwater applications, a binocular stereo vision system is investigated in this paper. Different with classical stereo vision problem, the challenge for underwater stereo vision system mainly comes from the light reflection between camera lens and water. Based on the proposed underwater stereo vision model and calibration method, a prototype of underwater 3D vision system is established. The system contains two cameras and the light-based illumination module, which can work under the water depth of 30 m. The experiments are implemented in the pool and near sea environments. Experimental results show that, the system has an observing distance up to 8 m in normal water condition. The effective measurement range is 0.5-4.5 m, and the measurement error varies from 2 to 20 mm with the increasing of observing distance. Precision of the proposed system can meet most underwater measurement requirement, and has great potentials in underwater observing and engineering applications.

Abstract:This paper presents a web-reading gas meter system based on WiFi communication technology. The MSP430F4152 low-power microcontroller is selected as the main controller chip. The gas usage information is collected through a reed sensor, and the gas usage detection and expense charging can be displayed in real-time. The microcontroller controls the MT7681 WiFi module, which connects to the remote server through the WLAN router and uploads the gas consumption data directly to the remote server. Finally, the user gas usage information can be updated on the Web server in real-time.

Abstract:Black phosphorus (BP) is a kind of direct bandgap 2D semiconductor with natural fold structure. It has attracted lots of attentions since 2014 for its outstanding physical properties. In this article, different-sized 2D BP nanosheets were successfully prepared by liquid exfoliation. The sizes, morphologies and thicknesses were characterized by scanning electron microscope, transmission electron microscope and atomic force microscope. Then the size-dependent Raman scattering spectra were collected. The biodegradability provides a possibility of BP for the biomedical application. Thus, degradation characteristics of BP nanosheets in aqueous solution were investigated. The time-dependent absorption spectra and pH revolution both suggest that the smaller BP sheets degraded faster, the predominant degradation occurred in the incipient 3 days. The underlying mechanism is attributed to the generation of orthophosphoric acid or other phosphorous acid.

Abstract:PM2.5 monitoring is an important means of air pollution control. Limited by the number of ground observation points, PM2.5 estimation from remote sensing data is an effective complement to conventional ground observation. The key idea of remote sensing estimation of PM2.5 is to retrieve aerosol optical depth firstly, and subsequently to reverse PM2.5 by aerosol optical depth based on the statistical relationship. This approach however is highly possible to cause error transmission, leading to instability of the inversion model. In this paper, we propose a PM2.5 remote sensing estimation method based on random forest algorithm to directly establish the relationship between moderate resolution imaging spectroradiometer (MODIS) image and ground measured PM2.5, so as to avoid the inversion error of atmospheric aerosol optical depth, finally obtain the PM2.5 estimation result with high precision. The method first uses random forest to train and test the MODIS image and ground monitoring station PM2.5 data after kriging interploation, and then selects the best model from multiple models according to the root mean square error (RMSE) of test index. Finally, the approach uses this model in the whole MODIS image to obtain the PM2.5 estimation result of the whole area. This experiment selects many MODIS image data from four seasons in Guangdong province to verify and compare the two performance indicators of R2 and RMSE. The results show that the proposed approach outperforms other approaches significantly.

Abstract:In the process of pedicle screw insertion surgery assisted by spinal surgery robot, the surgeon needs to spend a lot of time in searching and determining the location suitable for pedicle screw operation. In order to improve the operation efficiency, a rapid method based on machine learning was investigated to realize efficient planning of robot-assisted pedicle screw insertion. In the proposed method, the convolution neural network that commonly used in artificial intelligence research was introduced based on training set of spine computed tomography images. Firstly, the neural network model was set up to determine the adjustment parameters between layers in the network. Then the feature extraction and classification of sample image were carried out. The cross validation method was used to train sample data to verify the correctness of convolution neural network model. Finally, the method of machine learning was used to identify the computed tomography images of patients that suitable for the location of pedicle screw implant. With this proposed method, surgeons only need to complete the final fine planning based on the area of safety constraint, and efficiency of operation can be improved distinctly.

Abstract:Existing wireless data transmission modules have some disadvantages, such as high power consumption, short transmission distance, low reliability and high cost. In this paper, a new design of wireless data transmission module based on LoRa was proposed. The module uses SX1276 as the radio frequency chip and the low-power microprocessor STM8L151 as the main chip, and embeds the contiki operating system. We discuss the design of hardware and software in this module, and evaluate its performance. The final tests indicate that the proposed wireless transmission module has advantages of low power consumption, long transmission distance and high reliability. It is suitable for use in wireless meter reading and environmental monitoring systems.

Abstract:Excess oxygen in the supercritical water oxidation systems usually causes the problem of system operation cost improvement. To solve this problem, a high pressure water absorption principle based method was investigated for the O2 recycle. The Aspen Plus process of supercritical water oxidation system with oxygen recovery and the PSRK model was applied to study the influence of system parameters like pressure and temperature. The analyzing results showed that, with increasing pressure the purity of O2 can be increased but the O2 yield was decreased in the gas phase. With the increasing temperature, the ratio of O2 in gas phase can be increased but the purity of O2 was decreased. When the separator pressure and temperature were set to 8 MPa and 27℃, the ratio and purity of O2 was 89.29% and 83.33% respectively. The material and energy consumption cost of the system was calculated, and the results showed that the material and energy consumption cost was 2.811 ￥/kg chemical oxygen demand (COD). The cost can be reduced 21.01% in comparison with existing supercritical water oxidation system with oxygen recovery. Moreover, the reduction rate of the material and energy consumption cost increases gradually with the increasing of excess oxygen coefficient.

Abstract:The molecular mechanism of ischemic myocardial injury is still a hot topic in the international academic circles. In this paper, C57BL/6 wild type (WT) mouse strains, very low density lipoprotein (VLDL) receptor knockout (VLDLR-KO) mice and VLDL receptor transgenic (VLDLR-TG) mice, were selected to investigate on the effect of VLDL receptor on myocardial ischemic injury in vivo and in vitro. Key molecular signaling pathways were found based on the biomolecular network analyses. A causal relationship between VLDL receptor→MAPKs, AKT, NF-κB signaling pathway and the pathological phenotype of myocardial infarction, was identified by computational analysis of functional modules across biological networks, to illustrate the effect of VLDL receptor molecular mechanism in myocardial ischemic injury.