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Catalytic combustion gas sensors have been widely used for the leakage detection of combustible gases. However, the catalytic sensor with low preparation cost and high repeatability in a mass production have great importance. In this view, a new structure of high-performance catalytic sensor was proposed. Catalytic-type gas sensors based on screen-printing Platinum (Pt) heating electrode onto a porous alumina substrate was fabricated. This design enables porous alumina ceramics to act as the support of catalyst and substrate of heating electrode, simultaneously. The screen-printing technique obviously enhance the uniformity of the sensor devices in batch. To demonstrate the feasibility of this design, a prototype hydrogen sensor was prepared with a relatively high sensitivity around 30 mV/Vol% at 245°C and excellent a long-term stability. Additionally, the sensing performances of hydrogen devices were also verified by finite element method (FEM) modeling. The simulation results suggested that the response time and response value were related to the thickness of substrate and the operating temperature of sensors. The facile and large-scale fabrication method of the sensor device in this work is expected to have potential utility for detection in industry and for personalized applications.

Recommendations promoted worldwide have suggested a period of protection lasting more than 20 years against hepatitis B (HB) following primary immunization. Starting in 1987, universal HB vaccinations were carried out in Long An County, Guangxi Province, one of the earliest counties in which plasma-derived HB vaccine was delivered to newborns across China. Data collection targeted toward understanding the long term (26–33 years since primary immunization) immune effects of the plasma-derived HB vaccine was conducted in 2015; a second data collection was carried out in 2019 to assess seroconversion in the same cohort. This study qualitatively compared positive vs negative results and quantitatively assessed HB biomarkers – HB surface antigen (HBsAg), antibody to HBsAg (anti-HBs), HB e-antigen (HBeAg), antibody to HBeAg (anti-HBe), and antibody to HB core antigen (anti-HBc) – in serum 26–33 years after the full initial course of HB vaccination, then analyzed anti-HBs seroconversion using the two-phase sampling method in the same cohort and calculated the anti-HBs seroconversion rate from 2015 to 2019. The protective sero-conversion rate (anti-HBs ≥10mIU/mL) was 37.6% (192/511); the HBsAg-positive rate was 5.3% (27/511); the anti-HBs mean geometric titer (GMT) was 11.1 mIU/mL. Among the 143 participants involved in both 2015 and 2019 data collections, the seroconversion rate was 3.5% (5/143); two individuals had protective anti-HBs levels in 2015. These findings indicate that anti-HBs status can be seroconverted to a protective concentration level 4 years earlier in a high HBV epidemic region. The role of genomic mutations and the disappearance of immune memory and seroconversion should be investigated.

An electronic nose based on metal oxide semiconductor (MOS) sensors has been used to identify liquors with excessive methanol. The technique for a square wave temperature modulated MOS sensor was applied to generate the response patterns and a back-propagation neural network was used for pattern recognition. The parameters of temperature modulation were optimized according to the difference in response features of target gases (methanol and ethanol). Liquors with excessive methanol were qualitatively and quantitatively identified by the neural network. The results showed that our electronic nose system could well identify the liquors with excessive methanol with more than 92% accuracy. This electronic nose based on temperature modulation is a promising portable adjunct to other available techniques for quality assurance of liquors and other alcoholic beverages.

In compressed sensing (CS), the absolute value of the inner product of signal and atom (or dictionary) is used to select atom (or dictionary); the atoms (or dictionaries) with larger absolute values of inner product are selected to decompose and reconstruct signals. This characteristic usually makes it impossible to distinguish the edges of objects (or targets) in some complex cases, especially when the density of objects is very high. For example: let signal x1 = [···00110110···]T, x2 = [⋯001110100⋯]T; ψ1, ψ2, ψ3 and ψ4 denote several sparse basis matrices (i.e., sparse dictionaries); ψ1i = [⋯00000100⋯]T, ψ2j = [⋯00110000⋯]T, ψ3k = [⋯00111000⋯]T, and ψ4l = [⋯00111110⋯]T are the sparse bases (i.e., atoms) from these sparse basis matrices (i.e., dictionaries), respectively. For signal x1, ψ4l (or ψ4) is selected instead of ψ2j (or ψ2); likewise, for x2, ψ4l (or ψ4) will be selected instead of ψ3j(or ψ3) and ψ1i (or ψ1). This causes the edge of the object to be unrecognizable. Another example is in lp regularization, it is not necessarily the optimal case: the smaller the value of ||Ψd-1 x||0, the better the sparse basis matrix (i.e., dictionary), or the larger the weighing parameter. At present, the inner product is used to process almost all signals in CS. Choosing the dictionary that matches the signal best rather than the dictionary with the maximum inner product value can reconstruct the signal more accurately. In order to overcome the above shortcoming, we propose a fully automatic radar image processing algorithm of CS based on arbitrary block statistical histogram and dynamic dictionary. We use arbitrary block statistical histogram to calculate the non-zero block numbers of different sizes, which can better choose the appropriate sparse base (or dictionary) for the signal. Furthermore, the better measurement vector y can be obtained, and the signal can be reconstructed more accurately than the state-of-the-art methods at the receiving end. To realize the proposed method, we construct objective functions and flow charts for noiseless and noisy signals, respectively. In our method, for noiseless signal, discarding the sub-images that do not contain objects can reduce running time; for noisy signal, according to the theory of wavelet, choosing the appropriate wavelet (i.e., wavelet basis) can usually suppress noise. Our proposed algorithm can overcome the above shortcoming of CS in using the absolute value of the inner product, reduce running time, suppress-noise, and improve the signal-to-noise ratio (SNR). The simulation results show that our method is superior to the state-of-the-art methods.

Microwave heating of water-bearing coal can promote pore water evaporation. The pores are broken under the action of steam pressure, increasing the permeability of the coal. This study is aimed at investigating the mechanism of permeability improvement of water-bearing coal rock by microwave steam explosion. First, a microwave oven was used to irradiate and heat five groups of coal rock with different water contents; the NMR test was then conducted on the heated sample. Second, the internal vapor pressure and temperature changes during the heating process were obtained through the T-connector for samples with different water contents. Finally, a numerical experiment was used to explore the deformation characteristics of pores under three filling conditions. The experimental results showed that the total porosity increased significantly when the water content of coal increased from 0% to 8%, while the permeability increased by nearly 4.78 times. The extreme value of gas pressure inside the sample showed an increasing trend. The gas pressure and temperature were in line with the equation of state for an ideal gas during the rising phase. Numerical experiments showed that the pore boundary shrunk inward under vacuum conditions, and compressive stress appeared at the tip. The saturated humid air and liquid water conditions expanded the pore boundaries outward and caused tensile stress at the tip, with the latter being nearly 2.3 times larger than the former, making it more conducive to the development of pores. The findings of this study can be used as a reference value for the expansion of coalbed methane extraction technology.

In order to improve the portability of the automated test of the trunking communication system, this paper proposed a universal automated test solution for the trunking communication system. It’s based on the general architecture design of the trunking communication system, providing a replaceable communication protocol codec module. With the DSL-defined test script language describing the test cases, and efficient scheduling schemes for the test task, the automated functional test and performance test of the trunking communication system are realized. Theoretical analysis and experimental results show that the minimum load test task scheduling scheme based on user operation load prediction has lower response time and lower load balancing effect compared with the traditional static task scheduling scheme.

Because of the rapid development of Internet technology in recent years, the speed of information data growth is faster and faster, through the use of Internet information data to landscape architecture analysis and research, has become the main direction of industry development. Landscape planners are involved in a wide range of projects, and architectural objects are often very complex in layout. Projects are usually composed of multiple components. For the point clouds corresponding to these objects, the direct reconstruction of them is relatively complex, which requires macroscopic and reasonable planning on the regional scale. Generally, plots should be designed in three-dimensional space. The contents presented by planning and design of different scales are also different. In dealing with multi-level regional planning and design, this paper mainly focuses on the parametric design technology research of landscape architecture. First, it starts from the design of large areas, analyzes the status quo of regional scale, and then starts to design with the help of three-dimensional model. First will get the clusters of 3 d model the coarse segmentation class continue to split into more rules part, according to the characteristics of the model data, the first of 3 d model to differential information to estimate the point cloud data, calculate the normal vector and curvature of point cloud data, through a point cloud registration technology will point cloud unified under different Angle of view to the same coordinate system, through the big data landscape algorithm for geometric feature and image feature point detection, detailed point cloud data processing algorithms in the process of coarse segmentation of regional scale in the same cluster of different object segmentation, again through the panoramic image segmentation for interior point cloud of geometric structure information. The data can be classified intelligently, the corresponding point cloud data can be marked, and the geometric structure information can be marked into the point cloud data to be segmented through point cloud matching, so as to enhance knowledge reserves, find problems and solve problems timely.

In this paper, an adaptive track fusion algorithm is proposed based on the fusion algorithm combining the optimal weighting and recursive least squares method. Simulation results show that the method can effectively improve the accuracy of target detection in longitude, latitude, speed and heading. The ship tracks are more accurate after multi-source information fusion.

Under the guidance of the theory of mantle-branch structure-associated metallogenesis and on the basis of the geological characteristics, analysis of the ore-forming and ore-controlling structures, the geochemical characteristics of metallogenesis, the source of ore-forming materials, changes in the physical and chemical conditions of metallogenesis, changes in the vertical width of ore veins, and changes in gold grade of the Shihu gold deposit, the mechanism of its metallogenesis was discussed and the rules of vertical variation of ore veins were summarized in this study. It is pointed out that the orebodies under exploitation at present time should be in the middle and upper portions of gold veins in the Shihu gold mining district. Particularly on the basis of the characteristics of mantle-branch structure-associated metallogenesis, it is indicated that metallogenesis is controlled mainly by such ore-forming conditions as temperature and pressure. Deep-seated ore-forming fluids are characterized mainly by injection and precipitation. So the vein bodies in the adjacent metallogenic structures are of obvious comparability, and there would be great prospects for ore search both at depth and in the periphery of the Shihu gold deposit. Therefore, ore prospecting should be strengthened both at depth and in the peripheries.