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The industrial methane steam reforming reaction usually employs particulate catalyst that are easy to prepare and cost-effective, but suffer from problems such as high reactor pressure drop and low overall catalyst utilization. In this study, the Ni-Al2CaO4 powder prepared by the equal volume impregnation method was subjected to particle size control using a pressing method, and was made into catalyst particles of different sizes. Some of the catalysts were filled into honeycomb structures with cordierite and metal substrates, respectively, to prepare regular channel packing catalysts. The differences in methane steam reforming conversion rate, H2/CO selectivity, and overall pressure drop among the three catalysts were compared, and the influence of particle size and regular channel on reaction performance was systematically explored. The results showed that under the same conditions, as the catalyst particle size increased, the methane conversion rate and pressure drop increased. The regular channel packing catalysts with the two substrates showed similar pressure drop levels, but the metal substrate exhibited a higher methane conversion rate due to its excellent thermal conductivity. Compared with single-particle catalysts of the same size, the pressure drop of the metal substrate regular channel packing catalysts was reduced by more than 25%. Under the conditions of a gas hourly space velocity of 2000 h-1, a reaction temperature of 700 °C, and a water-to-carbon ratio of 3, the 40-60 mesh metal substrate regular packing catalysts showed a 7% increase in methane conversion rate, reaching 95.2%.

The vibration and noise problems of hybrid transmission during operation will affect the comfort of HEY. The research on the vibration and noise reduction of hybrid transmission can provide technical support for NVH performance improvement. This paper describes the detection and identification of noise sources, gear modification, optimization of boxes' natural frequency and increasing damping for vibration and noise reduction in hybrid transmission. Finally, the directions of development are analysed for vibration and noise reduction technology of hybrid transmission.

Accurate inversion of PM2.5 concentration is crucial for haze management. Currently commonly used inversion methods cannot accurately invert the concentration in non-site areas, so this paper proposes a PM2.5 concentration inversion method based on an integrated learning model. The method utilises the Top Atmospheric Reflectance (TOAR), observation angle and meteorological element data as input features, and screens the important features by Random Forest, and constructs an integrated inversion model using XGBoost and LightGBM. The results show that the model built by TOAR improves R2 by 2.9% and reduces RMSE and MAE by 2.67 and 1.45, respectively, compared with the AOD-based model, and our model has an inversion accuracy of 0.95, which is better than other models. We used the model to estimate and analyse the historical PM2.5 concentration changes at Huaihe station in Tianjin, China, and the results were consistent with the trend of the actual PM2.5 concentration distribution, and it is clear that the proposed model has a high inversion accuracy.

Ciconia boyciana is a rare migrant bird in China and is listed as endangered species by IUCN. In order to identify their important stopover sites during migration, based on the Random Forest and the MaxEnt model, the occurrence records of Ciconia boyciana in spring migration and autumn migration in 2021 and 24 environmental variables were used to simulate the potentially suitable stopover sites. Compared hotspot stopover sites with current conservation area distribution, the strategies of the conservation establishment were proposed.

Automatic body region localization in medical three-dimensional (3D)-CT images is a critical step of computerized body-wide Automatic Anatomy Recognition (AAR) system, which can be applied for radiotherapy planning and interest slices retrieving. Currently, the complex internal structure of human body and time consuming computation are the main challenges for the localization. Therefore, this paper introduces and improves the YOLO-v3 model into the body region localization for these problems. First, seven categories of body regions in a CT volume image I are defined based on the modification version of our previous work. Second, an improved YOLO-v3 model is trained to classify each axial slice into one of the seven categories. Then, the effectiveness of the proposed method is evaluated on 3D-CT images that collected from 220 subjects. The experimental results demonstrate that the slice localizing error is less than 3 NoS (Number of slices), which is competitive to the state-of-the-art methods. Beyond this, our method is simple and computationally efficient owing to its less training time, and the average computational time for localizing a volume CT images is about 3 second, which shows potential for a further application.

This study describes the web-based agricultural technology evaluation information system, which has been shown to provide a flexible interface with which to arrange various assessment and information management function procedures. Secondly, this study examines the effects of the application of the academic misconduct detection mechanism and abnormally scoring mechanism. In an evaluative study with the two evaluation business cycle of the system, it has been found that this system is more efficient, more accurate and more rigorous than the traditional offline evaluation model. It has also been shown that cheating behaviour in agricultural technological achievements information declaration and evaluation link can be detected accurately and promptly.

In this paper, thermosetting fluorine-containing polyurethane (S-FPU) was synthesized through a novel method with two-step process and its surface properties was studied. Firstly, fluorine-containing epoxy compound (FO) was obtained by epichlorohydrin (ECH) and tetrafluoropropanol (TFP). Further, the fluorinated polyether polyols (FPO) was synthesized by cationic copolymerization of tetrahydrofuran (THF) with the FO, the fluorine was located on the side chains of the FPO and the molecular weight of FPO was controllable, besides, the molecular weight distribution of FPO was narrow. Finally, the S-FPU was prepared by FPO as soft segment, MDI as a hard segment and TEA as chain extender. The influence of fluorine enrichment on the surface properties of S-FPU was studied by controlling curing temperature, curing time and structure of FPO. In addition, the surface fluorine content of S-FPU and the surface hydrophobicity were studied in detail. The results showed that with the curing temperature decreased, the surface fluorine content of S-FPU increased, and when the curing time was more than 10 hours, the fluorine element did not migrate to the surface. What’s more, with the molecular weight of FPO increased, the surface fluorine content of S-FPU increased.

In order to solve the problem that the vehicles within the university campus are increasing steadily and a large number of outside vehicles drive through the campus arbitrarily and park disorderly. In this paper, a campus intelligent vehicle management system based on ETC is designed, and the ETC technology is introduced. On the basis of analyzing the system’s hardware architecture and workflow, a design model of lane is given. Finally, it discusses the communication theory of Winsock, customs a format of data frame and proposes a Winsock-based intelligent data synchronization algorithm. The daily traffic volume has been decreased by 65% since the system is put into operation in a university.