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Summary: Background: Since 1992, when recombinant hepatitis B vaccine was introduced in China, government health officials have used nationally representative serological surveys to monitor progress in prevention and control of hepatitis B. In 2020, we conducted the fourth seroepidemiological survey, which for the first time included medical evaluation of the clinical status of HBsAg positive subjects over the age of 15 and their medical management. We report survey results in comparison with the three previous surveys. Methods: Consistent with previous national surveys, the 2020 survey used a stratified, three-stage cluster random sampling method to select for evaluation 1-69-year-olds in 120 national disease surveillance points. Blood samples were tested for HBsAg, anti-HBV surface antigen (anti-HBs), and anti-HBV core antigen (anti-HBc) in the National Hepatitis Laboratory of the Institute for Viral Disease Control and Prevention of China CDC. HBsAg positive subjects aged ≥15-year were evaluated for evidence of liver disease, and through face-to-face questionnaire-based survey, we determined the healthcare management cascade of HBV-infected individuals. Findings: HBsAg prevalence in 1–69-year-olds was 5.86%; in children 1–4 years of age, seroprevalence was 0.30%; 75 million people were living with HBV nationwide. Among HBsAg-positive individuals 15 years and older, expert medical examination found that 78.03% were HBsAg carriers with no evidence of liver damage, 19.63% had chronic HBV with liver enzyme abnormalities, 0.84% had evidence of cirrhosis, and 0.15% had evidence of liver cancer. 59.78% of HBsAg + individuals were aware that they were positive before the survey, 30 million were unaware; 38.25% of those who knew they were positive (17 million) had medical indications for antiviral treatment, and 17.33% of these individuals (3 million) were being treated with antivirals. Interpretation: The decline in HBsAg prevalence in the general population, from 9.72% in 1992 to 5.86% in 2020, and in 1–4-year-olds from 9.67% in 1992 to 0.30% in 2020, shows progress that continues on track toward WHO targets for prevention of new infections. Implementation of acceptable strategies to identify infected individuals and offer long-term medical monitoring and management will be important to prevent complications from hepatitis B infection and for meeting WHO cascade-of-care targets. Funding: The study was funded by the Major Science and Technology Special Project of China’s 13th 5-Year Plan (grant no. 2017ZX10105015); Central finance-operation of public health emergency response mechanism of Chinese Center for Disease Control and Prevention (131031001000200001, 102393220020010000017).

Wheat pests and diseases are one of the main factors affecting wheat yield. According to the characteristics of four common pests and diseases, an identification method based on improved convolution neural network is proposed. VGGNet16 is selected as the basic network model, but the problem of small dataset size is common in specific fields such as smart agriculture, which limits the research and application of artificial intelligence methods based on deep learning technology in the field. Data expansion and transfer learning technology are introduced to improve the training mode, and then attention mechanism is introduced for further improvement. The experimental results show that the transfer learning scheme of fine-tuning source model is better than that of freezing source model, and the VGGNet16 based on fine-tuning all layers has the best recognition effect, with an accuracy of 96.02%. The CBAM-VGGNet16 and NLCBAM-VGGNet16 models are designed and implemented. The experimental results show that the recognition accuracy of the test set of CBAM-VGGNet16 and NLCBAM-VGGNet16 is higher than that of VGGNet16. The recognition accuracy of CBAM-VGGNet16 and NLCBAM-VGGNet16 is 96.60 and 97.57%, respectively, achieving high precision recognition of common pests and diseases of winter wheat.

In the context of accelerated industrialization and urbanization, the importance of the green energy sector has become increasingly prominent. From the perspective of the role of the financial system, this article deeply explores the role mechanism and environmental constraint relationship of financial instruments in green energy development. The article constructs a measurement model of financial instruments on the efficiency of green energy development, introduces data spatial correlation into the econometric analysis framework, and establishes a spatial econometric model to analyze the impact of financial instruments on development efficiency. By testing the data from 2008 to 2020, the study shows that the level of global financial means support passes the significance level, and the magnitude of the mediating effect when the spatial Durbin model is simplified to an error model is about 13.5%. The study also found that enhancing green energy development can positively affect neighboring regions. This paper provides an effective methodological path for studying the role of financial instruments in green energy development, which is of great theoretical and practical significance for promoting the development of the green energy sector.

The structure of energy consumption and reducing the carbon footprint has become an important issue in the field of carbon and energy conservation. This paper adopts spatial econometric Analysis to construct a framework for analyzing the influencing factors of carbon emissions based on the STIRPAT model. It applies the K-means algorithm to effectively cluster and classify the energy consumption of different regions. Then, the article analyzed these clustering results in depth using the Kaya constant equation to calculate the carbon emissions of each area. The results of the carbon footprint analysis reveal that the Gini coefficient of carbon emissions in the eastern region peaked at 0.352 in 2014, while decreasing to a low of 0.284 in 2019. the western and central areas have the highest Gini coefficients of carbon emissions at 0.271 and 0.248, respectively. furthermore, from 2015 to 2022, the ecological pressure on the carbon footprint of the whole industry has always remained at 3.033 above, reaching a historical high of 3.433 in 2022.The application of this paper not only helps to solve the problems in the existing carbon footprint evaluation methods, but also provides a scientific basis for more effective management and reduction of carbon emission.

Insulin-like-growth factor-1 (IGF-1) is the ligand for insulin-like growth factor-1 receptor (IGF-1R), and the roles of IGF-1/IGF-1R in diabetic nephropathy (DN) are well-characterized previously. However, the biological functions of AG1024 (an IGF-1R inhibitor) in DN remain unknown. This study investigates the roles and related mechanisms of AG-1024 in DN. The experimental DN was established via intraperitoneal injection of streptozotocin, and STZ-induced diabetic rats were treated with AG1024 (20 mg/kg/day) for 8 weeks. The 24 h proteinuria, blood glucose level, serum creatinine, and blood urea nitrogen were measured for biochemical analyses. The increase in 24 h proteinuria, blood glucose level, serum creatinine, and blood urea of DN rats were conspicuously abated by AG1024. After biochemical analyses, the renal tissue specimens were collected, and as revealed by hematoxylin and eosin staining and Masson staining, AG-1024 mitigated typical renal damage and interstitial fibrosis in DN rats. Then, the anti-inflammatory effect of AG-1024 was assessed by western blotting and ELISA. Mechanistically, AG-1024 upregulated SOCS1 and SOCS3 expression and decreased phosphorylated JAK2, STAT1, and STAT3, as shown by western blotting. Collectively, AG-1024 (an IGF-1R inhibitor) ameliorates renal injury in experimental DN by attenuating renal inflammation and fibrosis via the SOCS/JAK2/STAT pathway.

The micro-size flake silver powders were prepared through wet-chemical reduction method by using a micro-jet reactor. Herein ascorbic acid was used as a reducing agent, and sulfuric acid was used as a stabilizer. And the lauric acid was used as a dispersing agent to prevent particles’ agglomeration. The micro-jet reactor collides the two solutions together and uniformly mixes outside the reactor, to avoid the problem of clogging in the microchannel. The effects of dispersant addition and micro-jet flow rate on the morphology, particle size, and other parameters of silver powder is investigated in the present work. Interestingly, the addition of dispersant agent and stabilizer have a significant impact on the morphology and parameter of the silver particles. Under the conditions of micro-jet flow rate of 50 mL·min−1, sulfuric acid addition amount of 2%, and lauric acid addition amount of 0.8% by the weight of silver nitrate, a kind of flake silver powders with 4.40–4.70 μm can be prepared. The volume resistivity of the silver paste prepared from the obtained flake silver powders is in the range of 1.4–1.6 × 10−4 Ω·cm−1, which meets the application test requirements of conductive silver paste.

The MoS2-doped graphite/copper self-lubricating composites (Gr-MoS2/Cu) were synthesized by a rapid microwave sintering procedure. In this paper, the thermal properties and friction behaviors of Gr-MoS2/Cu composites at room temperature to 200 °C were studied. The doping of molybdenum disulfide solid lubricant into graphite could promote the formation of friction film in the friction process, and optimize the friction and wear properties of graphite/copper composites. Meanwhile, the thermal and frictional properties of the composites at 200 °C are better than those at room temperature. In addition, the influence of the heat dissipation on the friction property of composites was analyzed and studied. The excellent heat dissipation property of the composites effectively mitigated the damage of the friction film and improved the friction property of the composites in the friction process.

Sparrow search algorithm (SSA) is easy to fall into local convergence and convergence stagnation. In order to solve these problems, this paper introduced Circle chaos map into the original SSA to improve its global search ability at the beginning of iteration. Meanwhile, it introduced T-distribution variation to affect the sparrow population position update rules in different iteration periods. Finally, we constructed the “similarity function” to measure the “dispersion” of the sparrow population, and formulated the search rules of the sparrow population under different “dispersion”. In order to test the specific optimization performance of the proposed algorithm, the test results of 54 test functions are compared with those of 9 other algorithms which are widely used, and then the test results are analyzed using non-parametric tests in statistics. At the same time, this paper introduces this algorithm into three concrete engineering test problems for testing. The results of these tests all prove that the proposed algorithm has stronger global optimization ability and higher convergence precision compared with other algorithms.

This paper presents a new swarm intelligence optimization algorithm: Flamingo Search Algorithm (FSA), which is inspired by the migratory and foraging behavior of flamingos. A mathematical model of flamingo behavior is built so that FSA has the global exploration and local exploitation capabilities required for an optimization algorithm. Three sets of experiments based on 68 test functions are designed to evaluate the convergence speed, optimization-seeking accuracy, stability, running time, and global search capability of FSA. The effect of different input parameters on the search results of FSA is then discussed, and the optimal parameter selection interval is summarized. In addition, nine test functions are selected to visualize the trajectory of the flamingo population during the search. The test results of the above designs all indicate that FSA is superior to other algorithms in solving optimization problems. Finally, three kinds of simulation experiments, which are push-pull circuit problem, path planning problem and network intrusion detection system, are designed to test the practicability of FSA. The code used for the main experiment in this article can be obtained from website https://github.com/18280426650/FSA.

To develop and test a mission-oriented and multi-dimensional benchmarking method for a small scale university aiming for internationally first-class basic research.

[Objectives] This paper aims to analyze the protective performance of different broadside protection structures subjected to semi-armor-piercing missile warheads. [Methods] Single-layer homogeneous steel armor structures and double-grid protection structures are designed, and the protective performance of different broadside protection structures in blocking medium subsonic semi-armor-piercing missile warheads is compared via numerical simulation. [Results] The results show that it is easy to design single-layer homogenous steel armor for use as broadside protection structure, but high strength steel with excellent mechanical properties should be used and the thickness should be more than 50 mm. In addition, consideration should be given to the construction of thin plates and thick plates, as well as the electrochemical corrosion of different types of steel. The above problems can be avoided by using a double-layer structure as the broadside protection structure. For double-grid protection structures, the weight resources should be allocated to the inner plate by increasing its thickness, thereby improving the overall protective ability of the double-grid protection structure. [Conclusions] The results of this study can provide useful references for the design of broadside protection structures capable of withstanding semi-armor-piercing missile warheads.

The influence of Ti addition (~0.10 wt%) on hot ductility of as-cast high-manganese austenitic steels has been examined over the temperature range 650–1,250 °C under a constant strain rate of 10−3 s−1 using Gleeble3500 thermal simulation testing machine. The fracture surfaces and particles precipitated at different tensile temperatures were characterized by means of scanning electron microscope and X-ray energy dispersive spectrometry (SEM–EDS). Hot ductility as a function of reduction curves shows that adding 0.10 wt% Ti made the ductility worse in the almost entire range of testing temperatures. The phases’ equilibrium diagrams of precipitates in Ti-bearing high-Mn austenitic steel were calculated by the Thermo-Calc software. The calculation result shows that 0.1 wt% Ti addition would cause Ti(C,N) precipitated at 1,499 °C, which is higher than the liquidus temperature of high-Mn austenitic steel. It indicated that Ti(C,N) particles start forming in the liquid high-Mn austenitic steel. The SEM–EDS results show that Ti(C,N) and TiC particles could be found along the austenite grain boundaries or at triple junction, and they would accelerate the extension of the cracks along the grain boundaries.

The high-temperature mechanical properties of twinning-induced plasticity (TWIP) steel with 0.05 % C, 25 % Mn, 3 % Al, 3 % Si have been investigated using the GLEEBLE 3500 machine. The result shows that the zero ductility temperature and the zero strength temperature of the TWIP steel are measured at 1,225 °C and 1,275 °C, respectively. The brittleness temperature interval I is from 1,200 °C to the melting point, and the brittleness temperature interval III is from 650 °C to 800 °C. The tensile fracture has been examined using the scanning electron microscope, optical microscope and electron backscatter diffraction to determine the fracture mechanisms. The result shows that the twin is not the main influencing factor of the high-temperature plasticity of TWIP steel. Instead, the degree of dynamic recrystallization determines its high-temperature plasticity. A small number of AlN particles are found near the fractures, but these particles are so coarse, therefore, have no influence on the brittle fracture, and ferrite transformation and work hardening are the main reasons that cause the brittle fracture.

The review was done in order to make clear the problem of the hot corrosion of the Thermal Barrier Coatings(TBCs)during gas turbine serving. This paper summarizes the factors resulting from the hot corrosion of TBCs during turbine service and classifies methods for enhancing the corrosive resistance of TBCs. A prospective methodology for improving corrosion resistance is also formulated. The main types of corrosion coating include phase reaction, oxidizing of the bond coating, salt-fog corrosion, CMAS corrosion and fuel impurity corrosion. So far, methods for improving the corrosion resistance of TBCs include developing new coating materials, anticorrosive treatment on the surface of TBCs, modifying the stacking configuration and improving the cleansing functions of the gas turbines. In the future, developing new materials with excellent performance will still be the main direction for boosting the improvement of the hot corrosion resistance of TBCs. Simultaneously, improving the tacking configuration and nanotechnology of TBC coatings are potential approaches for improving corrosion resistance. With the development of a Ceramic Matrix Composite (CMC), the focus of the hot corrosion of TBCs may turn to that of Environmental Barrier Coatings (EBCs).

This study investigated the effect of planetary ball mill parameters on the particle size of a powder mixture of alumina and magnesia, the composition of synthetic magnesium aluminate spinel (MAS), and the subsequent densification of MAS. The results show that the particle size of the milled powders decreases gradually from 32.39 μm to 11.69 μm with the increase of milling time from 1 h to 7 h at milling speed of 120 rpm. The particle size of the milled powders decreases gradually from 42.92 μm to 9.00 μm as the milling speed was increased from 60 rpm to 240 rpm at a milling time of 3 h. Only a spinel phase can be obtained from these calcined powders when the starting powders of the calcined powders are milled for more than 1 hour or at above 60 rpm. The relative density and flexural strength of the sintered products exceed 86.67% and 105 MPa, respectively.

Blockchain technology is the underlying technology of Bitcoin, which is fair, transparent and decentralized. The integrated energy system has the characteristics of open interconnection, user-centered and distributed peer-to-peer sharing, and its energy trading model will also be developed centrally to distributed. The characteristics of blockchain technology make it naturally applicable to energy transactions in integrated energy systems. This article first analyzes the characteristics of the integrated energy system market and summarizes the participants in the market. Then, based on the existing research and analysis, a blockchain-based energy transaction architecture is designed, and a weakly centralized management method is introduced. finally, the problems and challenges faced by the application of blockchain in energy transactions are analyzed.

The hardness, elastic modulus, and friction coefficient of the CuZn alloy before and after treatment at 700 °C and 3 GPa for 10 mins were measured by nanoindenter. Effects of high pressure heat treatment on its microstructure and micro-mechanical properties were discussed. The results show that high pressure heat treatment can refine the microstructures of the CuZn alloy, and its hardness, elastic modulus, ratio of hardness, and elastic recovery rate after the 3 GPa treatment increased by 15.44 %, 4.89 %, 8.82 % and 35.90 %, respectively. And the friction coefficient is also decreased.