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The method of characteristics has very strong geometric adaptability and can be used to solve the 3-D whole core problem of high temperature gas-cooled pebble-bed reactor. However, it suffers from the disadvantages of thousands of iterations and slow calculation speed. At present, there have been some attempts to reduce calculation time for method of characteristics, including coarse mesh finite difference (CMFD), general coarse mesh rebalance (GCMR) and general coarse mesh finite difference (GCMFD). The CMFD method is applied to realize the acceleration of regular region like squares. Furthermore, to break through the limitation of macroscopic regular geometry for the numerical acceleration method, researchers successively propose the GCMR method and the GCMFD method, but these methods are very complex to implement in irregular geometries and some approximation factors must be introduced. Based on the analysis of more dense tracks are arranged for the 3-D model, the sparse macro-track transport acceleration method was proposed, which greatly reduces the calculation amount of the acceleration equation and obtains a very good acceleration efficiency without reducing the accuracy. The 2-D method of characteristics divides the angular space into M azimuthal angles and P pole angles. The 3-D method of characteristics generally uses a level symmetric quadrature set. In 2-D geometry, the angle is relatively more dense at the poles. As a result, the 2-D macro-track transport acceleration can select a small number of azimuth angles with reflection symmetry and one pole angle as the solution directions of the acceleration equation. The sparse macro-track transport acceleration method implemented in this paper used the same angles as the method of characteristics. The number of tracks for 3-D problems is an order of magnitude higher than for 2-D problems. That is why reducing the number of 3-D tracks is a promising method for reducing the amount of accelerated equation calculation. This paper applied the macro-track transport acceleration method to 3-D whole core problem of high temperature gas-cooled pebble-bed reactor to solve the problem of irregular geometric numerical acceleration. The sparsity, macro-track length limit, and the maximum iteration step limit of the macro-track method are the main factors that affect the acceleration performance. The selection method of acceleration parameters was studied through two benchmark problems. Excellent speedup ratio can be obtained by setting the sparsity to 3-5, the macro-track length to around 2.0 cm, the acceleration iteration steps limit to 20-60. The results of 3-D small light water reactor benchmark and simplified pebble-bed reactor core model show that about 7 times the time speedup ratio and about corresponding 20 times the iterative step speedup ratio can be achieved.

In this paper, the main literature related to 4DCT imaging and reconstruction techniques over the past 20 years is reviewed, and the contents are summarized. This paper provides a systematic and comprehensive introduction to 4DCT research from five perspectives: the concept of 4DCT, scanning mode and imaging method, reconstruction algorithm, application, research status, and future development expectations. In this study, five types of reconstruction algorithms are summarized, and the advantages, disadvantages, and research difficulties of each algorithm are briefly evaluated. Finally, we conduct a brief statistical analysis on the cited works from the perspective of reconstruction methods, revealing the research progress and future research trends of 4DCT reconstruction algorithms.

ObjectivesIn order to effectively broaden the beam width of the 3 dB axis ratio of a Beidou antenna, this paper proposes a slotted laminated microstrip patch antenna loaded with parasitic elements. MethodsThe Beidou dual frequency band feature is realized through a two-layer substrate structure. The bandwidth is widened by slotting. Circular polarized radiation is achieved by cutting corners at the edge of the patch. At the same time, L-shaped parasitic elements are loaded around the patch to broaden the 3 dB axial ratio beam width of the antenna.ResultsThe measured and simulated results are in good agreement. The relative bandwidths of the antenna in the Beidou B1 and B2 bands are 3% and 7.5%. The beam width of the 3 dB axis ratio can reach 180° and 176°, and the maximum gain can reach 6 dBi. In the Beidou receiver test, the number of antenna satellites can reach more than 17, and the positioning accuracy is within meters. ConclusionsThis paper proposes and validates a high-precision positioning dual band Beidou navigation antenna with wide axis ratio beam width. The results can provide references for the design of small Beidou navigation antennas.

Lagerstroemia is a native plant in China, which has been cultivated for more than 1 500 years. It is an excellent summer flower woody plant, and is widely used in urban landscaping because of its beautiful color, long flowering period and the advantage of purifying air. The germplasm resources of Lagerstroemia indica are extremely rich. There are about 60 species of Lagerstroemia in the world, 40% of which are in China. The results of national and regional investigations have laid a good foundation for the study of L. indica. In recent years, the cultivation and application of new cultivars have been increased in various regions. The breeding method is mainly traditional breeding, and many new cultivars with good characters and high market value have been cultivated. With the rapid development of breeding technology and molecular biology, a breakthrough has been made in the researches on molecular assisted breeding of L. indica. In this paper, the classification research, germplasm resources, breeding research and introduction and application of L. indica were reviewed. We systematically sorted out the germplasm resources of L. indica in China, including 24 wild species and 350 cultivars, discussed the research process and development trend of breeding of L. indica at home and abroad, and summarized the current situation of introduction and application research. In regard to the current research status of L. indica, this paper offered reflections on future research directions to enhance investigations of L. indica, improve germplasm resource banks, and establish information sharing channels; efforts on breeding should be expanded beyond flower color, fragrance, plant type, resistance and extension of flowering period; and biological and intelligent technologies should be leveraged to strengthen breeding techniques and accelerate innovation in L. indica germplasms. Continuous application forms for L. indica resources should be developed according to local conditions to fully realize their value.

BackgroundThe development of railways has a long history, but there is limited research on the health of railway workers at home and abroad. China's high-speed railway development has attracted worldwide attention in recent years, and it is of great significance to study how to promote the health of this occupational population to ensure the safety of railway transportation. ObjectiveTo identify development trends and hotspots in the field of railway workers' health at home and abroad. MethodsThe research literature related to the health of railroad workers dated from January 1, 1973 to December 31, 2022 was searched using the China Knowledge Network Infrastructure (CNKI) and Web of Science Core Collection (WoS) databases. After screening and cleaning, the included literature was subjected to bibliometric analysis by applying CiteSpace 6.1R6 software to visualize and analyze literature co-citation, keyword emergence, and keyword timeline graphs, and by VOSviewer 1.6.19 to visualize and analyze country/region collaboration, keyword co-occurrence, and keyword clustering. ResultsDuring the period from 1973 until 2022, a total of 273 Chinese literature and 165 English literature were found to report studies related to the health of railway workers. The Chinese literature began to grow rapidly in 2009 and peaked in 2015, and the number of English literature published in a relatively flat state over the studied period. The country with the most papers indexed by Science Citation Index (SCI) was the United States (58 papers), which also presented the richest international collaborations. The document with the highest domestic citation frequency was published in the Chinese Journal of Mental Health in 1994, and the document with the highest SCI citation frequency was published in the American Journal of Epidemiology in 1994. The keyword co-occurrence analysis showed that the included Chinese literature mainly focused on health checkups, health management, hypertension, mental health, and chronic diseases and their prevalence; the included English literature focused on mortality, lung cancer, epidemiology, and diesel engine exhaust and its exposure. The analysis of emergent words showed that health management, frontline workers, and occupational stress were the topics of interest in Chinese literature in the last five years, while occupational stress, diesel exhaust emissions, and noise exposure were the topics of interest in English literature in the last ten years. The results of the timeline graph analysis suggested that the recent research directions in Chinese literature were health intervention, humanistic care, staff canteens, etc. There were few English-language articles related to this area after 2010. ConclusionThe research hotspots of railroad practitioners' health will keep changing with the development of high-speed railways in countries around the world. The outstanding rise of Chinese literature issued in the last decade has been in striking contrast to the slow progress and decreasing of English literature. The Chinese literature has gradually expanded the hotspots from chronic diseases to health management, occupational stress, and sleep disorders.

The nuclear reactor system is complex and the operating environment is harsh, resulting in the complex phenomena of multi-physics coupling. The multi-physics coupling codes developed in the early stage shows limitations on codes' scalability and generality. Therefore, it is of great significance to build a multi-physics coupling framework and conduct research on key technologies in coupling problems, which may accelerate the development process of autonomous multi-physics coupling platform in China. In this paper, the multi-dimensional and multi-physics coupling finite element analysis platform for nuclear reactor developed by XJTU-NuTHeL was introduced. The main work consisted of the development of thermal-hydraulic model, the research of fuel performance analysis technology and the establishment of multi-physics coupling framework. In terms of thermal-hydraulic calculation, XJTU-NuTHeL conducted a series of studies on pressurized water reactors and advanced reactors grounded in the advanced multi-physics coupling framework, and developed the nuclear reactor system safety analysis code, NUSAC. In addition, a subchannel analysis model tailored for liquid metal fast reactors was established, and the fully coupled subchannel transient analysis code, FLARE, was developed. NUSAC and FLARE were then verified against relevant codes and experimental data. In the realm of fuel performance analysis, considering the wide application of finite element method in solid mechanics and its versatile modeling capabilities, XJTU-NuTHeL developed a fuel performance analysis code, BEEs, based on finite element method. The code could not only conduct multi-physics coupling analysis for traditional rod fuels under steady and transient conditions, but also extends its applicability to accident tolerant fuels and other fuels with diverse geometric shapes. This paper focused on the study and analysis of coated particle dispersed fuel and plate type fuel. The multi-scale simulation results of coated particle dispersed fuels, as well as the thermomechanical and corrosion behavior of plate type fuels were shown. In the context of multi-physics coupling analysis, the efficiency and accuracy of different mesh grid mapping schemes were studied and a multi-physics coupling framework was established. An example of the framework was then presented, showcasing the integration of the fuel performance code BEEs, the Monte Carlo neutron physics code OpenMC, and reactor system safety analysis code NUSAC. The keys parameters of mechanics, thermal-hydraulic and neutronics were obtained and analyzed through the coupling different codes. The multi-dimensional and multi-physics coupling finite element analysis platform built in this paper can provide a strong support for the high-fidelity numerical simulation of nuclear reactor multi-scale and multi-physics coupling.

To prevent severe safety accidents caused by primary coolant leakage in pressurized water reactors (PWRs), it is necessary to monitor the leakage rate of key parts of the reactor coolant pressure boundary (RCPB) in order to take timely countermeasures. The primary coolant of PWRs is usually high-pressure supercritical water containing boron, which can produce 18F in the high neutron flux environment of the reactor. The leak rate of the RCPB can be inferred by measuring the activity concentration of the radioactive 18F aerosol produced by the coolant leaking into the containment. A measurable sample source is usually obtained by extracting sample gas containing 18F aerosol from the containment and filtering it in the monitor. The measurement method used by the monitor is to screen the γ signal by using the β signal as the gate signal, which is actually a γ relative measurement method using the coincidence method to reduce the background. The electronic design of the monitor prevents the β-channel signal from being recorded, which makes it impossible to achieve the absolute measurement as with conventional coincidence methods. To ensure the accuracy of the monitoring results, the 18F aerosol monitor needs to be calibrated. In this paper the monitor was calibrated using a standard 18F surface source produced by the intermittent spot method on a filter paper base. By means of the decay of the 18F source and the automatic recording function of the monitor, the indication number of the monitor was measured at six source activities of different orders of magnitude, i.e. the count of the energy spectrum at the position of the 511 keV γ-window. The data were used to obtain the activity response and uncertainty of the monitor's readings and to verify the feasibility of such a calibration scheme on the monitor. Two standard point sources of 22Na and 68Ge/68Ga were also used to calibrate the monitor to verify the feasibility of using long-lived nuclides to make alternative sources for calibration. Sets of 511 keV γ-window count data from γ and coincidence channels were recorded to investigate the effect of the γ coincidence additive effect and different β emission spectra on the activity response, and to determine which long-lived positron nuclides should be used in the field calibration. Calibration with a standard 18F surface source shows that the monitor can give stable and reliable readings of this type of standard source over different orders of magnitude within the range. The extended uncertainty (k=2) of the displayed activity response is 6.0%, which meets manufacturing requirements. And the calibration of the long-lived positron nuclide standard point sources shows that the positron spectrum has a great influence on the activity response of the monitor, and the γ coincidence additive effect is not very significant. Therefore, it is recommended to use 22Na with β energy close to 18F to make point sources or surface sources for field calibration.

The focal spot size of X-ray tube is one of the key factors affecting the imaging resolution, and it is also an important index to characterize the working performance of the X-ray source. Typically, after the X-ray tube is manufactured, the focal spot size must be measured and marked. Nowadays, the most widely used measurement standards for X-ray tube focal spot size in the world are IEC 60336, EN 12543, and ASTM E1165. Between various standards, there are differences in the focal spot size measurement methods, scope of application, loading factors and imaging equipment. Among these, the slit method of EN 12543 standard is mostly utilized in industrial X-ray tubes. However, due to its complex and precise design requirements, the test equipment, i.e., the slit camera, is difficult to produce and process, and the cost is high, which is not conducive to promotion and application. This paper studied the influence and variation of the measurement of the focal spot size at different slit sizes by using double tungsten alloy cylinders instead of slit camera. Based on the calibration of distance and position parameters in the cylinder method, the measurement equipment was conveniently positioned, and the distance between the focal spot and the translation mechanism was measured simultaneously, which improves the position accuracy of the focal spot size measurement. Additionally, the formula for determining the focal spot size in the slit method was improved, so that the slit method can be applied to a wide range of slit widths. In particular, the geometric magnification of the system can be measured directly when the slit width is large, skipping the step of measuring the distance between the focal spot and the translation mechanism. The experiment scheme has low requirements on the centering conditions of the equipment and the distribution of the X-ray source. In the data processing process, dark field correction and bright field correction were used to eliminate the problem of inconsistency in the response characteristics of each detector pixel, and the Wiener Filtering was performed on the signal output by the detector to deal with Gaussian noise and uniformly distributed noise. The experiment results show that relatively accurate measurement values can be obtained by measuring MXR-225HP/11 with double tungsten alloy cylinders with the same spacing as the focal spot size. The measurement relative error is less than 10%. According to international standards, when the measurement results are within plus or minus 10% of the theoretical value, it can be used as a method to determine the focal spot size. Therefore, the improved method in this paper is reliable and does not require high testing equipment, allowing it to be widely used. In addition, the geometric magnification of the focus measurement device can be directly calculated when the slit width is larger than the focal spot size, and the calculation results are consistent with the results measured in the cylinder method.

This paper proposes a radar signal transceiver framework that combines single-bit sampling and time division multiplexing receivers to satisfy the application requirements of low-cost lightweight radars. Firstly, this paper explains the advantages of saving the number of receivers by introducing the working principle of the framework. From the perspective of radar resource allocation, the importance of single-bit sampling in this framework was analyzed; additionally, the proposed framework can achieve better performance than a classical linear frequency modulation continuous wave radar using time and space exchange. Subsequently, the formulas for range, velocity and angle measurement were derived, along with the Cramér-Rao bound for estimating target parameters. Accordingly, the performance advantages of the proposed framework were verified, and the signal-to-noise ratio conditions for its stable operation were determined. Finally, this paper verifies the accuracy of the target acquisition principle of the proposed framework and the reliability of the performance analysis by using a velocity dimensional pairing algorithm based on single-bit two-dimensional multiple signal classification.

With the growing demand for radar target detection, Sparse Recovery (SR) technology based on the Compressive Sensing (CS) model has been widely used in radar signal processing. This paper first outlines the fundamental theory of SR and then introduces the sparse characteristics in radar signal processing from the perspectives of scene sparsity and observation sparsity. Subsequently, it explores these sparse properties to provide an overview of CS applications in radar signal processing, including spatial domain processing, pulse compression, coherent processing, radar imaging, and target detection. Finally, the paper summarizes the applications of CS in radar signal processing.

Orthogonal Frequency Division Multiplexing (OFDM) waveform design is one of the key physical layer technologies for achieving joint radar-communication. OFDM waveforms usually have issues with high Peak to Average Power Ratio (PAPR) and high waveform autocorrelation sidelobe levels. This paper proposes an integrated waveform design method based on data distortion to address the communication rate degradation problem of existing joint PAPR and autocorrelation sidelobe reduction methods. The paper also takes the Error Vector Magnitude (EVM) of communication data as one of the optimization objectives, reducing the communication bit error rate caused by data distortion. Firstly, an optimization model was constructed to minimize the Integrated Sidelobe Level Ratio (ISLR) and EVM under PAPR constraints. Secondly, based on the characteristics of the modulation constellation, the multi-objective high-dimensional non-convex optimization problem is transformed into two single objective optimization subproblems by using the data distortion of outer constellation modulation and all modulation data distortion. Convex relaxation operation and Alternating Direction Method of Multipliers (ADMM) are respectively used to solve the simplified subproblems, resulting in low ISLR waveform and low EVM waveform under PAPR constraint. The simulation results show that the integrated waveform designed by the proposed method can meet the requirements of PAPR, and has good sensing and communication performance.

Time Domain Coding Metasurface (TDCM) is an emerging technology enabling dynamic modulation of electromagnetic waves. In response to the control characteristics of this technology, this paper presents a radar jamming method based on TDCM intrapulse and interpulse coding optimization. First, optimization models are established in fast and slow time domains. By optimizing intrapulse and interpulse phase coding, the energy redistribution of targets is achieved, thereby generating deceptive interference on the range-Doppler two-dimensional plot. Subsequently, a genetic algorithm is employed to solve this discrete optimization problem. Furthermore, this paper analyzes the effect of various modulation factors on interference effectiveness in terms of TDCM coding strategies, providing guidance for achieving optimal strategies for deceptive interference.

Data governance capability is fundamental to coal mine intelligence construction. It could accelerate the intelligent construction of coal mines and promote the digital transformation of the coal industry so as to building a modern energy system in digital China. This paper therefore discusses the theory and methods of improving data governance capability for intelligent coal mines. Specifically, this study analyzes its strategic demands of intelligent coal mine construction on data governance and offers a working definition for data governance capability for intelligent coal mines. Then an evaluative system is proposed for the evaluation of data governance capability for intelligent coal mines. Further, by drawing on capability maturity theory, this study establishes a maturity model that specifies the improvement path of data governance capability for intelligent coal mines. Finally, based on the PDCA cycle theory, this paper puts forward strategies for improving data governance capability for intelligent coal mines, in order to 1)supplement existing theories of data governance capability enhancement, and 2)provide references for future practices of data governance.

ObjectiveKnowledge services in agricultural scenarios have the characteristics of long periodicity and prolonged activity time. Traditional recommendation models cannot effectively mine hidden information in agricultural scenarios, in order to improve the quality of agricultural knowledge recommendation services, agricultural contextual information based on agricultural time should be fully considered. To address these issues, a Time-aware and filter-enhanced sequential recommendation model for agricultural knowledge (TiFSA) was proposed, integrating temporal perception and enhanced filtering.MethodsFirst, based on the temporal positional embedding, combining the temporal information of farmers' interactions with positional embedding based on time perception, it helped to learn project relevance based on agricultural season in agricultural contexts. A multi-head self-attention network recommendation algorithm based on time-awareness was proposed for the agricultural knowledge recommendation task, which extracted different interaction time information in the user interaction sequence and introduced it into the multi-head self-attention network to calculate the attention weight, which encoded the user's periodic interaction information based on the agricultural time, and also effectively captured the user's dynamic preference information over time. Then, through the temporal positional embedding, a filter filtering algorithm was introduced to adaptively attenuate the noise in farmers' situational data adaptively. The filtering algorithm was introduced to enhance the filtering module to effectively filter the noisy information in the agricultural dataset and alleviate the overfitting problem due to the poorly normalized and sparse agricultural dataset. By endowing the model with lower time complexity and adaptive noise attenuation capability. The applicability of this method in agricultural scenarios was improved. Next, a multi-head self attention network with temporal information was constructed to achieve unified modeling of time, projects, and features, and represent farmers' preferences of farmers over time in context, thereby providing reliable recommendation results for users. Finally, the AdamW optimizer was used to update and compute the model parameters. AdamW added L2 regularization and an appropriate penalty mechanism for larger weights, which could update all weights more smoothly and alleviate the problem of falling into local minima. Applied in the field of agricultural recommendation, it could further improve the training effect of the model. The experimental data came from user likes, comments, and corresponding time information in the "National Agricultural Knowledge Intelligent Service Cloud Platform", and the dataset ml-1m in the movie recommendation scenario was selected as an auxiliary validation of the performance of this model.Results and DiscussionsAccording to the user interaction sequence datasets in the "National Agricultural Knowledge Intelligent Service Cloud Platform", from the experimental results, it could be learned that TiFSA outperforms the other models on two different datasets, in which the enhancement was more obvious on the Agriculture dataset, where HR and NDCG were improved by 14.02% and 16.19%, respectively, compared to the suboptimal model, TiSASRec; while on the ml-1m dataset compared to the suboptimal model, SASRec, HR and NDCG were improved by 1.90% and 2.30%, respectively. In summary, the TiFSA model proposed in this paper has a large improvement compared with other models, which verifies verified the effectiveness of the TiFSA model and showed that the time interval information of farmer interaction and the filtering algorithm play an important role in the improvement of the model performance in the agricultural context. From the results of the ablation experiments, it could be seen that when the time-aware and enhanced filtering modules were removed, the values of the two metrics HR@10 and NDCG@10 were 0.293 6 and 0.203 9, respectively, and the recommended performance was poor. When only the time-aware module and only the augmentation filtering module were removed, the experimental results had different degrees of improvement compared to TiFSA-tf, and the TiFSA model proposed in this paper achieved the optimal performance in the two evaluation metrics. When only the multi-head self-attention network was utilized for recommendation, both recommendation metrics of the model were lower, indicating that the traditional sequence recommendation method that only considered the item number was not applicable to agricultural scenarios. When the augmented filtering module was introduced without the time-aware module, the model performance was improved, but still failed to achieve the ideal recommendation effect. When only the time-aware module was introduced without the augmented filtering module, there was a significant improvement in the model effect, which proved that the time-aware module was more applicable to agricultural scenarios and can effectively improve the model performance of the sequence recommendation task. When both time-aware and augmented filtering modules were introduced, the model performance was further improved, which on the one hand illustrated the dependence of the augmented filtering module on the time-aware module, and on the other hand verified the necessity of adopting the augmented filtering to the time-aware self-attention network model.ConclusionsThis research proposes an agricultural knowledge recommendation model that integrates time-awareness and augmented filtering, which introduces the user's interaction time interval into the embedded information, so that the model effectively learns the information of agricultural time in the agricultural scene, and the prediction of the user's interaction time and the object is more closely related to the actual scene; augmented filtering algorithms are used to attenuate the noise in the agricultural data. At the same time, the enhanced filtering algorithm is used to attenuate the noise in the agricultural data, and can be effectively integrated into the model for use, further improving the recommendation performance of the model. The experimental results show the effectiveness of the proposed TiFSA model on the agricultural dataset. The ablation experiments confirm the positive effect of time-awareness and enhanced filtering modules on the improvement of recommendation performance.

This paper aims to comprehensively analyze the Alfven instability observed in the high βN discharge of EAST, considering both experimental observations and simulation studies. There are two purposes of this paper, the first one is to observe the AE activity in EAST, the second one is to apply and validate the FAR3d code in EAST. In the experimental analysis, the presence of a strong instability is detected using magnetic probes and electron cyclotron emission diagnostics. Two kinds of modes are observed:one's frequency ranging from approximately 70 kHz to 100 kHz, exhibiting an upward frequency sweep, and another frequency at around 60 kHz. These instabilities are found to destabilized near ρ=0.46 with a toroidal mode number of 2 calculated by toroidal Mirnov probe array. Complementing the experimental findings, simulations were performed using the eigensolver method of the FAR3d code. This is the first time that FAR3d code was applied on EAST, so the model needed to be validated by reproducing the AE activity. The simulation results successfully identify the dominant mode, toroidal Alfven eigenmode (TAE), occurring at ρ=0.45 with a frequency of 87 kHz, toroidal and poloidal number n/m=2/3, 2/4. Additionally, a sub-dominant mode, energetic particle mode (EPM), is identified at ρ=0.55 with a frequency of 62 kHz, n/m=2/4. The agreement between the simulation and experimental results confirms the accuracy of the simulation model in characterizing the instability types, as well as providing consistent location and frequency information. Furthermore, the FAR3d code is employed to evaluate the influence of the finite Larmor radius (FLR) effect. The simulation results demonstrate that the FLR effect has minimal impact on identifying low toroidal mode number (n) instability modes in the high βN discharge of EAST. Consequently, the FLR effect can be neglected during the mode identification process, allowing for accelerated calculations. While, in the simulation of high toroidal mode number, the FLR effects should be considered. In conclusion, this study presents a comprehensive analysis of the Alfven instability in the high βN discharge of EAST. By combining experimental observations with simulation results, the types of instabilities, their locations, and frequencies are successfully identified and found to be in good agreement. Additionally, the study confirms that the FLR effect has little influence on identifying low n instability modes, enabling faster calculations by excluding FLR effects during mode identification. These findings contribute to a better understanding of the Alfven instability in high βN discharges and provide valuable insights for future research in fusion plasma physics.

The diffusion coefficient of oxygen in zirconium alloy oxide film and matrix is an important parameter in corrosion kinetics of zirconium alloys. At present, there are some reports on the diffusion coefficient of oxygen in zirconium and oxide film, but the numerical values in the literature are quite different. In this paper, zirconium alloy was corroded in pure water to obtain a sample with an oxide film thickness of 1 μm. Through vacuum annealing test, the oxygen concentration distribution of the oxide film at four different temperatures was obtained, the diffusion coefficient of oxygen in zirconium alloy matrix was calculated, and the Arrhenius relation of the diffusion coefficient in this temperature range was obtained by fitting. Compared with the literature data, the trend is similar, but the values are different. The main reasons may be the following two aspects:One is the measurement deviation of oxygen concentration distribution curve, including spatial position deviation and concentration error, and the other is the different grain size of samples. The diffusion coefficient of oxygen in zirconium metal without irradiation obtained in this work can be mutually verified with the literature data, which has high reliability. Based on the corrosion weight gain curves of two zirconium alloys at four different temperatures, the diffusion coefficient of oxygen in the zirconium alloy oxide film was estimated by the equivalent diffusion model of the oxide film and the corrosion weight gain curve before the corrosion transition. It is found that the diffusion coefficient of oxygen in the zirconium alloy oxide film increases obviously with the increase of temperature, and the diffusion speed of atoms is significantly affected by the microstructure of the diffusion medium except temperature. Based on the research of two parts, it is found that the diffusion coefficient of oxygen in the oxide film is greater than that in zirconium metal when the temperature is below 440℃, and the diffusion coefficient of oxygen in the oxide film is more than twice that in zirconium metal when the temperature is below 400℃, which shows that the diffusion of oxygen in the oxide film of zirconium alloy is main at the interface at lower temperature (440℃ in this paper), and further shows that grain boundaries, pores and microcracks in the oxide film play a very important role in the corrosion behavior of the alloy. The above research provides important calculation parameters and basic research theory for the corrosion kinetic model of zirconium alloy. The results show that the diffusion coefficient of oxygen in Zr-Sn-Nb matrix follows a relationship as DZr(cm2/s)=0.18·exp(-180 000/RT). The diffusion coefficient of oxygen in oxide film, which follows a relationship as Dox(cm2/s)=3×10-7exp(-101 550/RT), is also evaluated by the weight gain profile in pre-transition stage.

The monolithic scintillation crystal detector has the ability to position the three-dimension interaction location of the gamma ray in the detector depending on accurate acquisition of scintillation light distribution. Depth estimation of light field can be solved by a lens array in light field technology. A new detector model was designed in the paper which introduced a lens array for positioning the interaction in the monolithic detector. The scintillation light is focused by each lens unit in the lens array. Photons in some discrete pixels of the photon counter array where the scintillation light is focus on are detected to form an image of multiple focus points instead of the scintillation light distribution detection based on continuous crystal. The position of the scintillation light source in the crystal can be reconstructed from the focus image through optical path inversion. The detector model consisting of a monolithic crystal, a lens array and a multi-pixel photon counter was established in the paper. The monolithic scintillator was a lutetium-yttrium silicate (LYSO) scintillator with dimensions 48 mm×48 mm×45 mm. The lens was hemispherical with a radius of 15 mm supposed to be uniformly distributed in 3×3 array and the material was as same as the crystal. The crystal and the lens array were considered as a whole in the simulation. The multi-pixel photon counter was set at 44.4 mm from the crystal surface. The pixel size of the photon counter array was 3 mm and the quantum efficiency was 30%. The axis of symmetry of the three parts was same. The reconstruction algorithm was based on optical path inversion from multiple focus points for locating the 3D position of gamma-ray interaction. The intersection points of the inverted optical paths and the set z plane with different depths in the crystal was calculated in the reconstruction process. When the intersection points converged towards the same point in the z0 plane, the depth of interaction was z0 and the intersection point in the z0 plane was the interaction point. The reconstruction results were analyzed to evaluate the performance of the monolithic scintillation crystal detector based on the lens array. The x/y resolution is better than 1.54 mm and the z resolution is better than 3.13 mm. The two interaction points when coincidence occurs are reconstruced in the condition that the energy is the same. The detector is feasible for the positioning of two interaction points by the reconstruction results of three groups of selected positions. The monolithic scintillation detector based on a lens array has both good positioning ability and position resolution. The detector is suitable for the position reconstruction of multiple interaction points.

Existing studies have clearly demonstrated that people eating more whole grains have reduced risks of many chronic metabolic diseases compared to those eating less. In the past 20 years, the whole grain industry has developed so rapidly in major developed countries and regions. In recent years, whole grains have also attracted extensive attention in our country. The research and development efforts of the whole grain standards in China have been strengthened. This paper introduced the progress of the global definition consensus of whole grain and whole grain food, summarized the international development status of whole grain raw materials and whole grain food related standards in many countries and institutions, such as the Working Group of ISO Whole Grain, the United States, Canada, the Netherlands, Codex Alimentarius Commission, and so on. This paper also reviewed the present situation of definition of the whole grain and whole grain food related standards in China. More than 20 relevant raw materials, food related standards and production technical regulations and the publishment situation of other whole grain standards in China, including national standards and industry standards and local standards and group standards, were summarized, and some whole grain related standards under formulation were also introduced. Finally, the paper puts forward the development direction and suggestions for the construction of whole grain standard system in China, including fully combining with the actual production situation of China’s whole grain food industry, integrating with international standards, and combining standard testing and certification. On the whole, the gradual improvement of the standard system of the whole grain food industry will help guide and regulate the high-quality and healthy development of the whole grain industry in China, and promote the creation of a diversified and healthy grain food ecology, and provide a technical basis for the development of the whole grain industry.

BackgroundPrinters can release particles, which is harmful to human health. However, there is insufficient research on how printing conditions affect the level of particles released by printers.ObjectiveTo explore the effects of different printing conditions on the level of printer-emitted particles.MethodsThe experiment was carried out in a closed experimental chamber, and the changes in the number concentration of particles (size range: 0.25-32 μm) and ozone concentration in the experimental chamber during designed printing process were monitored with a portable aerosol particle size spectrometer and an ozone detector respectively. The monitoring included three parts: 2 min before printing as the background number concentration, printing 72 sheets with a designed printing task sets, and then 10 min after printing. A set of printing tasks with predetermined conditions included font, font size, single/double-sided printing mode, page layout, paper size, paper brand, and paper moisture content. The association between printing conditions and level of printer-emitted particles was evaluated by Spearman correlation analysis.ResultsWhen printing in different fonts (Song and Kai) and different font sizes (14 points and 10.5 points), the number concentration peaks of particles in the experimental chamber were 14.71-59.35 P·cm−3, and there was no significant difference (P>0.05). There was no difference in the peak concentrations of printer-emitted particles between single-sided printing and double-sided printing (P>0.05), but there was a significant difference in the time of peak occurrence (P middle 1/ 3> lower 1/3). No increase in the concentration of printer-emitted particles was detected when printing with B5 paper. The peak concentration of printer-emitted particles in printing paper with varying degrees of paper moisture showed differences (P0.05).ConclusionBy changing printing conditions, the levels of printer-emitted particles are affected. Among them, page layout, paper size, and degree of paper moisture have a significant impact on the results; however, single/double-sided printing, font, font size, and paper brand have no significant impact on the results.

[Significance]Autonomous and intelligent agricultural machinery, characterized by green intelligence, energy efficiency, and reduced emissions, as well as high intelligence and man-machine collaboration, will serve as the driving force behind global agricultural technology advancements and the transformation of production methods in the context of smart agriculture development. Agricultural robots, which utilize intelligent control and information technology, have the unique advantage of replacing manual labor. They occupy the strategic commanding heights and competitive focus of global agricultural equipment and are also one of the key development directions for accelerating the construction of China's agricultural power. World agricultural powers and China have incorporated the research, development, manufacturing, and promotion of agricultural robots into their national strategies, respectively strengthening the agricultural robot policy and planning layout based on their own agricultural development characteristics, thus driving the agricultural robot industry into a stable growth period.[Progress]This paper firstly delves into the concept and defining features of agricultural robots, alongside an exploration of the global agricultural robot development policy and strategic planning blueprint. Furthermore, sheds light on the growth and development of the global agricultural robotics industry; Then proceeds to analyze the industrial backdrop, cutting-edge advancements, developmental challenges, and crucial technology aspects of three representative agricultural robots, including farmland robots, orchard picking robots, and indoor vegetable production robots. Finally, summarizes the disparity between Chinese agricultural robots and their foreign counterparts in terms of advanced technologies. (1) An agricultural robot is a multi-degree-of-freedom autonomous operating equipment that possesses accurate perception, autonomous decision-making, intelligent control, and automatic execution capabilities specifically designed for agricultural environments. When combined with artificial intelligence, big data, cloud computing, and the Internet of Things, agricultural robots form an agricultural robot application system. This system has relatively mature applications in key processes such as field planting, fertilization, pest control, yield estimation, inspection, harvesting, grafting, pruning, inspection, harvesting, transportation, and livestock and poultry breeding feeding, inspection, disinfection, and milking. Globally, agricultural robots, represented by plant protection robots, have entered the industrial application phase and are gradually realizing commercialization with vast market potential. (2) Compared to traditional agricultural machinery and equipment, agricultural robots possess advantages in performing hazardous tasks, executing batch repetitive work, managing complex field operations, and livestock breeding. In contrast to industrial robots, agricultural robots face technical challenges in three aspects. Firstly, the complexity and unstructured nature of the operating environment. Secondly, the flexibility, mobility, and commoditization of the operation object. Thirdly, the high level of technology and investment required. (3) Given the increasing demand for unmanned and less manned operations in farmland production, China's agricultural robot research, development, and application have started late and progressed slowly. The existing agricultural operation equipment still has a significant gap from achieving precision operation, digital perception, intelligent management, and intelligent decision-making. The comprehensive performance of domestic products lags behind foreign advanced counterparts, indicating that there is still a long way to go for industrial development and application. Firstly, the current agricultural robots predominantly utilize single actuators and operate as single machines, with the development of multi-arm cooperative robots just emerging. Most of these robots primarily engage in rigid operations, exhibiting limited flexibility, adaptability, and functionality. Secondly, the perception of multi-source environments in agricultural settings, as well as the autonomous operation of agricultural robot equipment, relies heavily on human input. Thirdly, the progress of new teaching methods and technologies for human-computer natural interaction is rather slow. Lastly, the development of operational infrastructure is insufficient, resulting in a relatively low degree of "mechanization".[Conclusions and Prospects]The paper anticipates the opportunities that arise from the rapid growth of the agricultural robotics industry in response to the escalating global shortage of agricultural labor. It outlines the emerging trends in agricultural robot technology, including autonomous navigation, self-learning, real-time monitoring, and operation control. In the future, the path planning and navigation information perception of agricultural robot autonomy are expected to become more refined. Furthermore, improvements in autonomous learning and cross-scenario operation performance will be achieved. The development of real-time operation monitoring of agricultural robots through digital twinning will also progress. Additionally, cloud-based management and control of agricultural robots for comprehensive operations will experience significant growth. Steady advancements will be made in the innovation and integration of agricultural machinery and techniques.

本文整理三位文化人類學家對教育的觀點。C. Geertz認為教育即文化限 縮，J. Henry認為教育即文化綑綁，G. D. Spindler則認為教育即文化干預、 文化壓縮，三者皆強調文化依賴教育擔負傳遞的功能，卻同時框限教育的內涵與運作。延伸討論的結果指出，教育的框限並非絕對的，教育不會被全然的文化所決定，在特定文化範圍內仍允許學校實施的彈性與個人抉擇的自由，也容許相對程度的創造；從文化相對論推論出教育的相對論，教育皆有其文化框限，各有其優缺點；每種教育模式都只是適應文化環境的文化選擇，沒有優劣差別，亦無放諸四海皆準的教育。在結論中，引用Spindler創用之文化治療概念，期待教育工作者從文化觀點進行質疑與批判，不需盲從於特定時空的教育模式，勇於發掘文化框限的機制與效應，以獲得教育的相對主體性，促成文化與教育的覺醒來支持合理教育的運作。 This article synthesizes the viewpoints of three cultural anthropologists on education. C. Geertz regards education as cultural reduction, J. Henry views it as cultural binding or fettering, and G. D. Spindler sees it as cultural intervention and compression. They all emphasize the reliance of culture on education for its transmission, yet at the same time, note how cultural also confines the operation of education. The extended discussion suggests that the limitations of education are not absolute. Education is not entirely determined by culture; there is still room for flexibility in implementation within the broader cultural space and freedom for individual choice, as well as opportunities for relative creativity. Derived from cultural relativism, the perspective adopted in this paper argues that all forms of education have their own cultural limitations, each with its advantages and disadvantages, and that every educational model is merely a cultural choice, adapted to its environment, with no superior or inferior models. In conclusion, drawing on Spindler’s concept of ‘cultural therapy,’ the paper calls for educators to critically question educational models from a cultural perspective, and to avoid blind adherence to specific educational models found in a particular time or place. It encourages the exploration of the mechanisms and effects of cultural constraints, with the goal of achieving relative subjectivity in education, and thereby fostering a better understanding of the interplay between culture and education that supports the rational operation of education.

ObjectiveThis paper aims to reveal the influence law of cushion pressure on the underwater noise radiation of air cushion vehicles (ACVs). MethodsAn ACV is taken as a computational example. First, the forming process of the skirt under cushion pressure is simulated according to the Newton–Raphson iteration method. Second, a numerical model considering skirt-air cushion-water coupling is established via the vibro-acoustic finite element method (FEM) and calibrated based on modal tests. Third, comparisons are made of the sound power level (SWL) of the ACV's underwater radiation noise under different pressure levels on the skirt and different cushion depression depths. ResultsUnderwater radiation noise is found to be positively correlated with air cushion pressure. The overall SWL increases by nearly 0.97 dB while the air cushion pressure increases by 1000 Pa. Increasing the stiffness of the skirt can effectively reduce the underwater radiation noise in the low frequency band, and increasing the cushion depression depth will increase the peak value of the SWL in the higher frequency band, and make the peak position shift to the low frequency direction. ConclusionThe influence law of air cushion pressure revealed in this paper has important guiding significance for evaluating and numerically predicting the acoustic performance of ACVs.

ObjectivesLow sampling rates on reconstruction surfaces cause high reconstruction error in near-field acoustic holography. Therefore, a deep learning-based approach which is applicable to planar sound sources and high-precision reconstruction with low sampling rates is put forward.MethodsA three-dimensional N-shaped convolution neural network for near-field acoustic reconstruction is established to extract features in the frequency dimension in order to make up for sparse sampling in the spatial dimension. A frequency focal mechanism, namely an adaptive frequency weight focus mechanism, is put forward to improve reconstruction precision in the natural frequency and high frequency. Moreover, this paper also raises frequency-scaled focal loss and frequency-scaled focal Kirchhoff–Helmholtz （KH） loss, which are considered regularization. To validate the proposed methods, datasets are created with COMSOL Multiphysics and Matlab.ResultsThe mean error range of 100–2 000 Hz of the algorithm proposed in this paper is only 4.96%, higher than those of SRCNN and PV-NN.ConclusionsThe proposed method is verified as having the potential to reconstruct the accurate velocity fields of sound sources under low sampling rates.

Automatic Target Recognition (ATR) is an interdisciplinary technological field related to pattern recognition, artificial intelligence, and information processing. ATR evaluation focuses on accessing ATR algorithms and systems. Due to the noncooperative targets, complex operating conditions, and multiple subjective preferences of the decision maker, ATR evaluation is performed for the entire ATR research process and shows its importance in guiding ATR development. This paper presents the connotation of ATR evaluation and briefly reviews ATR development. Furthermore, the conventional methods, applications, and latest developments in ATR evaluation are presented and discussed from the perspective of performance measures, test condition, inference and decision. Finally, several ATR evaluation research directions are summarized. This paper serves as a valuable reference for a better understanding of ATR evaluation and the effective adoption of various ATR evaluation methods.

To provide diverse book lending channels and services to the public and to guide healthy competition in library industry, this paper discusses the coopetition relationship between online shared bookstores and libraries from the perspective of readers’ choice behavior. According to the questionnaire survey from 187 readers in Guangzhou, MNL model is adopted to quantitatively analyze the effect of various factors such as personal attributes, borrowing requirements and habits on readers’ choice. Research shows that online shared bookstore and library, mainly public library, have different competition in terms of multi-dimensional needs and preferences. Thus, this paper proposes the potential cooperation mode between online bookstore and library in collection, data and space, so as to promote the mutually beneficial coexistence between them. (Article content in Chinese with English extended abstract)

The probabilistic safety assessment of nuclear containment under internal pressure is the key evaluation content for guaranteeing nuclear power plant safety, and the fragility assessment of the containment under internal pressure is the most crucial step in the probabilistic safety assessment of nuclear containment. At present, the internal pressure fragility assessment of the containment mostly adopts the simplified lognormal distribution model, which lacks a rigorous theoretical analysis. There are multiple uncertainty issues affecting structural responses of nuclear containment in the fragility analysis and the results of the fragility analysis should be on the basis of a rigorous capacity-demand model. Meanwhile, load parameters (i.e. internal pressure) are usually used as key information to assess the internal pressure failure probability of containment. However, damage and failure of containment are more intensively correlated to structural response parameters (e.g. structural acceleration, structural displacement, and damage indices) compared with load parameters. For this reason, this paper proposed an internal pressure fragility assessment method based on Bayesian theory for nuclear containment and a form of damage ratio was used as a parameter for fragility assessment of containment. The damage ratio was realized by defining the ratio of the damage area to the full area of the containment concrete. Specifically, the fragility assessment method first established a deterministic demand model for the containment under internal pressure, and then corrected the demand model by adding correction terms. After that, Bayesian estimation was used to gradually filter the correction terms, resulting in an accurate probabilistic demand model. Finally, a fragility assessment result was obtained by establishing a limit state equation for the containment. On this basis, the probabilistic model under internal pressure was introduced to realize the probabilistic safety assessment of the containment, and the results of probabilistic safety assessment were compared with those of conventional fragility assessment. The results show that the cumulative containment failure probability (CCFP) of the containment decreases gradually with the increase of the damage ratio and the coefficient of variation of the CCFP is obviously smaller than that of the conventional fragility assessment method. In this paper, Bayesian estimation is introduced for probabilistic safety assessment of internal pressure in containment, and the damage ratio is used as a key parameter for fragility assessment of containment, which can provide more accurate and conservative results for probabilistic safety assessment of internal pressure in containment.

Particle size and chemical composition are the basic parameters of nanomaterials. The nanoscale size endows nanomaterials with special properties different from bulk materials, such as surface and interface effect, small size effect, quantum size effect, macroscopic quantum tunneling effect and dielectric confinement effect. The type and content of chemical components determine the chemical properties of nanomaterials, such as chemical activity, catalytic selectivity, adsorption selectivity and biological affinity. To a large extent, particle size and chemical composition determine the application of nanomaterials in energy, electronics, environment, sensing, biomedicine and other fields. Therefore, the particle size and composition analysis of nanomaterials are of great significance for the optimization and application of their preparation process. Mass spectrometry is one of the main analytical techniques, which is used to detect the mass, elemental composition and chemical structure of particles or molecules, and it can analyze almost all types and forms of materials, with the characteristics of high analysis accuracy and high detection sensitivity. It has been more widely applied in nano-coating thickness analysis, nanomaterials composition analysis, trace impurity analysis and composition distribution analysis. In some recent research studies, mass spectrometry has also been used to analyze the number concentration, particle size and particle size distribution of nanoparticles, demonstrating its potential for particle size measurements in suspensions over a large size range. In this paper, the advances in studies on mass spectrometry in the analysis of the composition and particle size of nanomaterials were reviewed. The basic principles, advantages and disadvantages, range of application and application cases of inductively coupled plasma mass spectrometry, glow discharge mass spectrometry, secondary ion mass spectrometry and matrix-assisted laser desorption ionization mass spectrometry techniques applicable to the analysis of nanomaterials were introduced, demonstrating the potential of mass spectrometry in the characterization of nanomaterials. Finally, this paper summarized the challenges faced by mass spectrometry analysis technology in environmental interference, size characterization of particles with complex morphology, spatial resolution of components and insitu analysis. The strategies to overcome the above problems by designing special instruments for characterization of nanomaterials and combining with other separation and detection techniques were proposed, trying to provide some reference for the development of mass spectrometry characterization techniques of nanomaterials.

Sweet potato is a kind of low-calorie root food that has also been used for medicinal purpose. It is rich in a variety of essential nutrients and bioactive ingredients for the human body, and can be used to prevent various diseases. The quality of sweet potato directly affects its product quality, classification and quality grading and economic value. Rapid and efficient detection technologies play an important role in ensuring the quality and safety of sweet potato. Many studies on the rapid detection and analysis of sweet potato quality based on near-infrared spectroscopy (NIRS) have been reported. This paper comprehensively summarizes recent progress in the application of NIRS in the detection of the general chemical components (protein, starch, sugar, and water), active components (flavonoids and carotenoids), adulterants, heavy metals and microbial contamination in sweet potato as well as in its varietal identification. Moreover, this paper proposes future trends and research priorities for the application of NIRS in the quality detection of sweet potato. This review is expected to provide more references for further improvement of rapid quality assessment of sweet potato by NIRS and for the development of related fast testing equipment.

Helicobacter pylori is a type of bacteria that is commonly found in the stomach lining and is known to cause gastritis, gastric ulcers, and gastric cancer. Detection and diagnosis of Helicobacter pylori infection are crucial for effectively eradicating the pathogen. Currently, the 14C-urea breath test is widely considered the gold standard for detecting the infection. During the test, patients ingest capsules containing 14C-labeled urea. It is important to identify the active ingredient, 14C, in the 14C-urea capsules to ensure the quality and safety of the medication. Unfortunately, there is no clear method provided by the Chinese Pharmacopoeia or the United States Pharmacopoeia for identifying the 14C nuclide. To address this gap, a method for identifying the 14C nuclide in 14C-urea capsules using liquid scintillation counter measurement was developed in this paper. In the experiment, a solution of 14C-urea was mixed with ethanol and low-quenching scintillation cocktails, and then argon gas was used to remove oxygen and prepare a low-quenching sample. The liquid scintillation counter was used to measured the β spectrum, and five characteristic points were selected for comparison with the β spectrum of a standard non-quenched 14C source. The identified characteristic points included the maximum apparent energy value, the apparent energy value at the right end of the half-peak height, the apparent energy value at the right end of the 90% peak height, the 90% peak energy width, and half-height width. Successful identification of the 14C nuclides is achieved by comparing the β spectrum of the low-quenching sample with the standard non-quenched 14C source. Oxygen and ethanol are the main sources of quenching during the preparation of low-quenching samples. However, the experimental study shows that the dissolved oxygen in the scintillation cocktails could be effectively removed by flowing argon gas for 10 minutes, which significantly reduces the quenching degree and extends the validity period of the sample to 30 minutes. Furthermore, adding less than 1.67% ethanol to the sample results in no significant quenching. To avoid introducing new quenching sources, the distribution of 14C-urea in the capsule was analyzed, and it is found that more than 90% of the 14C-urea is located at the bottom of the capsule. The established nuclide identification method was used to identify 14C in three batches of 14C-urea capsules from a company in Shanghai, and the results are all qualified, validating the effectiveness and feasibility of the established method. In summary, the nuclide identification method developed in this paper can provide valuable experience for identifying nuclides in other radiopharmaceuticals, enhancing the safety and effectiveness of radiopharmaceuticals. Accurate identification of active ingredients in medications is essential for ensuring the safety of patients and improving the quality of healthcare.

The benchmarking critical experimental data can be used as a reference, providing basic data support for the macroscopic test of nuclear data, the design method verification of new nuclear energy system and the nuclear critical safety analysis, etc. As a crucial link in the process of benchmarking critical experimental data, the uncertainty analysis and evaluation of critical experimental data have been widely concerned and studied at home and abroad. Traditional GUM (Guide to the Uncertainty in Measurement) department based on the uncertainty analysis of the process “one change strategy at a time” uncertainty analysis method in calculation efficiency is low, cannot consider interval probability distribution characteristics of the input parameter error, defects of inaccurate results. In this paper, an uncertainty analysis method for critical experimental data was proposed based on perturbation theory and combination sampling method, and the probability distribution characteristics of input parameters in its error interval were restored by efficient Latin hypercube sampling method, so as to improve the accuracy and rationality of the uncertainty analysis of critical experimental data. By means of conjugate flux perturbation theory, the efficiency of critical experimental data uncertainty analysis was improved without significantly increasing the calculation time. Moreover, the efficient Latin hypercube sampling method and the conjugate flux perturbation method were verified and the feasibility of their application to the uncertainty analysis of critical experimental data was proved. Then, the Latin hypercube sampling program and complex modeling program were compiled, and the compiled program was verified and analyzed on the international critical safety benchmark question, and the calculation results obtained by the traditional critical experimental data uncertainty analysis method and the results given on the international critical safety benchmark question were compared. The conjugate flux perturbation uncertainty analysis method based on MCM (Monte Carlo method) analysis process improves the computational efficiency, makes the analysis results more reasonable and accurate, and proves that the uncertainty program is accurate and feasible for the uncertainty analysis of critical experimental data. Finally, the program was applied to the uncertainty analysis of critical experimental data of neutron toxicological effects in uranium solution obtained by China Institute of Atomic Energy, and a good result was obtained. Compared with the traditional critical experimental data uncertainty analysis method, the standard uncertainty of core characteristic value keff is improved, and the efficiency of uncertainty analysis is greatly improved. The uncertainty analysis method of critical experimental data studied in this paper and the program of uncertainty analysis can provide a more efficient and reasonable analysis method for benchmarking uncertainty analysis and multi-parameter sensitivity and uncertainty analysis of subsequent batches of critical experimental data.

Taking the release of radioactive aerosols in containment to the environment through cracks during nuclear power plant accidents as the research background, an experimental facility was established to study the deposition characteristics of aerosols in capillary tubes and the experiments were then conducted using the facility. The capillary tubes used in the experiments are PEEKsil tube. The gas flow inside the capillary was driven by pressure, with a maximum pressure difference of up to 500 kPa on both sides. The aerosol particles used in the experiments were titanium dioxide, with a mass median diameter of 1 mm. Organic filter membrane was used to collect the leaked aerosol, and then inductively coupled plasma-atomic emission spectrometry (ICP-AES) was adopted to obtain the titanium mass, which will be used to obtain the aerosol mass concentration at the capillary inlet and outlet. A methodology to calculate the aerosol deposition velocity based on the experimental data was developed in this paper, and then the relationship between dimensionless deposition velocity and relaxation time was built. It shows that the variation of dimensionless deposition velocity and relaxation time of aerosols in capillaries can be divided into rising zone and plateau zone, and the dimensionless relaxation time boundary between two regions is approximately between 70 and 100. In the rising zone, the dimensionless deposition velocity increases with the dimensionless relaxation time. In the platform zone, the dimensionless deposition velocity remains basically unchanged and is less than 0.03. Compared with the experimental results of aerosol deposition characteristics in conventional pipelines, the deposition velocity in this paper is relatively small. To analyze the deposition characteristics of aerosols in pipelines, numerical analysis has been conducted using the Lagrange method and the Eulerian method, among which the widely used Eulerian method is the three-layer deposition model. The model assumes that: 1) The particle flux across the boundary layer is steady and unidimensional, perpendicular to the surface; 2) The fluid is well mixed so that the particle concentration gradient exists only very close to the deposition surface; 3) There are no sources or sinks of particles within the boundary layer; and 4) The surface is a perfect sink for particles. To investigate the reasons for the smaller particle deposition velocity in the capillary tubes, this paper first restores the three-layer deposition model, which agrees well with the previous experimental results, and then adds Saffman force to the three-layer deposition model. In the modified three-layer deposition model, this paper introduces an average lag coefficient that reflects the difference in axial velocity between particles and fluid, and then evaluates the impact of lag coefficient on particle deposition velocity. The results show that when the lag coefficient increases to a certain value, the effect of Saffman force is significantly enhanced, and the dimensionless deposition velocity sharply decreases. In the experimental study on the deposition characteristics of aerosols in capillary tubes conducted in this paper, a compressible flow driven by high pressure difference is present in the capillaries. The airflow continuously accelerates in the flow direction, resulting in the acceleration of aerosol particles. The Saffman force always exists during the aerosol transportation in the capillary tubes. When the difference between particle velocity and gas flow rate reaches the certain value, the Saffman force greatly weakens the wall deposition of particles.

Surface wave exploration plays a vital role in obtaining target detection information by analyzing and retrieving the dispersion curve of surface waves. Although surface wave exploration technology originated in the 1960s, it has experienced significant advancements in recent decades and has found widespread applications in earthquake disaster and volcanic activity prediction, deep geological structure analysis, engineering construction, mining area and goaf assessment, subsidence area detection, and near-surface structure investigation, including celestial bodies such as stars. This paper aims to provide a comprehensive overview of surface wave exploration technology. It begins by discussing two types of data sources, namely active source and passive source, and proceeds to review the fundamental theory of surface wave exploration based on dispersion curve analysis and observations of horizontal and vertical amplitude ratios. This paper also provides a brief introduction to the surface wave inversion method. Additionally, it highlights the various application domains of surface wave exploration, outlines the current development trend, and presents future prospects for this technology.

[Introduction] With the emphasis and promotion of the electricity market system construction by the government, the electricity market is constantly growing towards a deeper and more unified direction. In order to promote the electricity market construction, the influence factors of the electricity market risk and its evaluation remain to be studied further. [Method] Based on the consideration of the whole cycle of electricity market trading, this paper took pre-trade risk, during-trade risk, and post-trade riskas the entry points, integrated the existing risks in each stage of electricity market, and established the risk evaluation index system for electricity market. Based on the thought of subjective and objective weighting, analytic hierarchy process (AHP) and entropy weight method were used to assign weights to the index system respectively, and fuzzy comprehensive evaluation (FCE) was adopted to evaluate the comprehensive risk level of the electricity market. [Result] The rationality, comprehensiveness and validity of the proposed model are verified through the analysis of the calculation examples of different electricity markets. [Conclusion] The model eatablished in this paper can conduct a comprehensive risk evaluation for the electricity market, and provide a theoretical reference for the construction of the risk system of the electricity market and its future development direction.

[Introduction] In order to change the current patrol inspection mode of power plant mainly based on manual patrol ins-pection, improve the intelligent level of power plant patrol inspection, and fully grasp the design method of robot autonomous patrol inspection system. [Method] This paper started from the design idea of the robot autonomous patrol inspection system, defined the system functions, and gave the design scheme of the patrol inspection system from the hardware architecture and software functions. Based on this design scheme, a 5G+ robot autonomous patrol inspection system integrating progressiveness and practicality was designed. In addition, in order to make the robot's patrol inspection results more intuitively reflect the actual operation of the power plant, this paper, based on intelligent image processing technology, completed the analysis and processing of instrument readings, valves, button switch status and other information. [Result] The 5G+ robot autonomous patrol inspection system can realize map construction, task deployment, autonomous navigation and execution of patrol inspection tasks, automatic identification of patrol inspection equipment, and use 5G to return patrol inspection data, complete the analysis of patrol inspection results and automatically generate patrol inspection reports. [Conclusion] The 5G+ robot autonomous patrol inspection system in intelligent power plant developed in this paper can significantly improve the patrol inspection efficiency, improve the intelligent level of power plant operation and maintenance, provide strong technical support for the independent patrol inspection operation of the power plant, provide reliable basis for professionals to comprehensively grasp the operation status of the boiler room, steam turbine room, booster station and auxiliary workshop, and ensure the safe operation of equipment in key areas while reducing personnel and increasing efficiency, better assist the construction of smart power plants.

[Introduction] Under the current situation of increasing automation level of distribution network, in order to solve the problem that the influence of distribution automation is not considered in traditional distribution network power supply reliability assessment methods, in this paper, a method for rapid assessment of power supply reliability of urban distribution network is proposed, which takes into account the automatic partitioning of distribution network. [Method] In this paper, based on the node division method of path characteristics, by demarcating automatic partitioning of distribution network, defining large and small segments, a method for evaluating the effect of power supply reliability improvement that was suitable for automatic partitioning of distribution network was proposed. [Result] Compared with the industry standard for reliability evaluation of medium-voltage distribution network, the proposed method fully considers the influence of distribution automation on reducing fault location, isolation and switching operation time, and the evaluation result is reduced by about 22%. [Conclusion] The proposed method can more accurately analyze the power supply reliability of the distribution network with a higher level of distribution automation, and is suitable for urban distribution network areas with a small power outage time base.

Single snapshot forward-looking imaging technology with high performance and resolution is crucial for enabling the development of automotive radars. However, range migration issues can limit the implementation of coherent integration methods, and improving system resolution is generally difficult due to hardware parameter limitations. Based on the Time-Division Multiplexing Multiple-Input-Multiple-Output (TDM-MIMO) forward-looking imaging systems of automotive millimeter wave radar, this paper proposes Doppler domain compensation and point-to-point echo correction measures for achieving multidomain signal decoupling. However, the accuracy of traditional single-dimension range and angle imaging is limited by the number of finite array elements and significant noise interference. Therefore, this paper proposes a multidomain joint estimation algorithm based on the Improved Bayesian Matching Pursuit (IBMP) method. The Bayesian method is based on the Bernoulli-Gaussian (BG) model, and the estimated parameters and support domain are iteratively updated in this method while adhering to the Maximum a Posteriori (MAP) criterion constraint to achieve the high-precision reconstruction of multidimensional joint signals. The final set of simulation and actual measurement results demonstrate that the proposed method can effectively solve the problem of range migration and improve the angle resolution of radar forward-looking imaging while exhibiting excellent noise robustness.

Vehicle targets in urban scenes have the characteristics of random distribution and can be easily disturbed by environmental factors during the detection process. Given the above issues, this paper proposes a detection method that utilizes multi-aspect Synthetic Aperture Radar (SAR) images for stationary vehicle target extraction. In the feature extraction stage, a novel feature extraction method called Multiscale Rotational Gabor Odd Filter-based Ratio Operator (MR-GOFRO) is designed for vehicle targets in multi-aspect SAR images, where the original GOFRO features are improved from four aspects—filter form, feature scale, feature direction and feature level. The improvement allows MR-GOFRO to adapt to possible variations in the target direction, scale, morphology, etc. In the image fusion stage, a Weighted-Non-negative Matrix Factorization (W-NMF) method is developed to adjust the feature weights from various images according to the feature quality. This method can reduce the quality degradation of the fusion features due to mutual interference between different aspects. The proposed method is verified on various airborne multi-aspect image datasets. The experimental results revealed that the feature extraction and feature fusion methods proposed in this paper enhance the detection accuracy by an average of 3.69% and 4.67%, respectively, compared with similar methods.

ObjectivesIn order to assess the vitality of shipborne equipment consists of important components of a warship system under the action of an anti-ship missile implosion load, this paper propose a response failure analysis method.MethodsThe shock response of a typical hull structure subjected to an internal explosion is numerically simulated, and the shock response spectrum is calculated to determine the impact environment of the location of the shipborne equipment. ResultsThrough the shock response spectrum of the typical position, the shock response parameters of shipborne equipment in different positions and at different installation frequencies are obtained, and a failure probability model is established through comparison with the shock design value, thereby forming a shock response failure analysis method for shipborne equipment. ConclusionsThe method proposed in this paper allows the calculation of the failure probability of typical shipborne equipment, and the results can provide references for the damage assessment and failure analysis of shipborne equipment under implosion load.

Nitrogen pressurization is widely used in nuclear reactor (such as passive nitrogen-type accumulators and nitrogen regulator) because of passive mechanism. However, nitrogen pressurization brings new challenges. Loss of coolant accident (LOCA) can lead to rapid reduction of pressure in primary circuit of pressurized water reactor (PWR), putting dissolved nitrogen in the water into a supersaturated state, which contributes to nitrogen release. In order to prevent the accumulation of released nitrogen, which may act as a threat to reactor safety, the migration and release characteristics of nitrogen were studied. In this paper, a nitrogen wall release model was established, the physical significance of the release source term was explained and the specific process of nitrogen release was revealed. In the case of LOCA in primary circuit of a PWR, the pressure in the primary circuit decreases and the susaturated dissolved nitrogen degas from the liquid and form nitrogen bubbles on nucleate sites. The susaturated dissolved nitrogen continuously degas at the gas-liquid interface of the bubble, leading to the sustained growth of nitrogen bubble. After reaching departure diameter, the buoyancy force on the nitrogen bubble is greater than surface tension and it escapes from the wall finally. In this paper, the mathematical modeling of nitrogen dissolution equilibrium, dissolved nitrogen convection and diffusion, the susaturated dissolved nitrogen wall release and nitrogen bubbles upward floating was carried out. Combined with the one-dimensional lumped parameter method, the mass conservation of the control volume was analyzed and the one-dimensional nitrogen mass conservation equation was deduced. To solve the one-dimensional nitrogen mass conservation equation, a one-dimensional lumped parameter nitrogen migration solution program was written based on MATLAB. The program was verified by the experimental data of small break loss of coolant accident (SBLOCA). The trends of dissolved nitrogen concentration and void fraction under pressure relief condition during SBLOCA were simulated. The results suggest that susaturated nitrogen degas on the wall in the form of bubbles. The bubble grows at a rate proportional to t1/2 and also proportional to (C-Ci)12. The influence of the initial nucleation radius on the growth period of the bubble is negligible and the bubble rises uniformly in the main stream after departure. Under pressure relief condition during LOCA, the nitrogen wall release effect is significant and the diffusion process of dissolved nitrogen is weak. Controlled by nitrogen wall release, the average concentration of dissolved nitrogen decreased by 19.5% and the void fraction became 4.33 times of the original, which indicates that wall release has significant effect on circuit, potentially affecting reactor safety. The simulation results are in good agreement with experimental data of SBLOCA, proving the reliability of wall release model and program.

Gamma-ray spectrometry uses the X-ray and characteristic gamma-rays associated with 235U, 238U and their decay daughters in uranium samples for analytical calculations to achieve rapid and timely nondestructive detection of sample enrichment. As one of the methods for determining uranium enrichment by gamma-ray spectrometry, the relative detection efficiency calibration method has been commonly used in nuclear safeguards on-site inspections to measure the enrichment of samples. Its core is the relative efficiency self-calibration using multiple characteristic gamma-rays of 235U in the low energy region of 120-186 keV and the characteristic gamma-rays of 238U decay daughter 234Pam in the high energy region of 258-1 001 keV. In this paper, the relative detection efficiency of the detector was obtained using the Monte Carlo method based on the actual characterization results of a coaxial-type high-purity germanium detector, the fitting results and errors of three different types of fitting formulas in different energy region ranges were investigated. A comprehensive analysis of the effect of the fitting formulas from the low-energy region to the medium-high energy region on the relative efficiency of the characteristic peaks shows the logarithmic transfer series function performs better results among the three fitting formulas. During the on-site inspection, the aluminum and stainless steel shieldings of the sample and the self-absorption of the uranium dioxide and uranium hexafluoride body source have a certain impact on the relative detection efficiency curve. The specific influence and changing trend of these factors on the curve were studied, and the fitted curves for thicker shields and strong self-absorption were then corrected by adding correction factors. The results show that after adding the correction factor, the fitting error of the relative detection efficiency curve for different shielding and self-absorption cases is reduced from 2%-4% to 1%-2% at the characteristic peaks used for enrichment calculation. The results of this paper have reference value for the nondestructive assay of uranium enrichment in the on-site inspection of nuclear safeguards.

The fully mechanized mining face adopting pre-driven recovery room is prone to large roof deformation at the final mining stage, which will lead to support crushing accidents. Based on the three main roof failure forms after longwall face entered recovery room, this paper established different mechanical models for roof sag of the recovery room. By analyzing energy release and work process in roof deformation, this paper obtained the immediate roof sag of recovery room under different main roof failure forms. Taking the large roof deformation and support crushing accident of recovery room in the N14201 longwall face of Zhangjiamao Coal Mine as example for analysis, this paper analyzed the influencing factors of the models and found that the main roof break position, the thickness of key block and its overlying strata, the rotation angle of key block and the supporting intensity have significant impact on the roof sag of recovery room. The research results confirmed that the reason for the support crushing accident in N14201 longwall face of Zhangjiamao Coal Mine: the main roof is broken within 4~6 m above the protective coal pillar, and the main key stratum is broken and unstable due to the mining of upper 3-1 coal seam.

High-voltage electric pulse(HVEP)drilling has become a new and efficient rock breaking method, which is also the research focus in the field of drilling speed increase. To probe into rock breaking mechanism of high voltage electric pulse, this study establishes a two-dimensional numerical model of multi-physical field coupling electric breakdown of single pair of electrodes. The model reproduces the generation of plasma channels in homogeneous red sandstone from the coupling of current field, electric breakdown field and circuit field. This paper analyzes the effect of electrode pair angle, voltage and electrode spacing on rock electrical breakdown(that is, the formation of plasma channel in rock). The model includes the circuit structure parameters of pulse tool, the occurrence and development of electrical breakdown, and the relationship between electrical breakdown intensity and time. Results indicate that the plasma channel begins to sprout from the partial area near the top of the discharge electrode and develops towards the partial weak dielectric strength. With the voltage value of loading pulse increasing gradually, the time of electrical breakdown decreases gradually; comparatively, the equivalent failure volume of rock model increases gradually, and there is a positive correlation between them. On the precondition that the rock can be electrically broken, increasing the electrode spacing can improve the rock breaking efficiency of high voltage electric pulse. The equivalent failure volume of rock shows significant fluctuations during the gradual increase of electrode inclination angle of discharge electrode, and its extreme value mostly appears in the range of electrode inclination angle of 35°~ 55°. To further promote the industrial application of high-voltage electric pulse rock breaking, this paper proposes a three-dimensional numerical model of multi-physical field coupling dynamic electric breakdown of red sandstone based on two-dimensional model, reproducing the appearance of the fracture crater in the rock during the rock breaking process with electrode bit. At the same time, the self-designed coaxial electrode bit is selected for experiments of electric breakdown, and the laboratory experimental results of electric breakdown confirm the simulation experimental results.

SignificanceOil crops play a significant role in the food supply, as well as the important source of edible vegetable oils and plant proteins. Real-time, dynamic and large-scale monitoring of oil crop growth is essential in guiding agricultural production, stabilizing markets, and maintaining health. Previous studies have made a considerable progress in the yield simulation of staple crops in regional scale based on remote sensing methods, but the yield simulation of oil crops in regional scale is still poor as its complexity of the plant traits and structural characteristics. Therefore, it is urgently needed to study regional oil crop yield estimation based on remote sensing technology.ProgressThis paper summarized the content of remote sensing technology in oil crop monitoring from three aspects: backgrounds, progressions, opportunities and challenges. Firstly, significances and advantages of using remote sensing technology to estimate the of oil crops have been expounded. It is pointed out that both parameter inversion and crop area monitoring were the vital components of yield estimation. Secondly, the current situation of oil crop monitoring was summarized based on remote sensing technology from three aspects of remote sensing parameter inversion, crop area monitoring and yield estimation. For parameter inversion, it is specified that optical remote sensors were used more than other sensors in oil crops inversion in previous studies. Then, advantages and disadvantages of the empirical model and physical model inversion methods were analyzed. In addition, advantages and disadvantages of optical and microwave data were further illustrated from the aspect of oil crops structure and traits characteristics. At last, optimal choice on the data and methods were given in oil crop parameter inversion. For crop area monitoring, this paper mainly elaborated from two parts of optical and microwave remote sensing data. Combined with the structure of oil crops and the characteristics of planting areas, the researches on area monitoring of oil crops based on different types of remote sensing data sources were reviewed, including the advantages and limitations of different data sources in area monitoring. Then, two yield estimation methods were introduced: remote sensing yield estimation and data assimilation yield estimation. The phenological period of oil crop yield estimation, remote sensing data source and modeling method were summarized. Next, data assimilation technology was introduced, and it was proposed that data assimilation technology has great potential in oil crop yield estimation, and the assimilation research of oil crops was expounded from the aspects of assimilation method and grid selection. All of them indicate that data assimilation technology could improve the accuracy of regional yield estimation of oil crops. Thirdly, this paper pointed out the opportunities of remote sensing technology in oil crop monitoring, put forward some problems and challenges in crop feature selection, spatial scale determination and remote sensing data source selection of oil crop yield, and forecasted the development trend of oil crop yield estimation research in the future.Conclusions and ProspectsThe paper puts forward the following suggestions for the three aspects: (1) Regarding crop feature selection, when estimating yields for oil crops such as rapeseed and soybeans, which have active photosynthesis in siliques or pods, relying solely on canopy leaf area index (LAI) as the assimilation state variable for crop yield estimation may result in significant underestimation of yields, thereby impacting the accuracy of regional crop yield simulation. Therefore, it is necessary to consider the crop plant characteristics and the agronomic mechanism of yield formation through siliques or pods when estimating yields for oil crops. (2) In determining the spatial scale, some oil crops are distributed in hilly and mountainous areas with mixed land cover. Using regularized yield simulation grids may result in the confusion of numerous background objects, introducing additional errors and affecting the assimilation accuracy of yield estimation. This poses a challenge to yield estimation research. Thus, it is necessary to choose appropriate methods to divide irregular unit grids and determine the optimal scale for yield estimation, thereby improving the accuracy of yield estimation. (3) In terms of remote sensing data selection, the monitoring of oil crops can be influenced by crop structure and meteorological conditions. Depending solely on spectral data monitoring may have a certain impact on yield estimation results. It is important to incorporate radar off-nadir remote sensing measurement techniques to perceive the response relationship between crop leaves and siliques or pods and remote sensing data parameters. This can bridge the gap between crop characteristics and remote sensing information for crop yield simulation. This paper can serve as a valuable reference and stimulus for further research on regional yield estimation and growth monitoring of oil crops. It supplements existing knowledge and provides insightful considerations for enhancing the accuracy and efficiency of oil crop production monitoring and management.

Cultural inheritance is the spiritual genealogy and life source to sustainable development for a journal. This paper took Science and Technology of Cereals, Oils and Foods (in brief “this journal”) as an example to review. The period of this journal has been divided into four stages, including the gestation period from 1991 to 1992, the early and long-term from1993 to 1996, the mature period from 1997 to 2018, and the new development period from 2019 to the present, in order to review its important performance, growth and progress in the changes of social times and the reform of Chinese scientific research system over more than 30 years. By sorting out the development history and the operating experience, the phased achievements and substantial progress in terms of operating characteristics were summarized. The historical contribution, hard work and harvest have also condensed. It could lay an important cornerstone for the journal to continue to carry forward the fine tradition and promote the construction of brand culture. This paper could also promote the journal development to a new level, and provide reference for peer journals to sort out their historical developments.

A gold@platinum (Au@Pt) nanozyme-based test strip for the convenient and sensitive detection of hydrogen peroxide residues in foods was developed using Whatman No.1 filter paper as the carrier, Au@Pt nanozyme as the catalyst, 3,3’,5,5’-tetramethylbenzidine as the color developer, and acetic acid-sodium acetate solution at pH 4.6 as the buffer system. The optimized test strip soaking time was 10 s. The test paper could detect hydrogen peroxide in samples within 3 min with a minimum detection limit of 0.34 mg/kg and a good linearity (R2 = 0.993 1). The test paper is easy to make, highly accurate, stable and simple to operate, and can be used in the real-time on-site detection of food products in various distribution channels.

Green ecological control of stored grain pests is one of the important tasks to promote green grain storage. Predator mite control of stored grain pests is a biological control technology that employs ecological factors to suppress the population of stored grain pests. Cheyletus malaccensis control the pest populations by feeding on the eggs and larvae of insect pests and mites. As Cheyletus malaccensis is the dominant predatory mites in Chinese grain warehouse, it has several advantages, including wide distribution, large quantity, significant quantities, a broad predation spectrum, and high predation levels. This paper briefly described the control technique for stored grain pests by C. malaccensis and the advantages of control by C. malaccensis based on our team's researches in recent years. In addition, low-cost and convenient artificial propagation and release technologies have been developed. These methods are non-polluting, residue-free and are effective in preventing resistance within warehouse applications. This paper provides guidance for the green, ecological and safe stored grain pests comprehensive control and for reduced application of chemical pesticides.

The shortage of high-quality protein feed resources has become an important variable affecting food security in China. Grain and oil processing by-products are abundant in China, but the feeding value is low. If these resources are processed through modern biotechnology, such as biofermentation, enzymolysis technology or synthetic biology, their quality and efficiency will be improved and can be used to replace the soybean meal. This paper summarized the production process, feed value and its application in soybean meal replacement of fermented feed, enzymolysis feed and microbial protein feed, and also introduced the research progress of microbial adsorption, degradation, or enzymes on removing mycotoxins, finally put forward the research prospect of development, industrialization application, standard establishment, and industry supervision for biological fermentation feed. This paper can provide guidance for the application of biotechnology in grain and oil feed resources.

BackgroundImmigrant health is an key node in achieving the goal of universal health coverage proposed by 2030 Agenda for Sustainable Development. The shock of severe public health emergency may exacerbate the original health-related contradictions of this group and bring more negative health effects. ObjectiveTo identify academic research hotspots and directions of immigrant health, and to examine trends in research hotspots before and after the public health emergency, so as to provide references to study immigrant health and response to public health emergency in the future. MethodsArticles (document type) included in Web of Science core collection from 2017-01-01 to 2022-12-31 were retrieved. Microsoft Excel 2019 was used for descriptive analysis of included papers. VOSviewer 1.6.19 and CiteSpace 6.1.R6 were combined to draw cooperation maps of authors, institutions, and countries/areas to understand their cooperation and communication, and to draw keywords co-occurrence map, keywords clusters map, and keywords burst map to examine the hotspots and trends of immigrant health research before and after public health emergency. ResultsA total of 5997 papers pertaining to immigrant health from 2017 to 2022 were included, and the number of publications every year were overall on the rise generating a group of productive core authors. Institutions from the United States, Canada, and Northern Europe not only tightly cooperated within their countries/areas, but also cooperated frequently among countries/areas, forming an international cooperation network with the United States as its core. The keywords co-occurrence map showed that from 2017 to 2022, the research hotspots of immigrant health mainly focused on target groups of women, children, and refugees, and the study topics of mental health, acculturation, and care. The results of cluster analysis and further extraction found that the research topics in this field were divided into five categories: maternal and child health care, acculturation and mental health, health services, health equity, and chronic disease. The keywords burst map revealed that the research hotspots shifted from ethnic group, risk behavior, and sexes to COVID-19, health equity, social isolation, and victimization under the impact of public health emergency. ConclusionThe cooperation and communication among study teams, institutions, and countries/areas have promoted the development of immigrant health study. Public health emergency has exacerbated the existing vulnerability of immigrants, and the topics related to health equity and social isolation of immigrants have raised attention becoming the research forefront. It is suggested that under the impact of public health emergency, corresponding public health policies are needed to mitigate health inequities and social support is also required for immigrants to ensure their physical and mental health.

This paper presents a cold-end optimization design study of a nuclear energy power conversion system in the context of low-temperature heat sink applications. Based on the principles of simple recuperation cycles and recompression cycles, the study focuses on the supercritical carbon dioxide power cycle and its cold-end optimization for application in low-temperature heat sink environments. These strategies are designed to enhance the efficiency and reduce the operating pressure of the supercritical carbon dioxide power cycle under low-temperature heat sink conditions. Three different cold-end optimization approaches were proposed, which include: a non-condensing liquid-phase compressed supercritical carbon dioxide power cycle, a condensing liquid-phase compressed supercritical carbon dioxide power cycle, and a gas-phase compressed supercritical carbon dioxide power cycle. This research established a thermodynamic analysis program, which modeled turbine machinery such as compressors and expanders using isentropic models. Heat exchangers such as recuperations and coolers were simplified and modeled, with pressure drops and end temperature differences assumed. The study’s thermodynamic analysis program was compared with computational results from a Sandia National Laboratories research report, confirming the accuracy of the thermodynamic analysis methodology presented in this paper. For a 100 MW scale power generation unit, the thermodynamic analysis program was used to conduct computational analyses on both simple recuperation cycles and recompression cycles. These cycles were driven by a medium-to-high-temperature reactor heat source with a turbine inlet temperature of 550 ℃, and a medium-to-low-temperature reactor heat source with a turbine inlet temperature of 315 ℃. The study reveals that the optimal cold-end optimization approach varies based on the heat source temperature and cycle configuration. For the medium-to-high-temperature reactor heat source, the gasphase compressed supercritical carbon dioxide power cycle in the simple recuperation cycle configuration achieves the highest efficiency at 39%. In the recompression cycle configuration, the condensing supercritical carbon dioxide power cycle achieves the highest efficiency at 48%. For the medium-to-low-temperature reactor heat source, regardless of the cycle type, the condensing supercritical carbon dioxide power cycle yields the highest efficiency, the highest efficiency is 28% for the simple recuperation cycle and 33% for the recompression cycle. When comparing the cold-end optimized supercritical carbon dioxide power cycle to conventional supercritical carbon dioxide power cycles with the same maximum temperature and pressure, the optimized system exhibits a reduction in operating pressure drop and an efficiency improvement of 2% to 4%. The cold-end optimized configurations of the supercritical carbon dioxide power cycle hold promising applications for nuclear energy power conversion systems with low-temperature heat sink environments.

In order to realize the power supply of small nuclear reactors in remote areas, the sub-channel analysis program BRESA of supercritical carbon dioxide (S-CO2) fuel assembly based on Modelica language was developed in this paper. According to the fuel assembly model of 37 rods, the axial and radial physical and thermal parameters of S-CO2 fuel assembly were calculated, and the flow mixing effect between channels was introduced to obtain the distribution law of thermal hydraulics parameters in the axial and radial directions, The enthalpy rise and temperature rise changes of various typical channels were studied. The results show that the enthalpy rise and temperature rise changes of the channel in the middle of the fuel assembly are high, while the enthalpy rise and temperature rise changes of the channel at the edge of the fuel assembly are low. Through comparison with relevant literature, it is proved that the thermal hydraulic parameters of this study meet the design requirements and the correctness of the program is verified. On the basis of steady-state calculations, the transient conditions of flow rate changes were analyzed, and the response characteristics of various parameters of fuel assemblies under transient conditions of linear increase, linear decrease, and sudden change in flow rate were analyzed. The response characteristics of reactor power response and control system were investigated and analyzed, and the spatial variation trends of enthalpy and pressure with time were obtained. The results indicate that under transient conditions, the reactor power will vary with flow fluctuations, which is related to the negative feedback effect of the control system and temperature. The pressure and enthalpy values also fluctuate and change when the flow rate changes, which is influenced by the dual effects of flow rate and power changes. Under transient conditions of sudden flow changes, enthalpy and pressure undergo sudden and significant fluctuations, with the maximum fluctuation of outlet enthalpy reaching 12%, posing a challenge to the safe operation of the reactor. The research results of this paper provide theoretical support and technical guidance for the design and research of supercritical carbon dioxide reactor systems.