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Organ transplantation is the most effective treatment for end-stage organ failure. However, donor shortage leads to many patients dying while waiting for transplants. With breakthroughs in basic research,advancements in gene editing technologies,and developments of new immunosuppressive drugs,xenotransplantation is regarded as the most promising solution to address the organ shortage crisis. In recent years, researchers both domestically and internationally have conducted multiple studies on non-human primates (NHPs), brain-dead donors,and patients with end-stage heart failure, end-stage renal disease, and advanced liver cancer. Nevertheless, challenges such as immune rejection and coagulation dysfunction continue to limit recipient survival, hindering significant breakthroughs in the clinical application of xenotransplantation. This review summarizes the latest developments in xenotransplantation research globally, with a focus on immune rejection and coagulation dysfunction following liver xenotransplantation.

The establishment and maintenance of a design assurance system（DAS）by the type certificate applicant is part of the requirements of CAAC airworthiness regulations, which has legal effect. Due to the late start of China's civil aviation industry, there is limited experience accumulated in the construction and review of DAS, and the Advisory Circular related to design assurance systems has not yet been formed. The authorities and industry lack effective technical guidance in reviewing and demonstrating compliance. By studying the requirements of domestic and foreign airworthiness authorities on design institutions, the core contents and relationship of the DAS three major functions are identified, the main architecture of DAS manual is proposed. 11 modules and 28 elements of DAS review and the corresponding review points are analyzed, and a review idea based on modularity and a review mode based on process intervention are proposed, which can help authorities and industry better carry out the construction and review of DAS.

ObjectiveThis study analyzes the omics data resources in human-infecting coronavirus animal models collected from various public databases, focusing on data distribution, dataset quantity, data types, species, strains, and research content. It aims to enhance our understanding of biological characteristics and pathogenic mechanisms of coronaviruses, thereby providing a solid foundation for devising effective therapeutic strategies and preventive measures.Methods Query strategies, including specific virus names, time ranges, and inclusion and exclusion criteria, were defined to retrieve data from major public omics databases such as GEO and ArrayExpress. Secondary filtering was performed based on different field types to obtain a more accurate data list. An omics data text database was established for bibliometric analysis. Co-occurrence networks were constructed for the analysis of the correlation strengths between different research themes, technical methods, and involved species. The cell types, organs, and biological pathways involved in studies were examined to further elucidate the pathogenic interplay between pathogens and hosts. Results About twenty public databases containing coronavirus-related omics data were identified, with a primary focus on novel coronavirus infection. Commonly used species include humans, mice, hamsters, and monkeys, while the commonly used virus strains are Wuhan-Hu-1 and USA-WA1/2020. Lung tissues are primarily used in animal models such as mice, macaques, and ferrets, while airway epithelial cells and Calu-3 cells are predominantly employed in human-related studies. Expression profiling data indicate that gene pathways involved in inflammation, cytokine response, complement pathway, cell damage, proliferation, and differentiation are significantly upregulated after infection. Proteomics studies reveal significant changes in phosphoproteome, ubiquitinome, and total proteome of patient samples at different infection stages. Specific protein categories, including viral receptors and proteases, transcription factors, cytokines, proteins associated with coagulation system, angiogenesis-related proteins, and fibrosis markers, show alterations after coronavirus infection. In addition, metabolomics data suggest that phosphocholine, phosphoethanolamine, arachidonic acid, and oleic acid could serve as potential metabolic markers. Epigenomics research indicates m6A methylation plays a role in SARS-CoV-2 replication, infection, and transmission, affecting host cell-virus interactions. Among these, N, S, and non-structural proteins 2 and 3 exhibit the most significant ubiquitination. Trends in microbiomics research suggest that microbial communities in the gut and wastewater are emerging as new research focuses. Conclusion The data types of coronavirus omics are diverse, with a wide variety of models and cell types used. The selection of species and technical methods for modelling varies based on the characteristics of different viruses. Multi-omics data from animal models of coronavirus infection can reveal key interactions between hosts and pathogens, identifying biomarkers and potential therapeutic targets, and provide valuable information for a deeper understanding of biological characteristics and infection mechanisms of coronaviruses.

Objective In order to improve train operational efficiency, it is necessary to monitor metro traction power consumption and establish a relevant energy consumption model for prediction analysis of metro traction power consumption. Method The basic principles of grey prediction model and BP (backpropagation) neural network are introduced. Taking the traction daily electricity consumption data for a typical metro station in Tianjin in June 2021 as example, the grey correlation analysis method is used to select the influencing factors with high correlation to the daily traction power consumption of metro. Based on the GM (1,1) grey prediction model, the short-term traction daily power consumption is predicted. The selected influencing factors with high correlation, the short-term traction daily power consumption predicted by GM (1,1) grey model, and the adjacent historical traction daily power consumption data are used as input for training in BP neural network model to establish the GM-BP grey neural network model. The required short-term metro traction daily power consumption prediction data is generated. Result & Conclusion Compared with conventional GM (1,1) grey prediction model and BP neural network model, the prediction error of short-term traction daily power consumption predicted by the GM-BP grey neural network model shows significant improvement, and can be used as effective metro traction power consumption data for short-term prediction data analysis.

An effective method for the internal interaction within modeling reality systems is provided by graphs; however, they have been unable to effectively display and capture the high-order heterogeneity that widely exists between multiple entities. Hypergraphs have been recognized for their ability to surpass the limitations imposed by low-order relationships. Hypernetwork link prediction, which involves predicting unknown hyperlinks based on the observed hypergraph structure, has increasingly become a hot topic in network science due to its capacity to fully describe the association patterns of complex systems. Existing methods typically design reasoning models for the entire topology, often overlooking the implicit aggregation characteristics within the network, which leads to an incomplete prediction of hyperlink categories. To address these issues, a coordination matrix minimization model based on hypergraph spectral clustering parser (SCL-CMM) was proposed. Initially, higher-order hypernetworks were mapped into heterogeneous hypergraphs with certain semantics. Subsequently, the spectral clustering parser was employed to extract the structural features of hyperlinks. The original hypergraph was reconstructed into multiple homoprotonic graphs, and the distribution of potential hyperlinks was inferred within the observation space of the subgraph, rather than the entire adjacency space, in order to restore the complete hypernetwork structure. This method federated learned the structural characteristics and aggregation attributes of hypernetworks to model the high-order nonlinear behavior of each subgraph, thereby solving the problems of single category and low precision in heterogeneous hypergraphs link prediction. Extensive comparative experiments were conducted on nine real datasets, demonstrating that this method significantly outperformed existing methods in terms of AUC score and recall rate.

Lithium-ion capacitors （LICs） are novel power energy storage devices， which have the advantages of both lithium-ion batteries and electric double-layer capacitors. However， the slow electrochemical dynamics of the battery-type anode limits the application of LICs. Metal selenides have attracted much attention because of their excellent conductivity， rapid reaction kinetics and high theoretical capacity. In this paper， the classification， structure and properties of metal selenides are systematically introduced， and three energy storage mechanisms of intercalation mechanism， conversion mechanism and alloying mechanism are discussed.Finally， the impacts of structural regulation， carbon material synergy， and bimetallic selenide construction on the electrochemical performance are analyzed. The application of metal selenide materials with structurally stable and high ion/electron transport capability prepared by the three modification methods is introduced in lithium-ion capacitors.

Objective The existing target speed planning algorithm for the automatic driving of urban rail transit train cannot handle in real time the temporary change of the line speed limit in case of emergency due to the large computational load and long computation time. With regard to the problem, a real-time target speed planning algorithm based on global optimization is proposed to generate the speed planning curve in real time. Method Based on the conditions of train current position, current speed and speed limit of the forward line, the speed planning curve is firstly generated in the shortest time through point by point calculation. Then the traction and braking levels are being adjusted to keep the train running at uniform acceleration or deceleration, optimizing the comfort index of the train running. Next, the cruising speed in the maximum speed limit section is adjusted to reduce unnecessary traction and braking time, optimizing the energy consumption index of the train running. Finally, the train speed planning curve is output. Result & Conclusion The simulation results show that the real-time speed planning curve generated by the proposed algorithm satisfies the basic constraints of safety, punctuality and accurate parking. Compared with the traditional algorithm, it improves the comfort level and reduces the energy consumption during train operation. Meanwhile, the proposed algorithm can effectively handle the temporary change of the line speed limit in emergency and optimize several operation indicators.

[ Objective ] The front piedmont belt of the northern slope of the Tianshan Mountains in Xinjiang is a crucial component of the mountain-oasis-desert ecosystem of the Tianshan northern slope. Investiga- ting the dynamic physiological adaptations of plants to drought stress and assessing methods for drought resistance , as well as selecting suitable tree species for vegetation restoration holds significant importance for the ecological restoration in this region. [ Methods ] 12 plant species planted in the piedmont belt of the northern slope of the Tianshan Mountains in Xinjiang were selected as the subjects. The study observed the spatiotemporal distribution of soil moisture following irrigation and analyzed the impact of drought stress and rewatering treatment on plant photosynthetic and physiological indicators. The drought resist- ance of these 12 species was evaluated using principal component analysis. [ Results ] ( 1 ) Following drought stress , soil moisture depletion occurred most rapidly in the 0-20 cm layer , followed by the 20- 40 cm layer , and was slowest in the 40-60 cm layer. Different plants employed different strategies to adapt their growth to drought stress. ( 2 ) Following drought stress , net photosynthetic rate ( P n ), stoma- tal conductance ( G s ), transpiration rate ( T r ), intercellular CO 2 concentration ( C i ), potential activity of PSⅡ ( F v / F o ), maximum photochemical efficiency of PSⅡ ( F v / F m ), electron transport rate ( ETR ), and chlorophyll content were decreased , while the activity of superoxide dismutase ( SOD ), proline content , malondialdehyde ( MDA ) content , and non-photochemical quenching coefficient ( q N ) were increased. Af- ter rehydration , there was a certain degree of recovery in each parameter , but none of them reached the in- itial levels. ( 3 ) The results of principal component analysis highlighted that factors like P n , chlorophyll content , ETR , and MDA content were major contributors. Species such as Haloxylon ammodendron , Tamarix chinensis , Rosa acicularis , and Caragana korshinskii demonstrated significant drought resili- ence. Hippophae rhamnoides , H . rhamnoides ‘ Xinji 5 ’, H . rhamnoides ‘ Xinji 1 ’, and Prunus sibirica showed moderate levels of drought resistance , while H . rhamnoides ‘ Xinji 4 ’, H . rhamnoides ‘ Xinji 3 ’, Xanthoceras sorbifolium , and H . rhamnoides ‘ Xinji 2 ’ exhibited relatively lower drought tolerance. [ Conclusion ] P n , chlorophyll content , ETR , and MDA content were crucial indicators for evaluating the adaptability of various plant species to drought stress. In the context of ecological restoration efforts in the piedmont belt of the Tianshan Mountains􀆴 northern slope in Xinjiang , prioritizing the cultivation of H . ammodendron , T . chinensis , R . acicularis , and C . korshinskii were recommended.

[Objective] In order to investigate the seasonal changes of base ions and available silicon and aluminum contents of black soil in northeast China under the change of snow depth in winter. [Methods] The environmental factors (temperature and humidity, moisture content, pH, total organic carbon), base ions, available silicon and activated aluminum of black soil in northeast China farmland were measured in snow removal group (SR), snow reduction group (SL), natural snow control group (C) and snow enhancement group (SA) were determined by artificial control of snow depth. The change process of the content of base ions and available silicon and aluminum in soil and their response to soil environmental factors were analyzed. [Results] The decrease of snow depth weakened the heat preservation effect of snow on black soil under seasonal snow cover, and the temperature and humidity (unfrozen water content) of 0—30 cm soil decreased significantly, which reduced the HCO3- content carried by unfrozen water during water and salt migration. The average pH of the soil was affected by the HCO3- content by the changes of -0.06, -0.04, - 0.02, and 0.01, respectively. With the decrease of soil alkalinity, the substitution ability of low-priced cations to high-priced cations in soil colloidal adsorption potential was enhanced, which increased the contents of exchange monvalent cations (Na+, K+), and decreased the contents of exchange and carbonate bivalent cations (Ca2+, Mg2+). Carbonate bivalent cation and exchange Na+ had positive and negative effects on TOC content, respectively, and the mean total organic carbon (TOC) content increased by 0.87, 1.09, 1.32 and 1.48 g/kg with the decrease of snow depth, respectively. The interaction between base ions and soil pH and TOC resulted in the decrease of soil pH and TOC content under the condition of reduced snow depth, which had an indirect effect on soil available silicon and aluminum content. The decrease of TOC content weakened the soil retention of low-active aluminum humate (Al-HA), and the decrease of pH promoted the conversion of low-active aluminum to high-active exchange aluminum (Ex-Al) and monomer hydroxyl aluminum (Hy-Al), which increased the soil aluminum toxicity, and promoted the dissolution of available silicon, resulting in the loss of soil silicon. [Conclusion] The reduction of seasonal snow cover in the middle and high latitudes caused by climate warming will affect the material and energy distribution of the black soil in Northeast China in winter, and thus change the growth and development environment of crops in the growing season. This study provided a certain scientific basis to reveal the seasonal variation process of soil mineral elements in the black soil region in Northeast China in winter.

ObjectiveTo investigate the noise level and influencing factors in metro platforms and station halls， thereby providing the scientific basis for the establishment of hygienic standards.MethodsDuring the morning peak（7：00‒9：30）and off-peak （9：30‒17：00） on weekdays， the noise levels were measured with noise meters at 39 monitoring points of 13 station platforms and 31 monitoring points of 6 station halls. The monitoring points arrangement and detection methods referred to the Examination methods for public places—Part 1： physical parameters（GB/T 18204.1‒2013）.ResultsThe measured noise level in the station ranged from 69.25 to 86.17 dB（A）， accounting for 44.74% below 75 dB（A）， 89.47% below 80 dB（A） and 97.37% below 85 dB（A）.The noise level of the platform ［（76.38±4.19） dB（A）］ was higher than that of the station hall ［（74.24±4.50） dB（A）］（P0.05）.ConclusionThe noise level in metro stations in the city does not fully meet the requirements of current relevant standards. It is suggested to take noise reduction measures to reduce the noise of metro stations.

Background At present, there has been a dramatic increase in the number of obese children and adolescents globally, among which the prevalence of obesity in children aged 5 to 19 years has increased by about 8 times, and the prevalence of obesity in children aged 2 to 4 years has increased by about 1 times. Exercise intervention has an important effect on improving obesity and enhancing cardiorespiratory fitness. However, studies on the effects of combined motion intervention on obese female adolescents aged 14-16 years have not been addressed. Objective To investigate the effects of 12-week combined motion intervention on body composition, cardiovascular risk factors and cardiopulmonary fitness in obese female adolescents. Methods From May to July 2022, 48 obese female adolescents aged 14 to 16 years old in Qufu City, Shandong Province were selected as research objects, numbered and divided into the experimental group (n=24) and control group (n=24) using random numbers. The experimental group finally included 20 female adolescents based on the inclusion and exclusion criteria, and the whole intervention lasted for 12 weeks, including rope skipping intervention and taekwondo intervention; while the control group did not perform any exercise intervention and other dietary or pharmacological interventions throughout the 12 weeks. The indicators such as height, body mass, body fat rate (BFR) , waist circumference, BMI, blood pressure (BP) , fasting plasma glucose (FPG) , insulin, insulin resistance index (HOMA-IR) and maximal oxygen uptake (VO2max) were detected before and after the 12-week combined motion intervention and compared between the two groups, as well as before and after the intervention. Pearson correlation analysis was used to explore the correlation of BFR and waist circumference with VO2max in obese female adolescents. Results Before the intervention, there was no significant difference in age, height, body mass, BFR, waist circumference, BMI, systolic blood pressure (SBP) , diastolic blood pressure (DBP) , pulse pressure difference, FPG, insulin, HOMA-IR, maximal number of completions (Laps) , maximal aerobic speed (MAS) , and VO2max between the two groups (P>0.05) . After 12-week combined motion intervention, BFR, waist circumference, SBP, DBP, FPG, insulin and HOMA-IR in the experimental group were lower than the control group, while Laps, MAS, VO2max was significantly higher than the control group (P

The protection of historical and cultural heritage sites is the main focus of land space planning and use control. Its protection and utilization are important for promoting the revitalization of rural culture and building a pattern of historical and cultural protection, and are essential for the research on comprehensive land consolidation in recent years. The historical trail of South China is a linear cultural heritage site of Guangdong's historical development. Exploring the connotative relationship between comprehensive land consolidation and the protection and utilization of linear cultural heritage is conducive to enhancing their synergy and superposition. This study begins with a connotation analysis and trend analysis of comprehensive land consolidation and linear cultural heritage protection and utilization, taking the connecting line of the Gutian section of the ancient Meiguan historical trail of the Southern China historical trail in Guangdong Province as an example to explore the working relationship between comprehensive land consolidation and the protection and utilization of linear cultural heritage. It proposes a comprehensive land consolidation path for linear cultural heritage protection and utilization. Results showed that: 1) The problems faced by the protection of historical trails were closely related to the goal and content of comprehensive land consolidation; 2) The protection of historical trails and the comprehensive land consolidation could be integrated into the implementation of land space planning, rights and interests protection, policy incentives, public participation and landscape coordination to jointly promote the enhancement of land space value; 3) Focusing on the dimensions of development orientation, planning layout, engineering design, overall planning funds and service operation, it is necessary to constantly innovate the path of comprehensive land improvement across the region, and comprehensively promote the protection and utilization of rural cultural heritage. Guangdong Province can fully utilize the platform tools of comprehensive land consolidation in the protection of South China historical trail, achieve the connection and integration of ancient cultural protection and utilization with land consolidation projects, and establish a mutual feedback relationship in work, innovate and establish a working mechanism for the integration and development of comprehensive land consolidation and historical trail protection, which is conducive to the synergistic effect of rural revitalization and historical and cultural protection, better service and support for rural revitalization and high-quality development.

This paper aims to address the limitations in existing research on the evolution of knowledge flow networks by proposing a meso-level institutional field knowledge flow network evolution model (IKM). The purpose is to simulate the construction process of a knowledge flow network using knowledge organizations as units and to investigate its effectiveness in replicating institutional field knowledge flow networks.

DC contactor is one of the most widely configured switching appliances in new energy systems and electric vehicles. The dynamic characteristic of DC contactor is one of the important indexes to measure the performance of DC contactor. A dynamic model of the electromagnetic mechanism of DC contactor with parallel double coil type is established in this paper. Dynamical model of the electromagnetic mechanism of DC contactor is simulated. The closing process simulation analyzed of the electromagnetic mechanism of DC contactor by using the co-simulation research method based on Adams and Maxwell. The research results show that the simulation closing time of the closing action the mechanism is consistent with the test closing time. The correctness of the simulation method is verified. At the same time, the influence of spring parameters, coil parameters and other factors on the closing motion characteristics of the mechanism is studied. The change of spring pre-pressure has little influence on the closing time within a certain range. The increase of coil ampere turns will lead to the decrease of closing time, the increase of coil internal resistance will lead to the increase of closing time and the more severe bouncing of moving contact. The simulation method and results can provide some reference for the improvement design and optimization of DC contactor electromagnetic mechanism.

Borane is a class of boron compounds, including active small borane molecules and relative stable polyhedral borane compounds, and has widely applied in energy storage, material science, and pharmaceutical medicine, especially as promising boron carriers for boron neutron capture therapy(BNCT), and many other fields. The synthesis of new borane molecules and optimization of the synthetic methods of boranes have been a significant part of boron chemistry over the last one hundred years. Herein, we have systematically summarized the syntheses of small borane molecules, polyhedral boranes, and carboranes; we also provided the molecular structures and 11B NMR spectra of borane compounds. Anticipatedly, this review will provide the basic knowledge for readers interested in borane chemistry and facilitate the readers for improving the synthetic methods of boranes and exploring the application of borane compounds.

One of the most cost-effective designs for the maneuvering reentry vehicle is a simple lifting configuration with a fixed angle of attack employing a single roll control system. However, the limited maneuverability due to its uncontrollable magnitude of lifting force leads to the major obstacle to achieve the accurate steering with multiple constraints, so seeking a suitable guidance method is the key to overcome this obstacle. Existing ways are not available to solve this problem. This paper presents a new guidance method, which combined with the Gauss pseudospectral method (GPM) to satisfy the constraints, and the rolling guidance law to track the optimized trajectory accurately. The simulation result illustrates that, this method is effective to realize the precision guidance with multiple constraints for fixed-trim reentry vehicle.

The study of carbon economics theory and its evolutionary laws in the context of carbon peaking and carbon neutrality is crucial for advancing global carbon emission reduction efforts and understanding the interaction between carbon markets and complex socioeconomic systems. Carbon markets play a significant role in reducing greenhouse gas emissions through the implementation of a theoretical carbon trading mechanism. This paper proposes a theoretical framework based on the concepts of “externality” and public goods theory, focusing on Pigouvian tax, Coase theorem, and the distribution of carbon emission rights through quotas. It also explores the underlying economic principle of the “green premium”. Carbon financing is expected to support future advancements in carbon-neutral technologies. Therefore, this paper summarizes the theory and examines the relationship between carbon trading and carbon finance markets. The mechanism of the carbon market operates based on supply and demand dynamics, and now the market is witnessing gradual expansion in which other evolutionary laws also play parts, such as carbon price fluctuations,improvements to the regulatory system, and the diversification of market participants. The main instruments in the carbon market include carbon taxes, trading, and offsets, with governments, businesses, and individuals playing different roles. This paper provides a systematic analysis of theoretical innovations and practical achievements in carbon market economics, serving as a valuable reference for strategic decision-making and technological innovation in the pursuit of carbon peaking and neutrality goals.

BackgroundSubchannel codes constitute an important computational tool in the field of reactor thermo-hydraulics. Uncertainty analysis methods can be used to effectively identify and quantify the uncertainties of code input parameters and model assumptions, thus improving the reliability of the code so as to provide a more reliable reference for thermo-hydraulic parameter design.PurposeThis paper aims to present an uncertainty analysis of a 10 MW small lead-bismuth reactor in steady-state and transient loss-of-flow accident scenarios by using the subchannel code SUBCHANFLOW.MethodsFirst, a full reactor core subchannel was modeled, and the input parameters that affect the target parameters were identified. Second, the optimal Latin hypercubic sampling method was used for sampling within the distribution range of the input parameters, and the samples were imported into SUBCHANFLOW to obtain the uncertainty bands for the steady-state and transient loss-of-flow accident scenarios. Finally, gray correlation analysis was employed to evaluate the steady-state and transient sensitivities.ResultsThe computational results indicate that the uncertainty bands of the target parameters envelop the nominal values in both the transient and steady-state cases. In the transient case, the maximum temperature tolerance upper limit of the pellet is 674.55 ℃ and that of the cladding is 618.31 ℃. Further, the calculation accuracy of each parameter is essentially below 7%. The uncertainty in the target parameters mainly originates from parameters such as the inlet temperature, fuel rod height, outlet pressure, total power, and thermal conductivity of the cladding, with the inlet temperature having the most significant effect.ConclusionsThis study demonstrated the computational uncertainty of the SUBCHANFLOW code and the difference in the sensitivity of each parameter to the system response under the steady-state and transient loss-of-flow accident scenarios. The findings help further optimize and improve the design and operation strategy of lead-bismuth reactors, thus enhancing their safety and reliability.

The uncertainties of distribution generations (DGs) and loads lead to severe voltage fluctuations in active distribution networks (ADNs). Meanwhile, energy storage systems (ESSs) and static var compensators (SVCs) can mitigate the uncertainties of power injections by regulating the active and reactive power. Considering the variations of multiple uncertain factors, this paper proposes a complex affine arithmetic (CAA) based uncertain sensitivity analysis method of voltage fluctuations in ADNs. First, affine models of active and reactive power injections are established. The correlations of noisy symbols are used to reflect the mitigation effects of ESSs and SVCs on the uncertainties introduced by DGs and loads. Next, sensitivity indicators of voltage fluctuations are defined based on the transitivity of noisy symbols. Then, a calculation method for sensitivity indicators based on the micro-increments of coefficients is proposed. Combined with the obtained indicators, a fast sensitivity method for calculating interval values of voltages is further proposed. The modified IEEE 33-bus system is tested to validate the accuracy and efficiency of the proposed method by comparison with the continuous utilization of power flow method. Moreover, the 292-bus system is tested to validate its applicability in a large distribution system. Facts have proved that this method improves the efficiency and reliability of calculations, and in different scenarios, it can achieve fast calculation of nodes and online analysis of the voltage fluctuation range in uncertain environments, provides an effective tool for voltage quality management in active distribution networks.

The nature of the interaction between actinide ions and ligands is of great significance in the application of the separation of actinide groups. Therefore, we have been devoted to this aspect in recent years. In this article, the coordination structure, stability and bonding properties of the complexes formed by uranyl and macrocyclic ligands are reviewed. First of all, our study found that the coordination structure of actinyl macrocyclic complexes depends on the size of the macrocyclic ligands; secondly, in the case of “side-on” coordination, uranyl tends to form a 1∶2 complex, while in the case of “insertion” structure, uranyl tends to form a 1∶1 complex; thirdly, it has been found that the ligands with ring size of 18 have excellent coordination ability when combined with uranyl, and ［CHP］4- has the strongest binding ability; finally, this stability is mainly due to the greater covalence of U-N than that of U-O and U-S. These structural rules and bonding characteristics provide important theoretical guidance for the experimental screening of reasonable and efficient ligands for the separation of actinides.

Abstracts AF6, a known polarity protein, contributes to the maintenance of homeostasis while ensuring tissue architecture, repair, and integrity. Mice that lack AF6 display embryonic lethality owing to cell–cell junction disruption. However, we show AF6 promotes necroptosis via regulating the ubiquitination of RIPK1 by directly interact with the intermediate domain of RIPK1, which was mediated by the deubiquitylase enzyme USP21. Consistently, while injection of mice with an adenovirus providing AF6 overexpression resulted in accelerated TNFα-induced necroptosis-mediated mortality in vivo, we observed that mice with hepatocyte-specific deletion of AF6 prevented hepatocytes from necroptosis and the subsequent inflammatory response in various liver diseases model, including non-alcoholic steatohepatitis (NASH) and the systemic inflammatory response syndrome (SIRS).Together, these data suggest that AF6 represents a novel regulator of RIPK1-RIPK3 dependent necroptotic pathway. Thus, the AF6-RIPK1-USP21 axis are potential therapeutic targets for treatment of various liver injuries and metabolic diseases.

As deep mining becomes prevalent in China's coal mining industry, coal-gas compound dynamic disasters pose increasing threat to the safety production of coal mines. This paper adopts the field data of Pingmei No. 8 coal mine for analysis, with the attempt to predict coal-gas compound dynamic disaster through convolutional neural network. Following the routine of the big data processing, we first employed Box-plot analysis and multiple interpolation method(MI)to clean the data. Combined with grey relation analysis(GRA), we established a coal-gas compound dynamic disaster index system. Then, principal component analysis(PCA)is used for dimensionality reduction of the data. Combined with the convolution neural network(CNN)in deep learning, we established the coal-gas compound dynamic disaster prediction model based on BMGP-CNN. The field data is used to compare and verify this model with BP, random forest(RF), support vector machine(SVM)and artificial neural network(ANN). It is found that BMGP-CNN model yields prediction results with satisfactory accuracy and quick convergence. The results offer implications for the prediction and prevention of coal-gas compound dynamic disasters.

Liver transplantation is the most effective treatment for end-stage liver diseases. However, the shortage of donor livers severely restricts the application of liver transplantation, and the impairments of liver function caused by intraoperative ischemia reperfusion injury and postoperative immune rejection also significantly affect the therapeutic efficacy. In order to improve the shortage of donor livers and further improve the efficacy of liver transplantation, a variety of cell therapies based on stem cells or somatic cells have been tried to repair and improve donor liver function. At present, the time points for cell therapy can be divided into the stage before procurement of donor livers, machine perfusion stage and stage after reperfusion of donor livers. In this review, we summarize the efficacy and the underlying mechanisms of cell therapy in the preservation and function repair of donor livers, so as to facilitate the application and promotion of cell therapy in the field of liver transplantation.

ObjectiveTo understand the pollution status of cadmium in wheat in 16 cities of Shandong Province and evaluate its dietary exposure and health risks.MethodsInductively coupled plasma mass spectrometry was performed to detect the cadmium content in wheat in 16 cities in Shandong Province from 2020 to 2021， and the dietary exposure to cadmium was calculated based on the wheat consumption of Shandong residents. The health risks caused by cadmium were evaluated using the margin of safety（MOS） and the health risk assessment model recommended by the United States Environmental Protection Agency.ResultsThe median of cadmium in wheat was 0.020 2 mg/kg， and the detection rate was 97.5%. The cadmium pollution in wheat was higher in southern Shandong Province and Jiaodong Peninsula， and lower in northwestern Shandong Province. The average monthly intake of cadmium from wheat by Shandong residents was 1.80 µg/kg·BW， which was less than the reference value of PTMI（25 µg/kg·BW）. The MOS of cadmium in wheat was 13.9 and the risk was acceptable. The average annual personal cancer risk was 0.46 × 10-5 per year， which was less than the standard of the international commission on radiation protection.ConclusionThere are regional differences in wheat pollution in Shandong Province， and the health risk of residents ingesting cadmium through wheat is at an acceptable level.

The existing research on ventilation control for long-distance heading face is mostly limited to the frequency conversion of local ventilation fans themselves. There is few research on the on-demand wind supply direction for long-distance heading face. In order to solve the above problem, a design scheme for an intelligent regulation and control system for local ventilation in long-distance heading face is proposed. The system consists of an underground monitoring system, a ventilation anomaly control system, and a ground workstation. The underground monitoring system achieves early warning of abnormal working conditions of local ventilation fans, dynamic analysis of air leakage inside the air ducts, and dynamic prediction of actual supply and demand air volume by real-time monitoring of underground ventilation fans, air ducts, and working surfaces. The ventilation anomaly control system identifies underground abnormal ventilation parameters, develops risk collaborative disposal strategies for different parameters and levels, and displays the specific distribution of parameters such as gas concentration in the heading face in real-time. The ground workstation excavates the potential laws between the air flow status of the heading face and the parameters of the air duct, forming an air flow-air duct control model. Real time control of the air duct is achieved based on the distribution status of the air flow in the heading face. At the same time, the workstation establishes a variable frequency predictive air regulation model that matches the theoretical air supply, actual air supply, and actual air demand. Based on the variable frequency air regulation model and real-time ventilation parameters, the operating frequency of the fan is determined. The on-demand air supply is achieved through intelligent variable frequency of the fan. In abnormal ventilation situations, based on the prediction of gas emission and the limit capacity of air venting gas, supplemented by drilling gas extraction to control the concentration of gas in the working face, the ventilation safety guarantee for the long-distance heading face is achieved. Taking the 23303 heading face of Zhuanlongwan Coal Mine as an example, numerical simulation of air flow is conducted to study the distribution status of air flow in the face. It provides a basis for adjusting the layout of wind speed sensors in the heading face. The paper proposes two different ventilation linkage control methods, namely variable frequency wind regulation under normal conditions and regulating exhaust air under abnormal conditions. The operating frequency of the fan is determined through supply and demand matching analysis under normal conditions to achieve intelligent variable frequency air regulation of the fan. In case of abnormal ventilation, four regulation and exhaust rules are adopted to ensure the ventilation safety of long-distance heading faces, while achieving the effect of energy conservation and emission reduction. A comprehensive evaluation system for the health indicators of the local ventilation system has been constructed. Through a comprehensive evaluation model and health index, real-time health 'physical examination' of the local ventilation system is achieved, and the risk levels of different indicators are quantitatively displayed to ensure that the local ventilation system is in a healthy state.

The dissipative Kerr soliton combs based on microresonators have attracted wide attention due to their high coherence and on-chip integration. Meanwhile, the soliton microcombs have shown broad applications in coherent communication, on-chip low-noise microwave synthesizer, optical clock, etc. However, the performance of these applications is typically limited by their bandwidth as the precise tuning of the soliton microcombs usually relies on the thermoelectric cooler, which is slow and may increase the system’s complexity. Here, we demonstrate the observation of dissipative solitons based on the magnesium fluoride resonator with an ultrahigh-quality (Q) factor of about 927 million. The ‘power-kicking’ scheme is employed to lock and stabilize the solitons actively. Also, tuning the acousto-optical modulator allows changing the bandwidth and recoil of the solitons. This approach enables more direct and concise feedback and reduces the system’s complexity.

[Objective] The high-quality development of tourism is closely related to Common Prosperity. It is of great significance to clarify the interaction between the two to promote the transformation and upgrading of China’s tourism industry and reaching the goal of Common Prosperity. [Methods] In this study, the improved entropy method was used to measure the high-quality development of tourism and the level of Common Prosperity. The coupling and coordination degree of high-quality tourism development and Common Prosperity was then analyzed. Finally, the PVAR Model was used to explore the interactive response relationship between high-quality development of tourism and Common Prosperity. [Results] The results show that: (1) The level of high-quality development of tourism and Common Prosperity showed a stable upward trend, but the growth rateZ was low and there existed spatial differences during 2010 to 2019. (2) The coupling and coordination degree of high-quality development of tourism and Common Prosperity showed a gradual progress from basic coordination to moderate coordination, showing a pattern of east > central > west. (3) There was a positive interaction between the high-quality development of tourism and Common Prosperity, and there exited differences between long-term and short-term effects of the two. In the short term, the magnitude of their mutual influence was greater; in the long term, the two are more influenced by their own development. [Conclusion] The level of high-quality tourism development of China and Common Prosperity are generally on the rise. However, there existed a certain gap in the development of various regions. So, targeted measures should be taken to improve the situation according to the characteristics of regional development.

Only by grasping the pulse of the times and continuously injecting the spirit of the times into Marxism can the construction of its discourse system have a source of living water. Based on artificial intelligence, this paper constructs the discourse system of contemporary politics and Marxism education from three aspects: synchronous resonance, comprehensive coordination, and human-computer interaction. The research data from seven universities from April to September 2022 were selected as research examples, and the degree of influence of artificial intelligence on the discourse capacity of contemporary politics and Marxism education was explored using multiple linear regression models and principal component factor analysis. The reliability test and exploratory factor analysis were conducted for the research questionnaire data, and the validation analysis was conducted for the influencing factors and influencing factors of Marxist educational discourse competence. The results show that the degree of influence of the homophily resonance ability factor on Marxist educational discourse ability is 42.78%, and the R2 test results of artificial intelligence technology homophily resonance, comprehensive coordination, and human-computer interaction are all greater than 0.5. The discourse ability of contemporary political and Marxist education is enhanced by 0.726 percentage points when university technology increases by 1 percentage point. The construction of the discourse system of contemporary political and Marxist education empowered by artificial intelligence requires deep excavation of the discourse content and the creation of high-quality discourse contexts in order to realize the full, whole and all-around nurturing of Marxist education in colleges and universities.

Using tip-enhanced photoluminescence (TEPL), we investigate micron-size monolayer MoS2 flakes. In a sequence of studies, we apply various voltages between the Ag-coated nano-tip and the MoS2 flakes and observe an intriguing result. During the TEPL measurement, we observe that the photoluminescence spectrum is blue shifted and the overall signal intensity is increased. We attribute this behavior to plasmon-induced electron injection into MoS2. Additionally, when the tip is negatively biased with respect to the sample during the TEPL measurement, the nonuniform TEPL images of MoS2 monolayer flakes containing defects are gradually changed to be uniform that reach saturation. We verify that this saturation state in TEPL can last over half a year.

Dynamic coal quantity detection for conveyor belt is the foundation and key to achieving energy consumption optimization measures for multi-stage belt conveyors such as coal flow starting and automatic speed regulation. The existing coal quantity detection methods based on ultrasonic have low precision. Multiple ultrasonic sensors are susceptible to interference. In order to solve the above problems, a dynamic coal quantity detection system for conveyor belts based on ultrasonic array is designed. Using the principle of ultrasonic ranging, the coal material height corresponding to the detection points of each ultrasonic sensor array element is detected in real-time through an ultrasonic array. The cross-section slicing method is used to calculate the total volume of coal material passing through the conveyor belt per unit time. The real-time coal flow and total coal quantity of the conveyor belt are calculated based on the coal material stacking density. In order to reduce the crosstalk of the same frequency acoustic wave and the error caused by the attenuation of ultrasonic waves in harsh underground environments, 10 ultrasonic sensor arrays with different center frequencies are selected and arranged in a 2×5 linear array form. The collected coal height data is compensated through multiple rows of ultrasonic sensors to improve the accuracy of coal height data detection. The analysis results of real-time performance indicate that the ultrasonic array detection speed theoretically meets the coal quantity detection requirements of a belt conveyor with a belt speed of 5 m/s. The experimental results show that the average relative errors of regular material volume detection are 4.99% and 5.16% at belt speeds of 0.125 m/s and 0.170 m/s, respectively. Under simulated actual operating conditions, the average relative error of coal quantity detection is 5.56%. In the low belt speed state, the system has a measurement accuracy of over 94% for regular materials and coal. It basically achieves real-time and accurate detection of the dynamic coal quantity of the conveyor belt, meeting the coal quantity detection requirements of the belt conveyor.

Currently, the borescope is the most used method with non-destructive testing in the process of aero-engine inspections and is the only way to obtain borescope images. In recent years, the artificial intelligence technologies such as deep learning are applied to aero-engine damage classification and detection, and some effective methods are proposed to achieve intelligent inspection of aero-engines, which have significant value for industrial applications. The benefits and disadvantages of aero-engine borescope inspection and its development are reviewed. The progress in the application of artificial intelligence technologies such as expert system and machine learning to engine borescope detection images is over-viewed. Some of the challenges in achieving intelligent aero-engine borescope inspection are summarized.

The dynamic change of scene fog concentration caused by spraying dust removal operation in the production state of underground coal mine working face leads to the blurred visual video image. This seriously affects the visual remote intervention coal mining control and operation in underground coal mine. Aiming at the above problems, a method of video fog concentration detection and real-time fog removal underground in coal mine working face is proposed. Firstly, the difference between the brightness value and the saturation value of the fog-containing video image is calculated based on the color attenuation prior to realize the fog concentration detection. The fog-containing image and the non-fog image are further identified. Secondly, the color attenuation prior and the scene change probability model are used for correcting the video time continuous cost function. The transmittance error between adjacent frames of the video is reduced. The flicker influence of the fog removed video image is reduced. Finally, the video fog concentration detection and real-time fog removal method in the coal mine working face and the Kim method are respectively used to process the foggy video of the coal mine underground scene. The experimental results show the following points. ① The fog concentration distribution in the image scene can be accurately calculated by the fog concentration detection method. The maximum connected region of the extracted fog concentration accounts for 38.693% of the total image pixels. The fog-containing images are those greater than 20% of the fog concentration threshold. According to the recognition result of the fog-containing image, the non-fog image is automatically ignored. The fog-containing image is selectively fog removed. ② The video fog concentration detection and real-time fog removal method in coal mine working face is used to remove the fog of the production video of different areas (a support area and a coal wall area) and different fog concentrations (a medium fog concentration and a higher fog concentration). The contrast of the video image is obviously enhanced after fog removal, and the visual effect is brighter and clearer. ③ The mean square error curve of the real-time fog removal method is lower than that of Kim method. This indicates that the mean square error value of the adjacent frames of the video is reduced after the continuous scene video is fog removed. The flicker phenomenon of the real-time fog removal result video is effectively suppressed. The contrast cost function and the color information loss cost function are used to estimate the transmittance of the fog-containing image. The ideal fog removal effect is obtained when the scene changes. ④ The mean value of mean square error between the adjacent frames of the fog removal result of the real-time fog removal method is reduced by 4.26 compared with the Kim method. The similarity between the adjacent frames is improved. The image flicker phenomenon between the adjacent frames is further suppressed. In the aspect of running time, the processing time of each frame of the real-time fog removal method is increased by 2 ms compared with the Kim method. However, the processing time of each frame is less than 40 ms, which meets the real-time requirement.

In order to obtain the energy change rule in coal adsorbing methane process, methane adsorption experiments were carried out with the temperature of 30 ℃, 15 ℃, 0 ℃, -15℃, -30 ℃, -45 ℃ and the initial adsorption pressure of 1 MPa, 1.5 MPa, 2 MPa, 2.5 MPa, 3 MPa by the high and low temperature intelligent adsorption experiment chamber. The results show that increasing the gas injection pressure and decreasing the adsorption temperature are two important factors that affect the increase of temperature variation in the process of methane adsorption; the surface free energy of coal samples with a certain mass decreases and the heat increases before and after methane adsorption, and the difference increases gradually due to the increase of methane pressure; in the process of coal adsorbing methane, either pressure boost or temperature drop will increase the coal temperature variation, it is essentially a phenomenon that methane molecular potential energy of coal surface free energy is converted into heat value to maintain the overall energy balance.

In deep mining, coal-rock is in a state of three unequal forces, and the intermediate principal stress has the influence on the deformation and strength characteristics of coal-rock. This study studied the deformation and seepage characteristics of gas-bearing composite coal-rock under different intermediate principal stresses by using true triaxial gas-solid coupling seepage test device for coal and rock. The results show : ① With the increase of intermediate principal stress, the strain in the direction of maximum principal stress first increases and then decreases when the peak strength is reached, and there is widening gap between the strain in the direction of intermediate principal stress and the strain in the direction of minimum principal stress.② Under low intermediate principal stress, the strain in the intermediate principal stress direction shows expansion and deformation, and when there is relatively high intermediate principal stress, the ε2-Δσ curve reaches the peak and then bounces back, and the strain in the intermediate principal stress direction finally shows compression and deformation.③ With the increase of intermediate principal stress, the trough value of relative permeability coefficient decreases, and the peak inflection point of relative permeability coefficient curve is consistent with the inflection point of ε1-Δσ curve.④ When the stress peak is reached, the total input energy of the specimen first increases and then decreases, which is similar to the changes of the specimen strength: The elastic strain energy first increases and then decreases, the dissipative energy continues to increase, Ue/U first increases and then decreases, and Ud/U first decreases and then increases.

BackgroundTraditional text-based system engineering in the design and application of passive residual heat removal systems (PRHRS) for lead-cooled fast reactors has several requirement problems, such as low development efficiency, a long iteration cycle, and model ambiguity.PurposeThis study aims to effectively address the aforementioned problems encountered in the PRHRS of lead-cooled fast reactors by adopting a model-based system engineering method.MethodsThe model-based system engineering (MBSE) method was preliminarily applied to the design requirement analysis of a PRHRS for lead-cooled fast reactors. During the design requirements study, the design process was combined with the preliminary design of the system architecture, comprising three parts: requirements analysis, functional analysis, and design synthesis.ResultsThe generated requirement and use case diagrams describe the system requirements and determine the top-level use cases of the system in the requirement analysis stage. The time sequence, activity, and state machine diagrams form the system function model and provide early confirmation and verification in the functional analysis stage. Finally, the white box model realizes the analysis and design of the system architecture in the design synthesis stage.ConclusionsThe system architecture designed by this method ensures the consistency of the design requirements. In the future, it will further reduce the design risk, improve the design efficiency, and provide an application reference for the design and optimization of digital lead-cooled fast reactors' passive residual heat removal systems.

When simultaneous localization and mapping (SLAM) technology is applied to autonomous positioning of unmanned aerial vehicles in coal mines, the use of feature points to construct maps can easily lead to degradation issues, resulting in inaccurate positioning. Moreover, due to its use of the body as a reference coordinate system, global positioning cannot be achieved. In order to solve the problems, a positioning method for underground unmanned aerial vehicles (UAV) in coal mines based on global point cloud map is proposed. The method uses Fast-LIO2 algorithm as the lidar SLAM algorithm to obtain UAV position and attitude estimation. An iterative nearest-neighbor algorithm is used for two-step matching of the acquired real-time lidar point cloud and the global point cloud map to achieve UAV position and attitude correction. To address the issue of point cloud matching speed not ensuring real-time positioning due to the excessive number of point clouds, a time-based position and attitude output strategy is designed to increase the frequency of outputting UAV position and attitude data. The SLAM precision and position and attitude correction effect of the UAV positioning method are tested in a 1 000 m underground coal mine roadway. The results show that in long-distance roadway environments, the cumulative positioning error of the Fast-LIO2 algorithm is less than 1 m, and is less than 0.3 m in the range of 600 m or more, which is significantly smaller than the cumulative positioning errors of LOAM-Livox algorithm and LIO-Livox algorithm. The position and attitude estimation output by the Fast-LIO2 algorithm has been corrected by the correction algorithm, and all flight paths are located in the global point cloud map, verifying the effectiveness of the position and attitude correction algorithm. The time consumption of single SLAM algorithm operation is 14.83 ms, the one of single position and attitude correction is 883 ms, and the output frequency of position and attitude data is 10 Hz, meeting the real-time requirements of UAV positioning.

With the progress of technology, the high-speed gear transmission device, which is widely used in energy, petrochemical and other fields, develops towards the direction of high power, high line speed, high efficiency and lightweight. The herringbone gear is usually used in this kind of transmission device, and its dynamic particularity under high speed conditions has an important influence on the reliable operation of the equipment. Therefore, the model of herringbone gear transmission is established, the dynamic characteristics of various herringbone gear transmission are analyzed under the conditions of driving and load excitation, the dynamic simulation is carried out, and the product is tested. The results show that when the load is constant, the greater the angular speed of the gear, the greater the contact force on the gear and the higher the collision frequency. When the input speed increases from 500 r/min to 1 000 r/min and 1 488 r/min, the difference of velocity fluctuation amplitude is 2.27 rad/s, 4.76 rad/s and 9.37 rad/s respectively, and the maximum contact force is 1.87 times and 2.44 times of that under 500 r/min, respectively. The number of angular velocity fluctuation increases to 1.94 times and 2.94 times of the case of 500 r/min, respectively. When the load increases, the angular velocity fluctuation of driven gears decreases and the contact force increases. This study provides reference for the design of this kind of high speed transmission devices.

Reliable predictors are urgently needed to identify stage II nasopharyngeal carcinoma (NPC) patients who could benefit from concurrent chemoradiotherapy (CCRT). We aimed to develop a nomogram integrating MRI-identified multidimensional features of lymph nodes to predict survival and assist the decision-making of CCRT for stage II NPC.

Abstract Background Hirschsprung-associated enterocolitis (HAEC), one of the most significant causes of morbidity and mortality for patients with Hirschsprung disease (HSCR), can occur before and after radical surgery. This study aims to identify the risk factors for HAEC before and after Soave. Methods A retrospective study of 145 patients with HSCR treated by transanal or combination with laparoscopic or laparotomy Soave procedure between January 2011 and June 2021 was performed. Data were retrieved from the medical records. HAEC was defined as the presence of clinical signs of bowel inflammation and requiring treatment with intravenous antibiotics and rectal irrigation for at least two days in the outpatient or inpatient department. Univariate analysis and multivariate regression models were used to identify risk factors for developing pre-and postoperative HAEC. Results The incidence of pre-and postoperative HAEC was 24.1% and 20.7%, respectively. More than 90% of the patients with the first episode of postoperative HAEC occurred within the first year after Soave. Long-segment aganglionosis was the independent risk factor for developing preoperative HAEC ([OR] 5.8, Cl 2.4–14.2, p

The ”efficiency improvement technology of front and rear wall hedging boilers based on combustion optimization and balancing heating surface wall temperature” is proposed and applied in a 1000MW unit of a power plant, which effectively reduces the large deviation of the heating surface wall temperature, increases the temperature of the main reheated steam, and improves the economy and safety.This paper introduces the principle of ”efficiency improvement technology of front and rear wall hedging boilers based on combustion optimization and balancing heating surface wall temperature”. It takes 1000MW unit as an example to introduce in detail how to use this technology to adjust combustion. The main steam increased by 6 °C, the reheat steam increased by 1.9 °C, the CO decreased from 2000–3000mg/Nm3 before adjustment to about 200 mg/Nm and the wall temperature deviation of the heating surface was significantly reduced. The technology can be widely used in ultra-supercritical once-through boilers with front and rear wall hedging swirl burners to improve the economy and safety of boilers, and has a broad space for promotion. The mutual restriction relationship between environmental performance and environmental protection, while taking into account the potential safety hazards caused by flue gas temperature deviation, establish a more comprehensive and complete combustion model.

As the depth increases, the ratio of horizontal to vertical stress on the coal rock strata will gradually decrease, which affects the crack propagation behavior around hydro-fracture injection hole. In order to explore the characteristics of hydro-fracture crack turning behavior at different depths, based on the mechanical model and adsorption and desorption model of coal seam, COMSOL was used to analyze the stress distribution and crack initiation pressure around the injection hole at different depths. The results show that at shallow depths, the ratio of horizontal stress to vertical stress is greater than 1, the cracks extend mainly horizontally, and the fracture is more likely to turn when the stress ratio increases. At a deeper depth, the ratio of horizontal stress to vertical stress is less than 1, the cracks extend mainly vertically, and the fracture is more likely to turn when the stress ratio decreases.

With the integration of information technology and traditional industries,it has become a trend to use computer-controlled machines instead of humans to perform repetitive,boring and even dangerous tasks.In order to effectively interact with computers in natural language,human-computer interaction and dialogue systems based on multi-turn dialogue technology have become a research hotspot in the field of artificial intelligence and natural language processing.In the grid control system,the dispatcher needs to do a large number of query operations manually.To reduce the complexity of existing dispatching system and improve the speed of emergency handling of dispatchers,multi-turn dialogue technology can be applied to realize intelligent voice query of power grid data.This paper first describes the basic architecture of the task-oriented multi-turn dialogue system,including functions and related algorithms of its three modules:natural language understanding,dialogue management,and natural language generation.Next,in order to meet the demand of power grid companies for specific scenarios such as intelligent data queries,this paper designs and implements a multi-module task-oriented multi-turn dialogue system which consists of natural language understanding module,dialogue management module,natural language generation module and knowledge base as core mo-dules.The grid dispatcher can ask the system questions and get answers in the form of natural language.This process does not require keyboard or mouse operations,which greatly improves the rapidity and convenience of the grid information query.

Mine belt fires are prone to cause heavy casualties due to their strong suddenness and difficulty in disaster relief and fire fighting. Quick and effective wind control, smoke exhaust, and evacuation are the keys to disaster relief. By studying the disaster mechanism and prevention and control mechanism of wind and smoke flow of well fire and its secondary disasters, the air volume distribution and air supply path of the original air control and smoke exhaust scheme were optimized, and the emergency linkage control method of wind and smoke flow in different fire scenarios was proposed. Based on the Froude number conservation model(Froude), the critical conditions for the balance of fire wind and smoke flow in inclined roadways are studied, and the formulas of critical wind speed and minimum exhaust air volume to prevent backsliding of smoke flow are obtained, and the optimal air control and exhaust scheme is quantified. The three-dimensional visualization ventilation network model of Yangchangwan Coal Mine is established by Ventsim software. The spreading law of wind and smoke flow in different fire source point scenarios and the smoke exhaust effect and air volume distribution before and after adopting the air control and smoke exhaust scheme are simulated respectively. The simulation results show that the optimized regulation scheme can not only satisfy the minimum air volume of the smoke control and exhaust path but also ensure the minimum air volume required for the escape of the people in the mining area and the gas dilution. The emergency control plan for catastrophic wind and smoke flow has been further improved.

In order to study the effect of graded loading rate on creep characteristics of anthracite, the effects of graded loading rate and stress level on instantaneous strain, creep strain and creep rate of coal samples were analyzed by triaxial creep tests of anthracite under four different graded loading rates. The results show that at the same stress level, the higher the graded loading rate is, the smaller the instantaneous strain is and the larger the creep strain is, but the increasing trend of creep strain gradually slows down; at the same loading rate, with the increase of the creep stress level, the instantaneous strain of coal samples shows an overall decreasing trend of rapidly decreasing-slowly decreasing-increasing, while the creep strain of coal samples shows an overall increasing trend of basically unchanged-slowly increasing-rapidly increasing; the change process of creep rate can be divided into three stages: rapid decay, slow decay and stability, at the same stress level, the higher the graded loading rate is, the higher the maximum creep rate is, and the faster the creep rate decays.

By using the newly introduced GeoLas HD 193 nm ArF excimer laser ablation system and the Agilent 7900 quadrupole inductively coupled plasma mass spectrometer (ICP-MS) in the Key Laboratory of Paleomagnetism and Tectonic Reconstruction at the Institute of Geomechanics, we successfully established the in-situ zircon U-Pb dating method and trace element analytical method by LA-ICP-MS. U-Pb dating experiments were carried out on Plešovice, Temora1 and Qinghu zircons under the experimental conditions of 32 μm beam spot diameter, 5.0 J/cm2 energy density and 5 Hz denudation frequency using the standard zircon 91500 as the external standard. The ideal age results are consistent with their recommended values, and the measured U-Pb ages for Plešovice zircon remain stable in different periods. Meanwhile, a comparative study of the U-Pb dating results in different laboratories was carried out on an unknown sample 11-5, and the dating results are consistent with that obtained in the State Key Laboratory of Geological Processes and Mineral Resources at China University of Geosciences (Wuhan) within analytical error. Trace elements in zircon standard 91500 and glass standard NIST SRM 612 were analyzed by using NIST SRM 610 as an external standard and 29Si as an internal standard, and the measured values are consistent with the recommended values of trace element contents. In addition, the influence of different beam spot diameters on the zircon U-Pb age results was explored by using the Plešovice zircon as an example. The results show that a denudation diameter of 16~44 μm can obtain reliable zircon U-Pb ages similar to the recommended age, and under the same energy density and denudation frequency conditions, U-Pb ages obtained by using 32~44 μm beam spot diameters are more accurate than those obtained by 16~24 μm beam spot diameters.

New urbanization promotes the free flow and redistribution of tourism elements in space and accelerates the transformation of the tourism economy to intensive and efficient development, which is one of the possible ways to optimize tourism efficiency. Taking 30 provinces in China as case studies, this study utilized the entropy method and bootstrap-data envelopment analysis to measure the level of new urbanization and tourism efficiency from 2001 to 2019. A bivariate LISA model was adopted to investigate their spatial correlation characteristics. Spatial Durbin and threshold models were used to analyze the spatial effect and dynamic non-linear impact of the development of new urbanization on tourism efficiency. The results revealed the following: 1) During the study period, the level of new urbanization and tourism efficiency in China showed varying degrees of fluctuation and improvement, with the largest increase in the Central and Western areas. Spatial differentiation characteristics were in the order of Eastern Area > Central Area > Western Area > Northeastern Area and Central Area > Eastern Area > Western Area > Northeastern Area. 2) A positive spatial correlation was observed between new urbanization and tourism efficiency. Local spatial correlation types of spatial agglomeration were namely H-H and L-L. A total of two new urbanization areas had a spatial effect on tourism efficiency. The direct and indirect effect coefficients were 0.274 3 and -0.634 5, respectively. New urbanization in this region was found to have a positive effect on the improvement of tourism efficiency, while the improvement of new urbanization in adjacent areas is expected to inhibit the improvement of tourism efficiency in this region. 3) Under the influence of the threshold variable of tourism industry status, the positive effect of new urbanization on tourism efficiency exhibited a double threshold, showing a U-shaped change trend of "decline first and then rise." Based on the results, this study proposes differentiated countermeasures to improve regional tourism efficiency, expands the research on the non-linear relationship between new urbanization and tourism economics from the perspective of comprehensive development of new urbanization, and enhances the academic attention on the feedback effect of new urbanization on tourism economy.

The technological development and application status of underground complex space UAVs are analyzed. It is pointed out that underground complex space UAVs face problems such as insufficient individual performance, limited environmental situational awareness and autonomous navigation capabilities, and limited formation collaboration capabilities. In order to solve the above problems, the development trends of key technologies for underground UAVs are prospected. ① Small and lightweight integrated UAV design technology is proposed. By improving the mechanical structure of the UAV, improving the integration of information perception sensors such as LiDAR and depth camera with control systems, and optimizing power management systems, the ultimate goal is to improve the cruise speed, endurance time, and other performance of individual UAV. ② Situation awareness and autonomous navigation technology in GPS rejection environment is proposed. The key technical challenges such as simultaneous localization and mapping (SLAM) navigation and real-time path planning should be overcome. The limitations of algorithms around specific scenarios should be gradually broken through. The perception capability, environmental adaptability, and robustness of unmanned systems should be improved. ③ Formation collaboration control technology under limited information is proposed. The technical problems such as heterogeneous/isomorphic UAV cluster collaboration, and wireless communication in complex channel environments should be overcome. By optimizing UAV swarm intelligence control strategies, information interaction mechanisms, and task decision-making collaboration mechanisms, the robustness of clustered unmanned systems should be enhanced. The adaptability of unmanned systems in complex underground environments should be improved. Furthermore, the task execution efficiency and success rate of unmanned systems should be improved.

We demonstrate high energy Q-switched pulse generation with the help of a large mode area gain waveguide in a silicon photonics device. Output pulse energy >150 nJ and laser slope efficiency of 40% is shown.

Climate prediction models have traditionally relied on complex physical equations to simulate the dynamics of the climate system, but these models often require significant computational resources and long computational lengths. In recent years, machine learning techniques have shown great potential for pattern recognition and prediction. Specifically, machine learning models have become a hot research direction in the field of climate science due to their advantages in processing large-scale datasets. In this work, we propose a convolutional neural network-based (CNN) model capable of processing and analysing large-scale climate datasets from satellites, including multi-dimensional data including temperature, air pressure, humidity, and CO2 concentration. The input is historical climate data, and the spatial features are extracted through the convolutional layer, and then the feature fusion and final prediction output are performed through the fully connected layer. Finally, we utilized historical climate data as the training set and tested the model on data over multiple time periods. The results show that compared with traditional physical models, CNN-based models provide higher accuracy and lower prediction errors in predicting global average temperature changes, precipitation, and extreme weather events.

In order to reduce nitrogen oxides in the earth's atmosphere caused by pollution. Thermal power plants are gradually adding a selective catalytic reduction denitrification technology during the operation of the power plant. But in the power plant in the process of the denitration, the phenomenon of sulfur dioxide (SO2) being oxidized to sulfur trioxide (SO3) occurs and cannot be accurately monitored. Therefore, in order to have a more intuitive understanding of SO3 emissions from power plants, we use a transfer learning based on VGG16 network to study it, which is of significant reference value for the application of machine learning techniques in predicting atmospheric pollution from thermal power plants. Real smoke data is put into the model to make predictions, analyze and verify the effects, and compare the predicted effects with other machine learning models showing that the transfer learning model has higher identification accuracy.