As a primary mineral product, platinum is an important strategic mineral in China, which is mainly used in the fields of automobile, jewelry, and chemical industry. In this study, a dynamic material flow analysis model of platinum in China for the period of 2016-2020 was constructed to quantitatively assess the anthropogenic flow and social inventory of platinum. Then the automotive industry was selected based upon the sectoral consumption approach to measure the end-of-life of platinum, and policy recommendations were made for the sustainable development and resource management of platinum based upon the findings. We found that:(1) China's platinum minerals are small and of low grade, and the available reserves and production of platinum ores are declining, with the national average grade of platinum being only 0.341 g/t;(2) the consumption and import dependence of platinum is largely increasing year by year, with the jewelry industry being the industry with the highest demand,and the stock and scrap of platinum in the automotive industry is also growing dramatically. All these findings indicate that we should explore new high-grade platinum mines and enter cooperative relationships with major platinum exporting countries; and that the future recycling potential in China is tremendous, while the improvement of the collection system of platinum-containing products after consumption can enhance the recycling of secondary resources to effectively recover platinum scrap, thus reduce the import dependence and well foster the sustainable use of platinum.

The curing performance of different 3D printing photosensitive resins varies, which are light cured under the same 3D printer. 2 characteristic parameters, critical exposure and transmission depth, were used to characterize the photosensitivity of photosensitive adhesives, and the mathematical relationship between critical exposure and transmission depth was explored. The measuring methods of critical exposure and penetration depth were studied. The effects of light intensity and resin color on resin curing were measured. Under certain conditions, the penetration depth generally increased with the increase of light intensity,and the critical exposure also increased with the increase of light intensity. Light colors have higher penetration depth than dark colors, and require higher critical exposure. The depth of cure decreases with increasing concentration of photoinitiator. The critical exposure decreases firstly with the increase of photoinitiator concentration, and then tends to be flat.

In order to deepen the understanding of the mechanism and process of coal and gas outburst, the correlation between coal and gas outburst and geological structure is studied in combination with literature review and case analysis. Then the influence of geological structure on outburst control factors is analyzed from three aspects of stress, gas and coal attributes. Finally, the geological tectonic process is considered as the incubation stage of the outburst, and the research direction of outburst mechanism and prevention methods in future is puts forward. The results show that geological structure not only changes the stress and gas environment of coal seam, but also changes the geometric shape of coal seam and physical structure of coal. The influence of coal physical structure change in geological structure area on outburst should be paid enough attention to. Taking the geological structure process into the outburst preparation stage, the geological structure process refers to the process of tectonic movement changing the stress and gas occurrence state of the original coal seam and the physical structure transformation of the coal seam. Based on the geological information of outburst, the formation and characteristics of tectonic coal, and the internal relationship between outburst and tectonic coal, the research directions of coal and gas outburst mechanism and prevention methods are summarized.

At present, DC transmission is developing toward high voltage and large capacity technology. Its advantages in longdistance transmission, cross-region networking and flexible dispatch are becoming more and more obvious, but at the same time, abnormal outage of DC system caused by critical equipment failure of converter station has a greater impact on power system. Therefore, it is of great significance to enhance the perception of critical DC equipment, to predict and handle the faults of critical DC equipment in advance, to reduce abnormal outage of DC system and to improve power supply reliability. Taking the multi-protocol wireless data of Ningxia State Grid converter station as an example, an improved particle swarm algorithm based on the gray wolf algorithm is proposed. The experimental results show that the particle swarm-wolf algorithm can more accurately predict the monitoring data of the converter station, reduce the prediction error, and provide a basis for the operation and maintenance of the converter station in the future.

Four kinds of test steels with different vanadium and nitrogen contents were smelted and cast by VN16 and FeV80 vanadium microalloying method. The effects of vanadium and nitrogen contents on the microstructure, strength and toughness of high strength hot-rolled steel plate were studied. The results show that the microstructure of test steels is ferrite and pearlite. When the nitrogen content is very low, the ferrite grain of vanadium microalloyed steel is coarse. Although increasing vanadium can refine the ferrite grain, the degree of refinement is not large. The ferrite grain of vanadium-nitrogen microalloyed steel is fine, and the increase of nitrogen can obviously refine the ferrite grain. The higher the nitrogen content, the greater the refinement degree. The nitrogen content is the main factor affecting the ferrite grain refinement. In vanadium microalloyed steel, the second phase particles are mainly precipitated in ferrite, which plays a strong role in precipitation strengthening, and the fine grain strengthening is relatively weak, resulting in the obvious increase of steel strength and decrease of toughness and plasticity when vanadium is added. In vanadium-nitrogen microalloyed steel, increasing nitrogen can effectively promote the precipitation of second phase particles in austenite, significantly enhance the fine grain strengthening effect of vanadium and weaken the precipitation strengthening effect, resulting in the improvement of steel strength, toughness and plasticity. The higher the nitrogen content, the more significant the strengthening effect.

As a core key component of new energy passenger vehicles, permanent magnet motor that add rare earth minerals such as dysprosium and terbium can improve the basic characteristics such as remanence and coercivity. With the acceleration of the comprehensive electrification of vehicles, the prominent contradiction between supply and demand of rare earth minerals is highlighted. A dynamic material flow analysis method is used in this study to predict the demand for praseodymium, neodymium, dysprosium, and terbium resources in China's passenger car electrification transformation. This analysis identifies the supply and demand risks for different rare earth resources. To promote the sustainable development of electric vehicles and sustainable utilization of rare earth resources in China, the study suggests coordinating the promotion of resource security and the dual carbon strategy, exploring resource reduction and alternative technologies, and scientifically promoting independent mining and international cooperation.

Walking aids can effectively ameliorate or keep the walking ability and balance ability of the elderly individuals. However, long-term assisted walking will have adverse effects on the musculoskeletal system of the upper extremities. This paper reviews the effects of bimanual-operated unpowered walking aids on the user's upper extremities from the perspectives of kinematics, kinetics and electromyography, along with a brief overview of the relationship between unpowered walking aids use and upper extremities injuries. The effects of changing the walking aids construction on the upper extremities are compared and further summarized. This work could provide a theoretical reference for the personalized designing and instructions of walking aids for the elderly individuals.

Innovation, promotion and application of green and low-carbon technology is an important measure to implement the "double carbon" goal, and it is also an important driving force to promote the green and low-carbon transformation of industry and achieve high-quality economic development. Using the system dynamics model, this paper takes 2015—2021 as the simulation period, explores the coupling model and driving mechanism of green patent output based on the three dimensions of government, enterprise, and university and research, verifies the validity of the model through historical test and sensitivity analysis, and simulates the change trend of green patent output in the future. The results show as follows. The three subsystems of government, enterprise, and university and research affect the output of green patents through different driving paths. Among all the driving paths, increasing the intensity of government's investment in university and research or scientific and technological innovation, enterprises' investment in industry, university and research, and financial institutions' investment in university and research can promote the increase of green patent output in the future. Therefore, this paper suggests that under the comprehensive action of the government, enterprises, and university and research, and guided by the green low-carbon industry and the "dual carbon" goal, taking green technology innovation as the means of development will further accelerate the completion of the "dual carbon" goal.

With the goal of carbon peaking and carbon neutralization in China, the demand for critical minerals in new energy transformation will grow rapidly. Four typical new energy related minerals of copper, lithium, cobalt and nickel are taken as the research objects in this study. This study analyzes the current situation and problems of new energy related minerals from four aspects: reserves security, supply and demand security, trade security and investment security. It is found that the supply security of new energy related minerals in China is faced with the problems of insufficient domestic reserves and contradiction between supply and demand. In addition, the centralized geographical distribution of imports and unstable production capacity of overseas mining investment projects also threaten the supply security of China’s new energy related minerals. In order to ensure the safe and stable supply of new energy minerals, the Chinese government and mining enterprises should improve the supply security capabilities domestically and overseas.
On the domestic front, the government and mining enterprises should strengthen the exploration and development of domestic resources and accelerate the layout of the whole mining industry chain. On the foreign side, the government and mining enterprises should expand overseas trade and investment cooperation and innovate the investment model of overseas mining projects.

The coal quality test data of about 150 thermal power enterprises are selected, and the coal calorific value prediction model based on L-M algorithm is built by analyzing the ubiquitous coal quality test data information. The experimental results show that: (1) the linear relationships between calorific value and carbon, ash are significant respectively, and the correlation coefficients are 0.8768 and 0.6880; (2) principal component analysis(PCA) method excavates the information of the principal component eigenvalue, characteristic matrix and score, which could realize the dimension reduction effect from six-dimensional matrix to four-dimensional matrix, and enhance the convergence stability of neural network in the training process; (3) based on the L-M algorithm, the training coefficient , verification coefficient and test coefficient of the Levenberg-Marquardt back propagation neural network prediction method(LMBP) model are 0.9957, 0.9942 and 0.9963 respectively, and the overall coefficient is 0.9931. Through the further verification of 20 groups of data to be tested, the LMBP prediction model is more reliable, the prediction accuracy is higher, and better to meet the actual forecast demand.

The leaf traits of Populus simonii × P.euphratica with different planting years were investigated and the suitable indexes for the adaptability evaluation of different forest ages was screened, which shall provide the theoretical basis for evaluating the adaptability of Populus simonii × P. euphratica in desert oasis. The leaf shape of Populus simonii × P. euphratica is mainly lanceolate and oval; the net photosynthetic rate, stomatal conductance, transpiration rate and intercellular CO₂ concentration of Populus simonii × P.euphratica increase with the growth age, and there are significant differences between different forest ages (P＜0.05), and the leaf traits of Populus euphratica have extremely significant correlations with each other (P<0.01), Net photosynthetic rate and stomatal conductance can be used as the main factors to evaluate leaf traits of Populus euphratica at different growth ages, the results of evaluating its leaf traits are more reliable with the increases of growth age.

As an important part of cultivating innovative talents and exporting scientific and technological achievements, academic departments have become the key factors affecting national scientific and technological competitiveness. Based on the five dimensions of resource cohesion, scientific research output, achievement transformation, international influence and talent guarantee, this paper constructs the "five forces evaluation" model, conducts a comparative study on the characteristics of scientific and technological activities of Chinese and American academic departments, and puts forward suggestions to strengthen the competitiveness of Chinese academic departments.

The prediction of forest fuel moisture content is of great significance to the forecast of forest fire risk and the protection of forest ecosystem. Based on the systematic analyses of the key meteorological factors affecting the forest fuel moisture content, the prediction models of the live and dead fuels moisture content of four different forest types, namely, Pinus yunnanensis (shady slope), Pinus yunnanensis (sunny slope), Pinus armandii and Platycladus orientalis, were established utilizing the methods of multiple regression, classification and regression tree (CART), etc. The results showed that the average relative errors of the multiple regression model in predicting the live and dead fuels moisture content in different forest types were between 5.90%~6.60% and 20.1%~36.9%, respectively. CART model was found applicable for the prediction of forest fuel moisture content based on meteorological factors. The optimal average relative errors of the prediction of live fuels moisture content (5.38%~7.00%) were significantly lower than that of dead fuels (22.88%~26.64%), which was consistent with the multiple regression model and generally had higher accuracies. Besides, the problem that the live fuel moisture content of Pinus yunnanensis (sunny slope) cannot be predicted was also solved. The research results are expected to provide some theoretical supports for the establishment and accuracy improvement of further prediction model of forest fuel moisture content and even the forecast model of forest fire risk.

Knee osteoarthritis (KOA) is the most common disease of the sports system, with a high disability rate, and is an urgent public health problem in China at present. Through a prospective clinical study, this study took KOA patients as the research objects, and aimed to compare the efficacy and recovery of domestic 3D printed orthopedic insoles and drug conservative treatment for different degrees of KOA patients. Indicators included the tibial varus angle (TBVA), knee joint range of motion (ROM), subjective score of the International Knee Joint Literature Committee (IKDC), pain visual simulation score (VAS), and clinical effectiveness, Knee joint injury and osteoarthritis score (KOOS). The results showed that the TBVA, KOOS-symptoms, KOOS-activities of daily living, and KOOS-quality of life in the orthopedic group were significantly lower than those in the medication group, while the IKDC score was significantly higher than those in the medication group. For patients with moderate KOA, the ROM and clinical effective rate in the orthopedic group were significantly higher than those in the medication group. It showed that the efficacy and prognosis of domestic 3D printed orthopedic insoles in the treatment of moderate and severe KOA were better than that of drug conservative treatment, and its efficacy was better for patients with moderate KOA.

The level of urban public service supply is an important factor affecting the healthy and stable development of a city, and its good spatial pattern helps to rationally allocate public resources and promote win-win development of urban cooperation. However, at present, the research on the spatial pattern and influencing factors of China's urban public service supply level is still insufficient. Therefore, this paper attempts to construct an index system to measure the level and spatial pattern of urban public service supply, and analyzes the spatial effect and influencing factors of urban public service supply level with the help of the spatial Durbin model. The research shows that: (1) From the perspective of time, the level of public service supply in Chinese cities generally shows a steady growth trend; from the perspective of spatial pattern, the level range of public service supply in most cities is at the lower and lowest levels, and there are differences. (2) The level of public service supply in Chinese cities shows obvious global and local spatial autocorrelation, and the convergence characteristics of spatial clubs are obvious. (3) The regression results of the spatial Durbin model show that the level of urban public service supply has a positive spillover effect in space; urban government governance capacity, population density, population urbanization rate, economic development level and industrial structure have a positive effect on cities in the region The level of public service supply, of which population density has the greatest impact, can increase the level of urban public service supply in the region by 11.5%. The population density and population urbanization rate have a significant negative effect on the supply level of public services in surrounding cities, which will cause the supply level of public services in surrounding cities to drop by 25.1% and 9.44%, respectively.

Deepwater jacket platform has found wide application in the South China Sea. Real-time and accurate acquisition of the forcing state of concerned members of the deepwater jacket platform can assess the safety status of the platform in service. Using the digital twinning methodology, this paper presents an axial force inversion method of deepwater jacket platform and carries out field verification on the LF 15-1 platform which is the largest jacket in Asia. Firstly, a digital twinning framework is established through an on-field monitoring system. Then, based on SACS simulation database and sea state interpolation algorithm, a procedure to calculate the axial force of concerned member under monitoring is developed. Finally, feasibility of the algorithm is verified on the LF 15-1 deepwater jacket platform with the prototype of monitored sea state data. The research results can provide reference for operation and maintenance of deepwater jacket platforms.

The cross-regional marine data cooperation has presently exhibited a certain foundation, however, due to the historical background, scientific and technical level, and safety factors, there are still some gaps in achieving "an accessible ocean"——a goal of the United Nations Decade of Ocean Science for Sustainable Development (2021-2030). By summarzing the development partnership and participation in global governance between China and the EU, this paper introduces the background of the emergence of CEMDnet and analyzes the status of cross-regional marine data cooperation. On this basis it proposes a replicable and extensible cross-regional data cooperation model and explains its effectiveness. Suggestions for future cross-regional marine data cooperation are put forward as well.

Aiming at the problems of current SG-CIM (state grid-common information model) such as difficult to achieve automatic update iteration and low efficient mining of new elements, an SG-CIM model automatic mapping technology based on BERT model and blocking filtering is proposed. On the basis of the existing SG-CIM, an SG-CIM knowledge map and data table knowledge graph are constructed at first. Secondly, by studying the entity alignment method based on BERT model and blocking filtering, the mapping relationship between the two knowledge graphs is established. Finally, the effectiveness of the proposed method is verified by experimental analysis of the text mapping effect. Results show that the accuracy of BERT model after finetuning on a self-made data set is more than 95%. This method lays a foundation for subsequent mining of new elements and automatic updating iteration of SG-CIM.

In order to intelligently meet the business requirements of the SG-CIM model designed by the State Grid Corporation of China and improve the quality and sharing of the graph data, this paper proposes a graph structure mapping model based on gaph attention network(GAT). First of all, using the data of SG-CIM model, an SG-CIM knowledge graph and a database table knowledge graph are constructed. The entities embedding in each graph are learned separately through the GAN, which are then embeded into a unified vector space. Finally, the graph structure mapping results of the two graphs are obtained after calculating the similarities based on the distances between the entity vectors. Experiments show that the proposed model achieves good results in automatic mapping of SG-CIM model.

In the process of deep learning network training, most existing methods aim to improve the model effect focus on the network. However, to improve the effect and accuracy of the model it is necessary to pay attention to the characteristics of the data. In this paper, batch-attention, a new training framework for deep learning model, is proposed, which changes the original training method from the data level. It is shown that the method can coordinate overfitting and underfitting of the deep learning model. Experimental comparisons using Resnet34, TNT and efficientnet-b7 on Cifar10 and Cifar100 data sets respectively prove that the batch-attention model has improved both accuracy and F1-score in the test set compared with the benchmark model. In addition, the mechanism of batch-attention is further analyzed in the follow-up experiment.

Risk prevention and hidden danger identification are important to urban safety. According to current laws and regulations on safety production and emergency management in China, the responsible subjects of safety management are those departments that are directly involved in risks and hidden dangers. In a comprehensive city there are great differences in the types and distributions of potential risks among industries. These differences should be taken into account so that targeted risk prevention and control measures can be formulated accordingly. This paper studies the distribution differences of potential safety risks in industries, proposes a concept of industry safety risk structure, defines an industry safety risk vector, and gives the quantification indexes of industry risk entropy and risk specificity by means of information entropy theory. Based on the analysis results of tens of thousands of cases it is found that determination of safety risk vector, industry risk entropy, and risk specificity is conducive to the comparative study of safety risks within and between industries and provides a basis for the classified monitoring of industrial safety risks.

Prestressed cable-stayed bridges are prone to crack due to various loads and temperatures. The traditional finite element method can not accurately describe the generation and expansion of cracks. In this paper, numerical simulation of a prestressed bridge panel is carried out to analyze the origin and long-term evolution of cracks based on the continuousdiscontinuous element method and multi physical field coupling. The results show that the gravity of the bridge panel itself, the cable force and the degree of bending and straightness of the bridge are not the main reasons for cracks of the bridge and that the prestress of the reinforcement hinders the cracks to a certain extent. The long-term cyclic effect of temperature plays a leading role in the initial crack of the bridge panels, and repeated loading of vehicle dynamic load in the later period makes the initial cracks further expand. The research results of this paper can provide a certain theoretical reference for analyzing causes of
bridge cracks.

With the continuous acceleration of urbanization, the impact of human activities on geological hazards has gradually increased, and people's lives and property safety have been threatened. Controlling geological hazards cannot delay. In this paper, nine factors such as slope gradient, relative elevation difference, slope direction, slope type, engineering geology groups, geomorphic type, rainfall, distance from rivers and distance from major traffic arteries are selected as evaluation indicators. The Information Value Model is used to evaluate the geological hazards susceptibility. The results show that: (1) This County can be divided into four types: extremely high susceptibility, high susceptibility, medium susceptibility and low susceptibility. Low susceptibility type is the largest, accounting for 64.64%, and extremely high susceptibility type is the smallest, accounting for 0.39%. (2) According to the verification, it can be seen that the density of geological hazards points in the extremely high areas and high areas is higher than that in medium susceptibility and low susceptibility areas, and the results are reasonable.

In this study, bioinformatics methods were used to preliminarily screen ischemic stroke (IS)-related differentially expressed genes (DEGs) and hub genes, and then predict potential IS therapeutics. DEGs were screened after transcriptome sequencing (RNA-Seq) in the cortex of the normal group and the bilateral internal carotid artery occlusion (BICAO) group. GO and KEGG enrichment analysis of DEGs were performed and protein interaction networks of DEGs were constructed, and key genes were obtained. Finally, IS related drugs were predicted according to the key genes. A total of 197 significant DEGs were obtained in this study, and enrichment analysis showed that these genes were mainly involved in metabolism, neuroactive ligandreceptor interactions, complement/coagulation cascade and biosynthesis of steroid hormones. DEGs have a close interrelationship, and among the genes most closely related, ORM1, SERPINA1 and GC all participate in the process of inflammation, oxidative stress and apoptosis, which are the key genes in the pathogenesis of IS. Therefore, inflammation, oxidative stress and apoptosis may be closely related to the occurrence and development of IS. It has potential clinical significance for drug treatment targeting hub genes such as ORM1, SERPINA1, and GC.

This study fully collects public data from industry authorities, uses sampling surveys and typical survey methods, and concludes that the total number of scientific and technological workers in China by the end of 2020 is 58.3578 million. Large as the scale is, there is still considerable room for improvement in talent intensity. The study argues that young people have become the main body of scientific and technological workers in China but their innovative and creative vitality is facing many constraints. Those with bachelor's degree or above have become the main body of the workers in China but strategic scientists and first-class innovative talents are lacking. The professional structure of Chinese workers adapting to the high-quality development of economy and society needs to be improved. Maintaining a reasonable structure of academic and vocational education is an urgent task. The sense of identity and professional recognition of scientific and technological workers in China is still insufficient and it is necessary to continue to exert efforts to promote the spirit of scientists and enhance the sense of professional honor and mission.