Using Google Earth to locate precisely the geographical location of 591 provincial traditional villages in Henan Province, the spatial correlation analysis of the social and natural factors, such as topography, population, economy, transportation network, etc. in Henan Province was conducted combining with ArcGIS 10.2 and SPSS 19.0. The results show that the traditional villages of Henan Province present the characteristics of the whole decentralized and local settlement in the spatial distribution, and there are two high density cores located in Pingdingshan and Anyang City. River system, traffic and population are the main factors affecting the distribution of traditional villages which are built along river, and distributed in the area of where the road traffic developed and the population is relatively sparse. The elevation, economy and urbanization rate are also the important factors affecting the development traditional villages, and the traditional villages are mostly distributed in the areas with low topography, medium level of economic development and urbanization rate. The climate is the reference factor of the traditional village′s foothold, whereas the precipitation and the temperature are not obvious with the traditional villages′ distribution.

To reflect the hospital scale and capacity of service more accurately, hospital scale is determined by size of residents, and the search radius is determined dynamically. The spatial accessibility of the main areas in Xi′an city is analyzed by using the original and the enhanced method. The results show the accessibility of main areas of Xi′an city is unequal, midwest is superior to the east, and the spatial accessibility of facilities decreases gradually from the northwest to the southeast. Accessibility is related to the density of street population around the hospital.With the similar hospital, the streets which have fiercer competition of the resource get low accessibility. Accessibility is also related to the hospital scale, under the similar resource competition, the streets with high level hospitals and convenient transportation get high accessibility. The enhanced method can present a more reasonable evaluation of the accessibility so that the differences of same level hospital could be judged efficiently.

Taking the Beijing-Tianjin-Hebei region as a case study, the development of coupling mechanism among tourism, urbanization and ecological environment of the city are analyzed. The coupling coordinative development and types among tourism, urbanization and ecological system were studied by building the tourism-urbanization-ecological evaluation index system and using the coupled coordination function and quantitative model. The result shows that coupling between tourism, urbanization and ecological environment system generally promoted from the imbalance to coordination from 2004 to 2013. Tourism industry is developing rapidly within the city, and it become more volatile. The urbanization level maintains steady growth. With the development of tourism and urbanization, ecological environmental problems are continuously emerging. The type of the coupling development is given priority to urbanization more than tourism in Beijing-Tianjin-Hebei region.

To investigate the effect of different sleep deprivations (SD) on the mood,learning and memory of mice, both multiple platform method and sleep deprivation tank method were used to observe the effects of the relative factors on the anxiety-like behavior,learning and memory.The following results were obtained.12 h SD and 24 h SD did not affect anxiety-like behavior, learning and memory in either of the above paradigms. The anxiety-like behavior was observed in mice subjected to 48 h SD via multiple platform method and the spatial memory was not affected，but sleep deprivation tank did not make mice appear anxiety-like behavior and spatial memory ability after 48 h SD. In the sleep deprivation tank experiment, a long-time SD could induce anxiety-like behavior, whereas the learning process of the mice slowed down and spatial memory was impaired after 3 weeks SD. Thus, deprivation tank is advantageous as an SD model for studies on human long-term sleep insufficiency.

Taking 156 healthy tourism destinations in ChangshaZhuzhouXiangtan urban agglomeration as research samples, applying spatial analysis methods such as nearest neighbor index, Ripley′s K(d) function, kernel density estimation and buffer analysis, the spatial structure and the spatial difference of different types of healthy tourism destinations were discussed, and the influencing factors were studied. The study found that healthy tourism resources in ChangZhuTan are rich, which can be divided into five basic types, that is forest health, water health, traditional Chinese medicine and so on. Healthy tourism destinations have significant agglomeration characteristics in ChangZhuTan. The healthy tourism destinations of the north is more than that of the south in ChangZhuTan, it is in the form of “V” shape circle structure. There is a high degree of gathering and a large number of oldage health care and rural healthy tourist destinations, the distribution of forest health and traditional Chinese medicine tourism is discrete, and the scale is large. The difference of natural resources is the internal driving force that affecting the spatial structure of the healthy tourism destinations, and traffic location, economic foundation and population density are important external thrust.

The outbreak of COVID-19 at the end of 2019 is spreading around the world, causing serious impact on socio-economic development and human health and safety. Clarification of the spatial-temporal spread of COVID-19 at individual and population levels is necessary for epidemic prevention and control as well as resource allocation. This study targeted on Shenzhen city which locates far away from the COVID-19 origin city of Wuhan but experienced high incidence of COVID-19. Based on the officially published and confirmed cases, manually collected case details and the related POI data of Shenzhen, the epidemiological characteristics, spatio-temporal evolution and prevention and control measures regarding COVID-19 in Shenzhen were analyzed through text analysis, mathematical statistics, spatial analysis and other methods. The results showed that: (1)the confirmed COVID-19 cases covered all age levels, mainly concentrated in the young adults. Most of them were the second generation of infection originating from the places out of Shenzhen, and they were mainly from family cluster transmission with “linear” migration and diffusion mode between cities. (2)The time evolution of epidemic experienced 4 stages: low incidence period, growing period, deceleration period and ending period. The number of cured cases presented the evolution process from slow growth to rapid growth. The time interval from onset to admission was mostly within 0~2 days, and the time interval from admission to diagnosis was about 1~3 days. (3)In terms of spatial distribution, the confirmed cases moved out mainly through two types: “directly from Hubei” and “stop by Hubei”, with the main purpose of visiting relatives during the Spring Festival. The spatial distribution of COVID-19 affected communities demonstrated “northeast to southwest” trend, mainly gathered in the southwest part around the “two cores”.(4)The overall risk distribution of the city was “two cores and three areas”. The high-risk areas were located in the south of Nanshan District and in the center of Futian District. Finally, combined with the situation of COVID-19, requirement of work recovery and the new risk from overseas, this study put forward an accurate prevention and control measure system based on the dimensions of “real-time, daily, normal”, “community, district, city” and “individual,family,society” from the perspective of “time-space-human” mutual feedback and integration.

Aiming at severe weather conditions, traffic flow predition modd based on random forest was proposed.Based on taxi data and weather conditions in New York city in 2016, screening the original GPS data layer by layer, the data that meet the definition of severe weather conditions are screened out. Based on the random forest regression method, the traffic flow prediction model under severe weather is studied, and the performance of the model is improved by adjusting the super parameters of the model. At the same time, the performance of random forest model is compared with that of BP neural network model and decision tree model, and the experimental results of random forest prediction model are better.

Based on the data of A-grade scenic spots of China in 2016, the number, grade structure and spatial distribution of A-grade scenic spots were studied by the means of GIS spatial analysis and some quantitative analysis methods including the nearest neighbor index, Gini coefficient and Anselin Local Moran I. The results showed that the development of A-grade scenic spots in China has entered into the stage of quality enhancement instead of the stage of quantity enlargement. The spatial distribution of A-grade scenic spots and population in China are overlapped spatially, 87% of A-grade scenic spots located in the east of Hu Huanyong line and formed three concentrated areas, including Beijing-Tianjin-Hebei region, Yangtze River Delta and Shandong Peninsula. Tourist receipts and tourism revenue are significantly and positively related to the number of A-grade scenic spots at provincial scale, especially related to the number of 5A and 4A scenic spots. Based on the above conclusions, five proposals for the developing of A-grade scenic spots in China are put forward, that is, quality improvement of scenic spots, priority development of A grade scenic spots in western regions, regional tourism cooperation, priority development of transportation and tourist products innovation of scenic spots.

To research the improving effects of Tai Chi exercise on the glucose Metabolism to abnormal glycoMetabolism patients, PubMed, WOS, EBSCO, Embase, Cochrane, CNKI, WanFang and SinoMed electronic databases were retrieved, and the Metaanalysis was conducted through RevMan 5.3 and StataSE 12.0 software. Tai Chi exercise can significantly decrease FBG (SMD=-0.85，95%CI is-1.17～-0.52，P＜0.000 1), 2 h PBG(MD=-1.03，95%CI is -1.34～-0.73，P＜0.000 01) ,HOMA(MD= -0.69，95%CI is-0.06～-1.31，P=0.03) and HbA1c（MD= -0.76，95%CI is-1.38～-0.14，P=0.02）, while can not on TG and TC(P＞0.05).Meta regression analysis indicated that the Tai Chi exercise type might be the main source of FBG combined effect heterogeneity.So Tai Chi exercise could be significantly improve glucose Metabolism function, insulin sensitivity compared to control group, and Tai Chi exercise type could be influence the improve effect of improving FBG.

Taking 6 819 traditional village lists published by the government as the research object, the spatial distribution characteristics of Chinese traditional villages and its influencing factors were studied using ArcGIS spatial analysis techniques and methods. The results show that Chinese traditional villages present the distribution characteristics of “core-edge” in space, and formed four agglomeration areas. Chinese traditional villages have strong imbalance in the spatial distribution of each provinces (autonomous regions, municipalities),cities and counties, and which are mostly distributed in the provincial border areas. The spatial distribution of Chinese traditional villages is affected by both natural environment and social environment, which mainly distributed in the valley, basin, low mountain, hilly and middle mountain far away from the main grain producing areas, and in the sunny slope areas or riverside areas far away from the central city and the economic and transportation less developed. The main factors influencing the spatial distribution of Chinese traditional villages from strong to weak are: rural per capita disposable income, slope direction, population density, river network density, distance from central city, elevation, agricultural land, traffic density.

Object detection is one of the core tasks in the field of computer vision. In recent years, with the rapid development of deep learning, the object detection technology based on deep learning has become the very popular mainstream algorithm. It has been widely used in many fields, such as face detection, vehicle detection, pedestrian detection, and unmanned driving, etc.. This paper systematically summarizes the current research progress of deep learning-based object detection algorithms, and thoroughly analyzes the advantages and disadvantages of each algorithm and its results on the datasets VOC2007 and COCO. Finally, the future development of object detection based on deep learning is also discussed in this paper.

The data of confirmed cases, death cases and cured cases of coronavirus disease 2019 (COVID-19) in seven epidemic seriously affected countries (Italy, South Korea, the United Kingdom, the United States, France, Spain, Germany) were obtained from the System Science and Engineering Center at Johns Hopkins University. Data were collected between March 4, 2020 and April 4, 2020. Traditional SIR model was used and improved by adding a new parameter to characterize the infection coefficient changes over time, and regression analysis was introduced to estimate the parameters. Based on the improved SIR model, the development of COVID-19 in 7 countries were simulated and predicted, and the effects of contact rate control measures of different countries on epidemic development were analyzed. Results showed that the improved SIR model was reliable for analyzing the epidemic trend of COVID-19. Apart from the United Kingdom and the United States, the other five countries have had their pandemic under initial control, while the United Kingdom and the United States need to do more to reduce the pandemic damage. Our finding confirmed the importance of reducing population contact rate in COVID-19 prevention and control, such as reducing assembly, avoiding contact and centralized admission, so as to provide reference for the subsequent epidemic prevention and control.

One new species of Hyboella Hancock from Guangxi was described. Type specimens were deposited in the Institute of Zoology, Shaanxi Normal University..

A new species of the genus Phlaeoba Stal is reported. The type specimens are deposited in the Institute of Zoology, Shaanxi Normal University.Phlaeoba jiuwanshanensis sp. nov. ( Figs. 1)This new species is allied to phlaeoba tenebrosa walker, but differs in : (1) In male, antenna reaching beyond the hind margin of pronotum; (2) Lateral keels of pronotum distinctly; (3) With numerous short longitudinal keels and large tubercles in the disc of pronotum; (4) Length of prozona longer than the length of metazoan about 1.3 times(♂) or 1.4 times (♀); (5) Interspace of mesosternal lobes nearly square; (6) Hind wing transparent, without light blue green or smoke color. Length of body: ♂ 18 mm; ♀ 25.5～26.5 mm.Length of pronotum: ♂ 5 mm; ♀ 6～7 mm.Length of elytra: ♂ 18 mm; ♀ 21～23 mm.Length of hind femur: ♂ 16 mm; ♀ 15～17 mm.Holotype ♀, Guangxi: Locheng, 08-2003; paratypes 1♂3♀, Guangxi: Locheng, 08-2003, collected by Deng Weian.

Moving coil transducers have been widely applied to such fields as ship noise simulation and sonar system calibration because of their small size, ultra-low frequency, and ultra-wideband emission. This paper summarized the structure and performance of moving coil transducer. The principle of ultra-low frequency and ultra-wideband emission was described in this paper. The research work of domestic and foreign scholars on the optimization of the driving magnetic circuit, the expansion of the working bandwidth, and the improvement of the working depth were also reviewed. Several hot issues in the research of moving coil transducer, such as nonlinear distortion and the influence of acoustic cavity on the performance, were discussed. It was proposed that optimizing the driving magnetic circuit to reduce the nonlinearity of the output force and improving the impedance matching between the moving coil transducer and the power amplifier can reduce the waveform distortion and harmonic distortion. The fluctuation of the source level can be suppressed by filling the gas with small characteristic impedance into the acoustic cavity. The future trend of moving coil transducer was also prospected. The research of moving coil transducer should focus on improving the ultra-low frequency acoustic radiation performance in large depth environment, increasing the continuous working time and reliability, and reducing the nonlinear distortion, so as to meet the application requirements.

Infrared polarization imaging detection technology introduces polarization information on the basis of traditional intensity information, which can effectively improve target detection and recognition capabilities under specific conditions. It has advantages such as high signal-to-noise ratio, anti camouflage, and anti-interference, and has broad application potential and good development prospects in target reconnaissance, detection, and strike fields. This article first introduces the theory of surface polarization of objects and related phenomena, especially the discovery of high-temperature polarization phenomenon of targets, which expands new fields for polarization detection applications.Based on the theory of target polarization, the research results of target polarization characteristics under different environments and application backgrounds were analyzed. Secondly, the development of infrared polarization detectors and the latest progress in target infrared polarization imaging detection in recent years were reviewed. The new requirements for infrared polarization detection technology in the current complex battlefield environment were summarized, including breaking through the bottleneck of real-time high-precision imaging technology, strengthening cloud and fog penetration, and anti occlusion interference performance.Finally, based on the summary of the target polarization mechanism, target polarization characteristics, and the development trend of polarization detector technology, it is proposed to deepen the theoretical research on target surface polarization, promote the development of high-precision infrared polarization detector preparation technology, explore multi-dimensional information fusion processing, and further look forward to the future development and application prospects of infrared polarization detection technology in military fields such as complex target recognition, anti stealth operations, and battlefield monitoring.

Polarization spectral imaging technology provides an effective solution to the imaging problems in complex scenes by combining intensity, polarization, and spectral information. Division-of-focal-plane polarization spectral imaging technology has become a significant development direction in this field due to its high compactness and strong real-time performance. This paper first reviews the development history of polarization spectral imaging technology and systematically compares the advantages and disadvantages of related technologies. Then, it focuses on the research progress of the division-of-focal-plane polarization spectral imaging system, providing a detailed overview of polarization spectral splitting elements, polarization spectral demosaicking algorithms, and existing polarization spectral image databases. It also systematically summarizes the core advantages of this technology, including high compactness, strong real-time performance, and low power consumption. Finally, it summarizes the applications of polarization spectral imaging technology in military reconnaissance, space exploration, medical diagnosis, and remote sensing detection. The analysis indicates that this technology has broad prospects in fields such as target detection, environmental monitoring, and medical diagnosis, but it still faces challenges such as low spatial resolution and insufficient accuracy in reconstructing polarization information currently. Based on this, future research should focus on optimizing the design and fabrication of polarization spectral splitting elements, improving demosaicking algorithms for high-quality image restoration, and further expanding its application capabilities in dynamic scenes and complex environments.

In order to improve the ability of ultrasonic guided wave technology in accurately detecting damage location, size and shape in plate-like structures, the low-resolution imaging results of the total focusing method(TFM) and the multi-scale deep learning algorithm model are combined to study a high-precision imaging method for targeting two type of damage:round holes and cracks.The high-precision imaging algorithm based on deep learning is composed of two parts: a convolutional neural network and a deconvolutional neural network. The multi-scale analysis, nonlinear enhancement and multi-level fusion functions of the neural network are used to improve the resolution. On the basis of the imaging results of the all-focus imaging algorithm, a network training database is constructed, and the trained network is used to detect and verify the two cases of circular hole-crack double damage and circular hole-circular hole double damage in the plate. The results show that the imaging method has high imaging accuracy, and can further obtain the fine features of the damage based on the precise location of the damage.

PsaA and PsaB are central proteins in photosystem Ⅰ, and play important roles in plant photosynthesis and stress regulation. Tobacco (Nicotiana tabacum L.) is a model crop for plant functional genomics research, while there are few studies on the functions of PsaA and PsaB genes. In order to understand the response of tobacco PsaA/PsaB genes to stress, the PsaA/PsaB gene family in tobacco genome were identified, and their physicochemical properties, subcellular localization, phylogenetic evolution, motifs and promoter regulatory elements were analyzed. The results showed that there are 27 PsaA/PsaB genes in tobacco. Compared with Arabidopsis thaliana, the tobacco PsaA/PsaB gene family undergone significant expansion and can be classified into three subfamilies based on their phylogenetic and structural features. The promoters of tobacco PsaA/PsaB genes contain numerous cis-regulatory elements responsive to light, low temperature, drought and plant hormones. RT-qPCR analysis revealed that most tobacco PsaA/PsaB genes were up-regulated under low temperature stress (8 up-regulated genes) and down-regulated under polyethylene glycol and jasmonic acid methyl ester stresses(8 and 7 down-regulated genes respectively). After potato virus Y(PVY) and tobacco mosaic virus (TMV) infection, the expression of most tobacco PsaA/PsaB genes were down-regulated. The down-regulated genes in the lower mesophyll and vein tissues were 19 and 17 after PVY infection, and 9 genes were down-regulated after TMV infection. In conclusion, tobacco PsaA/PsaB genes are involved in the response process of tobacco to various abiotic stresses, and the study results provide a reference for further exploring the role of PsaA/PsaB genes in regulating plant response to stress.

To further explore the law of hydraulic properties of overland flow, the hydrodynamic characteristics of overland flow under different flow rates and slopes with different roughness (0.2~0.6 mm, 0.6~1 mm, 1~1.4 mm, 1.4~2 mm, 2~3 mm particle size and smooth control group) were studied by the indoor fixed-bed water scouring test. The results show that the increase of the underlying surface roughness slows down the overland flow velocity and increases the water depth. The flow velocity and water depth are well related to the flow, slope, and roughness factors as a power function. The Reynolds number reaches the maximum value in the control group, and the flow pattern tends to be slow flow with increasing roughness. The resistance coefficient positively changes with roughness and is in a good regression relationship with the power function of flow, slope, and roughness factors. The calculated runoff shear stress is well related to the measured runoff shear stress on the smooth underlying surface, and the increase of roughness has a certain effect on the increase of measured runoff shear stress. The results are significant for a deeper understanding of soil erosion mechanisms and slope erosion control.

Though online reviews on social media platforms have been widely used in tourism research as data analytical sources in recent years, how they can be applied to destination recommendation needs further investigation.The review data of 239 5A scenic spots in China was retrieved from ctrip.com by Python programming and web-crawling technology. Natural language processing and deep learning technologies including BERT (Bidirectional Encoder Representations from Transformers) and word embedding were then imported to build a destination recommendation system for tourist destinations. The model was trained and validated on a dataset containing 57 360 reviews, with a classification accuracy of around 78% reached on 14 340 pieces of test data. Experimental results show that, with the aid of other tourists’ travel experiences and image perception, the proposed model can facilitate potential tourists in finding their ideal destinations to explore the first step of itinerary planning. The findings of this study extend the research scope of online reviews within tourism and hospitality and provide new insights into pre-trip travel counseling.

Accelerating the transformation of resource-based cities is an inevitable requirement for achieving high-quality economic development. In combination with the energy consumption structure of “coal is the largest” in China, 15 coal resource-exhausted cities were selected as the research objects, a three-dimensional indicator system of economic development, social welfare and ecological environment was built, the transformation performances of 15 cities during the planning period of the 《National Sustainable Development Plan for Resource based Cities (2013-2020)》(hereinafter referred to as the Plan) were quantitatively evaluated, and the obstacle factors affecting urban transformation were analyzed. The results indicated that:1) There was a significant spatiotemporal difference in transformation performances. In terms of space, the overall performance was generally lower than the average value of the national and provincial performance, and there were significant regional differences before and after the transformation. In the early stage, the western and northeastern regions were higher, while in the end, the central and eastern regions were higher. In terms of time, the overall performance showed a slow growth trend, but the dimensions of economic development were generally negative, while the dimensions of social welfare and ecological environment were generally positive.2) The transformation process could be divided into four categories, that is, economic dominance, balanced development, social welfare dominance, and ecological environment dominance.3) During the planning period of the four types of cities, there were differences and similarities in the obstacle factors. The six significant obstacle factors all cover three dimensions, and the ecological environment was the biggest pain point for transformation and development. It showed that the Plan had achieved remarkable results, but the transformation of coal resource-exhausted cities had not been completely completed, and follow-up policy support was still needed.

Graph convolutional neural network (GCN) has emerged as the intersection of graph theory and deep learning, becoming the hotspot research field of machine learning.Therefore, a comprehensive overview of the GCN is provided, and the available studies of GCN into two typical categories are summarized: spectral-based methods and spatial-based methods.These two typical types of GCN models are extensively discussed, the fundamental theoretical underpinnings of the graph convolution operations are delved into, diverse applications of GCN across various domains are showcased, the major challenges encountered by GCN are summarized, and valuable insights into the future trends of GCN advancement are offerred. Additionally, the potential utilization of GCN in butterfly recognition tasks is investigated, particularly in identifying butterfly species by leveraging images captured in natural habitats.

The edible quality recovery of kiwifruit treated by 1-methylcyclopropene was researched. ‘Qinmei’ kiwifruits were treated with 0.5 μL/L 1-MCP for 24 h during the period of pre-cooling, after 50 days cold storage at 0 ℃and returned it to room temperature, then they were treated by 0.008,0.04,0.08 mmol/L ethylene (Eth), 0.1,0.5,1.0 mmol/L salicylic acid (SA) and 0.02,0.1,0.2 mmol/L methyl jasmonate (MeJA) to recover for the quality. After the treatment the ethylene release rate, respiration rate, firmness, soluble solids, titratable acid and vitamin C content the kiwifruits placed at 20 ℃ for 7 days later, were detected. The results suggested that ethylene, salicylic acid, methyl Jasmonate promote normal ripen of kiwifruit treated by 1-MCP.Additionally,the quality of kiwifruit treated by 0.04 mmol/L ethylene, 0.5 mmol/L salicylic acid, 0.1 mmol/L methyl jasmonate treatment was better, and the treatment of 0.4 mmol/L ethylene was simple and feasible.

The resilience and efficiency of the inbound tourism economy are two significant factors affecting the economic growth recovery and high-quality development of inbound tourism.The entropy method and the DEA-Tobit model were used to measure the resilience level of Chinas inbound tourism economy from 2010 to 2019, the temporal and spatial pattern and obstacle factors were analyzed to explore the impact of resilience on the economic efficiency of inbound tourism. In the end, the growth recovery mechanism of inbound tourism was constructed.The results show that: the overall resilience of Chinas inbound tourism economy is improving, and areas of high resilience gradually spread from the eastern coast to the central and western regions. However, the national average is only 0.246 7, which has a large room for improvement. The positive spatial autocorrelation of inbound tourism economic resilience weakens gradually. The radiation effect of high-high areas and the diffusion effect of low-low areas decrease, while the polarization effect of high-low areas and the hollow effect of low-high areas increase. The main obstacle factors affecting the economic resilience of inbound tourism include the number of inbound tourists, inbound tourism income, economic development level, industrial structure level, market development and openness. When the economic resilience of inbound tourism increases by 1%, its efficiency increases by 0.243 2%. The economic resilience and efficiency of inbound tourism play a role in promoting the growth recovery of inbound tourism.

Aiming at the problems of low cutting efficiency of ultrasonic bone scalpel and the generation of thermal damage of bone tissue during surgery, a high-capacity ultrasonic bone scalpel with a secondary amplification structure was designed. Based on the equivalent length method of standing wave theory and finite element simulation, the design and optimization of the secondary amplified structure were carried out, and the vibration performance was tested and the bone cutting test was conducted. The results show that the resonance frequency of the ultrasonic bone scalpel with secondary amplification structure is 23 306 Hz, the amplitude is 140 μm, and the bone cutting surface is flat and damage-free, which meets the needs of clinical surgery.

To study the variations of phylogenetic diversity and species diversity of woody plant communities in Karst areas under different terrains and their influencing factors, woody plants in different terrains within the Maolan Dynamic Plot of Karst Forest Eco-system in South China were selected as the research objects. Utilizing the hierarchical partitioning (HP) method and Pearson correlation analysis, it examined the changing trends of diversity indices under different terrains (depression, valley, hillside, saddle, ridge and summit), the key terrain factors driving the diversity indices, and the interrelationship between species diversity and phylogenetic diversity. The results demonstrate that: 1)There is a significant difference in the community species richness index between depressions and saddles (P<0.05), while there is no significant difference in the community Pielou evenness index and Simpson dominance index among the six terrains. The Faith’s phylogenetic diversity index and the mean nearest taxon phylogenetic distance show significant differences between depressions and saddles. The mean pair phylogenetic distance shows a significant difference between hillsides and depressions,valleys. 2)The relative influence of aspect on the diversity indices is the largest and plays a leading role, followed by slope, and the influence of four topographic factors on the diversity indices is not significant.3)Species richness index is significantly positively correlated with Faith’s phylogenetic diversity index (P<0.000 1), significantly negatively correlated with mean nearest taxon phylogenetic distance and Simpson dominance index. Faith’s phylogenetic diversity index is significantly negatively correlated with mean nearest taxon phylogenetic distance. This study reveals that different terrains in the Maolan Karst area have different effects on species diversity and phylogenetic diversity, and the correlation between species diversity and phylogenetic diversity is not high. The aspect and slope jointly drive the variations of species diversity and phylogenetic diversity.

Photocatalytic technique is an effective method to solve the problems of energy conversion and environmental remediation, and graphitic carbon nitride (g-C₃N₄) has been considered as a promising photocatalytic material. However, the high carrier recombination rate severely limits the photocatalytic activity of g-C₃N₄. Constructing core-shell structure to form heterojunction with tight connection interfaces and large contact area has proved to be an excellent strategy to improve the carrier separation efficiency. Therefore, the research on core-shell structured g-C₃N₄-based heterojunction photocatalysis becomes a hot spot. In this review, the main functions of core-shell structure and the applications of core-shell structured materials are introduced. The performance and advantages of g-C₃N₄-based core-shell heterojunction photocatalytic materials are elaborated. The preparation methods of core-shell structured g-C₃N₄-based heterojunctions and the growth mechanism of g-C₃N₄ in the synthetic process are emphatically discussed. Finally, challenges and perspectives for the future research and development of g-C₃N₄-based core-shell heterojunctions are analyzed. This review will provide guidance for the development of new and efficient g-C₃N₄-based core-shell structured photocatalytic materials.

By using bibliometric method, the papers published in Journal of Shaanxi Normal University (Natural Science Edition) during 2003-2007 are analysed in order to provide some suggestions for the editors of the journal. The result shows that there are totally 617 articles in the 20 issues during 5 years; the average annual page is 379～435; each article covers 402 pages; of which 112% (808%) are ones of foundation items; the coauthored articles accounts for 88.33% and the mean cooperation rate is 270. The first authors of 460 papers are the teachers or students of the university, accounting for 7455% and 321 articles are graduate thesis, accounting for 5203%; the first authors of 315 articles own middle or senior professional titles; the average quotation is 10.38 articles, for the number and type of references in each paper are proper; the mean price index is 4768%. This shows that the journal has reached a high academic level, a high proportion of foundation items and an excellent editorial quality. It is suggested that the sources of the papers should be expanded and the discipline advantages of the university should be enhanced.

In recent years, ultrasonic imaging testing technology has made rapid development and become a research hotspot in the field of nondestructive testing. This paper focuses on the development history, research status and progress of six ultrasonic imaging detection methods: acoustic time reversal imaging, ultrasonic phased array imaging, synthetic aperture imaging, total focusing imaging, dispersive guided wave imaging and ultrasonic multi wave imaging. It shows that acoustic time reversal imaging is an adaptive focusing imaging method, which is not applicable to nonlinear and dissipative media in principle, and can only be applied after appropriate improvement. Ultrasonic phased array imaging, synthetic aperture imaging and total focusing imaging are all phase control methods based on ultrasonic array, which can realize adjustable sound beam. With the development of electronic hardware and software technology, ultrasonic array imaging will develop towards three-dimensional real-time imaging. By analyzing the focusing and imaging characteristics of dispersive guided waves and multi waves, several methods to focusing and imaging of dispersive guided waves and multi waves by controlling the excitation signal waveform of each array element of the transducer are discussed. By analyzing the latest research progress of these imaging detection methods, the development trend and existing problems of ultrasonic imaging detection are studied and summarized. It is shown that the integration of multiple imaging methods and multi-information imaging will become an important development direction of ultrasonic imaging detection, which can provide reference and research ideas for the research of ultrasonic imaging detection.

The Jordan (α，α)-derivations on a semiprime ring are studied. Using the properties of semiprime ring and the existed results, it is proved that every Jordan (α，α)-derivation on a semiprime ring is an (α，α)-derivation. In addition, the same results on Abelian rings and semisimple rings are given.

The catalytic synthesis of p-nitrobenzoic acid (PNBA) by oxidation of p-nitrotoluene with potassium permanganate (KMnO4) in the presence of phase transfer catalyst (PTC,PEG—600) are reported. The effects of different factors, such as amount of PEG—600, reaction temperature and time, amount of potassium permanganate, and basicity and acidity of reaction system, on the yield of PNBA were investigated. Under the optimal reaction conditions, molar amount of PEG—600, 5%, molar ratio of KMnO4 to PNT, 3∶1, reaction temperature, 95℃, reaction time, 3 h, the yield of PNBA was 51-6% in neutral reaction system. The experiment results show that PEG—600 is a good PTC for the synthesis.

Individual behavior plays an important role in the spread of emerging infectious diseases, and the ability to mitigate and control a disease through behavior changes is a vital aspect of response strategies. It is essential and important to understand how individuals’ behavior changes affect the spread of emerging infectious diseases. To address this, a psychological model of individual decision-making on social networks with infectious disease model (LHBM) is developed, and its applicability to the course of the 2009 A/H1N1 influenza outbreak is demonstrated.Individual behavior models (IBMs) are formalized to incorporate the rate of change of individuals’ behavior and investigated how individuals’ behavior changes affect the dynamical development of A/H1N1. In addition, approximate Bayesian computation sequential Monte Carlo (ABC SMC) methods are used to evaluate unknown parameters. The main results indicated that the novel model can depict the real transmission process and reveal the effects of individual behavior changes on A/H1N1 outbreak more accurately. Moreover, as far as mitigating and controlling emerging infectious diseases are concerned, it is essential for media publicity to focus on how to guide individuals’ behavior changes and get individuals to response positively.

The purpose of this study is to optimize PCR system to achieve efficient amplification for AT-rich DNA fragments.Four additives and four KOD-based high-fidelity DNA polymerases were studied for their amplification effects of four AT-rich fungal mitochondrial DNA fragments (AT contents: 72%~80%) with variable lengths of 1.0~5.4 kb. When applied alone, only magnesium ion facilitated the amplification, and the other three additives (bovine serum albumin(BSA), dimethyl sulfoxide(DMSO) and formamide) failed to produce the expected amplicon, which were contrary to their well-known facilitative effects on GC-rich DNA amplification. The presence of BSA or DMSO showed no impact on the amplification effect of magnesium ion, whereas the presence of formamide expressed inhibition effect on the facilitation function of magnesium ion. The four KOD-based polymerases (KOD-Plus-, KOD-Plus-Neo, KOD FX and KOD FX Neo) generated expected amplicons when magnesium ion was present in the PCR system, but KOD-Plus- and KOD-Plus-Neo failed to generate expected amplicon when magnesium ion was absent. This study verified that magnesium ion was critical for the successful amplification of AT-rich DNA fragments, and the optimal concentration was 1.75 mmol/L.The results provide a basis for the amplification of AT-rich DNA fragments in other eukaryotes.

Understanding the relationship between infrastructure and the tourism economy is crucial for optimizing infrastructure planning and enhancing the tourism sector’s quality and efficiency. Focusing on the Yangtze River Delta(YRD) urban agglomeration, this study establishes a comprehensive evaluation index system for infrastructure levels and tourism economic development. Using a coupling coordination model, this research analyzes the spatio-temporal evolution characteristics of their development and employs geographic detectors to investigate the driving mechanisms. Results indicate: 1)A steady upward trend in both the comprehensive evaluation index and coupling coordination degree of infrastructure and tourism economic development, with their coordination level transitioning rapidly between moderate and extreme coordination. Significant inter-provincial differences in coupling coordination are observed, with a spatial heterogeneity pattern of “Shanghai>Jiangsu>Zhejiang>Anhui”. 2)The coupling coordination degree exhibits a spatial distribution of “high in the east and low in the west, high in the center and low in the north and south”, with high and low coordination zones showing a spatial “expansion-convergence” trend. During the study period, the number of cities with lagging infrastructure increased gradually, mainly concentrated in Zhejiang and Shanghai regions. Meanwhile, cities with lagging tourism economic development converged and gathered in the northern part of the Yangtze River Delta. 3)The coupling coordination of infrastructure and tourism economic development is driven by various factors, including economic pulling force, government regulation force, urbanization driving force.The coordinated development of the two is driven by a comprehensive mechanism formed by eight driving forces,including economic operation and structural transformation mechanism, policy regulation and open cooperation mechanism, population agglomeration and consumption driving mechanism, and talent guarantee and technological innovation mechanism.

Plant secondary metabolites are a class of biologically active organic compounds synthesized through secondary metabolic pathways during plant growth. These compounds are not essential for plant development but play crucial roles in many aspects including plant survival, environmental adaptation and stress resistance. The WRKY transcription factor family, named for its characteristic conserved WRKYGQK domain, is one of the largest and most functionally diverse transcription factor families in higher plants. These factors are widely distributed across the plant kingdom and regulate the synthesis of secondary metabolites, thus participating in various physiological processes including plant growth, environmental responses, and chemical defense. This review discusses the structural features and classification of WRKY transcription factors, with a focus on their role in regulating the synthesis of plant secondary metabolites such as terpenes, phenolics and alkaloids. Future research should delve deeper into the mechanisms by which WRKY transcription factors function within the plant secondary metabolism regulatory network and their potential applications in enhancing plant stress resistance and improving the quality of secondary metabolites. Such studies will provide theoretical and practical insights for the advancement of agricultural biotechnology and the functional improvement of plants.

Three-way decision (3WD) is an important research direction in the field of granular computing, which conforms to human thinking and can effectively deal with uncertainty problems in practical decision-making processes. Three-way decision can effectively reduce the cost of decision-making, enhance the control of uncertain decision-making processes and improve the interpretability of model by introducing delay strategy. Therefore, a three-way decision based on machine learning is worth researching deeply. Firstly, the basic model of three-way decision is introduced.Secondly, the research status of three-way decision based on machine learning at domestic and foreign search results is analyzed by using CiteSpace and VOSviewer. Thirdly, from the perspectives of research questions, model methods, and application backgrounds, the integration of three-way decisions with clustering models, classification models, recommendation systems, and deep learning models are focused on.Finally, the future research directions of three-way decisions based on machine learning are given.

Multi-view imaging technology obtains rich scene information by capturing images from different angles, which can provide key visual data for fields such as autonomous driving, intelligent manufacturing and robot navigation. This paper first summarizes the components of common multi-view imaging systems, their working principles and implementation methods, and provides an in-depth analysis of the significant advantages of different multi-view imaging systems and their limitations from the key dimensions of dynamic imaging adaptability, imaging accuracy, cost-effectiveness, and comprehensive system performance. Then for the visual image enhancement technology, the application and effect in improving the quality of multi-view imaging are discussed by combining traditional image processing methods and deep learning techniques. Finally, the current status and future trends of the development of multi-view imaging technology are considered, and forward-looking predictions are made in the development directions of hardware innovation, algorithm optimisation and multi-modal data fusion.

This article used correlation and principal components analysis methods,selects the average temperature,the frostfree period, the precipitation, the latitude, total nine physical geography target, GDP, the gross population, the Engel′s coefficient, the Gini′s coefficient four human geography target, collected 19882009 year of Shaanxi Province young people track and field competition results, established the close degree between various factors and the movement results, used the system cluster to divide area into three suitable kinds; and calculated composite index which means being suitable to develop the young man sprint project.

Based on the reversible Diels-Alder reaction between furan and maleimide, a water-borne polyacrylate coating with self-healing properties driven by heat was successfully prepared, and the self-healing conditions were explored and optimized. A novel acrylate monomer with furan functional group (FEEMA) was synthesized. Stable acrylate emulsion was obtained by soap-free emulsion copolymerization. The results were verified by infrared spectroscopy, gel permeation chromatography (GPC) and particle size analysis (DLS). Then, polyether chain (D-400-BMI) was designed and synthesized, which could be dispersed in water. The crosslinked films were prepared by Diels-Alder reaction with water-based acrylate emulsion. The process of Diels-Alder and retro-DA reactions under different conditions were followed by infrared spectroscopy and differential scanning calorimetry. The results showed that the crosslinked membranes prepared by D-400-BMI had better repair performance when the content of FEEMA was 30% and the mass ratio of MMA and BA was 1/5. After the crosslinked membrane was scratched, the surface of the scratch and friction traces showed a good repair effect by heating for 140 ℃ and then slowly cooling to room temperature. The crosslinked membrane also has good heat resistance and mechanical properties, so it has potential application prospect in the self repair of scratch and microcrack of surface coatings.