The floral organs of Ranunculales show complex and diverse characteristics, which are ideal plant group to study the related problems of morphology and genetic evolution of floral organs. This paper reviewed the floral organ morphological diversity of Ranunculales. Combining the genome and transcriptome of Ranunculales as well as the flower development researches of representative species including Thalictrum thalictroides, Aquilegia coulela, Nigella damascena and Eschscholzia californica, the current research results on the function of MADS-box gene family A, B, C, D, E genes and their downstream target genes were elaborated.Besides, the breakthrough points and possible challenges of flower development research in Ranunculales in the future were forecasted. The aim is to enrich the understanding on the molecular pathways of floral organ development in basal eudicots.

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.

The rational and effective allocation of medical resources constitutes a crucial aspect of contemporary urban public space governance. Employing the framework of adaptability theory, an analysis framework to examine the spatial adaptability between urban medical resources and residential populations is constructed. Using Xi’an main urban area as a case study and leveraging point of interest (POI) data on medical resources, the research employs kernel density analysis, Ripley’s K function, location correlation, and Gaussian two-step floating catchment area method to explore the spatial agglomeration modes, scale thresholds, and spatial adaptability relationships with population scale of urban medical resources in Xi’an. Results reveal that urban medical resources in Xi’an exhibit a typical “core-periphery” structure and demonstrate a dependence on the main axis of urban development, with significant agglomeration effects observed in high-level development zones and satellite cities with CBD characteristics. Moreover, the characteristic scales corresponding to peak intensity of various medical resources are consistent, typically representing about 1/4 of the corresponding circle diameter when abstracted into circular areas of equal size. Additionally, the bidirectional location correlation model between urban medical resources and residential communities demonstrates an “asymmetric” structure, with significant leading effects of large-scale public medical resources in population allocation. Overall, the adaptability relationship between urban medical resources and population scale in Xi’an follows a circle decay structure of “strong center, weak periphery”, with different types of medical resources exhibiting differentiated characteristics in various urban circles. This reflects the compensation substitution effect and its spatial manifestation among hierarchical medical resource diagnosis and treatment systems under the dual allocation of urban macro planning and market resources.

In the early stages of drug discovery, deep generative models are emerging as crucial tools for molecular design. The simplified molecular input line entry system(SMILES) serves as a standard chemical representation widely used for model training and generation. However, due to the non-uniqueness and non-directionality of linear representations of molecular ring systems, existing unidirectional encoders face limitations in capturing the global semantic structure of samples and generating valid molecular rings. Therefore, a method called Chemical RWKV BERT (ChemRB) is proposed, which aims to deeply extract bidirectional information from a large amount of unlabeled data. To achieve this, two pre-training tasks are innovatively designed: ring-level feature prediction and global-span closure prediction. These pre-training tasks not only provide the model with rich contextual information but also further enhance its in-depth understanding of the structural properties of complex molecules. Experimental results show that the ChemRB model not only achieves significant performance improvements but also reaches optimal baseline performance on new molecular/sample evaluation metrics. This excellent performance fully validates the effectiveness of ChemRB in accurately capturing the inherent structural information of molecules, providing a solid empirical foundation for its application in related fields. Finally, through testing and application on EGFR inhibitors, the practical utility and broad application prospects of the ChemRB model are further validated.

Based on the location information of 650 intangible cultural heritage items and 735 traditional villages in Wuling Mountain area, the spatial distribution pattern and structural characteristics of the intangible cultural heritage items and traditional villages were discussed by using kernel density analysis and gravity center model, and the spatial location relationship was revealed. The heterogeneous factors affecting the distribution of intangible cultural heritage and traditional villages were analyzed with the help of ArcGIS 10.5, location entropy and geographic detector. The findings are as follows: 1) The spatial distribution of intangible cultural heritage and traditional villages in Wuling Mountain area has typical non-equilibrium characteristics. The spatial distribution pattern of intangible cultural heritage is significant in “large agglomeration but small dispersion”, and the spatial distribution law of traditional villages is prominent in “ring core group-zonal area”. From the perspective of spatial distance, the dislocation relationship between the two is obvious. 2) Under the influence of natural environment and cultural environment, the spatial distribution preferences of intangible cultural heritage and traditional villages are different, and the driving factors affecting the spatial distribution of intangible cultural heritage and traditional villages are different. The responses of the two to different factors are not only factor comprehensiveness, but also scale difference and spatial heterogeneity.3)The spatial distribution of intangible cultural heritage in the region is more significantly affected by cultural environment factors, and the spatial distribution of traditional villages in different regions is significantly different from each other. Different responses to heterogeneity factors are the cause of the dislocation relationship between intangible cultural heritage and traditional villages in spatial distribution.

Multispectral ghost imaging (MGI) based on code-multiplexing is a novel imaging technology that significantly enhances spectral imaging performance through cleverly designed encoding and decoding strategies, characterized by simplification and intelligence. This paper starts from the fundamental principles and key technologies of the MGI and thoroughly explores various coding multiplexing strategies and their reconstruction algorithms, primarily including coding multiplexing strategies based on random patterns, Hadamard patterns, and Fourier patterns, as well as corresponding reconstruction algorithms such as compressed sensing, Fourier inverse transform, and deep learning. These approaches exhibit unique characteristics in extracting the spatial structure and spectral properties of the target scene, showing different imaging advantages and applicable scenarios. However, the technique still faces challenges such as low projection efficiency and high computational complexity. In the future, it is expected to further improve the imaging performance of the MGI system through more efficient image reconstruction algorithms, intelligent technologies and advanced optics to meet the high-quality imaging needs of complex scenes.

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.

The data from the fifth to seventh national censuses was used to explore a grid based method for agricultural population based on land use types, 1.5 km of agricultural population grid density data in Shaanxi province was obtained to reveal the current characteristics and spatiotemporal evolution process of agricultural population distribution. Research found that in 2020, the agricultural population in Shaanxi province was densely distributed in the Guanzhong Plain and Hanzhong Basin, while the Northern Shaanxi Plateau and Qinba Mountains were relatively sparse. At the same time, the agricultural population is relative densely distributed in river valleys, while the density is extremely low in urban core areas, difficult to use land, and ecological protection and water conservation areas. From 2000 to 2020, the overall agricultural population density in Shaanxi province has generally decreased, but there are differences in the decline rates among different regions, leading to increased spatial heterogeneity. The reason may lie in the different changes in land use types and the slowdown in agricultural population size. The accuracy verification found that the agricultural population grid data has good consistency with the census data, and the fitting accuracy of the agricultural population grid dataset is relatively high. The research has alleviated the problem of plasticity area units, fully captured the detailed information of agricultural population distribution, and has policy reference value for accelerating the shaping of reasonably distributed modern agricultural human resources and achieving comprehensive rural revitalization.

Scenic byways serve as crucial conduits for fostering high-quality rural revitalization along their routes. Taking the viewpoint of scenic byways, this study analyzes the temporal and spatial evolution of transportation dominance and rural revitalization in regions along scenic byways in 2015, 2019 and 2021. Bivariate spatial autocorrelation methods are employed to elucidate their spatial adaptability. Findings reveal that transportation dominance along scenic byways is continually on the rise, with geographical location and tourism resource endowments being primary factors driving spatial disparities in transportation dominance. Additionally, the comprehensive value of rural revitalization in each region exhibits an upward trend, showcasing an inverted “U-shaped” spatial pattern with higher values in the east and lower values in the west, as well as higher values in the north and lower values in the south, and with developmental disparities observed between regions and dimensions. Furthermore, global analysis indicates a strong spatial alignment between transportation dominance and rural revitalization. Local spatial analysis categorizes their spatial alignment into four types: high adaptability, transportation dominance lagging, rural revitalization lagging, and double lagging.

The visible optical polarization simulation data set in the scattering medium is relatively scarce, which limits the polarization imaging algorithm in the development and verification for the scattering medium. By considering the effects of scattering degeneration and light in the scattered environment on polarizing imaging, a polarizing image simulation method in the scattered medium is proposed. First, the physical render is used to simulate the propagation path of light and obtain the non-degraded polarization images through the polarized filter. After that, the real scattering environment data set (underwater and foggy environment) was used to determine the scattering degradation parameters in different environments. These parameters are then integrated with the scattering degradation model to generate simulated scattering polarization images. The simulation results closely match the image in real scattering environments. The DoLP(degree of linear polarization) images and AoP (angle of polarization) images reflect the phenomenon of depolarization in real scattering environments. Simulating polarization images can be used to analyze the polarization properties of the object and background in the scattered medium, and can provide a solid foundation for improving various polarized scattering algorithms.

The national tourism leisure street block is a brand of urban street blocks recognized by the Ministry of Culture and Tourism and the National Development and Reform Commission, to meet the people’s pursuit of quality life, stimulate the vitality of cultural and tourism deep integration, and empower urban development. Based on the theory of urban spatial quality and the systematic summary of the national tourism leisure street block construction practice, this study draws the following conclusions. The essence of the tourism leisure street block is the practice of upgrading leisure needs and optimizing functional experience in block construction, which is the leisure upgrading of block space. The national street blocks are characterized by the focus on history and local traditional culture, the expansion of urban center, and the tourism experience and retail layout with local cultural themes. There are three major paths for the future development of tourism leisure blocks, namely, cultural inheritance of placeness, space placement of renewability, and protective operation of systematicness. The cultural inheritance of placeness should pay attention to location, locale, and sense of place. The space placement of renewability should focus on the people oriented, function, and vitality. The protective operation of systematicness should attach importance to integration, optimization and control of essential factors.

Developing flexible land use optimization allocation plans based on mathematical models and scenario simulations is crucial for promoting the coordinated development of ecological, agricultural, and economic lands in ecologically fragile agricultural areas. Taking the Ulan Buh irrigation district in the Hetao irrigation area as an example, this study utilizes morphological spatial pattern analysis (MSPA) and patch importance index to identify and extract ecological source areas. Subsequently, the NSGA-Ⅲ(non-dominated sorting genetic algorithm Ⅲ) and FLUS model are coupled to formulate elastic land use optimization allocation plans for ecologically fragile agricultural areas based on four scenario simulations. Results indicate that NSGA-Ⅲ can efficiently generate a Pareto solution set with multiple objectives, outperforming the 2020 land use benefits. However, scenarios prioritizing ecological security, food production, and economic development show marginal improvements in other objective benefits. Conversely, scenarios emphasizing balanced benefits development under minimal land use change conditions exhibit higher and more balanced comprehensive benefits. When devising land use optimization allocation plans, identifying land use coordination and conflict zones based on scenario-specific optimal allocations aids in formulating flexible plans to accommodate potential changes in economic policies and environments. Overall, this study provides insights for optimizing land use plans in ecologically sensitive and fragile agricultural areas.

By sequencing and analyzing the transcriptome of Picea wilsonii, the potential drought-related gene PwRhomboid was screened out, and its functional characteristics of drought resistance in Picea wilsonii were analyzed. Through bioinformatics analysis, the amino acid sequence and homologous gene of PwRhomboid were compared. The responses of PwRhomboid to different abiotic stresses and hormones were analyzed by RT-qPCR. Instantaneous transformation of tobacco leaves was conducted to detect the subcellular localization of PwRhomboid protein. PwRhomboid transgenic strains of Arabidopsis and potato were obtained and their drought phenotypes were verified. The results showed that the amino acid sequence of PwRhomboid has significant difference with those of its homologous species at N-terminus, but shows high similarity and good conservation at C-terminus. PwRhomboid protein is mainly localized on cell membrane. The expression level of PwRhomboid was significantly induced by drought, low temperature and abscisic acid, with the highest expression level observed in mature leaves.PwRhomboid can improve the drought resistance in transgenic Arabidopsis and potato. After drought treatment, compared with the control group Arabidopsis WT and pCM1205 strains, PwRhomboid overexpression strains PwRhomboid-L1 and PwRhomboid-L2 had higher survival rates, chlorophyll fluorescence F_v/F_m and Φ_PSⅡ. After polyethyleneglycol simulated drought treatment, the overexpression strains PwRhomboid-L3 and PwRhomboid-L4 resulted in higher potato seedling heights compared to the wild-type. The results showed that the expression level of PwRhomboid is affected by drought and hormones, and overexpression of PwRhomboid could improve the drought resistance of Arabidopsis and potato.

The cultural and entertainment industry plays a pivotal role in the urban economic transformation and the enhancement of residents’ quality of life. Based on point of interest (POI) data of Xi’an from 2010 to 2020, the spatial structural evolution of cultural and entertainment industry is investigated by employing Geo-information Tupu methodology and geographically and temporally weighted regression models. Specifically focusing on symmetry and hierarchy, the research aims to uncover the underlying mechanisms shaping the industry’s spatial configuration. Findings reveal a notable outward expansion of cultural and entertainment industry in Xi’an from the city center during the study period, exhibiting a multi-centralized trend characterized by discernible symmetry and hierarchical laws. The formation of diverse spatial structures is attributed to the interplay of transportation, demographic, regional economic, commercial, and industrial policy factors across multiple dimensions. Basic, developmental, and auxiliary factors influence the spatial distribution and site selection of industry hotspots through mechanisms involving supply and demand mechanism, trigger mechanism, and strengthening mechanism.

Grounded in humanistic principles and the needs of the main groups served by urban outdoor worker service stations, this study constructs evaluation indicators and quantitative assessment models from three dimensions: demand objectives, model evaluation, and feedback evaluation. Specifically, indicators such as transportation convenience degree, supply and demand index of roadside service stations, and supply and demand index of service stations within various land use categories are developed. Using Xiamen Island in Xiamen city as a case study, the rationality of the spatial distribution of urban outdoor worker service stations is investigated, along with an assessment of the extent to which these stations meet the needs of the target groups. Findings reveal significant spatial differentiation in the transportation convenience of service stations on Xiamen Island. While the number of service stations along urban branch roads and main roads/expressways generally matches supply and demand, there is a slight undersupply of stations along secondary trunk roads. Moreover, the matching degree of supply and demand varies across different land use categories, with relatively good matching observed in residential, commercial, business, and transportation facilities, but poorer matching in education, scientific research, cultural, sports, and medical healthcare facilities. Feedback evaluations from target groups align with the observed supply and demand matching status. Recommendations for optimizing the layout of urban outdoor worker service stations include the formulation of planning and construction standards, coordination in station planning and layout, and the revitalization of existing environments through renewal efforts.

Diabetic nephropathy (DN) is a major complication of diabetes mellitus and a major causative agent of chronic kidney disease.UBE2V1, as the only E2 enzyme involved in K63 ubiquitination, is involved in the development of diabetic nephropathy, while UHRF2 acts as E3 ubiquitin ligase in the K63 ubiquitination pathway. Real-time fluorescence quantification, gene silencing and overexpression, scratching test, western blot analysis, K63 ubiquitination protein isolation and immunoprecipitation were used to explore the mechanism of UHRF2 and UBE2V1 in the process of epithelial-mesenchymal transition of renal tubular epithelial cells induced by high glucose. It was found that high glucose could increase the expression of UHRF2 and UBE2V1 in renal tubular epithelial cells, leading to the development of epithelial-mesenchymal transition. The expression of epithelial-mesenchymal transition marker proteins α-SMA and ZEB1 was significantly up-regulated in renal tubular epithelial cells cultured with high glucose, while E-cadherin expression was significantly down-regulated. Knocking down of UHRF2 or UBE2V1 inhibited the up-regulation of α-SMA and ZEB1, and weakened the down-regulation of E-cadherin.UBE2V1 may mediate the up-regulation of UHRF2 transcription in renal tubular epithelial cells cultured with high glucose and may increase the ubiquitination of K63 in UHRF2.The results reflect that both UHRF2 and UBE2V1 are involved in the epithelial-mesenchymal transition of renal tubular epithelial cells under the condition of high glucose, which may synergistic promote the fibrosis of diabetic nephropathy. These findings provide a new idea for the treatment of diabetic nephropathy.

Empirical analysis of the spatial misalignment characteristics and driving factors of tourism urbanization quality and scale in the Wuling Mountain area of Hunan from 2011 to 2021 using the center of gravity model, spatial misalignment index, and econometric model. The results show that: 1) The quality and scale development level of tourism urbanization in the Wuling Mountain area of Hunan are generally on the rise, with the quality growth rate faster than the scale, but the overall scale is higher than the quality.In space, the quality and scale of tourism urbanization show a differentiation pattern of “high in the northeast and low in the southwest”. Wulingyuan, Yongding and Fenghuang, as “double high areas” of quality and scale, have become “leaders” in the development of tourism urbanization. 2) There is a spatial mismatch between the quality and scale of tourism urbanization in the Wuling Mountain area of Hunan: the degree of spatial mismatch shows a trend of first decreasing and then increasing with 2015 as the node.The direction of spatial displacement has shifted from a scale first positive displacement area to a quality first negative displacement area.The level of spatial misalignment presents a pyramid structure from high to low, with the proportion of low misalignment areas consistently remaining above 50%.3) Per capita GDP, per capita disposable income ratio of urban and rural residents, passenger turnover, and tourism industry agglomeration have a negative impact on the quality and spatial mismatch of tourism urbanization, while tourism population density has a positive impact on the quality and spatial mismatch of tourism urbanization.

Compared with the traditional nickel-based materials and rare earth-based materials, the magnetostrictive coefficient is small, the eddy current loss is large, and the preparation cost is high. Utilizing cobalt ferrite as the driving core of magnetostrictive ultrasonic transducer can achieve stable service and high-power output at elevated frequencies. In this paper, a longitudinal magnetostrictive ultrasonic transducer with resonant frequency of 30 kHz is designed based on the magnetostrictive characteristics of cobalt ferrite and the finite element simulation is used to analyze the dynamics and magnetic field of the transducer. The output characteristics of the cobalt ferrite magnetostrictive ultrasonic transducer are tested by impedance matching. The resonant frequency, output amplitude and working temperature of the prototype are tested. The results show that the magnetic field intensity is 0.1~0.25 T (301~653 Oe), which can meet the driving requirement of cobalt ferrite in the best driving range(250~750 Oe).When the driving voltage is 12 V and the signal gain is 20 dB, the actual resonant frequency of the transducer is 29.8 kHz, the output amplitude is 3.75 μm, and the stable working temperature is 60 ℃. The experimental results verify the reliability and application potential of cobalt ferrite in the field of magnetostrictive transducers.

In order to achieve accurate and rapid detection for Staphylococcus aureus in drugs, through adding internal amplification control (IAC) and optimizing PCR reaction system, an internal reference based fluorescence quantitative PCR rapid detection method of Staphylococcus aureus that can monitor the process in real time was established, and its specificity, detection limit, reproducibility and feasibility were verified. The verification results showed that the specificity of the established method was good with only Staphylococcus aureus showed typical amplification curve. The detection limit of Staphylococcus aureus genomic DNA was 0.23 pg/μL. There was a good linear relationship between C_t values and the copy numbers of template (R²=0.99). The relative standard deviations of reproducibility experiments were all less than 3.0%.Staphylococcus aureus can be detected 10 h after the bacteria increase in artificially contaminated drugs. The method can not only shorten the detection time of Staphylococcus aureus in drugs, but can also monitor the PCR reaction process, effectively prevent the occurrence of “false negative” result, thus can be used as a supplementary method for staphylococcus aureus detection.

The MADS-box family is one of the largest transcription factor families in plants, and plays an important role in adversity stress and flowering response. The function of AGL12-like subgroup in Vitis vinifera remains unclear. The VvAGL12 promoter (proVvAGL12) was cloned from the Pinot Noir grape genome, and the sequence elements of the promoter were analyzed. It was found that there were several cis-acting elements related to adversity stress in the promoter region. GUS expression vector driven by proVvAGL12 was constructed and transformed in Arabidopsis thaliana and tobacco. It was found that proVvAGL12 promoter fragment had activation activity in Arabidopsis thaliana, and it can drive GUS expression in leaves, stem segments, flower organs, roots and fruit pods in transgenic Arabidopsis thaliana plants.The expression activity can last the whole growth cycle. Transgenic Arabidopsis thaliana and tobacco stress treatment showed that the activity of proVvAGL12-driven GUS was regulated by gibberellin, abscisic acid, polyethylene glycol and low temperature.

The flood event has always been endangered high-quality development as for human society. Reconstructing and analyzing the impact-response process of the past flood events would be helpful to realize the mechanism and process of extreme climate events to human response, which could improve the adaptive capacity for natural disasters among human beings. In this study, archives and other historical documents were collected to reconstruct the spatial and temporal process of the flood event in 1811 Aksu. Furthermore, 26 points and 73 lines were extracted from above documents to reconstruct the impact-response process of this flood event, and social network analysis was applied to analyse the patterns of human interactions with climate change in the arid region. The main conclusions are as follows: 1) The flood event in 1811 Aksu was happened in the background of climate warming and humidification, and the interaction within the natural system among constant rainfall, ice and snow melt water, steep terrain exacerbated the impact of this flood event. 2) The main high-risk areas centralized in the Aksu city and adjacent villages, farmland. It was partly because the lower terrain and intense populations, various commodities near the city were prone to suffered by flood and waterlogging. 3) The flood affected the supporting system and population subsystem directly and indirectly affected the population subsystem, economic subsystem and social subsystem. In this process, there were 4 points (urban waterlogging, food production damaged, infrastructure damaged, famine) represented the main impacts of this flood event. 4) The human responses changed over time influenced by different disaster phases, including adjustment and adaption, which jointly effected to avoid the occurrence of post-disaster malignant events. And people constructed flood control engineering to prevent the occurrence of flood events that maintained the security and stability in northwestern frontier society during the middle and late Qing dynasty.

Janus-Helmholtz (JH) transducers and Janus-Hammer Bell (JHB) transducers have similar appearance and structure, but their vibration modes are different. This article firstly analyzes the structural parameters corresponding to different vibration modes in JH transducer and JHB transducer. Under the conditions determined by other parameters, through theoretical calculation, it is concluded that the relationship between the axial length L of the ring shell in the JH transducer and the inner radius a of the ring shell should satisfy 2<L/a<5.7. The value range corresponding JHB transducer is 0.1<L/a<0.3. Then the finite element special boundary condition setting method is used to analyze the vibration modes corresponding to the resonance peaks of the JH transducer and the JHB transducer. It is concluded that the lower-frequency vibration mode in the JH transducer is the Janus longitudinal vibration, and the high-frequency vibration mode is the cavity resonance mode.The lower-frequency vibration mode in the JHB transducer is the Janus longitudinal resonance, and the higher-frequency vibration mode is the ring breathing mode. Finally, the radial and axial transmitting voltage responses of the JH transducer and the JHB transducer are compared to analyze work performance under different working modes, and it is concluded that the JH transducer can achieve a wider operating bandwidth and a higher transmitting voltage response. The working bandwidth of JHB transducer is narrow, but the transmitting voltage response in the radial direction has small fluctuations, and the transmitting voltage response in the axial direction has large fluctuations.

Polygonatum kingianum Coll. et Hemsl. (PK), a well-known Food and Medicine homology in China, riches in various bioactive ingredients and has been consumed for thousands of years with a wide range of applications. PK has shown great tonic effects. Previous studies have consistently shown nutritional functions of PK including liver protection. The Nine Steaming Nine Drying is a traditional processing technique that has been considered as an effective method in enriching tonic properties, but its impacts on improving efficacy of PK on liver protection remain largely unexplored. This study herein applied integrative analysis of metabolomics and bioinformatics, as well as molecular docking, to reveal the core bioactive compounds responsible for the improved effects of Nine Steaming Nine Drying processed PK extracts (PPK) on the prevention and treatment of alcoholic liver injury and its underlying mechanisms.Through constructing an alcohol induced injury model using LO₂ cells, the regulatory effects of PPK on cell activity, oxidative stress, and alcohol metabolism enzymes (ethanol dehydrogenase and acetaldehyde dehydrogenase) were investigated. A total of 204 metabolites in the PPK were compared with crude PK extracts (CPK). Alcohol induced liver injury related targets were obtained by searching for DisGeNET, TTD, GeneCard, and OMIM databases, and a compound-target network was established. Results from protein-protein interaction networks and enrichment analysis identified 23 functional metabolites (including rutin, furanone, caffeic acid, gallic acid, etc.) that may be responsible for the protective effects of PPK on alcoholic liver injury via regulating 15 action targets involved in PI₃K-Akt, AMPK, NF- kB signaling pathways. High affinity between the identified key constituents of PPK and their predicted acting targets was confirmed using molecular docking. Results indicate that PPK can alleviate alcoholic liver injury by regulating oxidative stress, inflammation, and ethanol metabolisms. It provides novel insights in nutritional functions of PPK, and an effective strategy for systematically elucidating the mechanisms of functional foods.

In order to achieve non-destructive and rapid inspection of tissue microarrays, a fully automatic Mueller matrix microscopic imaging system was constructed by using the polarization imaging principle of the Mueller matrix. By integrating polarization optical components and imaging equipment with automatic control, this system can perform automatic imaging. The collected polarized image data is processed by using the Mueller matrix polar decomposition and Mueller matrix transformation algorithms to extract the key polarization characteristic parameters describing the sample. The results showed that in the experiment of distinguishing cervical cancer tissue samples from normal cervical tissue samples, the equivalent waveplate fast-axis azimuth θ and linear phase retardance δ are effective polarization parameters. By using statistical analysis, gray level co-occurrence matrix analysis and Tamura image processing methods to process the polarization parameter images, clear indications for diagnosing cervical cancer can be obtained. The fully automatic Mueller matrix microscopic imaging system can achieve rapid diagnosis of cancer by integrating multiple samples without frequently changing slices or switching to a high power objective.

To clarify the dynamic changes and clinical significance of heart rate variability in adolescent depression with aerobic exercise therapy,60 students of mild to moderate depression enrolled in 2022 were divided into the study group (5 cases dropped, 25 cases completed ) and the control group (2 cases dropped, 28 cases completed) equally. The patients in the study group received aerobic exercise therapy for 12 weeks, the patients in the control group did not receive any treatment.The clinical efficacy and heart rate variability index between the two groups were compared.The clinical efficacy and cure rate of the study group were significantly higher than those of the control group at the end of the 12th week (P<0.05).The 17-item Hamilton Depression Scale (HAMD-17) score in the two groups was significantly lower than that at baseline (P<0.01).Compared with the control group, the study group showed a more significant decrease in HAMD-17 at the end of the 12th week (P<0.001). The standard deviation of NN intervals(SDNN),standard deviation average of NN intervals(SDANN), and root mean square of successive RR interval differences(RMSSD) in the study group at the end of the 12th week were significantly increased than those before treatment (P<0.001).Compared with the control group, the scores of SDNN, SDANN, and RMSSD in the study group at the end of the 12th week changed more significantly (P<0.001). Negative correlations were found between baseline HAMD-17 score and SDNN, SDANN, and RMSSD (r=-0.343, P=0.012; r=-0.328, P=0.017; r=-0.401, P=0.003; respectively). The results indicate that 12-week aerobic exercise can significantly improve depression symptoms and autonomic nervous system function in adolescent depression patients. The severity of depression is related to impaired autonomic nervous system function, and heart rate variability can become a biological indicator for evaluating the efficacy of aerobic exercise in treating depression.

This study introduces a technique known as large-field optical sectioning structured illumination microscopy(large-field optical sectioning structured illumination microscopy, LF-OS-SIM) designed for three-dimensional tomographic microscopic imaging of thick specimens. The technique utilizes a one-dimensional grating projection to generate a striped structured light field, in conjunction with a spatial light modulator (spatial light modulator, SLM) for fast phase-shifting of the structured light spectrum. Compared to conventional OS-SIM techniques that are based on SLM/DMD projection, LF-OS-SIM enhances the spatial bandwidth product (spatial bandwidth product, SBP) by 4.7 times. Additionally, digital phase-shifting using the SLM is implemented to achieve a slicing speed of 20 frames per second. The LF-OS-SIM was employed for three-dimensional tomographic microscopic imaging of objects such as coins, three-dimensionally distributed fluorescent beads, and biological specimens. The results indicated that the imaging field of view (FOV) for LS-OS-SIM reached 1 030×780 μm³, with an axial tomographic imaging accuracy of 4.0±0.39 μm. Given its wide field of view, high resolution, and rapid slicing capabilities, LS-OS-SIM is anticipated to be extensively applied in the three dimensional imaging of both industrial microdevices and biological samples.

Aegilops tauschii, the D genome donor of wheat (Triticum aestivum), has a variety of genes resistant to biotic and abiotic stresses, and is the main gene pool for wheat genetic improvement. Heavy metal-associated isoprene plant protein (HIPP) plays an important role in regulating metal ion balance and detoxification in plants. In this study, the transgenic Arabidopsis thaliana overexpressing AetHIPP28 was obtained by Agrobacterium-mediated method, and the response of transgenic Arabidopsis thaliana to cadmium (Cd) stress was studied by a series of physiological and biochemical analyses.The results showed that AetHIPP28 was localized in the nucleus and plasma membrane. Overexpression of AetHIPP28 significantly enhanced Arabidopsis thaliana tolerance to Cd, and promoted the root growth of Arabidopsis thaliana under Cd stress. The ROS accumulation of transgenic Arabidopsis thaliana under Cd stress was significantly lower than that of the wild type, while the activity of antioxidant enzymes was significantly higher than that of the wild type. Meanwhile, overexpressing AetHIPP28 inhibited Cd²⁺influx and increased Cd accumulation in roots. These results suggest that overexpression of AetHIPP28 improves Cd tolerance in Arabidopsis thaliana by regulating ROS accumulation, antioxidant enzyme activity, Cd²⁺ influx and distribution in roots, which provide a reference for investigating the response mechanism of AetHIPP28 to Cd stress.

Aiming at the difficulties present in current automatic sleep staging methods, a method for automatic sleep staging of EEG and ECG dual modal signals by combining U²-Net and CBAM fusion attention is proposed.Firstly, the EEG-ECG signals in the MIT-BIH public dataset used in this paper are preprocessed. Then, the U²-Net network with multi-scale feature extraction module is used to extract waveform features in EEG and ECG in parallel. Secondly, CBAM fusion attention is used to assign weights to all features. Finally, the Softmax activation function is used to classify sleep periods into six. The results show that when sleep staging is performed based on U²-Net and CBAM fusion attention models, the overall accuracy of hexaclassification using ECG single-modal signals is 80.2%, and the F1 score is 75.3%. The overall accuracy of six classifications using EEG single-modal signals was 85.8%, and the F1 score was 81.7%;The overall accuracy of the six classifications using EEG-ECG dual-modal signals was 90.4%, and the F1 score was 85.6%. This shows that the bimodal sleep staging model proposed in this paper is feasible and effective, and provides a new idea for automatic sleep staging.

A high-resolution reconstruction method of split-focal plane mosaic images is proposed due to the low spatial resolution of split-focal plane multispectral cameras. The method realizes the acquisition of a demosaicking reflectance image, which shoot a diffuse reflective white plate to calibrate a division-of-focal-plane (DoF) mosaic sensor. The reflectance image and the DoF mosaic image are substituted into the fusion model of multispectral and hyperspectral images for high-resolution reconstruction. The reconstruction results of two reconstruction methods based on superpixel segmentation operators (least squares-multispectral data fusion method and regularized minimum rank-multispectral data fusion method) are analyzed, and the root mean square error of the two methods is about 0.12. The results show that the demosaicking method achieves better results in the migration of the high-resolution fusion model for spectral images, and the DoF mosaic images are highly restored in both the spatial and the spectral information.

Multimodal sentiment analysis, an inherently challenging research area, integrates textual, audio, and visual modalities to analyze human emotional tendencies. Existing studies suggest that the textual modality plays a dominant role in sentiment prediction. However, this predominance raises a potential issue: during training, machine learning models tend to learn spurious correlations between the input and the output, leading to an overreliance on textual information. This overreliance may cause models to incorrectly model spurious correlations between textual and sentiment labels, thus undermining the model's generalization ability. To address this challenge, an innovative counterfactual text debiasing(CFTB) algorithm is proposed for multimodal sentiment analysis. Our framework first employs causal graph to thoroughly analyze the causal relationships among the three modalities and the sentiment labels.Then, an auxiliary textual model is designed to precisely quantify the direct impacts of the textual modality to sentiment prediction and leverage an attention mechanism to accurately capture textual features that might introduce spurious correlations. During the inference phase, the CFTB algorithm demonstrates its unique advantage: it intelligently isolates the negative impacts caused by spurious textual associations from the overall multimodal information, while retaining and enhancing the beneficial information within the textual modality that genuinely contributes to sentiment prediction. Experiments on the MOSEI and MOSI datasets show that this framework can be effectively integrated into existing methods and has good generalization performance.

The polarization parameter images in polarization dehazing algorithms are highly susceptible to noise interference, and the brightness of the dehazed images is unstable. This leads to the algorithm’s inability to adapt universally to different lighting conditions. To address this issue, a new polarization dehazing algorithm is proposed, which introduces a novel polarization parameter image based on low-rank approximation to reduce noise interference. Additionally, a multi-exposure fusion method is employed to compress the image’s dynamic range. Comparative experiments demonstrate that this method effectively removes haze from images, exhibiting strong robustness and significantly improving the overall quality of haze-affected images captured in various environments. In terms of standard deviation, image information entropy, NIQE and PIQE, the indicaters of the proposed method are improved by 22.99%,4.06%,17.42%,32.89% and 33.33%,2.80%,12.31%,76.14% respectively compared with the method proposed by Schechner and dark channel method.

This study focuses on the real-time dynamic monitoring of meteorological factors and sap flow rates of Haloxylon ammodendron subjected to different pruning treatments in the northeast part of the Ulan Buh Desert. The sap flow characteristics of Haloxylon ammodendron at different time scales during the vigorous growth season (from June to August) under different pruning treatments were investigated and their responses to meteorological factors were examined. Water consumption model in relation to meteorological factors was established to reveal the patterns of water transportation in Haloxylon ammodendron after pruning. Thermal diffusion sap flow meter and automatic weather station were used to monitor the sap flow in Haloxylon ammodendron subjected to different pruning treatments and solar radiation, air temperature, relative humidity and vapor pressure deficit.Sap flow rates in Haloxylon ammodendron under different pruning treatments (120 cm pruning, 90 cm pruning, 60 cm pruning) exhibited a “broad peak” pattern on sunny days, while unpruned Haloxylon ammodendron displayed a “single-peak” pattern. On rainy days, sap flow rates fluctuated dramatically, presenting an “irregular multi-peak” curve, which are lower compared to those of sunny days. The daily average sap flow rates in unpruned, 120 cm pruned, 90 cm pruned and 60 cm pruned Haloxylon ammodendron were 2.314 6, 3.333 4, 1.333 3 and 0.767 2 cm/h, respectively. The daily water consumptions were 8.62, 13.43, 2.40 and 2.89 kg/d, respectively. On the hour scale, solar radiation was the primary factor influencing sap flow rates in both pruned and unpruned Haloxylon ammodendron.On the daily scale, solar radiation was the main factor affecting sap flow rates in 90 cm pruned and unpruned Haloxylon ammodendron, while air temperature influenced sap flow rates in 120 cm pruned Haloxylon ammodendron and wind speed affected sap flow rates in 60 cm pruned Haloxylon ammodendron.On the month scale, water consumption in 120 cm pruned Haloxylon ammodendron was mainly influenced by solar radiation and air temperature, water consumption in 90 cm pruned Haloxylon ammodendron was primarily influenced by relative humidity and solar radiation, and water consumption in 60 cm pruned Haloxylon ammodendron was mainly influenced by wind speed. With the increase in time scale, the number of meteorological factors included in the model decreased, and the explanatory power for sap flow decreased. The fitted equations in this study reached significant levels and can predict the transpiration characteristics of Haloxylon ammodendron at different time scales. The results of this study are of great significance for understanding the patterns of water transportation in Haloxylon ammodendron after pruning.

Through artificial rainfall simulations, the variations in surface runoff and sediment yield under different straw return rates (0.30, 0.45, 0.60, and 0.75 kg/m²) and methods (crushed mulch reversion (CV),crushed tillage reversion (RT), and mulch-crushed tillage reversion (CR)) are investigated, and the underlying mechanisms governing surface runoff and sediment yield patterns under different straw return methods and rates are analyzed. The results indicate that: 1)Under the same return method, straw return rates significantly affect the timing of runoff production, with increasing straw return rates leading to longer initial and stable runoff production time. Among the same straw return rates, there is minimal difference in runoff production time between CV and RT, while CR exhibits the most pronounced delay, with an initial runoff production time delayed by 19.42 to 55.17 minutes compared to CK. 2)With increasing straw return rates under the same return method, the initial and stable surface runoff intensities decrease, resulting in a significant reduction in total surface runoff. Notably, there is no significant difference in total surface runoff between RT and CR at straw return rates of 0.60 kg/m² and 0.75 kg/m². Moreover, under the same straw return rate, CR demonstrates significantly greater flow reduction benefits compared to CV and RT, with a decrease in initial runoff intensity ranging from 23.64 to 44.04 mm/h, and a reduction in total surface runoff ranging from 55.74% to 98.92% compared to CK. 3)Under the same return method, increasing straw return rates lead to a continual decrease in sediment yield intensity, resulting in a significant reduction in total surface sediment yield. There is no significant difference in total surface sediment yield among the three return methods at straw return rates of 0.60 kg/m² and 0.75 kg/m². Additionally, under the same straw return rate, CR demonstrates greater sediment reduction benefits compared to CV and RT, with sediment reduction benefits ranging from 93.73% to 99.99% compared to CK. Thus, it is evident that mulch-crushed tillage reversion (CR) with a straw return rate of 0.60 kg/m² is the optimal straw return mode.

To investigate the effect of composite nanofiber membrane prepared from isoorientin (ISO) and zein/Arabic gum (GA) on skin injury healing in mice, this study used blank spinning membrane as control, and wound dressings were applied to mice using zein/GA loaded nanofiber membrane, ISO loaded nanofiber membrane, and ISO-zein/GA loaded composite nanofiber membrane, respectively. The results showed that the nanofiber membranes loaded with zein/GA, ISO and ISO-zein/GA had promoting effects on wound healing in mice. They effectively reduced wound oxidative damage and mRNA expression levels of pro-inflammatory factors(TNF-α、IL-1β、iNOS), and promoted wound vascular reconstruction, thereby accelerating wound healing. The research results verify the promoting effect of ISO-zein/GA composite nanofiber membrane on wound healing, expand the application range of isoorientin, and provide ideas for the research of new wound dressing.

The aim of this study was to investigate the effects of Ginkgo biloba powder on growth performance, serum indexes, rumen microbiome and rumen metabolomics of Angus cattle. A total of 25 healthy Angus cattle with an average body weight of 453.8 kg aged 12~16 months were randomly divided into 5 groups. The cattle were fed the basal diet (Con, n=5) and diets containing 3% (G3, n=5), 6% (G6, n=5), 9% (G9, n=5) and 12% (G12, n=5) Ginkgo biloba powder, respectively. The pre-test lasted for 10 d and the trial lasted for 75 d. The results showed as follows: dietary Ginkgo biloba powder increased the average daily gain of Angus cattle, and significantly increased the dry matter intake of Angus cattle. Compared with Con group, serum triglyceride content in G9 group was significantly decreased,total antioxidant capacity was significantly increased,malonaldehyde concentrations in G6 and G9 groups were significantly decreased. Compared with Con group, the proportions of propionic acid in G6 and G9 groups were significantly increased, while the proportions of acetic acid were significantly decreased. There was no significant difference in the diversity and richness of rumen microbial communities among all groups. At the phylum level, compared with Con group, the relative abundances of Firmicutes in rumen of Angus cattle in G6 and G9 groups were significantly increased, while the relative abundances of Spirochaetota were significantly decreased. At the genus level, the relative abundances of F082_unclassified and Paludibacter_unclassified in G6 group were significantly decreased compared with Con group.The relative abundance of F082_unclassified in G9 group was significantly decreased, and that of Succiniclasticum was significantly increased. The results of rumen metabolomics showed that in positive ion mode, compared with Con group, the contents of fatty acids in the rumen of G6 and G9 groups were significantly decreased, and the contents of other metabolites were significantly increased. In negative ion mode, the contents of diazine and organic oxygen compounds in rumen of G6 and G9 groups were significantly decreased compared with Con group, while the contents of other metabolites were significantly increased. In conclusion, dietary supplementation of 6%~9% Ginkgo biloba powder has positive effects on the growth performance and blood indexes of Angus cattle, improves rumen fermentation parameters, and has certain effects on the composition of rumen metabolites. It is suggested that the optimal supplemental amount of Ginkgo biloba powder should be 6%~9% of the basal diet.

Multi-functional active peptide is a protein-derived compound that can act on multiple targets and deliver a variety of physiological effects, and has significant therapeutic effects on a variety of diseases. The existing multi-functional active peptide prediction model fails to fully consider the correlation between amino acids in the feature representation stage, which reduces the feature representation ability of the model, and the existing method adopts the strategy of converting the multi-label classification problem into multiple binary classification prediction problems, which leads to the inability of the model to consider the dependence between multiple functions of the active peptide in the prediction stage, which reduces the prediction accuracy of the model for multi-functional active peptides. In order to solve the above problems, a multi-functional active peptide prediction model based on label dependence is proposed, TCLD, which extracts the correlation between amino acids in the active peptide sequence through the Transformer encoder, and uses the ZLPR loss function to capture the dependence between multiple functions, which is used to improve the performance of the multi-functional active peptide prediction model. The experimental results show that the prediction performance of TCLD is better than that of the existing multi-functional active peptide prediction methods, which is helpful for researchers to quickly screen out multi-functional active peptide candidates with potential therapeutic value, thereby accelerating the research and development process of new drugs.

Imaging genetics suggests that there is a certain degree of correlation between neuroimaging and genes, leading researchers to pay attention to the analysis of diseases using genetic variations and imaging data. In practice, clinical doctors usually have limited data availability but still aspire to employ deep learning method for real-world problems. Considering the expanding data scale and expensive annotation costs, it becomes essential to develop an unsupervised learning method capable of utilizing multimodal data. To meet these needs, a representation learning method based on multimodal tabular data with contrastive learning (MTCL) is proposed. The model leverages resting-state functional magnetic resonance imaging (rs-fMRI) and single nucleotide polymorphisms (SNP) data without requiring any labeled information. To enhance interpretability, the model first transforms rs-fMRI and SNP data into a tabular structure through a feature extraction module. Then, a multimodal tabular data contrastive learning method is employed to fuse the dataset and obtain the fused data representation. On the dataset of major depressive disorder (MDD), our proposed method effectively improves the diagnostic performance of MDD. Additionally, the MTCL method combines model attribution techniques to explore imaging and genetic biomarkers associated with MDD, enhancing the interpretability of the model and aiding researchers in understanding the mechanisms underlying the disease.

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.

Rural tourism is an important engine for achieving the strategy of rural revitalization. Exploring the spatio-temporal evolution laws of rural tourism destinations is of great significance for promoting high-quality development of rural tourism. Based on the theory of “production-living-ecological” function, 303 provincial-level key rural tourism villages in Shaanxi province are taken as research objects to study the temporal-spatial distribution characteristics and influence mechanism of rural tourism destinations in Shaanxi province by using the methods of GIS spatial analysis and geographical detector. The conclusions are as follows: 1)The spatial distribution of all rural tourism destinations in Shaanxi province is characterized by gathering in mid to low altitude terrain, near the main transportation line, along rivers and lakes, showing a developing trend of polarization and sheet diffusion. Rural tourism destinations with dominant function production have the greatest spatial dependence on transportation and hydrological conditions.2)There are certain differences in the spatial distribution and evolution of rural tourism destinations dominated by different functions. Rural tourism destinations primarily driven by production functions exhibit the highest degree of agglomeration, displaying a contiguous expansion trend, and are predominantly situated in areas with flat terrain and dense river networks.The distribution of rural tourism destinations driven by life functions is largely consistent with the overall distribution, and there is a noticeable increase in the agglomeration of the high-density core areas.Rural tourism destinations driven by ecological functions exhibit a clear trend of outward expansion. These destinations are predominantly located in the border regions between cities, forming a point-to-axis distribution pattern. Additionally, a high-density distribution area has emerged at the southern foothills of the Qinling Mountains.3)There are differences in the influencing factors of spatial differentiation of rural tourism destinations dominated by different functions. Relevant policies exert the strongest influence on the spatial distribution of rural tourism destinations dominated by production functions. Rural tourism destinations dominated by life functions have a high spatial dependence on population distribution and surrounding scenic areas, while rural tourism destinations dominated by ecological functions are significantly affected by climate conditions and air quality.4)Natural ecological environment determines the basic spatial distribution pattern of rural tourism destinations, economic development level is an important driving force for the formation and development of rural tourism destinations, social and political conditions are guiding factors. Resource endowment foundation plays a prominent driving role in the spatial distribution differentiation of rural tourism destinations across various functional types. Furthermore, the interactive enhancement effect with economic development level surpasses that with social and political conditions.

Most Transformer-based object tracking models have limited extraction of target's local spatial feature information and insufficient utilization of temporal features, significantly affecting the performance of object tracking models in handling complex scenarios such as target occlusion, deformation, or scale changes. Therefore, a visual object tracking method with spatial-temporal feature enhancement and perception (STFEP) are proposed in this paper. On one hand, this method uses Transformer for the extraction and fusion of search region and temporal context features to obtain global feature information. By designing a local convolutional neural network, it extracts the target's local feature information and associates it with the target's global feature information, further enhancing the target's feature representation. On the other hand, a spatial-temporal feature perception mechanism is proposed to analyze the reliability and necessity of feature information at different moments, constructing dynamic templates to perceive richer spatial-temporal information, enabling the model to adapt to complex changes in targets and scenes. Experimental results on multiple datasets such as TrackingNet, GOT-10k, LaSOT and UAV123 show that the proposed method can track the target accurately and robustly, and the optimal results are obtained on GOT-10k dataset. AO, SR_0.5 and SR_0.75 were 73.7%, 83.8% and 70.6%, respectively.