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Continuous cropping of the important achlorophyllous medicinal orchid Gastrodia elata Blume causes an imbalance in soil microecology leading to soil-borne diseases. However, the impacts on different land covers remain largely unknown. Hence, this study aimed to investigate changes in the soil nutrient composition and the global microbial community structure in rhizospheres of G. elata cultivated on a barren slope (HPGJ) and under a forest (LXT) using integrated shotgun metagenomics and an analysis of soil chemical properties. High-throughput sequencing revealed an increase in the abundance of Proteobacteria, Actinobacteria, Mucoromycota, Basidiomycota, and Ascomycota, which drive N- and C-cycling genes in HPGJ and LXT. Notably, the fungal community was significantly improved in the HPGJ (from 0.17% to 23.61%) compared to the LXT (from 0.2% to 2.04%). Consequently, mineral cycling was enhanced in the HPGJ, resulting in a more improved soil nutrient composition than in the LXT. The soil chemical properties analysis unveiled a significant increase in the contents of the total nitrogen, NO3−-N, organic matter, total carbon, organic carbon, total sulfur, and total phosphorus in the HPGJ, while no changes were recorded in the LXT. It was noteworthy that the abundance of pathogenic microorganisms increased significantly in the HPGJ compared to the LXT. Our results provide supporting data to optimize G. elata cultivation on slopes. [ABSTRACT FROM AUTHOR]

University students, as a special group, face multiple psychological pressures and challenges, making them susceptible to social anxiety disorder. However, there are currently no articles using machine learning algorithms to identify predictors of social anxiety disorder in university students. This study aims to use a stacked ensemble model to predict social anxiety disorder in university students and compare it with other machine learning models to demonstrate the effectiveness of the proposed model. AUC and F1 are used as classification evaluation metrics. The experimental results show that in this dataset, the model combining logistic regression, Naive Bayes, and KNN algorithms as the first layer and Naive Bayes as the second layer performs better than traditional machine learning algorithms. This provides a new approach to studying social anxiety disorder. [ABSTRACT FROM AUTHOR]

With the continuous development of artificial intelligence technology and the exponential growth in the number of images, image detection and recognition technology is becoming more widely used. Image knowledge management is extremely urgent. The data source of a knowledge graph is not only the text and structured data but also the visual or auditory data such as images, video, and audio. How to use multimodal information to build an information management platform is a difficult problem. In this paper, a method is proposed to construct the result of image recognition as a knowledge graph. First of all, based on the improvement in the BlendMASK algorithm, the hollow convolution kernel is added. Secondly, the effect of image recognition and the relationships between all kinds of information are analyzed. Finally, the image knowledge graph is constructed by using the relationship between the image entities. The contributions of this paper are as follows. (1) The hollow convolution kernel is added to reduce the loss from extracting feature information from high-level feature images. (2) In this paper, a method is proposed to determine the relationship between entities by dividing the recognition results of entities in an image with a threshold, which makes it possible for the relationships between images to be interconnected. The experimental results show that this method improves the accuracy and F1 value of the image recognition algorithm. At the same time, the method achieves integrity in the construction of a multimodal knowledge graph. [ABSTRACT FROM AUTHOR]

The orthogonal triangular factorization (QRF) method is a widespread tool to calculate eigenvalues and has been used for many practical applications. However, as an emerging topic, only a few works have been devoted to handling dynamic QR factorization (DQRF). Moreover, the traditional methods for dynamic problems suffer from lagging errors and are susceptible to noise, thereby being unable to satisfy the requirements of the real-time solution. In this paper, a bounded adaptive function activated recurrent neural network (BAFARNN) is proposed to solve the DQRF with a faster convergence speed and enhance existing solution methods' robustness. Theoretical analysis shows that the model can achieve global convergence in different environments. The results of the systematic experiment show that the BAFARNN model outperforms both the original ZNN (OZNN) model and the noise-tolerant zeroing neural network (NTZNN) model in terms of accuracy and convergence speed. This is true for both single constants and time-varying noise disturbances. [ABSTRACT FROM AUTHOR]

Cultivated land quality (CLQ) is associated with national food security, benign economic development, social harmony, and stability. The scientific evaluation of CLQ provides the basis for achieving the "trinity" protection of cultivated land quantity, and quality, as well as ecology. However, the current research on CLQ evaluation has some limitations, mainly the poor consideration of evaluation indicators, time-consuming and labor-intensive data acquisition, and low precision of evaluation at the regional scale. Therefore, this study introduced multisource data to evaluate CLQ and proposed a new method for CLQ evaluation (natural grade evaluation, utilization grade evaluation, and economic grade evaluation), combining multisource data and the recurrent neural network (RNN) algorithm. Initially, optimal indicators were determined by correlation analysis and generalized linear regression coefficient methods based on factors related to CLQ acquired from multisource data. Then, CLQ evaluation models were constructed with the RNN algorithm on the basis of the aforementioned optimal indicators. Finally, the models were adopted to map CLQ. The present study was carried out in Guangzhou City, Guangdong Province, China. According to the results: (1) CLQ showed close relationship to pH, effective soil layer thickness (EST), chemical fertilizer application rate (CHFE), organic matter content (OMC), annual accumulated temperature (TEMA), 5–15 cm soil depth soil cation exchange capacity (CEC515), 0–5 cm soil depth soil cation exchange capacity (CEC05), 5–15 cm soil depth soil organic carbon content (SOC515), 0–5 cm soil depth soil organic carbon content (SOC05), field slope (FS), groundwater level (GWL), and terrain slope (TS). (2) All modeling accuracies ( R 2 ) were greater than 0.80 for the CLQ evaluation models constructed based on the RNN algorithm. The area and spatial distribution of each grade of CLQ evaluation were consistent with the actual situation. The best and the worst quality cultivated land occupied a small area, and the area without a gap with the actual CLQ was as high as 76%, indicating that the model results were reliable. The study shows the suitability of the method for evaluating CLQ at the regional scale, offering a scientific foundation for the rational utilization and management of cultivated land resources, as well as a reference for evaluating CLQ in the future. [ABSTRACT FROM AUTHOR]

Simple Summary: Biological control of plant diseases caused by fungal pathogens using antagonistic microorganisms including Bacilli has been considered to be an effective and safe alternative to chemical fungicides. Fusarium crown rot of wheat is a serious fungal disease affecting yield and grain quality. In this study, a newly isolated strain of Bacillus subtilis YB-15 from soil of wheat rhizosphere significantly inhibited Fusarium crown rot as well as improved growth of wheat seedlings. Multiple potential biocontrol and growth-promoting attributes of Bacillus subtilis YB-15 were determined in vitro and according to the whole genome sequencing analysis. Overall, the results demonstrated that Bacillus subtilis YB-15 has great potential for practical application in controlling plant fungal diseases and improving plant growth. Fusarium crown rot caused by Fusarium pseudograminearum is one of the most devastating diseases of wheat worldwide causing major yield and economic losses. In this study, strain YB-15 was isolated from soil of wheat rhizosphere and classified as Bacillus subtilis by average nucleotide identity analysis. It significantly reduced Fusarium crown rot with a control efficacy of 81.50% and significantly improved the growth of wheat seedlings by increasing root and shoot fresh weight by 11.4% and 4.2%, respectively. Reduced Fusarium crown rot may have been due to direct antagonism by the production of β-1, 3-glucanase, amylase, protease and cellulase, or by the ability of B. subtilis YB-15 to induce defense-related enzyme activities of wheat seedlings, both alone and in seedlings infected with F. pseudograminearum. Improved plant growth may be related to the ability of B. subtilis YB-15 to secrete indole acetic acid and siderophores, as well as to solubilize phosphorus. In addition, the genome of strain YB-15 was determined, resulting in a complete assembled circular genome of 4,233,040 bp with GC content of 43.52% consisting of 4207 protein-encoding genes. Sequencing the B. subtilis YB-15 genome further revealed genes for encoding carbohydrate-active enzymes, biosynthesis of various secondary metabolites, nutrient acquisition, phytohormone production, chemotaxis and motility, which could explain the potential of strain YB-15 to be plant growth-promoting bacteria and biological control agent. B. subtilis YB-15 appears to be a promising biocontrol agent against Fusarium crown rot as well as for wheat growth promotion. [ABSTRACT FROM AUTHOR]

In this paper, some tactics are considered in Xinjiang tourism industrial belt based on performance evaluation. First, we applied the Balanced Scorecard (BSC) to establish an evaluation system for Xinjiang tourism development in four dimensions: tourism performance, resource utilization, basic supporting capacity, and market attention. Second, the performance of tourism development in 14 Prefectures was evaluated using the Analytic Hierarchy Process (AHP) in 2018. Third, because the Prefectures were divided into four tourism industrial belts, a discussion was conducted to identify and understand the difference among them and their corresponding influence on regional tourism development using the Theil index and Entropy method. The result shows that (1) In all dimensions, the differences within each industrial belt were greater than those between industrial belts. (2) The tourism industrial belts displayed a differentiation phenomenon, in the dimension of significant difference being distinct for different belts. Finally (3), it is found that the resource utilization of all belts is significantly different. [ABSTRACT FROM AUTHOR]

Determining the coupling development mode and evolution process of the tourism–urbanization–ecological environment system is of great significance in promoting high-quality and sustainable development of tourism and the urban economy. In this study, an evaluation index system of the tourism–urbanization–ecological environment system was established, and the spatiotemporal differentiation of the coupling and coordination relationship of the tourism–urbanization–ecological environment system was analyzed for 35 major tourist cities in China from 2009 to 2018. The results show that the comprehensive development indices of the tourism industry subsystem and urbanization subsystem of China's major tourist cities have steadily increased. The comprehensive development indices of large-sized and medium-sized cities in the east are relatively high. From 2009 to 2018, the coordination degree and coupling degree of the tourism–urbanization–ecological environment' system of 35 tourist cities showed an upward trend. The growth rate of the coupling coordination degree lags behind the growth rate of the coupling degree, and the overall system coordination level is still low. There are significant differences in the coupling degree and coupling coordination degree among the eastern, central, and western cities. This study offers both theoretical and practical implications for further equalizing the development level between the cities, as well as improving the overall coordination between the tourism industry, urbanization, and the ecological environment in China. [ABSTRACT FROM AUTHOR]