Study on Tourism Economic Ecology of Provincial Capital Cities along the Silk Road

The Silk Road tourism area master plan (2008-2020) launched by the National Tourism Administration in 2007 takes the China section of the desert oasis silk road as the planning object, involving Henan Province, Shaanxi Province, Ningxia Hui Autonomous Region, Gansu Province, Qinghai Province, Xinjiang Uygur Autonomous Region and Xinjiang production and Construction Corps. Xi'an, Lanzhou, Xining, Yinchuan and Urumqi are all excellent tourist cities accepted by the National Tourism Administration, and they are also hot tourist cities in their provinces. Therefore, this paper selects the five provincial capital cities as the research object, and investigates the coordination degree of the tourism economic system and the ecological environment system of these cities, which is helpful to clarify the problems existing in the current tourism development and ecological environment protection of these cities. These studies can also provide reference for the relevant departments to formulate tourism development and ecological environment protection policies, and also have a certain reference for other cities along the silk road

Study on Tourism Economic Ecology of Provincial Capital Cities Along the Silk Road

The Silk Road tourism area master plan (2008-2020) launched by the National Tourism Administration in 2007 takes the China section of the desert oasis silk road as the planning object, involving Henan Province, Shaanxi Province, Ningxia Hui Autonomous Region, Gansu Province, Qinghai Province, Xinjiang Uygur Autonomous Region and Xinjiang production and Construction Corps. Xi'an, Lanzhou, Xining, Yinchuan and Urumqi are all excellent tourist cities accepted by the National Tourism Administration, and they are also hot tourist cities in their provinces. Therefore, this paper selects the five provincial capital cities as the research object, and investigates the coordination degree of the tourism economic system and the ecological environment system of these cities, which is helpful to clarify the problems existing in the current tourism development and ecological environment protection of these cities. These studies can also provide reference for the relevant departments to formulate tourism development and ecological environment protection policies, and also have a certain reference for other cities along the silk road

A new Approach to Erdos Collaboration Network using PageRank

Using the data on Paul Erdos, his co-authors and their co-authors, we can construct a network called the Erd?s Collaboration network. Then we do reduction, analysis and visualization with it using program Pajek. In this paper, we develop a reasonable academic influence measuring method applying PageRank algorithm on the case of the Erd?s Collaboration network. We find that ALON, NOGA M is the most influential mathematician in the network. In addition, to measure impact, we construct a dynamic model, whereas it needs too much data for us to calculate the dynamic index. Keywords: PageRank, Collaboration network, Network analysis

The relations between China and the European Union heading into the new century

After giving a brief historical review of the political and economic relations between the People’s Republic of China and the European Union, the author focuses on the present state of these relations and on their future prospects. In this sense, the author highlights the good state of bilateral contacts and common ground between both geographical areas, mainly in their view of the current international context, post-September 11 and with China’s entry into the World Trade Organisation

A Dynamic Scene Vision SLAM Method Incorporating Object Detection and Object Characterization

Simultaneous localization and mapping (SLAM) based on RGB-D cameras has been widely used for robot localization and navigation in unknown environments. Most current SLAM methods are constrained by static environment assumptions and perform poorly in real-world dynamic scenarios. To improve the robustness and performance of SLAM systems in dynamic environments, this paper proposes a new RGB-D SLAM method for indoor dynamic scenes based on object detection. The method presented in this paper improves on the ORB-SLAM3 framework. First, we designed an object detection module based on YOLO v5 and relied on it to improve the tracking module of ORB-SLAM3 and the localization accuracy of ORB-SLAM3 in dynamic environments. The dense point cloud map building module was also included, which excludes dynamic objects from the environment map to create a static environment point cloud map with high readability and reusability. Full comparison experiments with the original ORB-SLAM3 and two representative semantic SLAM methods on the TUM RGB-D dataset show that: the method in this paper can run at 30+fps, the localization accuracy improved to varying degrees compared to ORB-SLAM3 in all four image sequences, and the absolute trajectory accuracy can be improved by up to 91.10%. The localization accuracy of the method in this paper is comparable to that of DS-SLAM, DynaSLAM and the two recent target detection-based SLAM algorithms, but it runs faster. The RGB-D SLAM method proposed in this paper, which combines the most advanced object detection method and visual SLAM framework, outperforms other methods in terms of localization accuracy and map construction in a dynamic indoor environment and has a certain reference value for navigation, localization, and 3D reconstruction

Improving the Accuracy of Direction of Arrival Estimation with Multiple Signal Inputs Using Deep Learning

In this paper, an innovative cyclic noise reduction method and an improved CAPON algorithm (also the called minimum variance distortionless response (MVDR) algorithm) are proposed to improve the accuracy and reliability of DOA (direction of arrival) estimation. By processing the eigenvalues obtained from the covariance matrix of the received signal, the signal-to-noise ratio (SNR) can be increased by up to 5 dB by the cyclic noise reduction method, which will improve the DOA estimation accuracy. The improved CAPON algorithm has a convolution neural network (CNN) structure, whose input is the processed covariance matrix of the received signal, and the CAPON spectral value is used as the training label to obtain the estimated spatial spectrum. It retains the advantages of the CAPON algorithm, which can achieve blind source estimation, and simulations show that the proposed algorithm exhibits a better performance than the traditional algorithm in conditions of various SNRs and snapshot numbers. The simulation results show that, based on a certain SNR, the root mean square error (RMSE) of the improved CAPON algorithm can be reduced from 0.86° to 0.8° compared to traditional algorithms, and the angle estimation error can be decreased by up to about 0.3°. With the help of the cyclic noise reduction method, the angle estimation error decreases from 0.04° to 0.02°

Reporting form and content of research priorities identified in knee osteoarthritis clinical practice guidelines: a methodological literature analysis

Objectives Clinical practice guideline (CPG) developers conduct systematic summaries of research evidence, providing them great capacity and ability to identify research priorities. We systematically analysed the reporting form and content of research priorities in CPGs related to knee osteoarthritis (KOA) to provide a valuable reference for guideline developers and clinicians.Design A methodological literature analysis was done and the characteristics of the reporting form and the content of the research priorities identified in KOA CPGs were summarised.Data sources Six databases (PubMed, Embase, China National Knowledge Infrastructure, VIP Database for Chinese Technical Periodicals, Wanfang and Chinese Biomedical Literature Database) were searched for CPGs published from 1 January 2017 to 4 December 2022. The official websites of 40 authoritative orthopaedic societies, rheumatology societies and guideline development organisations were additionally searched.Eligibility criteria We included all KOA CPGs published in English or Chinese from 1 January 2017 that included at least one recommendation for KOA. We excluded duplicate publications, older versions of CPGs as well as guidance documents for guideline development.Data extraction and synthesis Reviewers worked in pairs and independently screened and extracted the data. Descriptive statistics were used, and absolute frequencies and proportions of related items were calculated.Results 187 research priorities reported in 41 KOA CPGs were identified. 24 CPGs reported research priorities, of which 17 (41.5%) presented overall research priorities for the entire guideline rather than for specific recommendations. 110 (58.8%) research priorities were put forward due to lack of evidence. Meanwhile, more than 70% of the research priorities reflected the P (population) and I (intervention) structural elements, with 135 (72.2%) and 146 (78.1%), respectively. More than half of the research priorities (118, 63.8%) revolved around evaluating the efficacy of interventions. Research priorities primarily focused on physical activity (32, 17.3%), physical therapy (30, 16.2%), surgical therapy (27, 14.6%) and pharmacological treatment (26, 14.1%).Conclusions Research priorities reported in KOA CPGs mainly focused on evaluating non-pharmacological interventions. There exists considerable room for improvement for a comprehensive and standardised generation and reporting of research priorities in KOA CPGs