AIM: To identify and characterize the 100 most influential articles in the field of myopia over the last decades.
METHODS: Articles on myopia published between January 1975 and March 2020 were searched through the Web of Science Core Collection database. Two independent authors reviewed and determined the 100 most cited articles. The characteristics of each eligible article were recorded, including authors, institutions, countries, journals, publication date, total citations (TCs), annual citations (ACs), research focus and article type.
RESULTS: The top 100 most influential articles were published between 1983 and 2016, with 1999 as the most prolific year. The mean number of TCs was 288 (range: 193-537) and the mean number of ACs was 19 (range: 7-109). Treatment and epidemiology of myopia were the most important research focus. These articles were published in 21 journals led by Ophthalmology (29%) followed by Investigative Ophthalmology & Visual Science (23%). The number of ACs for articles published in the last ten years was significantly higher than that for the other most-cited articles (44 vs 16, Mann-Whitney U test P<0.01). There is no difference in the number of TCs between original articles and review articles, while the number of ACs for review articles was significantly higher than that for original articles (22 vs 17, Mann-Whitney U test P<0.05).
CONCLUSION: This bibliometric analysis can provide us with concise information about the development trend of research in the field of myopia in the past few decades, and provide an important reference for researchers to guide future research.
At its present stage of internationalization of education, its architecture and forms have changed. The study of these aspects requires an integrated approach. Increasing the volume of exports of educational services remains a priority for Russia, which, according to the authors, does not realize its educational export potential sufficiently. The purpose of the article is to reveal the features of the current stage of internationalization of higher education through the compilation of its complex characteristics by a set of cross-sections, to interpret the calculations obtained in a new way, to identify new facts and factors affecting the development trend and to develop proposals for Russia as an exporter of educational services. The main sources used were the statistical databases of the WTO, the EEC of the EAEU. Analytical approach, comparative and statistical analysis were used. As a result, the authors found confirmation of the continuing trend of growth in global spending on education, the volume of investments in the global market of educational services, an increase in the number of foreign students, and the preservation of Russia's share in the number of foreign students. The authors also identified new characteristics of the global educational services market, such as: the acceleration of the growth rate of global exports of educational services, the decline in the share of the United States and the growth of the share of the UAE in the global educational services market, the transformation of Asian countries from donors to recipient countries of educational services.
This paper introduces the basic concepts and main characteristics of parallel self-organizing networks and analyzes and predicts parallel self-organizing networks through neural networks and their hybrid models. First, we train and describe the law and development trend of the parallel self-organizing network through historical data of the parallel self-organizing network and then use the discovered law to predict the performance of the new data and compare it with its true value. Second, this paper takes the prediction and application of chaotic parallel self-organizing networks as the main research line and neural networks as the main research method. Based on the summary and analysis of traditional neural networks, it jumps out of inertial thinking and first proposes phase space. Reconstruction parameters and neural network structure parameters are unified and optimized, and then, the idea of dividing the phase space into multiple subspaces is proposed. The multi-neural network method is adopted to track and predict the local trajectory of the chaotic attractor in the subspace with high precision to improve overall forecasting performance. During the experiment, short-term and longer-term prediction experiments were performed on the chaotic parallel self-organizing network. The results show that not only the accuracy of the simulation results is greatly improved but also the prediction performance of the real data observed in reality is also greatly improved. When predicting the parallel self-organizing network, the minimum error of the self-organizing difference model is 0.3691, and the minimum error of the self-organizing autoregressive neural network is 0.008, and neural network minimum error is 0.0081. In the parallel self-organizing network prediction of sports event scores, the errors of the above models are 0.0174, 0.0081, 0.0135, and 0.0381, respectively.
The creep slope is a dynamic development process, from stable deformation to instability failure. For the slope with sliding zone, it generally creeps along the sliding zone. If the sliding zone controlling the slope sliding does not have obvious displacement, and the slope has unexpected instability without warning, the harm and potential safety hazard are often much greater than the visible creep. Studying the development trend of this kind of landslide is of great significance to slope treatment and landslide early warning. Taking Xiashan village landslide in Huishan Town, Xinchang County, Zhejiang Province as an example, the landslide point was determined by numerical simulation in 2006. Generally, the landslide is a typical long-term slow deformation towards the free direction. Based on a new round of investigation and monitoring, this paper shows that there are signs of creeping on the surface of the landslide since 2003, and there is no creep on the deep sliding surface. The joint fissures in the landslide area are relatively developed, and rainfall infiltration will soften the soft rock and soil layer and greatly reduce its stability. This paper collects and arranges the rainfall data of the landslide area in recent 30 years, constructs the slope finite element model considering rainfall conditions through ANSYS finite element software, and carries out numerical simulation stability analysis. The results show that if cracks appear below or above the slope’s sliding surface, or are artificially damaged, the sliding surface may develop into weak cracks. Then, the plastic zone of penetration is offset; In the case of heavy rain, the slope can unload itself under the action of rainfall. At this time, the slope was unstable and the landslide happened suddenly.
Lignin is the second-largest plant polymer on Earth after cellulose. About 98% of lignin produced in the papermaking and pulping industry is used for combustion heating or power generation. Less than 2% of lignin is used in more valuable fields, mainly in the formulation of dispersants, adhesives, and surfactants. Asphalt is one of the most important materials in pavement engineering. It is a dark brown complex mixture composed of hydrocarbons with different molecular weights and their non-metallic derivatives. Because the chemical structure of lignin is similar to that of asphalt, it is a carbon-based hydrocarbon material. More researchers studied the application of lignin in pavement engineering. In this paper, the structure, application, and extraction technology of lignin were summarized. This is a review article describing the different applications of lignin in pavement engineering and exploring the prospects of the application. There are three main types of pavement materials that can be used for lignin in pavement engineering, which are asphalt, asphalt mixture, and roadbed soil. In asphalt, lignin can be used as a modifier, extender, emulsifier, antioxidant, and coupling agent. In asphalt mixtures, lignin can be used as an additive. In road base soils, lignin can be used as a soil stabilizer. Furthermore, the article analyzed the application effects of lignin from the life cycle assessment. The conclusions suggest that lignin-modified asphalt exhibits more viscosity and hardness, and its high-temperature resistance and rutting resistance can be significantly improved compared with conventional asphalt. In addition, some lignin-modified asphalt binders exhibit reduced low-temperature crack resistance and fatigue resistance, which can be adjusted and selected according to the climate change in different regions. The performance of lignin as an asphalt mixture additive and asphalt extender has been proved to be feasible. Lignin can also produce good mechanical properties as well as environmental benefits as a soil stabilizer. In summary, lignin plays an important role in asphalt pavement and roadbed soil, and it is likely to be a development trend in the future due to its environmental friendliness and low cost. More research is needed to generalize the application of lignin in pavement engineering.
Since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic, the pandemic situation has begun to undergo positive changes with the joint efforts of various countries and world organizations. However, pressures such as the COVID-19 mutations and the sharp rise in confirmed cases have brought uncertainties to the prevention and control of the pandemic. The overall situation is still severe and complex. Based on the multi-dimensional spatial-temporal COVID-19 data collected by the open-source NetEase News (NEN) website and a real-time dynamic website, it is to explore the characteristics of the pandemic data, visualize the development trend, and analyze the spread of the pandemic in this paper. Moreover, it is to provide a rule basis for the prevention and control of the COVID-19 pandemic by constructing the decision tree model. From the results, some suggestions are provided for decision-makers.
Accurate acquisition of the moisture field distribution in in situ soil is of great significance to prevent geological disasters and protect the soil ecological environment. In recent years, rapidly developed fiber-optic sensing technology has shown outstanding advantages, such as distributed measurement, long-distance monitoring, and good durability, which provides a new technical means for soil moisture field monitoring. After several years of technical research, the authors’ group has made a number of new achievements in the development of fiber-optic sensing technology for the soil moisture field, that is, two new fiber-optic sensing technologies for soil moisture content, including the actively heated fiber Bragg grating (AH-FBG) technology and the actively heated distributed temperature sensing (AH-DTS) technology, and a new fiber-optic sensing technology for soil pore gas humidity are developed. This paper systematically summarizes the three fiber-optic sensing technologies for soil moisture field, including sensing principle, sensor development and calibration test. Moreover, the practical application cases of three fiber-optic sensing technologies are introduced. Finally, the development trend of fiber-optic sensing technology for soil moisture field in the future is summarized and prospected.
Industrial green technology innovation has become an important content in achieving high-quality economic growth and comprehensively practicing the new development concept in the new era. This paper measures the efficiency of industrial green technology innovation and regional differences based on Chinese provincial panel data from 2005 to 2018, using a combination of the super efficiency slacks-based measure (SBM) model for considering undesirable outputs and the Dagum Gini coefficient method, and discusses and analyses the factors influencing industrial green technology innovation efficiency by constructing a spatial econometric model. The results show that: firstly, industrial green technology innovation efficiency in China shows a relatively stable development trend, going through three stages: “stationary period”, “recession period” and “growth period”. However, the efficiency gap between different regions is obvious, specifically in the eastern > central > western regions of China, and the industrial green technology efficiency innovation in the central and western regions is lower than the national average. Secondly, regional differences in the efficiency of industrial green technology innovation in China are evident but tend to narrow overall, with the main reason for the overall difference being regional differences. In terms of intra-regional variation, variation within the eastern region is relatively stable, variation within the central region is relatively low and shows an inverted ‘U’ shaped trend, and variation within the western region is high and shows a fluctuating downward trend. Thirdly, the firm size, government support, openness to the outside world, environmental regulations and education levels contribute to the efficiency of industrial green technology innovation. In addition, the industrial structure hinders the efficiency of industrial green technology innovation, and each influencing factor has different degrees of spatial spillover effects.
In regard to knowledge economy, the current concept in the model construction of online education, including distance education and online learning, generally refers to a kind of network-based learning behavior, similar to the concept of online training. Compared with traditional offline education methods, through the application of information technology and internet technology for content dissemination and rapid learning, online education has the characteristics of high efficiency, convenience, low threshold, and rich teaching resources. Online education covers a wide range of people, different forms of learning, and its classification methods are more diverse. Online education services are the fastest growing field of education informatization. At the moment, the most pressing problems include effectively integrating educational resources with internet technology, launching online education services and products that are highly interactive and would encourage personalized learning, increasing user stickiness, as well as avoiding trend-following and conceptualized investment.
Intelligent unmanned mining is a key process in coal mine production, which has direct impact on the production safety, coal output, economic benefits and social benefits of coal mine enterprises. With the rapid development and popularization of 5G+ intelligent mines and coal mine intelligent equipment in China, the intelligentization of intelligent unmanned mining has become an important research topic. Especially with the promulgation of some Chinese policies and regulations, intelligent unmanned mining technology has become one of the key technologies of coal mine production. To understand the connotation, status quo and development trends of intelligent unmanned mining, this paper takes the relationship between key technologies and engineering application of intelligent unmanned mining in China as the perspective. It is proposed that the intelligent unmanned mining technology is in the whole process of working face mining. A research structure of unmanned follow-up operation and safe patrol is changing to the mode of intelligent adaptive mining, followed by the basic concepts and characteristics of intelligent unmanned mining. Relevant researches that maybe beneficial to the proposed research content are reviewed in four layers, which include basic theory, key technology, mining mode, and overall design system theory and technology. Finally, the current intelligent unmanned mining mode and future trends in this field in China are summarized.