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In today's university era, reforming the English teaching model has become a major research topic for researchers. Based on this, this paper adopts a hierarchical and progressive model construction method to further explore the reform model of university English teaching in the context of educational ecology. First, this paper discusses the development of the layered progressive approach in various countries and the current status of the layered progressive approach. By allowing the use of the model of the layered progressive approach, the data related to the reform of university English teaching were analyzed and organized. The combination of internal optimization, data-theoretic learning algorithms, and data federation algorithms for the model of the hierarchical incremental approach are also investigated. The results of the study show that the layered progressive model of college English teaching reform has good results through specific practical applications in a strengthened educational ecosystem.

The higher education efficiency evaluation model using the data envelopment analysis method has interested many researchers. This paper uses bibliometric analysis on publications extracted from the Scopus database to provide a comprehensive overview of research publications on the measurement of higher education efficiency based on data envelopment analysis: its growth rate, major collaboration networks, the most important and popular research topic. A total of 169 related publications were collected and analyzed from 1988 to 2021. The analysis results show that: Publications published every year have increased sharply in the last six years; The quality of publications is relatively high as publications tend to be published in journals with high-ranking indexes; Countries with the most influence in studies on this topic are: Italy, China, Spain, the USA, and the United Kingdom; Authors with the most influence in this research direction are Agasisti T., Abbott M., Doucouliagos C., Avkiran N.K., and Johnes J.; The research cooperation among countries and among affiliations is not strong. Finally, the paper has provided recommendations for future studies based on the findings.

Breaking through the company's own green knowledge barriers through school-enterprise cooperation has become an important means for companies to expand market competitive advantages and environmental governance. This article uses China's non-financial listed company data from 2010 to 2021 to study the causal effect of school-enterprise cooperation on corporate green innovation. The results passed a series of robustness tests and confirmed that school enterprise cooperation can improve the level of green innovation of enterprises. This paper also uses the instrumental variable method to mitigate the causal relationship between the two. The results show that school-enterprise cooperation can still significantly improve corporate green innovation. The results of the mechanism test confirm that school-enterprise cooperation will promote corporate green innovation by reducing corporate green innovation risks and easing corporate financing constraints. At the same time, the heterogeneity analysis results show that school-enterprise cooperation has a better effect on improving green innovation for enterprises in heavily polluting industries, enterprises in years with low economic policy uncertainty, and enterprises with a high degree of government-enterprise connection. The findings of this article help to understand the intrinsic mechanism between school-enterprise cooperation and corporate green innovation, and confirm that school-enterprise cooperation can improve the climate and environmental innovation system, which has important practical significance for the construction of the industry-university-research system.

The severity of plastic pollution is increasing, and delaying sustainable development is not an option. China is a large consumer of plastic, so it is essential to encourage the use of eco-friendly shopping bags there. The paper focuses on the recognition and use of eco-friendly shopping bags among young people in Guangdong Province, China, and determines what factors can lead to a rise in the use of these bags. A questionnaire was utilized to gather data from 392 young people in Guangdong Province using a quantitative research approach. According to the data from the questionnaire, they generally are supportive of eco-friendly shopping bags. Ultimately, the paper's data emphasize the positive effects of materials (paper material), function (internal compartment), and design (green label). For the purpose of advocating sustainable development, this paper provides helpful guidance for the design of eco-friendly shopping bags. [ABSTRACT FROM AUTHOR]

For those receiving funding from the UK HEFCE-funded Open Educational Resource Programme (2009-2012), the sustainability of project outputs was one of a number of essential goals. Our approach for the hosting and distribution of health and life science open educational resources (OER) was based on the utilisation of the WordPress.org blogging platform and search engine optimisation (SEO) techniques to curate content and widen discovery. This paper outlines the approaches taken and tools used at the time, and reflects upon the effectiveness of web strategies several years post-funding. The paper concludes that using WordPress.org as a platform for sharing and curating OER, and the adoption of a pragmatic approach to SEO, offers cheap and simple ways for small-scale open education projects to be effective and sustainable.

In response to the problem of inaccurate classification of big data information in traditional English teaching ability evaluation algorithms, this paper proposes an English teaching ability estimation algorithm based on big data fuzzy K-means clustering. Firstly, the article establishes a constraint parameter index analysis model. Secondly, quantitative recursive analysis is used to evaluate the capabilities of big data information models and achieve entropy feature extraction of capability constrained feature information. Finally, by integrating big data information fusion and K-means clustering algorithm, the article achieves clustering and integration of indicator parameters for English teaching ability, prepares corresponding teaching resource allocation plans, and evaluates English teaching ability. The experimental results show that using this method to evaluate English teaching ability has good information fusion analysis ability and improves the accuracy of teaching ability evaluation and the efficiency of teaching resource application.

Data mining (DM) is an in-depth approach to data analysis by mining useful information from large amounts of data, and this technique is now being used in an increasing number of fields. In this paper, the authors present the design of a real-time data analysis system for sports training based on DM technology and use the corresponding mining tools of DM technology to discover relevant patterns or laws hidden in the data. Therefore, using the real-time data analysis system for sports training based on DM technology, useful information and patterns for improving examination performance can be obtained, which can improve targeted teaching methods and help students overcome learning difficulties, providing rational teaching, synchronizing courses, establishing preparation, effectively guiding students in course selection, and improving course quality and educational effectiveness.

With the advent of the big data internet era, the corresponding multimedia technology is also developing. At the same time, as an important place for students to improve their cognitive level and expand their knowledge coverage, the construction of knowledge and information in university libraries will have an important impact on the growth of students and the development of the library itself. Big data not only brings specific challenges to the intelligent information construction of libraries, but also provides opportunities for the further development of intelligent information construction. Therefore, this paper aims to analyze the intelligent informatization construction of university libraries in the multimedia big data environment, make suggestions for the further development of library intelligent informatization construction, and provide reference materials for library intelligent informatization construction.

This article describes how the Sichuan University - Pittsburgh Institute has embraced new methods and new technologies to ensure high-quality laboratory teaching during the COVID-19 pandemic. Taking Mechanical Measurements 1 course as an example, this paper introduces two lab projects that were successfully transferred into online experiments through remote-control platform and virtual simulation software, as well as three lab projects which were transformed into "pocket labs" where cheap and easy-access equipment was mailed to enable students to conduct experiments at home. Meanwhile, video demos, online Q&A sessions, feedback collection were employed to deliver a realistic lab experience to students.

The rise of big data technology provides direction and support for the reform and development of education. Big data technology can realize the inventory management and effective dynamic monitoring of schools, students, and teachers. It is conducive to comprehensively and accurately controlling the development of teaching activities, injecting new ideas and working ideas into teaching activities, and providing essential guidance for personalized teaching. This paper reviewed the detailed process of applying big data in education to teaching practice based on the case of a middle school in China. Furthermore, it pointed out the factors hindering the large-scale development of big data in the education field, aiming to provide directions for applying big data in education.

Substantial amount of research regarding L2 learners' beliefs has been conducted in recent years. However, not enough attention has been paid to investigating the nature of learners' beliefs; hence our understanding of the construct is contradictory in the sense that early research studies report stability in beliefs, while more recent studies provide evidence of change in learners' beliefs. This paper reports on a case study aiming at contributing to a deeper understanding of the nature of language learners' beliefs. Data were gathered longitudinally over an 18-week period using a number of tools. The findings reveal the complexity of learners' beliefs. The beliefs that the learners held were not always in harmony and some of them can be self-contradictory. Furthermore, while some beliefs may evolve and change over time and across situation, others may remain relatively stable, suggesting the complex and dual nature of learners' beliefs. Drawing on these findings, the paper concludes that learner beliefs can best be perceived as an inter-related construct that has dual features and sometimes can be paradoxical.

From the connotation of bilingual education in higher education in China, this paper analyzes the factors that may affect the quality and result of bilingual education, such as faculty and students' English level, teaching materials, curriculum system, classroom instruction, teaching quality control, as well as incentives and other factors. The paper focuses on Fuzzy-AHP model as a university bilingual education quality evaluation system, and build an evaluation index system for quality control of bilingual teaching. It also conducts quantitative analysis using analytic hierarchy process and fuzzy comprehensive evaluation on the degree of the bilingual education of business courses in Guangdong University of Foreign Studies (GDUFS), China. By selecting evaluation indicators and using analytic hierarchy process, the paper determines corresponding weight of the indicators. It also establishes sets of standard on evaluation and fuzzy relationship matrix, and conducts an empirical study on the degree of bilingual education of business courses in GDUFS. The paper has certain theoretical and practical significance for bilingualism in higher education in China.

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As an important way to expand financing channels, the listing can significantly improve the enterprises' comprehensive competitiveness. However, few studies pay attention to the continuous impact of listing years on enterprise innovation. Based on the sample data of Chinese enterprises before and after listing from 2004 to 2017, this paper discusses the relationship between the listing years and dual innovation. And analyzes the moderating effect of slack. The research shows that the listing years are related to the quantity and quality of innovation in the inverted U-shaped, but the inflection point of the innovation quantity is later than the innovation quality. Before listing, the innovation quantity and quality increased; after listing, the innovation quantity first increased and then decreased, while the innovation quality declined. High slack makes the inverted U-shaped relationship between the listing years and innovation quality steeper. [ABSTRACT FROM AUTHOR]

Unbalanced and insufficient development is a prominent problem in China's period of economic transformation, and an accurate grasp of the current situation and evolutionary trend of innovation and economic development is of great significance in finding a solution and promoting regional coordinated development. This paper introduces the framework of functional data analysis to the study of both innovation and economic development in China, examining its spatial dynamic distribution and convergence characteristic in greater depth. Empirical results revealed the following. (1) Significant regional differences exist in the absolute level of China's innovation development, with a balanced improvement in the development speed and growth potential. Significant differences exist in the absolute level and speed of economic development, but not in the potential energy of development as reflected by acceleration. (2) The σ(t) function of nationwide and regional innovation development shows a downward trend. There is σ(t) convergence in economic development nationwide and in the northeastern, eastern, and western regions, but the regional disparities in economic development within the six central provinces have not yet been effectively mitigated. (3) Nationwide and regional innovation development are in a state of β(t) convergence. There is significant β(t) convergence in the nationwide economic development, with a transition point from divergence to convergence in the northeastern, eastern, and western regions. However, the β(t) function of economic development in the central region shows a region-wide divergence. The findings of this paper have important policy implications for recognizing the balance and disparities in innovation and economic development among regions in China and promoting coordinated regional development. [ABSTRACT FROM AUTHOR]

This case study analyzed data from an asynchronous written mediated exchange between a native speaker and nonnative speaker of English. Three methods of analysis-error analysis, propositional complexity (idea units), and qualitative analysis were used to analyze learner performance over time. The results from these methods were visualized and interpreted according from Complex Dynamic Systems Theory (CDST) perspective, which allows longitudinal language production data to be interpreted from multiple perspectives so that change can be understood at both the micro and macro levels. Results from the analysis revealed patterns of linguistic change both within and between participants as they interacted over time. Several instances of continuity in language production were observed between the participants, including a drop in error rate that coincided with an increase in minor idea units during one turn of the exchange. Results from a qualitative analysis offer several explanations for this finding and are related to the implications this holds for CDST.

This paper investigates whether and how export growth to China varies following shocks in bilateral political relations between China and six Southeast Asian countries—Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam—between 2000 and 2019. High‐frequency news data is used to quantify bilateral political relations between each of the six countries and China. Then, a net cooperation index, plus separate indices of political cooperation and conflict, are placed in an augmented gravity model of trade situated in a vector autoregression framework alongside real exchange rate and industrial production variables to examine the short‐ (months) and long‐run (years) effects of shocks to bilateral political relations on each countryʼs exports growth to China. The results reveal that political relations with China played a role in Thailandʼs and Vietnamʼs exports growth to China but not in Indonesiaʼs, Malaysiaʼs, the Philippinesʼ and Singaporeʼs, and contribute new findings to the literature on politics and trade. Code and data for the analysis is available at: https://github.com/tradepolsrepository/tradepols.git. [ABSTRACT FROM AUTHOR]

Qualitative research strategy has been widely adopted by educational researchers in order to improve the quality of their empirical studies. This paper aims to introduce a generic inductive approach, pragmatic and flexible in qualitative theoretical support, by describing its application in a study of non-English major undergraduates' English learning transition from school to university in China. Through an analysis of how this case study was conducted, the main features of the generic inductive approach are discussed in detail. Subsequently, some suggestions for its effective use are put forward so that this approach can help to provide meaningful interpretive power to make sense of the findings in educational research.

In recent years, in order to address climate change and energy depletion, countries around the world have been constantly promoting energy transformation and structural upgrading. The effectiveness of RCEP has broadened the international east Asian new energy market. The development of renewable energy trade in the context of RCEP has attracted significant economic, environmental, and technical attention. Based on the background of RCEP in this study, the constant market share (CMS) model and the weighted dominant comparative advantage (IRCA) index are used to assess the export competitiveness of renewable energy products from 2006 to 2021. The data in this paper were obtained from the UN comtrade database according to the categorical statistics of HS codes. The results show that: (1) the overall competitiveness of Chinese renewable energy products shows an upward trend; (2) the comparative advantages of Chinese renewable energy products are strong, with some differences among different industries; (3) the growth effect is the main reason for the fluctuation of Chinese renewable energy product exports; and (4) the signing of RCEP has injected new vitality into Chinese renewable energy trade. Finally, based on the research conclusions, the paper puts forward corresponding policy proposal. [ABSTRACT FROM AUTHOR]

Conducting public opinion surveys on sensitive topics like NIMBY ("Not in My Backyard") facilities among China's rural population (often voiceless) is challenging. To advance relevant research, a new mixed-method approach is proposed in this paper based on fieldwork in Huizhou, China, concerning the T Nuclear Power Plant. The approach combines the paper-and-pencil interviewer-administered questionnaires (PAPIAQ) and bystanding interviews (BI). While PAPIAQ prioritizes researcher neutrality, potentially creating a barrier for less educated respondents, BI fosters deeper interaction and clarifies responses. This strengthens both data reliability (through PAPIAQ illustration) and BI text validity (through deeper understanding). Coded BI texts and statistically analysed PAPIAQ data (via elaboration procedure) ultimately generate a more valid and reliable understanding of rural sentiments on sensitive issues. [ABSTRACT FROM AUTHOR]

With the massive use of lithium-ion batteries in electric vehicles and energy storage, the environmental and resource problems faced by used lithium-ion batteries are becoming more and more prominent. In order to better resource utilization and environmental protection, this paper employs bibliometric and data analysis methods to explore publications related to waste lithium-ion battery recycling from 1984 to 2021. The Web of Science core set from the SCIE online database was used for this article. These findings demonstrate a considerable increase trend in the number of publications published in the subject of recycling used lithium-ion batteries, with a natural-sciences-centric focus. Argonne National Lab, Chinese Academy of Sciences, and China Academic and Scientific Research Center are the top three institutions in terms of quantity of papers published. The affiliated journals corresponding to these three institutions also have high impact factors, which are 106.47, 44.85, and 58.69, respectively. In comparison to comparable institutes in other nations, the American Argonne National Laboratory supports 223 research articles in this area. China and the US make up the majority of the research's funding. The two key aspects of current lithium-ion battery recycling research are material structure research and environmentally friendly recycling. Nevertheless, high-capacity lithium-ion batteries, waste lithium-ion integrated structures, and gentle recycling of spent lithium-ion batteries will be the major aspects of study in the future. It is hoped that the above analysis can bring new ideas and methods to the field of waste lithium-ion battery recycling and provide a basis for the subsequent research and application of waste lithium-ion battery recycling. [ABSTRACT FROM AUTHOR]

Nowadays, China is faced with increasing downward pressure on its economy, along with an expanding business risk on listed companies in China. Listed companies, as the solid foundation of the national economy, once they face a financial crisis, will experience hazards from multiple perspectives. Therefore, the construction of an effective financial crisis early warning model can help listed companies predict, control and resolve their risks. Based on textual data, this paper proposes a web crawler and textual analysis, to assess the sentiment and tone of financial news texts and that of the management discussion and analysis (MD&A) section in annual financial reports of listed companies. The emotional tones of the two texts are used as external and internal information sources for listed companies, respectively, to measure whether they can improve the prediction accuracy of a financial crisis early warning model based on traditional financial indicators. By comparing the early warning effects of thirteen machine learning models, this paper finds that financial news, as external texts, can provide more incremental information for prediction models. In contrast, the emotional tone of MD&A, which can be easily modified by the management, will distort predictions. Comparing the early warning effect of machine learning models with different input feature variables, this paper also finds that DBGT, AdaBoost, random forest and Bagging models maintain stable and accurate sample recognition ability. This paper quantifies financial news texts, unraveling implied information hiding behind the surface, to further improve the accuracy of the financial crisis early warning model. Thus, it provides a new research perspective for related research in the field of financial crisis warnings for listed companies. [ABSTRACT FROM AUTHOR]

With the increasing penetration of renewable energy resources, their variable, intermittent and unpredictable characteristics bring new challenges to the power system. These challenges require micro-meteorological data and techniques to provide more support for the power systems, including planning, dispatching, operation, and so on. This paper aims to provide readers with insights into the effects of micro-meteorology on power systems, as well as the actual improvement brought by micro-meteorology in some power system scenarios. This paper provides a review including the relevant micro-meteorological techniques such as observation, assimilation and numerical techniques, as well as artificial intelligence, presenting a relatively complete overview of the most recent and relevant micro-meteorology-related literature associated with power systems. The impact of micro-meteorology on power systems is analyzed in six different forms of power generation and three typical scenarios of different stages in the power system, as well as integrated energy systems and disaster prevention and reduction. Finally, a case study in China is provided. This case takes wind power prediction as an example in a power system to compare the performance when applying micro-meteorological data or not. The experimental results demonstrated that using the micro-meteorological reanalysis dataset with high spatial--temporal resolution for wind power prediction performed better, verifying the improvement of micro-meteorology to the power system to some extent. [ABSTRACT FROM AUTHOR]

Background: New graduate nurses often have certain potential safety hazards for patients due to insufficient knowledge and lack of clinical practice ability. To address these challenges, China has implemented a standardized training strategy. The improvements in the quality of this training involve not only the intervention of teaching methods but also the consideration of personality traits. Methods: The application software based on the BFI-2 Chinese scale was utilized to administer personality tests to nursing students; nursing students were invited to scan the QR code and voluntarily fill in a questionnaire, including basic information, personality test results, and a professional self-efficacy test scale; offline paper-based theoretical examination results of nursing students were collected before and after training. The data was then analyzed using SPSS software version 26.0, which involved descriptive analysis, one-way between-groups analysis of variance (ANOVA) and Spearman correlation analysis. Results: Based on the data, there were no observable differences in the theoretical results before and after training across different personality traits. In terms of skill assessment, conscientiousness exhibited the highest score at 78.91 ± 2.98 points, while negative emotionality showed the lowest score at 74.59 ± 2.12 points. These differences between different personality traits are statistically significant (P < 0.001). In terms of professional self-efficacy, conscientiousness scored the highest at 98.48 ± 12.69, while negative emotionality scored the lowest at 85.89 ± 11.71, with significant differences between different personality traits (P < 0.001). Professional self-efficacy was negatively correlated with agreeableness (r = -0.150, P = 0.044) and positively correlated with conscientiousness (r = -0.310, P < 0.001). Skill scores were negatively correlated with negative emotionality (r = -0.257, P < 0.001) and positively correlated with conscientiousness (r = 0.182, P = 0.014). Conclusions: This study shows that personality traits affect the skills test results and professional self-efficacy of nursing students. Conscientiousness scored the highest in this study, while negative emotionality scored the lowest. Therefore, personalized training plans are recommended to improve the quality of care for such nursing students and to further enhance patient safety. [ABSTRACT FROM AUTHOR]

The dynamics of housing prices can play a pivotal role in shaping household behavior. Motivated by the limited research on the impact of housing prices on consumption structure upgrading in China, this paper presents a series of analyses that deploy panel data from 276 Chinese cities between 2005 and 2019 to scrutinize this impact. Firstly, fixed effect models were used to investigate the relationship between urban housing price and the consumption structure upgrading, and it was found that urban housing price has an inverted U-shaped effect on the consumption structure upgrading of Chinese urban residents, while it has an inhibitory effect on the consumption structure upgrading of Chinese rural residents. Then, we conducted multiple robustness tests, all of which corroborated the benchmark results' reliability. Finally, deeper than existing research, the mechanism of the impact of urban housing prices on the consumption structure upgrading was further explored and it was found that increasing urban housing prices can affect consumption structure upgrading by affecting residents' marginal propensity to consume in development and enjoyment. Our findings provide key alternatives for China's government to promote residents' consumption structure upgrading. [ABSTRACT FROM AUTHOR]

In the context of the continuous promotion of China's big data development strategy, this paper quantitively analyses China's existing national-level big data policies from the perspective of policy instruments and coword networks, discusses the rationality of existing policies, explores ways to improve policies, and provides a reference for the innovation of China's big data policies. This paper carries out a quantitative textual analysis of China's national big data policy from the perspective of policy instruments using word frequency analysis to obtain a keyword coword matrix and visualization analysis tools to obtain a coword network. This paper further studies the network node characteristics and structure using social network analysis methods, including degree centrality, clustering analysis, and multidimensional scale analysis, to identify the policy structure and characteristics. Improving big data policy requires improvements in policy instruments on the supply side, resolving existing policy gaps, and strengthening coordination with other policies. [ABSTRACT FROM AUTHOR]

During the Ming Dynasty, China and Korea exchanged frequently and recorded a large amount of written information, which is of great value for understanding the culture of that time. The large amount of data makes it difficult to conduct quantitative analysis by researchers, which makes the analysis limited. This paper carries out a research on the cognition and analysis method of Chinese and Korean envoys to foreign cultures in Ming Dynasty based on big data analysis technology. Based on the literature research, this paper determines the ontology model establishment method to efficiently detect the written records of Chinese and Korean envoys in Ming Dynasty. The established ontology model and the improved clustering analysis method can improve the efficiency of data detection, reduce the error of data detection, and provide data basis for the research of this paper. According to the technology of big data analysis, this paper analyzes the focus and status class of Chinese and Korean envoys in Ming Dynasty and analyzes cognition of the Chinese and Korean envoys for the foreign culture. The results show that the envoys of the Chinese and Korean pay different attention to the foreign culture due to their different cognition of the foreign culture, compared with Ming Dynasty envoys, Korean envoys paid 15.3 percent less attention to geography, 19.7 percent more to history, 11.7 percent more to people, and 16 percent less to customs. This reflects the two envoys' different perceptions of the foreign culture. And the status class of the envoys exacerbates this difference. In the early Ming Dynasty, the creative diversity of Ming envoys was far lower than that of Korean envoys. As time went by, the creative diversity of Ming envoys increased. The results provide support for further understanding of Chinese and Korean culture and their relationship in Ming Dynasty. [ABSTRACT FROM AUTHOR]

This paper examines whether increased export opportunity improved the relative demand for skilled labors in China's migrants, and whether such effects further improved their investments in their next generation's education. To answer these questions, by employing the National Migrant Monitoring Data, Manufacturing Enterprise Survey, China Customs Database and China's Population survey data, and using international demand shocks to construct instrumental variables, we find that export opportunities do increase the demand for skilled migrants, their wages and the probability that they bring their school-age children to cities. These results indicate that export opportunities not only increase the demand and return for skilled migrants, but also promote the accumulation of human capital for the next generation. [ABSTRACT FROM AUTHOR]

This paper proposes a cloud multi-criteria group decision-making model for teacher evaluation in higher education which is involving subjectivity, imprecision and fuzziness. First, selecting the appropriate evaluation index depending on the evaluation objectives, indicating a clear structural relationship between the evaluation index and objectives and establishing a proper evaluation system are all critical and fundamental tasks. Then, collect expert evaluation data, process data, establish training set to build the decision trees, extract evaluation rules, simplify evaluation process, while reducing the cost of evaluation in real applications. Third, establish the interval cloud evaluation matrix through the decision cloud, transforming the evaluation value through the cloud model, determining the order of importance of the decision program, and make the decision. Finally, an addressing linguistic decision-making problem for college teacher evaluation is provided to illustrate the effectiveness of the proposed model.

In China, private enterprises are becoming more and more important subjects of technological innovation, however(at the same time) financing difficulties of private enterprises are also ubiquitous. The research on the impact of financing methods on technological innovation behavior of private enterprises is conducive for the government to launch more targeted financing support policies.I men private enterprises are becoming the mainbody of technological innovation, but the difficulties in financing is especially heavy in China. Based on the data of the World Bank survey on China's enterprises in 2012, this paper studies the impact of different financing methods on technological innovation behavior of private enterprises. The results show that (1) internal financing can promote the technological innovation behavior of enterprises better than external financing can do and (2) among the various forms of external financing, bank loans have the most significant impact on the technological innovation behavior of private enterprises, followed by commercial credit. [ABSTRACT FROM AUTHOR]

In recent years, companies have employed numerous methods to lower expenses and enhance system efficiency in the oilfield. Energy consumption has constituted a significant portion of these expenses. This paper introduces a normalized consumption factor to effectively evaluate energy consumption in the oilfield. Statistical analysis has been conducted on nearly 45,000 wells from six fields in China. Critical factors such as lifting method, daily production, pump depth, gas–oil ratio (GOR), and well deviation angle were evaluated individually. Results revealed that higher production could lead to lower normalized consumption for beam pumps, progressive cavity pumps, and electric submersible pump systems, thus enhancing system efficiency. Additionally, a higher GOR might result in lower normalized consumption for the beam pump system, while the deviation angle of the well showed negligible impact on the normalized consumption factor. This manuscript offers a method to assess the impacts of artificial lift methods on production and discusses suggestions for reducing consumption associated with each lifting method in the oilfield. [ABSTRACT FROM AUTHOR]

In recent years, global warming has become increasingly severe, and the ecological and environmental problems facing mankind have become increasingly serious. As the main areas of transportation activities, cities are also the main places of carbon emissions. As a necessary condition for human's daily-life travel, it is particularly important to calculate the carbon emissions from urban transportation. Due to the different characteristics of economy and population in different regions of a city, the carbon emissions of urban buses show different characteristics in terms of temporal and spatial distribution. The developments of science and technology promote the application of big data analysis to specific practical life, enabling people to research and solve problems from a new perspective. This paper uses the GPS data of urban buses in Sanya City, China, to identify operation conditions from urban buses, and calculates the distance and time under different conditions. Based on the measured data of carbon emissions, this paper visualizes the distribution characteristics of carbon emissions by density analysis; explains the time distribution characteristics by the visual analysis of carbon emissions in different time periods, working days and rest days, and different energy types; and illustrates the spatial distribution characteristics by the spatial distributions of carbon emissions from Sanya's buses on working days and rest days, as well as in different routes, providing reference for a low-carbon development of urban green transport. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to explore the relationship between formal environmental regulation (FER) and informal environmental regulation (IER), technological innovation and employment. Design/methodology/approach: This paper uses data from the 30 provinces of China during 2003–2015. The impacts of formal and IER and technological innovation on employment are estimated by generalized least squares, and the eastern region of China is analyzed separately. Findings: First, both formal and IERs have different degrees of significant impact on employment, and the relationship is not a simple linear. FER has an inverted U-shaped relationship with employment, but IER has a U-shaped relationship. However, in the test including technological innovation, the results of the national sample and the eastern sample are different. In the eastern sample, the relationship between informal regulation and employment has an inverted U-shaped curve. Second, the results of model 3 and model 6 show that technological innovation has a significant negative effect on employment both in the national and the eastern region sample. Research limitations/implications: This paper puts forward corresponding policy implications: first, in designing environmental regulations, it is necessary to consider not only the stringency but also the type of regulation. Second, environmental regulations need to be differentiated by region. Finally, when designing environmental regulations, it is necessary to consider more flexible employment policies that are contingent on the stringency of regulations, in order to prevent employment decline due to technological innovations. Originality/value: The conclusions about the influence of environmental regulation on employment reached are not consistent in China. Most existing research studies seldom consider environmental regulations into categories and focus only on the whole environmental regulation. This paper pays attention to the influences of different types of environmental regulations on employment. It analyzes the eastern region separately to explore whether there is a difference in the effects of environmental regulations. Furthermore, this considers the effect of technological innovation as a mediator. [ABSTRACT FROM AUTHOR]

With the advent of the era of national live broadcast, the "live broadcast + e-commerce" model reconstructs "people, goods, and fields", and merchants, platforms, and anchors create a new marketing system around consumers' perceptions, attitudes, and emotions to enhance consumer willingness. E-commerce live broadcast ultimately brings back the core of marketing, according to retailers. The psychological contract in the live broadcast is a variable, and its commitment or breach will have an effect on the consumer attitude and consumer emotions. From the perspective of the consumer, stronger consumption motivation, content quality, Netflix charm, trust, and highly interactive consumer expectations must exist. Based on the above background, the understanding of business infrastructure in the digital economy era should also be dynamically adjusted in conjunction with the concept of new infrastructure and business innovation practices. This paper investigates personalized recommendation assessment of credit degree based on data analysis of the live e-commerce industry based on new hybrid crow search algorithm in this context, delves into the state of e-commerce in China today, offers a profound discussion on e-commerce as well as credit degree, and concludes the paper with a general summary. [ABSTRACT FROM AUTHOR]

Microblog has become the "first scenario" under which the public learn about the epidemic situation and express their opinions. Public sentiment mining based on microblog data can provide a reference for the government's information disclosure, public sentiment guidance and formulation of epidemic prevention and control policy. In this paper, about 200,000 pieces of text data were collected from Jan. 1 to Feb. 26, 2020 from Sina Weibo, which is the most popular microblog website in China. And a public sentiment analysis framework suitable for Chinese-language scenarios was proposed. In this framework, a sentiment dictionary suitable for Chinese-language scenarios was constructed, and Baidu's Sentiment Analysis API was used to calculate the public sentiment indexes. Then, an analysis on the correlation between the public sentiment indexes and the COVID-19 case indicators was made. It was discovered that there is a high correlation between public sentiments and incidence trends, in which negative sentiment is of statistical significance for the prediction of epidemic development. To further explore the source of public negative sentiment, the topics of the public negative sentiment on Weibo was analyzed, and 20 topics in five categories were got. It is found that there is a strong linkage between the hot spots of public concern and the epidemic prevention and control policies. If the policies cover the hot spots of public concern in a timely and effective manner, the public negative sentiment will be effectively alleviated. The analytical framework proposed in this paper also applies to the public sentiment analysis and policy making for other major public events. [ABSTRACT FROM AUTHOR]

With the proliferation of online social networks, the identification or classification of real-life relationship between users has been very useful for many applications such as financial fraud detection. In real life, usually people with different relationships would present gifts with special meanings to each other on different dates. In many Asian cultures, especially in Chinese culture, the red packet is a traditional form of monetary gift. With the rapid development of the Internet, people gradually began to give electronic red packets instead of paper ones as the means of money gifting on social network platforms. As motivated, in this paper we advocate a novel approach that exploits users’ red packet interactions for users relationship identification on WeChat, one of the largest social platforms in China. Specifically, we analyze the WeChat red packets network, identify the real-life relationship types between users through mining the semantic information of the amount and sending time of each red packet. In order to better capture the red packet gifting behaviors between users for relationship identification, on one hand, we construct an Amount-Date Graph and apply the graph embedding method to learn embeddings of the amount and sending date of each red packet. On the other hand, we propose a novel sequential model, Cross & Attention Sequence Model (CASM), which explicitly learns the interactions between the latent semantic information of each red packet’s amount and sending date in the red packets sequence between two users. To validate our approach, we conduct comprehensive experiments on a real-world WeChat Users Red Packets dataset that involves 8 kinds of real-life relationships. The experiments show that our proposed approach performs significantly better than baselines and achieves 81.70 percent prediction accuracy. [ABSTRACT FROM AUTHOR]

The development of local government online questioning is a practical exploration to promote the digital governance of government. Exploring the influencing factors of local government online questioning response can provide guidance for the governance practice of online questioning. Based on the TOE framework, this paper constructs an analysis model of the influencing factors of local government online questioning response. By using SPSS tools to conduct regression analysis on data from 230 questionnaire samples, the results show five factors: technical competence, high-level support, perceived benefits, public readiness, and public satisfaction to the responsiveness of local government were 0.019, 0.332, 0.265, 0.156, and 0.048, respectively. Therefore, the research conclusion that technical ability, high-level support, perceived benefits, public readiness, and public satisfaction, have a positive impact on local government's response ability. The analysis of the influencing factors of government's online in this paper improves the existing research to a certain extent and provides a new path and perspective for the development of network politics in China. [ABSTRACT FROM AUTHOR]

The paper presents a novel statistical approach for analyzing the daily coronavirus case and fatality statistics. The survival discretization method was used to generate a two-parameter discrete distribution. The resulting distribution is referred to as the "Discrete Marshall–Olkin Length Biased Exponential (DMOLBE) distribution". Because of the varied forms of its probability mass and failure rate functions, the DMOLBE distribution is adaptable. We calculated the mean and variance, skewness, kurtosis, dispersion index, hazard and survival functions, and second failure rate function for the suggested distribution. The DI index demonstrates that the proposed model can represent both over-dispersed and under-dispersed data sets. We estimated the parameters of the DMOLBE distribution. The behavior of ML estimates is checked via a comprehensive simulation study. The behavior of Bayesian estimates is checked by generating 10,000 iterations of Markov chain Monte Carlo techniques, plotting the trace, and checking the proposed distribution. From simulation studies, it was observed that the bias and mean square error decreased with an increase in sample size. To show the importance and flexibility of DMOLBE distribution using two data sets about deaths due to coronavirus in China and Pakistan are analyzed. The DMOLBE distribution provides a better fit than some important discrete models namely the discrete Burr-XII, discrete Bilal, discrete Burr-Hatke, discrete Rayleigh distribution, and Poisson distributions. We conclude that the new proposed distribution works well in analyzing these data sets. The data sets used in the paper was collected from 2020 year. [ABSTRACT FROM AUTHOR]

The ''last mile'' service experience of catering O2O determines user satisfaction and user loyalty of catering O2O platforms. Evaluating user experience of catering O2O distribution link will help catering O2O platforms find problems in the distribution link and provide theoretical support for the improvement of user experience and user satisfaction. From the perspective of distribution link, based on the user experience theory, this paper uses the literature research method, Delphi method, and questionnaire survey method to establish user experience evaluation index system of catering O2O distribution link, including browsing experience, tangible experience, empathic experience, responsiveness experience, reliability experience, and assurance experience 6 factors, and also establishes the BP neural network model. On the basis, the paper selects the data of well-known platform users in East China coastal regions, and trains and simulates the model. The results show that the model can achieve the evaluation of user experience in O2O distribution link. Finally, suggestions for improving user experience in catering O2O distribution link in East China coastal regions are proposed. [ABSTRACT FROM AUTHOR]

This study proposes a new method named the IIS-map-based method for analyzing interactions in face-to-face collaborative learning settings. This analysis method is conducted in three steps: firstly, drawing an initial IIS-map according to collaborative tasks; secondly, coding and segmenting information flows into information items of IIS; thirdly, computing attributes of information flows and analyzing relationships between attributes and group performance. An example illustrates how the methodology uncovers the interaction process based on information flows. The empirical study aims to validate the effectiveness of this method through thirty groups' interactions. The result indicates that quantity of activation of the targeting knowledge network can predict group performance and the IIS-map-based analysis method can analyze interactions effectively. The primary contribution of this paper is the methodology for analysis of interactions based on information flows. (Contains 8 figures and 4 tables.)

This paper constructs a two-level data fusion model with the classroom environment monitoring background of colleges and universities. By judging the validity of the data received by each sensor, the model eliminates the influence of neglected monitoring values on fusion accuracy. It uses the adaptive weighted average method to fuse the data of the same type of sensors in each area and then uses the BP neural network to fuse the heterogeneous sensor data in the area. After each region sends the fusion result to the gateway node, the second-level fusion is performed. In the second-level fusion, the error between the actual output result and the expected output of the BP neural network is calculated, and it is used as the basic probability assignment in DS; then the D-S synthesis rule is used for decision-level fusion so as to realize the integration of the college classroom environment. Aiming at the shortcomings of the D-S evidence theory, we improved the algorithm with respect to the distance of evidence and the conflict factor. Through the exploration of the multisource data fusion analysis method, it is found that it plays an important role in early vocal music teaching. The quality of early vocal music-teaching teachers has a particularly important impact on the music level of college students. Schools with preschool education majors are important bases for teacher training in early vocal music teaching. In order to expand the application scope of the concept of multisource data fusion in the field of vocal music teaching in China, it is necessary to change the traditional vocal music teaching mode of existing college teachers and pay attention to the integration of multisource data fusion analysis methods and the reforms of colleges and universities. In this paper, the effectiveness of the two-level fusion model is verified by using two evaluation indicators: the mean absolute percentage error and the correlation coefficient. Then, comparing the calculation results of the improved algorithm and the classical algorithm in this paper, it is proved that the probability accumulation of this algorithm is more obvious and consistent with the expected results, which shows the optimization effect of the improved method. [ABSTRACT FROM AUTHOR]

miRNAs biomarkers are emerging as an essential part of clinical oncology. Their oncogenic and tumour suppressor properties playing a role in malignancy has generated interest in their potential for use in disease prognosis. While several studies on miRNA have been carried out across the globe, evaluating the clinical implications of miRNAs in cancer diagnosis and prognosis research has currently not been attempted. A study delineating the area of miRNA research, including the topics presently being focused on, the seminal papers in this field, and the direction of research interest, does not exist. This study aims to conduct a large-scale, global data analysis and bibliometric profiling analysis of studies to evaluate the research output of clinical implications of miRNAs in cancer diagnosis and prognosis listed in the SCOPUS database. A systematic search strategy was followed to identify and extract all relevant studies, subsequently analysed to generate a bibliometric map. SPSS software (version 27) was used to calculate bibliometric indicators or parameters for analysis, such as year and country of affiliation with leading authors, journals, and institutions. It is also used to analyse annual research outputs, including total citations and the number of times it has been cited with productive nations and H-index. The number of global research articles retrieved for miRNA-Cancer research over the study period 2003 to 2019 was 18,636. Between 2012 and 2019, the growth rate of global publications is six times (n = 15,959; 90.71 percent articles) that of 2003 to 2011. (2704; 9.29 per cent articles). China published the most publications in the field of miRNA in cancer (n = 7782; 41%), while the United States had the most citations (n = 327,538; 48%) during the time span. Of these journals, Oncotarget has the highest percentage of article publications. The journal Cancer Research had the most citations (n = 41,876), with 6.20 per cent (n = 41,876). This study revealed a wide variety of journals in which miRNA-Cancer research are published; these bibliometric parameters exhibit crucial clinical information on performance assessment of research productivity and quality of research output. Therefore, this study provides a helpful reference for clinical oncologists, cancer scientists, policy decision-makers and clinical data researchers. [ABSTRACT FROM AUTHOR]

Culture is an important feature that distinguishes human beings from animals. Human beings have created and developed various cultures and influenced people's psychology and behavior in different social forms. With the continuous improvement of China's international influence and cultural soft power, the number of foreign students studying in China is increasing year by year. In this paper, data mining is carried out on the data of international students, and the cross-cultural interaction model of international students is constructed. According to the characteristics of the research object, this paper explores the influence of cultural novelty and psychological capital on its cross-cultural adaptation in order to provide theoretical basis for the improvement of cross-cultural adaptation. It also promotes the better development of international students and the improvement of international exchange management in colleges and universities by providing some ideas for mental health education and management of international students. The importance of cultural study for international students in China is related not only to the development and improvement of foreign students' cognitive level of target culture, but also to the external communication of national cultural image. [ABSTRACT FROM AUTHOR]