LOCALIZATION PATH OF THE RESEARCH PARADIGMS OF LEGAL COMMENTARY IN CHINA—FOCUSING ON THE PUBLIC LEGAL SERVICE FUNCTION OF THE CASE-COMMENTARY RESEARCH ON THE STYLE OF CIVIL LITIGATION DOCUMENTS

Conducting case-commentary research on the style of civil litigation documents is a key method for judges to produce legal documents,develop professional writing and creative skills,and enhance legal thinking.Such a study is an important way to deepen the reform of the judicial power operation mechanism and to improve the trial management mode.Considering the background of the judicial responsibility system reform,the localization of the research paradigms and case-commentary methods of the style of litigation documents can help reach the consensus of the legal professional community.It also helps promote judgment rules and the spirit of the law.Legal commentaries convey the important functions of public legal services to the public.It is necessary to integrate the Style of Civil Litigation Documents,the"one-stop"litigation service with the reform practice of judicial committees in China,and conduct detailed research on the procedural ruling function and guiding function of the style of civil litigation documents.By studying the guiding function of civil litigation document style for judicial behavior,litigation procedure,and entity processing,it is good for judges to broaden their ideas and methods to write civil litigation documents,enabling an examination of the localization path and method of the legal commentary research paradigm and demonstrating how to continue using the paradigm within the context of the comprehensive reform of the judicial system.Moreover,the study emphasizes how to exert the function of public legal services integrated with the style of civil litigation documents.

Methodology and Trends of Linguistic Research in the Era of Big Data

This paper presents methodology and trends of linguistic research in the era of big data.We begin with a discussion of the role of linguists in the information society and illustrate the opportunities and challenges linguists are currently facing.After highlighting the significance of authentic data on linguistic research,we argue that language is a complex adaptive system driven by humans.Then,from the perspective of philosophy of science,we introduce the research paradigm of quantitative linguistics through several cases.Finally,we discuss how China’s linguistic research will benefit from the data-intensive approach in terms of scientification and internationalization.

Problems and Suggestions for the Scientific Research Management System of Universities

The revolution of science and technology in the new era is rising.New industries,formats,and models led by information technology are emerging.Scientific research has entered the fourth data-intensive paradigm.As an important part of the science and technology innovation system,universities also have new requirements for their scientific research management system.In this article,it is suggested that the efficiency and quality of scientific research management in universities could be enhanced by reconstructing the organizational structure of scientific research management,improve the service capabilities of scientific research managers,perfecting the scientific research evaluation system,and innovating the management model of cross-research teams.

Advances in machine learning-and artificial intelligence-assisted material design of steels

With the rapid development of artificial intelligence technology and increasing material data,machine learning-and artificial intelligence-assisted design of high-performance steel materials is becoming a mainstream paradigm in materials science.Machine learning methods,based on an interdisciplinary discipline between computer science,statistics and material science,are good at discovering correlations between numerous data points.Compared with the traditional physical modeling method in material science,the main advantage of machine learning is that it overcomes the complex physical mechanisms of the material itself and provides a new perspective for the research and development of novel materials.This review starts with data preprocessing and the introduction of different machine learning models,including algorithm selection and model evaluation.Then,some successful cases of applying machine learning methods in the field of steel research are reviewed based on the main theme of optimizing composition,structure,processing,and performance.The application of machine learning methods to the performance-oriented inverse design of material composition and detection of steel defects is also reviewed.Finally,the applicability and limitations of machine learning in the material field are summarized,and future directions and prospects are discussed.

Three Paradigms in Lu Xun Research and Contemporary Value Options

Research on Lu Xun is never simply the analysis of an individual writer, but constitutes an understanding of the cultural attributes represented by Lu Xun himself and his writings. Likewise, the evaluation of research on Lu Xun is never a simple evaluation of academic history, but rather a social evaluation associated with the value orientations of those times. At present, with the return of academic logic and the growing tendency toward private research, a noteworthy divergence of standpoints and evaluations of Lu Xun research has emerged. At the same time, as a prominent discipline that has been over-interpreted, research on Lu Xun is demonstrating a tendency toward redundancy and triviality. Three fundamental paradigms are commonly employed in research on Lu Xun： historical research that attempts to explore historical materials; academic research that focuses on knowledge interpretation and aesthetic evaluation; and contemporary research that pursues the contemporary meaning and values of Lu Xun＇s ideas. Each paradigm offers an insight into and understanding of Lu Xun＇s rich and complex spiritual world; each presents a paradox of one kind or the other; and each performs different value functions.

Experience inheritance from famous specialists based on real- world clinical research paradigm of traditional Chinese medicine

The current modes of experience inheritance from famous specialists in traditional Chinese medicine （TCM） include master and disciple, literature review, clinical-epidemiology-based clinical research observation, and analysis and data mining via computer and database technologies. Each mode has its advantages and disadvantages. However, a scientific and instructive experience inheritance mode has not been developed. The advent of the big data era as well as the formation and practice accumulation of the TCM clinical research paradigm in the real world have provided new perspectives, techniques, and methods for inheriting experience from famous TCM specialists. Through continuous exploration and practice, the research group proposes the innovation research mode based on the real-world TCM clinical research paradigm, which involves the inheritance and innovation of the existing modes. This mode is formulated in line with its own development regularity of TCM and is expected to become the main mode of experience inheritance in the clinical field.

Issues,Progress,and Recommendations in the Construction of Ecological Barrier on the Mongolian Plateau from the Perspective of Big Data

The Mongolian Plateau(MP),situated in the transitional zone between the Siberian taiga and the arid grasslands of Central Asia,plays a significant role as an Ecological Barrier(EB)with crucial implications for ecological and resource security in Northeast Asia.EB is a vast concept and a complex issue related to many aspects such as water,land,air,vegetation,animals,and people,et al.It is very difficult to understand the whole of EB without a comprehensive perspective,that traditional diverse studies cannot cover.Big data and artificial intelligence(AI)have enabled a shift in the research paradigm.Faced with these requirements,this study identified issues in the construction of EB on MP from a big data perspective.This includes the issues,progress,and future recommendations for EB construction-related studies using big data and AI.Current issues cover the status of theoretical studies,technical bottlenecks,and insufficient synergistic analyses related to EB construction.Research progress introduces advances in scientific research driven by big data in three key areas of MP:natural resources,the ecological environment,and sustainable development.For the future development of EB construction on MP,it is recommended to utilize big data and intelligent computing technologies,integrate extensive regional data resources,develop precise algorithms and automated tools,and construct a big data collaborative innovation platform.This study aims to call for more attention to big data and AI applications in EB studies,thereby supporting the achievement of sustainable development goals in the MP and enhancing the research paradigm transforming in the fields of resources and the environment.

Intelligent Assessment of Active and ReactivePower Flow with Satisfying Accuracy forN-k_(1)-k_(2) Cascading Outages

Addressed to the N-k_(1)-k_(2) cascading outages,it is computationally burdensome for the reliable calculation of active and reactive power flows.This paper builds a comprehensive framework with three algorithms,including the distribution factor(DF),the Newton-Raphson(NR),and the first iteration of NR algorithm(termed as 1J).Classifiers are designed to determine whether the NR algorithm should be employed for accuracy.Classifier features are extracted upon the analytical error of 1J.As reactive power is partially considered in the 1J but neglected in the DF algorithm,the deviation between the solutions is taken as one crucial feature.The support vector machine(SVM)is then utilized for classifier training.As the deep integration of the causal inference and the statistical paradigm,this framework calculates active and reactive power flows rapidly,reliably,and robustly.The effectiveness and robustness are fully validated in three typical IEEE systems.

Big data and the future of urban ecology:From the concept to results

Urban ecology is experiencing the third paradigm shift.To understand the interactions between the social system and the natural system in the city across time and space,and to provide theories and solutions to sustainable urban development are essential tasks for urban ecology in the next decade.Big data can play a crucial role in future urban ecology studies due to the interdisciplinary nature of urban ecology,the fact that cities are factories of big data,and the new insights gained by using big data in studies.Nevertheless,to translate big data from a concept to research results that can guide planning,policymaking,and management of cities,we need to overcome multiple challenges existing in the theoretical framework,data acquisition,and analytic methods.Urban ecologists should enhance the collaboration with the data scientists to increase the application of big data in studies of urban biodiversity,urban ecosystem services and human wellbeing,and processes of urban ecosystems.

Possible interpretation of disciplinary issues in education

Education must go beyond the borders of the disciplines and educators must make individual learning development a top priority for education if they wish to fulfill their mission in theory and practice,and in order to promote the social development by cultivating and developing the different individual learning.While individual development is a public issue,not a personal affair,it is also a social issue.Thus,educational research bases itself on each type of development,as well as to its existence in the mosaic of social and cultural understanding of the situation.Consequently,theoretical concept and empirical study combine an intrinsic pedagogical paradigm mechanism.Furthermore as a theoretical approach to methodology,awareness of the value of education and method-related activities,pedagogy becomes a special way of seizing the world.

中国民族学的研究范式及创新

In almost a century of its development,Chinese ethnology has gradually formed some significant academic paradigms.One of them is the"ethnic research paradigm"which concentrates on summarizing,organizing,and detailing social and cultural facts using"ethnicity"as its primary unit.This paradigm sees ethnicity as its foundational unit of study.Meanwhile,the"inter-ethnic research paradigm"transcends singular ethnic groups,spotlighting the complex interactions between multiple ethnic groups.It views a multi-ethnic community or region as its core research field,underscoring the nuances of cultural exchange,overlap,and shared experiences.These two paradigms,while distinct,are both invaluable to Chinese ethnology.They don't replace each other but rather work synergistically.Pioneering ethnologist,Fei Xiaotong,masterfully merged these paradigms in his groundbreaking"pluralism and unity"theory,ushering in a refreshed framework for Chinese ethnological studies.This article delves into these foundational paradigms from a historical academic lens,aiming to further refine and enrich the scientific methodologies employed in Chinese ethnology.