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This paper aims to study the FinTech enterprises and the management theories related to this subject in a scientific way.

This study is a bibliometric study on FinTech enterprises. Its origin is a survey of 1,749 papers in 6 traditional peer-reviewed academic databases (e.g. Science Direct and Scopus) and in the “gray” literature, published by other agents and not subject to double-blind peer review. In this analysis we use three approaches: academic paper or not; journal main interest, and main purpose of the paper.

The first approach shows 45% of papers without blind review. The second approach shows no concentration on any journal. It represents no concentration on any kind of specific journal. And the third approach shows four kinds of contents in all researched papers: FinTech categorizations; FinTech related to theory of disruptive innovation; FinTech and theories of administration or economy; and finally, FinTech and regulatory and legislative aspects.

The findings identified the emergence of new research strands, precedence of studies of “gray” literature to explain the phenomenon, distribution of studies in different fields of knowledge (e.g. information technology, business and law) and lack of consensus in theories to explain the matter.

This study aims to analyze the impact of Artificial Intelligence (AI) and Machine Learning (ML) on heritage conservation and preservation, and to identify relevant future research trends, by applying scientometrics.

A total of 1,646 articles, published between 1985 and 2021, concerning research on the application of ML and AI in cultural heritage were collected from the Scopus database and analyzed using bibliometric methodologies.

The findings of this study have shown that although there is a very important increase in academic literature in relation to AI and ML, publications that specifically deal with these issues in relation to cultural heritage and its conservation and preservation are significantly limited.

This study enriches the academic outline by highlighting the limited literature in this context and therefore the need to advance the study of AI and ML as key elements that support heritage researchers and practitioners in conservation and preservation work.

With the development of social productive forces and the advancement of agricultural practices since the founding of New China, the connotation of agricultural modernization with Chinese characteristics has undergone a process from formation to continuous expansion and deepening.

Its evolution can be roughly divided into four stages: the exploration stage, the formation stage, the establishment stage and the deepening stage. The historical evolution of the connotation of agricultural modernization with Chinese characteristics demonstrates four typical characteristics, namely increasingly scientific logical premise, continuously diversified orientations, increasingly improved core contents and progressively maturing strategies of development.

The achievements of agricultural modernization have laid a solid foundation for China's industrial modernization and the rapid development of the national economy. Meanwhile, the authors have identified through practical exploration a path of agricultural modernization with Chinese characteristics. In recent years, academic research on the connotation of agricultural modernization with Chinese characteristics has gradually heated up, and relevant achievements have emerged constantly.

The Communist Party of China (hereinafter “CPC”) has placed considerable emphasis on agricultural issues and has been committed to promoting agricultural modernization since the founding of New China. Through long-term persistence and unremitting efforts, China has made remarkable achievements in agricultural development: significantly improved agricultural production conditions and agricultural output capacity, constantly optimized agricultural structure and steadily increased the income of farmers.