The application of governance in recent years appears as a tool of entities that organize sport. Considering this aspect, it was observed that many sports entities present problems in following mechanisms to improve management, both in national and international contexts. Governance materializes with principles of transparency, accountability, equity, institutional integrity, and modernity, in order to aid sports entities. Thus, the development of sports entities could improve management, professionalization, and innovation. Based on the aforementioned, this article aims to demonstrate whether the principles of governance found in the literature are contemplated in Brazilian sports confederations, pointing to the possibility of finding distinct characteristics among the confederations, and the confederation with the highest index for Brazilian sports. The methodology is a longitudinal discursive analysis. The results use data from 2015 to 2022 from the Sou do Esporte Governance Awards and the analysis is based on five governance principles; transparency, equity, accountability, institutional integrity, and modernity. The confederations were found to have adopted the principles of governance to improve, professionalize, and optimize their sports management. The results suggest that the use of governance can enhance the confederations and improve the management, legitimacy, and development of sports in Brazil. The authors consider the nuances reported in the study as imperative to improve the progress of Brazilian sports, and the contribution made could generate other discussions in different contexts and countries.

The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has gained significant interest in modern agriculture. The appeal of AI arises from its ability to rapidly and precisely analyze extensive and complex information, allowing farmers and agricultural experts to quickly identify plant diseases. The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has gained significant attention in the world of agriculture and agronomy. By harnessing the power of AI to identify and diagnose plant diseases, it is expected that farmers and agricultural experts will have improved capabilities to tackle the challenges posed by these diseases. This will lead to increased effectiveness and efficiency, ultimately resulting in higher agricultural productivity and reduced losses caused by plant diseases. The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has resulted in significant benefits in the field of agriculture. By using AI technology, farmers and agricultural professionals can quickly and accurately identify illnesses affecting their crops. This allows for the prompt adoption of appropriate preventative and corrective actions, therefore reducing losses caused by plant diseases.

With the vigorous development of international trade and the in-depth advancement of economic globalization, China is facing the increasingly serious problem of invasive alien species, which poses a major threat to China’s ecological environment, economic development and human health. At present, although China has a comprehensive institutional norms in the prevention and control of invasion of alien species, but in the face of the challenge of invasion of alien species, China is still facing problems such as insufficient legal basis and imperfect specific legal system. Based on this understanding, this paper discusses the prevention and control of invasive alien species legal regulation, that although in recent years China has made certain achievements in the field of prevention and control of invasive alien species, but still faces a number of problems to be solved, should promote the relevant legislative amendments, and combined with the experience of developed countries to summarize the perfect.

This paper investigates the factors influencing credit growth in Kosovo, focusing on the relationship between credit activity and key economic variables, including GDP, FDI, CPI, and interest rates. Its analysis targets loans issued to businesses and households in Kosovo, employing a VAR model integrated into a VEC model to investigate the determinants of credit growth. The findings were validated using OLS regression. Additionally, the study includes a normality test, a model stability test (Inverse Roots AR Characteristic Polynomial), a Granger causality test for short-term relationships, and variance decomposition to analyze variable shocks over time. This research demonstrates that loan growth is primarily driven by its historical values. The VEC model shows that, in the long run, economic growth in Kosovo leads to less credit growth, showing a negative link between it and GDP. Higher interest rates also reduce credit growth, showing another negative link. On the other hand, more foreign direct investment (FDI) increases credit demand, showing a positive link between credit growth and FDI. The results show that loans and inflation (CPI) are positively linked, meaning higher inflation leads to more credit growth. Similarly, more foreign direct investment (FDI) increases credit demand, showing a positive link between FDI and credit growth. In the long term, higher inflation is connected to greater credit growth. In the short term, the VAR model suggests that GDP has a small to moderate effect on loans, while FDI has a slightly negative effect. In the VAR model, interest rates have a mixed effect: one coefficient is positive and the other negative, showing a delayed negative impact on loan growth. CPI has a small and negative effect, indicating little short-term influence on credit growth. The OLS regression supports the VAR results, finding no effect of GDP on loans, a small negative effect from FDI, a strong negative effect from interest rates, and no effect from CPI. This study provides a detailed analysis and adds to the research by showing how macroeconomic factors affect credit growth in Kosovo. The findings offer useful insights for policymakers and researchers about the relationship between these factors and credit activity.