The construction of journalism majors contains rich ideological and political resources. As one of the practical courses, the news interview and writing course is a professional basic course for journalism students. Therefore, for professionals who will undertake journalism in the future, they should not only have the ability to produce and disseminate information, but also shoulder the responsibility of telling Chinese stories, spreading Chinese voices, and delivering Chinese excellent culture. For the teaching of news interview and writing courses, students should be guided in thought, so that they have a sense of home and country, good professional ethics and social responsibility.

In this paper, we assess the results of experiment with different machine learning algorithms for the data classification on the basis of accuracy, precision, recall and F1-Score metrics. We collected metrics like Accuracy, F1-Score, Precision, and Recall: From the Neural Network model, it produced the highest Accuracy of 0.129526 also highest F1-Score of 0.118785, showing that it has the correct balance of precision and recall ratio that can pick up important patterns from the dataset. Random Forest was not much behind with an accuracy of 0.128119 and highest precision score of 0.118553 knit a great ability for handling relations in large dataset but with slightly lower recall in comparison with Neural Network. This ranked the Decision Tree model at number three with a 0.111792, Accuracy Score while its Recall score showed it can predict true positives better than Support Vector Machine (SVM), although it predicts more of the positives than it actually is a majority of the times. SVM ranked fourth, with accuracy of 0.095465 and F1-Score of 0.067861, the figure showing difficulty in classification of associated classes. Finally, the K-Neighbors model took the 6th place, with the predetermined accuracy of 0.065531 and the unsatisfactory results with the precision and recall indicating the problems of this algorithm in classification. We found out that Neural Networks and Random Forests are the best algorithms for this classification task, while K-Neighbors is far much inferior than the other classifiers.

Gastronomic tourism is a form of travel that has gained relevance today, making it crucial to understand the promotion and management strategies in specific destinations. This systematic review article aims to analyze these strategies, highlighting the importance of cultural authenticity and collaboration between local actors. The methodology used is aligned with a descriptive and correlational approach, using criteria of exhaustiveness and relevance to review ethnographic research and scientific articles. The results reveal the influence of ancestral knowledge on cultural tourism, as well as the challenges of food heritage and food transculturation. In this sense, the need to design promotional strategies that promote traditionality, identity and cultural empowerment in local communities is highlighted. In conclusion, this study provides a comprehensive understanding of gastronomic tourism promotion and management strategies, underscoring the importance of preserving cultural authenticity and promoting local collaboration for the sustainable development of gastronomic tourism.

In this study, we are interested in WCM (working capital management) strategies and profitability in the UK furniture manufacturing sector. Observing the period from 2007 to 2023 of public companies panel data has found that extreme (aggressive and conservative) and moderate (moderate) WCM approaches are associated with firm performance. The results indicate that a conservative WCM investment policy augments liquidity and profitability and thereby confirms that maintaining liquidity is conducive to operational efficiency. Novel to the literature and considering economic externalities and technological progress, the analysis carries important implications for academics and working capitalists concerning profitability enhancement via better WCM.

Cybercrime poses a growing threat to individuals, businesses, and governments in the digital age. This research aims to conduct a comprehensive study of the legal frameworks developed by international organizations to combat cybercrime, providing a comparative analysis of their approaches and highlighting strengths, weaknesses, and areas for improvement. The study employs a qualitative research methodology, utilizing a doctrinal approach to examine primary and secondary legal sources for data analysis. The results reveal the ongoing efforts of the United Nations and other international bodies to establish a unified approach to combating cybercrime through conventions on Cybercrime. The research emphasizes the importance of harmonizing laws, fostering international cooperation, and adapting to evolving cyber threats while maintaining a balance between security and individual rights. Recommendations include strengthening legal frameworks, enhancing public-private partnerships, and investing in capacity building and technical assistance for developing countries. The study concludes by highlighting the critical importance of comprehensive and harmonized cybercrime legislation in the global fight against cybercrime and calls for continued efforts to address the challenges posed by this ever-evolving threat.

This research delves into the intricate world of lacquer art in East Asia, aiming to unravel the relationships among artisan perspectives, aesthetic values, and the contemporary relevance of this ancient craft. The purpose is to provide a comprehensive understanding of how historical development, apprenticeship traditions, and evolving aesthetic values shape the intricate landscape of lacquer artistry. Employing a qualitative approach, this study conducts in-depth interviews with artisans and experts in the field of lacquer art. The research involves a comparative analysis of past literature, drawing upon historical and contemporary works to contextualize the findings within the broader trajectory of lacquer art. Thematic analysis is also applied to unravel the nuances of artisan perspectives, the transmission of knowledge through apprenticeship traditions, and the cultural and aesthetic dimensions embedded in lacquer paintings. This mixed-methods approach enriches the study by providing a holistic and nuanced exploration of the identified variables. The findings illuminate the enduring significance of apprenticeship traditions in preserving traditional lacquer techniques, with artisans actively navigating challenges posed by globalization and digital platforms. Aesthetic values, including symbolism and visual harmony, are revealed as integral components contributing to the narrative richness of lacquer paintings. The study uncovers the dynamic relationships among these variables, emphasizing the adaptive nature of lacquer art in a contemporary context. The implications extend to cultural preservation, heritage management, and educational initiatives, offering valuable insights for practitioners, policymakers, and educators involved in the realm of traditional crafts. The study contributes to theoretical frameworks on cultural continuity, knowledge transmission, and the socio-cultural dynamics of artistic practices.