This paper investigates the innovation policy used by the Chinese government and tries to give recommendations to other developing countries to achieve leapfrogging. The main results are as follows: (1) summarize the main HSR-related policy theme issued by the Chinese government, mainly technology transfer, the communication and collaboration with different actors, and the state’s role, (2) discuss the existing challenges and issues for HSR policies, (3) give recommended measures for other developing countries.

Ancient Minipe Anicut, Sri Lanka is world-famous for its engineering excellence. Due to its importance, conserving the ancient anicut, another anicut was constructed downstream in the 20th century. Nevertheless, the water diverted from the ancient anicut to the Minipe Left Bank (LB) Canal was kept as it was due to inherited agricultural importance. This research focuses on studying the contributions made by the adjacent catchment along the Minipe LB Canal. There are several level crossings along the Minipe Left Bank Canal from which the runoff of the local catchment flow into the Minipe LB Canal. Hydrologic Modeling System (HEC-HMS) is used to obtain the yield from each catchment into the Canal, which was compared with the annual diversions from Minipe anicut. The total yield from each stream has been compared with the annual diversion of the Minipe LB Canal from 2014 to 2020. The results obtained from this study reveal that there is sufficient water available for water augmentation in the basin, with an estimated annual average cumulative yield from the catchment of 453.6 MCM. This cumulative yield is 1.7 times the annual average diversion from the Mahaweli River, which is 271.9 MCM. With the findings, it is concluded that there is a potential to augment water from the catchment to address pertaining water shortages conveyance in the command area.

Africa has an extensive and varied cultural history that includes works of art, music, literature, customs, and historical locations. These cultural resources are essential for creating identities, promoting social cohesiveness, and advancing economic development. However, for these institutions to have the greatest impact on the world and contribute to sustainable development, they must be managed and engaged effectively. Exploring the management of cultural institutions in Africa and their potential for global impact and sustainable development is the goal of this research study. The study relies on the extensive review of available literature, case studies, and in-depth interviews with key informants, and data obtained, subjected to content and thematic analyses. It aims to uncover flexible management techniques that can improve the global reach and sustainable development of African cultural institutions by examining successful models and cutting-edge approaches. The results of this study will help those responsible for administering Africa’s cultural institutions to formulate practical guidelines and policy recommendations. Africa can further establish its cultural identity, advance cultural diplomacy, and utilize its cultural capital to propel social and economic advancement by utilizing the potential of these institutions for global impact and sustainable development.

The improper disposal of litter by tourists poses a significant threat to tourism destinations worldwide, including in Indonesia. To mitigate marine litter, promoting eco-friendly behavior (EFB) among tourists is essential. This study applies the extended Theory of Planned Behavior (TPB), which posits that an individual’s behavior is driven by their attitudes, subjective norms, and perceived behavioral control, to better understand the factors influencing eco-friendly behavioral intentions. In this research, ecological consciousness and ecological knowledge were added to the traditional TPB framework to gain deeper insights into tourist behavior. Data were collected through a structured questionnaire from 876 visitors to Lake Singkarak, Indonesia. The findings demonstrate that the inclusion of ecological consciousness and ecological knowledge significantly enhances the predictive power of the TPB model in explaining eco-friendly behavioral intentions. Based on these results, raising public awareness, improving government management, and enhancing the quality of lake attractions are recommended to encourage responsible tourism. These measures can reduce litter and conserve lake habitats, ultimately contributing to the sustainability of tourism in the region.

Prefabricated decoration is an efficient construction mode in the current construction field, with the main purpose of quickly improving the efficiency and quality of decoration through the effective application of modular decoration technology. Therefore, there is a high demand for efficient prefabricated technical talents in various construction units or enterprises in the construction industry. How to cultivate efficient prefabricated technical talents is a problem that relevant professional teachers in universities must pay attention to at present. This paper mainly analyzes the research and practice of the training mode of prefabricated technical talents, summarizes the connotation of prefabricated building and the importance of prefabricated building talent training, analyzes the key points and requirements of prefabricated building teaching, summarizes the problems existing in the training process of prefabricated building talents and puts forward corresponding optimization countermeasures, so as to lay a solid foundation for the optimization of the training mode of prefabricated talents in the next stage and the promotion of talent training level.

In this study, the authors propose a method that combines CNN and LSTM networks to recognize facial expressions. To handle illumination changes and preserve edge information in the image, the method uses two different preprocessing techniques. The preprocessed image is then fed into two independent CNN layers for feature extraction. The extracted features are then fused with an LSTM layer to capture the temporal dynamics of facial expressions. To evaluate the method's performance, the authors use the FER2013 dataset, which contains over 35,000 facial images with seven different expressions. To ensure a balanced distribution of the expressions in the training and testing sets, a mixing matrix is generated. The models in FER on the FER2013 dataset with an accuracy of 73.72%. The use of Focal loss, a variant of cross-entropy loss, improves the model's performance, especially in handling class imbalance. Overall, the proposed method demonstrates strong generalization ability and robustness to variations in illumination and facial expressions. It has the potential to be applied in various real-world applications such as emotion recognition in virtual assistants, driver monitoring systems, and mental health diagnosis.