Constructed wetlands have emerged as a sustainable alternative for decentralized wastewater treatment in developing countries which face challenges with urbanization and deteriorating infrastructure. This paper discusses the key factors affecting the implementation of constructed wetlands in developing countries. A case study research design was adopted, which focused on Bulawayo, Zimbabwe. A mixed-method approach was adopted for the study. Spatial analysis was conducted to identify potential sites for constructed wetlands in the city of Bulawayo. Semi structured interviews were conducted, with relevant stakeholders, such as town planners, civil engineers, NGO representatives, community leaders, and quantity surveyors. The findings reveal that political reforms, public acceptance, land availability, and funding are crucial for the successful implementation of constructed wetlands. Additionally, four sites were identified as the most favorable preliminary locations for these systems. The paper captures all the key factors relevant to the implementation of constructed wetlands (CWs) with a closer look at policy and the role it plays in the adoption of decentralized wastewater treatment systems. Formulating policy around the decentralized sanitation systems was considered imperative to the success of the systems whether in implementation or in operation. The paper adds to knowledge in the subject of sustainable wastewater treatment alternatives for developing countries. However, further research can be conducted with a different methodology to ascertain the applicability of the systems in developing urban cities considering other important aspects in the implementation of wastewater treatment systems.

Artificial intelligence has transformed teachers’ teaching models. This article explores the application of artificial intelligence in basic education in Macao middle schools. This study adopts case analysis in qualitative research, using a total of eight cases from the innovative technology education platform of the Macau education and Youth Development Bureau. These data illustrate how Macao’s artificial intelligence technology promotes teaching innovation in basic education. These eight cases are closely related to the application of artificial intelligence in basic education in Macao. The survey results show that Macao’s education policy has a positive effect on teaching innovation in artificial intelligence education. In teaching practice, the school also cooperates with the government’s policy. The application of AI technology in teaching, students’ learning styles, changes in teachers’ roles, and new needs for teacher training are all influential.

The idea of emotions that is concealed in human language gives rise to metaphor. It is challenging to compute and develop a framework for emotions in people because of its detachment and diversity. Nonetheless, machine translation heavily relies on the modeling and computation of emotions. When emotion metaphors are calculated into machine translation, the language is significantly more colorful and satisfies translating criteria such as truthfulness, creativity and beauty. Emotional metaphor computation often uses artificial intelligence (AI) and the detection of patterns and it needs massive, superior samples in the emotion metaphor collection. To facilitate data-driven emotion metaphor processing through machine translation, the study constructs a bi-lingual database in both Chinese and English that contains extensive emotion metaphors. The fundamental steps involved in generating the emotion metaphor collection are demonstrated, comprising the basis of theory, design concepts, acquiring data, annotating information and index management. This study examines how well the emotion metaphor corpus functions in machine translation by proposing and testing a novel earthworm swarm-tunsed recurrent network (ES-RN) architecture in a Python tool. Additionally, the comparison study is carried out using machine translation datasets that already exist. The findings of this study demonstrated that emotion metaphors might be expressed in machine translation using the emotion metaphor database developed in this research.

Molan, an intangible cultural heritage of the Zhuang nationality in China, faces a crisis due to traditional communication and inheritance models. In the digital era, leveraging advanced digital technology is crucial for revitalizing this ancient heritage. From a communication theory perspective, this paper uses field investigation and applies the classic 5W communication model by Lasswell to deeply analyze the crisis facing Molan culture. Integrating the media evolution theory of Levinson, it explores the benefits and methodologies of digital dissemination for ancient intangible cultural heritage and proposes a digital communication model. The paper emphasizes adopting the PGC (Professional Generated Content) + UGC (User Generated Content) production model and strictly adhering to the “Content is King” principle. It advocates for models such as “Social Media + Molan,” “Short Video + Molan,” and “Algorithm + Molan” to enhance communication effectiveness. These viewpoints aim to revitalize and preserve Molan culture in the digital age.

In this paper, a study developed at the University of Seniors in Aragón is presented. The Sono-libro, used as an innovative resource, is assessed in the proposal with an educational and pedagogical purpose. The aim is to understand the motivational and learning perception variation after the incorporation of the Sono-libro in the sample. In this quantitative longitudinal design study, the listening habits of the participants are comparatively analyzed at two moments: The first data collection took place before the implementation of the proposal, and the second collection occurred after the proposal. The sample consists of 116 subjects, with 64.16% being women and an average age of 66 years of age. Data was obtained through a validated ad hoc questionnaire judged by experts. The results of the data collections showed an increase in both motivation and perception of the learning obtained, indicating the benefits of incorporating digital resources into contexts of adult students.

From the perspective of the corporate life cycle, this study investigates the transmission mechanism of ‘technological innovation-financing constraints-carbon emission reduction’ in energy companies using panel data and mediating models, focusing on listed energy companies from 2014 to 2020. It explores the stage characteristics of this mechanism during different life cycle phases and conducts heterogeneity tests across industries and regions. The results reveal that technological innovation positively influences carbon emission reduction in energy enterprises, demonstrating significant life cycle stage characteristics, specifically more pronounced in mature companies than in growing or declining companies. Financing constraints play a mediating role between technological innovation and carbon reduction, but this is only effective during the growth and maturity stages. Further research shows that the impact of technological innovation on carbon emission reduction and the mediating role of financing constraints exhibit heterogeneity across different stages of the life cycle, industries, and regions. The conclusions of this paper provide references for energy companies in planning rational emission reduction strategies and for government departments in policy-making.