The Science and Technology Innovation Center holds a pivotal position in the national science and technology innovation system, and a scientific evaluation of the “Sci-tech Innovation Center” will guide its construction direction. This study found the advantages and disadvantages of the four cities through comparison; Hence improvement suggestions were proposed for the weaknesses of the four cities. There are two main paths for the government to drive technology innovation: STI (Science and Technology Innovation) mode and DUI (Doing, Using, Interacting) mode. With the aid of the evaluation index system of the Sci-tech Innovation Center, this article uses fuzzy sets, rough sets and fuzzy dynamic clustering methods to comprehensively evaluate the effects of driving technology innovation in the four cities of Beijing, Shanghai, Shenzhen and Guangzhou. The results found that Shenzhen has a significant effect in DUI, and Beijing has a significant effect in STI. The choice of path is related to the abundance of innovation resources.

Despite its leading role in the urban transport system, paratransit is accused of being unsustainable and hostile to modernity. The reform of the sector is necessary in the context of the modernization of the transport system of African cities. It requires the formalization of actors through technical and financial support such as fleet renewal projects. This article attempts to analyze the financing process and the level of formalism of the operators constituted within the AFTU in the context of the financing operation of paratransit operators in Dakar, Senegal. The methodological approach adopted is based on the analysis of qualitative data from questionnaire surveys carried out in the AFTU network in Dakar; official documents¹ were also used. The results show that the Dakar financing model put in place has made it possible to make significant progress in the reorganization of paratransit professionals. In addition to the concessioned lines, a salaried system was introduced, pricing is now official and the standardized ticketing system has been put in place. Nevertheless, improvements are expected on the working conditions of employees, the capacity building of actors and the evolution of the legal status of companies.

In order to overcome negative demographic trends in the Russian Federation, measures to stimulate the birth rate have been developed and financed at the federal and sub-federal levels. At the moment, on the one hand, there is a tendency to centralize expenditures for these purposes at the federal level, on the other hand, the coverage of the subjects of the Russian Federation, which introduce sub-federal (subnational) maternity capital (SMC), is expanding. The study was recognized to answer the question: whether the widespread introduction of SMC is justified, whether the effect of its use depends on the level of subsidization of the region and the degree of decentralization of expenditures.

Soundscape tourism has become one type of tourism, and its trend is emerging in most areas with hilly, forested, and natural landscapes, such as Bantul Indonesia, becoming a mainstay for region development and its community. This article explores four human manufactured soundscape tourism destinations in Bantul, Indonesia, examining the interrelationships between each tourism stakeholder and pinpointed development from a socio-economic perspective. We adopt a cross-case study approach, drawing main sources from government statistics, regulations, social media narratives, and online news. Using the NVivo 12 Plus software, we coded and annotated the research source. Our research revealed that in four case studies, tourism soundscapes emerged as the primary tourist attractions, with other attractions only marginally contributed. Presenting music or acoustic stages enabled tourism industry to reap benefits, particularly for local community and regional income. However, it is important to emphasize sustainability issues, thus, the continuous increased in music soundscape in nature has led to the formation of collaborations among tourism actors, with local communities “Pokdarwis” posed as the principal driving force behind destination development. This study demonstrates that human-manufactured soundscapes have the potential to increase visitor numbers and outperform natural soundscapes in natural destinations.

Since the systematic approach of the processes and their interactions, the aim is to establish the configuration of a construction project for the housing of the Weenhayek indigenous people. Applied from the theoretical research of various authors on a group of methodologies, phases and tools for project management, through rational scientific methods, such as descriptive, analytical, comparative, analytical-synthetic, inductive-deductive, historical-logical, analogies, modeling, systemic-structural-functional, systematization; and empirical methods, such as interpretivism that involves inductive, qualitative, phenomenological and transversal research, and the interview technique; the way in which the implementation processes are organized, interacted and structured is established. This reveals an alternative for the detailed configuration of a construction project for Weenhayek houses, based on phases, activities, actions and work tasks with characteristics in accordance with the needs of the project.

Credit policies for clean and renewable energy businesses play a crucial role in supporting carbon neutrality efforts to combat climate change. Clustering the credit capacity of these companies to prioritize lending is essential given the limited capital available. Support Vector Machine (SVM) and Artificial Neural Network (ANN) are two robust machine learning algorithms for addressing complex clustering problems. Additionally, hyperparameter selection within these models is effectively enhanced through the support of a robust heuristic optimization algorithm, Particle Swarm Optimization (PSO). To leverage the strength of these advanced machine learning techniques, this paper aims to develop SVM and ANN models, optimized with the PSO, for the clustering problem of green credit capacity in the renewable energy industry. The results show low Mean Square Error (MSE) values for both models, indicating high clustering accuracy. The credit capabilities of wind energy, clean fuel, and biomass pellet companies are illustrated in quadrant charts, providing stakeholders with a clear view to adjust their credit strategies. This helps ensure the efficient operation of banking green credit policies.