This research presents a novel approach utilizing a self-enhanced chimp optimization algorithm (COA) for feature selection in crowdfunding success prediction models, which offers significant improvements over existing methods. By focusing on reducing feature redundancy and improving prediction accuracy, this study introduces an innovative technique that enhances the efficiency of machine learning models used in crowdfunding. The results from this study could have a meaningful impact on how crowdfunding campaigns are designed and evaluated, offering new strategies for creators and investors to increase the likelihood of campaign success in a rapidly evolving digital funding landscape.

Ensuring access to quality education and career training is a crucial challenge, especially in developing nations. Vocational, scientific, technological, and engineering education are essential for active participation in any community and play a significant role in shaping life perspectives. The ability to sustain competitiveness depends on receiving high-quality vocational, scientific, technological, or engineering education and professional growth. These factors are vital for the long-term growth of prosperous economies and nation-building. Hence, this perspective review attempts to provide information on some contemporary pedagogies in science, technology, engineering, and mathematics (STEM) and science, technology, engineering, arts, and mathematics (STEAM) vis-à-vis scientific and engineering education in Nigeria. The study zooms into the challenges and possible solutions that will promote and enhance pedagogies in scientific and engineering education in Nigeria. The study adopted a perspective review approach in overviewing prior accessible studies (literatures) as well as a methodological framework. It is believed that this perspective review study will serve as a way forward for other developing nations.

This research study aims 1) to create a structural equation model for sports sponsorship of halal products in Thailand and 2) to examine the direct and indirect influence of variables that are components of the structural equation model for halal products, specifically in the context of becoming a sports sponsorship for halal products in Thailand. The study focused on a sample group of Thai Muslims interested in watching and following the news and participating in Thai sporting events. The researcher chose a sample size of 400 participants from this population, excluding backup data gathering and data analysis, to ensure the questionnaire’s quality and dependability. The results of the data analysis from the structural equation model created show that it is consistent with empirical data. The results of the statistical hypothesis test reveal that the level of religious adherence and the level of awareness of entering into sponsorship have both direct and indirect influences on consumer attitudes and purchase intentions with statistical significance at 0.01. It can also be identified that if a sponsor increases awareness among Muslim viewers through branding or product presentations in events that feature halal symbols or indicate compliance with religious standards, it will lead to a more positive attitude and higher purchase intentions. This insight can be applied to marketing promotion in administrative regions or countries where the majority of the population is Muslim.

This paper analyzes the impact of wage subsidies on lower-skilled formal workers in the Democratic Republic of Congo (DRC). It employs a multi-sectoral, empirically-calibrated general equilibrium model to capture the economy-wide transactions between the formal and informal sectors and assess policy simulations in the DRC. The simulations, both in the short and long run, indicate that when the government provides wage subsidies to lower-skilled workers, it significantly improves the real disposable incomes of both formal and informal households. There is a general increase across formal and informal sectors in real household disposable incomes due to the wage subsidy. The results show that subsidy allocation narrows the income gap between high and low-income households, as well as between formal and informal sectors. The findings are insightful for wage policy simulations, as the wage subsidy targeting lower-skilled formal workers increases real GDP from the expenditure side by 1.19% and 3.19% in the short and long run, respectively, from the baseline economy.

The authors’ decision to “read” and semiotically analyse the city’s text based on travelogues stems from their aesthetic, historical and informational value, the possibility of incorporating them “into the network” of other texts about Padua, thus shaping city image. The authors’ research on Slovak literature and culture also determined the choice. As a time frame, the nineteenth century is not accidental; the Slovak cultural environment (the territory of present-day Slovakia) witnessed the development of the travelogue genre and journeys to Italy. By interpreting and semiotic analysis of the selected authors’ travelogues and works, the paper draws attention to the uniqueness of Padua, the ways of its representation and the grasping of the urban space, which until now despite its importance in education, sciences and art has remained unnoticed in literary studies. Considering that only four Slovak travellers included Padua in their writings during the studied period, all of their works were reviewed to uncover their texts’ semantic potential. Interpretive immersions thus reflect the experiential reception of the author’s city image and perceiving its architectural structure. Through this, the authors develop a network of texts about Padua and support the typological classification according to its specific function or image. This paper articulates a variant of the Slovak phenomenon of Italian travel and a view of the meanings associated with urban spaces and places. It reflects the importance of travel writing for understanding the (literary) cityscape and its transformations and opens space for further research on the subject.

Foodborne diseases are a global health problem. Every year, millions of people die worldwide from these diseases. It has been determined that the high prevalence of these diseases is related to unfavorable socioeconomic conditions of the population. In this study, the relationship between foodborne diseases and socioeconomic conditions of the population was determined using principal component analysis as a multivariate statistical analysis technique. In this study, the socioeconomic variables of each Ecuador province and the prevalence of foodborne diseases (hepatitis A, salmonella, shigellosis and typhoid fever) during the years 2018 and 2019 were considered. The results show the relationship between foodborne diseases and the socioeconomic conditions of the population, as well as identifying regions more vulnerable to present high levels of prevalence of foodborne diseases, thus facilitating the implementation of social investment programs to reduce the prevalence of these diseases.