Perceptions of women’s roles and leadership in urban governance vary from country to country and culture to culture. While women are represented and participate fully in political decision-making in some countries, in Togo women’s participation in local governance is still limited. The aim of this research is to analyse perceptions of women’s leadership in urban governance in the communes of greater Lomé. Specifically, the study of the influence of general perceptions of the role of women on the development of their leadership in the urban governance of greater Lomé (i) and the implications of these perceptions on the participation of women in the urban governance of greater Lomé (ii). Semi-structured interviews were conducted in all the town halls of the thirteen greater Lomé autonomous district communes with 222 women and 162 men, i.e., a total of 384 people. The corpus created from the interviews, which were transcribed in their entirety, was analyzed using the theory of social dominance developed by Sidanius and Pratto to explain power relations and inequalities between social groups. The results show that perceptions of women’s participation in urban governance vary and are generally associated with several significant implications. The general perception is that women are not as competent or legitimate as men in political and administrative leadership roles. However, there is a growing recognition of the value of gender diversity in urban governance, with a growing awareness of the importance of including women in decision-making processes. From the point of view of the significant implications of perceptions, positive perceptions favor increased representation of women, innovation, and creativity, strengthening legitimacy, reducing inequalities, and presenting women as positive role models in urban governance.

Poverty, and especially the widening disparity between the rich and the poor, leads to social unrest that can interrupt the harmonious development of human society. Understanding the reasons for income inequality, and supporting the development of an effective strategy to reduce this inequality, have been major goals in socioeconomic research around the world. To identify the determinants of the income gap, we calculated the Gini coefficients for Chinese provinces and performed regression analysis and contribution analysis for heterogeneity, using data from 30 Chinese provinces from 2002 to 2018. We found that urbanization, higher education, and foreign direct investment in eastern China and energy in central and western China were important factors that increased the Gini coefficient (i.e., decreased equality). Therefore, paying more attention to the fair distribution of the factors that can increase the Gini coefficient and investing more in the factors that can reduce the Gini coefficient will be the keys to narrowing the income gap. Our approach revealed factors that should be targeted for solutions both in China and in other developing countries that are facing similar difficulties, although the details will vary among countries and contexts.

Background: The hotel industry is labor-intensive. Both technical and behavioral aspects of quality are considered to ensure service quality and customer satisfaction among the internal and external customers as a whole, creating a competitive advantage. Significance: Recruiting and selecting the right people is paramount to the success of the hospitality industry in the sense that the best delivery will be enhanced if proper procedures are used and the right people are selected who can handle their tasks to the best satisfaction of the customer. Method: The goal of the research was to explore the recruiting and selection practices/methods used in the hotel industry, as well as their employability. The study aims to explore the differences in the mix of recruitment and selection methods implemented in 4- and 5-star and different category hotels. As an enterprise, HRD comprises change, learning, and performance. Results: Based on the findings, it is imperative to invest in human resources as a capital asset to boost staff entities in terms of knowledge and capabilities, thereby contributing to better service quality and enhanced customer satisfaction. This would help fulfil the organizations’ objectives. Conclusion: The study concludes that the selected candidates are being analyzed properly and effectively. It is very important to note that the results of this study cannot be generalized as it deals with a restricted clientele, and this could only add on variables and instances to form a common standpoint for the other hotel managers.

Considering the need to adopt more sustainable agricultural systems, it is important that sweet potato breeding programs seek to increase not only root productivity, but also the productivity and quality of branches for silage production. The objective was to evaluate the genetic divergence and the importance of traits associated with the production and quality of branch silage in sweet potato genotypes. The experiment was conducted on the JK Campus of the Federal University of Vales do Jequitinhonha and Mucuri Valleys in a randomized block design with 12 treatments and four repetitions. Twelve characteristics of branches and silage were evaluated. There was genetic variability between the genotypes, making it possible to select parents divergent for future breeding programs for silage production. The genotypes BD-54 and BD-31TO were the most divergent in relation to the others, being indicated its use in crossbreeding aiming the improvement of the culture for silage, once the high performance per se of all genotypes evaluated has already been verified in previous works. The characteristics Na, TDN and NDF were those that most contributed to the divergence.

The cost of diagnostic errors has been high in the developed world economics according to a number of recent studies and continues to rise. Up till now, a common process of performing image diagnostics for a growing number of conditions has been examination by a single human specialist (i.e., single-channel recognition and classification decision system). Such a system has natural limitations of unmitigated error that can be detected only much later in the treatment cycle, as well as resource intensity and poor ability to scale to the rising demand. At the same time Machine Intelligence (ML, AI) systems, specifically those including deep neural network and large visual domain models have made significant progress in the field of general image recognition, in many instances achieving the level of an average human and in a growing number of cases, a human specialist in the effectiveness of image recognition tasks. The objectives of the AI in Medicine (AIM) program were set to leverage the opportunities and advantages of the rapidly evolving Artificial Intelligence technology to achieve real and measurable gains in public healthcare, in quality, access, public confidence and cost efficiency. The proposal for a collaborative AI-human image diagnostics system falls directly into the scope of this program.