This is a review of empirical studies with the objective of analyzing the theoretical-practical discussions that have been raised internationally to deepen the understanding of the access of rural youth to higher education as an object of study. For this purpose, a narrative review was designed, considering scientific articles published in three different languages and concerning studies conducted in 21 different countries in all regions of the world. The results reveal three discussions: a) the strong interest that higher education has regained in the life expectations of rural young people and their families, especially as a means of social advancement; b) the inequalities that most affect the access of rural youth to higher education are the lack of academic offerings in rural areas and the discontinuities that occur around rural socio-cultural capital; c) since the inequalities experienced by rural youth are diverse, actions to promote greater democratization cannot be limited to implementing systems of grants and scholarships. It is concluded that the major project consists of creating a differentiated higher education model that, in terms of location, academic offerings, recognition of knowledge, and articulation with the environment, allows rural youth to experience their professional training not as an inevitable process of acculturation, but as a continuation of their socio-cultural capital and their territorial yearnings.
This study replicates and extends Corbett and Kirsch (2001) and Vastag (2004) using a new data set to investigate the drivers of ISO 14000 certification diffusions using decision tree analysis. The findings indicate that at the national level, ISO 14000 certification diffusions are influenced by factors other than ISO 9000 certification diffusions, such as the number of environmental treaties signed and ratified, industrial activities as a percentage of GDP, and GDP per capita, thus provides a range of managerial insights and enhances scholarly understanding of sustainability beyond the influence of ISO 9000. Future studies might extend the countries included in this study to see if the results are the same. Future research may include other factors like a country’s Environmental, Social, and Governance (ESG) indicators to better understand its commitment to sustainability, including environmental sustainability. The country’s culture may influence customers, investors, and other stakeholders’ knowledge and desire for sustainable practices and inspire firms to obtain ISO 14000 certifications. Since larger firms may seek ISO 14000 certification, future studies may evaluate the influence of the number of large firms in various countries as drivers of ISO certification diffusions.
The main objective of the study was to assess the impact of fiscal management on macroeconomic stability in emerging countries between 2012 and 2022. The study drew on macroeconomic theory, which postulates the importance of responsible fiscal policies for economic stability. Information was taken from ten emerging Latin American countries, and the analysis was carried out through a quantitative approach, using an econometric model. A significant relationship was found between fiscal management and macroeconomic stability, evidencing that effective fiscal policies are crucial for macroeconomic stability in emerging countries. The findings emphasize that balanced fiscal management, which avoids falling into cycles of debt and deficit, is essential for long-term stability. Practices that promote fiscal stability, such as greater efficiency in public spending and effective tax collection, can contribute significantly to economic stability and sustained growth. The results also suggest that fiscal policies should take into account human development conditions and annual particularities in order to formulate effective fiscal policies. It highlights those countries with best fiscal practices, reflected in low debt-to-GDP levels and high fiscal stability, are more likely to achieve macroeconomic stability and sustainable economic growth.
The paper reports on the results of research on the institution of public-private partnerships in the field of implementation of state youth policy, particularly through socially important social youth projects, including social-entrepreneurial. The study explores social projects that enjoy the full range of support from all subjects in public-private partnerships: the state represented by public authorities, business structures, non-profit organizations, and youth. The authors highlight that the infrastructure of youth policy in the implementation of social-entrepreneurial youth projects needs to be changed conceptually. There is a need to establish comprehensive creative and professional spaces that shape young people’s personalities and practice a future-oriented model of organizing collaborative social projects.
This research aims to determine the strategy of the Jakarta Provincial Government in increasing the resilience and growth of small and medium enterprises (SMEs) within a collaborative governance framework post-COVID-19. This study explores the effectiveness of SMEs and facilities in accessing financing and fostering collaborative partnerships between SMEs, government agencies, and financial institutions by utilizing USAID’s Theory of Change (TOC). This research uses a qualitative approach supported by in-depth interviews and Focus Group Discussions to enrich the insights of SME stakeholders, large companies, and SME actors and assess the impact of their roles. The results of this research highlight the critical role of SME Cooperative Banks (SCB) in improving SMEs’ access to credit and financial services, including collaborative governance frameworks and partnerships between SMEs, government agencies, and banks, which were identified as necessary to improve policy coherence and encourage conducive SME business environment conditions. The main findings of this research underscore the importance of the SCB model, demonstrating its potential to improve SME resilience and economic sustainability. This SCB model enriches the TOC indicators introduced by USAID. The study identifies gaps in digital infrastructure and market access that hinder SME growth and recommends targeted interventions to address these challenges. This study shows that SCB offers a promising pathway to increase the resilience and growth of SMEs in Indonesia, especially if accompanied by effective collaborative governance strategies. These initiatives can encourage inclusive economic development and strengthen the role of SMEs as drivers of the local economy. Recommendations include expanding the SCB model to other regions, encouraging digitalization, facilitating market access, advocating for a supportive policy framework, and integrating these strategies to advance the principles of USAID’s Theory of Change, fostering sustainable SME development and economic resilience.
Retinal disorders, such as diabetic retinopathy, glaucoma, macular edema, and vein occlusions, are significant contributors to global vision impairment. These conditions frequently remain symptomless until patients suffer severe vision deterioration, underscoring the critical importance of early diagnosis. Fundus images serve as a valuable resource for identifying the initial indicators of these ailments, particularly by examining various characteristics of retinal blood vessels, such as their length, width, tortuosity, and branching patterns. Traditionally, healthcare practitioners often rely on manual retinal vessel segmentation, a process that is both time-consuming and intricate, demanding specialized expertise. However, this approach poses a notable challenge since its precision and consistency heavily rely on the availability of highly skilled professionals. To surmount these challenges, there is an urgent demand for an automatic and efficient method for retinal vessel segmentation and classification employing computer vision techniques, which form the foundation of biomedical imaging. Numerous researchers have put forth techniques for blood vessel segmentation, broadly categorized into machine learning, filtering-based, and model-based methods. Machine learning methods categorize pixels as either vessels or non-vessels, employing classifiers trained on hand-annotated images. Subsequently, these techniques extract features using 7D feature vectors and apply neural network classification. Additional post-processing steps are used to bridge gaps and eliminate isolated pixels. On the other hand, filtering-based approaches employ morphological operators within morphological image processing, capitalizing on predefined shapes to filter out objects from the background. However, this technique often treats larger blood vessels as cohesive structures. Model-based methods leverage vessel models to identify retinal blood vessels, but they are sensitive to parameter selection, necessitating careful choices to simultaneously detect thin and large vessels effectively. Our proposed research endeavors to conduct a thorough and empirical evaluation of the effectiveness of automated segmentation and classification techniques for identifying eye-related diseases, particularly diabetic retinopathy and glaucoma. This evaluation will involve various retinal image datasets, including DRIVE, REVIEW, STARE, HRF, and DRION. The methodologies under consideration encompass machine learning, filtering-based, and model-based approaches, with performance assessment based on a range of metrics, including true positive rate (TPR), true negative rate (TNR), positive predictive value (PPV), negative predictive value (NPV), false discovery rate (FDR), Matthews's correlation coefficient (MCC), and accuracy (ACC). The primary objective of this research is to scrutinize, assess, and compare the design and performance of different segmentation and classification techniques, encompassing both supervised and unsupervised learning methods. To attain this objective, we will refine existing techniques and develop new ones, ensuring a more streamlined and computationally efficient approach.
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