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The impact of entrepreneurship support programs on the survival of young agricultural enterprises: A Cox model approach
Full text linkThis study examines the factors influencing the survival of new agricultural enterprises created by young entrepreneurs, using a sample of 184 businesses over a three-year period after their creation. The analysis begins with a description of the sample’s characteristics and then employs two quantitative approaches: the non-parametric Kaplan-Meier method and the semi-parametric Cox model. Empirical results reveal several key elements that significantly impact business survival. Entrepreneurial training is crucial as it enhances the skills needed to address challenges. Prior experience in the agricultural sector also strengthens entrepreneurs\u27 resilience. Sufficient startup capital is essential for supporting initial operations and handling unforeseen issues. Innovation plays a vital role by enabling businesses to differentiate themselves and adapt to market changes. Finally, activity diversification helps mitigate risks and stabilize income. The study highlights the need for more diverse and adaptive post-creation support to effectively assist these businesses in their long-term development. Better-targeted and tailored support for young entrepreneurs could significantly improve survival rates and foster the sustainable growth of new agricultural enterprise
Superior Classification of Brain Cancer Types Through Machine Learning Techniques Applied to Magnetic Resonance Imaging
Full text linkBrain cancer remains one of the most challenging medical conditions due to its intricate nature and the critical functions of the brain. Effective diagnostic and treatment strategies are essential, particularly given the high stakes involved in early detection. Magnetic Resonance (MR) imaging has emerged as a crucial modality for the identification and monitoring of brain tumors, offering detailed insights into tumor morphology and behavior. Recent advancements in artificial intelligence (AI) and machine learning (ML) have revolutionized the analysis of medical imaging, significantly enhancing diagnostic precision and efficiency. This study classifies three primary brain tumor types—glioma, meningioma, and general brain tumors—utilizing a comprehensive dataset comprising 15,000 MR images obtained from Kaggle. We evaluated the performance of six distinct machine learning models: K-Nearest Neighbors (KNN), Neural Networks, Logistic Regression, Support Vector Machine (SVM), Decision Trees, and Random Forests. Each model\u27s effectiveness was assessed through multiple metrics, including classification accuracy (CA), Area Under the Curve (AUC), F1 score, precision, and recall. Our findings reveal that KNN and Neural Networks achieved remarkable classification accuracies of 98.5% and 98.4%, respectively, significantly surpassing the performance of other evaluated models. These results underscore the promise of ML algorithms, particularly KNN and Neural Networks, in improving the diagnostic process for brain cancer through MR imaging. Future research will focus on validating these models with real-world clinical data, aiming to refine and enhance diagnostic methodologies, thus contributing to the development of more accurate, efficient, and accessible tools for brain cancer diagnosis and management
Scientific production in education in latin america: bibliometric analysis of latin american education journals, period 2017-2022
Full text linkThis study analyzes scientific production in Latin American education journals indexed in SCOPUS during the period 2017-2022, with the aim of characterizing it by identifying patterns of collaboration, citation and productivity, to understand its dynamics and regional impact. Using a descriptive approach with bibliometric indicators, 22 educational journals were selected from the Scimago Journal Rank (SJR) and SCOPUS databases, to place a total of 6,488 documents, including research articles and bibliographic reviews, which recorded 15,651 signatures of 11,911. authors.The results highlight the leadership of Brazil, which concentrates 54.5% of the documents and 11 of the 22 journals analyzed. In addition, an increase of 16.5% in the annual production of publications and a growing trend in collaboration between authors was identified, with an average collaboration index of 2.41. However, the average citation impact is moderate, reaching 2.2 citations per document.In conclusion, the study shows a dynamic and constantly evolving panorama, characterized by Brazil\u27s leadership, growing internationalization and the strengthening of academic networks in the region. However, it is necessary to diversify analysis sources and optimize visibility strategies to increase the global impact of educational research in Latin America
Practices, Risks, and Regulations of Self-Medication in Ecuador, Analysis of Prevalence, Determinant Factors, and Patterns
Full text linkSelf-medication was identified as a significant global public health issue, particularly in regions with fragmented healthcare systems and economic disparities. This practice posed risks such as antimicrobial resistance, adverse drug reactions, and delayed diagnoses of serious conditions. This study aimed to analyze the prevalence, patterns, and drivers of self-medication in Latin America and compare these findings with other global contexts. A mixed-methods approach was employed, integrating quantitative data from secondary sources and qualitative analysis of cultural and regulatory influences. Data from Ecuador, Peru, Colombia, Brazil, and Spain were analyzed, revealing a prevalence range from 35% in Brazil to 82.9% in Ecuador. Antibiotics and analgesics were the most commonly used drugs, with their misuse contributing to increased public health risks, particularly antimicrobial resistance. Economic barriers, cultural norms, and healthcare access disparities were identified as key drivers. In Spain, stricter pharmaceutical regulations corresponded to a lower prevalence (40%), highlighting the role of policy enforcement. The findings underscored the need for effective interventions, including stricter regulations, public education campaigns, and improved healthcare access, to mitigate risks and improve health outcomes
Hydraulic modeling of Sebou tributaries for flood prevention in the el Gharb plain - Morocco
Full text linkFlooding is one of the most unpredictable natural hazards. In Morocco, the El Gharb plain is the most affected. The Rharb basin receives between 500 and 600mm of precipitation and includes 30% of Morocco\u27s water resources. All the factors that make the Rharb plain a vulnerable area are: climatic factors, lithology, geomorphology, the limited number of natural outlets for water drainage towards the Atlantic Ocean. The methodology adopted is based on the determination of flood zones and the hydraulic modeling of the main tributaries of the Oued Sebou and the main sanitation channels, in order to monitor the evolution of flood zones and evaluate the flow of the Oued Sebou to understand the functioning of the hydrographic network and the overflow points. According to the hydrographs established by the Gharb plain flood protection department, the maximum flow at the entrance to the city of Kenitra was estimated at 2,600 m3/s and the flow of the Oued at this level is of the order of 1,600 m3/s, which explains the overflows recorded at the level of the left bank of the Oued Sebou, the dead arm of the Oued. The results of these studies as well as the analysis of the history of the floods of the Oued Sebou, show that one to two major floods occur every 10 years and that the overflows reach upstream of the highway to the dead arm of the Oued and cover Merja-Fouarate such as the case of the flooding of the city of Kenitra in 2010
Systematic Review: Recent Advancements in Deep Learning Techniques for Facial Feature Recognition
Full text linkDeep Learning is a rapidly evolving field with critical contributions to various domains including security, healthcare, and human — computer interaction, etc. It reviews the significant developments in the area of facial recognition using deep learning techniques. It explains deep learning models such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Long Short-Term Memory Networks (LSTMs), and Generative Adversarial Networks (GANs), as well as hybrid models and transfer learning uses. It also addresses technical, ethical, and legal challenges that arise for facial analysis systems and emphasizes the need for real-time processing, multi-modal systems, and robust algorithms to improve the technical accuracy and fairness of facial analysis
The Factors That Affect Electronic Learning Students\u27 Behavioural Intentions In The Higher Education Tourism And Hospitality Disciplines
Full text linkIntroduction: This study aims to explore the factors influencing the intention of hospitality and tourism students in the UAE to adopt e-learning using the Technology Acceptance Model (TAM). E-learning has become an essential tool in higher education, particularly in response to the COVID-19 pandemic. The research seeks to identify the key determinants that affect students\u27 willingness to engage with e-learning platforms.Methods: A cross-sectional survey was conducted in two phases, involving 278 undergraduate students from a UAE university. The survey assessed various TAM constructs such as perceived usefulness, ease of use, system characteristics, and hedonic motivation. Data were analyzed using SmartPLS software and Structural Equation Modeling (SEM) to test the relationships between the variables.Results: The study found that perceived usefulness and ease of use were the most significant factors influencing students\u27 intention to adopt e-learning. Other influential factors included e-learning resources, platform functionality, subjective norms, and e-learning support. Additionally, hedonic motivation played an important role in enhancing students\u27 engagement with e-learning.Conclusions: The findings suggest that higher education institutions should focus on improving the perceived usefulness and ease of use of e-learning platforms while ensuring robust system functionality and support. The study contributes to the understanding of technology adoption in non-technical fields, offering insights that can inform e-learning strategies, especially in the context of future pandemics or disruptions
PRISMA Guidelines: Methodological Adaptation for Systematic Reviews in Education
Full text linkIntroduction: Systematic reviews in education require methodological adaptations due to the complexity of educational data and contexts, making it necessary to adjust the PRISMA guidelines, initially designed for health, to meet the needs of the educational field. Objective: To adapt the PRISMA guidelines for their methodological implementation in systematic reviews within the educational domain. Methodos: A documentary and comparative analysis between PRISMA and educational studies was conducted, complemented by consultations with specialists, allowing the development of an adapted framework based on rigorous criteria and methodological tools tailored to education. Results: An adapted framework was proposed, including inclusion and exclusion criteria, methodological procedures, and tools for quality assessment, positively impacting the relevance, applicability, and rigor of educational systematic reviews. Conclusions: The adaptation of PRISMA to the educational field will enhance the quality of systematic reviews, strengthening their impact on policies, pedagogical strategies, and evidence-based teaching practices in complex contexts such as Latin America
Novel Key Generator-Based SqueezeNet Model and Hyperchaotic Map
Full text linkCybersecurity threats are evolving at a very high rate, thus requiring the use of new methods to enhance the encryption of data and the communication process. In this paper, we propose a new key generation algorithm using the simultaneous use of the SqueezeNet deep learning model and hyperchaotic map to improve the hallmark of cryptographic security. The method employed in the proposed approach is built around the SqueezeNet model, which is lighter and faster in extracting features from the input image, and a hyperchaotic map, which is the main source of dynamic and non-trivial keys. The hyperchaotic map enhances complexity and randomness, securing the new cryptosystem against brute force and statistical attacks, and the key length depends on the number of features in the image. All our experiments prove that the proposed key generator works well in generating long, random, high entropy keys and is highly resistant to all typical cryptographic attacks. The promising profound synergy of deep learning and chaotic systems provides directions for the development of secure and effective methods of cryptography amid the exacerbated cyber threats. The technique was found to meet all the 15 criteria as tested through the NIST statistical test suite
Integrating Interior Design and Project Management: The Mediator\u27s Role in Enhancing Organizational Creativity and Efficiency
No full textIntroduction: The combination of interior design and project management is key to improving organizational creativity and efficiency. As firms compete for differentiation, it becomes necessary to optimize the design and management of workspaces. Methods: This research seeks to verify the hypothesis of the relationships between interior design quality, project management effectiveness, and organizational creativity and efficiency with the mediating effect of integration. A close-ended structured questionnaire was administered among 350 managers of Jordanian project management companies quantitatively to collect data. For the analysis the study conducted structural equation modeling (SEM) using Smart PLS 4. Results: The results shed light to confirm the existence of significant positive relationships between IDQ and OCE, PME and OCE, IDQ and INT, and PME and INT. Moreover, integration (INT) serves as a partial mediator between IDQ, PME and OCE. Conclusions: The study suggests that there is a need for a paradigm shift in project management approaches to promote the application of modern interior design techniques for improved organizational innovation and efficiency. Further studies should investigate these findings in other industries and other cultures