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Restricciones físicas y de políticas para la comunicación digital en organizaciones cubanas
(Escuela de Comunicación - CampCM, 2026)
Lao-León, Yosvani Orlando
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Sera-Rodríguez, Roxana
El presente artículo tiene como objetivo analizar las restricciones físicas y de políticas que afectan la comunicación digital en organizaciones cubanas, particularmente en la provincia de Holguín. Se aplicó un diseño longitudinal con un alcance descriptivo-explicativo. Para lo que se diseñó un cuestionario estructurado en diez preguntas con una escala Likert con ruptura. Fue aplicado a una muestra intencional de 15 organizaciones, su selección se justificó considerando la representatividad sectorial y la posibilidad de generalizar resultados en la provincia. El instrumento evaluó recursos tecnológicos, capacidades del personal, procedimientos normativos y gestión de contenidos digitales. Los resultados indican que las restricciones: insuficiente infraestructura tecnológica, limitados recursos financieros, falta de personal capacitado y ausencia de políticas, protocolos e indicadores, funcionan como un sistema interconectado que se interrelaciona con el contexto socio-tecnológico cubano. La precariedad financiera y de infraestructura, impide sostener inversiones e implementar sistemas de formación; la carencia de políticas internas y criterios de evaluación fragmentan los esfuerzos y dificultan la replicabilidad. Por eso, sectores regulados como el bancario y el de seguridad exhiben más limitaciones mientras el turismo presenta mejor desempeño. El diseño del Árbol de Realidad Actual permitió identificar como causas raíces la ausencia de políticas internas sostenibles y los escasos recursos financieros. Se requieren soluciones integrales como: marcos normativos internos, financiamiento persistente, capacitación vinculada a procesos y métricas accionables y sostenibles.
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Modelo de competencias investigativas para programas de doctorado en educación en universidades mexicanas: una propuesta desde la alfabetización informacional
(Universidade de Brasília, 2026-02)
Este artículo presenta los resultados de un proyecto de investigación doctoral centrado en el desarrollo de competencias investigativas como parte esencial de la alfabetización informacional en estudiantes de doctorado en educación. A partir de un análisis de programas de posgrado en universidades mexicanas, el estudio identificó la falta de modelos sistemáticos que orienten la formación integral en investigación, más allá de disciplinas metodológicas aisladas. En respuesta, se desarrolló un modelo propio de competencias investigativas, dirigido específicamente a estudiantes de doctorado en el ámbito educativo. El modelo se estructura en torno a cuatro categorías fundamentales: investigación científica, recuperación y gestión de información, métodos de trabajo colaborativo y ética de la investigación. Cada categoría incluye su definición, objetivos e indicadores, lo que proporciona una guía clara y coherente para el desarrollo de las competencias necesarias para la formación de investigadores de alto nivel. La investigación empleó un enfoque de métodos mixtos, que integró el análisis documental de los planes de estudio, cuestionarios aplicados a los estudiantes y una revisión de instrumentos institucionales. Esta metodología permitió una comprensión contextualizada y empírica de las brechas de formación existentes. El modelo propuesto constituye una herramienta teórica y práctica que fortalece la formación investigativa de los estudiantes de doctorado en educación, con el fin de contribuir al mejoramiento de los programas de doctorado en México y otros contextos latinoamericanos. Al concluir este trabajo, se considera que este es solo el comienzo de un amplio horizonte que se abre para la formación de investigadores que integren programas de doctorado de calidad en nuestro país. Se espera que, al menos, se comprenda mejor la importancia de que los estudiantes desarrollen habilidades investigativas, tan necesarias para la formación de nuevos doctores en el campo de la educación y, por qué no, en otras áreas del conocimiento.
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Sphonic: Development of a Mobile Application Using AI and AR for Learning Biomedical Concepts
(Springer Nature Switzerland, 2025)
Escobar-Castillejos, Daisy
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Báez Gómez Tagle, Enrique Ulises
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Chavarría-Reyes, Fernando Mauricio
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Sigüenza Noriega, Iñaki
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Cruz-Ledesma, Iván
This chapter covers the development of Sphonic, an iOS mobile application that combines artificial intelligence (AI) and augmented reality (AR) to improve biomedical education. Sphonic was designed to employ SwiftUI for its front end, while its back end is based on Django and hosted on Amazon Web Services. Sphonic intends to assist in explaining complex topics in chemistry and biology. Using Apple’s ARKit framework, Sphonic allows students to explore dynamic representations of DNA architecture, chemical bonding interactions, and biological processes to promote engagement and retention. On the other hand, the application features an OCR-based chemical equation solver, using Amazon Bedrock’s generative AI capabilities, that balances equations and offers comprehensive, step-by-step guidance, addressing conceptual deficiencies for learners. Additionally, Sphonic implements secure authentication protocols to protect user data and features a user-friendly interface that simplifies navigation. This chapter concludes by emphasizing the importance of AI and AR in modern education, demonstrating how these technologies could democratize access and understanding of scientific information and foster creativity in academic environments. ©The authors ©Srpinger.
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Development of a Mobile Application for Dermatological Diagnosis Using Image Recognition: The DermAware Case Study
(Springer Nature Switzerland, 2025)
Cedillo-Maldonado, Luis
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Sigüenza-Noriega, Iñaki
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Miranda-Mateos, Sara Rocio
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Reinoso-Fuentes, Lorenzo
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Pérez-Aguirre, Mauricio
This chapter discusses the development of DermAware, an iOS mobile application intended for assisting dermatological diagnosis through image recognition and machine learning. DermAware aims to serve as a supplementary resource for specialized medical professionals and patients, aiding the early identification and supervision of dermatological illnesses. The application was developed with SwiftUI for the front end and Django for the back end, providing scalability and secure data management. The application incorporates multiple components designed to enhance its usability. A real-time messaging module was designed to facilitate direct communication among users for prompt consultation scheduling. Health tracking functionalities, supported by Apple’s HealthKit, enable the collection and monitoring of patient data. The application integrates patient history management, allowing doctors to review previous assessments and track disease development conveniently. Ultimately, an authentication system guarantees data confidentiality and adherence to regulations. DermAware uses Apple’s CoreML framework alongside the ResNet50 convolutional neural network model to classify skin diseases. The system was trained using publicly accessible dermatological datasets, achieving an accuracy of 85% for detecting various skin conditions, including melanoma. The chapter finishes by addressing the technical challenges faced during development, evaluating potential enhancements, and discussing future developments in the field. These factors highlight the significance of AI-driven applications for improving medical diagnostics and healthcare accessibility. ©The authors ©Springer.
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Machine Learning Methods in Biomedical Field : Computer-Aided Diagnostics, Healthcare and Biology Applications
(Springer Nature Switzerland, 2026)
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Gomez-Coronel, Sandra L.
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Renza Torres, Diego
This book provides an in-depth exploration of machine learning techniques and their biomedical applications, particularly in developing intelligent computer-aided diagnostic systems, creating groundbreaking healthcare technologies, uncovering novel biological applications, and fostering sustainable health solutions. Integrating artificial intelligence, mathematical modeling, and emergent systems, this book highlights the profound impact of these advanced tools in not only enhancing problem-solving within the biomedical field but also in catalyzing the development of novel solutions. This book is a valuable resource for readers interested in understanding the revolutionary impact of novel machine learning methodologies on the biomedical landscape. Furthermore, it offers a blend of theory and practical applications for those interested in biomedical education and training, biology, medicine, and sustainable health development. ©The authors ©Springer.
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Orthosis Control Based on Electromyographic Signals and Machine Learning
(Springer Nature Switzerland, 2025)
Escobedo-Gordillo, Andrés
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Díaz, Fernando
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Villa, Jesús
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Sepúlveda, Miguel
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García-Casas, Sebastián
The human hand is indispensable for daily activities, and those who suffer from dysfunction due to strokes or accidents often require therapy to improve their condition. This study has developed a hand orthosis that uses surface Electromyographic (sEMG) signals and machine learning to address therapeutic needs and improve the quality of life for individuals with reduced motor skills in their hands and/or wrists. While current orthoses meet therapy requirements, they do not incorporate machine learning (ML) or sEMG sensors to optimize performance and accessibility. This chapter describes a remote-controlled, electro-mechanical orthosis that can replicate six basic movements of the human hand using three sEMG channels and ML. Our dataset of 14,400 samples, each labeled with a hand gesture, was generated by eight participants. The orthosis is comfortable and customizable for different users, as shown in prototype testing. The convolutional neural network (CNN) used achieves an accuracy of 90.38% with an inference time of 1.515 ms. Therefore, this orthosis system has significant potential for further development and practical application in patients who require such intervention. ©The authors ©Springer.
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Digital financial inclusion as a catalyst for innovation, economic growth, and sustainability: A bibliometric analysis (2014-2024)
(Pro-Metrics, 2025)
Salazar-Uribe, Mayra Yvette
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Salgado-García, Jorge Arturo
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Hernández-Lara, Ana Beatriz
Objective. This study aimed to conduct a bibliometric analysis of keywords to identify strategic topics in digital financial inclusion (DFI) and their relationship with sustainability and economic growth between 2014 and 2024. Design/Methodology/Approach. A bibliometric analysis was conducted on a sample of 1,234 academic articles indexed in Scopus using the Bibliometrix tool in R. Keyword co-occurrence was examined using multiple correspondence analysis and K-means clustering to reveal thematic structures. Results/Discussion. A total of six thematic clusters were identified: (1) threshold effect, (2) digital transformation, (3) central bank digital currencies (CBDCs), (4) sustainable development, (5) financial and digital literacy, and (6) fintech. These clusters demonstrated the evolution of DFI from its initial role as a technological enabler, such as fintech and blockchain, to its current impact on economic development, growth, and sustainability. This analysis proposed a conceptual model of DFI. In this model, digital literacy and fintech functioned as enablers. Meanwhile, CBDCs and blockchain technology served as structural tools. Digital financial inclusion was defined as a mechanism for inclusive economic development. Conclusion. The findings contributed to an understanding of how financial digitization is linked to sustainability strategies and long-term economic growth. ©The authors ©Iberoamerican Journal of Science Measurement and Communication ©Pro-Metrics
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WEFE nexus unveiled: a comprehensive review of monitoring and modelling methods in the water-energy-food-ecosystems nexus
(Purpose Led Publishing, 2025-10)
Sustainable resource management in the face of climate change is a pressing challenge for our society. This paper delves into the water-energy-food-ecosystems (WEFE) nexus, a scientific framework that supports the integrated assessment and management of the interconnected resources. Shifting from sectoral to cross-sectoral and transdisciplinary perspectives, the WEFE nexus addresses interdependencies and interactions among water, energy, food, ecosystems, and climate. This paper focuses on the extended nexus, incorporating ecosystems as a fourth pillar, underscoring the importance of considering ecosystems on an equal footing with water, energy, and food sectors. In addition, the paper emphasizes the significance of monitoring and modelling techniques, laying the foundations for understanding the nexus complexities and assessing uncertainty. The paper offers an overview of integrated nexus modelling, system analysis and socio-economic modelling, bridging the gap between nexus science and practice. It highlights the role of multifaceted stakeholder engagement methods, policy assessment, and institutional analysis in nexus models. Quantifying the nexus through indicators, and its alignment with the Sustainable Development Goals, EU Green Deal, and EU Blue Deal are also key focal points. Finally, the last part of the paper addresses challenges in existing nexus modelling attempts, advocates for the integration of transdisciplinary information, and presents lessons learned. The paper concludes with recommendations for the future of the WEFE nexus, emphasizing its potential in fostering transformative change toward sustainable resource management and inclusive policymaking.
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Econometría en tu idioma
(Universidad Panamericana, 2025)
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Luquín-García, Dolores
Nacido del aula y la inquietud estudiantil, Econometría en tu idioma transforma una disciplina compleja en una herramienta cercana, útil y reveladora. Con ejemplos prácticos, explicaciones detalladas y un enfoque pedagógico que respeta tanto la teoría como la intuición, los autores guían al lector desde los fundamentos de los modelos econométricos hasta su validación y aplicación en escenarios reales. Ideal para estudiantes de finanzas, administración y economía, este texto no solo enseña a “hacer regresiones”, sino a interpretar lo que los datos nos dicen sobre mercados, decisiones y fenómenos económicos. Una invitación a perderle el miedo a los modelos y a descubrir, en los números, las historias que moldean nuestro entorno.
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Creating Onomastic Social Network Maps of Books Using Their Indexes. Case Study: ‘Papyrus: The Invention of Books in the Ancient World’
(Wiley, 2025)
Repiso, Rafael
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Ortiz-Díaz, Erik M
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This paper proposes a methodology to create social networks using subject and onomastic indexes from books to facilitate content analysis in monographic works. Books have not been largely studied in this context because their contents have not been digitized as in comparison with scientific research articles. However, indexes have been proven as a useful tool to identify relations between terms or characters mentioned inside the texts. This technique is based in the co-presence among these elements and they further visualization, offering a new perspective for structural analysis within Social Sciences and Humanities books. The book ‘Papyrus: The Invention of Books in the Ancient World’ has been used as a study object to illustrate this technique and its possibilities. ©The authors ©Learned Publishing ©Wiley.

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