Universidad Latinoamericana de Ciencia y Tecnología

GeoLatinas, a not-for-profit, international organization founded in 2019, promotes and supports Latina women in Earth and Planetary Sciences. Our organization has team-led initiatives focused on mentoring, education, and outreach for professional and

This research provides an extensive examination of the adoption of deepfake technology throughout digital business ecosystems, analyzing 186 cross-sector deployments from 2017 to 2024 using a mixed-methods methodology that combines qualitative case studies with quantitative risk-benefit indicators. The study reveals notable differences in sectoral adoption results. For example, marketing had a 28% return on investment from tailored synthetic material, even if trust fell by 22% when the content was revealed. On the other hand, finance saw a 62% drop in synthetic fraud, although it cost $4.2 million to fix false positives. A geographic study shows that adoption rates are different in different parts of the world. For example, Asia-Pacific has a 63% acceptance rate under utilitarian-driven governance (2.9/5 regulation score), whereas the EU has a more conservative 38% acceptance rate under the General Data Protection Regulation (4.2/5 score). Technical benchmarks reveal significant detection weaknesses, with accuracy decreasing from 97% in controlled environments to 68.2% in practical applications, compounded by an 83% accessibility deficit for small and medium-sized enterprises (SMEs) requiring 8.7 TFLOPS equipment. The study enhances the field by presenting a Composite Risk-Benefit Index for sectoral risk assessment, suggesting a tiered governance framework in accordance with IEEE standards, and setting empirically validated detection thresholds. Key results show that effective adoption needs cross-functional governance (odds ratio = 4.2), dynamic transparency standards (73% consent uptake), and fair access solutions to close the gaps across SMEs. These ideas provide practical direction for companies navigating the equilibrium between innovation and responsibility in an age characterized by the widespread dissemination of synthetic media. Received: 19 February 2025 | Revised: 19 May 2025 | Accepted: 22 August 2025 Conflicts of Interest The author declares that he has no conflicts of interest in this work. Data Availability Statement Data sharing does not apply to this article as no new data were created or analyzed in this study. Author Contribution Statement Gabriel Silva-Atencio: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration.

The capacity to innovate has grown to be a major obstacle in the corporate environment in the digital age. For technology-based small and medium-sized enterprises (SMEs), open innovation provides a strategic and cultural means to improve their innovation capacity by using internal and external ideas, resources, and technical knowledge-how. Although earlier studies have examined how open innovation affects big businesses, there is a great knowledge vacuum on how open innovation and strategic orientation affect innovation performance in SMEs, especially in underdeveloped countries. This research fills this need by investigating in Costa Rican technology-based SMEs the link between open innovation, strategic orientation, and inventive performance using a quantitative, cross-sectional methodology. The research supports the suggested hypotheses using Cronbach’s alpha and statistical models, showing that strategic orientation and open innovation favorably affect inventive performance. The results add to the state of the art by giving empirical data from a developing economy setting and pragmatic advice for SMEs trying to improve their capacity for innovation in a fast-changing digital environment. Received: 14 January 2025 | Revised: 15 April 2025 | Accepted: 4 July 2025 Conflicts of Interest The author declares that he has no conflict of interest in this work. Data Availability Statement Data sharing is not applicable to this article as no new data were created or analyzed in this study. Author Contribution Statement Gabriel Silva-Atencio: Conceptualization, Methodology, Validation, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration, Funding acquisition.

Combining quantitative surveys of 150 experts with qualitative case studies, this research uses a mixed-methods approach to explore how industry professionals see the influence of the Internet of Things (IoT) on operational excellence (OpEx) and competitiveness throughout the transition to Industry 5.0. While noting adoption hurdles, especially for small and medium-sized enterprises (SMEs), the study’s goals include evaluating IoT’s role in process automation, data-driven decision-making, and sustainability. The research used Spearman’s correlation (ρ = 0.76, p < 0.05) to test hypotheses using a cross-sectional design using non-probabilistic sampling across manufacturing (30%), logistics (25%), healthcare (20%), and information technology (15%) sectors. Although notable adoption differences exist (SMEs 25% vs big enterprises 82%), key findings show that 75% of users see quantifiable OpEx benefits via predictive maintenance and quality control automation. Particularly stressing SME accessibility via modular solutions and worker upskilling, the study finds that IoT is a strategic differentiator in Industry 5.0 when applied via staged frameworks addressing technological, organizational, and human elements. Among the suggestions are creating uniform interoperability standards, government-backed IoT adoption initiatives for SMEs, and living laboratories for ongoing innovation. While considering cybersecurity and ethical concerns of industrial IoT ecosystems, future studies could use longitudinal designs to monitor IoT’s total cost of ownership and explore 5G-edge computing synergies. Received: 26 March 2025 | Revised:12 June 2025 | Accepted: 23 June 2025 Conflicts of Interest The author declares that he has no conflict of interest in this work. Data Availability Statement Data sharing does not apply to this article as no new data were created or analyzed in this study Author Contribution Statement Gabriel Silva-Atencio: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration, Funding acquisition.

Energy literacy is described as the public understanding of energy from both the affective and behavioural aspects. The idea of energy literacy gained momentum in the 1970s but thereafter dwindled continuously. Thus, efforts to appropriately identify and measure energy literacy characteristics have increased worldwide over the last two decades. This study administered a questionnaire to a sample of Mexicans who participated in several energy-related massive open online courses (MOOCs) to measure the extent of their energy literacy. Results revealed that participants expressed elevated concern about acting for energy conservation, but differences were noted based on variables such as gender, participant profiles, and climatic regions. The correlations between the instrument subscales (affective, behavioural, and cognitive) differed in various degrees across regions from the findings of other studies. This study offers fresh insights into energy education by observing new variables (i.e. participant profiles) in a Mexican sample of adults. Thus, it reinforces scholarly efforts to consolidate a theory of energy literacy.

Abstract: This paper suggests a new method for improving routes in complicated logistics systems by combining cognitive modeling with quantum computing algorithms, especially the Quantum Approximate Optimization Algorithm (QAOA). In the classic Traveling Salesman Problem (TSP), the model shows major improvements, beating traditional methods by 25% in finding solutions accurately and cutting computation time by 30%. Simulations show a 15% drop in travel time and a 20% cut in CO₂ emissions, highlighting how the model helps improve efficiency and support environmental sustainability. The innovation comes from combining two usually separate fields: cognitive modeling, which mimics how humans make decisions, and quantum computing, which allows for fast and large‑scale optimization. This teamwork between different fields encourages quick, flexible, and scalable decision‑making, which is essential in fast‑changing, real‑time logistics settings. The model matches the move towards Industry 5.0, which focuses on working together with machines and being environmentally friendly. It also supports the United Nations Sustainable Development Goals, especially Goal 9 (Industry, Innovation and Infrastructure) and Goal 13 (Climate Action). To make sure the study is valid, it uses open‑access datasets and simulates real‑life situations, such as smart warehouse operations and fleet management systems. The results highlight how quantum‑enhanced cognitive systems can change the game, providing a modern tool to build smarter, greener, and stronger supply chains. This research not only pushes the boundaries of optimization science but also lays the groundwork for using quantum algorithms in industry in the future.

This study explores the intersection between incremental risks introduced by sustainable sourcing practices in procurement and the role of Smart Digitalization Technologies (SDT) in mitigating these risks while enhancing operational efficiency, organizational effectiveness, and resilience.A mixed-methods approach was employed, combining a structured survey of procurement professionals with in-depth interviews with SDT providers.This methodology allowed for both quantitative validation of SDT's perceived effectiveness and qualitative insights into their strategic applications.Findings reveal that while SDT significantly contribute to risk identification and mitigation, particularly through supply chain visibility, automation, and data-driven decision-making, challenges remain.Poor data quality, unrealistic leadership expectations, and ineffective change management limit their full potential.Additionally, SDTs have yet to prove effective in managing crises, particularly unpredictable disruptions.This research highlights SDT as a catalyst for sustainable procurement maturity, reinforcing the relationship between sustainability and operational efficiency.However, successful implementation depends on organizational readiness and strategic alignment.A practical evaluation tool is provided to assess known risks and mitigation mechanisms.

Los Tribunales constitucionales alrededor del mundo suelen mantener algún grado de relacióncon sus homólogos o con tribunales internacionales o supranacionales, de modo tal que, bajouna interacción recíproca, conocida como diálogo entre cortes, lo resuelto por uno de ellos esreferenciado o citado por el otro y ese criterio, en esencia externo, surte eficacia en el ordenamientojurídico interno. En el presente estudio se abordará el instituto del diálogo entre cortes y,particularmente, bajo análisis de casos, se efectuará un recorrido en torno a la relación existenteentre la Sala Constitucional costarricense y la Corte Interamericana de Derechos Humanos, asícomo de un repaso de los principales fallos en que se ha aplicado y tutelado en Costa Rica el corpusiuris interamericano.

This research looks at how auditing affects strategic decision-making during Costa Rica's shift to Industry 5.0. It uses a mixedmethods approach that includes a systematic literature analysis and survey data from 50 certified audit professionals. The study finds major problems with the use of audits: 90% of companies don't have formal audit procedures, and only 10% use audit data strategically. Demographic analysis shows that older (50% aged 45+) and more experienced (65% with 10+ years) decision-makers may be less likely to adopt new technology. Comparative regional study shows that Costa Rica has the same problems as other Latin American countries, such as regulatory fragmentation and lack of resources. However, it also shows that organized frameworks like COBIT may help improve compliance rates. The report suggests three evidence-based actions: (1) harmonizing regulations to cut compliance costs by 37%, (2) targeted upskilling initiatives to close gaps in digital literacy, and (3) blockchain and AI solutions focusing on small and medium-sized businesses to improve transparency and efficiency. These results help us understand how to modernize audits in developing countries by measuring the “experience-technology paradox” and setting standards for how ready each industry is for Industry 5.0. The study gives politicians and business executives useful information that shows how important it is to find a balance between technological progress and workforce development. Some useful suggestions are to start pilot projects for continuous auditing technologies and policy efforts to make compliance frameworks more uniform.

The COVID-19 pandemic marked a before and after in the business world, causing a growing demand for applications that streamline operations, reduce delivery times and costs, and improve the quality of products. In this context, artificial intelligence (AI) has taken a relevant role in improving these processes, since it incorporates mathematical models that allow analyzing the logical structure of the systems to detect and reduce errors or failures in real-time. This study aimed to determine the most relevant aspects to be considered for detecting software defects using AI. The methodology used was qualitative, with an exploratory, descriptive, and non-experimental approach. The technique involved a documentary review of 79 bibliometric references. The most relevant finding was the use of regression testing techniques and automated log files, in machine learning (ML) and robotic process automation (RPA) environments. These techniques help reduce the time required to identify failures, thereby enhancing efficiency and effectiveness in the lifecycle of applications. In conclusion, companies that incorporate AI algorithms will be able to include an agile model in their lifecycle, as they will reduce the rate of failures, errors, and breakdowns allowing cost savings, and ensuring quality.