Universidad Nacional Pedro Henríquez Ureña

Text vectorization is indispensable for natural language processing (NLP). It allows us to transform text—from comments, reviews, documents, and even complete books—into formats or values that we can use as input in machine learning (ML) models. In this article, we present a comparative analysis between some of these methods used for text vectorization. The general purpose is to identify which of these methods offers a superior performance when applied together with some classification models on binary classification datasets. Each vectorization method, in combination with the models used, is evaluated by standard metrics in machine learning, such as Accuracy, Precision, Recall, F1-score and area under the curve (Receiver Operating Characteristic (ROC)) for a robust evaluation, demonstrating that the newest and most complex vectorization methods are not necessarily better for all binary classification tasks.

Ultrasonic Transit-Time Flow Measurement (TTFM) is one of the most effective techniques for evaluating the quality of coronary grafts; however, reliable measurement of very low blood flow rates requires high temporal resolution and stable signal processing. This work presents the design and development of a custom electronic module for TTFM applications, based on phase detection and time-to-voltage conversion. The proposed system employs a phase detector operating with a 2 MHz reference signal and a monostable time window that selects seven pulses from the received ultrasonic signal. The resulting phase-dependent pulse train is processed using a precision integrator and digitized by a 24-bit A/D converter. Experimental results show that the phase detector generates negative-edge pulses with durations of 10–15 ns, whose widths vary proportionally with the phase difference between the transmitted and received signals. Under zero-flow conditions, the system is adjusted to operate at 250 ns, corresponding to half of the reference period, thus avoiding saturation at extreme values. The integrator successfully converts these phase variations into stable voltage levels, enabling consistent digitization and real-time visualization. These results demonstrate that the electronic module is capable of measuring time intervals on the order of picoseconds derived from the difference in the propagation time of ultrasonic signals traveling upstream and downstream within a coronary artery, based on the ultrasonic transit-time method.

La competencia mediática es clave en la formación docente, especialmente en la educación secundaria, donde el profesorado desempeña un rol fundamental en la alfabetización mediática e informacional (AMI) del estudiantado. En la República Dominicana, su integración en la práctica docente sigue siendo un reto, debido a la falta de formación específica y de políticas educativas que la incorporen transversalmente en el mundo académico. Este estudio evalúa el nivel de competencia mediática en docentes de secundaria, identificando fortalezas y debilidades en la aplicación de estrategias pedagógicas basadas en la AMI. Para llevar a cabo la investigación se empleó un enfoque cuantitativo, descriptivo y de corte transversal a través de una encuesta con una muestra de 1.664 docentes del país. Los resultados indican un buen desempeño en referencia al acceso a la información y la comprensión crítica, pero dificultades en la producción de contenido digital y metodologías innovadoras. Se concluye que, aunque el profesorado posee competencias analíticas sólidas, es necesario fortalecer su producción y participación digital. Estos hallazgos pueden orientar políticas y estrategias de formación docente en AMI.

The objective of this study is to identify the determinants of social media advertising and its influence on purchase intention (PI). Four key factors such as information (IN), entertainment (EN), interactivity (IT) and privacy concern (PC) are investigated. Using a quantitative approach and structural equation modeling (SEM), data were collected from a sample of 213 participants. The results reveal that interactivity β = 0.30 is the factor with the greatest positive influence on purchase intention, followed by information and privacy concerns with β = 0.22 value for each. Although entertainment also has a positive influence on purchase intention β = 0.15, its influence is lower. In addition, it is highlighted that proper privacy management can increase consumer confidence and thus their willingness to buy. The proposed SEM model explained 37

Abstract The COVID-19 pandemic exposed critical vulnerabilities in globally concentrated biomedical supply chains and accelerated interest in nearshoring and hemispheric health-security strategies. The Dominican Republic, already the third-largest medical device exporter in Latin America, occupies a strategically significant but institutionally constrained position within this realignment. This study evaluates stakeholder perceptions of the principal opportunities and barriers affecting biomedical ecosystem development in the Dominican Republic, with particular attention to governance, workforce capacity, and value-chain upgrading pathways. Methods A concurrent mixed-methods design was employed, integrating a cross-sectional electronic survey of 142 purposively sampled domain experts (administered September–December 2025) with a qualitative executive consultation with senior government and industry leaders. Survey analyses combined descriptive statistics, one-sample t -tests against the scale neutral midpoint, chi-square goodness-of-fit tests, Friedman non-parametric ranking, Spearman rank correlations, and exploratory linear and logistic multivariable regression. Qualitative responses were analyzed using a framework approach grounded in the Triple Helix model of innovation systems. Results Perceived government support was significantly below neutral (mean = 2.67, SD = 1.12; p = 0.034). Workforce shortages (83.3%) and weak academia–industry collaboration (71.4%) were the most frequently endorsed barriers (χ 2 (5) = 18.7, p = 0.002). Regulatory modernization (88.1%) and workforce development (85.7%) ranked as the highest-priority policy levers (Friedman p = 0.005). Clinical trials and contract research organization services were the dominant sub-sector priority (76.2%, binomial p < 0.001). In multivariable analysis, perceived government support, talent availability, and confidence in IP protection jointly explained 46% of the variance in sector competitiveness ( R 2 = 0.46, p < 0.001). Strong majority support existed for a formal public–private biomedical coordination authority (73.8%, p < 0.001) Conclusion Institutional credibility and advanced human capital—rather than geography or market access—are the perceived binding constraints on the Dominican Republic’s biomedical trajectory. Regulatory modernization, targeted workforce investment, and the establishment of a national biomedical coordination authority represent the highest-leverage interventions for positioning the country as a hemispheric hub for biomedical manufacturing, clinical research, and health security.