The present study aims to evaluate the identity of the city in order to contribute to the develop-ment of strategies and action plans aimed at improving its image and positioning as a tourist destination. A mixedmethods approach was employed, combining qualitative and quantitative methods, including interviews and personal surveys. These were applied to local stakeholders involved in tourism and heritage, using a nonprobability sampling method based on expert judgment, and a structured questionnaire built around attributes and indicators of urban identity as a tourist destination. Statistical analysis was conducted using SPSS software. The study iden-tified eight attributes and 54 key indicators for evaluating the urban identity of Matanzas as a case study. Descriptive statistics were used to analyze the results. Respondents highlighted the bridges, rivers, and the bay as the city's main identity features. Although most attributes were considered highly important, the current state of the city was predominantly rated as negative or neutral, particularly in political, social, economic, and urban morphology aspects. The affective component of the identity showed neither a clearly defined nor positive characterization. These findings point to the need to strengthen distinctive attributes and indicators through urban mar-keting straegies, that is, to implement actions aimed at recovering and enhancing the city's pos-itive identity to improve its positioning in relevant tourism markets.
Optimising production processes is a key challenge in modern industry, with Machine Learning and Artificial Intelligence playing an increasingly important role. Yet, current approaches often require manual intervention and expert knowledge, slowing adoption. To overcome these limitations, this work proposes a methodology that integrates Automated Machine Learning with Large Language Models to carry out process optimisation in a highly automated, end-to-end manner. LLM are employed for code generation, enabling the creation of datasets from existing sources while accounting for contextual information expressed in natural language. AutoML then builds predictive models of the production process, which serve as objective functions in an optimisation algorithm. The methodology was validated through a case study involving four setups, consistently producing optimal solutions aligned with the defined goals. A comparative evaluation of thirteen LLMs for code generation and four AutoML frameworks for modelling was conducted. The best-performing LLMs, DeepSeek DeepSeek-R1, Anthropic Claude Sonnet 4, OpenAI gpt-oss-20b, and OpenAI GPT-5, achieved a 100% functional score. For modelling, TPOT and AutoGluon produced accurate results with coefficients of determination above 0.96 for all the target variables while yielding reliable optimisation solutions.
El sociograma es una técnica que evalúa las interacciones sociales dentro de un grupo de personas. El ámbito educativo es uno de los lugares donde se utiliza con mayor frecuencia, ya que se convierte en una herramienta invaluable para comprender de manera precisa las interacciones que se dan dentro del aula y que podrían pasar desapercibidas para el profesor. El enfoque de la investigación estuvo está en desarrollar un complemento para Moodle que brinde la posibilidad de ver un sociograma en cada curso, mostrando la interacción de los estudiantes como base para su participación. De este modo se logró determinar el nivel de unión presente dentro de un grupo de estudiantes y la posición que ocupa cada alumno en él, incluyendo al líder, aquel que puede estar aislado o rechazado por sus compañeros.
La sociedad contemporánea con sus acelerados cambios y los Objetivos de Desarrollo Sostenible, imponen a las universidades la formación de profesionales que investiguen, lideren y asuman trasformaciones comunitarias. El programa de formación de pregrado Gestión Sociocultural para el Desarrollo, de la Universidad de Matanzas, como respuesta a estas necesidades, forma un profesional con cualidades para mediar en la comunidad e impulsar las transformaciones socioculturales en ese ámbito. La presente pesquisa se basó en el paradigma interpretativo con un enfoque cualitativo, con el propósito de observar de forma objetiva el objeto de estudio: la formación de la competencia intervención comunitaria en la mencionada carrera. El tipo de investigación empleado, diseño transversal exploratorio con elementos descriptivos, facilitó el análisis y la recolección de datos de los estudiantes de la carrera en el año terminal. Se presentan acciones del trabajo docente y científico metodológico, como parte de la concepción teórico-metodológica para la formación de la competencia intervención comunitaria en este profesional. Se apreció transformación favorable, lo cual confirma el valor científico de la propuesta.
Public policies are an instrument of governments to solve social problems and represent the way to exploit local endogenous resources. The Cuban policies are aimed at diversifying the tourist offer, with special emphasis on forms such as health tourism. The present study aimed to propose a model of public policies for the management of health tourism at local level. A mixed methodology was used. The study was defined as exploratory, descriptive and explanatory; the methods of analysis-synthesis, induction-deduction, literature review, document analysis, survey and the Delphi method were used. The analysis of methodological background led to the elaboration of a new proposal adapted to the characteristics of the Cuban local context. The objective, principles and premises underpinning the tool were established, as well as the fundamentals of the components and their nterrelationships, which contributed to its graphical modelling, and the tool was validated by the evaluation of a team of experts. It was found to be necessary and relevant based on the gaps identified in the scientific literature regarding the design of public policies for health tourism at the local level
