El empleo de redes neuronales para la toma de decisiones dentro del proceso conglomerado KDD, en la gestión del mantenimiento en entidades de electro medicina, se hace cada vez más necesario, en u entorno lleno de datos. Weka como herramienta de minería de datos nos pone en una situación de ventaja al poder extraer conocimiento de los datos recopilados durante el proceso de explotación de los activos electro médicos.

Introduction: this article was conducted in the field of polymerase chain reaction (PCR) test safety, where it is essential to understand the contribution and impact of risk analysis methods to improve test safety medical diagnosis at the institutional level. In this context, the current study focuses on failure modes and effects analysis (FMEA) applied to the Perkin-Elmer/Cetus deoxyribonucleic acid (DNA) thermocycler.Objective: to describe the application of FMEA to improve the operational safety of Perkin-Elmer/Cetus DNA thermal cyclers used in medical diagnostics in ataxic patients. Methods: to carry out this study, a methodology based on an exhaustive review of the scientific literature available in academic databases and relevant sources was used. Previous studies on FMEA analysis of DNA thermocyclers in common and expanded forms were collected and analyzed.Results: the results obtained demonstrated that FMEA is an effective tool to identify and evaluate possible failure modes of Perkin-Elmer/Cetus DNA thermal cyclers. Several defects were identified and their consequences, causes and classification based on their severity and frequency were determined. Likewise, corrective actions are proposed to reduce the identified risks.Conclusions: early identification of possible failure modes and implementation of corrective actions can reduce risk and guarantee the quality of the diagnoses carried out and therefore improve operational safety

Natural language processing (NLP) is a branch of fabricated knowledge that focuses on the interaction between computers and human speech. Python is one of the most widely used programming dialects in handling common dialects due to its ease of use and the wide range of accessible libraries and devices. Through different widgets and libraries, Python allows engineers to work with content productively and successfully. Natural language management in Python has applications in a variety of areas, such as examining assumptions, automatic interpretation, and estimating research in social systems. In the field of neonatal medical services, the use of artificial intelligence (AI) and NLP can completely improve neonatal care by foreseeing possible dangers or complications during pregnancy, delivery, and postpartum care. Expandingly, AI can offer help in identifying intrinsic inconsistencies, formative disorders, and anticipating neonatal silent disintegration. Through AI calculations, silent weakening can be anticipated in neonatal clinics, allowing for faster and more accurate decisions. However, the use of AI in this context also raises moral, legitimate and social challenges that must be addressed with commitment and simplicity.

Urban mobility is undergoing a profound transformation driven by technological innovation, demographic shifts, and environmental imperatives. Among the most disruptive developments is the emergence of Shared Autonomous Vehicles (SAVs), which promise to redefine transportation efficiency, sustainability, and accessibility. This study aims to assess the potential impact of SAVs on future urban mobility, focusing on key dimensions such as traffic congestion, emissions, operational costs, and equity. A mixed-methods approach was employed, combining a systematic literature review, case studies of pilot cities (San Francisco, Gothenburg, Shenzhen), traffic microsimulations, and semi-structured interviews with experts in urban planning and autonomous technologies. Analytical tools included PTV Vissim for traffic modeling, multi-criteria decision analysis (MCDA), and demand forecasting software. Findings reveal that SAVs can reduce traffic congestion by up to 40% in densely populated areas, lower CO₂ emissions by 25%, and expand transport coverage in underserved zones. However, regulatory, technological, and social challenges remain, potentially hindering short-term implementation. The study concludes that while SAVs hold transformative potential, their success depends on integrated public policies, smart infrastructure, and broad societal acceptance.

Active transport infrastructure including pedestrian and cycling networks is essential to promote urban equity and sustainability, especially in peripheral zones marked by social vulnerability and structural limitations. In the Cuban context, where territorial disparities and infrastructure obsolescence persist, rethinking inclusive mobility models becomes urgent.Objective: This article aims to analyze, through a systematic review, the trends, approaches, and theoretical gaps surrounding active transport infrastructure in peripheral zones, emphasizing its contribution to territorial equity and urban sustainability in Cuba. Methods: A systematic literature review was conducted using databases such as Scopus, Redalyc, SciELO, and Google Scholar, focusing on publications from 2018 to 2023. Inclusion criteria targeted studies on urban planning, sustainable mobility, territorial equity, and spatial justice. A thematic analysis matrix and conceptual mapping tools were used to synthesize findings. Results: The review revealed a lack of Cuban studies focused on peripheral zones, with technical approaches dominating the discourse. Five key categories emerged: accessibility, connectivity, community participation, infrastructural resilience, and spatial justice. International studies offer replicable models, though contextual adaptation is required. An integrated analytical framework is proposed, linking physical, social, and environmental dimensions.

This study focuses on developing a procedure to diagnose and design quality planning at the Playa Pesquero Hotel, in accordance with the requirements of ISO 9001:2015. The research used theoretical, empirical, and statistical methods, including analysis and synthesis, inductive-deductive, structural-systemic, document review, direct observation, interviews, and surveys, among others. The most relevant results focus on conducting quality assessment and planning within the organization in question, highlighting the comprehensive assessment of the requirements: the organizational environment, management, and planning; as well as the design of the necessary requirements for quality planning at the Playa Pesquero Hotel.