Introduction Neurofibromatosis type 1 (NF1) is a multisystemic genetic disorder caused by pathogenic variants in the gene, characterized by variable clinical manifestations such as pigmentary abnormalities, neurofibromas, skeletal dysplasia, and tumor predisposition. However, genotype–phenotype correlations remain insufficiently explored, particularly in underrepresented populations. Methods Three unrelated Ecuadorian pediatric patients with a presumptive diagnosis of NF1 underwent detailed clinical evaluation, next-generation sequencing (NGS), using the TruSight Cancer panel, and ancestry analysis based on 46 ancestry-informative insertion–deletion (InDel) markers. Variants were classified according to ACMG/AMP guidelines using the Franklin and Variant Interpreter platforms, which incorporate in silico prediction tools to assess variant pathogenicity. Results Three distinct pathogenic variants were identified: one nonsense (p.Arg1534Ter) and two missense (p.Gln20His, p.Asp1644Asn). Clinical findings included early-onset orbital plexiform neurofibroma, multiple café-au-lait macules, axillary/inguinal freckling, radial bone dysplasia, cutaneous neurofibromas, and prepubertal gynecomastia. All patients exhibited predominantly Native American ancestry. analyses predicted a pathogenic classification of all variants. Early pigmentary signs, present in all cases, served as key diagnostic indicators. Conclusions This case series expands the mutational and phenotypic spectrum of NF1 in a pediatric Ecuadorian cohort. Findings underscore the diagnostic value of early pigmentary signs and highlight less commonly reported manifestations such as radial bone dysplasia and prepubertal gynecomastia. Integrating molecular diagnostics with early clinical evaluation may enable earlier and more precise diagnosis, guiding personalized management strategies. Further studies should investigate genotype–phenotype correlations and the influence of ancestry on NF1 expression.
El presente trabajo propone una revisión de la metodología de diseño puesta en práctica a partir de la aplicación del proyecto de vinculación “Estrategia de branding y educación administrativa financiera orientada a las unidades de economía popular y solidaria (UEPS) en la provincia de Pichincha”, realizado por los estudiantes de la carrera de Diseño Gráfico de la Universidad UTE. Este proyecto tuvo como objetivo principal proponer soluciones desde la gestión estratégica de marca a problemas comunicacionales identificados en microemprendimientos. Este artículo plantea que, por un lado, el proceso de creación de marca debe resultar del diálogo que se genera entre los diseñadores gráficos y los representantes de los emprendimientos, ya que, de este modo, se pueden transmitir adecuadamente los valores que identifican al pequeño negocio. Por otro, plantea de manera teórica cómo el manejo adecuado de la identidad visual permite a los representantes de las UEPS generar una relación sostenible y significativa con sus clientes, lo cual puede mejorar su desarrollo económico. Por tanto, se considera que el branding es una herramienta que favorece la incidencia de los pequeños negocios dentro de la dinámica comercial actual.
El diagnóstico predictivo de motores de inducción es fundamental para mejorar eficiencia y reducir costos. Este estudio introduce un chatbot en Telegram basado en el modelo T5 de NLP, adaptado para interpretar descripciones técnicas y generar diagnósticos automáticos con una precisión del 96.2 %, F1-score de 95.1 % y sensibilidad de 94.8 %. La principal novedad radica en aplicar T5 —un enfoque de texto puro— en lugar de métodos previos centrados en señales físicas como vibraciones o corriente, integrándolo en una interfaz móvil accesible. Las implicaciones son significativas: permite diagnósticos rápidos desde cualquier dispositivo, apoyando el mantenimiento predictivo en entornos reales. Sin embargo, su limitación radica en que el modelo fue entrenado con datos sintéticos, lo que puede afectar su rendimiento en situaciones reales con ruido e imprevistos, el enfoque demuestra ser viable, eficiente y escalable, aunque requiere validación real y capacidades adaptativas.
Polymers have extensive applications in various industries. One of them is the application of polymer materials in the textile industry which is an important and profitable industry. Assessment of physical and chemical properties of polymers can serve for analysis purposes of constitutive materials of apparel. This paper presents a mechanical study on the torsional dynamic behavior of textile microfibers i.e., polyester and nylon which are the common materials in the textile industry. As observed in the former investigation, microfibers have different cross-sections. Hence, elliptical and triangular shapes are considered for cross-section of textile microfibers. Nonlocal strain gradient theory in conjunction with Timoshenko-Gere theory is implemented to derive the partial differential governing equations of polyester and nylon microfibers. The accuracy of the utilized methodology is compared with the findings of former investigations. Moreover, two boundary conditions i.e., clamped–clamped and clamped-free are taken into account. At last, the impacts of various remarkable variants including microfibers cross-section geometry parameters, length scale, and nonlocal parameters on the variation of natural torsional frequency are evaluated and demonstrated in a set of tables and diagrams.
Wear from friction is a major cause of component failure in internal combustion engines, as parts frequently come into contact with each other. Engine oils are used to lubricate these parts and minimize wear. A common approach to reducing friction is to use higher-viscosity oils, which form a thicker protective film between moving components, preventing direct contact. However, while thicker oils can reduce wear, they also increase the energy required to keep the engine running, leading to higher power dissipation. In recent years, the use of nanoparticle-infused lubricants has gained attention for their ability to improve surface properties, enhance heat transfer, boost engine efficiency, and lower maintenance costs. This study explores the effects of adding nanoparticles to engine oils, focusing on their impact on the lubrication and wear resistance of gears and other automotive parts. The results revealed that oils with a higher concentration of nanoparticles significantly reduced the coefficient of friction and wear on stationary discs, confirming the superior lubricating performance of nanoparticle-infused oils. Furthermore, the pressure and anti-wear characteristics of these nano-oils were evaluated, showing marked improvements over conventional oils without nanoparticles.
