Bicycle use has become more important today, but more information and planning models are needed to implement bike lanes that encourage cycling. This study aimed to develop a methodology to predict the speed a cyclist can reach in an urban environment and to provide information for planning cycling infrastructure. The methodology consisted of obtaining GPS data on longitude, latitude, elevation, and time from a smartphone of two groups of cyclists to calculate the speeds and slopes through a model based on a recurrent short-term memory (LSTM) type neural network. The model was trained on 70% of the dataset, with the remaining 30% used for validation and varying training epochs (100, 200, 300, and 600). The effectiveness of recurrent neural networks in predicting the speed of a cyclist in an urban environment is shown with determination coefficients from 0.77 to 0.96. Average cyclist speeds ranged from 6.1 to 20.62 km/h. This provides a new methodology that offers valuable information for various applications in urban transportation and bicycle line planning. A limitation can be the variability in GPS device accuracy, which could affect speed measurements and the generalizability of the findings.

El presente trabajo analiza cómo se implementan y qué impacto tienen las herramientas tecnológicas para la enseñanza de la Probabilidad y Estadística a partir de nivel medio. Se realizó una Revisión Sistemática, para así obtener datos cualitativos y cuantitativos sobre las investigaciones reportadas. Se destaca que la implementación de herramientas tecnológicas de la información y la comunicación (TIC) en la educación en el área de Probabilidad y Estadística permite conocer y explorar las aplicaciones del área y así profundizar en el aprendizaje de las temáticas, lo que permitiría generar una cultura estadística deseable para situaciones cotidianas.

La implementación de actividades en un curso depende de la modalidad educativa, lo que exige una planeación adaptada al contexto de su aplicación. El presente artículo tiene como objetivo describir el desarrollo y evaluación de un curso de regularización en modalidad virtual, en el que se implementaron actividades autogestivas orientadas a contenidos de probabilidad y estadística a nivel posgrado. La muestra incluyó a 132 aspirantes y estudiantes distribuidos en cuatro iteraciones, quienes participaron a través de Moodle, quienes respondieron un cuestionario final que evidenció algunos factores determinantes, como el manejo de la plataforma, la presentación de las actividades, el uso de recursos TIC y la retroalimentación continua. La aplicación de la Investigación Basada en Diseño (IBD) permitió realizar modificaciones progresivas que mejoraron tanto la experiencia de aprendizaje de los estudiantes como su rendimiento académico. El enfoque autogestivo brinda flexibilidad, al permitir a los estudiantes organizar su tiempo y espacio para completar las actividades propuestas dentro de los plazos establecidos. Sin embargo, se identificaron desafíos asociados con la modalidad a distancia, lo que motivó a implementar estrategias adicionales, tales como una mejor planificación y una comunicación constante entre el docente y los estudiantes.

While mining provides critical raw materials for modern infrastructure and the energy transition, it leaves behind severe environmental damages, such as soil mercury (Hg) contamination. In the present study, we present the first study evaluating the relationship of the ectomycorrhizal fungus Pisolithus arhizus with Trifolium repens (white clover) as a novel nature-based mycoremediation strategy for mercury-stressed soils. Through a controlled 2 × 2 factorial experiment over six months, we demonstrate that P. arhizus significantly enhances both plant biomass and heavy-metal tolerance. Inoculation achieved a 9.53% reduction in soil Hg and drove a dramatic 53% increase in stem growth under Hg stress (compared to 36% in non-contaminated conditions) once the extraradicular mycelial network was established. Furthermore, we report novel soil-chemistry dynamics under Hg stress, including a 16% shift in electrical conductivity alongside unexpected increases in the available potassium (+9%) and phosphorus (+3%). These findings present first results for a novel approach of mycoremediation by incorporating P. arhizus into T. repens co-cultivation as a viable remediation strategy, prior to field-scale remediation.

Antimicrobial resistance (AMR) constitutes a growing global threat, facilitated by the dissemination of antibiotic resistance genes (ARGs) through wastewater treatment plants (WWTPs). This systematic review, conducted following the PRISMA guidelines, compiles the risks associated with ARGs, as well as the factors that promote horizontal gene transfer (HGT) and the technologies applied for their removal. The literature shows that WWTPs act as reservoirs, where biological treatment conditions and the presence of sub-inhibitory contaminants (antibiotics, metals, and pharmaceuticals) accelerate HGT. Although conventional methods (chlorination, ozonation, UV) are effective at eliminating antibiotic-resistant bacteria (ARB), their ability to degrade persistent genetic material is insufficient. Therefore, advanced oxidation processes (AOPs) emerge as a key solution, with the photo-Fenton process standing out due to efficiently generating hydroxyl radicals, achieving the degradation of ARGs, an essential step to mitigate the spread of AMR into the environment.