En un mundo caracterizado por cambios vertiginosos y una creciente presión social y tecnológica, el libro "Salud Mental en la Educación Moderna" emerge como una guía integral para abordar los desafíos de la salud mental en el ámbito educativo. Marcelo Storoszczuk Durán ofrece un análisis profundo y multidisciplinario que combina investigación, experiencia docente y estrategias prácticas. Esta obra se centra en las estrategias educativas inclusivas y sostenibles, empoderando al personal educativo, y fomentando la resiliencia, la diversidad y el bienestar psicológico en las aulas. Ademas, se logran combatir los estigmas y mitos sobre la salud mental, en consonancia con la educación en el siglo XXI. Dirigido a educadores, padres, profesionales, y cualquier ávido lector, este libro se convierte en un recurso esencial para construir ambientes educativos saludables e inclusivos, que promuevan el desarrollo integral de estudiantes y docentes, así como de la sociedad en su conjunto.

Este articulo busca analizar la complejidad de brindar educación en situaciones adversas, contextos críticos, y traumas. Integrando aspectos de la psicología, la sociología, y la pedagogía, se estudian las consecuencias e implicaciones a corto, medio y largo plazo para los individuos y comunidades afectadas, incluyendo traumas, secuelas, y migración extrema. Después, se busca comprender las estrategias utilizadas para la educación en entornos críticos, entendiendo el rol de los gobiernos, las organizaciones no gubernamentales, y la comunidad educativa internacional al abordar las necesidades de los grupos azotados por emergencia. Finalmente, se discuten estrategias innovadoras que involucren nuevas tecnologías y políticas enfocadas en la resiliencia, con el objetivo de informar y guiar a la formulación e implementación de prácticas efectivas en este ámbito crítico.

This study investigates the role of Artificial Intelligence (AI) in enhancing the transfer of training within the United Arab Emirates (UAE) government sector, particularly in Dubai. The primary objective is to explore how AI can facilitate the application of newly acquired skills and knowledge in real-world job sce-narios, thereby improving employee performance and productivity. The research addresses the impact of AI on training process, and potential methods to en-hance its effectiveness. This research contributes to the understanding of AI’s role in training transfer and provides practical recommendations for leveraging AI to enhance training outcomes in government organization.

Among sexually transmitted infections (STIs), syphilis stands out for its silent and systemic nature. There are acquired (sexually transmitted) and congenital (mother-to-child) syphilis, caused by the bacterium Treponema pallidum. In recent years, there has been a significant increase in syphilis cases in Brazil, especially among men, reflecting an epidemic scenario in the country. It may be related to different factors such as: unprotected sex, multiple sexual partners, socioeconomic issues and failures in the implementation of sexual education and public health programs. The objective of this study is to identify the epidemiological patterns of acquired syphilis in Brazil between 2013 and 2023, analyzing the variation in notifications over time in different Brazilian states. Underreporting of syphilis underestimates the scale of the problem and hinders the planning of effective actions to control it. To mitigate this problem, it is essential to improve reporting systems, invest in training health professionals to ensure more accurate data collection, and promote educational campaigns that reach the most vulnerable populations.

Este presente proyecto brinda información referente al como las tecnologías pueden llevarse de la mano con la educación, sirviendo como apoyo a los estudiantes para que puedan mejorar la comprensión en las distintas disciplinas en su desarrollo académico, a través de juegos, creando ambientes favorables autogestivos.

A paper detailing the historical impacts of Uzbek carpet weaving on the development of art as a whole in Uzbekistan and the rest of Central Asia, from ancient times to the modern day.

El presente artículo aborda la urgente necesidad de adaptación del sistema educativo a las cambiantes tendencias del mundo moderno. En un contexto donde las transformaciones tecnológicas y laborales se suceden a un ritmo vertiginoso, las reformas educativas tradicionales se enfrentan al desafío de volverse obsoletas antes de ser completamente implementadas y evaluadas. En este sentido, se destaca la importancia de replantear los fundamentos del sistema educativo mediante la introducción de un nuevo paradigma: el Sistema Educativo Modular (SEM). Este enfoque busca proporcionar una solución efectiva y sostenible al problema de la obsolescencia acelerada de las reformas educativas. Se propone un sistema altamente adaptable y flexible, capaz de ajustarse ágilmente a las demandas cambiantes del entorno. El Sistema Educativo Modular se fundamenta en la creación de un marco estructural que permita la fácil modificación de sus componentes clave, desde los programas de estudio hasta los métodos de evaluación.

Active safety systems for powered two wheelers (PTWs) are considered a key pillar to further reduce the number of accidents and thus of injured riders and fatalities. Enhanced awareness for the current riding situation is required to improve the performance of current systems as well as to enable new ones; this includes the detection of the rider’s intention – the action that is planned by the rider for the short-term future. The prediction of a continuous trajectory for the upcoming seconds of the ride is one way to express rider intention. Our work pursues the prediction of the PTW lateral dynamic state by means of a roll angle trajectory over the upcoming 4 s of riding. It thus considers the special vehicle dynamics characteristics of single-track vehicles that negotiate bends at a roll angle compared to cars. A deep learning (DL) prediction model that is based on a Long-Short Term Memory (LSTM) layer is optimized and trained for this task using a broad on-road riding dataset that focuses on the rural road environment. Inputs to the prediction model are PTW internal signals only, that are measurements of vehicle dynamics, rider inputs, and rider behavior. The latter two groups of signals are non-common for current series production PTWs and were especially added to our test bike before gathering the riding data set. The prediction performance of the optimized DL model is compared to a simple heuristic algorithm using multiple metrics in the roll angle and position trajectory domain. Evaluation on a representative test data set shows a significantly improved detection of rider intention by the DL model in all metrics. Reasonable lateral trajectory accuracy is achieved for at least 2 s of the total 4 s prediction horizon in 99 % of all test cases, given the chosen model architecture and input features. Furthermore, the feature importance of the especially added non-common measurement signals of steering and rider behavior is investigated in an ablation study. It reveals the importance of steering signals in the first second of the prediction horizon whereas the rider behavior signals aid trajectory prediction performance for up to 2.5 s.

This project examines the practices of six Norwegian municipalities, which in a va-riety of ways are trying to enable mentally disabled residents to build or buy their own homes. The survey has confirmed some previous findings: the financing model operat-ed by the Norwegian State Housing Bank makes it possible for many mentally disabled persons to purchase homes on the ordinary housing market. However, even though private developers are without exception friendly, this appears to be a complicated and resource-demanding process. The cases show how municipalities can enable better processes in different ways. Leaving home can be a major upheaval both for young mentally disabled people and their parents, entailing changes in the young person’s re-sponsibilities, personal economy, and sense of independence. The overall objective is achieving inclusivity. Some of the homes are quite ordinary and are located among other similar homes, but our findings indicate that to date, residents experience little or no positive interaction with their other neighbors. Natural meeting places and commu-nal areas dedicated to entire neighborhoods occur only rarely in new housing projects. If we are to meet the objectives of inclusivity and participation, we have to expand our focus and not only look at the homes but also at the neighborhood in which the resi-dents shall be included.

In the past years, cargo bicycles in different configurations have gained popularity for many use cases. Their configurations differ substantially. Single-track cargo bicycles and their kinematics are linked closely to conventional bicycles. The kinematics of inverted tricycles, so-called tadpole trikes, are different. In this work, we model the motion for such a tadpole tricycle with articulated steering in order to predict the kinematic potential of such a vehicle. A single-track model for vehicle kinematics is implemented and compared to a planar model that incorporates a term for the lean (or roll) angle. To do so, the connection between steering and lean angle is calculated by the help of wheel flop. This is validated by inversing the modelling process and optimizing the geometrical approach function with the help of naturalistic cycling studies. The tricycle used for this study is measured experimentally in order to find the parameters for the model. It is then equipped with measuring devices and we present our instrumented tadpole cargo tricycle. By the help of it, we validate the two presented kinematic models for the motion of the tadpole tricycle with real world measuring data for given driving scenarios. These models are impinged with data from our experimental driving maneuvers. It is shown that our derived kinematic models hold reasonably well against the measurements for short term predictions during driving scenarios below the limits of driving dynamics. For the performed test scenarios, we compare the experimentally measured trajectory with the simulated ones and quantify the error. It is shown that a planar model that incorporates lean performs minimally better compared to a single-track model. We discuss model limitations as well as potential inaccuracies caused by the used measuring devices on our instrumented cargo tricycle. With the help of the kinematic models, motion prediction of tadpole cargo tricycles can be undertaken. The range for which the implemented planar models are considered to be valid is depicted by the range of forward speeds until the liftoff condition. For motion prediction, a single-track model is considered feasible, as the more complicated planar model with lean does not substantially outperform it. For maneuvers at the limits of driving dynamics, more sophisticated dynamic models are needed, as the simple kinematic models presented in this work are not sufficient for this kind of tasks.