This work reviews the key challenges surrounding teaching Science, Technology, Engineering, and Mathematics subjects known as STEM. The research has uncovered a significant gap between traditional teaching styles and the need to develop and adapt to new remote-learning modalities. The work describes the technological, pedagogical, social, and institutional challenges, finally identifying the importance of their joint interaction. Since the COVID-19 pandemic, it has become evident that STEM educators must increase their awareness and knowledge of instructional models focused on using digital platforms. The current trend is centred on developing remote-learning tools, which will likely become the predominant learning norm as the economy’s viability increases. However, these remote-learning approaches must maintain interaction with the physical world, as understanding real-world phenomena is crucial for improving learning processes. STEM learning through e-learning will have a greater chance of success if academic institutions collaborate with other sectors of society, such as the business sector, to receive feedback for the continuous improvement of the proposed teaching methods.

This paper presents an active control design for the synchronization of two identical Petrzela chaotic systems (Petrzela, J.; Gotthans, T. New chaotic dynamical system with a conic-shaped equilibrium located on the plane structure. Applied Sciences. 2017, 7, 976) on master-slave configuration. For the active control, the parameters of both systems are assumed to be a priori known, the control law by means of the dynamic of the error synchronization is designed to guarantee the convergence to zero of error states and the synchronization process is verified by numerical simulation. By taking advantage of the execution and implementation facilities of microcontroller based chaotic systems in digital devices, the active controller is implemented in a 32 bits ARM microcontroller. The experimental results were obtained by using the fourth order Runge-Kutta numerical method to integrate the differential equations of the controller, where the results were measured with a digital oscilloscope.

Operation Sequencing (OS) is one of the most critical tasks in a CAPP system. This process could be modelled as a combinatorial problem where finding a suitable solution within a reasonable time interval is difficult. This work implements a novel Discrete Differential Evolution Algorithm (DDEA) to solve the OS problem, focusing on parts of up to 76 machining operations; the relationships among operations are represented as a directed graph; the contributions of the DDEA are as follows: (1) operates with a discrete representation in the space of feasible solutions; (2) employs mutation and crossover operators to update solutions and to reduce machining and setup costs, (3) possess a local search strategy to achieve better solutions, and (4) integrates a statistical method based on quantiles to measure the quality and likelihood for an achieving a solution. To demonstrate the efficiency and robustness of the DDEA, five prismatic parts with different numbers of machining operations as benchmarks to address the OS problem were selected. The results generated the same OS for parts with a few machining operations (up to 23 machining operations). Conversely, for parts with more machining operations, the DDEA needs more runs to achieve the best solution.

This study presents a novel algorithm implementation that optimizes manually recorded toolpaths with the use of a 3D-workpiece model to reduce manual error induced. The novel algorithm has three steps: workpiece declaration, manual toolpath declaration, and toolpath optimization using steepest descent algorithm. Steepest descent finds the surface route wherein the manually recorded toolpaths traverse over a 3D-workpiece surface. The optimized toolpaths were simulated and tested with an industrial robot showing minimal error compared to the desired optimized toolpaths. The results obtained from the presented implementation on three different trajectories demonstrate that the proposed methodology can reduce the manual error induced using as a reference the CAD-workpiece surface.

In this work, the study of smoke fire transportation inside of a subway passenger platform is presented. The study includes a set of numerical simulations to observe the behavior of the air inside the platform. Two smoke transport simulations using the FDS program are also included. Subsequently, the development of a 3D - 1:100 scale model is described and it was used to perform an experimental observation of the phenomenon. The model was built by using a 3D printer which allowed to include more architectural details of the real scenario. The inclusion of these details allowed to observe qualitative similarity between the results of the simulation and the experimental work. Although there are clear differences between what could happen in a real scenario and what was observed in the scale model, it was identified that the model is an important complement to the simulations. In addition to the simulations, the use of this type of 3D models allows the observation of the phenomenon by different specialists such as firefighters, policeman, medical personnel, etc., in the same place and its intention is to provide a more interactive tool to the observation group, increasing the time devoted to the development of contingency actions and reducing the costs associated with the logistics of a real simulacrum. The model allows to better identify the strengths, opportunities, weaknesses and threats of the contingency procedures developed by the safety and hygiene groups and to make their corresponding adjustments if necessary.

One important challenge that faces the metallurgic industry turns around the constant increment in the mechanical resistance of certain finished products. Metallurgic advantages can be obtained from the inclusion of microparticles in metallic materials, but this inclusion involves complex challenges as the internal stress distribution can be modified. In this work, the simulation of a cooling sequence in 7075 aluminum with a SiO₂ microparticle is presented. Two models of two-dimensional (2D) type were constructed in ANSYS^®2019 with circular and oval shape microparticles located inside the aluminum. Both models were subjected to the same thermomechanical transient analysis to compare the remaining stress distributions around the microparticles after the thermal load and to observe the effect of the geometrical shape. The results show remaining stresses increased in the oval model as a consequence of the geometrical shape modification. After applying a tension load in the analyzed specimens, shear stress concentrations were observed with a higher magnitude around the covertex of the oval shape. The results can be very useful for the creation of materials with controlled remnant stress located in specific or desired locations in the matrix.