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Permanent URI for this collectionhttps://hdl.handle.net/11285/345284
Artículo científico o editorial en una publicación periódica académica sujeto a revisión de pares. Cumple con los índices internacionales o bases de datos de amplia cobertura, como el listado del Current Contents, ISI WEB of Knowledge (http://isiknowledge.com/) e índice de revistas mexicanas de CONACYT (www.conacyt.mx/dac/revistas). Éstos indizan y resumen los artículos de revistas seleccionadas, en todas las áreas del saber.
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- Computational shape design optimization of femoral implants: towards efficient forging manufacturing(MDPI, 2024-09) Tuninetti, Víctor; Fuentes, Geovanni; Oñate Soto, Angelo Giovanni; Narayan X, Sunny; Celentano, Diego; García Herrera, Claudio; Menacer, Brahim; Pincheira, Gonzalo; Garrido, César; Valle, Rodrigo; Department of Mechanics and Advanced Materials, Campus Monterrey, School of Engineering and Sciences, Tecnológico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Tecnológico, 64849 Monterrey, N.L., Mexico; https://ror.org/04v0snf24; https://ror.org/0460jpj73; https://ror.org/03ayjn504; https://ror.org/04teye511; https://ror.org/02ma57s91; https://ror.org/023rr0h32; https://ror.org/01s4gpq44; https://ror.org/04dndfk38; NARAYAN, ROGERTotal hip replacement is one of the most successful orthopedic operations in modern times. Osteolysis of the femur bone results in implant loosening and failure due to improper loading. To reduce induced stress, enhance load transfer, and minimize stress, the use of Ti-6Al-4V alloy in bone implants was investigated. The objective of this study was to perform a three-dimensional finite element analysis (FEA) of the femoral stem to optimize its shape and analyze the developed deformations and stresses under operational loads. In addition, the challenges associated with the manufacturing optimization of the femoral stem using large strain-based finite element modeling were addressed. The numerical findings showed that the optimized femoral stem using Ti-6Al-4V alloy under the normal daily activities of a person presented a strains distribution that promote uniform load transfer from the proximal to the distal area, and provided a mass reduction of 26%. The stress distribution was found to range from 700 to 0.2 MPa in the critical neck area of the implant. The developed computational tool allows for improved customized designs that lower the risk of prosthesis loss due to stress shielding.
- Assessing antioxidant and pour point depressant capacity of turmeric rhizome extract in biolubricants(MDPI, 2024-08-07) Joseph, Samuel; Kaisan, Muhammad Usman; Sanusi, Yinka Sofihullahi; Narayan X, Sunny; Menacer, Brahim; Valenzuela, Marian; Salas Burgos, Alexis; Oñate Soto, Angelo Giovanni; Mahroogi, Faisal Omar; Tuninetti, Víctor; Department of Mechanics and Advanced Materials, Campus Monterrey, School of Engineering and Sciences, Tecnológico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Tecnológico, Monterrey 64849, Mexico; https://ror.org/007tbc964; https://ror.org/019apvn83; https://ror.org/03ayjn504; https://ror.org/023rr0h32; https://ror.org/04v0snf24; https://ror.org/0460jpj73; https://ror.org/03rcp1y74; Rahnejat, HomerNatural polyphenols found in plants are secondary metabolites and act as natural antioxidants. Phenols prevent lipid oxidation by donating their hydrogen to free radicals generated between reactions of oxygen with unsaturated fatty acids. This work aims to examine turmeric extract for its capacity to act as an antioxidant and pour point depressant additive in biolubricants. The study involved extracting turmeric rhizome and analyzing the extract using the gas chromatography-mass spectrometry (GC-MS) and Fourier-transform infrared spectroscopy (FTIR) techniques to identify phenolic compounds and the nature of bonds in terms of abundance peak areas. The yield of concentrated turmeric rhizome extract by weight was 3.7%. The FTIR analysis revealed O-H band at 3336 cm−1, C-H asymmetric and symmetric stretching at 2940 and 2834 cm−1, C=C cyclic ring at 1680–1515 cm−1. The phenols detected by the GC-MS technique are phenol, 2 -methoxy-3-(2-propenyl) occupying 36.3% area at 16.5 min retention time and Phenol, 2-methoxy-4-(2-propenyl)-, acetate having 3.8% area at 3.8 min retention time. The results show promising capacity of turmeric rhizome extract to act as antioxidant and pour point depressant additive in biolubricants.
- The level of happiness and Its relationship with personal and occupational well-being in women leaders at a mexican university: an exploratory study(MDPI, 2024-08-06) Ortiz Meillón, Viviana; Guerra Leal, Eva María; Vázquez Parra, José Carlos; https://ror.org/03ayjn504This exploratory study aims to identify the state of well-being of a select group of women leaders in a Mexican university by analyzing the relationship between their perception of happiness and their satisfaction with their life and work. Through the application of a psychometric battery, this work examined how these leaders manage their well-being within an environment that is simultaneously empowering and demanding. Methodologically, a descriptive statistical analysis was performed, including a correlation analysis of all items. As a result, the research identified positive correlations between the variables age and positive perceptions of work and life, which are strongly associated with high personal and professional satisfaction. In addition, people who find their work rewarding and feel that their life is close to their ideal tend to be more satisfied in general. Although this study intended to be exploratory, it also sought to contribute a deeper understanding of the well-being status of women in university leadership positions in Mexico. In doing so, it filled an important gap in the literature on gender, leadership, and well-being in Latin American academia by highlighting the complexity of managing and supporting women in leadership positions.
- Importance of university students’ perception of adoption and training in artificial intelligence tools(MDPI, 2024-08-03) Vázquez-Parra, José Carlos; Henao Rodríguez, Diana Carolina; Lis Gutiérrez, Jenny Paola; Palomino Gámez. Sergio; https://ror.org/03ayjn504Undoubtedly, artificial intelligence (AI) tools are becoming increasingly common in people’s lives. The educational field is one of the most reflective on the importance of its adoption. Universities have made great efforts to integrate these new technologies into their classrooms, considering that every future professional will need AI skills and competencies. This article examines the importance of student perception and acceptance in adopting AI tools in higher education effectively. It highlights how students’ positive perceptions can significantly influence their motivation and commitment to learning. This research emphasizes that to integrate AI into university curricula successfully, it is essential to include its technologies in all areas of study and foster positivity among students regarding their use and training. This study’s methodology applied the validated instrument “Perception of Adoption and Training in the Use of Artificial Intelligence Tools in the Profession” to a sample of Mexican students. This exploratory analysis highlights the need for educational institutions to understand and address student perceptions of AI to design educational strategies that incorporate technological advances, are pedagogically relevant, and align with the students’ aspirations and needs.
- Simulation of vacuum distillation unit in oil refinery: Operational strategies for optimal yield efficiency(MDPI, 2024-08-02) Muhammad, Shahrukh Atta; Haris, Khan; Muhammad, Ali; Rasikh, Tariq; Ahmed Usman, Yasir; Muhammad Mubashir, Iqbal; Sullah Ud, Din; Jaroslaw, Krzywanski; https://ror.org/040gykh71; https://ror.org/048g2sh07; https://ror.org/03ayjn504; https://ror.org/0566yhn94Oil refineries play a crucial role in meeting global energy demands, and optimizing the efficiency of critical processes is vital for economic feasibility and environmental sustainability. Simulation is an essential tool for the optimization of valuable products. This work presents the rigorous simulation of a vacuum distillation unit (VDU) based on actual data from the vacuum distillation processes using Aspen HYSYS V10. The Peng–Robinson fluid package is used in this simulation, and an input assay with a standard density of 29 API_60 (879.8 kg/m3) is employed. True boiling point (TBP) assay data are the type that is being used. Methane, ethane, propane, i-Butane, n-Butane, i-Pentane, and n-Pentane are the components listed in the simulation. The research determines that achieving a yield capacity of 685 tons/h requires thirty stages in the atmospheric distillation unit and twelve stages in the vacuum distillation unit while operating at 420 °C temperature and 9 kPa pressure. Adjustments in the flash section temperature (FST) and steam flow rate (SFR) are proposed to enhance operational efficiency. Increasing the FST from 370 °C to 400 °C and adjusting SFR from 10 tons/h to 26 tons/h increases the Light Vacuum Gas Oil (LVGO) yield by 7.2% while elevating the FST from 400 °C to 430 °C and adjusting SFR from 10 tons/h to 26 tons/h enhances the High Vacuum Gas Oil (HVGO) yield by 7.4%. These optimization strategies offer a practical and effective approach for refineries to improve the economic benefits of vacuum distillation units. The implications of this research can act as a computational thinking exercise for higher education students considering the case study where only through changing the operational strategies can the yield be enhanced by 10.81% in the vacuum distillation unit of the oil refinery.
- Efficient mako shark-inspired aerodynamic design for concept car bodies in underground road tunnel conditions(MDPI, 2024-07-24) Venegas, Ignacio; Oñate Soto, Angelo Giovanni; Pierart Vásquez, Fabián Gonzalo; Valenzuela, Marian; Narayan X, Sunny; Tuninetti, Víctor; Department of Mechanics and Advanced Materials, Campus Monterrey, School of Engineering and Sciences, Tecnológico de Monterrey, Av. Eugenio Garza Sada 2501 Sur, Tecnológico, Monterrey 64849, Nuevo León, Mexico; https://ror.org/04dndfk38; https://ror.org/0460jpj73; https://ror.org/04v0snf24; https://ror.org/03ayjn504The automotive industry continuously enhances vehicle design to meet the growing demand for more efficient vehicles. Computational design and numerical simulation are essential tools for developing concept cars with lower carbon emissions and reduced costs. Underground roads are proposed as an attractive alternative for reducing surface congestion, improving traffic flow, reducing travel times and minimizing noise pollution in urban areas, creating a quieter and more livable environment for residents. In this context, a concept car body design for underground tunnels was proposed, inspired by the mako shark shape due to its exceptional operational kinetic qualities. The proposed biomimetic-based method using computational fluid dynamics for engineering design includes an iterative process and car body optimization in terms of lift and drag performance. A mesh sensitivity and convergence analysis was performed in order to ensure the reliability of numerical results. The unique surface shape of the shark enabled remarkable aerodynamic performance for the concept car, achieving a drag coefficient value of 0.28. The addition of an aerodynamic diffuser improved downforce by reducing 58% of the lift coefficient to a final value of 0.02. Benchmark validation was carried out using reported results from sources available in the literature. The proposed biomimetic design process based on computational fluid modeling reduces the time and resources required to create new concept car models. This approach helps to achieve efficient automotive solutions with low aerodynamic drag for a low-carbon future.
- The use of socioscientific issues in science lessons: a scoping review(MDPI, 2024-07-09) Viehmann, Cristina; Fernández Cárdenas, Juan Manuel; Reynaga Peña, Cristina Gehibie; Tecnológico de Monterrey; https://ror.org/03ayjn504; Rocha dos Reis, Pedro GuilhermeSocioscientific issues represent an innovative approach within the realm of STEM education as they integrate real-world problems, promote critical thinking, and encourage interdisciplinary learning, thus preparing students to address complex societal challenges through scientific inquiry. The objective of this scoping review was to analyze the use of SSIs in science lessons. A database search of Web of Science and Scopus focused on articles published between 2013 and 2023. When applying the inclusion and exclusion criteria, a total of 106 articles were selected. The scoping review revealed a focus on socioscientific issues within high school and undergraduate curricula, particularly pertaining to environmental, genetic, and health-related concerns, as well as localized SSIs. A variety of methodological approaches, predominantly qualitative, were applied to capture the educational dynamics of integrating socioscientific issues into pedagogy. Inquiry-based learning emerges as a preferred pedagogical model, stimulating student engagement with real societal challenges. The educational resources employed encompass both conventional texts and digital tools, such as data mapping and visualization software, facilitating a multifaceted comprehension of SSIs. Pedagogical techniques are diverse, incorporating argumentation, role-playing, and digital media to enrich the teaching and learning experience. Nevertheless, the incorporation of socioscientific issues faces obstacles, including resistance to pedagogical innovation, the inherent complexity of the topics, and the demand for specialized teacher training.
- Effectiveness of using ChatGPT as a tool to strengthen benefits of the flipped learning strategy(MDPI, 2024-06-18) Huesca Juárez, Gilberto; Martínez Treviño, Yolanda; Molina Espinosa, Jose Martín; Sanromán Calleros, Ana Raquel; Martínez Román, Roberto; Cendejas Castro, Eduardo Antonio; Bustos Gardea, Raime Alejandro; https://ror.org/03ayjn504In this study, we evaluate how ChatGPT complements and enriches the traditional flipped learning strategy in higher education, particularly in engineering courses. Using an experimental design involving 356 students from basic programming courses in undergraduate engineering programs, we compared the normalized learning gain between groups that used the ChatGPT-assisted flipped learning strategy (focus groups) and those that followed a traditional video-based flipped learning methodology (control groups). The intervention lasted ten weeks, with two sessions of two hours each week. A pre-test–post-test analysis revealed that the focus groups showed significant improvement in normalized learning gain values compared to the control groups. These results confirm that incorporating ChatGPT into the flipped learning strategy can significantly enhance student performance by providing a more active, interactive, and personalized approach during the teaching–learning process. We conclude that the flipped learning strategy, upgraded with the assistance of ChatGPT, provides an effective means to improve understanding and application of complex concepts in programming courses, with potential to be extended to other areas of study in higher education. This study opens routes for future research on the integration of artificial intelligence into innovative pedagogical strategies with the goal of scaffolding the learning experience and improving educational outcomes.
- Effectiveness of challenge-based learning in undergraduate engineering programs from competencies and gender perspectives(MDPI, 2024-02-29) Huesca Juárez, Gilberto; Rodríguez Rosales, Adriana; Lara Prieto, Vianney; Ruiz Cantisani, Maria Ileana; Acevedo Mascarúa, Joaquín; School of Engineering and Sciences, Tecnologico de Monterrey; https://ror.org/03ayjn504; Gamage, KelumActive learning strategies are widely studied, but perspective on their effectiveness in complete undergraduate studies or about their contribution to closing the gender gap are still required. Challenge-based learning has been around for more than a decade. However, results have been collected in limited time and application environments, for example, one semester or one activity in a course. In this work, we present a quantitative study that was applied to results of the National Center for the Evaluation of Higher Education’s Engineering Bachelor’s Degree Standardized General Examination of 4226 students comparing those who received a traditional educational model and those who received a challenge-based learning educational model. A statistical analysis of communication and disciplinary competencies found that the traditional educational model induces a greater marginal significant result in the test. Additionally, we found that female students perform better in communication competencies while male students perform better in disciplinary competencies. Our results confirm that challenge-based learning is as effective as a traditional educational model when applied during complete undergraduate studies while developing competencies like critical thinking, long-term retention, leadership, multidisciplinary teamwork, and decision-making. Challenge based learning is a prolific learning strategy for evolving into a new way of teaching in undergraduate programs.
- Integration of deep learning and collaborative robot for assembly tasks(MDPI, 2024-01-18) Mendez Meraz, Armando Enrico; Ochoa, Oscar; Olivera Guzman, David; Soto Herrera, Victor Hugo; Luna Sánchez, José Alfredo; Lucas Dophe, Carolina; Lugo del Real, Eloina; Ayala Garcia, Ivo Neftali; Alvarado Pérez, Miriam; González de Alba, Alejandro; Tecnologico de Monterrey; https://ror.org/03ayjn504Human–robot collaboration has gained attention in the field of manufacturing and assembly tasks, necessitating the development of adaptable and user-friendly forms of interaction. To address this demand, collaborative robots (cobots) have emerged as a viable solution. Deep Learning has played a pivotal role in enhancing robot capabilities and facilitating their perception and understanding of the environment. This study proposes the integration of cobots and Deep Learning to assist users in assembly tasks such as part handover and storage. The proposed system includes an object classification system to categorize and store assembly elements, a voice recognition system to classify user commands, and a hand-tracking system for close interaction. Tests were conducted for each isolated system and for the complete application as used by different individuals, yielding an average accuracy of 91.25%. The integration of Deep Learning into cobot applications has significant potential for transforming industries, including manufacturing, healthcare, and assistive technologies. This work serves as a proof of concept for the use of several neural networks and a cobot in a collaborative task, demonstrating communication between the systems and proposing an evaluation approach for individual and integrated systems.