• Identification of material properties using nanoindentation and surrogate modeling

      Li, Han; Gutierrez, Leonardo; Toda, Hiroyuki; Kuwazuru, Osamu; Liu, WenliHangai, Yoshihiko; Kobayashi, Masakazu; Batres Prieto, Rafael; Tecnologico de Monterrey (Elsevier, 2016)
      In theory, identification of material properties of microscopic materials, such as thin film or single crystal, could be carried out with physical experimentation followed by simulation and optimization to fit the simulation result to the experimental data. However, the optimization with a number of finite element simulations tends to be computationally expensive. This paper proposes an identification methodology based on nanoindentation that aims at achieving a small number of finite element simulations. The methodology is based on the construction of a surrogate model using artificial neural-networks. A sampling scheme is proposed to improve the quality of the surrogate model. In addition, the differential evolution algorithm is applied to identify the material parameters that match the surrogate model with the experimental data. The proposed methodology is demonstrated with the nanoindentation of an aluminum matrix in a die cast aluminum alloy. The result indicates that the methodology has good computational efficiency and accuracy.
    • IGF-1 modulates gene expression of proteins involved in inflammation, cytoskeleton, and liver architecture

      Rocio García De la Garza; Gabriel Amador Aguirre; Irene Martín Del Estal; Mariano García-Magariño Alonso; María Inmaculada Castilla de Cortázar Larrea; Víctor Javier Lara Díaz; Luis Alonso Morales Garza
    • Impelling research productivity and impact through collaboration: a scientometric case study of knowledge management

      Ceballos, Hector G.; Fangmeyer Jr, James Andrew; Galeano Sánchez, Nathalíe M.; Juarez, Erika; Cantú Ortíz, Francisco J.; Tecnologico de Monterrey (Palgrave Macmillan, 2017-07-11)
      A case study for impelling university research productivity and impact through collaboration is presented. Scientometric results support the hypothesis that a knowledge management model increased research collaboration and thereby boosted a university’s number of publications and citations. Results come from fifteen years of data at a Mexican university with 2400 researchers who produced 24,000 works in fifteen research disciplines. These data are treated with social network visualizations and algorithms to identify patterns of collaboration and clustering, as well as with normalizations to make disciplines comparable and to verify increasing citation impact. The knowledge management model implemented in the study may be a costeffective way for universities to intensify collaboration and improve research performance.
    • Implementación del ABP como método para promover competencias de colaboración en un ambiente virtual

      Rivera Vázquez, Nohemi; Agudelo Quiroz, Adriana M.; Ramos Arcos, Xitlali M.; Vargas Mateus, Jackeline C. (2015-07-09)
    • Importance of molecular interactions in colloidal dispersions

      ARMANDO GAMA GOICOCHEA;26327; ARMANDO GAMA GOICOCHEA;26327
    • In-service teachers’ self-perceptions of digital competence and OER use as determined by a xMOOC training course

      Ramírez-Montoya, María-Soledad; Mena, Juanjo; Rodríguez-Arroyo, José A.; Matthieu Guitton; Tecnologico de Monterrey (Elsevier, 2017-09)
      Digital Competence (DC) is considered a driver for educational innovation since its immediate result is the production of new digital media resources for teaching such as Open Educational Resources (OER). This study aims to determine teachers' DC through their participation in a MOOC training course and establish the extent to which DC better enables the production of OER. A group of 863 in-service teachers participated in the study. A 26-item validated questionnaire on DC and the use of OER was delivered to participants, and course facilitators' weekly reports were collected. An ordinal logarithmic regression was conducted to verify whether teachers who hold positive self-perceptions of DC are more prone to using OER in their teaching. Mean differences between traditional teaching and online teaching were also tested. Reports were content analysed using a SWOT matrix. Our model predicts that only in-service teachers that perceive themselves as digital experts can reach an intermediate level in the production of OER. Furthermore, online teaching significantly favours teachers' DC but is highly significant in OER production. The main implication is that training teachers' DC is required to prepare teachers for the use of OER; however, teacher education should first address teachers’ actual level of performance.
    • Incidencia de los estilos de aprendizaje en el aprovechamiento académico de los alumnos de comunicación utilizando el Ipod

      Hernández Núñez, José A.; Tamez Herrera, Claudia; Lozano Rodríguez, Armando (2013-11-06)
    • Increase of productivity through the study of work activities in the construction sector

      Natella Antonyán; Imelda de Jesús Loera Hernández; Gerardo Espinosa Garza
    • Indicators of pedagogical quality for the design of a Massive Open Online Course for teacher training

      Gómez Zermeño, Marcela G.; Sancho-Vinuesa, Teresa; Alemán de la Garza, Lorena Y.; Tecnologico de Monterrey (Springer Open, 15/01/2015)
      Abstract Massive Open Online Courses (MOOCs) have generated high expectations and revolutionized some educational practices by providing open educational resources for reference, usage and adaptation; therefore, their pedagogical quality is often questioned. The objective of this study is to identify indicators related to pedagogical, functional, technological and time factors in order to assess the quality of the MOOC entitled “Liderazgo en gestión educativa estratégica a través del uso de la tecnología” (Leadership in strategic educational management through the use of technology), offered as a teacher training program through Coursera to 10.161 participants. Via the Delphi method, a group of 55 experts agreed that time is a key factor to be considered in the design of learning activities. It was concluded that without measuring results, the success of a MOOC could not be evaluated; thus, institutions and consortia must establish evaluation indicators to focus their efforts on the enhancement of pedagogical quality. By providing relevant information, the learning potential of educational resources based on connectivism principles can be evaluated, and so can the quality of MOOCs. The goal is to contribute to a vision of a future in which everyone has access to a world-class education.
    • Inferring modules of functionally interacting proteins using the Bond Energy Algorithm

      Watanabe, Ryosuke L.; Morett, Enrique; Vallejo Clemente, Edgar E.; Tecnologico de Monterrey (Open Access Publisher, 2008-06-17)
      Abstract Background Non-homology based methods such as phylogenetic profiles are effective for predicting functional relationships between proteins with no considerable sequence or structure similarity. Those methods rely heavily on traditional similarity metrics defined on pairs of phylogenetic patterns. Proteins do not exclusively interact in pairs as the final biological function of a protein in the cellular context is often hold by a group of proteins. In order to accurately infer modules of functionally interacting proteins, the consideration of not only direct but also indirect relationships is required. In this paper, we used the Bond Energy Algorithm (BEA) to predict functionally related groups of proteins. With BEA we create clusters of phylogenetic profiles based on the associations of the surrounding elements of the analyzed data using a metric that considers linked relationships among elements in the data set. Results Using phylogenetic profiles obtained from the Cluster of Orthologous Groups of Proteins (COG) database, we conducted a series of clustering experiments using BEA to predict (upper level) relationships between profiles. We evaluated our results by comparing with COG's functional categories, And even more, with the experimentally determined functional relationships between proteins provided by the DIP and ECOCYC databases. Our results demonstrate that BEA is capable of predicting meaningful modules of functionally related proteins. BEA outperforms traditionally used clustering methods, such as k-means and hierarchical clustering by predicting functional relationships between proteins with higher accuracy. Conclusion This study shows that the linked relationships of phylogenetic profiles obtained by BEA is useful for detecting functional associations between profiles and extending functional modules not found by traditional methods. BEA is capable of detecting relationship among phylogenetic patterns by linking them through a common element shared in a group. Additionally, we discuss how the proposed method may become more powerful if other criteria to classify different levels of protein functional interactions, as gene neighborhood or protein fusion information, is provided.
    • Inflammation following acute myocardial infarction: Multiple players, dynamic roles, and novel therapeutic opportunities

      Ong S.-B.; Hernández-Reséndiz S.; Crespo-Avilan G.E.; Mukhametshina R.T.; Kwek X.-Y.; Cabrera-Fuentes H.A.; Hausenloy D.J.
    • Influence of PEEK Coating on Hip Implant Stress Shielding: A Finite Element Analysis

      Eduardo Alejandro Flores Villalba; Héctor Rafael Siller Carrillo; José Antonio Díaz Elizondo; Oscar Martínez Romero; Ciro Angel Rodríguez González