Facultad de Ingeniería - CampCM

City
Ciudad de México
Country
MX
Director
Hiram Eredi Ponce Espinosa
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    Mapping the Antibiofilm Peptide Space with Similarity Networks and Curated Negative Sets
    (American Chemical Society (ACS), 2025)
    Castillo-Mendieta, Kevin
    ;
    Marrero Ponce, Yovani  
    ;
    Márquez, Edgar A.
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    García-Giménez, José Luis
    ;
    Antunes, Agostinho
    Biofilm-forming microorganisms pose a growing threat in clinical and industrial settings due to their tolerance to conventional antimicrobials. Antibiofilm peptides (ABFPs) offer a promising alternative, yet their discovery is challenging due to sequence diversity and complex mechanisms of action. We present the most comprehensive curated ABFP dataset to date and systematically compare it against two negative sets: quorum sensing peptides (QSPs) and random peptides (RPs). Classical statistical analyses combined with alignment-free similarity networks─Chemical Space Networks (CSNs) and Half-Space Proximal Networks (HSPNs)─identified compositional and physicochemical features that distinguish ABFPs from negative sets. Integration of quantitative biofilm inhibition (MBIC) and eradication (MBEC) data enhanced the resolution of meaningful patterns in the antibiofilm chemical space. Network analyses revealed conserved ABFP-enriched clusters with bioactivity data, distinctive motifs absent in negative sets, and central peptides with high topological importance that may serve as scaffolds for developing potent antimicrobials. QSPs and RPs, as biologically distinct comparators, served as robust filters refining ABFP signatures and reducing false positives. Projection onto the HSPN confirmed that ABFPs occupy a unique and well-defined region of sequence space. This integrative framework─combining curated datasets, compositional profiling, and network topology─provides a practical platform to accelerate ABFP discovery by identifying key features that can be incorporated into rule-based filters for prioritizing promising candidates. © 2025 The Authors. Published by American Chemical Society.
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    Research ecosystem 2025
    (Universidad Panamericana, 2025)
    Llergo Bay, María Guadalupe Fernanda  
    ;
    Velázquez Rodríguez, Sergio
    ;
    Reyes Moreno, Antonio de los
    ;
    Mendoza, Abraham  
    ;
    García Álvarez, Santiago  
    Dear campus members, It is with great satisfaction that we present our Research Ecosystem 2025, a publication that reflects the sustained growth and strategic maturation of research at Universidad Panamericana. This edition builds on an increasingly comprehensive vision of university research, one in which technology transfer and innovation, institutional funding for research, and international rankings positioning affirm themselves as complementary pillars of our scientific activity. Our scientific production maintains its commitment to quality, with more than 50% of our indexed publications appearing in high-impact Q1 and Q2 journals. This year’s report also introduces, for the first time, a dedicated section on copyright and industrial models alongside patents, reflecting the growing diversity and maturity of our intellectual property portfolio, now spanning areas as varied as aeronautics, semiconductor technology, healthcare devices, and sustainable materials. © Universidad Panamericana.
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    Preface
    (Springer Science and Business Media Deutschland GmbH, 2026)
    Martinez-Villaseñor, Lourdes  
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    Transparency as a moderator of the relationship between web-scraping awareness and privacy-protective behavior: a quasi-experimental onboarding study
    (Frontiers Media SA, 2026)
    Betancourt-Barrita, Cecilia
    ;
    Berumen-Glinz, Lorena Alexandra  
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    Cal Y Mayor Peña, Francisco
    ;
    Escobar Castillejos, David  
    Introduction: Automated data collection practices, such as web scraping, are widely used for personalization on interactive platforms, and they raise recurring questions about privacy, transparency, and user trust. Prior work has examined these constructs separately. Less is known about whether transparency in onboarding disclosures is associated with a weaker relationship between awareness of automated data collection and privacy-protective behavior. This study examines the relationship between privacy-protective behavior and user trust in a simulated social media environment.Methods: A quantitative, between-subjects, scenario-based quasi-experimental survey was conducted with 325 participants. The study employed a simulated Instagram onboarding scenario with two transparency conditions: low and high. Privacy-related outcomes were operationalized as two binary privacy-protective behaviors (adjusting privacy settings and refusing to use a platform), summed into a behavior index that takes integer values of 0, 1, or 2. Additional measures assessed web-scraping awareness, user trust, perceived transparency, and control variables related to social media use and privacy sensitivity. Hypotheses were tested using ordinary least squares regression for the behavior index and continuous outcomes, and logistic regression for each binary behavior, including an interaction term to examine the moderating effect of the transparency condition.Results: Greater awareness of web scraping was associated with a higher likelihood of low-barrier privacy-protective behavior, particularly adjusting privacy settings. The transparency condition was associated with a weaker awareness–behavior relationship, consistent with the proposed moderation model. In contrast, the privacy-protective behavior index did not significantly predict user trust in the platform.Discussion: The findings are consistent with transparency operating as a contextual buffer of the link between awareness of automated data collection and privacy-protective behavior, rather than as a direct antecedent of trust. Because condition assignment was self-selected and baseline awareness differed across conditions, the results are interpreted as conditional associations within a simulated onboarding context rather than as causal effects. The results inform the design of onboarding disclosures in AI-driven platforms. © The authors © Frontiers in Computer Science.
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      2
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    Non-Contact Respiratory Rate Estimation in Newborns During Quiet Sleep Using Video Magnification Techniques and a 3D Convolutional Neural Network
    (IEEE, 2024)
    Escobedo Gordillo, Andrés Emiliano
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    Rivas-Scott, Orlando Yael
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    Brieva, Jorge  
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    Moya-Albor, Ernesto  
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    Cabon, Sandie
    In this paper, we present a new non-contact strategy to estimate the respiratory rate (RR) in a neonatal intensive care unit (NICU) based on the Eulerian motion video magnification technique and a 3D Convolutional Neural Network (3D CNN). The magnification procedure was carried out using the Hermite decomposition. The RR is estimated using a 3D CNN and a region of interest (ROI) detected manually. We have tested the method on 8 infants in NICU during quiet sleep. A contact respiratory signal is acquired synchronously to the videos to compute the RR as reference for training the CNN. To compare the performance of the method, we compute the Mean Absolute Error, the Root Mean Squared Error and metrics from the Bland and Altman analysis to investigate the agreement of the method with respect to the respiratory signal reference. The proposed solution shows an agreement with respect to the reference of 95% and root mean squared error of 2.88. ©The authors ©IEEE.
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    Data-Driven Innovation for Intelligent Technology : Perspectives and Applications in ICT
    (Springer Cham, 2024)
    Ponce, Hiram  
    ;
    Brieva, Jorge  
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    Lozada Flores, Octavio  
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    Martinez-Villaseñor, Lourdes  
    ;
    Moya-Albor, Ernesto  
    This book focuses on new perspectives and applications of data-driven innovation technologies, applied artificial intelligence, applied machine learning and deep learning, data science, and topics related to transforming data into value. It includes theory and use cases to help readers understand the basics of data-driven innovation and to highlight the applicability of the technologies. It emphasizes how the data lifecycle is applied in current technologies in different business domains and industries, such as advanced materials, healthcare and medicine, resource optimization, control and automation, among others. This book is useful for anyone interested in data-driven innovation for smart technologies, as well as those curious in implementing cutting-edge technologies to solve impactful artificial intelligence, data science, and related information technology and communication problems. ©Springer. ©The authors. ©The editors
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    Evaluating user perception and satisfaction in a digital platform designed for executive function assessment: a user-centered evaluation of Bloom 2.0 in higher education
    (Frontiers Media SA, 2026-06-12)
    Atristain-Suárez, Connie  
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    Martínez-Orozco, Elizabeth
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    Escobar Castillejos, David  
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    Paipa-Galeano, Luis A.
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    García-Becerra, Andrea Milena
    Introduction Digital platforms are increasingly used in higher education to deliver content, assess learning, and measure complex cognitive processes such as executive functions. Although the DeLone and McLean information systems success framework has been widely applied to e-learning platforms, empirical evidence on user-centered evaluation of digital cognitive assessment tools in higher education remains limited. Methods The study evaluated Bloom 2.0, a web-based platform that administers six executive function tasks: Tower of Hanoi (3-disc and 4-disc), Raven’s Progressive Matrices, Stroop, Token Test, and the Wisconsin Card Sorting Test. Sixty-four undergraduate students from Universidad Panamericana (Mexico City) completed the full six-task battery in March 2026. Of these, 55 also responded to a 15-item Spanish adaptation of Doll and Torkzadeh’s End-User Computing Satisfaction (EUCS) survey and two open-ended prompts. Data were analyzed using descriptive statistics, Cronbach’s α , and inductive thematic coding of open-ended responses. Results Overall satisfaction was high ( M = 4.28 , S D = 0.91 on a 1–5 scale), with 81.0% of responses rated 4 or 5. Internal consistency was high (Cronbach’s α = 0.936 for the full scale; α = 0.749 – 0.874 across dimensions). Accuracy was the highest-rated EUCS dimension ( M = 4.39 ), whereas Content received the lowest mean rating ( M = 4.20 ). Open-ended responses yielded six themes, with instruction clarity the most frequent (58%). The remaining themes were overall positive comments, interface and visual design, cognitive fatigue during the Raven task, the closing and feedback experience, and anxiety related to visible timers or error counters. Discussion Bloom 2.0 was usable in this undergraduate sample and produced internally consistent satisfaction responses. The findings address users’ perceptions of system quality and satisfaction and do not constitute psychometric validation of the underlying cognitive tasks. No criterion or convergent validity was evaluated against a clinician-administered reference battery in this study. The main issues were related to task instructions, interpretation of feedback, and usability elements associated with task guidance. The next version should revise task instructions, improve the closing feedback screen, and recalibrate task cutoffs before the platform is compared with a clinician-administered reference battery.
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    A visuo-haptic simulator for understanding magnetic forces for engineering majors
    (ICERI, 2024)
    Neri-Vitela, Luis
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    Robledo-Rella, Víctor
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    Noguez, Julieta
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    Escobar Castillejos, David  
    ;
    Gonzalez-Nucamendi, Andres
    According to the embodied cognition theory, adding extra sensory channels for user interaction with an online learning scenario can improve understanding and long-term retention of physical phenomena. In this regard, the implementation of visuo-haptic simulators (VHSs), which integrate touch into a visual simulator, may enhance users' learning experiences by allowing them to manipulate objects and feel forces realistically. Haptic technology and VHSs have been used for training in various fields like surgery, navigation, and industrial applications. In education, VHSs have also been applied to explain physics concepts from elementary to undergraduate levels. Our research group has consistently applied a methodology to develop VHSs for undergraduate engineering students over several years, called VIS-HAPT. Using this methodology, several VHSs have been developed to explain physics concepts, such as electric forces between different charge distributions, friction forces exerted by a surface on a block, and the buoyant force on an object immersed in a liquid. In this project, we introduce a new VHS designed to clarify the nature of magnetic forces, a challenging concept for our students. This VHS features a fixed long straight conducting wire and a rectangular conducting loop in the same plane, with one side of the loop parallel to the wire. Users can adjust parameters like the magnitude and direction of currents in the wire and loop, the distance between them, and the loop's dimensions, and perceive the corresponding effects on the magnetic force exerted by the wire on the loop. Through the haptic feedback provided by the VHS students can feel the strength of this force, perceive its direction, and simultaneously visualize its value on the screen, enhancing their learning experience. The VHS was tested with 117 junior undergraduate engineering students at Tecnologico de Monterrey, Mexico City Campus, during the February-June 2024 term. To study the impact of the VHS on students’ learning, the student sample was randomly divided into an experimental group (N = 81), who used the VHS, and a control group (N = 36) who did not. Guided by detailed instructions, experimental students conducted several practices to explore the magnetic force by adjusting the physical parameters of the VHS. In a parallel way, control students received more traditional lecture-based instruction. A feedback perception questionnaire about the VHS experience was administered to the experimental students. The results show that most experimental students expressed a very positive opinion on their interaction with the VHS and found it user-friendly, motivating, realistic, and helpful in understanding magnetic forces. Additionally, by administering identical pre-tests and post-tests instruments to both experimental and control groups, learning gains were calculated for both student groups. The preliminary results are promising, in the sense that the average learning gains for the experimental students was larger than the one for the control students. The statistical significance of this result is discussed. Overall, the results of this work suggest that the use of the magnetic force VHS, complemented with appropriate learning strategies, can improve students' understanding and retention of electromagnetic concepts better than only applying traditional instruction methods. ©ICERI2024 Proceedings ©The authors.
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