Facultad de Ingeniería - CampCM

City

Ciudad de México

Country

Director

Hiram Eredi Ponce Espinosa

Parent Organisation

Campus Ciudad de México

OrgUnit's Publications

Now showing 1 - 10 of 978

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Preface
(Springer Science and Business Media Deutschland GmbH, 2026)
Martinez-Villaseñor, Lourdes
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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
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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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Sistema de tele operación de robots móviles omnidireccionales con emulación háptica de los sentidos de la vista y el oído
(2010)
Aguilera Sánchez, José Antonio
;
Varona, Jorge
Maestría en Ciencias - Tesis presentada en UP Aguascalientes
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Multiobjective model to optimize charging station location for the decarbonization process in Mexico
(2025)
Ruiz Barajas, Francisco
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Olivares-Benitez, Elias
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Adrian Ramirez‐Nafarrate
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Rosa G. González‐Ramírez
<jats:title>Abstract</jats:title><jats:p>Electric vehicles (EVs) offer significant potential for advancing sustainable environmental goals. However, their widespread adoption has been concentrated in urban areas, raising challenges for interurban travel. In many countries, charging station networks are primarily located within cities, highlighting a key opportunity for expansion to support longer distance journeys. This article addresses the facility location problem for EV charging stations to enable interurban travel. We propose a multiobjective optimization model based on the flow refueling location model with three objectives: maximizing CO<jats:sub>2</jats:sub> emissions reduction, minimizing total costs, and reducing user charging time. The model is solved using an epsilon constraint approach, and Mexico's charging station network is used as a case study. Through computational experiments, various scenarios are evaluated, and a comparative analysis is performed between electric and internal combustion vehicles. Results show that deploying 20 strategically located charging stations could mitigate 3.1 million tons of CO<jats:sub>2</jats:sub>, requiring an investment of nearly USD 3.9 million.</jats:p>
37
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Cybernetic Insights on GenAI and Learning in Higher Education
(IEEE, 2026)
Salinas-Navarro, David Ernesto
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Vilalta-Perdomo, Eliseo
The rapid diffusion of Generative Artificial Intelligence (GenAI) is reshaping learning conditions, not by introducing new activities but by reorganising existing feedback structures among students, teachers, and learning environments. This study adopts a cybernetic perspective to explore how Gen AI influences the recursive processes of enquiry, collaboration, and reflection. Drawing on the concepts of feedback, adaptation, and regulation, this paper frames GenAI as an active participant in learning systems, redistributing agency, and reshaping the rhythm of interaction. A methodological guide is proposed for constructing case studies across disciplines, combining documentary artefacts and participant accounts to map the cybernetic dynamics in practice. A case study of a Quality Management module illustrates how GenAI reconfigures individual reflection, group collaboration, and assessment practices. This study contributes to cybernetic learning theory by showing how GenAI affects agency and feedback structures, and by providing a framework for designing ethical GenAI learning environments. This study acknowledges the limitations that future studies must address to examine student learning outcomes. The paper concludes by highlighting the research question: How does Gen AI reshape learning as a recursive cybernetic process? Scholars are invited to explore this in their own contexts in future studies. © The authors © IEEE.
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Optimización de proyectos bajo modelos de gestión
(2013)
Barajas Huerta, Jaaziel Daniel
4
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Multitarget Design of Steroidal Inhibitors Against Hormone-Dependent Breast Cancer: An Integrated In Silico Approach
(MDPI AG, 2025)
Rodríguez-Macías, Juan
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Saurith-Coronell, Oscar
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Vargas-Echeverria, Carlos
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Insuasty Delgado, Daniel
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Márquez Brazón, Edgar A.
Hormone-dependent breast cancer, particularly in its treatment-resistant forms, remains a significant therapeutic challenge. In this study, we applied a fully computational strategy to design steroid-based compounds capable of simultaneously targeting three key receptors involved in disease progression: progesterone receptor (PR), estrogen receptor alpha (ER-α), and HER2. Using a robust 3D-QSAR model (R2 = 0.86; Q2_LOO = 0.86) built from 52 steroidal structures, we identified molecular features associated with high anticancer potential, specifically increased polarizability and reduced electronegativity. From a virtual library of 271 DFT-optimized analogs, 31 compounds were selected based on predicted potency (pIC50 > 7.0) and screened via molecular docking against PR (PDB 2W8Y), HER2 (PDB 7JXH), and ER-α (PDB 6VJD). Seven candidates showed strong binding affinities (ΔG ≤ −9 kcal/mol for at least two targets), with Estero-255 emerging as the most promising. This compound demonstrated excellent conformational stability, a robust hydrogen-bonding network, and consistent multitarget engagement. Molecular dynamics simulations over 100 nanoseconds confirmed the structural integrity of the top ligands, with low RMSD values, compact radii of gyration, and stable binding energy profiles. Key interactions included hydrophobic contacts, π–π stacking, halogen–π interactions, and classical hydrogen bonds with conserved residues across all three targets. These findings highlight Estero-255, alongside Estero-261 and Estero-264, as strong multitarget candidates for further development. By potentially disrupting the PI3K/AKT/mTOR signaling pathway, these compounds offer a promising strategy for overcoming resistance in hormone-driven breast cancer. Experimental validation, including cytotoxicity assays and ADME/Tox profiling, is recommended to confirm their therapeutic potential. ©The authors ©MDPI.
15Scopus© Citations 4
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Vision-Based Autonomous Navigation with Evolutionary Learning
(2020)
Coronel, Sandra L.
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Moya-Albor, Ernesto
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Ponce, Hiram
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Brieva, Jorge
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Chávez Domínguez, Rodrigo
In this paper, we propose a vision-based autonomous robotics navigation system, it uses a bio-inspired optical flow approach using the Hermite transform and a fuzzy logic controller, the input membership functions were tuned applying a distributed evolutionary learning based on social wound treatment inspired in the Megaponera analis ant. The proposed method was implemented in a virtual robotics system using the V-REP software and in communication con MATLAB. The results show that the optimization of the input fuzzy membership functions improves the navigation behavior against an empirical tuning of them. © 2020, Springer Nature Switzerland AG.
1 9Scopus© Citations 2
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Integration of quality tools to define the scope of a Cubesat scientific/technology demonstration mission
(2021)
Zarate-Villazon, Ángel M.
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Espinosa, Erick
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Savage-Briz, Alejandra
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Sánchez-Henkel Moreno, Juan P.
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Laguna-Juárez, Carlos
Tailoring requirements based on the expectations of stakeholders is a complex task for any space mission. The typical stakeholder expectation definition process relies heavily on the stakeholders’ clear understanding of the necessity and impact of the potential design solution. Contrary to commercial missions, in which the customer has a better understanding of the requirements needed to satisfy their goals, in science and technology demonstration missions stakeholders only have a vague idea of the expected capabilities of the technology being developed. In fact, many of these missions are a pathfinder for the expected performance of future missions. This issue leads to uncertainty in the design, difficulty in establishing precise requirements and, consequently to unsatisfied stakeholders and failed objectives in the end. In this paper a method to coincide stakeholders expectations with the development of a science and technology mission from an early stage is presented. The method consists of the creation of a task force focused on understanding the problem presented by the stakeholders at greater depth. Afterwards, this task force works with the systems engineering team in the following analyses. First, a quality function deployment has been developed to determine the importance of certain features and requirements in the design in regards to that problem. Also, a Pareto diagram has been created to focus the design effort into the issues that have greater significance to the stakeholders. The feedback from this task force has enabled the systems engineering team to assess the risks in a better informed way. These changes have helped the team to agilize the decision making process and added certainty about the direction of the design alignment so it can fulfill stakeholders’ expectations. Moreover, it ensures that the mission has the maximum possible value for the stakeholder’s objectives, due to the fact the task force’s main objective is to study in greater depth the problem presented by them. This method has been tested within the development of a 3U Cubesat for the study of atmospheric density using electric propulsion designed and built by undergraduate students. The method proposed provides value in two of the most important aspects in spacecraft development: it ensures that the spacecraft is developed according to stakeholders’ expectations and reduces the time consumed in the process of capturing these expectations by all the technical team, which can be significant when these are not absolutely clear.
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Branding interno en una empresa de servicios en México
(2020)
Terán-Bustamante, Antonia
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Martínez Velasco, Antonieta Teodora
El objetivo de la presente investigación es analizar los procesos de branding interno de una empresa de servicios del conocimiento en México, de manera que estos permitan fortalecer sus ventajas competitivas a través del liderazgo de su capital humano. Lo anterior se logra a través de dilucidar si la capacitación y motivación hacia la marca influyen positivamente en el desempeño de esta. La estrategia metodológica es de tipo cuantitativo a través de herramientas estadísticas y de machine learning. La evidencia muestra que la alineación por parte de los empleados con los valores de la marca muestra un impacto positivo y significativo con su motivación a favor de la marca y el desempeño de esta. Los factores más significativos dentro de la dimensión de compromiso es el binomio capacitación y liderazgo de los jefes.
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Facultad de Ingeniería - CampCM

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