Ciencias Exactas y Ciencias de la Salud
Permanent URI for this collectionhttps://hdl.handle.net/11285/551039
Pertenecen a esta colección Tesis y Trabajos de grado de las Maestrías correspondientes a las Escuelas de Ingeniería y Ciencias así como a Medicina y Ciencias de la Salud.
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- Assessment of Alzheimer's disease-related blood and urine biomarkers for wastewater-based epidemiological studies(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-11) Armenta Castro, A.; Aguilar Jiménez, Osear Alejandro; emimmayorquin; Montesinos Castellanos, Alejandro; Flores Tlacuahuac, Antonio; School of Engineering and Sciences; Campus Monterrey; de la Rosa Flores, Orlando DanielIncidence of Alzheimer's disease, the leading cause of dementia and the fifth cause of death among elderly patients, has been rapidly increasing in recent years due to continued demographic aging. However, access to diagnosis and adequate care remains limited, especially in low-to-middle income countries, leaving an approximate 41 million cases currently undiagnosed. Such limitations can crucially compromise the quality and availability of care that can be provided to those in need. Wastewater surveillance, which is based on the detection and quantification of biomarkers in wastewater samples, has emerged as a promising tool to assess public health in a time and resource-efficient manner, providing important information for public health authorities and healthcare providers when used in tandem with relevant socioeconomic data and clinical reports. While its potential for monitoring infectious diseases has been proven, efforts towards the integration of biomarkers of chronic and degenerative diseases into such surveillance platforms are still needed. This dissertation aims to evaluate the main biomarkers related to Alzheimer’s disease, including proteins, long non-coding RNAs, and oxidative stress biomarkers, for their integration into wastewater surveillance biomarkers. Moreover, machine learning-based algorithms to correlate the concentration of biomarkers in wastewater to the clinical reports of incidence of a disease were developed using SARS-CoV-2 surveillance in university campuses across Mexico as a relevant case study, to develop effective data analysis strategies to integrate wastewater surveillance data into epidemiological models that allow for public health risk assessment and forecasting. This dissertation contributes to the consolidation of wastewater surveillance as a tool for comprehensive public health risk assessment and data-driven decision-making by demonstrating a pipeline for the integration of new biomarkers into surveillance platforms and effective, easily-interpretable data integration.
- Desempeño de pastas y morteros base cemento portland compuesto con adiciones de relleno inerte de caliza(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-11) Méndez Páramo, Rafael Alfredo; Torres Acosta, Andrés Antonio; emimmayorquin; Crespo Sánchez, Saúl Enrique; Anaya Díaz, Miguel; Escuela de Ingeniería y Ciencias; Campus Monterrey; Herrera Soto, Eduardo SadótEsta tesis evalúa el desempeño que tienen las pastas y morteros a base de cemento portland compuesto cuando la adición es relleno inerte de caliza (RIC). Se analizaron 6 tipos de cemento. Uno de los seis cementos fue del tipo cemento portland ordinario (CPO) que se utilizó como control para ver el desempeño del cemento portland compuesto (CPC). Primeramente, se caracterizaron los polvos de éstos con base a tres parámetros (densidad, pérdida por ignición y finura). Después se fabricaron pastas con los mismos cementos para evaluar sus parámetros físicos (cantidad de agua para consistencia normal, tiempos de fraguado y la coordenada L*). Finalmente se fabricaron morteros con los mismos para evaluarlos mecánica, física y químicamente (contenido de agua para fluidez normal, resistencia a la compresión, resistividad eléctrica, y profundidad de carbonatación). Los morteros se evaluaron a los 3, 28, 56 y 90 días de curado. Dos series de especímenes se curaron por 28 días y después se colocaron a la intemperie para determinar el efecto del medio ambiente durante 150 y 335 días. Los resultados mostraron que a mayor RIC tenga un cemento, este tendrá densidades más bajas, necesita mayor cantidad de agua para alcanzar consistencia normal en pastas y fluidez normal en morteros. En pastas de cemento se observó que a mayor es el contenido del RIC, menores serán los tiempos de fraguado inicial y final, lo que implica que la caliza endurece más rápido la pasta de cemento. Se determinó que las pastas de cemento con mayor RIC alcanzaron mayores valores de la coordenada L*, lo que implica que a mayor RIC mayor la blancura de la pasta de cemento. Los resultados obtenidos con las mezclas de mortero demostraron que a mayor es el contenido de RIC, su resistencia es mayor a edades tempranas, sin embargo, a edades mayores esta resistencia se queda estanca y los morteros fabricados con bajos contenidos de RIC, aumentan su resistencia con la edad. No se encontró una tendencia marcada en los valores de resistividad eléctrica de los morteros evaluados en función del contenido de RIC. Para los morteros que se expusieron al ambiente natural urbano entre 150 y 335 días, se observó un efecto en detrimento en las propiedades mecánicas de los mismos: a mayor contenido de RIC, mayor fue la reducción en la resistividad eléctrica y en la resistencia a la compresión. Esto se determinó por que la resistividad eléctrica se redujo entre un 10% y un 15% en los morteros fabricados con altos contenido de RIC. Por otro lado, la resistencia a la compresión se redujo entre un 15% y un 30% luego de los 335 días de exposición natural al ambiente de Querétaro. Ambas características físicas del material se vieron afectadas debido a que se encontraron fisuras en la superficie de los cubos, producto aparentemente de las reacciones químicas entre material y ambiente de exposición, que regularmente posee CO2 y S02. Finalmente, se comprobó que la prueba de pérdida por ignición ayuda a determinar indirectamente el contenido de RIC del cemento, para de esta manera reducir las posibles afectaciones que podrían generar a materiales base cemento Portland (lechadas, morteros y concretos) diseñándolos, dependiendo del uso y ambiente al que será sometido durante su vida de servicio.
- Impact of Industry 4.0 on Small and Medium Enterprises: Evaluation of Maturity Indices and Implementation Methodologies(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-11) Delgado González, Jessica; Román Flores, Armando; emimmayorquin; Cuan Urquizo, Enrique; School of Engineering and Sciences; Campus Monterrey; Vázquez Hurtado, CarlosThe digital transformation driven by Industry 4.0 technologies is reshaping global economic and business paradigms. Small and medium-sized enterprises (SMEs) in Mexico, which represent 99.8% of the country's economic units and contribute over 52% to its GDP, face significant barriers such as limited financial resources, technological gaps, and cultural resistance. These constraints, highlighted in recent studies, underscore the need for tailored tools to support their digitalization efforts. This thesis develops a digital maturity model specifically adapted to Mexican SMEs, integrating practical tools such as an assessment framework and a step-by-step action plan. The study begins by analyzing the theoretical foundations of Industry 4.0 and existing digital maturity models while addressing challenges unique to SMEs. Building on this foundation, the proposed model evaluates SMEs' current digital maturity and provides actionable recommendations through a simulation applied to a representative SME. The results demonstrate the model’s utility in identifying areas for improvement, fostering innovation, and enhancing competitiveness and sustainability in a globalized market. This work contributes academically by adapting global models to local contexts and practically by offering a replicable framework to bridge the digital divide in this critical economic sector.
- Evaluation of the biological activity of wounding stress-treated carrots on the development of obesity and associated metabolic disorders(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-11) Castorena Ramírez, Mariana Denise; Jacobo Velázquez, Daniel Alberto; emimmayorquin; Chuck Hernández, Cristina Elizabeth; Licona Cassani, Cuauhtémoc; School of Engineering and Sciences; Campus Monterrey; Rabadán Chávez, Griselda MericiaAdipose tissue is a complex multicellular organ that serves as both an energy reservoir and an endocrine organ responsible for maintaining energy homeostasis through a set of integrated endocrine and metabolic responses. By storing and mobilizing energy as needed, adipose tissue supports metabolic balance. Similarly, the gut microbiota—a complex intestinal microbial ecosystem—plays a critical role in metabolic health, impacting obesity through lipid metabolism, energy extraction, and inflammation modulation. Postharvest wounding stress, a type of abiotic stress induced by cutting followed by a storage period, has been shown to significantly increase the total phenolic content in carrots, particularly chlorogenic acid (CHA). Given the antioxidant, anti-inflammatory, and anti-obesogenic effects of this dietary phytochemical, this study aimed to evaluate the effect of consuming carrots treated with wounding stress on diet-induced obesity (DIO) and associated metabolic disorders in rats. Male Wistar rats were fed a standard (SD) or hypercaloric diet (HD) supplemented with wounding stress-treated carrots (wsC) or nonstressed carrots (nsC) for 8 weeks. In HD-fed rats, daily consumption of 5 g of wsC (HDwsC) led to a significant decrease in body weight gain (18%) and total white adipose tissue (WAT) accumulation (9.7%) without changes in food or energy intake compared to the HD group. HD-wsC supplementation also improved fat mass distribution, with a significant increase in subcutaneous WAT (20%) and a decrease in visceral WAT (17.3%). These shifts in adipose tissue were consistent with improvements in lipid profiles, as the HD-wsC group showed increased HDL-c levels (40%) and reduced triglycerides (39%), total cholesterol (35%), LDL-c (8.3%), and VLDL-c (38.6%). Additionally, HD-wsC improved glucose metabolism, enhancing oral glucose tolerance and insulin sensitivity, as reflected in lowered AUC values (4.3% and 5.2%, respectively, vs. HD group). Microbiota analysis further revealed that HD-wsC partially alleviated gut dysbiosis, preserving microbial diversity, increasing beneficial bacteria like Butyricoccaceae, and reducing pathogenic bacteria such as Rickettsiaceae. These findings suggest that wounding stress treated-carrots may offer an effective dietary intervention for obesity management, acting through modulation of adipose tissue function, lipid profiles, and gut microbiota composition.
- Improving the design of multivariable milling tools combining machine learning techniques(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-05) Ramírez Hernández, Oscar Enrique; Olvera Trejo, Daniel; emipsanchez; Puma Araujo, Santiago Daniel; Martínez Romero, Oscar; School of Engineering and Sciences; Campus Monterrey; Fuentes Aguilar, Rita QuetziquelChatter in milling operations degrades surface quality, compromises dimensional accuracy, accelerates tool wear and may damage spindle components. One effective strategy to mitigate chatter while maintaining high productivity is the use of specialized milling tools, such as multivariable milling cutting tools (MMCT), designed with variable geometry in their pitch (𝜙) and helix (β) angles. However, identifying the combination of these angles remains challenging because of the absence of analytics models that link MMCT geometrical parameters with dynamic stability limits. This study proposes a novel approach that integrates analytical lobes calculation with machine learning to enhance tool design efficiency. We find optimal tool geometry (pitch and helix angles) and cutting conditions (spindle speed and axial depth) to maximize the Material Removal Rate (MRR) in milling of a single degree of freedom. Our approach employs a genetic algorithm (GA) combined with a pattern recognition neural network (NN) to predict whether specific parameter combinations will yield stable or unstable behavior. The Multilayer Feedforward Neural Network is trained using a database generated from simulation of a SDOF mathematical model of milling, a non-autonomous Delay Differential Equation. The solution to the DDE is approximated through the Enhanced Multistage Homotopy Perturbation Method (EMHPM). The database includes 23,606,700 observations, covering a catalog of 36,318 MMCT configurations and 650 cutting conditions (axial depth of cut and spindle speed) for each tool configuration. The NN training database uses an approach for handling variable cutting coefficients based on exponential fitting model to describe their variation. These coefficients were characterized at small radial immersion of 1.86 mm using cutting forces of five MMCTs with a diameter of 0.5 in. This approach accurately predicts cutting forces, achieving an NRMSE below 10% when compared with experimental signals. The trained NN estimates the stability of the milling process with an error of 3.3%. Additionally, the combined use of the NN and GA reduces computation time by 98% compared to the GA with EMHPM. The selection of five combinations of geometric parameters that maximize MRR in a range between 26% and 120%, compared to the MRR of a regular tool, which is 190,493 mm³/min, has been performed. The rate of increase in MRR depends on each of the five selected geometries (see Chapter 5). Moreover, without the proposed approach, identifying the improved geometry would require up to 25 days using an exhaustive search scheme, where a SLD is generated for 10,000 cutting conditions for every tool configuration.
- Circular economy: Tequila vinasse treatment for upcycling and downcycling(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-04) Ramos Reyes, María Fernanda; Gradilla Hernández, Misael Sebastián; Tuesta Popolizio, Diego A.; García Garcia, Christian Enrique; School of Engineering and Sciences; Campus Monterrey; González López, Martin EstebanTequila is one of Mexico's most iconic distilled beverages, with a steadily growing industry that also embodies a significant cultural legacy. However, most tequila producers in the country face challenges in managing the waste generated during production due to the high costs of treatment and the low economic returns from by-products. This thesis begins by exploring the intricate relationships between tequila production and various industrial, environmental, and governmental sectors through a comprehensive mapping process. The second section examines the production of distillates, including bioethanol, tequila, and other alcoholic beverages, focusing on the treatment of substantial liquid waste known as vinasse, which is produced at a rate of 10-15 liters per liter of distilled product. This waste presents critical environmental challenges, such as eutrophication, soil pollution, and toxicity. A systematic review conducted in this thesis evaluates various pathways for valorizing distillery vinasse. The review includes 72 treatments involving ethanol industry vinasse, tequila vinasse, and their combinations with agro-industrial residues, categorized into three main valorization strategies: waste-to-energy, waste-to-food, and waste-to-product. Biotechnological treatments, such as two-stage anaerobic digestion and fungal anaerobic fermentation, achieved the highest yields and product diversity. Moreover, bacterial processes demonstrated significant potential for producing high-value products like polymers, enzymes, and proteins. The third part of this thesis is about an aerobic treatment in co-cultures and monocultures using strains like C. utilis, R. mucilaginosa, K. marxianus, A. niger, A. oryzae, and R. oligosporus were explored for contaminant removal and high-protein biomass production. The C. utilis and A. oryzae co-culture generated the best results at the tube scale, showing remotion up to 63.52% TN removal, 86.87% P removal, and 46.21% COD removal over 72 hours in the benchtop scale. A kinetic study modeled biomass growth using a biphasic Zwietering-modified Gompertz model, achieving a maximum protein of 47.27 g kg⁻¹. The thesis also explores other high-value products using this substrate, such as phenols, and the importance of these remotions.
- Development and testing of Spirometer with pulmonary rehabilitation for patients of Amyotrophic Lateral Sclerosis(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-04) Perez Ortiz, Claudia Xochitl; Antelis Ortiz, Javier Mauricio; emimmayorquin; Mendoza Montoya, Omar; School of Engineering and Sciences; Campus Monterrey; Caraza Camacho, RicardoAmyotrophic Lateral Sclerosis is one of the most aggressive neurological diseases affecting the lower and upper motor neurons, it diseases and eventually kills the motor neurons, leaving the patient unable to walk, move, talk, and eventually breathe. For this reason, the main cause of death in ALS is respiratory failure. However ALS patients usually only see specialized health assistants every 2 to 3 months in ALS clinics. Inspiratory Muscle Training (IMT) is a form of resistance workout for the lungs, and it has been found to increase survival in ALS individuals for 12 months. Spirometers, devices that measure lung capacity, could help patients measure their lung state, and adjust therapies accordingly at home. For this reason, an automatic spirometer prototype that can record the state of the lungs, adjust itself, and perform IMT rehabilitation in ALS patients is proposed. Results show that the proposed spirometer prototype could measure FVC and PEF with an average accuracy of 96.98% and 92.6% respectively, and could improve FVC by 13.7%, and FEV1 by 13.6% with inspiratory incentive training.
- Desarrollo de un material compuesto basado en metal "arcilla metálica" para aplicaciones de manufactura aditiva en la fabricación de microdispositivos(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-03) López Solís, Sergio Jesús; Segura Cárdenas, Emmanuel; emimmayorquin; Ulloa Castillo, Nicolas Antonio; Melo Máximo, Dulce Viridiana; Montañez Rodríguez, Abraham; Escuela de Ingeniería y Ciencias; Campus MonterreyEstá investigación explora el desarrollo y la validación de un compuesto metálico llamado “arcilla metálica” mediante fabricación aditiva por extrusión. Su objetivo es identificar los parámetros clave para la composición del material, el proceso de fabricación y las condiciones de sinterización. El estudio analiza la formulación del compuesto metálico, la adaptación de una impresora 3D para la extrusión y los hallazgos experimentales sobre materiales como Inconel 718 y acero inoxidable 316L. Se estudian y prueban varias proporciones de agua, polvo metálico y aglutinante orgánico para lograr una extruibilidad óptima, y el análisis termogravimétrico y espectroscópico ayuda a comprender las propiedades térmicas. El trabajo también evalúa las optimizaciones de la impresión 3D, incluidos los ajustes de la impresora, los tamaños de las boquillas y las resoluciones de impresión, y examina la fabricación de microcanales con un enfoque en la precisión y los procesos de sinterización para minimizar la porosidad. El estudio concluye con información sobre cómo mejorar la calidad y la reproducibilidad de la impresión, lo que contribuye a la fabricación de microdispositivos de arcilla metálica.
- Advanced path tracking: a study on autonomous vehicle control against different scenarios(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-03) Castillo Sánchez, Juan Pablo; González Hernández, Hugo Gustavo; emipsanchez; Moreno Moreno, Jesús; School of Engineering and Sciences; Campus Ciudad de México; Reyes Avendaño, Jorge AntonioAutonomous vehicles have been progressively deployed around the world, bringing numerous challenges remaining in hand due to their intrinsically complex nature. Among them, one of the most critical issues is motion control since it determines the performance of autonomous driving against a wide range of scenarios. This research evaluates the performance of different path tracking control strategies under specific driving conditions and trajectories, along with the exploration of localization algorithms, a fundamental step preceding the motion control stage. The proposed control techniques were simulated based on a single-track 2-DOF vehicle model and then validated through indoor physical tests on a Quanser scaled mobile platform called QCar.
- Quality 4.0 methodology for manufacturing processes(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2024-12-03) Macias Arregoyta, Daniela; Morales Menéndez, Rubén; emipsanchez; Vázquez Lepe, Elisa Virginia; School of Engineering and Sciences; Rectoría Tec de Monterrey; Escobar Díaz, Carlos A.In this work, the pathway for the implementation of Quality 4.0 is reviewed. Several articles are written to detail the evolution from the execution of Six sigma DMAIC methodology and how it can be adapted to the use of AI to create smart factories and smart processes. The main objective is to expand the current conformance rate of this methodology and find the defective items that can be overlooked in manufacturing processes. This research ranges from the selection of the data to train the available models, how can it be corrected and improved, the different processes to handle real-world data sets, the use of different ML algorithms for data analysis, the adaptation of this MLAs to quality standards in Quality 4.0 practices, to the curricular needs for Quality 4.0 for problem solving replacing Six Sigma practices. This thesis will focus only on the description of the decay of the Six Sigma DMAIC paradigm and its evolution to Quality 4.0, and the Process Monitoring for Quality methodology for rare event detection, which are the most noted journal papers in which I could collaborate.
