Luis Fernando Morales-Mendoza

Écoconception de procédés : approche systémique couplant modélisation globale, analyse du cycle de vie et optimisation multiobjectif: L’objectif de ce travail est de développer un cadre méthodologique et générique d’éco-conception de procédés chimiques couplant des outils de modélisation et de simulation traditionnels de procédés (HYSYS, COCO, ProSimPlus et Ariane), d’Analyse du Cycle de Vie (ACV), d’optimisation multiobjectif basée sur des Algorithmes Génétiques et enfin des outils d’aide à la décision multicritère (ELECTRE, PROMETHEE, M-TOPSIS). Il s’agit de généraliser, d’automatiser et d’optimiser l’évaluation des impacts environnementaux au stade préliminaire de la conception d’un procédé chimique. L’approche comprend trois étapes principales. Les deux premières correspondent d’une part aux phases d’analyse de l’inventaire par calcul des bilans de matière et d’énergie et d’autre part à l’évaluation environnementale par ACV. Le problème du manque d’information ou de l’imprécision dans les bases de données classiques en ACV pour la production d’énergie notamment sous forme de vapeur largement utilisée dans les procédés a reçu une attention particulière. Une solution proposée consiste à utiliser un simulateur de procédés de production d’utilités (Ariane, ProSim SA) pour contribuer à alimenter la base de données environnementale en tenant compte de variations sur les conditions opératoires ou sur les technologies utilisées. Des sous-modules « énergie » sont ainsi proposés pour calculer les émissions relatives aux impacts liés à l’utilisation de l’énergie dans les procédés. La troisième étape réalise l’interaction entre les deux premières phases et l’optimisation multi-objectif qui met en jeu des critères économiques et environnementaux. Elle conduit à des solutions de compromis le long du front de Pareto à partir desquelles les meilleures sont choisies à l’aide de méthodes d’aide à la décision. L’approche est appliquée à des procédés de production continus : production de benzène par hydrodéalkylation du toluène HDA et production de biodiesel à partir d’huiles végétales. Une stratégie à plusieurs niveaux est mise en oeuvre pour l'analyse de l'optimisation multi-objectif. Elle est utilisée dans les deux cas d'étude afin d'analyser les comportements antagonistes des critères.

This work addresses a central challenge in process eco‐design: how to efficiently integrate environmental and economic criteria—often conflicting—into early design stages while managing the high dimensionality of Life Cycle Assessment (LCA) indicators. To this end, we propose a generic six‐level multi‐objective methodology combining process simulation, LCA, a modified NSGA‐II genetic algorithm, and multiple criteria decision‐making (MCDM) models (ELECTRE, PROMETHEE, M‐TOPSIS). The approach is applied to the hydrodealkylation of toluene (HDA) for benzene production. Starting from a set of five criteria (four environmental end‐points and economic performance), later expanded to 14 environmental mid‐points, the method identifies redundant indicators and reduces the optimization to the most influential objectives. Results show that a bi‐objective optimization (economic performance vs. human‐health impacts) is sufficient to represent trade‐offs previously captured by the full 14‐indicator space. Quantitatively, the optimized solutions achieve 12%–18% reductions in environmental end‐point impacts relative to single‐objective economic optimization, without increasing operating costs. Mid‐point results indicate that ozone layer depletion is the dominant contributor among human‐health categories, guiding the formulation of a refined optimization problem. MCDM techniques consistently identify similar compromise solutions, confirming the robustness of the reduced‐criteria strategy. Overall, this framework demonstrates that combining LCA, multi‐objective optimization, and MCDM into a structured multi‐level workflow enables engineers to reduce problem complexity while achieving environmentally improved designs that remain economically viable.

Craft beer production has grown extensively worldwide. The variety of products and grains that can be used in production make this artisanal product unique. In this study, we propose a system dynamics model that allows for the evaluation of different production scenarios in which figs are used as the main ingredient. This research is inspired by the real case of small fig producers in Valle del Mayo in Navojoa, Sonora, Mexico, who, in 2020, took on the challenge of creating a processing factory for fig-derived products. This paper presents the development and application of a system dynamics approach to model the entire supply chain of overripe figs, i.e., figs that cannot be marketed in prime quality but can still be used in the production of derivative products. The method used for its development encompasses the following stages: (1) defining the craft beer supply chain variables; (2) elaborating on causal diagrams; (3) producing model stock and flow diagrams; (4) model validation; (5) sensitivity analysis and scenario evaluations; and (6) building a graphical user interface (GUI). The proposed model allows managers to assess several production policies under various assumptions of capacity and beer demand, demonstrating its value as an effective tool for strategic decision making.

Cancer is one of the leading causes of death worldwide. Conventional cancer therapies are not selective to cancer cells resulting in serious side effects on patients. Thus, the need for complementary treatments that improve the patient's response to cancer therapy is highly important. To predict and evaluate the physicochemical characteristics and potential anticancer activity of the peptides identified from S. hispanica protein fraction in silico tools. Peptides derived from Salvia hispanica's protein fraction <1 kDa were identified and analyzed for the prediction of their physicochemical properties. The characterized peptide sequences were then submitted to a multi-criteria decision analysis to identify the peptides that possess the characteristics to potentially exert anticancer activity. Through molecular docking analysis, the potential anticancer activity of the Potentially Anticancer Peptide (PAP)-1, PAP-2, PAP-3, PAP-4, and PAP-5 was estimated by their binding interactions with cancer and apoptosis-related molecules. All five evaluated PAPs exhibited strong binding interactions (< -100 kcal/mol). However, PAP-3 showed the lowest binding free energies with several of the targets. Thus, PAP-3 shows potential to be used as a nutraceutical or ingredient for functional foods that adjuvate in cancer treatment. Conclusions: Through the molecular docking studies, the binding of the PAPs to target molecules of interest for cancer treatment was successfully simulated, from which PAP-3 exhibited the lowest binding free energies. Further in vitro and in vivo studies are required to validate the predictions obtained by the in silico analysis. [GRAPHICS] .

This study started from a fig-derived product project in the 2022–2026 Strategic Plan from Sonora, Mexico, to develop technological solutions in complex environments and provide a global panorama from the industry to the prevailing situation in Valle del Mayo. A technological solution is based on a graphical interface to support decision-making in fig supply, production and distribution in the administration process, given that the main problem has been the lack of a processing plant with a sustainable approach. Four options were set up for nine producers—figs in syrup, dehydrated, marmalade, compost—based on the system dynamics methodology to solve the problem of factory installation. Six stages were followed: (1) mapping the system to determine variables and parameters; (2) constructing the causal diagram; (3) developing the flow and level diagram and model equations; (4) simulating and validating the current model; (5) designing policies and evaluating scenarios using a multi-criteria analysis; and (6) developing the graphical interface. The main conclusions show that fig-derived products and their distribution can feature in diverse markets in a graphics environment supported by complex mathematical models in the supply chain along with the capacity to generate income into utilities to support the decision of the physical factory prior to important investments.

The construction industry has a relevant social and economic function and has become fundamental to achieving the Paris Agreement and the United Nations Sustainable Development Goals. This industry contributes significantly to global CO₂ emissions due to embodied and operating energy. There are methodologies to evaluate them, but they lack integration with other variables. In the case of buildings and assessing safety and costs, environmental assessment needs to be incorporated; current methodologies are complex to implement and, in general, costly in terms of economic and human resources. This research proposes the Environmental Economic Index (EEI) to evaluate structural building projects and support decision-making, obtained from a simplified methodology. In the case study, located in San Luis Potosi, Mexico, the same building structure was designed to subject to different operational loads and lateral forces, with structural concrete and structural steel. For this building, the concrete structure subject to seismic actions had a better result when estimating the EEI and comparing it with the other structural alternatives. The contribution of this work is to develop a simplified methodology to evaluate structural projects in the design phase, which integrates economic, environmental, and safety variables and supports decision-making in designers and real estate developers.

Sugarcane cultivation requires correct fertilizer rates. However, when nutrients are not available, or there is over-fertilization, the yields are significantly reduced and the environmental burden increase. In this study, it is proposed a decision support system (DSS) for the correct NPK (nitrogen, phosphorus and potassium) fertilization. The DSS consists of two fuzzy models; the edaphic condition model (EDC-M) and the NPK fertilization model (NPK-M). The DSS using parameters from soil analysis and is based on the experience of two groups of experts to avoid the bias to the reality of a single group of professionals. The results of the DSS are compared with the results of soil analysis and those of the group of experts. One hundred and sixty tests were developed in the NPK-M. The N rate shows R²=0.981 for the DSS and R²=0.963 for soil analyzes. The P rate shows R²=0.9702 for the DSS and R²=0.9183 for the soil analyzes. The K rate shows R²=0.9691 for the DSS and R²=0.9663 for the soil analyzes. Environmental results indicate that the estimated rates with the DSS do reduce the environmental impact on the tests performed.

El desarrollo de colecciones es un proceso que permite a las bibliotecas contar con el material bibliográfico adecuado para atender las necesidades de su comunidad de usuarios. En este proceso, una de las restricciones principales es la reducción en la asignación del presupuesto. Por lo tanto, se requiere analizar la colección bibliográfica con base en indicadores cuantitativos para conocer las características y necesidades informativas de la comunidad. La evaluación cuantitativa es una herramienta que facilita al responsable bibliotecario la toma de decisiones para la adquisición y descarte de material bibliográfico. Como propuesta, este trabajo utilizó un modelo de minería de datos para analizar los indicadores relacionados con: 1) número de volúmenes por subclase temática, 2) número de usos por subclase temática, y 3) número de volúmenes en uso por subclase temática. El modelo se validó con un estudio estadístico de las transacciones de préstamos tanto a domicilio como en sala registrados en una de las bibliotecas de la Universidad Autónoma de Yucatán durante el periodo de mayo de 2011 a junio de 2017.