Experimental Determination of the Standard Enthalpy of Formation of Trimellitic Acid and Its Prediction by Supervised Learning.

The standard molar enthalpy of formation for trimellitic acid (TMAc) in the crystalline phase at 298.15 K, ΔfHm°(cr), was calculated experimentally from the enthalpy of combustion through combustion calorimetry experiments. Likewise, the standard molar enthalpy of sublimation was determined from the standard molar enthalpy of fusion and from the standard molar enthalpy of vaporization from differential scanning calorimetry and thermogravimetry, respectively. Subsequently, the standard molar enthalpies of formation in the gas-phase at 298.15 K, ΔfHm°(g), were calculated. The enthalpies of formation for TMAc, hemimellitic, and trimesic acids were predicted using multiple linear regression (MLR) with a nonreplacement evaluation technique. MLR was applied to the data set that allowed estimating these thermochemical properties with an R2 greater than 0.99. This model was used to compare the predicted and experimental results for benzene carboxylic acids.

Modified Oregonator: an Approach from the Complex Networks Theory / Oregonador Modificado: un Enfoque desde la Teoría de Redes Complejas

Abstract: Within the framework of Systems Biology, this paper proposes the complex network theory as a fundamental tool for determining the most critical dynamic variables in complex biochemical mechanisms. The Belousov-Zhabotinsky reaction is proposed as a study model and as a complex bipartite network. By determining the structural property authority, the most relevant dynamic variables are specified, and a mathematical model of the Belousov-Zhabotinsky reaction is obtained. The bidirectional coupling of the proposed model was made with other models associated with biological processes, finding synchronization phenomena when varying the coupling parameter. The time series obtained from the numerical solution of the coupled models were used to construct their images using the Gramian Angular Field technique. In the end, a supervised learning tool is proposed for the classification of the type of coupling by analyzing the images, obtaining score percentages above 94%. The hereby proposed methodology could be extended to the experimental field in order to determine anomalies in the coupling and synchronization of different physiological oscillators.

Resumen: En el marco de la Biología de sistemas, se propone en el presente trabajo a la teoría de redes complejas como una herramienta fundamental para la determinación de las variables dinámicas más importantes en mecanismos bioquímicos complejos. Se emplea como modelo de estudio la reacción de Belousov-Zhabotinsky y se plantea como una red compleja bipartita. Mediante la determinación de la propiedad estructural autoridad, se determinan las variables dinámicas con mayor relevancia y se obtiene un modelo matemático de la reacción de Belousov-Zhabotinsky. Se realizó el acoplamiento bidireccional del modelo planteado con otros modelos asociados a procesos biológicos, encontrándose fenómenos de sincronización al variar el parámetro de acoplamiento. Las series de tiempo obtenidas de la solución numérica de los modelos acoplados se emplearon para construir sus respectivas imágenes mediante la técnica de campo angular gramiano. Finalmente, se propone una herramienta de aprendizaje supervisado para la clasificación del tipo de acoplamiento mediante el análisis de las imágenes, obteniéndose porcentajes de exactitud por encima del 94%. La metodología propuesta en el presente trabajo podría extenderse y trasladarse al campo experimental con la finalidad de determinar anomalías en el acoplamiento y sincronización de distintos osciladores fisiológicos.