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A prediction model for electrical strength of gaseous medium based on molecular reactivity descriptors and machine learning method.

J Mol Model

January 2025

Hubei Key Laboratory·for High-Efficiency-Utilization of Solar Energy and Operation, Control of Energy-Storage System, Hubei-University of Technology, Wuhan, 430068, China.

Context: Ionization and adsorption in gas discharge are similar to electrophilic and nucleophilic reactions. The molecular descriptors characterizing reactions such as electrostatic potential descriptors are useful in predicting the electrical strength of environmentally friendly gases. In this study, descriptors of 73 molecules are employed for correlation analysis with electrical strength.

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Introduction: Therapeutic drug monitoring (TDM) in inflammatory rheumatic diseases (RMDs) is gaining interest. However, there are unresolved questions about the best practices for implementing TDM effectively in clinical settings.

Objective: The primary objective of this study was to evaluate whether early TDM of adalimumab predicts drug survival at 52 weeks in patients with RMDs.

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Purpose: Carcinoembryonic antigen (CEA) is an important prognostic factor for rectal cancer. This study aims to introduce a novel cutoff point for CEA within the normal range to improve prognosis prediction and enhance patient stratification in rectal cancer patients.

Methods: A total of 316 patients with stages I to III rectal cancer who underwent surgical tumor resection were enrolled.

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Context: DNAN/DNB cocrystals, as a newly developed type of energetic material, possess superior safety and thermal stability, making them a suitable alternative to traditional melt-cast explosives. Nonetheless, an exploration of the thermal degradation dynamics of the said cocrystal composite has heretofore remained uncharted. Consequently, we engaged the ReaxFF/lg force field modality to delve into the thermal dissociation processes of the DNAN/DNB cocrystal assembly across a spectrum of temperatures, encompassing 2500, 2750, 3000, 3250, and 3500 K.

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This review aimed to explore the impact of extrusion on Andean grains, such as quinoa, kañiwa, and kiwicha, highlighting their macromolecular transformations, technological innovations, and contributions to food security. These grains, which are rich in starch, high-quality proteins, and antioxidant compounds, are versatile raw materials for extrusion, a continuous and efficient process that combines high temperatures and pressures to transform structural and chemical components. Extrusion improves the digestibility of proteins and starches, encourages the formation of amylose-lipid complexes, and increases the solubility of dietary fiber.

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