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Tb3+-activated LTA zeolite-derived boro-aluminosilicate glass samples with a composition of xTb2O3-68(Na2O-Al2O3-SiO2)–32B2O3 (x = 0.2, 1.0 and 10 extra wt%) were prepared using the melt-quenching method. The emission spectra recorded upon ultraviolet (UV) excitation with two different wavelengths of 193 and 378 nm showed blue light (5D3 to 7FJ=6,5,4 and 5D4 to 7F6 transitions of Tb3+) and green light (5D4 to 7F5 transition of Tb3+) emissions with comparable intensities up to a Tb3+ concentration of 10 extra wt%. Of note, the mean decay times of the green luminescence of the glass samples were relatively fast (<20 μs). The synthesized glass has potential in applications concerning UV imaging, UV detection, and plasma display panels. [ABSTRACT FROM AUTHOR]

The increasing integration of distributed generations brings great challenges to the power grid. In this paper, a distributed photovoltaic (PV) integration methodology in distribution network is established for large-scale PV penetration. Firstly, a PV integration model was formulated with the aim of maximizing PV integration capacity and enhancing the voltage profile. Specially, the PV large-scale integration model for county-wide promotion is proposed by considering various typical integration scenarios. Additionally, a novel improved multi-objective Teaching-Learning based optimization (TLBO) algorithm, namely, IM-TLBO, was proposed to seek an optimal Pareto front of the PV integration model. The IM-TLBO algorithm innovatively incorporates the elite reverse learning search strategy to enhance exploration in the solution space. Moreover, the differentiated teaching guided by optimal individual and central location is employed to improve the efficiency of the "teaching" process. Meanwhile, a cyclic crowded sort deletion based on crowding distance is developed to enhance the diversity of elite individuals and the distribution characteristics of the Pareto Frontier. Finally, the performance of IM-TLBO is tested in benchmark functions. Also, a simulation case in IEEE 33 bus system is performed to verify the proposed PV integration method. It is observed that the proposed method in this paper can not only realize the overall optimal integration of roof distributed PV, but also improve voltage profile. The results of IM-TLBO are compared to other classical algorithms, and it is shown that IM-TLBO outperformed them in terms of convergence, distribution and diversity. [ABSTRACT FROM AUTHOR]

Background: Human genetic studies have identified several mitochondrial amidoxime-reducing component 1 (MTARC1) variants as protective against metabolic dysfunction-associated steatotic liver disease. The MTARC1 variants are associated with decreased plasma lipids and liver enzymes and reduced liver-related mortality. However, the role of mARC1 in fatty liver disease is still unclear., Methods: Given that mARC1 is mainly expressed in hepatocytes, we developed an N-acetylgalactosamine-conjugated mouse Mtarc1 siRNA, applying it in multiple in vivo models to investigate the role of mARC1 using multiomic techniques., Results: In ob/ob mice, knockdown of Mtarc1 in mouse hepatocytes resulted in decreased serum liver enzymes, LDL-cholesterol, and liver triglycerides. Reduction of mARC1 also reduced liver weight, improved lipid profiles, and attenuated liver pathological changes in 2 diet-induced metabolic dysfunction-associated steatohepatitis mouse models. A comprehensive analysis of mARC1-deficient liver from a metabolic dysfunction-associated steatohepatitis mouse model by metabolomics, proteomics, and lipidomics showed that Mtarc1 knockdown partially restored metabolites and lipids altered by diet., Conclusions: Taken together, reducing mARC1 expression in hepatocytes protects against metabolic dysfunction-associated steatohepatitis in multiple murine models, suggesting a potential therapeutic approach for this chronic liver disease., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Association for the Study of Liver Diseases.)