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The optimal scheduling method of the power grid considering the node coupling degree and the duality of mutual inverse mapping is studied to effectively establish the random dynamic scene of the power grid and improve its optimal scheduling effect. Considering the duality of the mutual inverse mapping, a random dynamic scene of the power grid is generated. The optimization model of the grid random dynamic scene partition was established considering the coupling degree of the nodes in the region. The anti-prey particle swarm optimization algorithm was used to solve the optimization model, and the scene partition results were obtained. To construct an optimization scheduling model for the regional power grid with the objective functions of minimizing energy abandonment rate and grid loss and the constraints of power flow, output, and climbing power. A predator-prey particle swarm optimization algorithm is used to solve the optimization scheduling model, and the minimum energy abandonment rate, minimum grid loss, and corresponding optimal scheduling strategies are obtained. The experimental results show that this method can effectively generate random dynamic scenes of a power grid and has a better scene partitioning effect. Under different working conditions, this method can achieve optimal dispatching of the power grid and reduce the power grid energy abandonment rate and network loss.

Being one of the main elements of water resources, lakes perform an indispensable part in social production as well as in life. During recent decades, the area of the lake has significantly altered due to global climate variability and growing intensity of the anthropogenic activities. The shrinkage and expansion of lakes have seriously affected both its ecological function and the sustainable development of the regional economy. With this study, we obtain the areas of 38 lakes in China by using the Landsat serial of remote-sensing satellite images in the period 1989–2019 in combination with NDWI water body index and Otsu adaptive thresholding method according to Google Earth Engine (GEE) to explore the trends of lake area changes and related drivers. The outcomes revealed that (1) the overall lake area in the Yunnan-Guizhou Plateau Lake Region (YGP_LR) showed a decreasing trend during the period from 1989 to 2019; the total area of the two lakes(Selin Co and Yangzhuoyong Co) in the Qinghai-Tibet Plateau (QTP_LR) shows an expanding trend; the area of Wulungu Lake in the Mong-Xin Plateau Lake Region (MXP_LR) and Xingkai Lake in the Northeast Plain and Mountain Lake Region (NPM_LR) on a tendency to expand; the area of lakes in the Eastern Plain Lake Region (EP_LR) fluctuated greatly, and the overall area shows a decreasing trend. (2) The increase of temperature promoted the expansion of lake area fed by glacier melt. The increase of rainfall is conducive to the expansion of lake area. The lake area of YGP_LR and EP_LR is closely related to the conversion of other land use types. (3) The lake area of the QTP_LR (Selin Co, Yangzhuoyong Co) varies are mainly affected by climatic factors. Lake area changes in the YGP_LR, Northeast Plain and Mountainous Lake Region (Xingkai Lake), MXP_LR (Wulungu Lake), and EP_LR are influenced by a combination of both climatic changes and the activities of humans. Impact factors of area change in the NPM_LR (Xingkai Lake) need to be further explored.

Objective: To examine the effects of accumulated heat in GI tract (AHGIT) on lung tissue protein expression in pneumonic mice. Methods: Nebulized lipopolysaccharides (LPS) were administered to induce a pneumonic mouse model (M1), and a high-calorie/protein diet combined with nebulized LPS was used to induce AHGIT pneumonia (M2). Isobaric tag for relative and absolute quantitation (iTRAQ) proteomics was applied to study lung protein expression, followed by bioinformatics analysis. Results: M1 mice developed alveolar damage with prominent septum thickening, vascular dilation, hyperaemia and infiltration of large amounts of inflammatory cells. M2 mice developed more severe pathological responses. A total of 2626 proteins were reliably identified in the lung tissue. Compared with normal mice, the M1 mice had 344 differentially expressed proteins in their lungs, which are involved in the following biological processes: response to organic substance, response to cytokine, response to external stimulus, defense response and immune system process. They are also involved in the following Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways: ECM-receptor interaction, leukocyte transendothelial migration, Fc gamma R-mediated phagocytosis, complement and coagulation cascades, and antigen processing and presentation. Compared with the M1 group, the M2 mice had 164 differentially expressed proteins in their lungs, including 14 upregulated and 150 downregulated proteins. These proteins are involved in the following biological processes: small molecule metabolism, ribose phosphate metabolic process, cell adhesion and biological adhesion. The relevant KEGG pathways included oxidative phosphorylation, Citrate cycle (TCA cycle), complement and coagulation cascades, and vascular smooth muscle contraction. Conclusions: AHGIT aggravated the lung inflammatory damage in the mice with LPS-induced pneumonia. It may affect the mouse substance/energy metabolism, and therefore the immune function, to aggravate the LPS-induced inflammatory damage.

This article contains data on the Laser Scanning Confocal Microscopy (LSCM) and Transmission Electron Microscopy (TEM) images related to multi-scaled self-assemblies resulting from ‘green’ cationic glycine betaine surfactant/anionic kappa-carrageenan interactions. These data gave clear evidence of the evolution of the micron-, nano-sized structures obtained at two surfactant/polymer molar ratios (3.5 and 0.8) and after the dilution of the aqueous dispersions with factors of 5 and 10 times. This data article is related to the research article entitled, “Monitoring the architecture of anionic ĸ-carrageenan/cationic glycine betaine amide surfactant assemblies by dilution: A multiscale approach” (Gaillard et al., 2017) [1].