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With the rapid growth in the proportion of renewable energy access and the structural complexity of distributed energy systems, traditional microgrid (MG) scheduling methods that rely on mathematical optimization models and expert experience are facing significant challenges. Therefore, it is essential to present a novel scheduling technique with high intelligence and fast decision-making capacity to realize MGs' automatic operation and regulation. This paper proposes an optimal scheduling decision-making method for MGs based on deep neural networks (DNN). Firstly, a typical mathematical scheduling model used for MG operation is introduced, and the limitations of current methods are analyzed. Then, a two-stage optimal scheduling framework comprising day-ahead and intra-day stages is presented. The day-ahead part is solved by mixed integer linear programming (MILP), and the intra-day part uses a convolutional neural network (CNN)—bidirectional long short-term memory (Bi LSTM) for high-speed rolling decision making, with the outputs adjusted by a power correction balance algorithm. Finally, the validity of the model and algorithm of this paper are verified by arithmetic case analysis. [ABSTRACT FROM AUTHOR]

It is well-known that structures composed of super high-rise buildings accumulate damages gradually due to ultra-long loads, material aging, and component defects. Thus, the bearing capacity of the structures can be significantly decreased. In addition, these effects may cause inestimable life and property losses upon strong winds, earthquakes, and other heavy loads. Hence, it is necessary to develop real-time health monitoring methods for super high-rise buildings to deeply understand the running state during operation, timely discover potential safety potentials, and to provide reference data for reinforcement design. Along these lines, in this work, the built super high-rise buildings (Yunding Building) and super high-rise buildings (the Main Tower of the Shandong International Financial Center), under construction, were selected as the research objects. The overall dynamic deformation laws of super high-rise buildings were monitored by using ground-based real aperture radar (GB-RAR) technology for its advantages in non-contact measurement, remote monitoring, and real-time display of observation results. Denoising of the observation data was also carried out based on wavelet analysis. The visualization of the space state of the Yunding Building was realized based on handheld LiDAR technology. From the acquired results, it was demonstrated that the measuring accuracy of GB-RAR could reach the submillimeter level, while the noises under a natural state of wavelet analysis were eliminated well. The maximum deformation values of the Yunding Building and the Main Tower of Shandong International Financial Center under their natural state were 9.63 mm and 16.46 mm, respectively. Under sudden wind loads, the maximum deformation of the Yunding Building could be as high as 895.79 mm. The overall motion state switched between an S-shaped pattern, hyperbolic-type, and oblique line, presented the characteristics of nonlinear elastic deformation. [ABSTRACT FROM AUTHOR]

Vinylidene chloride copolymer microspheres were synthesized by in situ suspension copolymerization of vinylidene chloride (VDC), methyl methacrylate (MMA), and/or acrylonitrile (AN) in the presence of a paraffin blowing agent. The effects of shell polymer properties including compositions, glass transition temperature (Tg), crosslinking degree, blowing agent type, and encapsulation ratio (Er) on the expansion properties of copolymer microspheres were investigated. Moreover, the diffusion properties of blowing agent in copolymer microspheres were studied. The results show that VDC-MMA-AN copolymer microspheres exhibited excellent expansion properties, and the volume expansion ratio (Ev) and the apparent density were decreased over 40 times, but it was difficult to expand for the VDC-MMA copolymer microspheres. In addition, the moderately crosslinked inside of the polymer shell enhanced the Ev more than 30 and the stable expansion temperature range (Tr) was about 30 °C by adding 0.2–0.4 wt% of divinyl benzene. The Tg of the shell polymer must be higher than the boiling point of the blowing agent as a prerequisite; the lower the boiling point of the blowing agent, the higher the internal gas pressure driven microsphere expansion, and the wider the Tr. By increasing the Er of blowing agent improved the Ev of the microspheres. The diffusion of pentane blowing agent in VDC-MMA-AN copolymer microspheres were divided into Fick diffusion and non-Fick diffusion. [ABSTRACT FROM AUTHOR]

In response to the significant ecological damage caused by unsustainable mining practices in the Qilian Mountains, ecological restoration projects have been undertaken in recent years. Analyzing the changes in soil microbial communities during the restoration process of mine meadows helps to reveal the mechanism of the restoration process in alpine mining areas. To explore the characteristics of soil microbial community distribution and their relationships with soil environmental factors during the restoration of alpine grasslands in the Qilian Mountains, we conducted surveys and analyses in two restoration levels low restoration (LR) and high restoration (HR) in the eastern Qilian Mountains, along with an undisturbed natural grassland control (NG). We found that as the degree of high-altitude mining area recovery increases, there were significant increases in vegetation cover, vegetation height, above-ground biomass, vegetation Shannon–Wiener index, soil organic carbon (SOC), soil water content (SWC), total nitrogen (TN), total phosphorus (TP), total potassium (TK), available phosphorus (AP), and available nitrogen (AN). Conversely, soil pH and electrical conductivity (EC) significantly decreased, with soil pH decreasing from 6.93 to 4.13. Restoration of high-altitude mining area grasslands significantly alters the distribution and composition of soil bacteria and fungi, while the impact on soil microbial community changes was not significant. Notably, with increasing recovery level, the dominant bacterial phyla are Acidobacteria and Proteobacteria, while the dominant fungal phyla are Ascomycota and Basidiomycota. These results indicate that changes in vegetation and soil properties both affect the composition of soil microbial communities, with soil properties having a greater influence. Soil fertility and nutrient levels emerge as the primary drivers influencing soil microbial composition communities and the degree of high-altitude mining area grassland recovery. [ABSTRACT FROM AUTHOR]

The issue of heavy metal pollution has gradually emerged as a significant global concern. Microbial fuel cells (MFCs) hold immense potential for clean energy production and pollutant treatment. However, their limited power generation efficiency hampers the large-scale implementation of MFCs. The porous microstructure of biochar and the excellent physical and chemical properties of rutile render both materials promising catalysts with positive potential. In this study, we employed biochar as a carrier for rutile to fabricate a novel rutile–biochar (Rut-B) composite material, investigating its efficacy in enhancing MFC power generation efficiency as a cathode catalyst, as well as its application in heavy metal pollutant degradation. Scanning electron microscopy (SEM) results confirmed the successful preparation of biochar-loaded rutile composites. The MFC achieved maximum current density and power density values of 152.26 mA/m2 and 9.88 mW/m2, respectively—an increase of 102.7% and 224% compared to the control group without the addition of Rut-B. Furthermore, the biochar-loaded rutile MFC exhibited excellent performance in degrading heavy metal pollutants; within 7 h, the Pb2+ degradation rate reached 92.4%, while the Zn2+ degradation rate reached 84%. These rates were significantly higher than those observed in the control group, by factors of 437.2% and 345%, respectively. The cyclic degradation experiments also demonstrated the outstanding stability of the system over multiple cycles. In summary, this study successfully combined natural rutile with biochar to create an efficient electrode catalyst that not only enhances electricity generation performance but also provides an environmentally friendly and cost-effective approach for remediating heavy metal pollution. [ABSTRACT FROM AUTHOR]

The 3′-untranslated region (3′-UTR) of PD-L1 is significantly longer than the coding sequences (CDSs). However, its role and regulators have been little studied. We deleted whole 3′-UTR region by CRISPR-Cas9. Prognostic analysis was performed using online tools. Immune infiltration analysis was performed using the Timer and Xcell packages. Immunotherapy response prediction and Cox regression was performed using the R software. MicroRNA network analysis was conducted by the Cytoscape software. The level of PD-L1 was significantly and dramatically up-regulated in cells after deleting the 3′-UTR. Additionally, we discovered a panel of 43 RNA-binding proteins (RBPs) whose expression correlates with PD-L1 in the majority of cancer cell lines and tumor tissues. Among these RBPs, PARP14 is widely associated with immune checkpoints, the tumor microenvironment, and immune-infiltrating cells in various cancer types. We also identified 38 microRNAs whose individual expressions are associated with PD-L1 across different cancers. Notably, miR-3139, miR-4761, and miR-15a-5p showed significant associations with PD-L1 in most cancer types. Furthermore, we revealed 21 m6A regulators that strongly correlate with PD-L1. Importantly, by combining the identified RBP and m6A regulators, we established an immune signature consisting of RBMS1, QKI, ZC3HAV1, and RBM38. This signature can be used to predict the responsiveness of cancer patients to immune checkpoint blockade treatment. We demonstrated the critical role of the 3′-UTR in the regulation of PD-L1 and identified a significant number of potential PD-L1 regulators across various types of cancer. The biomarker signature generated from our findings shows promise in predicting patient prognosis. However, further biological investigation is necessary to explore the potential of these PD-L1 regulators. [ABSTRACT FROM AUTHOR]