24 research outputs found
Adaptive SPPâCNNâLSTMâATT wind farm cluster short-term power prediction model based on transitional weather classification
With the expansion of the scale of wind power integration, the safe operation of the grid is challenged. At present, the research mainly focuses on the prediction of a single wind farm, lacking coordinated control of the cluster, and there is a large prediction error in transitional weather. In view of the above problems, this study proposes an adaptive wind farm cluster prediction model based on transitional weather classification, aiming to improve the prediction accuracy of the cluster under transitional weather conditions. First, the reference wind farm is selected, and then the improved snake algorithm is used to optimize the extreme gradient boosting tree (CBAMSO-XGB) to divide the transitional weather, and the sensitive meteorological factors under typical transitional weather conditions are optimized. A convolutional neural network (CNN) with a multi-layer spatial pyramid pooling (SPP) structure is utilized to extract variable dimensional features. Finally, the attention (ATT) mechanism is used to redistribute the weight of the long and short term memory (LSTM) network output to obtain the predicted value, and the cluster wind power prediction value is obtained by upscaling it. The results show that the classification accuracy of the CBAMSO-XGB algorithm in the transitional weather of the two test periods is 99.5833% and 95.4167%, respectively, which is higher than the snake optimization (SO) before the improvement and the other two algorithms; compared to the CNNâLSTM model, the mean absolute error (MAE) of the adaptive prediction model is decreased by approximately 42.49%â72.91% under various transitional weather conditions. The relative root mean square error (RMSE) of the cluster is lower than that of each reference wind farm and the prediction method without upscaling. The results show that the method proposed in this paper effectively improves the prediction accuracy of wind farm clusters during transitional weather
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Author Correction: A deep-learning pipeline for the diagnosis and discrimination of viral, non-viral and COVID-19 pneumonia from chest X-ray images.
Robust propagation of a steady optical beam through turbulence with extended depth of focus based on spatial light modulator
Finding appropriate strategies to increase the robustness through turbulence with extended depth of focus (DOF) is a common requirement in developing high-resolution imaging through air or water media. However, conventional lenses with a specially designed structure require high manufacturing costs and are limited by a lack of dynamic modulation characteristics. Spatial light modulators (SLMs) are unique flat-panel optical devices which can overcome the distance limitation of beam propagation for the dynamic modulation property. In this work, we address the dynamic generation of a steady optical beam (STOB) based on the mechanism of transverse wave vector elimination. STOBs generated by the SLM have significant advantages over Gaussian beams for the characteristics of peak intensity, robust propagation, extended-DOF beam profile, and dynamic wavefront modulation over a long distance under strong turbulent media. Our versatile, extensible, and flexible method has promising application scenarios for the realization of turbulence-resistant circumstances
Corrosion Behavior in Magnesium-Based Alloys for Biomedical Applications
Magnesium alloys exhibit superior biocompatibility and biodegradability, which makes them an excellent candidate for artificial implants. However, these materials also suffer from lower corrosion resistance, which limits their clinical applicability. The corrosion mechanism of Mg alloys is complicated since the spontaneous occurrence is determined by means of loss of aspects, e.g., the basic feature of materials and various corrosive environments. As such, this study provides a review of the general degradation/precipitation process multifactorial corrosion behavior and proposes a reasonable method for modeling and preventing corrosion in metals. In addition, the composition design, the structural treatment, and the surface processing technique are involved as potential methods to control the degradation rate and improve the biological properties of Mg alloys. This systematic representation of corrosive mechanisms and the comprehensive discussion of various technologies for applications could lead to improved designs for Mg-based biomedical devices in the future
Synergistic Effect in Plasmonic CuAu Alloys as Co-Catalyst on SnIn<sub>4</sub>S<sub>8</sub> for Boosted Solar-Driven CO<sub>2</sub> Reduction
The photoreduction of CO2 to chemical fuels represents a promising technology to mitigate the current energy dilemma and global warming problems. Unfortunately, the original photocatalysts suffer from many side reactions and a poor CO2 conversion efficiency. The rational combination of active co-catalyst with pristine photocatalysts for promoting the adsorption and activation of CO2 is of vital importance to tackle this grand challenge. Herein, we rationally designed a SnIn4S8 nanosheet photocatalyst simultaneously equipped with CuAu alloys. The experimental results proved that the CuAu alloy can trap the electrons and enhance the separation and transport efficiency of the photogenerated carrier in the photocatalyst, alleviating the kinetical difficulty of the charge transfer process because of the preferable localized surface plasmon resonance (LSPR). Furthermore, the CuAu alloy works as the synergistic site to increase the CO2 adsorption and activation capacity. The optimized CuAu-SnIn4S8 photocatalyst exhibited a superior performance with CO generation rates of 27.87 ÎŒmol gâ1 hâ1 and CH4 of 7.21 ÎŒmol gâ1 hâ1, which are about 7.6 and 2.5 folds compared with SnIn4S8. This work highlights the critical role of alloy cocatalysts in boosting a CO2 activation and an efficient CO2 reduction, thus contributing to the development of more outstanding photocatalytic systems
Laser Coherent Combination With Circular Array of Airy Beams
A high-efficiency laser coherent combination method based on the virtue of the self-transverse acceleration effect of Airy beams is proposed and demonstrated by converting an array of Gaussian beams into Airy beams array to reduce laser beams separation distance. The coherent combination procedures of circular array for both Airy and Gaussian beams are theoretically and experimentally studied. The results show that the central intensity of the laser coherent combination of the circular array of Airy beams is 14.33 times higher than that of the Gaussian beams array, and the combined efficiency of the circular array of Airy beams is 1.64 times higher than that of the Gaussian beams circular array. The method may provide an efficient way to increase combination efficiency of laser coherent combination array and may have a broad application prospect in optical communication, particle capture, material processing
Crosstalk between hepatitis B virus X and highâmobility group box 1 facilitates autophagy in hepatocytes
Hepatitis B virus (HBV) X (HBx) protein is a pivotal regulator of HBVâtriggered autophagy. However, the role of HBxâinduced epigenetic changes in autophagy remains largely unknown. The cytoplasmic (Cyt) highâmobility group box 1 (HMGB1) has been identified as a positive regulator of autophagy, and its Cyt translocation is closely associated with its acetylation status. Here, we evaluated the function of HMGB1 in HBxâmediated autophagy and its association with histone deacetylase (HDAC). Using cell lines with enforced expression of HBx, we demonstrated that HBx upregulated the expression of HMGB1 and promoted its Cyt translocation by acetylation to facilitate autophagy. We further identified the underlying mechanism by which decreased nuclear HDAC activity and expression levels contribute to the HBxâpromoted hyperacetylation and subsequent translocation of HMGB1. We also identified the HDAC1 isoform as a critical factor in regulating this phenomenon. In addition, HBx bound to HMGB1 in the cytoplasm, which triggered autophagy in hepatocytes. Pharmacological inhibition of HMGB1 Cyt translocation with ethyl pyruvate prevented HBxâinduced autophagy. These results demonstrate a novel function of acetylated HMGB1 in HBxâmediated autophagy in hepatocytes
Stacking Engineering of Heterojunctions in HalfâMetallic Carbon Nitride for Efficient CO2 Photoreduction
Abstract Enhancing charge separation in semiconductor photocatalysts is a major challenge for efficient artificial photosynthesis. Herein, a compact heterojunction is designed by embedding halfâmetallic C(CN)3 (hmâCN) hydrothermally in BiOBr (BOB) as the backbone. The interface between hmâCN and BOB is seamless and formed by covalent bonding to facilitate the transmission of photoinduced electrons from BOB to hmâCN. The transient photocurrents and electrochemical impedance spectra reveal that the modified composite catalyst exhibits a larger electron transfer rate. The photocatalytic activity of hmâCN/BOB increases significantly as indicated by a CO yield that is about four times higher than that of individual components. Densityâfunctional theory calculations verify that the heterojunction improves electron transport and decreases the reaction energy barrier, thus promoting the overall photocatalytic CO2 conversion efficiency. The halfâmetal nitride coupled semiconductor heterojunctions might have large potential in artificial photosynthesis and related applications