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您的检索式：作者名="Mingfang Qian"
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| 1 | Short-term Wind Speed Prediction with a Two-layer Attention-based LSTM显示文摘Wind speed prediction is of great importance because it affects the efficiency and stability of power systems with a high proportion of wind power.Temporal-spatial wind speed features contain rich information;however,their use to predict wind speed remains one of the most challenging and less studied areas.This paper investigates the problem of predicting wind speeds for multiple sites using temporal and spatial features and proposes a novel two-layer attentionbased long short-term memory(LSTM),termed 2Attn-LSTM,a unified framework of encoder and decoder mechanisms to handle temporal-spatial wind speed data.To eliminate the unevenness of the original wind speed,we initially decompose the preprocessing data into IMF components by variational mode decomposition(VMD).Then,it encodes the spatial features of IMF components at the bottom of the model and decodes the temporal features to obtain each component's predicted value on the second layer.Finally,we obtain the ultimate prediction value after denormalization and superposition.We have performed extensive experiments for short-term predictions on real-world data,demonstrating that 2Attn-LSTM outperforms the four baseline methods.It is worth pointing out that the presented 2Atts-LSTM is a general model suitable for other spatial-temporal features. | Jingcheng Qian Mingfang Zhu Yingnan Zhao Xiangjian He | 2021 | Computer Systems Science & Engineering2021，39，11： | 1 |
| 2 | Ultra-high strength GNP/2024Al composite via thermomechanical treatment显示文摘The 5.0 vol.%GNP/2024Al composites were prepared by accumulated shear deformation combined with heat treatment,i.e.the thermomechanical treatment(TMT).The results showed that homogeneous distributed GNPs that aligned along the plastic deformation direction were obtained by six-pass drawing in the solution heat treatment state.The introducing of high-density dislocations in Al matrix by multiple drawing resulted in enhanced nucleation of precipitates and subsequent uniform growth during ageing.Consequently,ultra-strength GNP/2024Al composites,with yield and ultimate tensile strength 482 and571 MPa,respectively,were achieved.The high strength was attributed to homogeneous dispersion of undamaged GNPs,fine and dispersed precipitations and work-hardening effect.This work demonstrated that TMT could act as a feasible strategy for preparing high-performance GNP/Al composites. | Zhong Zheng Xuexi Zhang Mingfang Qian Jianchao Li Muhammad Imran Lin Geng | 2022 | Journal of Materials Science & Technology2022，，13： | 1 |
| 3 | P-aminobenzoic acid promotes retinal regeneration through activation of Ascl1a in zebrafish显示文摘The retina of zebrafish can regenerate completely after injury.M ultiple studies have demonstrated that metabolic alte rations occur during retinal damage;however to date no study has identified a link between metabolites and retinal regeneration of zebrafish.Here,we performed an unbiased metabolome sequencing in the N-methyl-D-aspartic acid-damaged retinas of zebrafish to demonstrate the metabolomic mechanism of retinal regeneration.Among the differentially-ex pressed metabolites,we found a significant decrease in p-aminobenzoic acid in the N-methyl-D-aspartic acid-damaged retinas of zebrafish.Then,we investigated the role of p-aminobenzoic acid in retinal regeneration in adult zebrafish.Impo rtantly,p-aminobenzoic acid activated Achaetescute complex-like 1a expression,thereby promoting Müller glia reprogramming and division,as well as Müller glia-derived progenitor cell proliferation.Finally,we eliminated folic acid and inflammation as downstream effectors of PABA and demonstrated that PABA had little effect on Müller glia distribution.Taken together,these findings show that PABA contributes to retinal regeneration through activation of Achaetescute complex-like 1a expression in the N-methyl-Daspartic acid-damaged retinas of zebrafish. | Meihui He Mingfang Xia Qian Yang Xingyi Chen Haibo Li Xiaobo Xia | 2024 | Neural Regeneration Research2024，19，8： | 0 |
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