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| 1 | The Solar Upper Transition Region Imager(SUTRI)Onboard the SATech-01 Satellite显示文摘The Solar Upper Transition Region Imager(SUTRI)onboard the Space Advanced Technology demonstration satellite(SATech-01),which was launched to a Sun-synchronous orbit at a height of~500 km in 2022 July,aims to test the on-orbit performance of our newly developed Sc/Si multi-layer reflecting mirror and the 2k×2k EUV CMOS imaging camera and to take full-disk solar images at the Ne VII 46.5 nm spectral line with a filter width of~3 nm.SUTRI employs a Ritchey-Chrétien optical system with an aperture of 18 cm.The on-orbit observations show that SUTRI images have a field of view of~416×416 and a moderate spatial resolution of~8″without an image stabilization system.The normal cadence of SUTRI images is 30 s and the solar observation time is about16 hr each day because the earth eclipse time accounts for about 1/3 of SATech-01's orbit period.Approximately15 GB data is acquired each day and made available online after processing.SUTRI images are valuable as the Ne VII 46.5 nm line is formed at a temperature regime of~0.5 MK in the solar atmosphere,which has rarely been sampled by existing solar imagers.SUTRI observations will establish connections between structures in the lower solar atmosphere and corona,and advance our understanding of various types of solar activity such as flares,filament eruptions,coronal jets and coronal mass ejections. | Xianyong Bai Hui Tian Yuanyong Deng Zhanshan Wang Jianfeng Yang Xiaofeng Zhang Yonghe Zhang Runze Qi Nange Wang Yang Gao Jun Yu Chunling He Zhengxiang Shen Lun Shen Song Guo Zhenyong Hou Kaifan Ji Xingzi Bi Wei Duan Xiao Yang Jiaben Lin Ziyao Hu Qian Song Zihao Yang Yajie Chen Weidong Qiao Wei Ge Fu Li Lei Jin Jiawei He Xiaobo Chen Xiaocheng Zhu Junwang He Qi Shi Liu Liu Jinsong Li Dongxiao Xu Rui Liu Taijie Li Zhenggong Feng Yamin Wang Chengcheng Fan Shuo Liu Sifan Guo Zheng Sun Yuchuan Wu Haiyu Li Qi Yang Yuyang Ye Weichen Gu Jiali Wu Zhe Zhang Yue Yu Zeyi Ye Pengfeng Sheng Yifan Wang Wenbin Li Qiushi Huang Zhong Zhang | 2023 | Research in Astronomy and Astrophysics2023，23，6： | 1 |
| 2 | 6-15 Status Report of On-line Ion Sources in 2015显示文摘In 2015, the service time of the two on-line ion sources of HIRFL-CSR accelerator facility, SECRAL and LECR3, is 3 335.5 and 3 168.5 h, respectively, amouting to 6 504 h. Except 26Mg7+, which was required by the accelerator but failed to be produced due the oxidation of the material, 20 kinds of ion beams have been delivered successfull.The failure time is 49 h this year, mainly attributed to the breakdown of the cryostat system. | Feng Yucheng Lu Wang Zhang Wenhui Ma Hongyi Yang Yao Fang Xing Guo Junwei Ma Baohua Wang Hui Qian Cheng Zhang Junjie Li Jibo Jin Qianyu sheng Sifan Liu Pengyan Li Xixia Zhao Huanyu Zhang Xuezhen Sun Liangting | 2015 | IMP & HIRFL Annual Report2015，，1： | 0 |
| 3 | Construction of N,O co-doped carbon anchored with Co nanoparticles as efficient catalyst for furfural hydrodeoxygenation in ethanol显示文摘Hydrodeoxygenation of furfural(FF)into 2-methylfuran(MF)is a significant biomass utilization route.However,designing efficient and stable non-noble metal catalyst is still a huge challenge.Herein,we reported the N,O co-doped carbon anchored with Co nanoparticles(Co-SFB)synthesized by employing the organic ligands with the target heteroatoms.Raman,electron paramagnetic resonance(EPR),electrochemical impedance spectroscopy(EIS),and X-ray photoelectron spectroscopy(XPS)characterizations showed that the co-doping of N and O heteroatoms in the carbon support endows Co-SFB with enriched lone pair electrons,fast electron transfer ability,and strong metal-support interaction.These electronic properties resulted in strong FF adsorption as well as lower apparent reaction activation energy.At last,the obtained N,O co-doped Co/C catalyst showed excellent catalytic activity(nearly 100 mol%FF conversion and 94.6 mol%MF yield)and stability for in-situ dehydrogenation of FF into MF.This N,O co-doping strategy for the synthesis of highly efficient catalytic materials with controllable electronic state will provide an excellent opportunity to better understand the structure-function relationship. | Hui Yang Hao Chen Wenhua Zhou Haoan Fan Chao Chen Yixuan Sun Jiaji Zhang Sifan Wang Teng Guo Jie Fu | 2023 | Journal of Energy Chemistry2023，，3： | 0 |
| 4 | COVID-19 induces new-onset insulin resistance and lipid metabolic dysregulation via regulation of secreted metabolic factors显示文摘Abnormal glucose and lipid metabolism in COVID-19 patients were recently reported with unclear mechanism.In this study,we retrospectively investigated a cohort of COVID-19 patients without pre-existing metabolic-related diseases,and found new-onset in suli n resista nee,hyperglycemia,and decreased HDL-C in these patie nts.Mecha nistically,SARS-CoV-2 infecti on in creased the expression of RE1-silencing transcription factor(REST),which modulated the expression of secreted metabolic factors including myeloperoxidase,apelin,and myostatin at the transcriptional level,resulting in the perturbation of glucose and lipid metabolism.Furthermore,several lipids,including(±)5-HETE,(±)12-HETE,propionic acid,and isobutyric acid were identified as the potential biomarkers of COVID-19-induced metabolic dysregulation,especially in insulin resistance.Taken together,our study revealed insulin resistance as the direct cause of hyperglycemia upon COVID-19,and further illustrated the underlying mechanisms,providing potential therapeutic targets for COVID-19-induced metabolic complications. | Xi He Chenshu Liu Jiangyun Peng Zilun Li Fang Li Jian Wang Ao Hu Meixiu Peng Kan Huang Dongxiao Fan Na Li Fuchun Zhang Weiping Cai Xinghua Tan Zhongwei Hu Xilong Deng Yueping Li Xiaoneng Mo Linghua Li Yaling Shi Li Yang Yuanyuan Zhu Yanrong Wu Huichao Liang Baolin Liao Wenxin Hong Ruiying He Jiaojiao Li Pengle Guo Youguang Zhuo Lingzhai Zhao Fengyu Hu Wenxue Li Wei Zhu Zefeng Zhang Zeling Guo Wei Zhang Xiqiang Hong Wei kang Cai Lei Gu Ziming Du Yang Zhang Jin Xu Tao Zuo Kai Deng Li Yan Xinwen Chen Sifan Chen Chunliang Lei | 2022 | Signal Transduction and Targeted Therapy2022，7，1： | 0 |
| 5 | Accuracy improvement for classifying retinal OCT images by diseases using deep learning-based selective denoising approach显示文摘In ophthalmology,retinal optical coherence tomography(OCT)images with noticeable structural features help identify human eyes as healthy or diseased.The recently hot arti ficial intelligence(AI)realized this recognition process automatically.However,speckle noise in the original retinal OCT image reduces the accuracy of disease classi fication.This study presents a timesaving approach based on deep learning to improve classi fication accuracy by removing the noise from the original dataset.Firstly,four pre-trained convolutional neural networks(CNNs)from the ImageNet Large Scale Visual Recognition Challenge(ILSVRC)were trained to classify the original images into two categories:The noise reduction required(NRR)and the noise-free(NF)images.Among the CNNs,VGG19 BN performed best with 98%accuracy and 99%recall.Then,we used the block-matching and 3D filtering(BM3D)algorithm to denoise the NRR images.Those noise-removed NRR and the NF images form the processed dataset.The quality of images in the dataset is prominently ameliorated after denoising,which is valid to improve the models'performance.The original and processed datasets were tested on the four pre-trained CNNs to evaluate the effectiveness of our proposed approach.We have compared the CNNs,and the results show the performance of the CNNs trained with the processed dataset is improved by an average of 2.04%,5.19%,and 5.10%under overall accuracy(OA),Macro F1-score,and Micro F1-score,respectively.Especially for DenseNet161,the OA is improved to 98.14%.Our proposed method demonstrates its effectiveness in improving classi fication accuracy and opens a new solution to reduce denoising time-consuming for large datasets. | Lantian Hu Ruixiang Guo Sifan Li Jing Cao Qian Liu | 2023 | Journal of Innovative Optical Health Sciences2023，16，6： | 0 |
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