Search Results - "Zhang, Yaojie"

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  1. 1

    Geopolitical risk and oil volatility: A new insight by Liu, Jing, Ma, Feng, Tang, Yingkai, Zhang, Yaojie

    Published in Energy economics (01-10-2019)
    “…•We explore the role and effective usage of GPR in forecasting oil volatility.•The GPRS index is constructed by filtering the GPR larger than a threshold.•The…”
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  2. 2

    Is implied volatility more informative for forecasting realized volatility: An international perspective by Liang, Chao, Wei, Yu, Zhang, Yaojie

    Published in Journal of forecasting (01-12-2020)
    “…Inspired by the commonly held view that international stock market volatility is equivalent to cross‐market information flow, we propose various ways of…”
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  3. 3

    Structure characteristics of a water-soluble polysaccharide purified from dragon fruit (Hylocereus undatus) pulp by Xu, Lishan, Zhang, Yaojie, Wang, Lizhi

    Published in Carbohydrate polymers (01-08-2016)
    “…•The precise structure of a dragon fruit pulp polysaccharide (DFPP) was identified.•DFPP had a molecular weight of 2.2×103kDa.•→4-β-d-GlcpA-1→, →6-β-d-Galp-1→…”
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  4. 4

    Good, bad cojumps and volatility forecasting: New evidence from crude oil and the U.S. stock markets by Chen, Yixiang, Ma, Feng, Zhang, Yaojie

    Published in Energy economics (01-06-2019)
    “…In this article, we investigate the impacts of jumps, cojumps and their signed components on forecasting oil futures price volatility in the framework of the…”
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  5. 5

    Out‐of‐sample volatility prediction: A new mixed‐frequency approach by Zhang, Yaojie, Ma, Feng, Wang, Tianyi, Liu, Li

    Published in Journal of forecasting (01-11-2019)
    “…This paper proposes a new mixed‐frequency approach to predict stock return volatilities out‐of‐sample. Based on the strategy of momentum of predictability…”
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  6. 6

    Convolutional multi-head self-attention on memory for aspect sentiment classification by Zhang, Yaojie, Xu, Bing, Zhao, Tiejun

    Published in IEEE/CAA journal of automatica sinica (01-07-2020)
    “…This paper presents a method for aspect based sentiment classification tasks, named convolutional multi-head self-attention memory network &#x0028 CMA-MemNet…”
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  7. 7

    Forecasting stock returns: Do less powerful predictors help? by Zhang, Yaojie, Zeng, Qing, Ma, Feng, Shi, Benshan

    Published in Economic modelling (01-05-2019)
    “…This paper proposes a simple but efficient way to improve the predictability of stock returns. Instead of torturously constructing new powerful predictors, we…”
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  8. 8

    Investors’ perspective on forecasting crude oil return volatility: Where do we stand today? by Liu, Li, Geng, Qianjie, Zhang, Yaojie, Wang, Yudong

    “…In this paper, we review studies of oil volatility prediction from a new perspective: that of investors who require economic evaluations of forecasting…”
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  9. 9

    Modelling and forecasting crude oil price volatility with climate policy uncertainty by He, Mengxi, Zhang, Yaojie, Wang, Yudong, Wen, Danyan

    “…The impact of climate risk on economic and financial fields has attracted considerable interest from academics and practitioners. Recent literature documents…”
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  10. 10

    The Light- and Jasmonic Acid-Induced AaMYB108-like Positive Regulates the Initiation of Glandular Secretory Trichome in Artemisia annua L by Liu, Hang, He, Weizhi, Yao, Xinghao, Yan, Xin, Wang, Xiuyun, Peng, Bowen, Zhang, Yaojie, Shao, Jin, Hu, Xinyi, Miao, Qing, Li, Ling, Tang, Kexuan

    “…The plant Artemisia annua L. is famous for producing “artemisinin”, which is an essential component in the treatment of malaria. The glandular secretory…”
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  11. 11

    Engineering the expression of plant secondary metabolites-genistein and scutellarin through an efficient transient production platform in Nicotiana benthamiana L by Yao, Xinghao, Wuzhang, Kuanyu, Peng, Bowen, Chen, Tiantian, Zhang, Yaojie, Liu, Hang, Li, Ling, Fu, Xueqing, Tang, Kexuan

    Published in Frontiers in plant science (06-09-2022)
    “…Plant natural products (PNPs) are active substances indispensable to human health with a wide range of medical and commercial applications. However, excessive…”
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  12. 12

    Facile and Efficient Fabrication of Bandgap Tunable Carbon Quantum Dots Derived From Anthracite and Their Photoluminescence Properties by Jia, Jianbo, Sun, Yue, Zhang, Yaojie, Liu, Quanrun, Cao, Jianliang, Huang, Guangxu, Xing, Baolin, Zhang, Chuanxiang, Zhang, Lina, Cao, Yijun

    Published in Frontiers in chemistry (28-02-2020)
    “…Low-cost and earth-abundant coal has been considered to have a unique structural superiority as carbon sources of carbon quantum dots (CQDs). However, it is…”
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  13. 13

    An Effective Strategy to Synthesize Well-Designed Activated Carbon Derived from Coal-Based Carbon Dots via Oxidation before Activation with a Low KOH Content as Supercapacitor Electrodes by Zhang, Yaojie, Jia, Jianbo, Sun, Yue, Xu, Bing, Jiang, Zhendong, Qu, Xiaoxiao, Zhang, Chuanxiang

    Published in Nanomaterials (Basel, Switzerland) (01-11-2023)
    “…The development of coal-based activated carbon for supercapacitors provides a robust and effective approach toward the clean and efficient use of coal, and it…”
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  14. 14

    To jump or not to jump: momentum of jumps in crude oil price volatility prediction by Zhang, Yaojie, Wang, Yudong, Ma, Feng, Wei, Yu

    Published in Financial innovation (Heidelberg) (06-06-2022)
    “…A well-documented finding is that explicitly using jumps cannot efficiently enhance the predictability of crude oil price volatility. To address this issue, we…”
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  15. 15

    A high-efficiency Agrobacterium-mediated transient expression system in the leaves of Artemisia annua L by Li, Yongpeng, Chen, Tiantian, Wang, Wei, Liu, Hang, Yan, Xin, Wu-Zhang, Kuanyu, Qin, Wei, Xie, Lihui, Zhang, Yaojie, Peng, Bowen, Yao, Xinghao, Wang, Chen, Kayani, Sadaf-Ilyas, Fu, Xueqing, Li, Ling, Tang, Kexuan

    Published in Plant methods (16-10-2021)
    “…Abstract Background The Agrobacterium -mediated transient transformation, which proved effective in diverse plant species, has been widely applied for…”
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  16. 16

    JoSDW: Combating Noisy Labels by Dynamic Weight by Zhang, Yaojie, Xu, Huahu, Xiao, Junsheng, Bian, Minjie

    Published in Future internet (01-02-2022)
    “…The real world is full of noisy labels that lead neural networks to perform poorly because deep neural networks (DNNs) are prone to overfitting label noise…”
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  17. 17

    A high-efficiency trichome collection system by laser capture microdissection by Qin, Wei, Li, Yongpeng, Peng, Bowen, Liu, Hang, Chen, Tiantian, Yan, Xin, Zhang, Yaojie, Wang, Chen, Yao, Xinghao, Fu, Xueqing, Li, Ling, Tang, Kexuan

    Published in Frontiers in plant science (22-08-2022)
    “…Trichomes, which are classified as glandular or non-glandular, are hair-like epidermal structures that are present on aerial parts of most plant species…”
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  18. 18

    Matching is the Key Factor to Improve the Production of Patchoulol in the Plant Chassis of Marchantia paleacea by Zhang, Yaojie, Zhou, Lu, Tang, Kexuan, Xu, Meihui, Miao, Zhiqi

    Published in ACS omega (29-12-2020)
    “…The valuable terpenoids, such as artemisinin acid, have achieved bioproduction in the chassis of microbes recently. In this study, Marchantia paleacea L, a…”
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  19. 19

    AaWRKY17, a positive regulator of artemisinin biosynthesis, is involved in resistance to Pseudomonas syringae in Artemisia annua by Chen, Tiantian, Li, Yongpeng, Xie, Lihui, Hao, Xiaolong, Liu, Hang, Qin, Wei, Wang, Chen, Yan, Xin, Wu-Zhang, Kuanyu, Yao, Xinghao, Peng, Bowen, Zhang, Yaojie, Fu, Xueqing, Li, Ling, Tang, Kexuan

    Published in Horticulture research (01-10-2021)
    “…Artemisia annua , a traditional Chinese medicinal plant, remains the only plant source for artemisinin production, yet few genes have been identified to be…”
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  20. 20

    Forecasting crude oil futures market returns: A principal component analysis combination approach by Zhang, Yaojie, Wang, Yudong

    Published in International journal of forecasting (01-04-2023)
    “…To improve the predictability of crude oil futures market returns, this paper proposes a new combination approach based on principal component analysis (PCA)…”
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