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136 results on '"Ren, Mingjian"'

6. Plant-microbe interactions in wheat to deal with abiotic stress

Author

Li, Xiaolan, primary, Ren, Qunli, additional, Liao, Chengcheng, additional, Wang, Qian, additional, Ren, Mingjian, additional, Zhang, Mingsheng, additional, Qian, Xiaokang, additional, Yang, Shengwei, additional, Hu, Huan, additional, Wang, Miao, additional, and Liu, Jianguo, additional

Published
2023
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14. Threshold quantile regression neural network.

Author

Yang, Lixiong, Bai, Hujie, and Ren, Mingjian

Subjects
QUANTILE regression, MONTE Carlo method, ARTIFICIAL neural networks, FORECASTING, STATISTICS
Abstract

For modelling the threshold effect in parameters of the quantile neural network models, this paper introduces a model called threshold quantile regression neural network (TQRNN), which allows a threshold effect in the quantile regression neural network (QRNN). We develop the estimation procedure of the proposed model and suggest test statistics for threshold effect and the linear setting used typically in the quantile regression framework. We conduct Monte Carlo simulations to assess the performance of estimation and testing procedures, and compare the forecasting performance of the TQRNN model relative to the QRNN model. Through Monte Carlo simulations, we show that the estimation and testing procedures work well in finite samples, and there is little loss in forecast accuracy by employing the suggested TQRNN model even when the true data is generated from a QRNN model; on the contrary, ignoring an existing threshold effect can deteriorate the forecast accuracy of the QRNN model. All the simulation results support the usefulness of the TQRNN model. [ABSTRACT FROM AUTHOR]

Published
2024
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19. Panel threshold model with covariate-dependent thresholds and unobserved individual-specific threshold effects.

Author

Yang, Lixiong, Chen, I-Po, Lee, Chingnun, and Ren, Mingjian

Subjects
MONTE Carlo method, CASH flow, ECONOMIC expansion, DYNAMIC models, EMPIRICAL research
Abstract

This article introduces a panel threshold model with covariate-dependent and time-varying thresholds and unobserved individual-specific threshold effects (PTCDI). We develop methods for estimation and inference for threshold parameters in the proposed PTCDI model by employing the correlated random effects (CRE) device. We also suggest test statistics for linearity, threshold constancy, unobserved individual-specific threshold effects, and for determining the number of thresholds. We derive the asymptotic properties of the proposed estimator in the small-threshold-effect framework and establish the limiting distributions of the suggested test statistics. We also investigate the extension to dynamic panels and show that both the static and dynamic models can be handled uniformly in the CRE framework. Monte Carlo simulation results indicate that the estimation, inference, and testing procedures have the desired performance in finite samples. The model is illustrated with two empirical applications to the relationship between cash flow and investment and the nexus between inflation and economic growth. [ABSTRACT FROM AUTHOR]

Published
2024
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24. ADMM-Net for Beamforming Based on Linear Rectification with the Atomic Norm Minimization.

Author

Gong, Zhenghui, Zhang, Xinyu, Ren, Mingjian, Su, Xiaolong, and Liu, Zhen

Subjects
BEAMFORMING, NOISE, ALGORITHMS, RADAR interference
Abstract

Target misalignment can cause beam pointing deviations and degradation of sidelobe performance. In order to eliminate the effect of target misalignment, we formulate the jamming sub-space recovery problem as a linearly modified atomic norm-based optimization. Then, we develop a deep-unfolding network based on the alternating direction method of multipliers (ADMM), which effectively improves the applicability and efficiency of the algorithm. By using the back-propagation process of deep-unfolding networks, the proposed method could optimize the hyper-parameters in the original atomic norm. This feature enables the adaptive beamformer to adjust its weight according to the observed data. Specifically, the proposed method could determine the optimal hyper-parameters under different interference noise matrix conditions. Simulation results demonstrate that the proposed network could reduce computational cost and achieve near-optimal performance with low complexity. [ABSTRACT FROM AUTHOR]

Published
2024
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29. Genome-wide analysis of the Tritipyrum WRKY gene family and the response of TtWRKY256 in salt-tolerance

Author

Li, Kuiyin, Liu, Xiaojuan, He, Fang, Chen, Songshu, Zhou, Guangyi, Wang, Yuhai, Li, Luhua, Zhang, Suqin, Ren, Mingjian, and Yuan, Yuanyuan

Subjects
Plant Science
Abstract

IntroductionThe transcription factor WRKY is widespread in the plant kingdom and plays a crucial role in diverse abiotic stress responses in plant species. Tritipyrum, an octoploid derived from an intergeneric cross between Triticum aestivum (AABBDD) and Thinopyrum elongatum (EE), is a valuable germplasm resource for introducing superior traits of Th. elongatum into T. aestivum. The recent release of the complete genome sequences of T. aestivum and Th. elongatum enabled us to investigate the organization and expression profiling of Tritipyrum WRKY genes across the entire genome.ResultsIn this study, 346 WRKY genes, from TtWRKY1 to TtWRKY346, were identified in Tritipyrum. The phylogenetic analysis grouped these genes into three subfamilies (I-III), and members of the same subfamilies shared a conserved motif composition. The 346 TtWRKY genes were dispersed unevenly across 28 chromosomes, with 218 duplicates. Analysis of synteny suggests that the WRKY gene family may have a common ancestor. Expression profiles derived from transcriptome data and qPCR demonstrated that 54 TtWRKY genes exhibited relatively high levels of expression across various salt stresses and recovery treatments. Tel1E01T143800 (TtWRKY256) is extremely sensitive to salt stress and is on the same evolutionary branch as the salt-tolerant A. thaliana genes AtWRKY25 and AtWRKY33. From 'Y1805', the novel AtWRKY25 was cloned. The Pearson correlation analysis identified 181 genes that were positively correlated (R>0.9) with the expression of TtWRKY256, and these genes were mainly enriched in metabolic processes, cellular processes, response to stimulus, biological regulation, and regulation of biological. Subcellular localization and qRT-PCR analysis revealed that TtWRKY256 was located in the nucleus and was highly expressed in roots, stems, and leaves under salt stress.DiscussionThe above results suggest that TtWRKY256 may be associated with salt stress tolerance in plants and may be a valuable alien gene for improving salt tolerance in wheat.

Published
2022
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35. Selection Signatures in Chinese Sorghum Reveals Its Unique Liquor-Making Properties

Author

Zhang, Liyi, primary, Ding, Yanqing, additional, Xu, Jianxia, additional, Gao, Xu, additional, Cao, Ning, additional, Li, Kuiying, additional, Feng, Zhou, additional, Cheng, Bing, additional, Zhou, Lengbo, additional, Ren, Mingjian, additional, Lu, Xiaochun, additional, Bao, Zhigui, additional, Tao, Yuezhi, additional, Xin, Zhanguo, additional, and Zou, Guihua, additional

Published
2022
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37. Additional file 4 of Genome-wide identification, phylogenetic analysis, and expression profiles of trihelix transcription factor family genes in quinoa (Chenopodium quinoa Willd.) under abiotic stress conditions

Author

Li, Kuiyin, Fan, Yue, Zhou, Guangyi, Liu, Xiaojuan, Chen, Songshu, Chang, Xiangcai, Wu, Wenqiang, Duan, Lili, Yao, Maoxing, Wang, Rui, Wang, Zili, Yang, Mingfang, Ding, Yanqing, Ren, Mingjian, Fan, Yu, and Zhang, Liyi

Abstract

Additional file 4: Figure S2. Schematic representation of the chromosomal distribution of the C.quinoa trihelix genes.

Published
2022
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38. Additional file 3 of Genome-wide identification, phylogenetic analysis, and expression profiles of trihelix transcription factor family genes in quinoa (Chenopodium quinoa Willd.) under abiotic stress conditions

Author

Li, Kuiyin, Fan, Yue, Zhou, Guangyi, Liu, Xiaojuan, Chen, Songshu, Chang, Xiangcai, Wu, Wenqiang, Duan, Lili, Yao, Maoxing, Wang, Rui, Wang, Zili, Yang, Mingfang, Ding, Yanqing, Ren, Mingjian, Fan, Yu, and Zhang, Liyi

Abstract

Additional file 3: Figure S1. Distribution of cis-acting elements in the promoter region of the CqTH gene family.

Published
2022
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39. Additional file 6 of Genome-wide identification, phylogenetic analysis, and expression profiles of trihelix transcription factor family genes in quinoa (Chenopodium quinoa Willd.) under abiotic stress conditions

Author

Li, Kuiyin, Fan, Yue, Zhou, Guangyi, Liu, Xiaojuan, Chen, Songshu, Chang, Xiangcai, Wu, Wenqiang, Duan, Lili, Yao, Maoxing, Wang, Rui, Wang, Zili, Yang, Mingfang, Ding, Yanqing, Ren, Mingjian, Fan, Yu, and Zhang, Liyi

Abstract

Additional file 6: Figure S3. Phylogenetic relationship and motif composition of the trihelix proteins from C.quinoa with five different plant species.

Published
2022
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47. Contributors

Author

Adhikary, Saju, Afroz, Nadia, Agarwal, Disha, Agrawal, Yamini, Ahmad, Zeeshan, Alharbi, Saif, Ali, Mohammed Anwar, Alotaibi, Fahad, Alrajhi, Abdullah, Ameen, Muhammad, Amzad, Mst. Anamika, Anjali, Annu, Ansary, Most. Waheda Rahman, Anuragi, Hirdayesh, Arifuzzaman, Md., Athar, Tabinda, Atta, Kousik, Baidya, Ananya, Batool, Aneesa, Baviskar, Vijendra S., Bera, Anurag, Bhutia, K.L., Chang, Cheng, Chowdhury, Shukti Rani, Dash, Sri Sai Subramnyam, Desai, Shreenivas A., Deswal, Kapil, Devi, Yengkhom Linthoingambi, Dubey, Rajiv, Dutta, Debjani, Germ, Mateja, Gezgin, Sait, Gokmen Yilmaz, Fatma, Gopalareddy, K., Goyal, Alisha, Gunasekera, Dinoo, Hamurcu, Mehmet, Hasanuzzaman, M., Hena, Mst. Hasna, Hossain, Akbar, Hu, Huan, Ilyas, Ashal, Islam, Md. Rafiqul, Islam, Tofazzal, Jui, Sohana, Karmakar, Snehashis, Kesarwani, Amit, Keya, Ayesha Azad, Khan, Mohd. Kamran, Kumar, Manoj, Kumar, Mukesh, Kumar, Pawan, Kumari, Anita, Lakra, Nita, Li, Haoyu, Li, Xiaolan, Liao, Chengcheng, Liu, Jianguo, Maitra, Sagar, Majeed, Sadia, Malik, Hina Ahmed, Malik, Riffat Naseem, Manorma, Masuda, Mst. Salma, Meenakshi, Mia, M.A. Baset, Mishra, Udit Nandan, Mondal, Saptarshi, Mondal, Subhasis, Mosfeq-Ul-Hasan, Md., Mukherjee, Soumik, Munjal, Renu, Mushrat, Zarin, Myskova, Aneta, Navathe, Sudhir, Oak, Manoj D., Pal, Apurba, Pandey, Anamika, Pandey, Himanshu, Panwar, Megha, Patil, Ravindra, Pawar, Pravin Bhausaheb, Poddar, Nitesh Kumar, Pramanick, Biswajit, Pramanick, Sankar, Prodhan, Most. Maria Haque, Qian, Xiaokang, Quraishi, Umar Masood, Ram, Hanuman, Rana, Vineeta, Ranjan, Sudarshana, Ratnasekera, Disna, Reena, Ren, Mingjian, Ren, Qunli, Roy, Disha, Rustagi, Anjana, Sadhukhan, Rahul, Saeed, Muhammad, Sarker, Ajanta, Shah, Maksud Hasan, Sharma, Shreya, Singh, Aditya Pratap, Singh, Sanjay Kumar, Singhal, Rajesh Kumar, Soni, Aarti, Swami, Pooja, Talaat, Neveen B., Topal, Ali, Turin, Mst. Tanjina Shahanaj, Venkatesan, Suhasini, Wang, Miao, Wang, Qian, Wang, Xiaoyu, Yadav, Devvart, Yang, Shengwei, Yang, Zige, Yashavanthakumar, K.J., Yousaf, Hamza, Zargar, Sajad Majeed, Zhang, Mingsheng, and Zhi, Pengfei

Published
2023
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