Browsing by Author "Zhang, Min"

Now showing 1 - 5 of 5
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    Genome sequences of wild and domestic bactrian camels
    Jirimutu; Wang, Zhen; Ding, Guohui; Chen, Gangliang; Sun, Yamin; Sun, Zhihong; Zhang, Heping; Wang, Lei; Hasi, Surong; Zhang, Yan; Li, Jianmei; Shi, Yixiang; Xu, Ze; He, Chuan; Yu, Siriguleng; Li, Shengdi; Zhang, Wenbin; Batmunkh, Mijiddorj; Ts, Batsukh; Narenbatu; Unierhu; Bat-Ireedui, Shirzana; Gao, Hongwei; Baysgalan, Banzragch; Li, Qing; Jia, Zhiling; Turigenbayila; Subudenggerile; Narenmanduhu; Wang, Zhaoxia; Wang, Juan; Pan, Lei; Chen, Yongcan; Ganerdene, Yaichil; Dabxilt; Erdemt; Altansha; Altansukh; Liu, Tuya; Cao, Minhui; Aruuntsever; Bayart; Hosblig; He, Fei; Zha-ti, A.; Zheng, Guangyong; Qiu, Feng; Sun, Zikui; Zhao, Lele; Zhao, Wenjing; Liu, Baohong; Li, Chao; Chen, Yunqin; Tang, Xiaoyan; Guo, Chunyan; Liu, Wei; Ming, Liang; Temuulen; Cui, Aiying; Li, Yi; Gao, Junhui; Li, Jing; Wurentaodi; Niu, Shen; Sun, Tao; Zhai, Zhengxiao; Zhang, Min; Chen, Chen; Baldan, Tunteg; Bayaer, Tuman; Li, Yixue; Meng, He (Springer Nature, 2012-11)
    Bactrian camels serve as an important means of transportation in the cold desert regions of China and Mongolia. Here we present a 2.01 Gb draft genome sequence from both a wild and a domestic bactrian camel. We estimate the camel genome to be 2.38 Gb, containing 20,821 protein-coding genes. Our phylogenomics analysis reveals that camels shared common ancestors with other even-toed ungulates about 55-60 million years ago. Rapidly evolving genes in the camel lineage are significantly enriched in metabolic pathways, and these changes may underlie the insulin resistance typically observed in these animals. We estimate the genome-wide heterozygosity rates in both wild and domestic camels to be 1.0 x 10(-3). However, genomic regions with significantly lower heterozygosity are found in the domestic camel, and olfactory receptors are enriched in these regions. Our comparative genomics analyses may also shed light on the genetic basis of the camel's remarkable salt tolerance and unusual immune system.
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    Research on sub/super-synchronous oscillation suppression method for direct-drive wind turbine based on energy compensation
    Ma, Jing; Zhang, Min; Phadke, Arun G. (2021-08-17)
    A method to suppress sub/super-synchronous oscillation of direct-drive wind turbines based on energy compensation is proposed. First, the transient energy model of direct-drive wind turbine is built, and the negative damping energy terms that lead the oscillation of direct-drive wind turbine are extracted. On this basis, the expressions of voltage compensation terms corresponding to negative damping energy terms are derived by backward deduction, thus supplementary energy branches are constructed, and their impact on fundamental frequency characteristics of wind turbine is analyzed. And then, with the compensation energy of supplementary branches reaching the maximum and the increment of fundamental-frequency voltage being the minimum as the objective, and with the frequency-domain characteristic and fundamental-frequency voltage characteristic of control links being satisfied as constraints, a scheme to optimize the compensation coefficients of multiple branches is established. Finally, the model of direct-drive wind turbine is built in RT-LAB for hardware-in-the-loop tests. Simulation results verify that, the method can realize fast frequency-dependent suppression of sub/super-synchronous oscillation in different frequency bands concerning different grid strengths.
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    Risk Assessment in Chinese Hospitalized Patients Comparing the Padua and Caprini Scoring Algorithms
    Chen, Xiaolan; Pan, Lei; Deng, Hui; Zhang, Jingyuan; Tong, Xinjie; Huang, He; Zhang, Min; He, Jianlin; Caprini, Joseph A.; Wang, Yong (2018-12)
    The current venous thromboembolism (VTE) guidelines recommend all patients to be assessed for the risk of VTE using risk assessment models (RAMs). The study was to evaluate the performance of the Caprini and Padua RAMs among Chinese hospitalized patients. We reviewed data from 189 patients with deep venous thrombosis (DVT) and 201 non-DVT patients. Deep venous thrombosis risk factors were obtained from all patients. The sensitivity and specificity of the Caprini and Padua scores for all patients were calculated. The receiver operating curve (ROC) and the area under the ROC curve (AUC) were used to evaluate the performance of each score. We documented that age, acute infection, prothrombin time (PT), D-dimer, erythrocyte sedimentation rate, blood platelets, and anticoagulation were significantly associated with the occurrence of DVT (P < .05). These results were true for all medical and surgical patients group (G1), as well as the analysis of medical versus surgical patients (G2). Finally, analysis of the scores in patients with and without cancer was also done (G3). The Caprini has a higher sensitivity but a lower specificity than the Padua (P < .05). Caprini has a better predictive ability for the first 2 groups (P < .05). We found Caprini and Padua scores have a similar predictive value for patients with cancer (P > .05), while Caprini has a higher predictive ability for no cancer patients in G3 than Padua (P < .05). For Chinese hospitalized patients, Caprini has a higher sensitivity but a lower specificity than Padua. Overall, Caprini RAM has a better predictive ability than Padua RAM.
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    Self-Correlation and Cross-Correlation Learning for Few-Shot Remote Sensing Image Semantic Segmentation
    Wang, Linhan; Lei, Shuo; He, Jianfeng; Wang, Shengkun; Zhang, Min; Lu, Chang-Tien (ACM, 2023-11-13)
    Remote sensing image semantic segmentation is an important problem for remote sensing image interpretation. Although remarkable progress has been achieved, existing deep neural network methods suffer from the reliance on massive training data. Few-shot remote sensing semantic segmentation aims at learning to segment target objects from a query image using only a few annotated support images of the target class. Most existing few-shot learning methods stem primarily from their sole focus on extracting information from support images, thereby failing to effectively address the large variance in appearance and scales of geographic objects. To tackle these challenges, we propose a Self-Correlation and Cross-Correlation Learning Network for the few-shot remote sensing image semantic segmentation. Our model enhances the generalization by considering both self-correlation and cross-correlation between support and query images to make segmentation predictions. To further explore the self-correlation with the query image, we propose to adopt a classical spectral method to produce a class-agnostic segmentation mask based on the basic visual information of the image. Extensive experiments on two remote sensing image datasets demonstrate the effectiveness and superiority of our model in few-shot remote sensing image semantic segmentation. The code is available at https://github.com/linhanwang/SCCNet.
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    Urbanization and Income Inequality in Post-Reform China: A Causal Analysis Based on Time Series Data
    Chen, Guo; Glasmeier, Amy K.; Zhang, Min; Shao, Yang (PLOS, 2016-07-19)
    This paper investigates the potential causal relationship(s) between China’s urbanization and income inequality since the start of the economic reform. Based on the economic theory of urbanization and income distribution, we analyze the annual time series of China’s urbanization rate and Gini index from 1978 to 2014. The results show that urbanization has an immediate alleviating effect on income inequality, as indicated by the negative relationship between the two time series at the same year (lag = 0). However, urbanization also seems to have a lagged aggravating effect on income inequality, as indicated by positive relationship between urbanization and the Gini index series at lag 1. Although the link between urbanization and income inequality is not surprising, the lagged aggravating effect of urbanization on the Gini index challenges the popular belief that urbanization in post-reform China generally helps reduce income inequality. At deeper levels, our results suggest an urgent need to focus on the social dimension of urbanization as China transitions to the next stage of modernization. Comprehensive social reforms must be prioritized to avoid a long-term economic dichotomy and permanent social segregation.