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14,267 results on '"Hao Li"'

17. Tirofiban for Stroke without Large or Medium-Sized Vessel Occlusion

Author

Wenjie Zi, Jiaxing Song, Weilin Kong, Jiacheng Huang, Changwei Guo, Wencheng He, Yinquan Yu, Bo Zhang, Wanjie Geng, Xiaolin Tan, Yaoyu Tian, Zongtao Liu, Minghua Cao, Daoyou Cheng, Bo Li, Wenguo Huang, Junsheng Liu, Pengfei Wang, Zhou Yu, Hao Liang, Shuang Yang, Mingshan Tang, Wenhua Liu, Xianjun Huang, Shugai Liu, Yufeng Tang, Youlin Wu, Li Yao, Zhu Shi, Pengcheng He, Haojin Zhao, Zhuo Chen, Jun Luo, Yue Wan, Qiang Shi, Maorong Wang, De Yang, Xianglin Chen, Fang Huang, Jinlin Mu, Hao Li, Zhimin Li, Jingbang Zheng, Shunli Xie, Tieying Cai, Yuqi Peng, Weihua Xie, Zhongming Qiu, Chang Liu, Chengsong Yue, Linyu Li, Yan Tian, Dahong Yang, Jian Miao, Jie Yang, Jinrong Hu, Raul G. Nogueira, Duolao Wang, Jeffrey L. Saver, Fengli Li, and Qingwu Yang

Subjects
General Medicine
Published
2023

22. Indobufen versus aspirin in patients with acute ischaemic stroke in China (INSURE): a randomised, double-blind, double-dummy, active control, non-inferiority trial

Author

Yuesong Pan, Xia Meng, Baoshi Yuan, S Claiborne Johnston, Hao Li, Philip M Bath, Qiang Dong, Anding Xu, Jing Jing, Jinxi Lin, Yong Jiang, Xuewei Xie, Aoming Jin, Yue Suo, Hongqin Yang, Yefang Feng, Yanhua Zhou, Qing Liu, Xueli Li, Bin Liu, Hui Zhu, Jinguo Zhao, Xuerong Huang, Haitao Li, Yunyun Xiong, Zixiao Li, Yilong Wang, Xingquan Zhao, Liping Liu, Yongjun Wang, Yanxia Wang, Cunrui Wang, Yazhou Han, Ming Yu, Guoping Zou, Aisheng Wu, Guiru Zhang, Ping Zhang, Mingzong Yan, Jia Zhang, Jingyan Zhao, Huitian Zhang, Qinde Qi, Jianling Zhang, Zhishan Zhu, Wenfeng Fan, Liguo Chang, Lan Tan, Liang Zhao, Yanzhong Xue, Peiru Liu, Xiaohua Ju, Zuowen Zhang, Linwen Li, Feng Wei, Lixia Yang, Xuemei Li, Zhixiong Zheng, Hui Liang, Yan Wei, Ming Zhang, Ting Wang, Jianbo Yang, Panbing Huang, Guojun Tan, Yongming Chen, Jin Zhou, Zhongping An, Chunlei Li, Guohua Chen, Runxiu Zhu, Xin Sun, Yong Liu, Mei Zhang, Yanguang Zhuo, Fanwen Meng, Kebo Li, Wei Zhang, Xiangting Chai, Ke Deng, Jianhua Li, Zhiyou Cai, Hailian Jin, Bo Li, Xiaomei Zhang, Beihai Ge, Wei Hu, Zhen Jiao, Lianmei Zhong, Lijie Ren, Xinyi Li, Songdi Wu, Yinguo Wan, Jinghua Zhang, Xiaoyan Ma, Jizheng Hu, Ge Zhang, Chunling Zheng, Jun Xu, YuAn Zou, Zhihui Duan, Changxin Li, Qingxiu Zhang, Xiaoming Song, Zhengchang Jia, Chun Wang, Peining Shao, Jijun Teng, Hua Bao, Yangkun Chen, Yunfei Wei, Xu Zhang, Xisi Meng, Guangning Li, Pengke Pan, Aixia Zhuang, Xiaofei Chen, Jun Tang, Hongwei An, Shihao You, Yanyan Tang, Guilian Zhang, Hongyan Li, Miao Guo, Chunlei Yu, Ying Li, Haichao Liu, Pengfei Liang, Guangming Kang, Huijie Sun, Yu Che, Juan Tang, Dandan Li, Xiaopeng Feng, Yu Geng, Huibing Wang, Ping Shen, Huaiping Zhu, Farong Li, Lifang Zhang, Minghua Cao, Yong You, Guiyun Cui, Jun Gu, Xiangfeng Zhang, Xiaojun Liu, Houqin Chen, Yuehua Zhang, Hongnian Zhao, Ke Liang, Rui Zhi, Ling Ma, Yuanhua Wu, Yalan Geng, Ping Sun, Bing Zhong, Dongxue Li, Jingya Jiao, Yanlei Hao, Guozhong Li, Shaohua Su, Weiping Ju, Lianqiu Min, Liyan Guo, Yafei Shangguan, Yingdong Tai, Ying Xing, Hongshan Chang, Wenya Chen, Hongtao Tang, Shuchun Huang, Jingxian Fang, Donghui Yu, Hailong Zhao, Lei Xu, Aimei Wu, Hebin Wan, Hongliang Wang, Zhihui Shen, Qing Zhang, and Qian Wang

Subjects
Neurology (clinical)
Published
2023

25. Focusing on scRNA-seq-Derived T Cell-Associated Genes to Identify Prognostic Signature and Immune Microenvironment Status in Low-Grade Glioma

Author

Jiayu Wen, Qiaoyi Huang, Jiuxiu Yao, Wei Wei, Zehui Li, Huiqin Zhang, Surui Chang, Hui Pei, Yu Cao, and Hao Li

Subjects
Immunology, Cell Biology
Abstract

Background. The clinical outcomes of low-grade glioma (LGG) are associated with T cell infiltration, but the specific contribution of heterogeneous T cell types remains unclear. Method. To study the different functions of T cells in LGG, we mapped the single-cell RNA sequencing results of 10 LGG samples to obtain T cell marker genes. In addition, bulk RNA data of 975 LGG samples were collected for model construction. Algorithms such as TIMER, CIBERSORT, QUANTISEQ, MCPCOUTER, XCELL, and EPIC were used to depict the tumor microenvironment landscape. Subsequently, three immunotherapy cohorts, PRJEB23709, GSE78820, and IMvigor210, were used to explore the efficacy of immunotherapy. Results. The Human Primary Cell Atlas was used as a reference dataset to identify each cell cluster; a total of 15 cell clusters were defined and cells in cluster 12 were defined as T cells. According to the distribution of T cell subsets (CD4+ T cell, CD8+ T cell, Naïve T cell, and Treg cell), we selected the differentially expressed genes. Among the CD4+ T cell subsets, we screened 3 T cell-related genes, and the rest were 28, 4, and 13, respectively. Subsequently, according to the T cell marker genes, we screened six genes for constructing the model, namely, RTN1, HERPUD1, MX1, SEC61G, HOPX, and CHI3L1. The ROC curve showed that the predictive ability of the prognostic model for 1, 3, and 5 years was 0.881, 0.817, and 0.749 in the TCGA cohort, respectively. In addition, we found that risk scores were positively correlated with immune infiltration and immune checkpoints. To this end, we obtained three immunotherapy cohorts to verify their predictive ability of immunotherapy effects and found that high-risk patients had better clinical effects of immunotherapy. Conclusion. This single-cell RNA sequencing combined with bulk RNA sequencing may elucidate the composition of the tumor microenvironment and pave the way for the treatment of low-grade gliomas.

Published
2023

28. Joint Intent Detection Model for Task-oriented Human-Computer Dialogue System using Asynchronous Training

Author

Yirui Wu, Hao Li, Lilai Zhang, Chen Dong, Qian Huang, and Shaohua Wan

Subjects
General Computer Science
Abstract

How to accurately understand low-resource languages is the core of the task-oriented human-computer dialogue system. Language understanding consists of two sub-tasks, i.e., intent detection and slot filling. Intent detection still faces challenges due to semantic ambiguity and implicit intentions with users’ input. Moreover, separately modeling intent detection and slot filling significantly decrease the correctness and relevance between questions and answers. To address these issues, we propose a joint intent detection method using asynchronous training strategy. The proposed method firstly encodes local text information extracted by CNN and relationship information among words emphasized by attention structure. Later, a joint intent detection model with asynchronous training strategy is proposed by either fusing hidden states of intent detection and slot filling layers, or adopting the key information to fine-tune the whole network, greatly increasing the relevance of intent detection and slot filling subtasks. The accuracy achieved by the proposed method tested on an open-source airline travel dataset and a self-collected electricity service dataset, i.e., ATIS and ECSF, are 97.49% and 89.68%, respectively, which proves the effectiveness of joint learning and asynchronous training.

Published
2023

30. Two new species of the spider genus Putaoa (Araneae, Linyphiidae) from southern China

Author

JINXIN LIU, XIANG XU, GUSTAVO HORMIGA, HAIQIANG YIN, and HAO LI

Subjects
Arthropoda, Arachnida, Animalia, Araneae, Pimoidae, Animal Science and Zoology, Biodiversity, Ecology, Evolution, Behavior and Systematics, Taxonomy
Abstract

Two new species of the genus Putaoa Hormiga and Tu, 2008 from southern China are described, Putaoa annulata n. sp. (♂♀) and Putaoa titanoverpa n. sp. (♂♀), for a total number of five described species in this genus. Detailed descriptions and illustrations of the two new species are provided. A map of collecting localities is also provided for all five Putaoa species.

Published
2023

37. Clinical efficacy of low-dose glucocorticoid therapy for critically ill patients with severe fever with thrombocytopenia syndrome: A retrospective cohort study

Author

Gang Wang, Yan-Li Xu, Ying Zhu, Ming Yue, Jing Zhao, Hong-Han Ge, Xiao-Lei Ye, Yuan-Ni Liu, Xiao-Yi Gong, Li-Gang Zhang, Shu-Ying Geng, Jia-Hao Chen, Jing-Tao Zhang, Ning Cui, Chun Yuan, Zhen-Yu Hu, Xiao-Ai Zhang, Hao Li, Ling Lin, and Wei Liu

Subjects
Microbiology (medical), Infectious Diseases, General Medicine
Published
2023

39. Early-Life Cardiovascular Risk Factor Trajectories and Vascular Aging in Midlife: A 30-Year Prospective Cohort Study

Author

Yang Wang, Jie Wang, Xiao-Wei Zheng, Ming-Fei Du, Xi Zhang, Chao Chu, Dan Wang, Yue-Yuan Liao, Qiong Ma, Hao Jia, Gui-Lin Hu, Yu Yan, Yue Sun, Chen Chen, Xiao-Yu Zhang, Hao Li, Ting Zou, Ze-Jiaxin Niu, Zi-Yue Man, Lan Wang, Wen-Jing Luo, Guan-Ji Wu, Yu-Ming Kang, John Chang, Christian Delles, Yao Lu, and Jian-Jun Mu

Subjects
Internal Medicine
Abstract

Background: Vascular aging, as assessed by structural and functional arterial properties, is an independent predictor of cardiovascular outcomes. We aimed to explore the associations of individual cardiovascular risk factors from childhood to midlife and their accumulation over a 30-year span with vascular aging in midlife. Methods: Using data from the ongoing cohort of Hanzhong Adolescent Hypertension study, 2180 participants aged 6 to 18 years at baseline were followed for over 30 years. Distinct trajectories of systolic blood pressure (SBP), body mass index (BMI), and heart rate from childhood to midlife were identified by group-based trajectory modeling. Vascular aging was assessed by carotid intima media thickness or brachial-ankle pulse wave velocity. Results: We identified 4 distinct SBP trajectories, 3 distinct BMI trajectories, and 2 distinct heart rate trajectories from childhood to midlife. Persistently increasing SBP, high-increasing BMI, and high-stable heart rate were all shown to have a positive association with brachial-ankle pulse wave velocity in midlife. For carotid intima–media thickness, similar associations were observed for persistently increasing SBP and high-increasing body mass index. After further adjustment for SBP, body mass index and heart rate at the time of vascular assessment in 2017, associations were also observed for cardiovascular risk factor trajectories accumulation with brachial-ankle pulse wave velocity (β, 0.656 [95% CI, 0.265–1.047]) and with carotid intima media thickness (β, 0.045 [95% CI, 0.011–0.079]) in adulthood. Conclusions: Longitudinal exposure to individual cardiovascular risk factors from childhood to midlife and cardiovascular risk factor accumulation were associated with an increased risk of vascular aging in midlife. Our study lends support for early targeting of risk factors in order to prevent cardiovascular disease later in life.

Published
2023

45. CODEBench: A Neural Architecture and Hardware Accelerator Co-Design Framework

Author

Shikhar Tuli, Chia-Hao Li, Ritvik Sharma, and Niraj K. Jha

Subjects
FOS: Computer and information sciences, Computer Science - Machine Learning, Hardware and Architecture, Hardware Architecture (cs.AR), Image and Video Processing (eess.IV), FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Hardware Architecture, Software, Machine Learning (cs.LG)
Abstract

Recently, automated co-design of machine learning (ML) models and accelerator architectures has attracted significant attention from both the industry and academia. However, most co-design frameworks either explore a limited search space or employ suboptimal exploration techniques for simultaneous design decision investigations of the ML model and the accelerator. Furthermore, training the ML model and simulating the accelerator performance is computationally expensive. To address these limitations, this work proposes a novel neural architecture and hardware accelerator co-design framework, called CODEBench. It is composed of two new benchmarking sub-frameworks, CNNBench and AccelBench, which explore expanded design spaces of convolutional neural networks (CNNs) and CNN accelerators. CNNBench leverages an advanced search technique, BOSHNAS, to efficiently train a neural heteroscedastic surrogate model to converge to an optimal CNN architecture by employing second-order gradients. AccelBench performs cycle-accurate simulations for a diverse set of accelerator architectures in a vast design space. With the proposed co-design method, called BOSHCODE, our best CNN-accelerator pair achieves 1.4% higher accuracy on the CIFAR-10 dataset compared to the state-of-the-art pair, while enabling 59.1% lower latency and 60.8% lower energy consumption. On the ImageNet dataset, it achieves 3.7% higher Top1 accuracy at 43.8% lower latency and 11.2% lower energy consumption. CODEBench outperforms the state-of-the-art framework, i.e., Auto-NBA, by achieving 1.5% higher accuracy and 34.7x higher throughput, while enabling 11.0x lower energy-delay product (EDP) and 4.0x lower chip area on CIFAR-10., Comment: Published at ACM Transactions on Embedded Computing Systems. Code available at https://github.com/jha-lab/codebench

Published
2023

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