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1,110 results on '"Shi, Yingying"'

155. Evaluation of the Rapid Antigen Detection Test for Diagnosing SARS-CoV-2 during the COVID-19 Pandemic: Experience from a Centralized Isolation Site in Shanghai, China

Author

Zhong, Xu, primary, Zhang, Li, additional, Ma, Di, additional, Shi, Yingying, additional, Wu, Jiayin, additional, Xu, Xiaosheng, additional, Chen, Weihong, additional, Wu, Beiwen, additional, Tang, Yiding, additional, Qu, Hongping, additional, Xie, Qing, additional, Yang, Yi, additional, Liu, Jialin, additional, and Xin, Haiguang, additional

Published
2023
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159. The Effect of Blood Velocity in Solid Tumor on Intratumorally Accumulation and Penetration of Nanocarriers and Drugs

Author

Wang, Sijie, primary, Zhang, Junlei, additional, Liu, Huihui, additional, Guo, Xuemeng, additional, Lu, Yichao, additional, Guan, Guannan, additional, Luo, Zhenyu, additional, Shi, Yingying, additional, Jiang, Mengshi, additional, Lin, Qing, additional, Zhou, Huanli, additional, Zhao, Xiaoqi, additional, Luo, Lihua, additional, and You, Jian, additional

Published
2023
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161. Knowledge Map Analysis of Environmental Regulation Research Hotspot Evolution in our Country

Author

Feng Lili, Shi Yingying, Feng xin, Li Jiapei, and Liu Yuan

Subjects
environmental regulation, Bibliography. Library science. Information resources
Abstract

[Purpose/significance] The current environmental challenges have become sensitive social and political issues in China. Sorting out existing environmental regulations have important implications for environmental regulation practices and theoretical development. [Method/process] This paper took 1473 CNKI core journal articles in the field of environmental regulation from January 1, 1998 to July 2, 2019 in China as analysis samples，used Citespace visual analysis method for time slicing，and took the keywords as the core，based on the hotspot cluster analysis，clarified the research evolution of environmental regulation and predicted future development trends to explore future research directions in the field of environmental regulation. [Result/conclusion]The research in the field of environmental regulation relies on the Porter hypothesis, environmental Kuznets curve, evolutionary game and other theoretical foundations, and mainly uses the spatial Dubin model, directional distance function and other research methods to analyze the field of environmental regulation in different periods. At present, research in the field of environmental regulation mostly focuses on the relationship between environmental regulation and technological innovation, economic development, industrial competitiveness, industrial structure, etc., but ignores the optimization of the environmental system, the degree of implementation of the environmental system by enterprises, regional differences in the environment, and the important role of cooperation between private organizations and the government in environmental governance, etc. Therefore, these have also become the development trend in the field of environmental regulation in the future.

Published
2021
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169. Nonlysosomal Route of mRNA Delivery and Combining with Epigenetic Regulation Optimized Antitumor Immunoprophylactic Efficacy

Author

Liu, Yu, primary, Liu, Xu, additional, Huang, Jiaxin, additional, Shi, Yingying, additional, Luo, Zhenyu, additional, Zhang, Junlei, additional, Guo, Xuemeng, additional, Jiang, Mengshi, additional, Li, Xiang, additional, Yin, Hang, additional, Qin, Bing, additional, Guan, Guannan, additional, Luo, Lihua, additional, Zhou, Yun, additional, and You, Jian, additional

Published
2022
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172. Application of Metagenomic Next Generation Sequencing in the Diagnosis of Pulmonary Infectious Pathogens from Bronchoalveolar Lavage Samples in Patients Underwent Allogeneic Hematopoietic Stem Cell Transplantation

Author

Yu, Jian, primary, Shi, Yingying, additional, Zhao, Yanmin, additional, Ye, Yishan, additional, Fu, Huarui, additional, Luo, Yi, additional, Lai, Xiaoyu, additional, Liu, Lizhen, additional, Yang, Li, additional, Liu, Meng, additional, Huang, He, additional, and Shi, Jimin, additional

Published
2022
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176. The Molecular Epidemiology of Prevalent Klebsiella pneumoniae Strains and Humoral Antibody Responses against Carbapenem-Resistant K. pneumoniae Infections among Pediatric Patients in Shanghai

Author

Wang, Jie, primary, Ma, Ruijing, additional, Pan, Fen, additional, Wu, Yongqin, additional, Pan, Yuqing, additional, Liu, Yanan, additional, Yu, Fangyuan, additional, Yu, Jingran, additional, Lun, Heyuan, additional, Shi, Yingying, additional, Zhang, Hong, additional, and He, Ping, additional

Published
2022
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184. SWEPT-SOURCE OPTICAL COHERENCE TOMOGRAPHY DETECTION OF BRUCH MEMBRANE AND CHORIOCAPILLARIS ABNORMALITIES IN SORSBY MACULAR DYSTROPHY

Author

Iyer, Prashanth G., primary, Zhou, Hao, additional, Zhang, Qinqin, additional, Chu, Zhongdi, additional, Shen, Mengxi, additional, Shi, Yingying, additional, Liu, Jeremy, additional, Trivizki, Omer, additional, Lam, Byron L., additional, Wang, Ruikang K., additional, Gregori, Giovanni, additional, and Rosenfeld, Philip J., additional

Published
2022
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194. Personality traits predict regression of pelvic girdle pain after pregnancy: a longitudinal follow-up study

Author

An Xiao, Gong Long, Tan Mingsheng, Yi Ping, Shi Yingying, and Tang Xiang-sheng

Subjects
Adult, Personality Tests, Pelvic girdle pain (PGP), medicine.medical_specialty, Outcomes, 03 medical and health sciences, 0302 clinical medicine, Pelvic Girdle Pain, Pregnancy, Risk Factors, Internal medicine, medicine, Humans, Low back pain, 030212 general & internal medicine, Prospective Studies, Big Five personality traits, Personality traits, Prospective cohort study, Pain Measurement, Extraversion and introversion, integumentary system, business.industry, Pregnant women, Postpartum Period, Obstetrics and Gynecology, Conscientiousness, Gynecology and obstetrics, Pelvic girdle pain, medicine.disease, Neuroticism, Pregnancy Complications, RG1-991, Female, medicine.symptom, business, 030217 neurology & neurosurgery, Research Article, Personality
Abstract

Background Pelvic girdle pain (PGP) is a multifactorial condition with a partly unknown etiology. This condition can be mentally and physically compromising both during and after pregnancy. To provide all-around preventive measures to improve the recovery from PGP, it is a necessity for obstetricians and orthopaedists to develop predictive studies about the worse prognosis for this condition. Therefore, this study aims to determine whether personality traits can predict the consequences of long-term pregnancy-related PGP. Methods This was a prospective study conducted from January 2015 to August 2018. A total of 387 pregnant women were enrolled in this study. According to whether they had experienced PGP during the past 4 weeks, the subjects were classified into no PGP and PGP groups. Persistent PGP after the pregnancy was defined as a recurrent or continuous visual analog score (VAS) pain rating of ≥3 for more than 1 week. The Quick Big Five Personality Test (QBFPT) was used to assess personality traits. Data were obtained by mail or in the clinic. The authors collected data including age, BMI, educational level, annual household income, cesarean delivery, breastfeeding, unexpected sex of the baby, parity, sick leave, no or rare ability to take rest breaks at work, and PGP in the previous pregnancy. Results Of 387 included women, 264 subjects experienced PGP during the pregnancy with a mean age of 26.3 ± 4.5 years. A total of 80 of 264 (30.3%) women experienced persistent PGP after the pregnancy. Persistent PGP after the pregnancy was associated with higher levels of neuroticism (OR = 2.12, P = 0.001). Comparing women with persistent PGP, those who reported higher levels of extraversion and conscientiousness were more likely to recover from this condition (OR = 0.65, P = 0.001; OR = 0.78, P = 0.010, respectively). Besides, neuroticism was positively associated with higher pain scores (r = 0.52, P = 0.005). However, extraversion and conscientiousness domains showed negative correlations with pain score (r = − 0.48, P = 0.003; r = − 0.36, P = 0.001). Conclusions Personality traits were significantly associated with the outcomes of PGP.

Published
2021

197. Intellectual Curve Scene Text Detection from Natural Images Using MSER Descriptor Based Region Segmentation Approach

Author

C. Teixeira Samuel, Kalita Jahnabi, Wang Huayuan, Qin Weiwei, Shi Yingying, Xia Mingrong, Kumar Deepak, Yang Miaomiao, Páramo-Pérez Itzel, Elizabeth Reyes-Martínez Juana, Chandra Remya, S. Lopes Daiana, SIngh Ramandeep, Padilla-Vaca Felipe, Tamayo-Nuñez Jessica, Anaya-Velázquez Fernando, de Melo Rodrigues Veridiana, Chetia Dipak, Idalia Vargas-Maya Naurú, Li Gai, Franco Bernardo, Zhang Jiewen, Sun Ruihua, Liliana España-Sánchez Beatríz, Zhang Haohan, Zhao Jing, Abdizadeh Tooba, Vijayan Dileep, N.C. Gimenes Sarah, Sun Yajing, Banerjee Rintu, de la Mora Javier, Abdizadeh Rahman, Jiménez-Charris Eliécer, Rangel-Serrano Ángeles, Ma Limin, Solano-Redondo Luis, Rudrapal Mithun, Hadizadeh Farzin, and Montealegre-Sánchez Leonel

Subjects
Control and Optimization, Computer Networks and Communications, Computer science, business.industry, Natural (music), Segmentation, Pattern recognition, Text detection, Artificial intelligence, Electrical and Electronic Engineering, business, Computer Science Applications
Abstract

Background: A novel method to detect the text region from the natural image using the discriminative deep feature of text regions is presented with deep learning concept in this manuscript. Objective: Curve Text Detection (CTD) from the natural image is generally based on two different tasks: learning of text data and text region detection. In the learning of text data, the goal is to train the system with a sample of letters and natural images, while, in the text region detection, the aim is to confirm whether the detected regions are text region or not. The emphasis of this research is on the development of deep learning algorithm. Methods: A novel approach has been proposed to detect the text region from natural images which simultaneously tackles three combined challenges: 1) pre-processing of the image without losing text region; 2) appropriate segmentation of text region using their strokes, and 3) training of data. In pre-processing, image enhancement and binarization are done then morphological operations are defined with the Maximally Stable Extremal Region (MSER) based segmentation technique which operates on the basis of stroke region of text and then finds out the (Speed Up Robust Feature) SURF key point from those regions. Results: Based on the SURF feature, text region is detected from the images using a trained structure of Artificial Neural Network (ANN) which is based on deep learning mechanism. Conclusion: CTW-1500 dataset is used to simulate the proposed work and the parameters like Precision, Recall, F-Measure (H-mean), Execution time, Accuracy and Error Rate are computed and are compared with the existing work to depict the effectiveness of the work.

Published
2021

198. ER-Targeting PDT Converts Tumors into In Situ Therapeutic Tumor Vaccines

Author

Liu, Xu, primary, Liu, Yu, additional, Li, Xiang, additional, Huang, Jiaxin, additional, Guo, Xuemeng, additional, Zhang, Junlei, additional, Luo, Zhenyu, additional, Shi, Yingying, additional, Jiang, Mengshi, additional, Qin, Bing, additional, Du, Yongzhong, additional, Luo, Lihua, additional, and You, Jian, additional

Published
2022
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