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2,829 results on '"Li, Wenting"'

56. Widening the Lens on PFASs: Direct Human Exposure to Perfluoroalkyl Acid Precursors (pre-PFAAs).

Author

McDonough, Carrie, Li, Wenting, Bischel, Heather, De Silva, Amila, and DeWitt, Jamie

Subjects
PFASs, bioaccumulation, biotransformation, human exposure, nontarget analysis, per- and polyfluoroalkyl substances, precursor, risk assessment, Animals, Biotransformation, Fishes, Fluorocarbons, Humans, Water Pollutants, Chemical
Abstract

Determining health risks associated with per-/polyfluoroalkyl substances (PFASs) is a highly complex problem requiring massive efforts for scientists, risk assessors, and regulators. Among the most poorly understood pressing questions is the relative importance of pre-PFAAs, which are PFASs that degrade to highly persistent perfluoroalkyl acids. How many of the vast number of existing pre-PFAAs are relevant for direct human exposure, and what are the predominant exposure pathways? What evidence of direct exposure to pre-PFAAs is provided by human biomonitoring studies? How important are pre-PFAAs and their biotransformation products for human health risk assessment? This article outlines recent progress and recommendations toward widening the lens on human PFAS exposure to include the pre-PFAA subclass.

Published
2022

57. High-resolution chirplet transform: from parameters analysis to parameters combination

Author

Zhu, Xiangxiang, Li, Bei, Yang, Kunde, Zhang, Zhuosheng, and Li, Wenting

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

The standard chirplet transform (CT) with a chirp-modulated Gaussian window provides a valuable tool for analyzing linear chirp signals. The parameters present in the window determine the performance of the CT and play a vital role in high-resolution time-frequency (TF) analysis. In this paper, we give the window shape analysis of the CT and compare it with the extension that employs a rotating Gaussian window by the fractional Fourier transform. The given parameters analysis provides theoretical guidance for developing high-resolution CT. We then propose a multi-resolution chirplet transform (MrCT) by combining multiple CTs with different parameter combinations. These are combined geometrically to obtain an improved TF resolution by overcoming the limitations of any single representation of the CT. By deriving a combined instantaneous frequency equation, we further develop a high-concentration TF post-processing approach to improve the readability of the MrCT. Numerical experiments on simulated and real signals verify the effectiveness of the proposed methods.

Published
2021

80. Preoperative and intraoperative assessment of myometrial invasion in patients with FIGO stage I non-endometrioid endometrial carcinoma—a large-scale, multi-center, and retrospective study

Author

Yang, Xiaohang, Yin, Jingjing, Fu, Yu, Shen, Yuanming, Zhang, Chuyao, Yao, Shuzhong, Xu, Congjian, Xia, Min, Lou, Ge, Liu, Jihong, Lin, Bei, Wang, Jianliu, Zhao, Weidong, Zhang, Jieqing, Cheng, Wenjun, Guo, Hongyan, Guo, Ruixia, Xue, Fengxia, Wang, Xipeng, Han, Lili, Li, Xiaomao, Zhang, Ping, Zhao, Jianguo, Li, Wenting, Dou, Yingyu, Wang, Zizhuo, Liu, Jingbo, Li, Kezhen, Chen, Gang, Sun, Chaoyang, Sun, Pengming, Lu, Weiguo, and Yao, Qin

Published
2023
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82. PPGN: Physics-Preserved Graph Networks for Real-Time Fault Location in Distribution Systems with Limited Observation and Labels

Author

Li, Wenting and Deka, Deepjyoti

Subjects
Computer Science - Machine Learning, Electrical Engineering and Systems Science - Systems and Control
Abstract

Electrical faults may trigger blackouts or wildfires without timely monitoring and control strategy. Traditional solutions for locating faults in distribution systems are not real-time when network observability is low, while novel black-box machine learning methods are vulnerable to stochastic environments. We propose a novel Physics-Preserved Graph Network (PPGN) architecture to accurately locate faults at the node level with limited observability and labeled training data. PPGN has a unique two-stage graph neural network architecture. The first stage learns the graph embedding to represent the entire network using a few measured nodes. The second stage finds relations between the labeled and unlabeled data samples to further improve the location accuracy. We explain the benefits of the two-stage graph configuration through a random walk equivalence. We numerically validate the proposed method in the IEEE 123-node and 37-node test feeders, demonstrating the superior performance over three baseline classifiers when labeled training data is limited, and loads and topology are allowed to vary., Comment: 10 pages, 4 figure

Published
2021
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83. Machine Learning for Variance Reduction in Online Experiments

Author

Guo, Yongyi, Coey, Dominic, Konutgan, Mikael, Li, Wenting, Schoener, Chris, and Goldman, Matt

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning
Abstract

We consider the problem of variance reduction in randomized controlled trials, through the use of covariates correlated with the outcome but independent of the treatment. We propose a machine learning regression-adjusted treatment effect estimator, which we call MLRATE. MLRATE uses machine learning predictors of the outcome to reduce estimator variance. It employs cross-fitting to avoid overfitting biases, and we prove consistency and asymptotic normality under general conditions. MLRATE is robust to poor predictions from the machine learning step: if the predictions are uncorrelated with the outcomes, the estimator performs asymptotically no worse than the standard difference-in-means estimator, while if predictions are highly correlated with outcomes, the efficiency gains are large. In A/A tests, for a set of 48 outcome metrics commonly monitored in Facebook experiments the estimator has over 70% lower variance than the simple difference-in-means estimator, and about 19% lower variance than the common univariate procedure which adjusts only for pre-experiment values of the outcome.

Published
2021

84. Exploring Collaborative Caption Editing to Augment Video-Based Learning

Author

Bhavya, Bhavya, Chen, Si, Zhang, Zhilin, Li, Wenting, Zhai, Chengxiang, Angrave, Lawrence, and Huang, Yun

Abstract

Captions play a major role in making educational videos accessible to all and are known to benefit a wide range of learners. However, many educational videos either do not have captions or have inaccurate captions. Prior work has shown the benefits of using crowdsourcing to obtain accurate captions in a cost-efficient way, though there is a lack of understanding of how learners edit captions of educational videos either individually or collaboratively. In this work, we conducted a user study where 58 learners (in a course of 387 learners) participated in the editing of captions in 89 lecture videos that were generated by Automatic Speech Recognition (ASR) technologies. For each video, different learners conducted two rounds of editing. Based on editing logs, we created a taxonomy of errors in educational video captions (e.g., Discipline-Specific, General, Equations). From the interviews, we identified individual and collaborative error editing strategies. We then further demonstrated the feasibility of applying machine learning models to assist learners in editing. Our work provides practical implications for advancing video-based learning and for educational video caption editing.

Published
2022
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85. Application of comprehensive nursing interventions in patients with diabetic nephropathy (综合护理干预在糖尿病肾病患者中的应用研究)

Author

TIAN Yixian (田忆贤), LI Wenting (李文婷), ZHAO Haijie (赵海杰), LI Jiaqi (李佳琪), XUE Ning (薛宁), CHENG Lili (程丽丽), and LI Yanhua (李艳华)

Subjects
diabetic nephropathy, end-stage renal disease, dietary, psychological care, traditional chinese medicine, comprehensive nursing, 糖尿病肾病, 终末期肾脏病, 饮食, 心理护理, 中医, 综合护理, Nursing, RT1-120
Abstract

Diabetic nephropathy is one of the main common diseases in nephrology endocrinology. This paper reviews studies about comprehensive nursing interventions such as dietary guidance, exercise nursing, drug treatment, psychological nursing, traditional Chinese medicine treatment and health education for patients with diabetic nephropathy, and provides reference for comprehensive treatment of diabetic nephropathy. (糖尿病肾病是肾病内分泌科的常见病之一。本研究就饮食护理、运动护理、用药指导、心理护理以及中医治疗等护理干预在糖尿病肾病患者中的应用现状进行综述, 旨在为制定和优化糖尿病肾病患者综合护理方案提供参考。)

Published
2023
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