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686 results on '"Wang, Huixia"'

103. Tetrolet Regularization and Learning for Single Frame Image Super-Resolution

Author

Xiao, Liang, Li, Heng, Wang, Huixia, Wang, Liqian, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Yang, Jian, editor, Fang, Fang, editor, and Sun, Changyin, editor

Published
2013
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104. Is it possible to use low-dose deep learning reconstruction for the detection of liver metastases on CT routinely?

Author

Lyu, Peijie, primary, Liu, Nana, additional, Harrawood, Brian, additional, Solomon, Justin, additional, Wang, Huixia, additional, Chen, Yan, additional, Rigiroli, Francesca, additional, Ding, Yuqin, additional, Schwartz, Fides Regina, additional, Jiang, Hanyu, additional, Lowry, Carolyn, additional, Wang, Luotong, additional, Samei, Ehsan, additional, Gao, Jianbo, additional, and Marin, Daniele, additional

Published
2022
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113. The effects of temperature on sleep experience: evidence from China.

Author

Wang, Chenggang, Liu, Keqiao, and Wang, Huixia

Subjects
TEMPERATURE effect, SLEEP, SHIFT systems, HEAT waves (Meteorology), HIGH temperatures
Abstract

A large body of literature estimates the high-temperature effects on a variety of economic and health outcomes. This paper provides convergent evidence of a possible working mechanism behind those effects. That is, upon examining nationally representative self-report measures in China, we studied the relationship between temperature and people's sleep experience, an essential input for productivity and health outcomes. By analysing county-level daily temperature data and the CFPS self-reported sleep experience data, our findings indicate that high temperature can increase the probability of reporting poor sleep experiences in China. Additionally, elderly, lower educated, and rural residents may be more vulnerable to the damage of heatwaves. Our results imply that high temperature can adversely and significantly impact people's sleep experience, though its effect can be partially offset by installing air conditioners. [ABSTRACT FROM AUTHOR]

Published
2023
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116. Two‐Dimensional Detergent Expansion Strategy for Membrane Protein Studies

Author

Zhao, Fei, primary, Zhu, Zhihao, additional, Xie, Linshan, additional, Luo, Feng, additional, Wang, Huixia, additional, Qiu, Yanli, additional, Luo, Weiling, additional, Zhou, Fang, additional, Xue, Dongxiang, additional, Zhang, Zhihui, additional, Hua, Tian, additional, Wu, Dong, additional, Liu, Zhi‐Jie, additional, Le, Zhiping, additional, and Tao, Houchao, additional

Published
2022
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123. Protecting playgrounds:local-scale reduction of airborne particulate matter concentrations through particulate deposition on roadside ‘tredges’ (green infrastructure)

Author

Maher, Barbara A., Gonet, Tomasz, Karloukovski, Vassil V., Wang, Huixia, Bannan, Thomas J., Maher, Barbara A., Gonet, Tomasz, Karloukovski, Vassil V., Wang, Huixia, and Bannan, Thomas J.

Abstract

Exposure to traffic-related particulate air pollution has been linked with excess risks for a range of cardiovascular, respiratory and neurological health outcomes; risks likely to be exacerbated in young children attending schools adjacent to highly-trafficked roads. One immediate way of reducing airborne PM concentrations at the local (i.e., near-road community) scale is installation of roadside vegetation as a means of passive pollution abatement. Roadside vegetation can decrease airborne PM concentrations, through PM deposition on leaves, but can also increase them, by impeding airflow and PM dispersion. Critical to optimizing PM removal is selection of species with high particle deposition velocity (Vd) values, currently under-parameterised in most modelling studies. Here, the measured amounts of leaf-deposited magnetic PM after roadside greening (‘tredge’) installation, and measured reductions in playground PM, particle number and black carbon concentrations demonstrate that air quality improvements by deposition can be achieved at the local, near-road, community/playground scale. PM deposition on the western red cedar tredge removed ~ 49% of BC, and ~ 46% and 26% of the traffic-sourced PM2.5 and PM1, respectively. These findings demonstrate that roadside vegetation can be designed, installed and maintained to achieve rapid, significant, cost-effective improvement of air quality by optimising PM deposition on plant leaves.

Published
2022

124. Latent group detection in functional partially linear regression models.

Author

Wang, Wu, Sun, Ying, and Wang, Huixia Judy

Subjects
FUNCTIONAL groups, REGRESSION analysis, ASYMPTOTIC distribution, K-means clustering, PANEL analysis, LATENT variables
Abstract

In this paper, we propose a functional partially linear regression model with latent group structures to accommodate the heterogeneous relationship between a scalar response and functional covariates. The proposed model is motivated by a salinity tolerance study of barley families, whose main objective is to detect salinity tolerant barley plants. Our model is flexible, allowing for heterogeneous functional coefficients while being efficient by pooling information within a group for estimation. We develop an algorithm in the spirit of the K‐means clustering to identify latent groups of the subjects under study. We establish the consistency of the proposed estimator, derive the convergence rate and the asymptotic distribution, and develop inference procedures. We show by simulation studies that the proposed method has higher accuracy for recovering latent groups and for estimating the functional coefficients than existing methods. The analysis of the barley data shows that the proposed method can help identify groups of barley families with different salinity tolerant abilities. [ABSTRACT FROM AUTHOR]

Published
2023
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