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10,528 results on '"Shi, Xiao"'

101. Evaluation method for abandoned coal mine gas storage reservoir sites

Author

SHI Xiao-ming, WU Zhi-de, LIU Xu-zheng, LIU Bing-bing, and DENG Xue-jie

Subjects
abandoned coal mine, underground gas storage, site evaluation, fuzzy comprehensive evaluation method, Oils, fats, and waxes, TP670-699, Gas industry, TP751-762
Abstract

Underground gas storage plays an important role in the strategic reserve, peak shaving and stable supply of natural gas. Due to the complex geological conditions in China, very limited sites are available for the construction of gas storage. Thus, it is a good choice to build gas storage in the abandoned coal mine with rich resources. For this purpose, it is particularly important to establish an evaluation method for abandoned coal mine type gas storage. Hence, the factors affecting the conversion of abandoned coal mines into gas storage were summarized and analyzed based on the research results of gas storage site selection at home and abroad from the five aspects of hydrogeology, caprock tightness, geologic structure, influencing factors of abandoned coal mine, and other safe and economic factors. Then, a fuzzy comprehensive evaluation model based on hierarchical analysis was established and a comprehensive evaluation table of storage sites was prepared to evaluate the sites of abandoned coal mines. Besides, the evaluation model was applied to the site evaluation of a coal mine in Shaanxi. The evaluation results show that the coal mine is at an excellent grade and has the potential to be transformed into gas storage. Generally, the evaluation method has certain guiding implications for China to develop abandoned coal mine type gas storage.

Published
2023
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102. A Machine Learning Approach for Recruitment Prediction in Clinical Trial Design

Author

Liu, Jingshu, Allen, Patricia J, Benz, Luke, Blickstein, Daniel, Okidi, Evon, and Shi, Xiao

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

Significant advancements have been made in recent years to optimize patient recruitment for clinical trials, however, improved methods for patient recruitment prediction are needed to support trial site selection and to estimate appropriate enrollment timelines in the trial design stage. In this paper, using data from thousands of historical clinical trials, we explore machine learning methods to predict the number of patients enrolled per month at a clinical trial site over the course of a trial's enrollment duration. We show that these methods can reduce the error that is observed with current industry standards and propose opportunities for further improvement., Comment: Machine Learning for Health (ML4H) - Extended Abstract

Published
2021

122. Feasibility study of measuring $b\to s\gamma$ photon polarisation in $D^0\rightarrow K_1(1270)^- e^+\nu_e$ at STCF

Author

Fan, Yu-Lan, Shi, Xiao-Dong, Zhou, Xiao-Rong, and Sun, Liang

Subjects
High Energy Physics - Experiment
Abstract

We report a sensitive study of measuring $b\to s\gamma$ photon polarisation in $D^{0}\to K_1(1270)^-e^+\nu_e$ with an integrated luminosity of $\mathcal L$ = 1 ab$^{-1}$ at a center-of-mass energy of 3.773 GeV at future Super Tau Charm Facility. More than 61,000 signals of $D^{0}\to K_1(1270)^-e^+\nu_e$ are expected. Based on a fast simulation software package, the statistical sensitivity for the ratio of up-down asymmetry is estimated to be $1.5\times 10^{-2}$ by performing a two-dimensional angular analysis in $D^{0}\to K_1(1270)^-e^+\nu_e$. Combining with measurements of up-down asymmetry in $B\to K_1\gamma$, the photon polarisation in $b\to s\gamma$ can be determined model-independently.

Published
2021
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