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835 results on '"Wang, Yunqi"'

210. CROUCHING TIGER, ASCENDING DRAGON: THE TRENDS AND DYNAMICS OF MALAYSIA-CHINA RELATIONS.

Author

Lai Yew Meng, De Silva, Maureen, and Wang Yunqi

Subjects
POWER (Social sciences), MALAYSIANS, DRAGONS, GEOPOLITICS, NATIONAL interest, CONTINUITY, UNCERTAINTY
Abstract

This article examines the trends and dynamics of Malaysia-China relations, with emphasis on the post-Cold War era and beyond. More specifically, it explicates the interplay of external and domestic dynamics that have defined Malaysia's China policy amid shifting regional strategic and domestic political milieu. This article contends that Malaysia's "hedging" policy vis-à-vis China has been primarily shaped by the country's ruling-elite's perceptions of its external conditions in the context of East Asia's evolving power dynamics, tempered by their domestic political expediency. It further argues that despite the periodical recalibrations having given the impression of policy-shifts, they have not fundamentally altered Malaysia's China policy-approach. Instead, continuity rather than change has been the hallmark, since the "structural conditionalities" driving and constraining Malaysia's relations with China continue to be informed by Malaysian rulingelite's domestic political considerations, as they strive to optimise as much the country's external interests, as to consolidate their domestic legitimacy. The findings inform Putrajaya's persistence on "light-hedging" as the optimal policyoption, when dealing with Beijing, to advance Malaysia's national survival and interests as a "smaller-state", amid the evolving regional geopolitics, shaped by power asymmetry, rivalry and uncertainty. [ABSTRACT FROM AUTHOR]

Published
2023
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215. Integration of a Metal–Organic Framework Film with a Tubular Whispering-Gallery-Mode Microcavity for Effective CO2 Sensing

Author

Kong, Ye, primary, Zhao, Zhe, additional, Wang, Yunqi, additional, Yang, Shuo, additional, Huang, Gaoshan, additional, Wang, Yang, additional, Liu, Chang, additional, You, Chunyu, additional, Tan, Ji, additional, Wang, Chao, additional, Xu, Borui, additional, Cui, Jizhai, additional, Liu, Xuanyong, additional, and Mei, Yongfeng, additional

Published
2021
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219. Towards Low-Carbon Operation of Integrated Energy Systems: Modeling and Its Applications

Author

Wang, Yunqi

Subjects
Demand management, Low carbon, Power system
Abstract

Excessive anthropogenic carbon emissions with growing energy demand have exacerbated global climate change, which would endanger the sustainable development of human society. To cope with this issue, carbon emission reduction and low-carbon transition have become inevitable in the energy sector. Some of the most notable developments foreseen in the energy sector focus on the integrated energy systems (IESes). IESes are expected to host a large proportion of low-carbon energy, including renewable energy sources (RESes) to supply a growing share of total demand. In addition, with the help of the mature energy market, price-based financial schemes are permeated into the energy sector, aiming to achieve carbon emission control via eliminating high-carbon energy through a market mechanism. However, these new paradigms bring economic and performance challenges to operational and planning practices. Integrating different multiple energy carriers should consider more physical limitations, economic diversity, and reciprocal conversion, which challenges the conventional single-network-based modelling approach. In particular, the low-carbon operation relies on clean energy produced by RESes, but the intermittent output affects system reliability. From the carbon economy perspective, existing unidirectional money flow moves the burden of energy consumption by simply passing carbon impacts to customers. Meanwhile, levelling carbon costs based on energy amount would lead to an inequitable issue; it is also deficient in achieving effective carbon mitigation and sacrifices consumer surplus. The goal of this thesis is focusing on the IESes including modelling, operation, and optimisation towards a decarbonised society. Emphasis is put on the underlying driver of carbon emission, the energy demand side; analyses are conducted on network-based optimal centralized approaches assuming perfect communication and monitoring infrastructures. The main body (i.e. chapters exclude introduction, literature, and conclusion) of this thesis can be divided into two parts in accordance with the novel low-carbon operation framework and relevant application. The first part is composed of Chapters 3 and 4, which clarify the responsibility of carbon emission and describe the detailed `virtual' carbon distribution in energy networks. Further, a low-carbon operation framework is proposed considering that customers manage their demand in a carbon-oriented, cost-effective way. The second part is composed of Chapters 5, 6 and 7. It exploits the feasibility and flexibility of energy conversion and energy techniques based on the main structure of the proposed framework. As the carbon impacts are exerted via trading circumstances, the market risks are quantified and tackled. The last chapter investigates the uncertainties brought by intermittent output from RESes and the demand side. This thesis shows what methods, decisions and strategies can be used in the operation and planning of modern IESes under the interactive influence of carbon policies to tackle the challenges posed by the low-carbon energy transition. Several benchmark test systems have been employed to demonstrate the effectiveness of the proposed models. Experiments using existing approaches in the literature, where applicable, have also been conducted. The result shows that the proposed models are reasonable and feasible and also practical and accurate. The conclusion can also be drawn that the energy demand side is motivated to reduce carbon emissions by identifying individual carbon information and managing relevant environmental assets, which accelerates establishing a forward cycle for the entire IES towards carbon neutrality.

Published
2021

230. Inline Infrared Chemical Identification of Particulate Matter

Author

Stefan M. B. Bäumer, Wang Yunqi, Javier Nuñez, and Arjen Boersma

Subjects
010504 meteorology & atmospheric sciences, Infrared, inline chemical identification, cyclone, Analytical chemistry, Infrared spectroscopy, 010501 environmental sciences, exposome, Hollow waveguide, lcsh:Chemical technology, 01 natural sciences, Biochemistry, Article, Analytical Chemistry, Particulate matter sensor, lcsh:TP1-1185, Electrical and Electronic Engineering, infrared spectroscopy, Instrumentation, Chemical composition, 0105 earth and related environmental sciences, Detector, hollow waveguide, Particulates, particulate matter sensor, Cyclone, Atomic and Molecular Physics, and Optics, Amorphous solid, Exposome, Particle-size distribution, Particle size, Inline chemical identification
Abstract

The health and environmental effects of particulate matter (PM) in the air depend on several parameters. Besides particle size, shape, and concentration, the chemical nature of the PM is also of great importance. State-of-the-art PM sensors only detect the particle size and concentration. Small, low-cost sensors only identify PM according to PM2.5 and PM10 standards. Larger detectors measure the complete particle size distribution. However, the chemical composition of PM is not often assessed. The current paper presents the initial stages of the development of an infrared-based detector for the inline assessment of the chemistry of PM in the air. By combining a mini cyclone that is able to concentrate the particles at least a thousand fold and a hollow waveguide that aligns the flow of particles with infrared light, the feasibility of the concept was shown in this study. A clear differentiation between amorphous and crystalline silica was demonstrated at outdoor PM levels of lower than 1 mg per cubic meter.

Published
2020

232. Pyrotinib Treatment in Patients With HER2-positive Metastatic Breast Cancer and Brain Metastasis: Exploratory Final Analysis of Real-World, Multicenter Data

Author

Anwar, Munawar, primary, Chen, Qitong, additional, Ouyang, Dengjie, additional, Wang, Shouman, additional, Xie, Ning, additional, Ouyang, Quchang, additional, Fan, Peizhi, additional, Qian, Liyuan, additional, Chen, Gannong, additional, Zhou, Enxiang, additional, Guo, Lei, additional, Gu, Xiaowen, additional, Ding, Boning, additional, Yang, Xiaohong, additional, Liu, Liping, additional, Deng, Chao, additional, Xiao, Zhi, additional, Li, Jing, additional, Wang, Yunqi, additional, Zeng, Shan, additional, Hu, Jinhui, additional, Zhou, Wei, additional, Qiu, Bo, additional, Wang, Zhongming, additional, Weng, Jie, additional, Liu, Mingwen, additional, Li, Yi, additional, Tang, Tiegang, additional, Wang, Jianguo, additional, Zhang, Hui, additional, Dai, Bin, additional, Tang, Wuping, additional, Wu, Tao, additional, Xiao, Maoliang, additional, Li, Xiantao, additional, Liu, Hailong, additional, Li, Lai, additional, and Yi, Wenjun, additional

Published
2021
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239. Optimal Power Scheduling Using Data-Driven Carbon Emission Flow Modelling for Carbon Intensity Control.

Author

Wang, Yunqi, Qiu, Jing, and Tao, Yuechuan

Subjects
*CARBON emissions, *CARBON, *ENERGY consumption, *SCHEDULING, *DYNAMICAL systems
Abstract

Regarding the continuing increase of anthropogenic carbon emissions in the power system with growing energy consumption, researchers have focused on managing the demand side to achieve low-carbon transition. However, such a low-carbon transition cannot be achieved effectively without the proper incentive scheme. Moreover, it is desired to improve the computation quality of carbon tracing tools and extend their applications by state-of-art techniques. To fulfil these existing research gaps, this paper proposes a low-carbon optimal scheduling model with demand response (DR) based carbon intensity control. It aims to reduce the dependence of customers on energy sources with high carbon intensities while decreasing reasonable energy consumption. Likewise, a data-driven approach conducted with the Bayesian interfere regression is proposed to carry out the carbon emission flow (CEF) model to cope with the drawbacks of the conventional emission calculation. Moreover, the storage emission and relevant dynamic impacts to the system are fully considered. The proposed data-driven approach is tested on a series of IEEE systems with different sizes, its high accuracy and efficiency are proved by the simulation results. Further, simulation results indicate that the proposed scheduling model can effectively achieve carbon emission mitigation. [ABSTRACT FROM AUTHOR]

Published
2022
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240. Corrigendum: Effectiveness and Safety of Pyrotinib, and Association of Biomarker With Progression-Free Survival in Patients With HER2-Positive Metastatic Breast Cancer: A Real-World, Multicentre Analysis

Author

Chen, Qitong, primary, Ouyang, Dengjie, additional, Anwar, Munawar, additional, Xie, Ning, additional, Wang, Shouman, additional, Fan, Peizhi, additional, Qian, Liyuan, additional, Chen, Gannong, additional, Zhou, Enxiang, additional, Guo, Lei, additional, Gu, Xiaowen, additional, Ding, Boni, additional, Yang, Xiaohong, additional, Liu, Liping, additional, Deng, Chao, additional, Xiao, Zhi, additional, Li, Jing, additional, Wang, Yunqi, additional, Zeng, Shan, additional, Hu, Jinhui, additional, Zhou, Wei, additional, Qiu, Bo, additional, Wang, Zhongming, additional, Weng, Jie, additional, Liu, Mingwen, additional, Li, Yi, additional, Tang, Tiegang, additional, Wang, Jianguo, additional, Zhang, Hui, additional, Dai, Bin, additional, Tang, Wuping, additional, Wu, Tao, additional, Xiao, Maoliang, additional, Li, Xiantao, additional, Liu, Hailong, additional, Li, Lai, additional, Yi, Wenjun, additional, and Ouyang, Quchang, additional

Published
2021
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