Calculated Opening-Up: Explaining the Motivation Behind China’s Policy on International Students

This thesis explores the motivation behind China\u27s policy on international students. It seeks to explain why China forms a policy without clear benefits for Chinese people. Using the concept of instrumentalist and organizational realist approaches, the thesis is centered on political competition and political pursuit to analyze the documents of China\u27s international education policy. The main findings of this thesis expound that the ruling class makes China\u27s policy on international students an instrument of achieving political goal. The thesis indicates that the policy is not in the best interest of the public and the public have not effectively participated the process of policymaking. It argues that China expects that some of the international students would become the leaderships of their home countries and establish friendly relationships with China in the future. The policy made by the central government suggests China\u27s ambition to vie with western powers; whereas the policymakers from provincial governments and universities attempt to pursue higher political positions. The thesis shows that as the ruling class in China, the Chinese Communist Party used the state as an instrument for pursuing their own interests

Adaptive neural network cascade control system with entropy-based design

A neural network (NN) based cascade control system is developed, in which the primary PID controller is constructed by NN. A new entropy-based measure, named the centred error entropy (CEE) index, which is a weighted combination of the error cross correntropy (ECC) criterion and the error entropy criterion (EEC), is proposed to tune the NN-PID controller. The purpose of introducing CEE in controller design is to ensure that the uncertainty in the tracking error is minimised and also the peak value of the error probability density function (PDF) being controlled towards zero. The NN-controller design based on this new performance function is developed and the convergent conditions are. During the control process, the CEE index is estimated by a Gaussian kernel function. Adaptive rules are developed to update the kernel size in order to achieve more accurate estimation of the CEE index. This NN cascade control approach is applied to superheated steam temperature control of a simulated power plant system, from which the effectiveness and strength of the proposed strategy are discussed by comparison with NN-PID controllers tuned with EEC and ECC criterions

Acupuncture in Treatment of Chronic Functional Constipation

Constipation is not only a symptom but is a predominant presenting symptom in many diseases. The prevalence is between 3 and 27% worldwide, and is especially prevalent in the elderly population. The aetiology is multifactorial. Laxative abuse or enema use are usually a norm in patients’ constipation. Patients tend not to seek further medical aid after several unsuccessful therapies and this can seriously affect their quality of life

Light effects on seedling growth in simulated forest canopy gaps vary across species from different successional stages

Tropical forests continue to suffer from various kinds of disturbances in the Anthropocene. An immediate impact of disturbances on forest ecosystems is the creation of numerous large and small canopy gaps, which dramatically affect forest structure and function. Yet, we know little about the effect of canopy gaps on forest successional trajectory. More specifically, the responses of seedlings from different successional stages to increased light intensity under large and small canopy gaps in understory remain unclear. In this study, dominant tree seedlings from early-, mid-, and late-successional stages were selected, respectively from a tropical montane forest in Hainan Island, China to study their growth rate, biomass and traits. Our results showed that the light condition under small canopy gaps (SG, 10–15% of full sunlight) and large canopy gaps (LG, 40–50% of full sunlight) induced greater increment of relative growth rates for seedlings from early- and mid-successional stages relative to that in late-successional stage. Both SG and LG also significantly increased photosynthesis rate, leaf area (LA), light saturation point (LSP), root mass ratio (RMR) and root: shoot ratio, but decreased specific leaf area (SLA) of seedlings across successional stages. Tree seedlings from the earlysuccessional stage displayed the greatest decrease in leaf mass ratio, increase in LA, LSP, and RMR, in comparison to those from mid- and late- successional stages. Light condition and SLA were the most important factors for seedlings’ relative growth rate across successional stages. SLA connected the interaction between the light condition and successional stage on seedlings’ growth, thereby jointly explaining the 93% variation of seedlings’ growth, combining with area-based light saturated rate of CO2 assimilation. Our study highlights the distinct effect of disturbance-induced canopy gaps on seedling regeneration in the understory in tropical forest due to the variation of light intensity. We suspect that the seedlings from late-successional stage will recover relatively slow after disturbances causing canopy losses, which can have detrimental impacts on structure feature an

Comparison of phenology estimated from reflectance-based indices and solar-induced chlorophyll fluorescence (SIF) observations in a temperate forest using GPP-based phenology as the standard

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Remote Sensing 10 (2018): 932, doi:10.3390/rs10060932.We assessed the performance of reflectance-based vegetation indices and solar-induced chlorophyll fluorescence (SIF) datasets with various spatial and temporal resolutions in monitoring the Gross Primary Production (GPP)-based phenology in a temperate deciduous forest. The reflectance-based indices include the green chromatic coordinate (GCC), field measured and satellite remotely sensed Normalized Difference Vegetation Index (NDVI); and the SIF datasets include ground-based measurement and satellite-based products. We found that, if negative impacts due to coarse spatial and temporal resolutions are effectively reduced, all these data can serve as good indicators of phenological metrics for spring. However, the autumn phenological metrics derived from all reflectance-based datasets are later than the those derived from ground-based GPP estimates (flux sites). This is because the reflectance-based observations estimate phenology by tracking physiological properties including leaf area index (LAI) and leaf chlorophyll content (Chl), which does not reflect instantaneous changes in phenophase transitions, and thus the estimated fall phenological events may be later than GPP-based phenology. In contrast, we found that SIF has a good potential to track seasonal transition of photosynthetic activities in both spring and fall seasons. The advantage of SIF in estimating the GPP-based phenology lies in its inherent link to photosynthesis activities such that SIF can respond quickly to all factors regulating phenological events. Despite uncertainties in phenological metrics estimated from current spaceborne SIF observations due to their coarse spatial and temporal resolutions, dates in middle spring and autumn—the two most important metrics—can still be reasonably estimated from satellite SIF. Our study reveals that SIF provides a better way to monitor GPP-based phenological metrics.This research was supported by U. S. Department of Energy Office of Biological and Environmental Research Grant DE-SC0006951, National Science Foundation Grants DBI 959333 and AGS-1005663, and the University of Chicago and the MBL Lillie Research Innovation Award to Jianwu Tang and China Scholarship Council No. 201506190095 to Z. Liu. Xiaoliang Lu was also supported by the open project grant (LBKF201701) of Key Laboratory of Land Surface Pattern and Simulation, Chinese Academy of Sciences

A flame combustion model-based wildfire-induced tripping risk assessment approach of transmission lines

With the intensification of global climate change, the frequency of wildfires has markedly increased, presenting an urgent challenge in assessing tripping failures for power systems. This paper proposes an innovative method to evaluate the spatial wildfire-induced tripping risk of transmission lines based on a flame combustion model. Firstly, Bayes theory is employed to assess the spatial probability of wildfire occurrence. Subsequently, Wang Zhengfei’s flame combustion model is utilized to estimate the potential flame height of wildfires along the transmission corridor. Thirdly, the insulation breakdown risk of the transmission line is calculated based on the relative height difference between the flame and the transmission line. Finally, the spatial wildfire-induced tripping risk of the transmission line is then determined by combining the wildfire occurrence probability and the insulation breakdown risk. A case study conducted in Guizhou province, China validates the accuracy of the proposed model. Utilizing ArcGIS, the wildfire occurrence probability distribution in Guizhou is visualized to enhance the efficiency of operation and maintenance. The results indicate that over 80% of wildfire incidents occurred in areas with occurrence probabilities exceeding 50%