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Background Parkinson's disease (PD) is frequently accompanied with anxiety, depression, sleep disorders, autonomic dysfunction, cognitive impairment, and other non-motor symptoms, among which autonomic dysfunction and cognitive impairment severely impair the quality of life. The relationship between autonomic dysfunction and cognitive impairment in PD is still controversial. Objective To analyze the characteristic of autonomic dysfunction and its correlation with cognitive impairment in PD patients. Methods A total of 156 patients with idiopathic PD admitted to Henan Provincial People's Hospital between September 2018 and November 2020 were enrolled. General data of patients, including age, sex, duration of disease, age of onset and years of education, were collected. According to the prevalence and duration of autonomic dysfunction, they were divided into autonomic dysfunction group (AutD group, n=107) and non-autonomic dysfunction group (NAutD group, n=49) . The part Ⅲ of the Unified Parkinson's Disease Rating Scale (UPDRS-Ⅲ) was used to assess motor symptoms. The Hoehn-Yahr (H-Y) scale was used to assess the severity of PD. The non-motor symptoms were assessed by the Non-motor Symptoms Scale (NMSS) . The Hamilton Anxiety Scale (HAMA) and Hamilton Rating Scale for Depression 24-item (HAMD-24) were used to evaluate anxiety and depression symptoms, respectively. The 39-item Parkinson's Disease Questionnaire (PDQ-39) was used to evaluate PD-specific health related quality of life. Autonomic function was evaluated by Scales for Outcomes in Parkinson's disease-Autonomic (SCOPA-AUT) . Cognitive function was evaluated by Mini-mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) . Spearman correlation analysis was used to explore the correlation between autonomic function (assessed using the SCOPA-AUT score) and cognitive function (assessed using the MMSE score and MoCA score) . Results Among the 156 patients, 83 were male and 73 were female, with a mean age of (63.9±0.7) years. AutD group had greater mean age (t=-4.391, P

Allocating emission quotas among provinces fairly and efficiently is a critical issue for China. We developed a carbon quota allocation framework at the provincial level considering both the equity and efficiency principles based on a multi-objective non-linear programming model. We established a carbon Gini coefficient and an emission abatement cost function to measure the equity and efficiency of quota allocation, respectively. We then introduced them as objectives into a multi-objective non-linear programming model and obtained the optimal emission quota allocation for 30 provinces in China, by realizing the trade-off between the equity and efficiency principles. Our analysis revealed that Chinese carbon emissions have not yet peaked and that the proportion of carbon emission in each province is similar. Moreover, provinces with higher GDP per capita, carbon intensity, and historical accumulated carbon emissions should shoulder more burden of carbon intensity reduction and higher marginal reduction costs. The rationality analysis indicates that our method outperforms traditional methods according to the principles of both equity and efficiency. We conclude by offering policy recommendations for the establishment of a national unified carbon market. [ABSTRACT FROM AUTHOR]

CO2 Emissions Trading Scheme is a key policy instrument for dealing with increasing greenhouse gas emissions. This work aims at giving some policy recommendations on the design of China's National Emissions Trading Scheme. The experience accumulated in China's Carbon Emissions Trading Pilots is quite valuable for China's National Emissions Trading Scheme, so it is important to analyze the determinants of the prices in these pilots. We use the difference-in-differences model to study various policies respectively, including auction, investment access of individual and institutional traders, and carbon forward. Principal components of economy, energy, climate and allowance characteristic are respectively extracted from alternative variables, such as CPI, energy price, extreme temperature, in four categories. These principal components are set as control variables. Results show that these policies play a big role in the price discovery and stabilization. Auction drives the market price to approach the auction completion price. Carbon price exhibits a positive sensitivity to non-regulated entities' participation and carbon forward. All the significant variables together can reflect most of the pilots' price information. Policies have heterogeneous impacts on carbon price. The finding is robust to alternative specifications. [ABSTRACT FROM AUTHOR]