Base-case analysis. by Yiping An (20609789)

“…One-way sensitivity analysis identified AOM’s drug cost as the parameter with the greatest impact on results. Probabilistic sensitivity analysis revealed that with a 40% price reduction, the probability of AOM being cost-effective is only 41.70%. …”

One-way sensitivity analysis. by Yiping An (20609789)

Trends of prevalence (A), incidence (B) deaths (C), and DALYs (D) rates of chronic obstructive pulmonary disease per 100,000 population among adults aged ≥70 years by sex and socio... by Kaifang Meng (13848535)

Data_GDP/ Ndvi. by Qianhong Mao (22305184)

“…Most of the mean value of ESs showed a gradient increasing differences along urban-fringe-rural, while the greatest decrease occurs in fringe expansion and urban expansion areas; and (3) interactions for changes in ES pairs also more closely linked in these two regions, with synergies dominating. …”

Flow chart of the study. by Qianhong Mao (22305184)

“…Most of the mean value of ESs showed a gradient increasing differences along urban-fringe-rural, while the greatest decrease occurs in fringe expansion and urban expansion areas; and (3) interactions for changes in ES pairs also more closely linked in these two regions, with synergies dominating. …”

Example of manual identification. by Qianhong Mao (22305184)

“…Most of the mean value of ESs showed a gradient increasing differences along urban-fringe-rural, while the greatest decrease occurs in fringe expansion and urban expansion areas; and (3) interactions for changes in ES pairs also more closely linked in these two regions, with synergies dominating. …”

Data_soil. by Qianhong Mao (22305184)

“…Most of the mean value of ESs showed a gradient increasing differences along urban-fringe-rural, while the greatest decrease occurs in fringe expansion and urban expansion areas; and (3) interactions for changes in ES pairs also more closely linked in these two regions, with synergies dominating. …”

Data_road. by Qianhong Mao (22305184)

“…Most of the mean value of ESs showed a gradient increasing differences along urban-fringe-rural, while the greatest decrease occurs in fringe expansion and urban expansion areas; and (3) interactions for changes in ES pairs also more closely linked in these two regions, with synergies dominating. …”

Excel_ESs and transfer matrix. by Qianhong Mao (22305184)

“…Most of the mean value of ESs showed a gradient increasing differences along urban-fringe-rural, while the greatest decrease occurs in fringe expansion and urban expansion areas; and (3) interactions for changes in ES pairs also more closely linked in these two regions, with synergies dominating. …”

Data sources and descriptions. by Qianhong Mao (22305184)

“…Most of the mean value of ESs showed a gradient increasing differences along urban-fringe-rural, while the greatest decrease occurs in fringe expansion and urban expansion areas; and (3) interactions for changes in ES pairs also more closely linked in these two regions, with synergies dominating. …”

Coupling coordination types. by Qianhong Mao (22305184)

“…Most of the mean value of ESs showed a gradient increasing differences along urban-fringe-rural, while the greatest decrease occurs in fringe expansion and urban expansion areas; and (3) interactions for changes in ES pairs also more closely linked in these two regions, with synergies dominating. …”

Results_urban-fringe-rural. by Qianhong Mao (22305184)

“…Most of the mean value of ESs showed a gradient increasing differences along urban-fringe-rural, while the greatest decrease occurs in fringe expansion and urban expansion areas; and (3) interactions for changes in ES pairs also more closely linked in these two regions, with synergies dominating. …”

Land use map in Suzhou (2010 and 2022) based on GlobeLand30 classification. by Qianhong Mao (22305184)

Structure diagram of dynamic urban–fringe–rural areas. by Qianhong Mao (22305184)

ESs Changes in urban, fringe, and rural areas from 2010 to 2022. by Qianhong Mao (22305184)

Spatiotemporal patterns of urban–fringe–rural structure in Suzhou. by Qianhong Mao (22305184)

Multiple ESs interaction relationships under CCDM and trend direction analysis. by Qianhong Mao (22305184)

Spatial patterns and changes of ESs in Suzhou from 2010 to 2022. (Republished from Ministry of Natural Resources of China, http://bzdt.ch.mnr.gov.cn). by Qianhong Mao (22305184)

Spatiotemporal patterns of interactions among multiple ESs. by Qianhong Mao (22305184)

Alcohol-related monthly crude rates between 2018 and 2024, stratified by gender, age and cause of death. by Tony Wong (779773)