Data_road. by Qianhong Mao (22305184)

“…The findings include the following: (1) from 2010 to 2022, the spatial structure of urban-fringe-rural areas in Suzhou changed considerably, with 69.04% rural areas transformed into fringe areas, and 50.83% fringe areas developed into urban areas; (2) based on transition process, the region was further divided into urban maintenance, urban expansion, fringe maintenance, fringe expansion, and rural retention areas. 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)

“…The findings include the following: (1) from 2010 to 2022, the spatial structure of urban-fringe-rural areas in Suzhou changed considerably, with 69.04% rural areas transformed into fringe areas, and 50.83% fringe areas developed into urban areas; (2) based on transition process, the region was further divided into urban maintenance, urban expansion, fringe maintenance, fringe expansion, and rural retention areas. 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)

“…The findings include the following: (1) from 2010 to 2022, the spatial structure of urban-fringe-rural areas in Suzhou changed considerably, with 69.04% rural areas transformed into fringe areas, and 50.83% fringe areas developed into urban areas; (2) based on transition process, the region was further divided into urban maintenance, urban expansion, fringe maintenance, fringe expansion, and rural retention areas. 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)

“…The findings include the following: (1) from 2010 to 2022, the spatial structure of urban-fringe-rural areas in Suzhou changed considerably, with 69.04% rural areas transformed into fringe areas, and 50.83% fringe areas developed into urban areas; (2) based on transition process, the region was further divided into urban maintenance, urban expansion, fringe maintenance, fringe expansion, and rural retention areas. 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)

“…The findings include the following: (1) from 2010 to 2022, the spatial structure of urban-fringe-rural areas in Suzhou changed considerably, with 69.04% rural areas transformed into fringe areas, and 50.83% fringe areas developed into urban areas; (2) based on transition process, the region was further divided into urban maintenance, urban expansion, fringe maintenance, fringe expansion, and rural retention areas. 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. …”

Significance of the bell-shaped excess terms from regressions with Model 1. by Alfred Körblein (10202563)

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Regression using Model 2: Significance of the inverse of GDP as a covariate. by Alfred Körblein (10202563)

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Flow diagram of the patient selection into the final analysis. by Zi-Rong Chen (9227618)

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Associations between demographic variables, In4_SED and SE changes at 6 and 12 months after 4_SED (<i><i>n</i></i> = 80). by Zi-Rong Chen (9227618)

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Table 2 - Early identification of the efficacy of 0.125% atropine treatment for children with Myopia: A prospective pilot study by Zi-Rong Chen (9227618)

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<b>Nest mass in forest tits </b><b><i>Paridae</i></b><b> </b><b>increases with elevation and decreasing body mass, promoting reproductive success</b> by Clara Wild (19246606)

“…We found that nest mass increased by ~ 60% along the elevational gradient, but the effect of canopy openness on nest mass was not significant, while nest mass decreased along the ranked species from the smallest <i>Periparus ater</i> to the medium-sized <i>Cyanistes caeruleus</i> and the largest <i>Parus major</i>. …”

Data Sheet 2_An exploratory analysis of bezisterim treatment associated with decreased biological age acceleration, and improved clinical measure and biomarker changes in mild-to-m... by Christopher L. Reading (21236861)

Data Sheet 1_An exploratory analysis of bezisterim treatment associated with decreased biological age acceleration, and improved clinical measure and biomarker changes in mild-to-m... by Christopher L. Reading (21236861)

Detailed information of the observation datasets. by Weidong Ji (129916)

“…Generally speaking, there is no clear linear relationship between scores and the other variables. On longer time scales (6–24 hours), the score and correlation between ERA5 and observations further increased, while the centered root-mean-square error (CRMSE) and standard deviation decrease. 4) Hourly wind data with a regular spatial distribution in ERA5 reanalysis provides valuable information for further detailed research on meteorology or renewable energy perspectives, but some inherent shortcomings should be considered.…”

General technical specification for GW154/6700. by Weidong Ji (129916)

“…Generally speaking, there is no clear linear relationship between scores and the other variables. On longer time scales (6–24 hours), the score and correlation between ERA5 and observations further increased, while the centered root-mean-square error (CRMSE) and standard deviation decrease. 4) Hourly wind data with a regular spatial distribution in ERA5 reanalysis provides valuable information for further detailed research on meteorology or renewable energy perspectives, but some inherent shortcomings should be considered.…”

Path analysis diagram illustrating the associations between alexithymia, social support, anticipated stigma and patient satisfaction, with their respective correlation coefficients... by Keya Bibikar (22386306)

P values of Kruskal–Wallis test at 95% significance level. by Fahd Saeed Alakbari (10701871)

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Table 1_Increased frequencies of human Th-17 CD4+ T-cells and decreased T-regulatory cells in patients with early and advanced metabolic dysfunction-associated steatotic liver dise... by Elżbieta Supruniuk (16736637)

Table 2_Increased frequencies of human Th-17 CD4+ T-cells and decreased T-regulatory cells in patients with early and advanced metabolic dysfunction-associated steatotic liver dise... by Elżbieta Supruniuk (16736637)

Comparative Analysis of Chills Experience Across Three Groups: This table presents a detailed comparison of three groups (A, B, and C) in terms of their experiences with chills. It... by Felix Alexandre Schoeller (20988295)

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