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. …”

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)

PET acquisition parameters. by Edward M. Lawrence (3146364)

“…Comparing wbPET/CT to the subsequently acquired wbPET/MR, blood pool had a slight decrease in SUV_mean. The liver as well as parotid gland showed a slight increase in activity although the absolute bias only ranged from 0.45–1.28. …”

Evidence of the 2010-2015 anomaly in CGO raw data and MLO-CGO difference. by Roger J. Francey (22075453)

Seed germination kinetics of M. stenopetala under the effect of different PEG concentrations. by Nadia Khater (22553166)

Fig 5 - by Edward M. Lawrence (3146364)

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)

Principal component analyses (left) and cumulative components (right) of the studied parameters of moringa plants under drought stress conditions. by Nadia Khater (22553166)

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

Bland Altman analysis assessing inter-modality variability between PET/CT and PET/MR acquisitions. by Edward M. Lawrence (3146364)

“…<p>A slight bias of decreased SUV_mean for blood pool (top) and increased SUV_mean for liver (middle) and parotid gland (bottom) was seen for wbPET/MR compared to wbPET/CT regardless of reader. …”

Indices for N to S atmospheric transport. by Roger J. Francey (22075453)

Electrogastrography. by Chrysostomi Christina Tsianou (16007224)

Electrogastrography. by Chrysostomi Christina Tsianou (16007224)

Effect of squalene on antioxidative parameters from the three experimental models. by Clara Gabás-Rivera (613994)

Reference organ inter-subject variability according to reader and modality. by Edward M. Lawrence (3146364)

(A) Serotonin and (B) Dopamine levels in brain tissues. by Hammad Ismail (4227988)