Sensitivity to small changes. by Ariel Burman (20329776)

The identified significant high-rate spatial-temporal clusters of new detected leprosy cases in Yunnan, China, 2011–2020. by Xiaohua Chen (257762)

Seasonal spatial-temporal trend of NDVI in burned areas across Africa (2001–2020). Percentages (%) of increases or decreases (%) based on the Mann-Kendall test and statistically significant (<i>p</i> < 0.05) and non-significant (p > 0.05) values. by Oswaldo Maillard (20660661)

Table 1_Subjective spatial orientation discomfort is associated with decreased real-world spatial performance and lower cognitive function.docx by Johannes Gerb (10287758)

Various natural factors and spatial distribution of the Grand Canal (East Zhejiang section)-Maritime Silk Road cultural heritage. by Jie Li (15030)

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BMR decreases with age. by Henrik H. Berntsen (11767710)

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Variable declaration of spatial econometric model. by Xiaofan Zhang (841027)

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Test results of spatial econometric model. by Xiaofan Zhang (841027)

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Heatmaps for direction and significance of dependence on radial position for all pairs in HFF cells. by Elizabeth H. Finn (7060988)

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A spatial Durbin model compared to a spatial error and lag model. by Sakar Hasan Hamza (20978818)

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Significant distribution of BL genes among annotated bacterial sources from patients comparing the pre- and post-eradication states. by Dita Gudra (4439767)

Source data for graphs. by Tucker Hopkins (20790529)

Relative risk of official bed bug complaints per NTA area for New York City incorporating a temporally structured fixed effect. by Kathryn P. Hacker (3329439)

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GTDE decreased the expression of the NLRP3 inflammasome and AGEs in the cerebral cortex. by Hui-Chuan Kuo (12368492)

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Pathway associated with decreased inflammation. by Monica N. Mweetwa (17054522)

The LM test is used to determine whether models contain spatial lag or spatial error. by Sakar Hasan Hamza (20978818)

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Estimation results of three spatial econometric models. by Xiaofan Zhang (841027)

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Data source and description. by Yunxia Zhang (30848)

“…The results show that: (1) the level of non-grain of cultivated land in Lianyungang City increased gradually from 6.01% to 11.10% from 2002 to 2022, and grain cultivation was mainly shifted to greenhouse vegetables, construction and development and abandonment. (2) the level of non-grain of cultivated land showed a spatial pattern of high along the north-west-south-east and decreasing to the two sides, and the pattern showed a trend of gradual weakening, with Moran’s I decreased from 0.90 to 0.42. (3) The dominant factors of the spatial differentiation of non-grain of cultivated land in different periods are different, among which GDP, population density, NDVI, and precipitation are always the main influencing factors. …”

Carbon emission factors for primary carbon sources. by Lingzhi Tan (19146572)

Source data of this study divided into three tables. by Martin Wasserbauer (6239699)