Spatial information is significantly decreased in dCA1 and vCA1 in APP/PS1 mice. by Udaysankar Chockanathan (18510288)

“…(C) In vCA1, spatial information was decreased in APP/PS1 mice relative to C57BL/6 controls (mean ± std: C57BL/6 = 0.138 ± 0.065, APP/PS1 = 0.112 ± 0.035, p < 10⁻⁶, two-sided Wilcoxon rank-sum test, n_C57BL/6 = 689 units from 6 recording sessions, n_APP/PS1 = 651 units from 8 recording sessions). …”

Both MRI and SR-PCI demonstrated significant decreases in clinically-relevant articular cartilage parameters. by Suranjan Bairagi (17087667)

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Binary comparison matrix of increasing and decreasing trends in fire density from summer to autumn and comparison of different cases of spatial overlap of these spatial trends. by Peyman Karami (5909264)

Boruta, random forest model variable significance and ranking for biological sound producers. by Lindsey Transue (15322306)

“…Bars represent the significance (mean Z-score) of each variable from the Boruta wrapper algorithm based on a random forest model. …”

Estimation results of spatial Durbin panel data model. by Yuanzhi Guo (16624797)

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Decrease in cell movement as revealed by IPA. by Afrooz Jahedi (14636554)

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Estimation results of spatial Durbin panel data model by regions. by Yuanzhi Guo (16624797)

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Spatial Dubin panel model estimation results. by Xiaoyu Wan (644814)

“…It is found that: (1) the scale and vitality of China’s digital technology innovation have increased significantly, and there are obvious spatial differentiation characteristics, and the innovation level of "eastern coastal—central and western interior" is decreasing, forming a cluster distribution pattern in the Yangtze River Delta region, Beijing, Guangdong, and other places, and the degree of agglomeration is decreasing. (2) The overall regional differences in China’s digital technology innovation are large, the differences between the East and the West dominate the interregional differences, and the net differences between regions are the main factors leading to regional differences. (3) There is a significant positive spatial correlation between the scale and vitality of digital technology innovation, which has a significant spatial spillover effect. (4) The results confirm that the level of economic development, digital access, financial scientific and technological support, technology market development level, and R&D intensity have a significant positive impact on the scale and vitality of digital technology innovation; The investment in scientific and technological talents has a significant positive impact on the scale of digital technology innovation, but has no significant impact on the vitality of digital technology innovation.…”

Boruta, random forest model variable significance and ranking for sound pressure levels and anthropogenic noise detections. by Lindsey Transue (15322306)

“…Bars represent the significance (mean Z-score) of each variable from the Boruta wrapper algorithm based on a random forest model. …”

ECoG timescales decrease during spatial attention. by Isabel Raposo (21615517)

“…Bottom: timescales significantly decrease during covert attention relative to the attend-out condition (two locations: <i>p</i> = 0.0244; four locations: <i>p</i> < 0.0001; mean ± SEM; whiskers indicate maximum and minimum; dots correspond to individual electrodes). …”

Parallel bonding model. by Qingwen Li (1510687)

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Linear contact model. by Qingwen Li (1510687)

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Spatial distributions of the TVDI in the different seasons in the Santun River Irrigation Area, Xinjiang. by Yuxin Wei (11510974)

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Mechanical model of geogrid element. by Qingwen Li (1510687)

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Shows 48/86 genes have differential expression consistent with the direction of decrease in cell movement. by Afrooz Jahedi (14636554)

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Persistent AF decreases left atrial organizational index. by Terrence Pong (511730)

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CCD evaluation results of different eco–geological divisions in Northeast China. by Guofang Tao (12368729)

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Spatial econometric model estimation results. by Zijie Li (776536)

“…In the stage of high-quality development (2012 present), the contribution rate of technological factors continued to rise and become the dominant factor, while the contribution rate of land factors has decreased to a lower level. (2) Regarding spatial characteristics, the spatial econometric model reveals significant spatial agglomeration characteristics of capital and labor, and land factors positively affect local and neighboring economic growth. …”

Speed and time cost for different road types. by Jilei Tao (20208621)

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Mesoscopic parameters of PFC3D-FLAC3D coupling model. by Qingwen Li (1510687)

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