The global disease burden of osteoarthritis for both sexes in 204 countries and territories. by Xiaoqing Chen (89898)

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Machine Learning Model Performance Sorted by Decreasing MAE. by Renan N. D. Almeida (9265283)

PAP I point mutations lead to a decrease in pYV PCN, plasmid stability, and T3SS activity. by Katherine Schubert (5452712)

Univariable associations between childhood factors and suicidal ideation. by Massimiliano Orri (560000)

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Multivariable associations between childhood factors and suicidal ideation. by Massimiliano Orri (560000)

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Influencing factors of APCA. by Wenping Ning (19871091)

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The significance of the specific Nusselt number on a variety of factors. by Siva Sankari (2827295)

The significance of the specific Nusselt number on a variety of factors. by Siva Sankari (2827295)

The significance of the specific Nusselt number on a variety of factors. by Siva Sankari (2827295)

The significance of the specific Nusselt number on a variety of factor. by Siva Sankari (2827295)

Kaplan-Meier survivor estimates by functional outcome, age group, hospital bill payment and housing status. by Farayi Kaseke (19560197)

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Motifs significantly enriched in decreased ATAC peaks relative to unchanged ATAC peaks at 30 minutes. by Thomas G. Scott (4092892)

Isotype control overlays. by Chen Lu (135200)

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Original uncropped blot. by Chen Lu (135200)

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Raw Data. by Chen Lu (135200)

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Change in influenza vaccination uptake from May 2020 to October 2024 (weighted). by Hannah Melchinger (20234665)

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

“…Based on the Reference Relationship Table of the Classification of Core Industries of Digital Economy and the International Patent Classification (2023), the patent authorization data of digital technology from 2012 to 2022 were obtained, and the spatiotemporal situation of China’s digital technology innovation was analyzed by using ArcGIS software, Dagum’s Gini coefficient, and Moran’s I index, and the spatial Dubin panel model was used to explore the influencing factors of digital technology innovation. 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.…”

Age-standardized rates of PUD globally and for 21 GBD regions by SDI, 1990–2021. by Wende Hao (10315597)

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Odds ratio of multivariable analysis of factors for Shiga-toxin producing <i>Escherichia coli</i> (<i>stx</i> by Amete Mihret Teshale (12072758)

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Estimates of the differencing parameter, d, in Eq (1). by Luis Alberiko Gil-Alana (14659817)