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significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
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level decrease » levels decreased (Expand Search), level increased (Expand Search), teer decrease (Expand Search)
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
greater decrease » greatest decrease (Expand Search), greater increase (Expand Search), greater disease (Expand Search)
level decrease » levels decreased (Expand Search), level increased (Expand Search), teer decrease (Expand Search)
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9601
Osteogenesis-related primer sequences.
Published 2024“…MiR-145a-3p inhibited the osteogenic differentiation ability of MC3T3-E1 cells by targeting and suppressing the expression level of Runx2 protein. Inhibition of miR-145a-3p levels significantly improved the osteogenic differentiation ability of MC3T3-E1 cells.…”
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9602
Cell-targeted transgenic control of 5HT<sub>2A</sub>R levels in neurons and glia during the experience-dependent critical period.
Published 2024“…Two-way ANOVA with Tukey’s multiple comparison shows EB experience-dependent increase in 5HT<sub>2A</sub> receptor levels in both transgenic controls (<i>n</i> = 10 each, <i>repo-</i>Gal4<i>; p</i> = 5.38 × 10<sup>−10</sup>, <i>elav</i>-Gal4; <i>p</i> = 0.0205), a significant decrease in 5HT<sub>2A</sub> receptor levels in both RNAi conditions (<i>n</i> = 10 each, <i>repo-</i>Gal4<i>; p</i> = 4.63 × 10<sup>−10</sup>, <i>elav-</i>Gal4; <i>p</i> = 1.05 × 10<sup>−9</sup>), and a significant elevated EB response with glial <i>5HT</i><sub><i>2A</i></sub><i>R</i> OE (<i>n</i> = 10/condition, <i>p</i> = 2.36 × 10<sup>−9</sup>). …”
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9603
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9604
Data Sheet 1_GBD: incidence rates and prevalence of anxiety disorders, depression and schizophrenia in countries with different SDI levels, 1990–2021.pdf
Published 2025“…</p>Results<p>In countries with different SDI levels, the age-standardized average annual percentage change (AAPC) in the incidence of anxiety were all shown to be increasing, and there were large gender differences between the different SDI levels, with a maximum of 0.97 (0.76–1.18) for females in countries with a high SDI level, Age-standardized more rates per 100,000 people in high SDI countries, from 658.87 in 1990 to 841.56 in 2021, and the largest gender differences in countries with a low to moderate SDI level, with AAPCs for males and females of 0.04 (0.04–0.05), 0.86 (0.63–1.09); for depression, only the countries with medium-high SDI levels were statistically significant compared to the countries with medium-low SDI levels, with AAPCs of 0.05 (0.04–0.07), 0.04 (0.04–0.05); for schizophrenia in addition to the AAPCs of the countries with medium-high SDI levels showed an increase of 0.16 (0.13–0.18); the rest decreased.…”
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9605
Final dataset.
Published 2025“…While a significant association between these attributes was observed, a comprehensive path analysis revealed that each attribute independently correlated with higher SDQ scores, suggesting that child maltreatment leads to these difficulties through accelerated aging and decreased eye contact. …”
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9606
Demographic Characteristics of Participants.
Published 2025“…While a significant association between these attributes was observed, a comprehensive path analysis revealed that each attribute independently correlated with higher SDQ scores, suggesting that child maltreatment leads to these difficulties through accelerated aging and decreased eye contact. …”
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9607
Table 1_Effects of neutral detergent fiber levels on apparent nutrient digestibility and intestinal microbiota composition and function in forest musk deer.docx
Published 2025“…At the genus level (the relative abundance > 1%), the three groups did not change (p > 0.05) significantly. …”
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9608
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9609
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9610
Planning data for different plots.
Published 2025“…<div><p>Automated large-scale farmland preparation operations face significant challenges related to path planning efficiency and uniformity in resource allocation. …”
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9611
Common turning methods.
Published 2025“…<div><p>Automated large-scale farmland preparation operations face significant challenges related to path planning efficiency and uniformity in resource allocation. …”
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9612
Algorithm comparison.
Published 2025“…<div><p>Automated large-scale farmland preparation operations face significant challenges related to path planning efficiency and uniformity in resource allocation. …”
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9613
Agricultural field path planning diagram.
Published 2025“…<div><p>Automated large-scale farmland preparation operations face significant challenges related to path planning efficiency and uniformity in resource allocation. …”
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9614
Schematic diagram of AIC operation.
Published 2025“…<div><p>Automated large-scale farmland preparation operations face significant challenges related to path planning efficiency and uniformity in resource allocation. …”
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9615
Partial field data of Huaxing Farm.
Published 2025“…<div><p>Automated large-scale farmland preparation operations face significant challenges related to path planning efficiency and uniformity in resource allocation. …”
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9616
Beluga Whale Optimization algorithm flow chart.
Published 2025“…<div><p>Automated large-scale farmland preparation operations face significant challenges related to path planning efficiency and uniformity in resource allocation. …”
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9617
Different operating angles θ = 90°, θ = 180°.
Published 2025“…<div><p>Automated large-scale farmland preparation operations face significant challenges related to path planning efficiency and uniformity in resource allocation. …”
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9618
Farm land preparation operation scheduling plan.
Published 2025“…<div><p>Automated large-scale farmland preparation operations face significant challenges related to path planning efficiency and uniformity in resource allocation. …”
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9619
NSGA-III algorithm flow chart.
Published 2025“…<div><p>Automated large-scale farmland preparation operations face significant challenges related to path planning efficiency and uniformity in resource allocation. …”
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9620
Illustrative diagram of the three crash types.
Published 2025“…</p><p>Results</p><p>Significant risk factors for overtaking crashes included heavy goods vehicles (HGVs) as crash partners (AOR = 1.30, 95% CI 1.27–1.33), and elderly crash partners (AOR = 2.01, 95% CI = 1.94–2.09), and decreased risk in rural area with speed limits of 20–30 miles per hour (AOR = 0.45, 95% CI = 0.43–0.47). …”