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significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
i decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
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HDECO: A method for Decreasing energy and cost by using virtual machine migration by considering hybrid parameters
Published 2025“…<h2>Summary</h2><p dir="ltr">This research introduces <b>HDECO</b> (Hybrid Decreasing Energy and Cost Optimization) — a method designed to reduce both energy consumption and execution cost in cloud datacenters through intelligent virtual machine migration. …”
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Evogliptin attenuates the phenotypic switch of VSMCs during CER treatment by decreasing the osteogenesis-associated genes <i>in-vitro.</i>
Published 2025“…(B, C) Summarized bar graph showed EVO significantly decreased calcium deposition and calcium content in CER treated P<sub>i</sub>-induced VSMCs. …”
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Mechlorethamine gel causes epithelium thinning, epithelium-stroma separation, and decreased total stroma cell count.
Published 2025“…<p>A) Epithelium thickness decreased, and B) the percentage of epithelium-stroma separation increased after NM exposure. …”
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Decreased childhood asthma hospitalizations linked to hotter, drier climate with lower wind speed in drylands
Published 2025“…Monthly trends in hospitalizations and climatic variables were calculated. A generalized additive model analyzed the association between these trends, and the Mann-Kendall test determined if trends were increasing, decreasing, or not significant. …”
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Supplementary Material for: Longitudinal Decrease in Left Ventricular Size with Age: Impact on Mortality and Cardiovascular Hospitalization
Published 2025“…Sensitivity analysis using annual LVEDD change (>1mm/year) demonstrated a significant association with mortality (HR 1.45, 95% CI 1.26-1.66, p<0.001) and the combined endpoint of death/cardiovascular hospitalization (HR 1.26, 95% CI 1.12-1.41, p<0.001). …”
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Presentation 1_Prehospital tranexamic acid decreases early mortality in trauma patients: a systematic review and meta-analysis.pdf
Published 2025“…Compared to the control group, the prehospital TXA group exhibited a significant reduction in 24-h mortality with an OR of 0.72 and a 95% CI of 0.54–0.94 (p = 0.02), while no statistically significant difference in the incidence of venous thromboembolism (VTE; OR: 1.14, 95% CI: 0.98–1.33, p = 0.09). …”
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Table_1_FMT intervention decreases urine 5-HIAA levels: a randomized double-blind controlled study.DOCX
Published 2024“…However, in the placebo group, GSRS, CARS, and SRS scores showed no significant changes, while ABC scores decreased from 72 to 58.75 (p = 0.034). …”
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Data from: Colony losses of stingless bees increase in agricultural areas, but decrease in forested areas
Published 2025“…</p><p><br></p><p dir="ltr">#METADATA</p><p dir="ltr">#'data.frame': 472 obs. of 28 variables:</p><p dir="ltr"> #$ ID: Factor variable; a unique identity for the response to the survey</p><p dir="ltr"> #$ Year: Factor variable; six factors available (2016, 2017, 2018, 2019, 2020, 2021) representing the year for the response to the survey</p><p dir="ltr"> #$ N_dead_annual: Numeric variable; representing the number of colonies annually lost</p><p dir="ltr">#$ N_alive_annual: Numeric variable; representing the number of colonies annually alive</p><p dir="ltr"> #$ N_dead_dry: Numeric variable; representing the number of colonies lost during the dry season</p><p dir="ltr">#$ N_alive_dry: Numeric variable; representing the number of colonies alive during the dry season</p><p dir="ltr"> #$ N_dead_rainy: Numeric variable; representing the number of colonies lost during the rainy season</p><p dir="ltr">#$ N_alive_rainy: Numeric variable; representing the number of colonies alive during the rainy season</p><p dir="ltr"> #$ Education: Factor variable; four factors are available ("Self-taught","Learned from another melip","Intro training","Formal tech training"), representing the training level in meliponiculture</p><p dir="ltr"> #$ Operation_Size: Numeric variable; representing the number of colonies managed by the participant (in n)</p><p dir="ltr"> #$ propAgri: Numeric variable; representing the percentage of agricultural area surrounding the meliponary (in %)</p><p dir="ltr"> #$ propForest: Numeric variable; representing the percentage of forested area surrounding the meliponary (in %)</p><p dir="ltr">#$ temp.avg_annual: Numeric variable; representing the average annual temperature (in ºC)</p><p dir="ltr">#$ precip_annual_sum: Numeric variable; representing the total accumulated precipitation (in mm)</p><p dir="ltr">#$ precip_Oct_March_sum: Numeric variable; representing the total accumulated precipitation between October to March (in mm)</p><p dir="ltr">#$ precip_Apri_Sept_sum: Numeric variable; representing the total accumulated precipitation between April to September (in mm)</p><p dir="ltr">#$ temp.avg_Oct_March: Numeric variable; representing the total accumulated precipitation between October to March (in ºC)</p><p dir="ltr">#$ temp.avg_Apri_Sept: Numeric variable; representing the total accumulated precipitation between April to September (in ºC)</p><p dir="ltr"> #$ Importance_dead: Factor variable; three factors are available Normal","High","Very high"), representing the perception of the significance of annual colony losses</p><p dir="ltr"> #$ Climatic_environmental: Binary variable; representing if the participant considered climatic and environmental problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr"> #$ Contamination: Binary variable; representing if the participant considered contamination problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr"> #$ Nutritional: Binary variable; representing if the participant considered nutritional problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Sanitary: Binary variable; representing if the participant considered sanitary problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Queen: Binary variable; representing if the participant considered queen problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Time: Binary variable; representing if the participant considered time problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Economic: Binary variable; representing if the participant considered economic problems as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Attacks: Binary variable; representing if the participant considered time attacks as a potential driver (1) or not (0) of their annual colony losses</p><p dir="ltr">#$ Swarming: Binary variable; representing if the participant considered swarming problems as a potential driver (1) or not (0) of their annual colony losses</p><p><br></p>…”