Office characteristics and RW adoption. حسب Yasuhiko Deguchi (3167955)

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Newly occurring LTSA-MD cases in workers for over a month. حسب Yasuhiko Deguchi (3167955)

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Difference in the number of LTSA between FY 2020 and FY 2019. حسب Yasuhiko Deguchi (3167955)

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Determination of SCFA content in fecal stool and intestinal metabolites of rats in each group. حسب Shudan Liu (7049483)

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Pairwise comparison of adult longevity across treatments. P-values from pairwise comparisons between control conditions and irradiation doses. Values in boldface indicate significa... حسب Flavia Cerasti (21655934)

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Data from: Colony losses of stingless bees increase in agricultural areas, but decrease in forested areas حسب Malena Sibaja Leyton (18400983)

"…</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>…"

Survey-weighted association of flavonoids and six subclasses intake with MASLD. حسب Yuwei He (1565941)

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Survey-weighted baseline characteristic of the study population by MASLD. حسب Yuwei He (1565941)

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Weighted Quantile Sum model regression index weights for the MASLD. حسب Yuwei He (1565941)

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Association between flavonoid intakes and metabolic dysfunction-associated steatotic liver disease (MASLD) using a Restricted Cubic Spline regression model, adjusted for age, sex,... حسب Yuwei He (1565941)

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The flowchart of the sample selection from NHANES 2007-2010, 2017-2018. حسب Yuwei He (1565941)

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Equivalent effect model. حسب Xueting Ma (390540)

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Simulation model. حسب Xueting Ma (390540)

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Displacement of soil particles in z direction. حسب Xueting Ma (390540)

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Simulation parameters [13]. حسب Xueting Ma (390540)

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Displacement of soil particles in x direction. حسب Xueting Ma (390540)

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Soil particle simulation model. حسب Xueting Ma (390540)

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Multi-factor experimental results. حسب Xueting Ma (390540)

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Frequency-displacement curve. حسب Xueting Ma (390540)

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Bonding bonds between soil particles. حسب Xueting Ma (390540)

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