Multivariate analysis of sociodemographic and other factors associated with the KAP scores. by Sara Saleh (6733619)

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Bivariate analysis of sociodemographic and other factors associated with the practice scores. by Sara Saleh (6733619)

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Data from: Colony losses of stingless bees increase in agricultural areas, but decrease in forested areas by 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>…”

Spatiotemporal changes in factors influencing the health level of older adults in the Yangtze River Economic Belt, 2010–2020. by Mengmeng Yang (475288)

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Multivariate logistic regression analysis on the risk factors associated with prolonged APTT. by Huan Wang (109286)

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Average difference in mean daily exercise minutes in the week before and after the specified software transition, using different minimum data thresholds. by Shelby L. Sturrock (10751675)

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Average difference in mean daily active calories in the week before and after the specified software transition, using different minimum data thresholds. by Shelby L. Sturrock (10751675)

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Plasma cholesterol and LDL-C levels. by Xueqin lu (22250795)

Significantly decreased necrosis observed on wheat leaves inoculated with <i>ΔZtknr4</i>. by Erika Kroll (20537020)

Changes in inflammatory cytokine levels compared with baseline values in all patients over time. by Jia Song (495396)

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Forest plot of pooled effects of ecological factors associated with TB incidence. by Alemneh Mekuriaw Liyew (9216921)

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Factors associated with anemia stratified by age group: By logistic regression. by Alejandro Rojas Chaves (20614814)

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Decreased IL-1 and inflammasome, and chemokine gene expression pattens in response to Pam3CSK4 in BRD diagnosed calves. by Cian Reid (17274007)

Mean age of patients submitting stool samples per study site. by Amete Mihret Teshale (12072758)

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FGF18 injections increase TIMP1 and decrease MMP13 and NOGGIN, suggesting healing of degeneration induction of anabolic effect. by Flavia Gomes Velasque Gama (21175112)

Changes in the UACR and urinary β2-MG levels compared with baseline values over time. by Jia Song (495396)

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Comparison of the rates of decline in the UACR and urinary β2-MG levels between the two subgroups. by Jia Song (495396)

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Comparison of serum vitamin D and calcium levels in patients with stable and unstable intertrochanteric fractures included in this study. by Kamran Alijanpour (20314706)

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Sociodemographic, occupational, and clinical risk factors associated with low workability and results of Logistic regression analysis among diabetic workers. by Sarah A. Bolbol (21702891)

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Expression levels of SACMV DNA-A and DNA-B encoded virulence factors in TME3 and T200 at 12, 32 and 67dpi measured by RT-qPCR. by Bulelani L. Sizani (21485746)

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