Variables for the bromeliad agent representing a single <i>T. utriculata</i> rosette. by Alexandra M. Campbell (3284094)

(A) Auxiliary marking points to ensure complete and accurate seating of the prosthesis. by Long Li (6555)

The distribution of <i>Giardia duodenalis</i> assemblages in domestic and wild populations of nonhuman mammalian species with a larger number of isolates. by Kareem Hatam-Nahavandi (7384790)

Reducing Dscam1 diversity decreases adult lifespan in a cluster-specific manner, also see S6 and S7 Figs. by Haiyang Dong (4783608)

Reducing Dscam1 diversity decreases adult lifespan in an exon-specific manner, Related to Fig 3. by Haiyang Dong (4783608)

Definitions of the variables. by Yulian Ding (5984591)

Variables of trees located at coordinates . by Alexandra M. Campbell (3284094)

“…Furthermore, uncertainty analysis showed that the mean MSI of the population decreased over a 100-year period without weevil predation, and this trend was exacerbated by the presence of weevil predation.…”

Global parameters and variables for the model. by Alexandra M. Campbell (3284094)

“…Furthermore, uncertainty analysis showed that the mean MSI of the population decreased over a 100-year period without weevil predation, and this trend was exacerbated by the presence of weevil predation.…”

Variables of patch located at coordinates . by Alexandra M. Campbell (3284094)

“…Furthermore, uncertainty analysis showed that the mean MSI of the population decreased over a 100-year period without weevil predation, and this trend was exacerbated by the presence of weevil predation.…”

Cinacalcet administered early in the inactive phase markedly decrease parathyroid Ki-67 index. by Søren Egstrand (10906087)

Response distributions for the questions that represent the latent variable ‘cautious sexual attitudes’. by Abigail A. Lee (19935335)

Concentrations (c) or activities (a) of the biochemical compounds involved in the cellular respiration and energy metabolism and their variability in the workerbees sampled from th... by Jerzy Paleolog (3220308)

Study-related adverse events. by Benjamin R. Lewis (22279166)

“…We recorded 12 study-related, Grade 1–2 AEs and no serious AEs. In a linear mixed model analysis (LMM), the MBSR + PAP arm evidenced a significantly larger decrease in QIDS-SR-16 score than the MBSR-only arm from baseline to 2-weeks post-intervention (between-groups effect = 4.6, 95% CI [1.51, 7.70]; <i>p</i> = 0.008). …”

Study flow chart. by Benjamin R. Lewis (22279166)

“…We recorded 12 study-related, Grade 1–2 AEs and no serious AEs. In a linear mixed model analysis (LMM), the MBSR + PAP arm evidenced a significantly larger decrease in QIDS-SR-16 score than the MBSR-only arm from baseline to 2-weeks post-intervention (between-groups effect = 4.6, 95% CI [1.51, 7.70]; <i>p</i> = 0.008). …”

Study CONSORT diagram. by Benjamin R. Lewis (22279166)

“…We recorded 12 study-related, Grade 1–2 AEs and no serious AEs. In a linear mixed model analysis (LMM), the MBSR + PAP arm evidenced a significantly larger decrease in QIDS-SR-16 score than the MBSR-only arm from baseline to 2-weeks post-intervention (between-groups effect = 4.6, 95% CI [1.51, 7.70]; <i>p</i> = 0.008). …”

Lifespan of <i>C. elegans</i> is robust to increases or decreases in rDNA copy number within the natural range. by Ashley N. Hall (14755301)

Principle Coordinates Analysis (PCoA) projected onto 2 dimensions between pol-wgs mixtures and nFL genome, full dataset by August Guang (9975678)

Decreased childhood asthma hospitalizations linked to hotter, drier climate with lower wind speed in drylands by Klézio Silva Monte (20579829)

“…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. …”

<b>Extreme drought decreases the stability of above- but not belowground productivity across Eurasian steppes</b> by Yingjie Yan (6535112)

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>…”