S10 Fig - by Jordan K. Abbott (8934239)

Subjects:

Increasing the number of commonly represented features decreases the assignment error rate, but increases the level of redundancy between the representations. by W. Jeffrey Johnston (8463480)

“…This is true for points with any distribution that has non-zero variance. <b>C</b> At the average distance between two points (dashed lines), the probability of an assignment error decreases by orders of magnitude as the dimensionality of the commonly represented space increases, without changing the estimator variance for the representations <i>D</i>_<i>XY</i> = 10. …”

Both cis- and trans-cycles decrease in number upon treatment with auxin. by Manu Aggarwal (15990691)

“…(C) The number of trans-cycles also decreased. (D) The opacity of edge (<i>c</i>_<i>i</i>, <i>c</i>_<i>j</i>) indicates a difference in the number of trans cycles between control and auxin-treated that go through chromosomes <i>c</i>_<i>i</i> and <i>c</i>_<i>j</i>. …”

An osprey nest with a large chick and an unhatched egg (photo P. Saurola). by Matti Viluksela (321291)

Subjects:

Average effect size decreased as sample size increased for all types of analyses (<i>p</i> < .001). by Luke J. Ney (12621627)

Matrix crosslinking decreases cell migration persistence. by Michael Pamonag (12295175)

In the absence of <i>eIF4E1</i>, global translation activity decreases while virus accumulation increases. by Delyan Zafirov (17420106)

The PRAME-AS knockout cells showed a decrease in migration, proliferation, stemness, and viability. by Zahra Hosseininia (22265113)

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>…”

Percentage of exhale flux penetrating through the mask fabric for different values of <i>c</i>_<i>k</i>; a–c and d–f decreasing porosity for outward and inward protection... by Akshay Anand (118579)

Percentage of US adults with health insurance coverage by income-level, age 60 to 70 years. by Rahul Aggarwal (4428457)

Measures of access and affordability by income level, age 57 to 73 years. by Rahul Aggarwal (4428457)

“Surface Browsing” May Allow “Filter-Feeding” Protozoa to Exert Top-Down Control on Colony-Forming Toxic Cyanobacterial Blooms by Wenjie Xu (183092)

“…We show that this is not so: the model ciliate Paramecium has an impact on Microcystis populations through grazing, even when large colonies occur, and this leads to a corresponding decrease in toxic microcystins. …”

“Surface Browsing” May Allow “Filter-Feeding” Protozoa to Exert Top-Down Control on Colony-Forming Toxic Cyanobacterial Blooms by Wenjie Xu (183092)

“…We show that this is not so: the model ciliate Paramecium has an impact on Microcystis populations through grazing, even when large colonies occur, and this leads to a corresponding decrease in toxic microcystins. …”

“Surface Browsing” May Allow “Filter-Feeding” Protozoa to Exert Top-Down Control on Colony-Forming Toxic Cyanobacterial Blooms by Wenjie Xu (183092)

“…We show that this is not so: the model ciliate Paramecium has an impact on Microcystis populations through grazing, even when large colonies occur, and this leads to a corresponding decrease in toxic microcystins. …”

The HMR complex components BOH1 and BOH2 largely colocalize with HMR in proximity to centromeres and HP1a domains (related to Fig 1). by Andrea Lukacs (3752956)

Seven out of the 11 human cytidine deaminases are more highly expressed in tumor versus normal tissue and their higher expression is correlated with a decrease in survival. by Mason A. McCool (11889842)

“…An increase in expression and a decrease in survival quadrant are indicated by the gray background. …”

GI-1d-a: Comparison of estimates of people for dataset A (left bar) and B (right bar) per region. The largest discrepancies occur in areas of NE, SE and SW Germany and adjacent reg... by Isabell Schmidt (6331013)

Spatial stability is decreased in APP/PS1 mice in both dCA1 and vCA1. by Udaysankar Chockanathan (18510288)

Subjects:

NHERF1 protein levels increase with increased cell density. by Camille M. Drews (4721175)

“…<p>(<b>A</b>) Protein levels of endogenous NHERF1 increase with cell confluency. …”