A noxious temperature decrease without a prior increase produces a subtly larger decrease in pain intensity. by Benedict J. Alter (9745466)

Results on the trimmed datasets with a decreasing number of papers per author available for training and testing. by Leonard Bauersfeld (16475015)

Long COVID prevalence decreases with vaccine uptake in the U.S. by Manlio De Domenico (626037)

“…<p>(A) Prevalence in U.S. states and the U.S. exhibits a decreasing trend with respect to vaccine uptake, both in the population vaccinated with at least one dose (top) and two doses (bottom), with the largest gap between 100% vaccinated and 100% unvaccinated scenarios observed in the reference population of adults who had COVID-19. …”

Pairwise correlations in APP/PS1 mice are decreased in dCA1, but increased in vCA1. by Udaysankar Chockanathan (18510288)

Subjects:

Population entropy in APP/PS1 mice is decreased in dCA1, but increased in vCA1. by Udaysankar Chockanathan (18510288)

Subjects:

Brief Report: Increased technology use associated with lower A1C in a large pediatric clinical population by G. Todd Alonso (9568724)

During electrical stimulation the decrease in compound action potential (CAP), but not of ATP, is larger in <i>Plp</i>^null/y mice. by Andrea Trevisiol (9647910)

Pairwise correlations of excitatory neurons in APP/PS1 mice are decreased in dCA1, but increased in vCA1. by Udaysankar Chockanathan (18510288)

Subjects:

MS decreases the larger amplitude distribution in adult rats. by Jesús David Ayala-Rodríguez (17364296)

Mean squared error of estimates decreases with larger datasets. by Alexander Eugene Zarebski (12078347)

Large <i>Bgl-</i>FaNaC neurons labeled with HCR <i>in situ</i> hybridization. by Laura C. Vicente-Rodríguez (16437803)

Alterations in fat body Lsd1 and Lsd2 levels upon the genetic increase or decrease in cardiac Snail TF levels. by Ying Liu (18461)

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

Subjects:

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

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)

“…The distribution shifts to the right (toward larger distances) as the dimensionality of the space increases. …”

Spatial information of excitatory neurons in APP/PS1 mice are decreased in dCA1 and vCA1. by Udaysankar Chockanathan (18510288)

Subjects:

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

The HMR C-terminus is required for HMR physiological function in <i>D</i>. <i>melanogaster</i>. by Andrea Lukacs (3752956)

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

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>…”