Fig 6 - by Mark Altaweel (4925275)

Urban sites collected for this article. by Mark Altaweel (4925275)

RZC purification of 6-hb dimer. by Jason Sentosa (16617743)

RZC purification of high and low aspect ratio DNA origami nanostructures. by Jason Sentosa (16617743)

Descriptive statistics of surface soils (0–30 cm) in the study area [34]. by Orhan Mete Kılıc (11707457)

Geographic representation of centrality measures for streets in the ancient town of Dura Europos in modern Syria. by Mark Altaweel (4925275)

Upwelling index series. by Antonio Bode (1473376)

Cohesion characteristics and statistical significance analysis of different ingredients across IDDSI levels^b'*'. by Muxi Chen (9294270)

Adhesion characteristics and statistical significance analysis of different ingredients across IDDSI levels^b'*'. by Muxi Chen (9294270)

Hardness characteristics and statistical significance analysis of different ingredients across IDDSI levels^b'*'. by Muxi Chen (9294270)

Distribution of different ingredients at the same IDDSI level (Percentage and frequency) and statistical significance analysis (Chi-square test)^b'*'. by Muxi Chen (9294270)

Sociodemographic characteristics of the sample. by Senay Yildirim-Kahriman (22693464)

“…A moderate negative correlation was observed between CAM and CAM-MYCS scores (r = −0.511; p < 0.001), indicating that increased awareness of real causes is associated with decreased belief in myths. …”

Relationships between hardness and IDDSI levels. by Muxi Chen (9294270)

“…Cohesiveness varied without a clear linear trend, showing significant changes at specific IDDSI levels for meats, grains, and tubers (<i>p</i>≤0.05). …”

Glycerol gradient preparation and RZC purification (S1 Movie in S1 File). by Jason Sentosa (16617743)

Per capita payoffs under different experimental conditions. by Julie C. Jarvey (12859384)

Response times. by Aoife M. Fitzpatrick (13955365)

Rabbit length of stay data. by Ashley Sum Yin U. (18437434)

“…The median LOS of rabbits was 29 days, highlighting the pressing need to improve their time to adoption. A linear model was constructed to identify predictors of LOS of adopted rabbits (n = 1203) and revealed that intake year, intake month, source of intake, age, cephalic type, and breed size significantly predicted time to adoption for rabbits (F(37, 1165) = 7.95, <i>p</i> < 2.2e-16, adjusted R² = 0.18). …”

Surrender reasons (n = 649). by Ashley Sum Yin U. (18437434)

“…The median LOS of rabbits was 29 days, highlighting the pressing need to improve their time to adoption. A linear model was constructed to identify predictors of LOS of adopted rabbits (n = 1203) and revealed that intake year, intake month, source of intake, age, cephalic type, and breed size significantly predicted time to adoption for rabbits (F(37, 1165) = 7.95, <i>p</i> < 2.2e-16, adjusted R² = 0.18). …”

R script. by Ashley Sum Yin U. (18437434)

“…The median LOS of rabbits was 29 days, highlighting the pressing need to improve their time to adoption. A linear model was constructed to identify predictors of LOS of adopted rabbits (n = 1203) and revealed that intake year, intake month, source of intake, age, cephalic type, and breed size significantly predicted time to adoption for rabbits (F(37, 1165) = 7.95, <i>p</i> < 2.2e-16, adjusted R² = 0.18). …”

Surrender reasons and descriptions. by Ashley Sum Yin U. (18437434)

“…The median LOS of rabbits was 29 days, highlighting the pressing need to improve their time to adoption. A linear model was constructed to identify predictors of LOS of adopted rabbits (n = 1203) and revealed that intake year, intake month, source of intake, age, cephalic type, and breed size significantly predicted time to adoption for rabbits (F(37, 1165) = 7.95, <i>p</i> < 2.2e-16, adjusted R² = 0.18). …”