The update step size of the attractor set in different regions. by Long Di (9977453)

Factors associated with AL score (multivariable regression analyses for the third follow-up). by Eric Priedemann (21175492)

Subjects:

Flow of premises through the study. by Eleni Mantzari (6991172)

Subjects:

Additional file 7 of Decreased complement 4 and interleukin-10 as biomarkers in aqueous humour for non-exudative age-related macular degeneration: a case control study by Juliane Schikora (20871169)

Additional file 11 of Decreased complement 4 and interleukin-10 as biomarkers in aqueous humour for non-exudative age-related macular degeneration: a case control study by Juliane Schikora (20871169)

Additional file 10 of Decreased complement 4 and interleukin-10 as biomarkers in aqueous humour for non-exudative age-related macular degeneration: a case control study by Juliane Schikora (20871169)

Additional file 3 of Decreased complement 4 and interleukin-10 as biomarkers in aqueous humour for non-exudative age-related macular degeneration: a case control study by Juliane Schikora (20871169)

Female regression coefficients for regression #3 across development in set size = 2 and set size = 4. by Juliana Chase (20469427)

“…All statistics are done identically and are reported in the text. There was a slight decrease in the regression coefficient weight of intercept for set size = 2 (A), but not set size = 4 (F). …”

Effect of session on winning model parameters for set size = 2 and set size = 4 for both male and females. by Juliana Chase (20469427)

“…<p>To test if mice adjusted one-back strategies with experience, we next compared how parameter weights (y-axis) changed across the 6 sessions analyzed for each mouse (x-axis). Since set size = 2 and set size = 4 days were interspersed, we combined set size data and analyzed sessions chronologically. …”

Data Set. by Yang Li (7082)

Parameter sets generated through Latin hypercube sampling. by Alexandra M. Campbell (3284094)

Annual treatment frequencies in all eyes. by Yasuyuki Sotani (20114144)

“…<p>The number of anti-VEGF treatments, STTA, MA-PC, PPV, and total treatments (mean ± SD) significantly decreased from 2.6 ± 1.6, 0.3 ± 0.8, 0.6 ± 0.8, 0.1 ± 0.3, and 3.7 ± 1.7 preoperatively to 0.8 ± 1.9, 0.0 ± 0.2, 0.3 ± 1.0, 0.0, and 1.2 ± 2.2; at year 2 to 0.7 ± 2.0, 0.1 ± 0.6, 0.0 ± 0.2, 0.0 ± 0.2, and 1.0 ± 2.1; and at year 3 to 0.9 ± 2.2, 0.0, 0.2 ± 1.0, 0.0 ± 0.2, and 1.1 ± 3.1 (Kruskal–Wallis test, P < 0.001; Dunn’s test, **P < 0.01). …”

Annual number of outpatient visits in all eyes. by Yasuyuki Sotani (20114144)

“…<p>Mean visit frequency (mean ± standard deviation) significantly decreased from 11.5 ± 4.3 preoperatively to 8.8 ± 4.1, 5.0 ± 3.4, and 4.4 ± 3.2 visits in the first, second, and third postoperative years, respectively (Kruskal–Wallis test, P < 0.001; Dunn’s test, **P < 0.01). …”

Time course of central retinal thickness (CRT) in recurrence and non-recurrence groups. by Yasuyuki Sotani (20114144)

“…These values significantly decreased in the first postoperative year to 2.3 ± 2.6, 0.1 ± 0.3, 0.8 ± 1.6, 0, and 3.1 ± 2.8; in the second year to 2.1 ± 2.8, 0.4 ± 1.0, 0.0, 0.1 ± 0.3, and 2.6 ± 2.8; and in the third year to 2.0 ± 2.2, 0, 0.6 ± 1.7, 0.1 ± 0.3, and 2.8 ± 3.5 (Kruskal–Wallis test, p < 0.001; <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0332941#pone.0332941.g007" target="_blank">Fig 7</a>). …”

Annual treatment frequencies in recurrence and non-recurrence groups. by Yasuyuki Sotani (20114144)

“…These significantly decreased to 2.3 ± 2.6, 0.1 ± 0.3, 0.8 ± 1.6, 0.0, and 3.1 ± 2.8 in the first year; 2.1 ± 2.8, 0.4 ± 1.0, 0, 0.1 ± 0.3, and 2.6 ± 2.8 in the second year; and 2.0 ± 2.2, 0, 0.6 ± 1.7, 0.1 ± 0.3, and 2.8 ± 3.5 in the third year (Kruskal–Wallis test, p < 0.001; Dunn’s test, *P < 0.05, **P < 0.01). …”

Strategy parameters across development for female mice in set size = 2 and set size = 4 from winning computational model. by Juliana Chase (20469427)

“…However, female mice had a significant decrease in parameter S1 “Inappropriate Lose-Shift” in set size = 4 (H: <i>p</i> = 0.04) with a trend in a similar direction in set size = 2 (C: <i>p</i> = 0.08).…”

Intraoperative facial and intraoral photographs of the case with mandibular third molar extraction. by Lijuan Liu (136685)

Strategy parameters across development for male mice in set size = 2 and set size = 4 from winning computational model. by Juliana Chase (20469427)

“…RL parameter <i>α</i>₊ learning rate and decision noise parameter softmax <i>β</i> were stable across development in both set size = 2 (A-B) and set size = 4 (F-G). Both parameters S1 “Inappropriate Lose-Shift” and S3 “Inappropriate Lose-Stay” decreased significantly with age in set size = 2 (C: <i>p</i> = 0.02, E: <i>p</i> = 0.04), but not in set size = 4 (H,J). …”

Posttreatment facial, intraoral photographs, and radiographs of the case with mandibular third molar extraction. by Lijuan Liu (136685)

Pretreatment facial, intraoral photographs, and radiographs of the case with mandibular third molar extraction. by Lijuan Liu (136685)