HDECO: A method for Decreasing energy and cost by using virtual machine migration by considering hybrid parameters by Arash GhorbanniaDelavar (22563696)

“…<h2>Summary</h2><p dir="ltr">This research introduces <b>HDECO</b> (Hybrid Decreasing Energy and Cost Optimization) — a method designed to reduce both energy consumption and execution cost in cloud datacenters through intelligent virtual machine migration. …”

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

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)

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). …”

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

Thematic clouds for lectures. by Ignacio García-Espona (21395335)

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)

Displacement cloud maps. by Maogang Tian (21485116)

AL scores at baseline and follow-ups. by Eric Priedemann (21175492)

Subjects:

Superimposition of the cephalometric tracings obtained before and after treatment of case with mandibular third molar extraction. by Lijuan Liu (136685)

Comparison of pretreatment cephalometric variables between premolar extraction and mandibular third molar extraction groups. by Lijuan Liu (136685)

Candidates from the RF method. The top 25 random forest candidates ranked by mean decrease in accuracy and mean decrease in Gini Index are in the first and second columns, respectively.... by Zoë Parker Cates (22184243)

“…The top 25 random forest candidates ranked by mean decrease in accuracy and mean decrease in Gini Index are in the first and second columns, respectively. …”

Predicted^* value of age at school entry (in years), by level of height-for-age. by Rabi Joël Gansaonré (20416803)