Relation between training-related changes in unipedal and bipedal stance. by Cristina Dolciotti (16317330)

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Consolidation of training-induced changes in unipedal stance: 95% Area, Y Sway Amplitude and LFS. by Cristina Dolciotti (16317330)

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Consolidation of training-induced changes in unipedal stance: Path Length, X Sway Amplitude and Velocity. by Cristina Dolciotti (16317330)

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Time course of 95% Area, X and Y Amplitude Sway during postural training. by Cristina Dolciotti (16317330)

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Correlations between unipedal and bipedal stance parameters recorded at the beginning of the training and of the control session. by Cristina Dolciotti (16317330)

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Flow diagram. by Cristina Dolciotti (16317330)

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Comparison of neutrophils, lymphocyte and platelet between the two groups. by Changxu Wang (17826805)

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S1 File - by Changxu Wang (17826805)

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Baseline patient characteristics and surgical and anesthetic datas. by Changxu Wang (17826805)

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Postoperative pain assessment indexes, nausea and vomiting frequency, and postoperative recovery of patients in two groups. by Changxu Wang (17826805)

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The flow chart of the study. by Changxu Wang (17826805)

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Comparison of postoperative NLR, PLR, and SII between the two groups. by Changxu Wang (17826805)

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The global disease burden of <i><i>Klebsiella pneumoniae</i></i> associated LRI for both sexes in 204 countries and territories. (a) The number of deaths in 2021; (b) The EAPC of d... by Juanjuan Li (399633)

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Descriptive statistics of outcomes at baseline, post-intervention, and follow-up and estimates of the linear mixed effects model for the outcomes. by Ana Beato (20489933)

16S rRNA sequence analysis of intestinal microbiota in rats. by Ye Cheng (513097)

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Regional differences in cholinergic sweating in the lower limb by Tatsuro Amano (19855662)

“…Sweat rate, activated sweat gland density, and sweat gland output were measured via transdermal iontophoresis at the volar forearm, anterior and posterior thigh, anterior and posterior lower leg, and dorsal foot. Sweat rate at the forearm (all <i>P</i> ≥ 0.265) and foot (all <i>P</i> ≥ 0.077) did not differ significantly across age groups. …”

Importance of the predictor variables for estimating AGB using a random forest model. by Kasip Tiwari (22232186)

Flow diagram of participants selection. by Wei Huang (36889)

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Minimal data set. by Wei Huang (36889)

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Weighted comparison of baseline characteristics. by Wei Huang (36889)

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