Training-induced changes in bipedal stance. by Cristina Dolciotti (16317330)

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

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Relation of the changes in Y Sway Amplitude and LFS induced by postural training with those in 95% Area. 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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(A) Auxiliary marking points to ensure complete and accurate seating of the prosthesis. by Long Li (6555)

Change in influenza vaccination uptake from May 2020 to October 2024 (weighted). by Hannah Melchinger (20234665)

Water level changes in the foresight scenarios. by Zihao Duan (17403792)

“…Compared to 1930, the water level decreased by 2.6 m by 2023, with 1935 marking the onset of a significant downward trend. …”

Water level changes in the Caspian Sea. by Zihao Duan (17403792)

“…Compared to 1930, the water level decreased by 2.6 m by 2023, with 1935 marking the onset of a significant downward trend. …”

Methods used to extract shoreline changes. by Zihao Duan (17403792)

“…Compared to 1930, the water level decreased by 2.6 m by 2023, with 1935 marking the onset of a significant downward trend. …”

Between-group differences in 95% Area, Y Sway Amplitude and LFS during postural training. by Cristina Dolciotti (16317330)

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Time course of Path Length, LFS and Velocity during postural training. 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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Cinacalcet administered early in the inactive phase markedly decrease parathyroid Ki-67 index. by Søren Egstrand (10906087)

Coastal area changes during the period 1985–2023. by Zihao Duan (17403792)

“…Compared to 1930, the water level decreased by 2.6 m by 2023, with 1935 marking the onset of a significant downward trend. …”

Modelled policy outcomes, with posterior values for individual nodes ranked from 1-5 across the parties - Green, Reform UK, Liberal Democrat, Conservative, and Labour, where 1 is the lowest rank and 5 is the highest. The parties are ranked for each policy node in the network (e.g., income tax), based on the direction of change (“performance indicator”) stated in the first column (e.g., lowest, highest, most, improvement). For example, a value of 5 for Green tax means that green tax is lowest under Reform UK’s policies, while a value of 1 means that green tax is highest under the Green Party’s policies. Larger text in bold and italic font indicates that the directional change (i.e., increase or decrease) of a node under a party’s policies is consistent with the direction indicated, whereas black text indicates an opposite directional change (e.g., income tax is predicted to decrease under Reform UK in alignment with the performance indicator, and increase under Green and Labour). by Richard Stafford (174326)

“…Larger text in bold and italic font indicates that the directional change (i.e., increase or decrease) of a node under a party’s policies is consistent with the direction indicated, whereas black text indicates an opposite directional change (e.g., income tax is predicted to decrease under Reform UK in alignment with the performance indicator, and increase under Green and Labour).…”

nsP4-C483Y or Q192L mutations decrease sensitivity to 4′-FlU. by Peiqi Yin (6533747)

Changes in AL (A) and SE (B) according to the treatment time estimation curve in patients given 0.125% atropine. by Zi-Rong Chen (9227618)

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Table 2 - Early identification of the efficacy of 0.125% atropine treatment for children with Myopia: A prospective pilot study by Zi-Rong Chen (9227618)

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Each square gives extinction probability p (AB) or median population change d (CD) for 100 simulations at . by Alexandra M. Campbell (3284094)