Table 1_The evolution of three-dimensional knee kinematics after ACL reconstruction within one year.docx by Lingchuang Kong (21163574)

“…</p>Results<p>After ACLR, the IKDC and KOOS scores of patients significantly improved between 3 and 12 months postoperatively, showing good subjective functional recovery. …”

Table1_Organic fertilizer increases pumpkin production by improving soil fertility.docx by Fangfang Ren (1835083)

“…Compared to CK, the average soil bulk density was significantly decreased by 8.27–18.51% (P< 0.05); the soil organic carbon, available phosphorus, available potassium, and nitrate nitrogen under H treatment were increased by an average of 32.37%, 21.85%, 18.70%, and 36.97%, respectively. …”

Data Sheet 1_Valve-in-valve transcatheter aortic valve replacement (TAVR) leads to lower device success compared to TAVR in native stenosis.pdf by Michael Paukovitsch (16428786)

“…The overall rate of device success amounted to 66% in ViV-TAVR, compared to 96.1% in TAVR (p < 0.01) and ViV-TAVR was independently associated with reduced device success (OR: 0.07, 95%CI: 0.045–0.12, p < 0.01) in multivariate regression. While ViV-TAVR decreased peak and mean gradients significantly, in 31% of patients elevated mean gradients (≥20 mmHg) were observed at discharge. …”

Figure 6 from Membrane-bound Heat Shock Protein mHsp70 Is Required for Migration and Invasion of Brain Tumors by Maxim Shevtsov (15023874)

“…<p>Inhibition of mHsp70 results in decreased motility of patient-derived brain tumor cells. …”

Automated matching and visualisation of magnetic flux leakage data in shale gas pipeline based on ICP and DBSCAN algorithm by Leyao Gu (17897654)

“…Despite many pipelines have completed two or more rounds of internal inspection and have accumulated substantial data, effectively analyzing and utilizing this MFL data remains a significant challenge. To that end, this study proposes a novel combined model that integrates Iterative Closest Point (ICP) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) fusion to match multiple MFL data. …”

Table 3_Effects of silver nanoparticles on the physiology, stress, and mineral uptake of banana cultivars in vitro and greenhouse.xlsx by Natalia Mendoza (22038296)

“…Rooting experiments revealed similar trends with high AgNP concentrations resulting in a decreasing root number and size. Greenhouse experiments on Gros Michel bananas, evaluating AgNP uptake through foliar and drench applications at 0, 25, 50, and 100 mg L^-1, monitored over a month, showed no statistically significant differences in growth parameters between treated plants and controls. …”

Table 5_Effects of silver nanoparticles on the physiology, stress, and mineral uptake of banana cultivars in vitro and greenhouse.xlsx by Natalia Mendoza (22038296)

“…Rooting experiments revealed similar trends with high AgNP concentrations resulting in a decreasing root number and size. Greenhouse experiments on Gros Michel bananas, evaluating AgNP uptake through foliar and drench applications at 0, 25, 50, and 100 mg L^-1, monitored over a month, showed no statistically significant differences in growth parameters between treated plants and controls. …”

Table 2_Effects of silver nanoparticles on the physiology, stress, and mineral uptake of banana cultivars in vitro and greenhouse.xlsx by Natalia Mendoza (22038296)

“…Rooting experiments revealed similar trends with high AgNP concentrations resulting in a decreasing root number and size. Greenhouse experiments on Gros Michel bananas, evaluating AgNP uptake through foliar and drench applications at 0, 25, 50, and 100 mg L^-1, monitored over a month, showed no statistically significant differences in growth parameters between treated plants and controls. …”

Table 6_Effects of silver nanoparticles on the physiology, stress, and mineral uptake of banana cultivars in vitro and greenhouse.xlsx by Natalia Mendoza (22038296)

“…Rooting experiments revealed similar trends with high AgNP concentrations resulting in a decreasing root number and size. Greenhouse experiments on Gros Michel bananas, evaluating AgNP uptake through foliar and drench applications at 0, 25, 50, and 100 mg L^-1, monitored over a month, showed no statistically significant differences in growth parameters between treated plants and controls. …”

Table 1_Effects of silver nanoparticles on the physiology, stress, and mineral uptake of banana cultivars in vitro and greenhouse.xlsx by Natalia Mendoza (22038296)

“…Rooting experiments revealed similar trends with high AgNP concentrations resulting in a decreasing root number and size. Greenhouse experiments on Gros Michel bananas, evaluating AgNP uptake through foliar and drench applications at 0, 25, 50, and 100 mg L^-1, monitored over a month, showed no statistically significant differences in growth parameters between treated plants and controls. …”

Data Sheet 1_Effects of silver nanoparticles on the physiology, stress, and mineral uptake of banana cultivars in vitro and greenhouse.pdf by Natalia Mendoza (22038296)

“…Rooting experiments revealed similar trends with high AgNP concentrations resulting in a decreasing root number and size. Greenhouse experiments on Gros Michel bananas, evaluating AgNP uptake through foliar and drench applications at 0, 25, 50, and 100 mg L^-1, monitored over a month, showed no statistically significant differences in growth parameters between treated plants and controls. …”

Table 4_Effects of silver nanoparticles on the physiology, stress, and mineral uptake of banana cultivars in vitro and greenhouse.xlsx by Natalia Mendoza (22038296)

“…Rooting experiments revealed similar trends with high AgNP concentrations resulting in a decreasing root number and size. Greenhouse experiments on Gros Michel bananas, evaluating AgNP uptake through foliar and drench applications at 0, 25, 50, and 100 mg L^-1, monitored over a month, showed no statistically significant differences in growth parameters between treated plants and controls. …”

Image 4_Effects of silver nanoparticles on the physiology, stress, and mineral uptake of banana cultivars in vitro and greenhouse.tif by Natalia Mendoza (22038296)

“…Rooting experiments revealed similar trends with high AgNP concentrations resulting in a decreasing root number and size. Greenhouse experiments on Gros Michel bananas, evaluating AgNP uptake through foliar and drench applications at 0, 25, 50, and 100 mg L^-1, monitored over a month, showed no statistically significant differences in growth parameters between treated plants and controls. …”

Image 1_Effects of silver nanoparticles on the physiology, stress, and mineral uptake of banana cultivars in vitro and greenhouse.tiff by Natalia Mendoza (22038296)

“…Rooting experiments revealed similar trends with high AgNP concentrations resulting in a decreasing root number and size. Greenhouse experiments on Gros Michel bananas, evaluating AgNP uptake through foliar and drench applications at 0, 25, 50, and 100 mg L^-1, monitored over a month, showed no statistically significant differences in growth parameters between treated plants and controls. …”

Image 5_Effects of silver nanoparticles on the physiology, stress, and mineral uptake of banana cultivars in vitro and greenhouse.tif by Natalia Mendoza (22038296)

“…Rooting experiments revealed similar trends with high AgNP concentrations resulting in a decreasing root number and size. Greenhouse experiments on Gros Michel bananas, evaluating AgNP uptake through foliar and drench applications at 0, 25, 50, and 100 mg L^-1, monitored over a month, showed no statistically significant differences in growth parameters between treated plants and controls. …”

Image 3_Effects of silver nanoparticles on the physiology, stress, and mineral uptake of banana cultivars in vitro and greenhouse.tif by Natalia Mendoza (22038296)

“…Rooting experiments revealed similar trends with high AgNP concentrations resulting in a decreasing root number and size. Greenhouse experiments on Gros Michel bananas, evaluating AgNP uptake through foliar and drench applications at 0, 25, 50, and 100 mg L^-1, monitored over a month, showed no statistically significant differences in growth parameters between treated plants and controls. …”

Table 7_Effects of silver nanoparticles on the physiology, stress, and mineral uptake of banana cultivars in vitro and greenhouse.xlsx by Natalia Mendoza (22038296)

“…Rooting experiments revealed similar trends with high AgNP concentrations resulting in a decreasing root number and size. Greenhouse experiments on Gros Michel bananas, evaluating AgNP uptake through foliar and drench applications at 0, 25, 50, and 100 mg L^-1, monitored over a month, showed no statistically significant differences in growth parameters between treated plants and controls. …”

Table 1_Comparative transcriptomic and molecular biology analyses to explore potential immune responses to Vibrio parahaemolyticus challenge in Eriocheir sinensis.docx by Duanduan Chen (6860495)

“…<p>Vibrio parahaemolyticus is a significant pathogen affecting shrimp and crab farming, particularly strains carrying genes associated with acute hepatopancreatic necrosis syndrome. …”

Friedman statistic and p-value across iterations. by Marwah Salman (22593380)

“…<div><p>The direct current (DC) in optical orthogonal frequency division multiplexing (DCO-OFDM) scheme is commonly adopted in light fidelity (Li-Fi) technology as it offers a spectrally efficient solution. A prior study adopted a machine learning (ML)-based solution to predict the optimum DC bias using key parameters, including the statistical properties of the OFDM transmitted signal and a polynomial regression model. …”

The effect of DC bias on clipping noise variance. by Marwah Salman (22593380)

“…<div><p>The direct current (DC) in optical orthogonal frequency division multiplexing (DCO-OFDM) scheme is commonly adopted in light fidelity (Li-Fi) technology as it offers a spectrally efficient solution. A prior study adopted a machine learning (ML)-based solution to predict the optimum DC bias using key parameters, including the statistical properties of the OFDM transmitted signal and a polynomial regression model. …”