Effects of Hypoxia on Heart Rate Variability in Healthy Individuals: A Systematic Review by André Luiz Musmanno Branco Oliveira (6153938)

Effects of a structured education program on glycemic control in type 1 diabetes by Ana Paula F. Pacheco (4828593)

Transport of gaseous pollutants by convective boundary layer around a human body by Dusan Licina (805207)

Analysis of the functional performance of infants with congenital zika syndrome: a longitudinal study by Danielly Laís Pereira Lima (7031624)

Removal of bisphenol A by adsorption on organically modified clays from Burkina Faso by Issaka Garikoé (9604658)

Data from: Responses of the collared flycatcher to the changing climate: a comprehensive view by Laczi (14826043)

Change in macrophage polarization from M1 to M2 phase after SOD treatment. by Moon-Beom Kim (18554558)

Life Cycle Environmental Impacts of Sewage Sludge Pyrolysis and Their Dynamic Evolution by Jan Matuštík (22500291)

MOCR strength could predict the size of hearing deterioration caused by a violin practice. by Sho Otsuka (844383)

“…<p>Correlation of ipsilateral MOCR strength with the elevation of hearing threshold at 4 kHz (A) and with CEOAE decrease at 4 kHz in the left ear (B). …”

MARS model for classification of seropositive/chagasic subjects. by Nisha Jain Garg (102122)

“…Protein spots in panels A&B are identified as spot #-protein name, and fold change (increase ↑, red; decrease ↓, blue) are plotted on each bar. …”

Ball valve pipeline geometric modeling. by Weiqing Xu (1279959)

“…<div><p>Hydrogen is a clean energy source, and blending it with natural gas in existing pipeline networks is a key transition solution for transportation cost reduction. …”

Hydrogen volume fraction change in the pipeline. by Weiqing Xu (1279959)

“…<div><p>Hydrogen is a clean energy source, and blending it with natural gas in existing pipeline networks is a key transition solution for transportation cost reduction. …”

Mesh independence verification. by Weiqing Xu (1279959)

“…<div><p>Hydrogen is a clean energy source, and blending it with natural gas in existing pipeline networks is a key transition solution for transportation cost reduction. …”

Role of ALIX and TSG101 in the entry of PEDV or PEAV VLP into Vero cells. by Xiongnan Chen (13307178)

Valve parameters and simulation results. by Weiqing Xu (1279959)

“…<div><p>Hydrogen is a clean energy source, and blending it with natural gas in existing pipeline networks is a key transition solution for transportation cost reduction. …”

PV1 treatment ameliorates EAU. by Pedro Henrique Papotto (791904)

Undulation pipeline geometric modeling. by Weiqing Xu (1279959)

“…<div><p>Hydrogen is a clean energy source, and blending it with natural gas in existing pipeline networks is a key transition solution for transportation cost reduction. …”

Structure diagram of ensemble model. by Hongqi Wang (2208238)

“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. Additionally, a secondary validation using experimental data from other researchers confirms the model’s good agreement with previous results, demonstrating its robust generalization ability. …”

Fitting formula parameter table. by Hongqi Wang (2208238)

“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. Additionally, a secondary validation using experimental data from other researchers confirms the model’s good agreement with previous results, demonstrating its robust generalization ability. …”

Test plan. by Hongqi Wang (2208238)

“…Comparative analysis highlights the significant enhancement in prediction accuracy achieved by the proposed ensemble model over single machine learning models, with root mean square error (RMSE) values below 0.05 and mean absolute percentage error (MAPE) values remaining under 2.5% in both frozen and unfrozen states. Additionally, a secondary validation using experimental data from other researchers confirms the model’s good agreement with previous results, demonstrating its robust generalization ability. …”