The average speed of the model (step length/step duration), <i>v</i>, vs. the phase of a perturbation pulse, <i>φ</i> for a pulse of constant amplitude and duration. by Jooeun Ahn (299192)

Supplementary Material for: Venous Chamber Design: A Comparative Analysis of Retention Characteristics by figshare admin karger (2628495)

“…Methods Flow retention characteristics at 20, 30, 40, 50, and 60 s in a top-feed chamber (where blood flow enters vertically from the top and passes through a mesh within the air trap chamber with a chamber 12 mL in volume) and a side-feed chamber (where blood flow enters from the side and bottom, without a mesh filter, with a flow deviator and 6mL chamber volume) were evaluated using a 30% glycerin and iodine povidone-solution. …”

The geometry of the lactation curve based on Wood's equation: a two-step prediction by Jhone Gleison de Oliveira (10446485)

Activin A affects NPC morphology and increases the number of neurons during proliferation. by Griselda Rodríguez-Martínez (140821)

“…Treatment with either Activin A or TGF-β1 caused a 50% reduction in cell area, relative to control cells. …”

Orientation to a goal direction supported by the MB long-term visual memory. by Roman Goulard (4790184)

“…<p><b>A.</b> Mushroom bodies model diagram. The visual Projection Neurons (vPN) correspond to the visual units (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1009383#pcbi.1009383.g002" target="_blank">Fig 2</a>) extracting edge from the panoramic view. …”

Balanced Dataset Distribution. by Mudhafar Jalil Jassim Ghrabat (22177655)

“…We surpassing other models as such, CNN, VGG19, ResNet50.</p></div>…”

Mapping Blood Lead Levels in China during 1980–2040 with Machine Learning by Yanni Zhang (347305)

“…A machine learning model, using the random forest algorithm and 2973 generated samples, was created to predict county-specific blood lead levels in China from 1980 to 2040. Geometric mean blood lead levels in children (i.e., age 14 and under) decreased significantly from 104.4 μg/L in 1993 to an anticipated 40.3 μg/L by 2040. …”

Mapping Blood Lead Levels in China during 1980–2040 with Machine Learning by Yanni Zhang (347305)

“…A machine learning model, using the random forest algorithm and 2973 generated samples, was created to predict county-specific blood lead levels in China from 1980 to 2040. Geometric mean blood lead levels in children (i.e., age 14 and under) decreased significantly from 104.4 μg/L in 1993 to an anticipated 40.3 μg/L by 2040. …”

Effect of STPKLRR on AjTmod phosphorylation and coelomocytes phagocytosis. by Fa Dai (15810913)

Modeling of soil organic carbon loss by water erosion on a tropical watershed by Guilherme Henrique Expedito Lense (4704619)

“…The applied methodology represents a cost-effective and relatively fast method to estimate the soil organic carbon loss by water erosion and allows the determination of the areas that most need intervention, aiming to decrease the impact of agriculture on greenhouse gas emissions. …”

TFEB nuclear translocation after serum starvation. by Collin M. MacLeod (17512385)

Inhibition of HIV-1 replication by KIR2DL5⁺ and KIR2DL5^- NK cells. by Pia Fittje (12936621)

Prediction of <i>Tinospora crispa</i> know phytoconstituents and its druggability [16]. by Ummu Mastna Zuhri (12915225)

Growth inhibition. by Gábor Patyi (11846776)

Data_Sheet_1_Creation of a Low-Alcohol-Production Yeast by a Mutated SPT15 Transcription Regulator Triggers Transcriptional and Metabolic Changes During Wine Fermentation.PDF by Qing Du (1610224)

Adaptation affects the gain and slope of neural power spectral densities. by Brian Nils Lundstrom (14659973)

“…(c) Adaptation alters the slope of PSDs, decreases the overall gain, and affects lower frequencies (e.g. 0–10 Hz) more than higher frequencies (e.g. 30–50 Hz). …”

Prediction bias for the different genotyping methods and sequencing coverages across the four traits. by Harrison J. Lamb (11722247)

Fig 2 - by Ying Zhang (40767)

S3 Fig - by Mahvash Farajzadeh-Dehkordi (17468232)

Table_1_A Stem Cell Surge During Thyroid Regeneration.docx by Risheng Ma (63192)

“…In addition, there was a ~50% decrease in transcription of thyroid specific genes (thyroglobulin, TSH receptor, and sodium-iodide symporter). …”