Video2_Magnetospheric responses to solar wind Pc5 density fluctuations: Results from 2D hybrid Vlasov simulation.MP4 by Hongyang Zhou (2352637)

“…With the new time-varying boundary setup, we introduce a monochromatic Pc5 range periodic density variation in the solar wind. …”

Video4_Magnetospheric responses to solar wind Pc5 density fluctuations: Results from 2D hybrid Vlasov simulation.MP4 by Hongyang Zhou (2352637)

“…With the new time-varying boundary setup, we introduce a monochromatic Pc5 range periodic density variation in the solar wind. …”

Video1_Magnetospheric responses to solar wind Pc5 density fluctuations: Results from 2D hybrid Vlasov simulation.MP4 by Hongyang Zhou (2352637)

“…With the new time-varying boundary setup, we introduce a monochromatic Pc5 range periodic density variation in the solar wind. …”

Video3_Magnetospheric responses to solar wind Pc5 density fluctuations: Results from 2D hybrid Vlasov simulation.MP4 by Hongyang Zhou (2352637)

“…With the new time-varying boundary setup, we introduce a monochromatic Pc5 range periodic density variation in the solar wind. …”

Image_5_Wheat F-box Protein TaFBA1 Positively Regulates Plant Drought Tolerance but Negatively Regulates Stomatal Closure.tif by Jie An (543888)

“…Further, we found that TaFBA1 can interact with RCAR1 (an ABA receptor) and ABI5. …”

Video5_Evaluation of women’s aging influence on sperm passage inside the fallopian tube using 3D dynamic mechanical modeling.MP4 by Mayssam Nassir (18351408)

Video5_Evaluation of women’s aging influence on sperm passage inside the fallopian tube using 3D dynamic mechanical modeling.MP4 by Mayssam Nassir (18351408)

Image_5_p90RSK-MAGI1 Module Controls Endothelial Permeability by Post-translational Modifications of MAGI1 and Hippo Pathway.TIFF by Rei J. Abe (5723054)

Image_5_p90RSK-MAGI1 Module Controls Endothelial Permeability by Post-translational Modifications of MAGI1 and Hippo Pathway.TIFF by Rei J. Abe (5723054)

Schematic depiction of <i>GBA1</i> targeting strategy. by Nicole K. Polinski (10947787)

Image 5_Slavs in the closet: computational genomic analysis reveals cryptic slavic signatures in the Avar Khaganate and their contribution to medieval Croatian population formation... by Todor Chobanov (22288636)

Image_5_PtoMYB031, the R2R3 MYB transcription factor involved in secondary cell wall biosynthesis in poplar.tif by Feng Tang (136667)

Level of mucin secretion and water channel expression. by Ji Eun Kim (403026)

The effect of Gas6 recombinant protein on the expression of ZO-1 and occludin in Caco-2 cells without <i>K</i>. <i>pneumoniae</i> infection. by Hitoshi Tsugawa (296864)

Data_Sheet_1_Differences in Compositions of Gut Bacterial Populations and Bacteriophages in 5–11 Year-Olds Born Preterm Compared to Full Term.PDF by Thilini N. Jayasinghe (8979299)

“…We performed a multi'omics [i.e., 16S rRNA amplicon and shotgun metagenomic sequencing, SPME-GCMS (solid-phase microextraction followed by gas chromatography-mass spectrometry)] analysis to investigate the structure and function of the fecal microbiome (as a proxy of the gut microbiota) in our cross-sectional cohort. …”

Data cleaning and preparation algorithm. by Ayana Ablayeva (22103708)

“…</p><p>Results</p><p>Over the decade, age-standardized incidence rates decreased from 5.55 to 5.40 per 100,000, while mortality rates rose from 3.75 to 4.75 per 100,000. …”

Data_Sheet_5_Mendelian randomization in blood metabolites identifies triglycerides and fatty acids saturation level as associated traits linked to pancreatitis risk.PDF by Jiarui Mi (11170284)

“…To reveal the causal associations between plasma metabolites and pancreatitis risks, we performed two-sample Mendelian randomization (MR) and Bayesian model averaging (MR-BMA) analyses in European ancestry.…”

Data_Sheet_5_Sea Surface Temperature Imagery Elucidates Spatiotemporal Nutrient Patterns for Offshore Kelp Aquaculture Siting in the Southern California Bight.docx by Jordan N. Snyder (8375745)

Data_Sheet_1_Transient Receptor Potential Cation Channel Subfamily V Member 4 Mediates Pyroptosis in Chronic Obstructive Pulmonary Disease.docx by Yafei Rao (7310363)

Training set data expansion. by Qingjun Yu (1649473)

“…Based on the PyTorch deep learning framework, the initial U²-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. …”