Analysis of differential microbiome and classification prediction model between case and control groups. by Chuan Zhang (187157)

“…<p><b>(A)</b> Linear discriminant analysis [LDA; (log10)>2] and (B) effect size (LEfSe) analysis revealed significant differences (P < 0.01) in the microbiota of the case (orange, negative score) and control groups (blue, positive score) groups. …”

RMSF. by Curtis Chepsiror (21368103)

Raw data. by Mohamed Condé (22622306)

“…Increased use of opiates in the Emergency Department, elevated total leucocyte count, breath rate, and decreased red blood cell count were not significantly associated with ACS occurrence (p > 0.05). …”

Risk factors for ACS (multivariate analysis). by Mohamed Condé (22622306)

“…Increased use of opiates in the Emergency Department, elevated total leucocyte count, breath rate, and decreased red blood cell count were not significantly associated with ACS occurrence (p > 0.05). …”

Raw data. by Mohamed Condé (22622306)

“…Increased use of opiates in the Emergency Department, elevated total leucocyte count, breath rate, and decreased red blood cell count were not significantly associated with ACS occurrence (p > 0.05). …”

Characteristics of the 280 VOCs at inclusion. by Mohamed Condé (22622306)

“…Increased use of opiates in the Emergency Department, elevated total leucocyte count, breath rate, and decreased red blood cell count were not significantly associated with ACS occurrence (p > 0.05). …”

Timeline for study enrollment. by Saeun Park (20410160)

“…</p><p>Conclusions</p><p>Negative COVID-19 experiences were significantly associated with more severe depression and anxiety in Ugandan caregivers, regardless of their children’s malaria status. …”

Dataset used in the manuscript. by Saeun Park (20410160)

“…</p><p>Conclusions</p><p>Negative COVID-19 experiences were significantly associated with more severe depression and anxiety in Ugandan caregivers, regardless of their children’s malaria status. …”

The performance of eigenvectors of the covariance matrix in a model with more complex population structure. by Joshua G. Schraiber (8027060)

Classification of Anti-HlyE IgG Responses. by Jo Walker (22404069)

Fig 9 - BC. by Curtis Chepsiror (21368103)

Fig 10 - EC. by Curtis Chepsiror (21368103)

Delta <i>CC</i> heatmap. by Curtis Chepsiror (21368103)

AMP binding free energy calculations and per-residue decomposition of holo and PfIleRS-SANC systems. by Curtis Chepsiror (21368103)

Basic situation of different vegetation types. by Ye Xiao (3913402)

“…The largest total DOC stock was observed in EBF, while BF and EBF had significantly higher MBC and EOC stocks than SH, CFF, and MCBF (<i>P</i> < 0.05). …”

Evaluation of PCR amplification bias and PCR amplification efficiency. by Trang Thi Quynh Tran (20485595)

Scheme of g-λ model with larger values λ. by Zhanfeng Fan (20390992)

“…The findings suggest that when λ is respectively equal to 4.19, 8.57, 10, and 12.15, the peak particle velocity (PPV) of the transmitted waves is significantly close to the incident wave amplitude. Furthermore, when λ is fixed, the energy transmission coefficient increases with the incident wave amplitude but decreases with the incident wave frequency. …”

Validation and predictive accuracy of the cerebrovascular model, by Hadi Esfandi (21387211)

“…This observation suggests that the myogenic response is potentially linearly potentiated with increasing WT; however, the decreased constriction ability of muscles in the sloped phase, is proven to be advantageous for the vasculature, as it prevents reduced blood flow in deeper layers at high ABNP values. …”

The percentage of studies that resulted in insect death increased over time. by Craig D. Perl (3326880)

“…There was a significant decrease in the proportion of studies reporting just invasive handling (without death) over time (linear regression; t_20,18 = 4.00, p = 0.001, R²= 0.44). …”

Study sample. by Nipaporn Butsing (19470003)

“…One increased National Institute of Health Stroke Scale (NIHSS) score decreased adjusted BI scores by 3.6.</p><p>Conclusion</p><p>The time after discharge, gender, stroke subtype, and stroke severity are significant factors affecting functional outcomes after a stroke. …”