Histograms of model vertex von Mises stress values exceeding 5 MPa. by Nathan L. Wright (18389458)

Effect of parameter <i>a</i> on the model equations by increasing and decreasing value of <i>a</i> to 25%. by Shakoor Ahmad (168711)

“…<p><b>(a)</b> By increasing the value ‘<i>a</i>’ from 0.107 to 0.134. <b>(b)</b> By decreasing the value ‘<i>a</i>’ from 0.107 to 0.08.…”

TITAN decreaser macroinvertebrate heatmap Heatmap of sensitive (i.e., <i>z-</i>) macroinvertebrate taxa (y-axis) to at least one of the five stressors, in decreasing order of numbe... by Brent J. Bellinger (21156150)

Method for the Large-Scale Synthesis of Multifunctional 1,4-Dihydro-pyrrolo[3,2‑<i>b</i>]pyrroles by Mariusz Tasior (1457731)

“…A thorough investigation has enabled the optimization of the synthesis of 1,4-dihydro-pyrrolo­[3,2-<i>b</i>]­pyrroles. Although salts of such metals as vanadium, niobium, cerium, and manganese were found to facilitate the formation of 1,4-dihydro-pyrrolo­[3,2-<i>b</i>]­pyrroles from amines, aldehydes, and diacetyl, we confirmed that iron salts are the most efficient catalysts. …”

Method for the Large-Scale Synthesis of Multifunctional 1,4-Dihydro-pyrrolo[3,2‑<i>b</i>]pyrroles by Mariusz Tasior (1457731)

“…A thorough investigation has enabled the optimization of the synthesis of 1,4-dihydro-pyrrolo­[3,2-<i>b</i>]­pyrroles. Although salts of such metals as vanadium, niobium, cerium, and manganese were found to facilitate the formation of 1,4-dihydro-pyrrolo­[3,2-<i>b</i>]­pyrroles from amines, aldehydes, and diacetyl, we confirmed that iron salts are the most efficient catalysts. …”

Benchmarking DFT Accuracy in Predicting O 1s Binding Energies on Metals by Elizabeth E. Happel (22391811)

Subjects:

Benchmarking DFT Accuracy in Predicting O 1s Binding Energies on Metals by Elizabeth E. Happel (22391811)

Subjects:

Simulation results (1^st case). by Tuan Anh Nguyen (121944)

Subjects:

The computed weighted sum of type I (dark gray) and type II (light gray) errors ( by Farrokh Habibzadeh (12256529)

Antibody and antigen responses to Lufotrelvir vs placebo day 1–90. by Elizabeth S. Munroe (21568166)

Model diagnostics for all death events. by Xin Zhang (35492)

“…Moreover, composite pollutants exhibited a higher risk effect, reaching its peak after one week; however, there was a decrease in single-day cumulative effects as more pollutant types were included. …”

Simulation results (1^st case). by Tuan Anh Nguyen (121944)

Antibody and antigen responses to Ensovibep vs placebo day 1–90. by Elizabeth S. Munroe (21568166)

The number of expected vaccinations decreases with the expected vaccination time, whereas the peak of infections increases. by Simon K. Schnyder (16632244)

Costs and Benefits of Popular <i>P</i>‑Value Correction Methods in Three Models of Quantitative Omic Experiments by Steven R. Shuken (14500192)

“…We show how increasing sample size, decreasing variability, or increasing effect size can enable the detection of all true changes while still correcting <i>p</i>-values, and we present basic guidelines for omic experimental design. …”

Patient journey–Admission to discharge (all cases). by Olive Kabajaasi (4575343)

Antibody and antigen responses to nMAb vs placebo day 1–90 for Bamlanivimab. by Elizabeth S. Munroe (21568166)

Antibody and antigen responses to nMAb vs placebo day 1–90 for Sotrovimab. by Elizabeth S. Munroe (21568166)

Species occurrence along the NO₃¯ gradient (sorted by decreasing 25th percentile values). by Willem Kaijser (12872371)

Antibody and antigen responses to nMAb vs placebo day 1–90 for Amubarvimab/ Romlusevimab. by Elizabeth S. Munroe (21568166)