TITAN decreaser diatom heatmap. by Brent J. Bellinger (21156150)

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)

ROC curve and AUC value of all models. by Tiago de Oliveira Barreto (20485207)

“…The results evidenced which models could adequately assist medical regulators during the decision-making process for bed regulation, enabling even more effective regulation and, consequently, greater availability of beds and a decrease in waiting time for patients.…”

Explanation of condition nodes and decision nodes in the SCM, ordered by decreasing centrality. by Stella D. Juventia (19961247)

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

<b>Supporting data for manuscript</b> "<b>Voluntary locomotion induces an early and remote hemodynamic decrease in the large cerebral veins</b>" by Kira Shaw (18796168)

“…The locomotion values (traces and metrics) are in arbitrary units with larger integers representing a greater displacement of the spherical treadmill, the hemodynamic (Hbt) values (traces and metrics) are a percentage change from the normalised baseline (prior to stimulus presentation), and the corresponding time series vector is presented in seconds. …”

The ROC curves and AUC values of the diagnostic model. by Zhe Wu (582498)

AUC of various models to predict imeglimin efficacy for liver function evaluated by ROC curves. by Naruyoshi Gyoutoku (22537831)

Subjects:

Changes in blood pressure, HbA1c, blood lipid and liver function-related indicator values compared with baseline values in all patients over time. by Jia Song (495396)

Area under the ROC Curve (AUC) analysis to predict AIS conversion at 6-months and 1-year following acute cervical tSCI. by Harshit Arora (22008280)

Area under the ROC curve (AUC) analysis to predict neurological severity at 6-months and 1-year following acute cervical tSCI. by Harshit Arora (22008280)

AUC statistics as calculated from simulated time series. Each statistical metric was calculated within sliding windows, throughout the pre-critical interval. We considered five-, fifteen-, and thirty-day sliding windows. Given that the temperature of the system increased to 12°C on day sixty, we also considered three pre-critical intervals: Days 1 to 60, Days 20 to 60, and Days 30 to 60. To evaluate trends in these metrics, we calculated Kendall’s rank correlation coefficient during the pre-critical interval, and compared control (constant temperature, non-epidemic) and warming (warming treatment, epidemic emergence) coefficients across simulations and experimental populations by calculating the area under the curve (AUC) statistic. Values less than 0.5 suggest that a decrease in the statistical metric indicates emergence, while values greater than 0.5 suggest that an increase in the statistical metric indicates emergence, with more extreme values indicating stronger tre by Madeline Jarvis-Cross (22394247)

“…Values less than 0.5 suggest that a decrease in the statistical metric indicates emergence, while values greater than 0.5 suggest that an increase in the statistical metric indicates emergence, with more extreme values indicating stronger tre</p>…”

Input parameter ranking for discrete measurements: Each column displays parameters (P) and their influence values (E) calculated using Eq 11, shown in decreasing order of influence.... by Harry Saxton (19165441)

“…<p>Input parameter ranking for discrete measurements: Each column displays parameters (P) and their influence values (E) calculated using <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0326112#pone.0326112.e114" target="_blank">Eq 11</a>, shown in decreasing order of influence. …”

Calculation of peak force and impulse values from force plate data. by Leena Inkilä (20614460)

Changes in blood pressure, HbA1c, blood lipids and liver function-related indicator values from 3 months to 6 months of treatment in all patients. by Jia Song (495396)

Column charts of WiAUC in therapy and control group at baseline and follow-up. by Felix L. Herr (21544362)

Box plots showing baseline prevalence and mean egg count at pre-MDA1 in districts that were responders compared to those that were persistent hotspots of decreasing praziquantel ef... by Takafira Mduluza (39754)

Demographic and clinical characteristics of study sample (<i>N</i> = 1810). by Olivia Ojala (14057026)

<i>Ctsz</i>^{<i>−/−</i>} mice have higher lung burden and earlier spleen dissemination during acute infection followed by greater chronic inflammation and mortality risk.... by Rachel K. Meade (22216529)

Study 1_CFA1. by Chen-Yueh Chen (9740047)

“…Findings from Analysis of Covariance (ANCOVA) in Study II indicate that in Experiment I, positive electronic word of mouth does not help improve value co-creation among spectators while negative electronic word of mouth does decrease value co-creation among spectators. …”