Relationship between monthly NDVI and climatic variables values (Tmax, maximum air temperature; P, precipitation; VPD, vapor pressure deficit), in areas with decreasing trends (<i>p</i> < 0.05). by Oswaldo Maillard (20660661)

Decrease in loss during the training process. by Muhammad Idrees (92773)

Proportion of the increase (green) or decrease (red) in forest cover in areas with different fire recurrences in Africa, according to the Mann-Kendall test and statistically signif... by Oswaldo Maillard (20660661)

PRCC values (with <i>p</i>-values in parentheses) for the median final population size and difference in mean MSI at the final time, without weevil predation and with weevil predat... by Alexandra M. Campbell (3284094)

Seasonal spatial-temporal trend of NDVI in burned areas across Africa (2001–2020). Percentages (%) of increases or decreases (%) based on the Mann-Kendall test and statistically significant (<i>p</i> < 0.05) and non-significant (p > 0.05) values. by Oswaldo Maillard (20660661)

TITAN thresholds and percentile estimates for benthic macroinvertebrate and diatom communities deemed to be sensitive decreasers or tolerant increasers. The thresholds represent the largest fsum <i>z</i> value in the main data analysis run (i.e., the median), whereas the 5^th and 95^th percentile change points are determined from 500 bootstrap replicate runs.... by Brent J. Bellinger (21156150)

“…<p>TITAN thresholds and percentile estimates for benthic macroinvertebrate and diatom communities deemed to be sensitive decreasers or tolerant increasers. The thresholds represent the largest fsum <i>z</i> value in the main data analysis run (i.e., the median), whereas the 5^th and 95^th percentile change points are determined from 500 bootstrap replicate runs. …”

The correlation coefficient (<i>r</i>) between NDVI values and the seasonal series (2001–2020) of maximum air temperature (Tmax), precipitation (P), and vapor pressure deficit (VPD... by Oswaldo Maillard (20660661)

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)

MWM training data. by Robert Botelho (20308297)

Relationship between monthly NDVI and climatic variables values (Tmax, maximum air temperature; P, precipitation; VPD, vapor pressure deficit), in areas with increasing trends (<i>... by Oswaldo Maillard (20660661)

Paeameter ranges and optimal values. by Zhen Zhao (159931)

“…Subsequently, the feature factors corresponding to the model with the highest accuracy were selected as the optimal feature subsets and used in the model construction as input data. Additionally, considering the imbalanced in population spatial distribution, we used the K-means ++ clustering algorithm to cluster the optimal feature subset, and we used the bootstrap sampling method to extract the same amount of data from each cluster and fuse it with the training subset to build an improved random forest model. …”

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

Largest changes in influenza vaccine rates, Pre- vs. Post-COVID-19. by Tyler B. Nofzinger (21560244)

Subjects:

Forest plot of ROR values used to assess gender differences in penicillamine-related AEs. by Wenlong Qian (22608053)

Subjects:

Yearly crude rates normalized by their 1999 value. by Tony Wong (779773)

“…<p>Values below 1 indicate crude rate decreases relative to their 1999 value, those above 1 indicate increases. …”

Boxplot visualization of RAP values for statistical pairwise comparisons of ANOVA factors sex, task speed and SPL phase. by Jonas Kirsch (20642910)

Subjects:

5-year persistence of innate immune responses to VZV-gE after RZV administration. Data were derived from 14 RZV recipients who received 2 doses of vaccine at Days 0 and 60. Demogra... by Michael J. Johnson (5818168)

Moran’s I value, Z value and P value of CCD-GFEE. by Dalai Ma (17847101)

“…Within them, the CCD of Chengdu is the highest, Chongqing has achieved the largest stage leap. (4) The global Moran’s I consistently remained positive and exhibited a tendency of initially rising and subsequently falling, indicating that the spatial aggregation effect of CCD-GFEE first increased and then decreased. (5) The CCD-GFEE driving factors are examined using the spatial econometric model, and it has been observed that the impact of population size and government intervention on CCD-GFEE is negative, while the impact of industrial structure, technological progress and economic level on the coupling and coordination of CCD-GFEE is positive. …”

Table of values for <i>p.</i> by Long Di (9977453)

S1 Data - by James Anaba Akolgo (14129379)