Schematic for measuring <i>D</i> and <i>D</i>′ values. by Hong Zhang (25820)

“…A recommended median area factor of 1.43 is therefore proposed. The measured <i>I</i>_s decreases following a power-law trend as <i>β</i> and <i>D</i> increase, with weathering reducing the sensitivity of <i>I</i>_s to <i>β</i> but not significantly altering its sensitivity to <i>D</i>. …”

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)

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

S1 Raw data - by Dominic Michael Rasp (19959412)

“…Ten active soccer players carried out the Loughborough Intermittent Shuttle Test, during which hamstring strength of both legs was assessed on seven occasions via the optimized 90:20 Isometric Posterior Chain Test. …”

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. …”

A visual comparison of the associated resistance data from Table 1 with the values of <i>k</i>_cat, <i>K</i>_M, catalytic efficiency (<i>k</i>_cat/<i>... by J. Roadnight Sheehan (20141887)

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)

Distribution of <i>L</i>(<i>p</i>) with an absolute error when a single observation is randomly sampled at each time point, with the smallest observation (blue) and the largest obs... by Hyeontae Jo (20469463)

“…As the <i>L</i>(<i>p</i>) distribution associated with the larger observation tends to have higher overall values, the likelihood of it being ultimately selected decreases.…”

Forest plot and volcano plot of ROR values (95% CI) for the first 30 high signal intensity AEs of penicillamine versus trientine. by Wenlong Qian (22608053)

bta-miR-484 Inhibits Bovine Intramuscular Adipogenesis by Regulating Mitotic Clonal Expansion via the MAP3K9/JNK/CCND1 Axis by Xinhao Ma (11795429)

Subjects:

bta-miR-484 Inhibits Bovine Intramuscular Adipogenesis by Regulating Mitotic Clonal Expansion via the MAP3K9/JNK/CCND1 Axis by Xinhao Ma (11795429)

Subjects:

bta-miR-484 Inhibits Bovine Intramuscular Adipogenesis by Regulating Mitotic Clonal Expansion via the MAP3K9/JNK/CCND1 Axis by Xinhao Ma (11795429)

Subjects:

bta-miR-484 Inhibits Bovine Intramuscular Adipogenesis by Regulating Mitotic Clonal Expansion via the MAP3K9/JNK/CCND1 Axis by Xinhao Ma (11795429)

Subjects:

bta-miR-484 Inhibits Bovine Intramuscular Adipogenesis by Regulating Mitotic Clonal Expansion via the MAP3K9/JNK/CCND1 Axis by Xinhao Ma (11795429)

Subjects:

<i>r</i>² values for <i>α</i> relationships. by James Cushway (19942288)

The multiple criteria qualitative value-based pricing framework “MARIE” for new clinical status by Akina Takami (16407200)

Tissue, days post-infection (dpi) and the top 10 most significant genes with increased and decreased expression with valid gene symbols for the response contrasts. by Gillian P. McHugo (8965919)

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)

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

“…The random forest was constructed using feature subsets that were selected via different feature selection methods, namely MIC-RF, RFECV-RF and MDA-RF. …”