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

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

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)

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

Youthful systemic milieu in young recipients decreased apoptosis and oxidative stress damage in allografts, and promoted proliferation. by Chengjun Yu (12136227)

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)

Deep learning-based locomotive syndrome prediction method. by Junichi Kushioka (12236447)

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Mean values of physical parameters of rock samples. by Dengke Yang (842532)

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S2 File - Factors influencing effective decrease of controlled attenuation parameters in metabolic-associated steatotic liver disease: A multilevel linear regression analysis at Va... by Sonsawan Sangprasert (22772538)

Block diagram for Average Value-based irrigation system. by Gourab Saha (8987405)

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Flow chart of Average Value-based control system. by Gourab Saha (8987405)

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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. Results are presented for progressively expanding discrete measurement sets (from Set 1 to Set 3F). Only parameters with influence values greater than 0.01 are shown. by Harry Saxton (19165441)

“…Only parameters with influence values greater than 0.01 are shown.</p>…”

Oviduct Glycoprotein 1 (OVGP1) Diagnoses Polycystic Ovary Syndrome (PCOS) Based on Machine Learning Algorithms by Fengjuan Wang (768949)

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Calculation of peak force and impulse values from trial with overlap. by Leena Inkilä (20614460)

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

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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)

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P values of Kruskal–Wallis test at 95% significance level. by Fahd Saeed Alakbari (10701871)

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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. Sensitive taxa change points derived from decreaser sum <i>z</i>- relative to increasing impervious cover (I.C.; %), specific conductivity (SpCond; μS cm^-1), total nitrogen (TN; μg L^-1), and total phosphorus (TP; μg L^-1). Tolerant taxa change point derived from increaser sum <i>z</i>+ value. Flow permanence responses are opposite those of other stressors such that increasers are sensitive to decreasing FPI.... by Brent J. Bellinger (21156150)

“…Tolerant taxa change point derived from increaser sum <i>z</i>+ value. Flow permanence responses are opposite those of other stressors such that increasers are sensitive to decreasing FPI. …”

Sensor value scenario for average value algorithm. by Gourab Saha (8987405)

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Monthly runoff observation values and variation in 4 hydrological stations in the YLRB. by Jintao Li (448681)

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