Table_1_A point mutation in MC06g1112 encoding FLOWERING LOCUS T decreases the first flower node in bitter gourd (Momordica charantia L.).xlsx by Jian Zhong (329110)

“…A point mutation (C277T) in MC06g1112, which results in a P93S amino acid mutation between parental lines, may be responsible for decreasing FFN in bitter gourd. …”

Mean and standard deviation of the signals in the left and right liver lobe for b = 50 and b = 800 s/mm², normalized to the monopolar signal at b = 50 s/mm² i... by Tobit Führes (12647099)

Eigenvalues of equilibrium points. by Yaohong Yang (12213256)

(A) Auxiliary marking points to ensure complete and accurate seating of the prosthesis. by Long Li (6555)

Mean and standard deviation of the three dimensions and of the global score of STS before COVID-19. by Martina Gnerre (12329356)

Mean and standard deviation of the three dimensions and of the global score of STS during COVID-19. by Martina Gnerre (12329356)

Mean and standard deviation of the three dimensions and of the global score of STS after COVID-19. by Martina Gnerre (12329356)

Decreasing fluconazole susceptibility of clinical South African <i>Cryptococcus neoformans</i> isolates over a decade by Serisha D. Naicker (8648370)

BAL cells count at different time-points. by Zahra Khalajzeyqami (6865475)

DART-ID decreases missing datapoints across runs. by Albert Tian Chen (6900215)

Image 5_Exploration of the diagnostic and prognostic roles of decreased autoantibodies in lung cancer.tif by Ying Ye (72583)

“…Moreover, 5 of the decreased autoantibodies can also be applied for supervising bone metastasis in lung adenocarcinoma. …”

Differences in b-vitamins in response to a control diet or a diet containing MCOA: a. by Natalie E. Diether (16705804)

Table5_Effects of exercise modalities on decreased blood pressure in patients with hypertension.docx by Thiago Rozales Ramis (5311217)

Arrangement of noise monitoring points. by Xue Liu (420033)

Scaling exponent α for the whole measuring period 1980–2000 as a function of publication year; numbers are the averages of successive five-years blocks, each five-years block is lo... by Anthony F. J. van Raan (7517696)

S1 File - by Yonghui Zhang (279832)

“…The CSPM, driven by the optimized CSPs, is then evaluated against two independent phenological datasets from Exp. 2 and Exp. 4 described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0302098#pone.0302098.t002" target="_blank">Table 2</a>. Root means square error (RMSE) (mean absolute error (MAE), coefficient of determination (R²), and Nash Sutcliffe model efficiency (NSE)) are 15.50 (14.63, 0.96, 0.42), 4.76 (3.92, 0.97, 0.95), 4.69 (3.72, 0.98, 0.95), 3.91 (3.40, 0.99, 0.96) and 12.54 (11.67, 0.95, 0.60), 5.07 (4.61, 0.98, 0.93), 4.97 (4.28, 0.97, 0.94), 4.58 (4.02, 0.98, 0.95) for using one, two, three, and four observed phenological stages in the CSPs estimation. …”

Detailed information on field experiments. by Yonghui Zhang (279832)

“…The CSPM, driven by the optimized CSPs, is then evaluated against two independent phenological datasets from Exp. 2 and Exp. 4 described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0302098#pone.0302098.t002" target="_blank">Table 2</a>. Root means square error (RMSE) (mean absolute error (MAE), coefficient of determination (R²), and Nash Sutcliffe model efficiency (NSE)) are 15.50 (14.63, 0.96, 0.42), 4.76 (3.92, 0.97, 0.95), 4.69 (3.72, 0.98, 0.95), 3.91 (3.40, 0.99, 0.96) and 12.54 (11.67, 0.95, 0.60), 5.07 (4.61, 0.98, 0.93), 4.97 (4.28, 0.97, 0.94), 4.58 (4.02, 0.98, 0.95) for using one, two, three, and four observed phenological stages in the CSPs estimation. …”

List of symbols used in this study. by Yonghui Zhang (279832)

“…The CSPM, driven by the optimized CSPs, is then evaluated against two independent phenological datasets from Exp. 2 and Exp. 4 described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0302098#pone.0302098.t002" target="_blank">Table 2</a>. Root means square error (RMSE) (mean absolute error (MAE), coefficient of determination (R²), and Nash Sutcliffe model efficiency (NSE)) are 15.50 (14.63, 0.96, 0.42), 4.76 (3.92, 0.97, 0.95), 4.69 (3.72, 0.98, 0.95), 3.91 (3.40, 0.99, 0.96) and 12.54 (11.67, 0.95, 0.60), 5.07 (4.61, 0.98, 0.93), 4.97 (4.28, 0.97, 0.94), 4.58 (4.02, 0.98, 0.95) for using one, two, three, and four observed phenological stages in the CSPs estimation. …”

Data sources for calibration and evaluation. by Yonghui Zhang (279832)

“…The CSPM, driven by the optimized CSPs, is then evaluated against two independent phenological datasets from Exp. 2 and Exp. 4 described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0302098#pone.0302098.t002" target="_blank">Table 2</a>. Root means square error (RMSE) (mean absolute error (MAE), coefficient of determination (R²), and Nash Sutcliffe model efficiency (NSE)) are 15.50 (14.63, 0.96, 0.42), 4.76 (3.92, 0.97, 0.95), 4.69 (3.72, 0.98, 0.95), 3.91 (3.40, 0.99, 0.96) and 12.54 (11.67, 0.95, 0.60), 5.07 (4.61, 0.98, 0.93), 4.97 (4.28, 0.97, 0.94), 4.58 (4.02, 0.98, 0.95) for using one, two, three, and four observed phenological stages in the CSPs estimation. …”

HRV parameters at different time points. by Shiying Liu (1569478)