Analysis of variance of HbO₂ in bilateral PFC. by Xinyu Dai (5100731)

“…</p><p>Results</p><p>Following the intervention, a significant difference in CR10 was observed between the various groups. …”

fNIRS equipment coordinates. by Xinyu Dai (5100731)

“…</p><p>Results</p><p>Following the intervention, a significant difference in CR10 was observed between the various groups. …”

Changes of muscle oxygen saturation. by Xinyu Dai (5100731)

“…</p><p>Results</p><p>Following the intervention, a significant difference in CR10 was observed between the various groups. …”

Analysis of variance of CR10. by Xinyu Dai (5100731)

“…</p><p>Results</p><p>Following the intervention, a significant difference in CR10 was observed between the various groups. …”

Placement on the forehead. by Xinyu Dai (5100731)

“…</p><p>Results</p><p>Following the intervention, a significant difference in CR10 was observed between the various groups. …”

IMW intervention plan design. by Xinyu Dai (5100731)

“…</p><p>Results</p><p>Following the intervention, a significant difference in CR10 was observed between the various groups. …”

Effect of dilution factor and replicate number on the reproducibility of αSyn^D seed concentration estimates in PD (A-D) and DLB (E-H) brain homogenates by ED RT-QuIC ass... by Ankit Srivastava (742990)

Model fit indices for social isolation. by Juhee Choi (2619733)

“…The data were analyzed using multilevel modeling with a three-way interaction design.</p><p>Results</p><p>A significant three-way interaction was found between time, depression severity, and COVID-19 diagnosis, while anxiety severity showed no significant interaction. …”

Multilevel model analysis of social isolation. by Juhee Choi (2619733)

“…The data were analyzed using multilevel modeling with a three-way interaction design.</p><p>Results</p><p>A significant three-way interaction was found between time, depression severity, and COVID-19 diagnosis, while anxiety severity showed no significant interaction. …”

Acoustic Startle at 28 dpf. by Morgan Barnes (7876373)

“…(C) There is a significant decrease of PPI in the 48+ and 72 + fish (p < 0.0001). …”

Modulation of performance during learning. by Daniel Ramandi (10047543)

“…The ‘W_exp’ value shows the weight of the exponential component in each distribution. (B) A longitudinal comparison of the average exponential fit weight between WT and zQ175 mice reveals that while WT mice show a decreasing trend, indicating a shift towards longer duration (“timed”) trials, zQ175 mice maintain a consistently high exponential weight, demonstrating no significant change over time (b; RM two-way ANOVA, genotype p = 0.0106 F(1, 22) = 7.795, days p < 0.0001 F(5.262, 115.4) = 7.616, interaction p < 0.0001 F(57, 1250) = 2.834). …”

Related to Fig 2. by Mohammad Nafees Ansari (22232505)

“…(<b>C</b>) Cell proliferation studies show a decrease in the proliferation of BT-474_RICTOR^SH cells (mean ± SEM, <i>n</i> = 3) compared to BT-474_SCRAM^SH cells. …”

RICTOR silencing inhibits cell proliferation via UGCG regulation. by Mohammad Nafees Ansari (22232505)

“…(<b>C</b>) Cell proliferation studies show a decrease in the proliferation of MCF-7_RICTOR^SH cells (mean ± SEM, <i>n</i> = 4) compared to MCF-7_SCRAM^SH cells. …”

Complexity comparison of different models. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. …”

Dynamic window based median filtering algorithm. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. …”

Flow of operation of improved KMA. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. …”

Improved DAE based on LSTM. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. …”

Autoencoder structure. by Li Yuan (102305)

“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. …”

Validation and predictive accuracy of the cerebrovascular model, by Hadi Esfandi (21387211)

“…<p>(a-f) dependency of blood flow in capillaries on the cortical depth and ABNP values: (a) mean and standard deviation of blood flow in Cap1 segments for various ABNP values, (b) layer-specific average blood flow in capillaries across the entire monophasic flat autoregulation range, (c) indicates that the superficial layers have a more nonuniform hemodynamic distribution in capillaries, (d) mean capillary blood flow across different vascular layers at physiological ABNP values (50-70 mmHg), (e) WT changes in superficial PA segments are more significant than in deeper segments across the autoregulation range. …”

Related to Fig 1. by Mohammad Nafees Ansari (22232505)

“…(<b>E</b>–<b>H</b>) Absolute quantification (mean ± SEM, <i>n</i> = 3–4) of GM3 (E), GD3 (F), GM2 (G), and GM1 (H) gangliosides shows an increase in GD3 and GM2 gangliosides and a decrease in GM3 and GM1 gangliosides in BT-474_UGCG^OE cells compared to BT-474 cells. …”