A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets by Xinghai Zhong (21450285)

Subjects:

A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets by Xinghai Zhong (21450285)

Subjects:

A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets by Xinghai Zhong (21450285)

Subjects:

A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets by Xinghai Zhong (21450285)

Subjects:

A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets by Xinghai Zhong (21450285)

Subjects:

A Wettability Gradient Synergistic Bionic Wedge-Shaped Track for Ultrafast and Long-Distance Spontaneous Transport of Droplets by Xinghai Zhong (21450285)

Subjects:

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)

Aβ and vGlut2 staining of 6-, 9-, and 12-month dLGN sections show significant plaque load and accelerated loss of retinal ganglion cell axon terminals in the 5xFAD mice. by Shaylah McCool (20818280)

Average Gait Speed (A), Cadence (B), Step Length (C), and Walk Ratio (D) across Terrains; Violin plots with individual participant data of A) gait speed, B) cadence, C) average ste... by Benjamin S. Killen (22766029)

(A) Procedural steps for minimally invasive Ponto surgery (MIPS). The MIPS procedure involves the following steps: (i) A circular incision is created at the selected site via a 4-... by Marsel Ganeyev (21453399)

Subjects:

Model-averaged coefficients, significance, and relative importance (RI) of the predictor variables for the GLMMs to evaluate effects on: (A) overall pollinator abundance; (B) fruit... by Carmelo Gómez-Martínez (9384385)

Generated spline library. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Correlation coefficient matrix. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

RMSE versus learning rate. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

RMSE versus training parameters. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Assembly process of machine recognition form. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Process of steel truss incremental launching. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

CGAN and AutoML stacking device. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

U-wave estimates versus R-matrix noise variance. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”

Sliding window process. by Zhe Hu (787283)

“…Following model updates with measured data, the accumulated prediction error rapidly decreases. The proposed prediction method for shape errors during pushing exhibits high accuracy and versatility in similar projects, significantly reducing time spent on manual error handling and minimizing computational inaccuracies.…”