Pathogen induced cytokine storm signaling pathway ‐ Expression overlay: PAS-highFIB-highGCX vs. Naive-noFIB-highGCX. by Melissa A. Hausburg (20529229)

Communication between innate and adaptive immune cells ‐ Expression overlay: PAS-highFIB-highGCX vs. Naive-noFIB-highGCX. by Melissa A. Hausburg (20529229)

Interleukin-10 signaling pathway ‐ Expression overlay: PAS-highFIB-highGCX vs. Naive-noFIB-highGCX. by Melissa A. Hausburg (20529229)

Role of macrophages, fibroblasts, and endothelial cells in rheumatoid arthritis (modified)–Expression overlay: PAS-highFIB-highGCX vs. Naive-noFIB-highGCX. by Melissa A. Hausburg (20529229)

Posterior predictive checks using simulated marker expression data. by Christiaan H. van Dorp (9449599)

Regular spiking neuron (sustained chopper) that exhibits accurate identification of envelope frequency from its spike trains. by Chris Scholes (3309477)

Relevant parameters of the benchmark models. by Wang Xiaoqian (10502222)

“…Engineering verification calculations indicated that the BP neural network model can predict concrete performance under actual working conditions with a small error rate. Compared with traditional models, the neural network model has comprehensive advantages in terms of fitting accuracy, reduced overfitting, and enhanced stability.…”

Peak strain and stress values of the specimens. by Wang Xiaoqian (10502222)

“…Engineering verification calculations indicated that the BP neural network model can predict concrete performance under actual working conditions with a small error rate. Compared with traditional models, the neural network model has comprehensive advantages in terms of fitting accuracy, reduced overfitting, and enhanced stability.…”

Aggregate characteristic curves. by Wang Xiaoqian (10502222)

“…Engineering verification calculations indicated that the BP neural network model can predict concrete performance under actual working conditions with a small error rate. Compared with traditional models, the neural network model has comprehensive advantages in terms of fitting accuracy, reduced overfitting, and enhanced stability.…”

Characteristic chart of algorithm efficiency. by Wang Xiaoqian (10502222)

“…Engineering verification calculations indicated that the BP neural network model can predict concrete performance under actual working conditions with a small error rate. Compared with traditional models, the neural network model has comprehensive advantages in terms of fitting accuracy, reduced overfitting, and enhanced stability.…”

Improved BP network algorithm flow. by Wang Xiaoqian (10502222)

“…Engineering verification calculations indicated that the BP neural network model can predict concrete performance under actual working conditions with a small error rate. Compared with traditional models, the neural network model has comprehensive advantages in terms of fitting accuracy, reduced overfitting, and enhanced stability.…”

TDS530 Static strain gauge. by Wang Xiaoqian (10502222)

“…Engineering verification calculations indicated that the BP neural network model can predict concrete performance under actual working conditions with a small error rate. Compared with traditional models, the neural network model has comprehensive advantages in terms of fitting accuracy, reduced overfitting, and enhanced stability.…”

Antibodies used in this study. by Gillian C. A. Taylor (3909568)

“…In one case (<i><i>Ncaph2</i></i>), a C-terminal auxin-inducible degron fusion strongly increased protein stability in some tissues but decreased it in others. Destabilisation resulted from tissue-specific ‘leakage’ of the auxin-inducible degron, which depended on TIR1 expression, and occurred selectively in the small intestine where basal concentrations of auxin/ indole-3-acetic acid can reach levels that are sufficient to trigger protein degradation in cultured cells. …”

BP neural network architecture. by Wang Xiaoqian (10502222)

“…Engineering verification calculations indicated that the BP neural network model can predict concrete performance under actual working conditions with a small error rate. Compared with traditional models, the neural network model has comprehensive advantages in terms of fitting accuracy, reduced overfitting, and enhanced stability.…”

Peak strain and stress curves. by Wang Xiaoqian (10502222)

“…Engineering verification calculations indicated that the BP neural network model can predict concrete performance under actual working conditions with a small error rate. Compared with traditional models, the neural network model has comprehensive advantages in terms of fitting accuracy, reduced overfitting, and enhanced stability.…”

Coarse and fine aggregates used for testing. by Wang Xiaoqian (10502222)

“…Engineering verification calculations indicated that the BP neural network model can predict concrete performance under actual working conditions with a small error rate. Compared with traditional models, the neural network model has comprehensive advantages in terms of fitting accuracy, reduced overfitting, and enhanced stability.…”

Loading setup for cured samples. by Wang Xiaoqian (10502222)

“…Engineering verification calculations indicated that the BP neural network model can predict concrete performance under actual working conditions with a small error rate. Compared with traditional models, the neural network model has comprehensive advantages in terms of fitting accuracy, reduced overfitting, and enhanced stability.…”

Steel tube material property test. by Wang Xiaoqian (10502222)

“…Engineering verification calculations indicated that the BP neural network model can predict concrete performance under actual working conditions with a small error rate. Compared with traditional models, the neural network model has comprehensive advantages in terms of fitting accuracy, reduced overfitting, and enhanced stability.…”

Measurement point arrangement and loading device. by Wang Xiaoqian (10502222)

“…Engineering verification calculations indicated that the BP neural network model can predict concrete performance under actual working conditions with a small error rate. Compared with traditional models, the neural network model has comprehensive advantages in terms of fitting accuracy, reduced overfitting, and enhanced stability.…”

STCDSRAC axial compressive stress–strain curves. by Wang Xiaoqian (10502222)

“…Engineering verification calculations indicated that the BP neural network model can predict concrete performance under actual working conditions with a small error rate. Compared with traditional models, the neural network model has comprehensive advantages in terms of fitting accuracy, reduced overfitting, and enhanced stability.…”