Fig 3 - by Elizabeth Garcia (23115)

Fig 5 - by Elizabeth Garcia (23115)

IF analysis of N-cadherin in esophageal tissue from pediatric control (0–5 Eos/HPF) and EoE patients (>15 Eos/HPF). by Elizabeth Garcia (23115)

IF analysis of TWIST1 in esophageal tissue from pediatric control (0–5 Eos/HPF) and EoE patients (>15 Eos/HPF). by Elizabeth Garcia (23115)

Localization trajectory for experiment 2. by Li Wang (15202)

“…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”

Localization trajectory for experiment 1. by Li Wang (15202)

“…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”

Tendency chart of monthly FVC mean. by Yichuan Zhang (2888345)

“…The high and very high coverage areas in each month are mainly distributed on the outskirts of the park, while the medium, medium-low, and low coverage areas are mainly located in the central and middle parts of the park. …”

WGCNA as well as the co-expression network. by Hao Wang (39217)

Expression of ACE-2, TMPRSS2, Cathepsin B, and Cathepsin L genes in the epithelium of ex vivo infected central cornea and corneoscleral rim at H0 (<i>n =</i> 5 samples). by Corantin Maurin (9155070)

SARS-CoV-2 RNA expression in ex vivo infection. by Corantin Maurin (9155070)

Process of UWB location prediction based on LSTM. by Li Wang (15202)

“…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”

Time of flight ranging model. by Li Wang (15202)

“…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”

Snake optimizer algorithm optimization process. by Li Wang (15202)

“…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”

Crane experimental platform. by Li Wang (15202)

“…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”

SO-LSTM loss value curve. by Li Wang (15202)

“…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”

UWB data grouping. by Li Wang (15202)

“…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”

Network model and time slot allocation. by Li Wang (15202)

“…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”

SO-LSTM algorithm parameters. by Li Wang (15202)

“…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”

Visualization of ranging error in experiment 1. by Li Wang (15202)

“…In comparison to conventional approaches such as the least squares method (LS) and the Kalman filter method (KF), the proposed SO-LSTM-based positioning method significantly reduces the root mean square error (RMSE) by 63.39% and 58.01%, respectively, while also decreasing the maximum positioning error (MPE) by 60.77% and 52.65%.…”

Demographic and clinical parameters. by Jesse D. de Groot (15401476)

“…Multiple general linear models were used to asses white matter and gray matter volumetric differences between time points. A mean RT dose map was created and compared to the VBM results.…”