Growth of bacteria in various media and temperatures with or without Sf14 infection. by Nykki D. Ross (20933968)

Subjects:

PFU counts and calculations. by Nykki D. Ross (20933968)

Subjects:

Image 3_Significance of LRFN4 in prognosis and tumor microenvironment of lung adenocarcinoma.tif by Nana Wang (533812)

Image 2_Significance of LRFN4 in prognosis and tumor microenvironment of lung adenocarcinoma.tif by Nana Wang (533812)

Image 1_Significance of LRFN4 in prognosis and tumor microenvironment of lung adenocarcinoma.jpeg by Nana Wang (533812)

GTWR results of factors affecting the health level of older adults in the Yangtze River Economic Belt. by Mengmeng Yang (475288)

Subjects:

Molecular dynamics simulation results for Apo-TP53 (red), wild-typeTP53. by Ashraf Attia Mahmoud (21262201)

Study Data. by Jonathan S. Jahr (2709088)

“…It has also been hypothesized that the bradycardia and rare instances of cardiac arrest occurring after the use of sugammadex may be due to a transient decrease in circulating corticosteroids, causing a temporary ‘mini Addisonian crisis.’ …”

Study outcomes. by Jonathan S. Jahr (2709088)

“…It has also been hypothesized that the bradycardia and rare instances of cardiac arrest occurring after the use of sugammadex may be due to a transient decrease in circulating corticosteroids, causing a temporary ‘mini Addisonian crisis.’ …”

Patient characteristics. by Jonathan S. Jahr (2709088)

“…It has also been hypothesized that the bradycardia and rare instances of cardiac arrest occurring after the use of sugammadex may be due to a transient decrease in circulating corticosteroids, causing a temporary ‘mini Addisonian crisis.’ …”

Parkinson’s and age-matched control results. by Adam M. Roth (19845864)

Group results for Experiment 1 and 2. by Adam M. Roth (19845864)

Protein identification results. by Huiyang Jia (14444661)

Testing set error. by Xiangjuan Liu (618000)

“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. …”

Internal structure of an LSTM cell. by Xiangjuan Liu (618000)

“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. …”

Prediction effect of each model after STL. by Xiangjuan Liu (618000)

“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. …”

The kernel density plot for data of each feature. by Xiangjuan Liu (618000)

“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. …”

Flowchart of the STL. by Xiangjuan Liu (618000)

“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. …”

SARIMA predicts season components. by Xiangjuan Liu (618000)

“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. …”

Bi-LSTM architecture diagram. by Xiangjuan Liu (618000)

“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. …”