Image_5_Next-Generation Camera Trapping: Systematic Review of Historic Trends Suggests Keys to Expanded Research Applications in Ecology and Conservation.TIFF by Zackary J. Delisle (10200560)

Table_5_Next-Generation Camera Trapping: Systematic Review of Historic Trends Suggests Keys to Expanded Research Applications in Ecology and Conservation.XLSX by Zackary J. Delisle (10200560)

Analysis of scotopic electroretinograms in the <i>Aplp2</i> knockout mice. by Andrei V. Tkatchenko (789098)

“…Lack of <i>Aplp2</i> causes a dose-dependent decrease in the b-wave amplitude (F(2, 18) = 6.9, p = 6.0 × 10⁻³). …”

Image_9_Next-Generation Camera Trapping: Systematic Review of Historic Trends Suggests Keys to Expanded Research Applications in Ecology and Conservation.TIFF by Zackary J. Delisle (10200560)

Table_4_Next-Generation Camera Trapping: Systematic Review of Historic Trends Suggests Keys to Expanded Research Applications in Ecology and Conservation.DOC by Zackary J. Delisle (10200560)

Table_1_Next-Generation Camera Trapping: Systematic Review of Historic Trends Suggests Keys to Expanded Research Applications in Ecology and Conservation.docx by Zackary J. Delisle (10200560)

Table_6_Next-Generation Camera Trapping: Systematic Review of Historic Trends Suggests Keys to Expanded Research Applications in Ecology and Conservation.XLSX by Zackary J. Delisle (10200560)

Image_4_Next-Generation Camera Trapping: Systematic Review of Historic Trends Suggests Keys to Expanded Research Applications in Ecology and Conservation.TIFF by Zackary J. Delisle (10200560)

Image_3_Next-Generation Camera Trapping: Systematic Review of Historic Trends Suggests Keys to Expanded Research Applications in Ecology and Conservation.TIFF by Zackary J. Delisle (10200560)

Image_6_Next-Generation Camera Trapping: Systematic Review of Historic Trends Suggests Keys to Expanded Research Applications in Ecology and Conservation.TIFF by Zackary J. Delisle (10200560)

Image_8_Next-Generation Camera Trapping: Systematic Review of Historic Trends Suggests Keys to Expanded Research Applications in Ecology and Conservation.TIFF by Zackary J. Delisle (10200560)

Reduction of motor proteins perturbs the bi-directional movement of TKV vesicles. by Min Jung Kang (616217)

“…Arrows indicate the direction of change with 50% reduction of motors. <b>E:</b> Box plots of duration-weighted segmental velocities of TKV-GFP vesicles in larvae with 50% kinesin or dynein compared to larvae with 100% kinesin or dynein show no significant changes (NS) in both the anterograde and retrograde velocities. …”

Table_4_CoMB-Deep: Composite Deep Learning-Based Pipeline for Classifying Childhood Medulloblastoma and Its Classes.docx by Omneya Attallah (770722)

“…Next, the CoMB-Deep explores the best combination of fused features, enhancing the performance of the classification process using two search strategies. Afterward, it employs two feature selection techniques on the fused feature sets selected in the previous step. …”

Data_Sheet_1_CoMB-Deep: Composite Deep Learning-Based Pipeline for Classifying Childhood Medulloblastoma and Its Classes.ZIP by Omneya Attallah (770722)

“…Next, the CoMB-Deep explores the best combination of fused features, enhancing the performance of the classification process using two search strategies. Afterward, it employs two feature selection techniques on the fused feature sets selected in the previous step. …”

Table_3_CoMB-Deep: Composite Deep Learning-Based Pipeline for Classifying Childhood Medulloblastoma and Its Classes.docx by Omneya Attallah (770722)

“…Next, the CoMB-Deep explores the best combination of fused features, enhancing the performance of the classification process using two search strategies. Afterward, it employs two feature selection techniques on the fused feature sets selected in the previous step. …”

Table_1_CoMB-Deep: Composite Deep Learning-Based Pipeline for Classifying Childhood Medulloblastoma and Its Classes.docx by Omneya Attallah (770722)

“…Next, the CoMB-Deep explores the best combination of fused features, enhancing the performance of the classification process using two search strategies. Afterward, it employs two feature selection techniques on the fused feature sets selected in the previous step. …”

Table_7_CoMB-Deep: Composite Deep Learning-Based Pipeline for Classifying Childhood Medulloblastoma and Its Classes.docx by Omneya Attallah (770722)

“…Next, the CoMB-Deep explores the best combination of fused features, enhancing the performance of the classification process using two search strategies. Afterward, it employs two feature selection techniques on the fused feature sets selected in the previous step. …”

Table_6_CoMB-Deep: Composite Deep Learning-Based Pipeline for Classifying Childhood Medulloblastoma and Its Classes.docx by Omneya Attallah (770722)

“…Next, the CoMB-Deep explores the best combination of fused features, enhancing the performance of the classification process using two search strategies. Afterward, it employs two feature selection techniques on the fused feature sets selected in the previous step. …”

Image_1_CoMB-Deep: Composite Deep Learning-Based Pipeline for Classifying Childhood Medulloblastoma and Its Classes.TIF by Omneya Attallah (770722)

“…Next, the CoMB-Deep explores the best combination of fused features, enhancing the performance of the classification process using two search strategies. Afterward, it employs two feature selection techniques on the fused feature sets selected in the previous step. …”

Table_5_CoMB-Deep: Composite Deep Learning-Based Pipeline for Classifying Childhood Medulloblastoma and Its Classes.docx by Omneya Attallah (770722)

“…Next, the CoMB-Deep explores the best combination of fused features, enhancing the performance of the classification process using two search strategies. Afterward, it employs two feature selection techniques on the fused feature sets selected in the previous step. …”