Lost cases. by Nan Tang (642590)

“…</p><p>Results</p><p>The intervention group showed a significant decrease in anxiety (t =  11.906, P <  0.001) and depression scores (t =  14.991, P <  0.001), as well as PSQI scores (t =  7.055, P <  0.001), and increased FertiQoL scores (t =  -2.828, P <  0.001). …”

Group control-before intervention. by Nan Tang (642590)

“…</p><p>Results</p><p>The intervention group showed a significant decrease in anxiety (t =  11.906, P <  0.001) and depression scores (t =  14.991, P <  0.001), as well as PSQI scores (t =  7.055, P <  0.001), and increased FertiQoL scores (t =  -2.828, P <  0.001). …”

Patient satisfaction with SFA intervention(%). by Nan Tang (642590)

“…</p><p>Results</p><p>The intervention group showed a significant decrease in anxiety (t =  11.906, P <  0.001) and depression scores (t =  14.991, P <  0.001), as well as PSQI scores (t =  7.055, P <  0.001), and increased FertiQoL scores (t =  -2.828, P <  0.001). …”

Pre-Experiment. by Nan Tang (642590)

“…</p><p>Results</p><p>The intervention group showed a significant decrease in anxiety (t =  11.906, P <  0.001) and depression scores (t =  14.991, P <  0.001), as well as PSQI scores (t =  7.055, P <  0.001), and increased FertiQoL scores (t =  -2.828, P <  0.001). …”

Group SFA-after intervention. by Nan Tang (642590)

“…</p><p>Results</p><p>The intervention group showed a significant decrease in anxiety (t =  11.906, P <  0.001) and depression scores (t =  14.991, P <  0.001), as well as PSQI scores (t =  7.055, P <  0.001), and increased FertiQoL scores (t =  -2.828, P <  0.001). …”

Comparison experiment of accuracy improvement. by Zhongjian Xie (4633099)

“…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”

Comparison experiment of accuracy improvement. by Zhongjian Xie (4633099)

“…Secondly, a lightweight convolutional module is introduced to replace the standard convolutions in the Efficient Long-range Aggregation Network (ELAN-A) module, and the channel pruning techniques are applied to further decrease the model’s complexity. Finally, the experiment significantly enhanced the efficiency of feature extraction and the detection accuracy of the model algorithm through the integration of the Dynamic Head (DyHead) module, the Content-Aware Re-Assembly of Features (CARAFE) module, and the incorporation of knowledge distillation techniques. …”

Demographic data of female participants (n = 30). by Vanessa Wellauer (18408477)

“…Core temperature was significantly higher in the HWI than the CWI group (postInt and 30 min), while it was significantly lower in the CWI group than CON (30 min). …”

Raw data used for statistical analysis. by Vanessa Wellauer (18408477)

“…Core temperature was significantly higher in the HWI than the CWI group (postInt and 30 min), while it was significantly lower in the CWI group than CON (30 min). …”

CONSORT flowchart of participants. by Vanessa Wellauer (18408477)

“…Core temperature was significantly higher in the HWI than the CWI group (postInt and 30 min), while it was significantly lower in the CWI group than CON (30 min). …”

Hydrate-Based Gas Storage Made Greener: Methane Hydrate Formation Enhancement with a Low-Toxicity Promoter by Katipot Inkong (7979942)

Subjects:

Hydrate-Based Gas Storage Made Greener: Methane Hydrate Formation Enhancement with a Low-Toxicity Promoter by Katipot Inkong (7979942)

Subjects:

Hydrate-Based Gas Storage Made Greener: Methane Hydrate Formation Enhancement with a Low-Toxicity Promoter by Katipot Inkong (7979942)

Subjects:

Hydrate-Based Gas Storage Made Greener: Methane Hydrate Formation Enhancement with a Low-Toxicity Promoter by Katipot Inkong (7979942)

Subjects:

Hydrate-Based Gas Storage Made Greener: Methane Hydrate Formation Enhancement with a Low-Toxicity Promoter by Katipot Inkong (7979942)

Subjects:

Hydrate-Based Gas Storage Made Greener: Methane Hydrate Formation Enhancement with a Low-Toxicity Promoter by Katipot Inkong (7979942)

Subjects:

Hydrate-Based Gas Storage Made Greener: Methane Hydrate Formation Enhancement with a Low-Toxicity Promoter by Katipot Inkong (7979942)

Subjects:

Hydrate-Based Gas Storage Made Greener: Methane Hydrate Formation Enhancement with a Low-Toxicity Promoter by Katipot Inkong (7979942)

Subjects:

Addressing Imbalanced Classification Problems in Drug Discovery and Development Using Random Forest, Support Vector Machine, AutoGluon-Tabular, and H2O AutoML by Ayush Garg (21090944)

Subjects:

Advancing Circular Bioeconomy through a Systems-Level Assessment of Food Waste and Industrial Sludge Codigestion by Md. Nizam Uddin (21632518)

“…Improved microbial communities contributed to higher COD removal (92%) in the FW-PPMS system compared to monodigestion (80% removal). …”