Porous Metal Transpiration Cooling Structures Fabricated via Laser Powder Bed Fusion 由 Jianqiang Gong (22660604)

Data Sheet 1_Interpretable machine learning model for predicting covert hepatic encephalopathy in patients with cirrhosis: a multicenter study.docx 由 Yilong Liu (8952695)

“...</p>Methods<p>This retrospective study included 503 patients with liver cirrhosis from 16 medical centers in China. ...”

Simulated serological data using serosim and subsequent results using the full mixture model on (a) HAI, (b) IgG and (c) IgM data with additional observational noise. 由 Marco Hamins-Puértolas (15238661)

Additional file 1 of Global Insights on Wearable Technology Adoption by Coaches: Determinants of Current Use, Decision Making, and Future Intention To Use 由 Peter Düking (12336498)

Eligibility Assessment, Covariate Assessment, Risk Windows, and Reference Windows Relative to Time 0 for the Self-Controlled Risk Interval Design. 由 Shelby S. Fisher (22676406)

Eligibility assessment, covariate assessment, and follow-up windows relative to time 0 for the cohort design. 由 Shelby S. Fisher (22676406)

“...Note: This figure displays the analyses with follow-up starting on the day after Time 0, and Time 0 included in the washout windows. Additional analyses were performed with follow-up beginning on Time 0, and the washout windows ending on the day before Time 0....”

The interactive amr.watch application here shows an overview from 179,518 <i>E. coli</i> genomes available as of 31 March 2025. 由 Sophia David (4172902)

Provisional study schedule of MUSIBOT. 由 Pierre Angelvy (22683450)

“...<div><p>Introduction</p><p>Botulinum toxin injections are a common treatment for managing spasticity resulting from central nervous system damage, including stroke, multiple sclerosis, and traumatic brain injury. ...”

LdrA expression causes transient growth arrest and the FLAG tag does not affect its toxicity. 由 Yuto Nakamura (1493086)

Similarly to S9, but F4-Fz electrode pairs. 由 Magaly Catanzariti (20865500)

“...Hypnogram analysis was used to assess sleep architecture, including alterations in cycle patterns and time spent in each stage. ...”

Similarly to S9, for F3-FCz electrode pairs. 由 Magaly Catanzariti (20865500)

“...Hypnogram analysis was used to assess sleep architecture, including alterations in cycle patterns and time spent in each stage. ...”

Similarly to S9, for F3-F4 electrode pairs. 由 Magaly Catanzariti (20865500)

“...Hypnogram analysis was used to assess sleep architecture, including alterations in cycle patterns and time spent in each stage. ...”

Similarly to S9, for F3-Fz electrode pairs. 由 Magaly Catanzariti (20865500)

“...Hypnogram analysis was used to assess sleep architecture, including alterations in cycle patterns and time spent in each stage. ...”

Similarly to S9, but for F4-Cz electrode pairs. 由 Magaly Catanzariti (20865500)

“...Hypnogram analysis was used to assess sleep architecture, including alterations in cycle patterns and time spent in each stage. ...”

Full Data. 由 Yasmine S. S. Muir (16007230)

“...Additionally, in female koalas, the detection of mucosal PhaHV-1 and greater KoRV proviral <i>pol</i> loads were equal predictors of chlamydial reproductive disease. ...”

The architecture of the SVNC-Net. 由 Mehmet Zahid Genc (22683526)

“...To evaluate its performance and efficiency, a comparative analysis was conducted against well-known CNN-based models, including UPerNet, EMANet, CCNet, SegNet, and ShuffleNet. ...”

Segmentation accuracy of the models. 由 Mehmet Zahid Genc (22683526)

“...To evaluate its performance and efficiency, a comparative analysis was conducted against well-known CNN-based models, including UPerNet, EMANet, CCNet, SegNet, and ShuffleNet. ...”

Training and implementation details. 由 Mehmet Zahid Genc (22683526)

“...To evaluate its performance and efficiency, a comparative analysis was conducted against well-known CNN-based models, including UPerNet, EMANet, CCNet, SegNet, and ShuffleNet. ...”

Fold assignments for each evaluation round. 由 Mehmet Zahid Genc (22683526)

“...To evaluate its performance and efficiency, a comparative analysis was conducted against well-known CNN-based models, including UPerNet, EMANet, CCNet, SegNet, and ShuffleNet. ...”

Computational efficiency of the models. 由 Mehmet Zahid Genc (22683526)

“...To evaluate its performance and efficiency, a comparative analysis was conducted against well-known CNN-based models, including UPerNet, EMANet, CCNet, SegNet, and ShuffleNet. ...”