Table 1_Exploring the role of TikTok for intersectionality marginalized groups: the case of Muslim female content creators in Germany.docx by Fatima El Sayed (20146977)

“…They shape the platform’s functionalities through creative use, while TikTok’s algorithm and virality logic drive creators to blend entertainment with personal content. …”

Data Sheet 1_Deciphering novel mitochondrial signatures: multi-omics analysis uncovers cross-disease markers and oligodendrocyte pathways in Alzheimer’s disease and glioblastoma.do... by Xuan Xu (781842)

“…</p>Results<p>Our analysis identified four significant cross-disease mitochondrial markers: EFHD1, SASH1, FAM110B, and SLC25A18. These markers showed both shared and unique expression profiles in AD and GBM, suggesting a common mitochondrial mechanism contributing to both diseases. …”

Table 1_Deciphering novel mitochondrial signatures: multi-omics analysis uncovers cross-disease markers and oligodendrocyte pathways in Alzheimer’s disease and glioblastoma.xlsx by Xuan Xu (781842)

“…</p>Results<p>Our analysis identified four significant cross-disease mitochondrial markers: EFHD1, SASH1, FAM110B, and SLC25A18. These markers showed both shared and unique expression profiles in AD and GBM, suggesting a common mitochondrial mechanism contributing to both diseases. …”

Ricker seismic profile. by Zhenjing Yao (22189970)

“…Then, the decomposed effective intrinsic mode functions (IMFs) are extracted to separate and suppress random noises. …”

Noise reduction on testing sets from STEAD. by Zhenjing Yao (22189970)

“…Then, the decomposed effective intrinsic mode functions (IMFs) are extracted to separate and suppress random noises. …”

SNR comparison of real-field seismic profile. by Zhenjing Yao (22189970)

“…Then, the decomposed effective intrinsic mode functions (IMFs) are extracted to separate and suppress random noises. …”

The flowchart of GWO-VMD method. by Zhenjing Yao (22189970)

“…Then, the decomposed effective intrinsic mode functions (IMFs) are extracted to separate and suppress random noises. …”

The 147th single trace. by Zhenjing Yao (22189970)

“…Then, the decomposed effective intrinsic mode functions (IMFs) are extracted to separate and suppress random noises. …”

Supplementary file 1_Unraveling the bacterial composition of a coral and bioeroding sponge competing in a marginal coral environment.docx by Sambhaji Mote (6311663)

“…This study focuses on the coral Turbinaria mesenterina and sponge C. thomasi, both known for their distinct symbiotic associations with Symbiodiniaceae. …”

MCCN Case Study 2 - Spatial projection via modelled data by Donald Hobern (21435904)

“…This study demonstrates: 1) Description of spatial assets using STAC, 2) Loading heterogeneous data sources into a cube, 3) Spatial projection in xarray using different algorithms offered by the <a href="https://pypi.org/project/PyKrige/" rel="nofollow" target="_blank">pykrige</a> and <a href="https://pypi.org/project/rioxarray/" rel="nofollow" target="_blank">rioxarray</a> packages.…”

Data Sheet 1_Machine learning models integrating intracranial artery calcification to predict outcomes of mechanical thrombectomy.pdf by Guangzong Li (16696443)

“…Eleven ML algorithms were trained and validated using Python, and external validation and performance evaluations were conducted. …”

Data Sheet 1_Mycobiome analysis of leaf, root, and soil of symptomatic oil palm trees (Elaeis guineensis Jacq.) affected by leaf spot disease.pdf by Abiodun Abeeb Azeez (20393835)

“…Additionally, a large proportion of the identified keystone species consisted of rare taxa, suggesting potential role in ecosystem functions. Surprisingly both AS and SS leaf samples shared taxa previously associated with oil palm leaf spot disease. …”

Image 1_Mitochondrial insights: key biomarkers and potential treatments for diabetic nephropathy and sarcopenia.tif by Yi Wei Chen (21684728)

“…Utilizing four machine learning algorithms (LASSO, SVM, XGBoost, RF), we pinpointed three mitochondrial hub genes. …”

DataSheet2_Identification and validation of efferocytosis-related biomarkers for the diagnosis of metabolic dysfunction-associated steatohepatitis based on bioinformatics analysis... by Chenghui Cao (12472029)

“…To screen for biomarkers for diagnosis, we applied machine learning algorithm to identify hub genes and constructed a clinical predictive model. …”

Table 1_Integrated transcriptomic and network analysis reveals candidate immune–metabolic biomarkers in children with the inattentive type of ADHD.xlsx by Qiaoyan Shao (22357861)

“…The ADHD-I molecular landscape was explored through functional enrichment, immune cell profiling, pharmacological screening, and ligand-receptor interaction modeling.…”

Image 1_Integrated transcriptomic and network analysis reveals candidate immune–metabolic biomarkers in children with the inattentive type of ADHD.tif by Qiaoyan Shao (22357861)

“…The ADHD-I molecular landscape was explored through functional enrichment, immune cell profiling, pharmacological screening, and ligand-receptor interaction modeling.…”

Table 2_Integrated transcriptomic and network analysis reveals candidate immune–metabolic biomarkers in children with the inattentive type of ADHD.xlsx by Qiaoyan Shao (22357861)

“…The ADHD-I molecular landscape was explored through functional enrichment, immune cell profiling, pharmacological screening, and ligand-receptor interaction modeling.…”

DataSheet1_Identification and validation of efferocytosis-related biomarkers for the diagnosis of metabolic dysfunction-associated steatohepatitis based on bioinformatics analysis... by Chenghui Cao (12472029)

“…To screen for biomarkers for diagnosis, we applied machine learning algorithm to identify hub genes and constructed a clinical predictive model. …”

A New Control Approach for a Multi-Controlled Wheelchair Utilizing Deep Learning Framework and Raspberry Pi by Sudipta Chatterjee (536333)

“…Employing a deep learning algorithm, it performs real-time object detection and tracks its current position in various environmental conditions. …”

DataSheet1_Application of a risk score model based on glycosylation-related genes in the prognosis and treatment of patients with low-grade glioma.docx by Binbin Zou (11358315)

“…However, the biological function of glycosylation-related genes in LGG remains largely unexplored. …”