Figure 3 from Chromothripsis-Mediated Small Cell Lung Carcinoma by Natasha Rekhtman (15014156)

“…<b>B,</b> CN log ratio plots from the FACETS algorithm displaying the distinctive oscillating CN states on chromosomes with chromothripsis. …”

Supporting files for thesis "Deep-learning-based Morphological Modelling: Case Study in Soft Robot Control, Shape Sensing and Deformation" by Yingqi Li (9151304)

“…The algorithm of deep deterministic policy gradient (DDPG) along with domain randomization and offline retraining facilitates fast initialization and stable path following, even under varying tip load, demonstrating its advantages over Jacobian model-based and supervised-learning-based control methods. …”

Table 1_An immunotherapy guide constructed by cGAS-STING signature for breast cancer and the biofunction validation of the pivotal gene HOXC13 via in vitro experiments.docx by Zhenling Dai (22011134)

“…In this study, we aim to explore the role of the cGAS-STING pathway in breast cancer immunotherapy resistance.</p>Methods<p>Multiple machine learning algorithms were applied to construct an immunotherapy subgroup model and in vitro experiments were performed to verify the HOXC13 in regulating BRCA immunity.…”

Image 2_An immunotherapy guide constructed by cGAS-STING signature for breast cancer and the biofunction validation of the pivotal gene HOXC13 via in vitro experiments.tif by Zhenling Dai (22011134)

“…In this study, we aim to explore the role of the cGAS-STING pathway in breast cancer immunotherapy resistance.</p>Methods<p>Multiple machine learning algorithms were applied to construct an immunotherapy subgroup model and in vitro experiments were performed to verify the HOXC13 in regulating BRCA immunity.…”

Image 1_An immunotherapy guide constructed by cGAS-STING signature for breast cancer and the biofunction validation of the pivotal gene HOXC13 via in vitro experiments.tif by Zhenling Dai (22011134)

“…In this study, we aim to explore the role of the cGAS-STING pathway in breast cancer immunotherapy resistance.</p>Methods<p>Multiple machine learning algorithms were applied to construct an immunotherapy subgroup model and in vitro experiments were performed to verify the HOXC13 in regulating BRCA immunity.…”

Supplementary file 1_An interpretable stacking ensemble model for high-entropy alloy mechanical property prediction.docx by Songpeng Zhao (21563714)

“…Three machine learning algorithms-Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Gradient Boosting (Gradient Boosting)-were integrated into a multi-level stacking ensemble, with Support Vector Regression serving as the meta-learner. …”

Supplementary information files for "Explainable machine learning models for predicting the ultimate bending capacity of slotted perforated cold-formed steel beams under distortion... by L Simwanda (19921680)

“…Utilizing a dataset from 432 non-linear finite element analysis simulations of CFS Lipped channels, ten ML algorithms, including four basic and six ensemble models, were evaluated. …”

Processed InShaPe dataset: Large-scale multi-shape phase retrieval dataset for PBF-LB/M laser beam shaping SLM phase mask estimation. by Shengyuan Yan (22248700)

“…Software. https://doi.org/10.6084/m9.figshare.27650946.v2</p><p><br></p><p dir="ltr">This simulated dataset containing six beam shapes is used for training and testing on the complex forward path application, PBF-LB/M beam shaping system, in our paper "Efficient Gerchberg-Saxton algorithm deep unrolling for phase retrieval with complex forward path". …”

From GIS to HBIM and Back: Multiscale Performance and Condition Assessment for Networks of Public Heritage Buildings and Construction Components by Teresa Fortunato (21076099)

“…GIS-based inventory approach of networked construction materials, components, and performances is established by unified performance descriptors and diagnostic tests. GIS-BIM data exchange routines by programming codes and algorithms are developed in Python. …”

Supplementary file 1_Local adaptation and validation of a transdiagnostic risk calculator for first episode psychosis using mental health patient records.docx by Elizabeth Ford (381364)

“…Baseline and outcome coded diagnoses were supplemented with NLP-derived diagnosis data. …”

Additional file 1 of The two ends of the spectrum: comparing chronic schizophrenia and premorbid latent schizotypy by actigraphy by Szandra László (21420583)

“…There is provided further information about data collection and processing, machine learning algorithms, and other program codes, and more details about the findings…”

<b>R</b><b>esidual</b> <b>GCB-Net</b>: Residual Graph Convolutional Broad Network on Emotion Recognition by Qilin Li (535447)

“…<p dir="ltr">Electroencephalogram (EEG) data are commonly applied in the emotion recognition research area. …”

Cringe - Emotional manipulation as a tool of political control in Albanian digital campaigns (2025) by Edlira Gugu (21793610)

“…</p><p dir="ltr"><b>Key findings include:</b></p><ul><li>Perfect correlation (r = 1.000) between cringe intensity and electoral success</li><li>Identification of six strategic cringe tactics used by politicians</li><li>Discovery of 58 anonymous pages using artificial amplification (ratios up to 396:1)</li><li>Evidence of cringe functioning as affective governance and social control</li></ul><p dir="ltr"><b>Dataset contents:</b></p><ul><li>Full research paper (English & Albanian versions)</li><li>Interactive data visualizations and statistical analysis</li><li>Comprehensive emotions lexicon for cringe phenomenon</li><li>Detailed supplementary materials with coded examples</li><li>Methodology documentation and ethics compliance records</li></ul><p dir="ltr"><b>Methodology:</b> Mixed-methods approach combining computational analysis with qualitative discourse analysis. …”

Table 2_Identification and validation of pyroptosis-related genes in Alzheimer’s disease based on multi-transcriptome and machine learning.docx by Yuntai Wang (21356525)

“…Additionally, we validated the expression patterns of these key genes using the expression data from AD mice and constructed potential regulatory networks through time series and correlation analysis.…”

Table 1_Identification and validation of pyroptosis-related genes in Alzheimer’s disease based on multi-transcriptome and machine learning.xlsx by Yuntai Wang (21356525)

“…Additionally, we validated the expression patterns of these key genes using the expression data from AD mice and constructed potential regulatory networks through time series and correlation analysis.…”

Table 1_Development of an alkaliptosis-related lncRNA risk model and immunotherapy target analysis in lung adenocarcinoma.docx by Xiang Xiong (1810234)

“…</p>Methods<p>The TCGA database was utilized to obtain RNA-seq-based transcriptome profiling data, clinical information, and mutation data. We conducted multivariate Cox regression analysis to identify alkaliptosis-related lncRNAs. …”

Video 1_TDE-3: an improved prior for optical flow computation in spiking neural networks.mp4 by Matthew Yedutenko (5142461)

“…We conducted an in-depth quantitative investigation of optical flow coding with TDE and compared TDE-2 vs. TDE-3 in terms of energy efficiency and coding precision. …”

Info-graphics summarising how to navigate the field of AI in the form of a tube (metro) map. by Aidan Crilly (21743791)

“…The rules in this paper are ordered according to the flow of scientific explorations: Framing the scientific problem and finding AI algorithms (Zone 2), coding (Zone 3), and testing and interpreting results (Zone 4). …”

<b>Supplementary Materials for:</b> <b>Pan-Cancer Analysis Reveals LncRNA CDKN2B-AS1 as an Immune-Related Biomarker Validated in LIHC and ACC</b> by Dandan Lin (18192946)

“…This study comprehensively investigates the role of the long non-coding RNA CDKN2B-AS1 in cancer prognosis and tumor microenvironment across multiple cancer types using bioinformatic analyses.…”

Presentation1_Extrachromosomal circular DNAs in prostate adenocarcinoma: global characterizations and a novel prediction model.pdf by Qingliu He (12528332)

“…</p>Methods<p>Circular_seq was used in conjunction with the TCGA-PRAD transcriptome dataset to sequence, annotate, and filter for eccDNA-amplified differentially expressed coding genes (eDEGs) in PRAD and para-cancerous normal prostate tissues. …”