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. …”

Image 1_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.tif by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 9_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 6_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 3_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 7_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 10_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 2_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 5_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 8_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 4_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 1_Transcriptomic insights into the mechanism of action of telomere-related biomarkers in rheumatoid arthritis.xlsx by Lijuan Feng (3746086)

“…Biomarkers were subsequently identified using machine learning algorithms, receiver operating characteristic analysis, and expression level comparisons between RA and control samples. …”

Table 1_Plasma exosomal lncRNA-related signatures define molecular subtypes and predict survival and treatment response in hepatocellular carcinoma.docx by Fangmin Zhong (17415318)

“…</p>Methods<p>The transcriptomic data from 230 plasma exosomes and 831 HCC tissues were integrated. …”