Identification of ferroptosis-related LncRNAs as potential targets for improving immunotherapy in glioblastoma حسب Zhaochen Wang (12176245)

"…<p>The effect of ferroptosis-related long non-coding RNAs (lncRNAs) in predicting immunotherapy response to glioblastoma (GBM) remains obscure. …"

Supplementary Material for: Investigating the value of umbilical artery eucapnic pH as a biomarker for adverse neonatal outcomes: A systematic review حسب figshare admin karger (2628495)

"…However, conventional potential of hydrogen (pH) and base deficit (BD) methods have limitations in neonates. …"

Turkish_native_goat_genotypes حسب Yalçın YAMAN (20209833)

"…</p><p dir="ltr">Nine heterogeneous machine-learning models—including penalised linear methods, gradient-boosting algorithms, and interaction-sensitive tree ensembles—were applied to examine genotype–phenotype relationships. …"

AI Influence in the Educational Environment حسب Lev Radman (21381269)

"…The CSV file contains Likert-scale and categorical responses, with a separate README describing each variable and coding scheme.</p><p dir="ltr"><b>Potential reuse</b><br>Researchers can replicate or extend technology-acceptance models in emerging-economy contexts, compare student versus professional cohorts, or conduct secondary analyses on AI self-efficacy and algorithmic trust.…"

SBDI Sativa curated 16S GTDB database حسب Daniel Lundin (11036598)

"…Subsequently, branch lengths for the tree are optimized based on the original alignment of 16S sequences using IQTREE [Nguyen et al. 2015] with a GTR+F+I+G4 model. …"

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

"…It can accurately reflect the emotional changes of the human body by applying graphical-based algorithms or models. EEG signals are nonlinear signals. …"

ImproBR Replication Package حسب Anonymus (18533633)

"…<br><br>**Import Errors:**<br>Make sure you're in the replication package directory:<br>```bash<br>cd ImproBR-Replication<br>python improbr_pipeline.py --help<br>```<br><br>## Research Results & Evaluation Data<br>### RQ1: Bug Report Improvement Evaluation (139 reports)<br>**Manual Evaluation Results:**<br>- [`RQ1-RQ2/RQ1/manual_evaluation/Author 1 Responses.csv`](<u>RQ1-RQ2/RQ1/manual_evaluation/Author 1 Responses.csv</u>) - First evaluator assessments<br>- [`RQ1-RQ2/RQ1/manual_evaluation/Author 2 Responses.csv`](<u>RQ1-RQ2/RQ1/manual_evaluation/Author 2 Responses.csv</u>) - Second evaluator assessments <br>- [`RQ1-RQ2/RQ1/manual_evaluation/Final Results.csv`](<u>RQ1-RQ2/RQ1/manual_evaluation/Final Results.csv</u>) - Consolidated evaluation results<br><br>**Inter-Rater Agreement (Cohen's Kappa):**<br>- [`RQ1-RQ2/RQ1/cohen's_cappa_coefficient_matrices/confusion_matrix_s2r_label.png`](<u>RQ1-RQ2/RQ1/cohen's_cappa_coefficient_matrices/confusion_matrix_s2r_label.png</u>) - Steps to Reproduce κ scores<br>- [`RQ1-RQ2/RQ1/cohen's_cappa_coefficient_matrices/confusion_matrix_ob_label.png`](<u>RQ1-RQ2/RQ1/cohen's_cappa_coefficient_matrices/confusion_matrix_ob_label.png</u>) - Observed Behavior κ scores<br>- [`RQ1-RQ2/RQ1/cohen's_cappa_coefficient_matrices/confusion_matrix_eb_label.png`](<u>RQ1-RQ2/RQ1/cohen's_cappa_coefficient_matrices/confusion_matrix_eb_label.png</u>) - Expected Behavior κ scores<br><br>**Algorithm Results:**<br>- [`RQ1-RQ2/RQ1/algorithm_results/improbr_outputs/`](<u>RQ1-RQ2/RQ1/algorithm_results/improbr_outputs/</u>) - ImproBR improved reports<br>- [`RQ1-RQ2/RQ1/algorithm_results/chatbr_outputs/`](<u>RQ1-RQ2/RQ1/algorithm_results/chatbr_outputs/</u>) - ChatBR baseline results<br>- [`RQ1-RQ2/RQ1/algorithm_results/bee_analysis/`](<u>RQ1-RQ2/RQ1/algorithm_results/bee_analysis/</u>) - BEE tool structural analysis<br><br>### RQ2: Comparative Analysis vs ChatBR (37 pairs)<br>**Similarity Score Results:**<br>- [`RQ1-RQ2/RQ2/algorithm_results/similarity_scores/overall_tfidf.csv`](<u>RQ1-RQ2/RQ2/algorithm_results/similarity_scores/overall_tfidf.csv</u>) - TF-IDF similarity scores<br>- [`RQ1-RQ2/RQ2/algorithm_results/similarity_scores/overall_word2vec.csv`](<u>RQ1-RQ2/RQ2/algorithm_results/similarity_scores/overall_word2vec.csv</u>) - Word2Vec similarity scores<br>- [`RQ1-RQ2/RQ2/algorithm_results/similarity_scores/exact_string_comparisons.json`](<u>RQ1-RQ2/RQ2/algorithm_results/similarity_scores/exact_string_comparisons.json</u>) - Complete TF-IDF comparison with scores for each comparison unit (full debugging)<br>- [`RQ1-RQ2/RQ2/algorithm_results/similarity_scores/word2vec_comparisons.json`](<u>RQ1-RQ2/RQ2/algorithm_results/similarity_scores/word2vec_comparisons.json</u>) - Complete Word2Vec comparison with scores for each comparison unit (full debugging)<br><br>**Algorithm Outputs:**<br>- [`RQ1-RQ2/RQ2/algorithm_results/ImproBR_outputs/`](<u>RQ1-RQ2/RQ2/algorithm_results/ImproBR_outputs/</u>) - ImproBR enhanced reports<br>- [`RQ1-RQ2/RQ2/algorithm_results/ChatBR_outputs/`](<u>RQ1-RQ2/RQ2/algorithm_results/ChatBR_outputs/</u>) - ChatBR baseline outputs<br>- [`RQ1-RQ2/RQ2/dataset/ground_truth/`](<u>RQ1-RQ2/RQ2/dataset/ground_truth/</u>) - High-quality reference reports<br>## Important Notes<br><br>1. …"

Figure 8 from Prostate Cancer Progression Modeling Provides Insight into Dynamic Molecular Changes Associated with Progressive Disease States حسب Runpu Chen (14942572)

"…Each tumor sample was color-coded by its <i>ERG</i> fusion status inferred by the <i>ERG</i> gene expression level. …"

Microscopic Detection and Quantification of Microplastic Particles in Environmental Water Samples حسب Derek Lam (11944213)

"…This approach offers a valuable complement to current monitoring strategies and supports broader efforts in environmental health protection. …"

Table 1_Associations of lung function impairment and biological aging with mortality and cardiovascular disease incidence: findings from UK biobank participants.docx حسب Jiali Chen (5696)

"…PhenoAgeAccel was calculated using algorithms based on clinical biomarkers, and frailty was evaluated according to five established criteria. …"

<b>A virtual tracer experiment to assess the temporal origin of root water uptake, evaporation, and </b><b>drainage</b> حسب Paolo Nasta (19710883)

"…</p><p dir="ltr"><a href="" target="_blank">Two open-source Matlab scripts are available in the zip-files. The PT.m Matlab code determines the drainage transit time based on the particle tracking algorithm, while the VTE.m Matlab code determines the drainage and RWU transit times and relative rainfall contributions to actual evaporation, actual transpiration, and drainage using isotope transport simulations in HYDRUS-1D</a>. …"

Data Sheet 1_MACRPO: Multi-agent cooperative recurrent policy optimization.pdf حسب Eshagh Kargar (20458304)

"…The results show superior performance against other algorithms. The code is available online at https://github.com/kargarisaac/macrpo.…"

Video 2_MACRPO: Multi-agent cooperative recurrent policy optimization.mp4 حسب Eshagh Kargar (20458304)

"…The results show superior performance against other algorithms. The code is available online at https://github.com/kargarisaac/macrpo.…"

Video 1_MACRPO: Multi-agent cooperative recurrent policy optimization.mp4 حسب Eshagh Kargar (20458304)

"…The results show superior performance against other algorithms. The code is available online at https://github.com/kargarisaac/macrpo.…"

Video 3_MACRPO: Multi-agent cooperative recurrent policy optimization.mp4 حسب Eshagh Kargar (20458304)

"…The results show superior performance against other algorithms. The code is available online at https://github.com/kargarisaac/macrpo.…"

Subtidal seagrass and blue carbon mapping at the regional scale: a cloud-native multi-temporal Earth Observation approach حسب Mar Roca (20435036)

"…We developed a satellite-based workflow to complement <i>in situ</i> seagrass monitoring efforts in the Balearic Islands (Western Mediterranean), reducing field expenses while covering regional spatial scales. …"

Survey Data on NSSI, Stress Response, Emotional Regulation Strategies and gender in Chinese Undergraduates حسب Yilin Ma (21154754)

"…</p><p dir="ltr"><b>Behavioral sub-questionnaire (AFASM1-12) :</b> Assesses NSSI with or without visible tissue damage</p><p dir="ltr"><b>Functional sub-questionnaire (BFASM1-19):</b> Measures three function types</p><ul><li><i>Automatic negative reinforcement: r</i>efers to engaging in NSSI to relieve or escape from an unpleasant internal state</li><li><i>Social positive reinforcement: </i>refers to engaging in NSSI to create a favorable state or to fulfill social needs</li><li><i>Emotional expression:</i>refers to engaging in NSSI as a means of expressing one’s emotional experiences</li></ul><p dir="ltr"><b>Scale:</b> 5-point Likert scale</p><h3><b>4.Gender</b></h3><ul><li>In this study, males were coded as “1” and females as “2”.</li></ul><p dir="ltr"><b>Usage Notes</b></p><ul><li></li><li>Each row represents one participant; columns include both item‑level and aggregated subscale scores.…"

Table 1_Artificial intelligence in nursing: an integrative review of clinical and operational impacts.pdf حسب Salwa Hassanein (20843468)

"…Key concerns include data privacy risks, algorithmic bias, and the potential erosion of clinical judgment due to overreliance on technology. …"

Table 2_Artificial intelligence in nursing: an integrative review of clinical and operational impacts.pdf حسب Salwa Hassanein (20843468)

"…Key concerns include data privacy risks, algorithmic bias, and the potential erosion of clinical judgment due to overreliance on technology. …"

Table 3_Artificial intelligence in nursing: an integrative review of clinical and operational impacts.pdf حسب Salwa Hassanein (20843468)

"…Key concerns include data privacy risks, algorithmic bias, and the potential erosion of clinical judgment due to overreliance on technology. …"