Data Sheet 1_Integrated diagnostics and time series sensitivity assessment for growth monitoring of a medicinal plant (Glycyrrhiza uralensis Fisch.) based on unmanned aerial vehicl... حسب Ao Zhang (372387)

"…Background<p>Water and nitrogen are essential elements prone to deficiency during plant growth. Current water–fertilizer monitoring technologies are unable to meet the demands of large-scale Glycyrrhiza uralensis cultivation. …"

Data Sheet 2_Integrated diagnostics and time series sensitivity assessment for growth monitoring of a medicinal plant (Glycyrrhiza uralensis Fisch.) based on unmanned aerial vehicl... حسب Ao Zhang (372387)

"…Background<p>Water and nitrogen are essential elements prone to deficiency during plant growth. Current water–fertilizer monitoring technologies are unable to meet the demands of large-scale Glycyrrhiza uralensis cultivation. …"

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.…"

Supplementary information files for "Explainable machine learning models for predicting the ultimate bending capacity of slotted perforated cold-formed steel beams under distortion... حسب 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. …"

Confusion_Matrix_Data.zip حسب Mohammad Farhad Bulbul (21003494)

"…<p dir="ltr">This research paper proposes a novel approach for human activity recognition using depth video data, focusing on improving accuracy by effectively capturing motion information and utilizing a robust classification method. Here's a breakdown of the key elements:</p><p dir="ltr"><b>. …"

Supporting files for thesis "Deep-learning-based Morphological Modelling: Case Study in Soft Robot Control, Shape Sensing and Deformation" حسب 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. …"

Electronic supplement to "Computational De Novo Design of Group II Introns Yields Highly Active Ribozymes" حسب Deni Szokoli (21503496)

"…Here we use the RNA inverse folding algorithm aRNAque to design G2Is de novo, yielding three novel self-splicing ribozymes with unusually stable structures. …"

<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. …"

Gaze Inputs for Targeting: The Eyes Have It, Not With a Cursor حسب Ajoy S. Fernandes (22293773)

"…If the participant looked out of the grid boundary, on button press, we chose to select the last targeted element, but no other algorithms to enhance performance were employed. …"

IUTF Dataset(Enhanced): Enabling Cross-Border Resource for Analysing the Impact of Rainfall on Urban Transportation Systems حسب Xuhui Lin (19505503)

"…</p><h2>Data Structure</h2><p dir="ltr">The dataset is organized into four primary components:</p><ol><li><b>Road Network Data</b>: Topological representations including spatial geometry, functional classification, and connectivity information</li><li><b>Traffic Sensor Data</b>: Sensor metadata, locations, and measurements at both 5-minute and hourly resolutions</li><li><b>Precipitation Data</b>: Hourly meteorological information with spatial grid cell metadata</li><li><b>Derived Analytical Matrices</b>: Pre-computed structures for advanced spatial-temporal modelling and network analyses</li></ol><h2>File Formats</h2><ul><li><b>Tabular Data</b>: Apache Parquet format for optimal compression and fast query performance</li><li><b>Numerical Matrices</b>: NumPy NPZ format for efficient scientific computing</li><li><b>Total Size</b>: Approximately 2 GB uncompressed</li></ul><h2>Applications</h2><p dir="ltr">The IUTF dataset enables diverse analytical applications including:</p><ul><li><b>Traffic Flow Prediction</b>: Developing weather-aware traffic forecasting models</li><li><b>Infrastructure Planning</b>: Identifying vulnerable network components and prioritizing investments</li><li><b>Resilience Assessment</b>: Quantifying system recovery curves, robustness metrics, and adaptive capacity</li><li><b>Climate Adaptation</b>: Supporting evidence-based transportation planning under changing precipitation patterns</li><li><b>Emergency Management</b>: Improving response strategies for weather-related traffic disruptions</li></ul><h2>Methodology</h2><p dir="ltr">The dataset creation involved three main stages:</p><ol><li><b>Data Collection</b>: Sourcing traffic data from UTD19, road networks from OpenStreetMap, and precipitation data from ERA5 reanalysis</li><li><b>Spatio-Temporal Harmonization</b>: Comprehensive integration using novel algorithms for spatial alignment and temporal synchronization</li><li><b>Quality Assurance</b>: Rigorous validation and technical verification across all cities and data components</li></ol><h2>Code Availability</h2><p dir="ltr">Processing code is available at: https://github.com/viviRG2024/IUTDF_processing</p>…"

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. …"

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 حسب 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 حسب 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 حسب 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.…"

Methodological overview. حسب Jinming Xiao (12517096)

"…<p>(A) The source reconstruction of TMS-evoked potential of each subject was performed using dSPM method based on MNE software library. The time series of cortical activity were extracted through Schaefer 200 parcellation atlas. …"

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. …"

<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.…"