Description of clusters in Differential Altas. حسب Litian Han (17350823)

Statistical description of datasets. حسب Varun Malik (21212874)

Workflow summary: GRN motif, cell signaling model, and inference framework. حسب Michael Alexander Ramirez Sierra (20209354)

Hierarchical arrangement of the hermaphrodite connectome with neurons clustered by community (not illustrated: community 1, containing many motor neurons and body wall muscles; com... حسب Scott W. Emmons (8082275)

3D Deformable cell based model. حسب Roland M. Dries (6620132)

"…(A) Description of the properties of the simulated cell. …"

Overall model performance. حسب Theogene Kubahoniyesu (20391184)

Overall model performance. حسب Theogene Kubahoniyesu (20391184)

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

"…While most G2Is are believed to be inactive in vivo in the absence of maturase proteins, we show that Arq.I2 self-splices in Escherichia coli cells. Our results demonstrate that highly active variants of large and complex ribozymes can be designed de novo with relative ease using existing inverse folding algorithms, paving the way for the design of bespoke ribozymes derived from G2Is for the development of biotechnological tools.…"

Workflow to extract and define myocardial motion and deformation patterns during early heart morphogenesis. حسب Morena Raiola (22439390)

"…The computational workflow comprises four main components: 1) Estimating Individual Live Image Motion (blue shapes): Following image preprocessing, we extracted the underlying motion using a non-rigid registration algorithm, resulting in a set of Transformation. The accuracy of motion detection was evaluated by comparing tracked cells to computed tracking using a stepwise and sequential interpolation. …"

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>…"

Polyanion sodium cathode materials dataset حسب Martin Hoffmann Petersen (13626778)

"…For example, Na_2.56TM_1.72(SO₄)₃ structures are split into single transition metal ion types<i> Na2M2SO4_alluadite_single_total.xyz </i>and multiple transition metal ion types <i>Na2M2SO4_alluadite_multiple_optimization.xyz. …"

Supplementary Data: Biodiversity and Energy System Planning - Queensland 2025 حسب Andrew Rogers (17623239)

"…</li></ul><h3>Analysis Scripts</h3><p dir="ltr">Complete set of R scripts for reproducing all analyses:</p><ul><li><b>percent cost increase_line plot.R</b>: Creates visualizations of energy cost impacts under different conservation scenarios</li><li><b>Zonation curves.R</b>: Generates conservation performance curves and coverage statistics</li><li><b>NPV_bar_plot.R</b>: Produces economic analysis plots with Net Present Value breakdowns</li><li><b>domestic_export_map_iterations.R</b>: Creates spatial maps of renewable energy infrastructure for domestic and export scenarios</li></ul><h2>Technical Specifications</h2><h3>Data Formats</h3><ul><li><b>Spatial Data</b>: ESRI Geodatabase (.gdb), Shapefile (.shp), GeoTIFF (.tif)</li><li><b>Tabular Data</b>: CSV, Microsoft Excel (.xlsx, .xls)</li><li><b>Analysis Code</b>: R scripts (.R)</li></ul><h3>Software Requirements</h3><ul><li><b>R</b> (≥4.0.0) with packages: sf, dplyr, ggplot2, readr, readxl, tidyr, furrr, ozmaps, ggpattern</li><li><b>ESRI ArcGIS</b> or <b>QGIS</b> for geodatabase access and spatial analysis</li><li><b>Zonation</b> conservation planning software (for methodology understanding)</li></ul><h3>Hardware Recommendations</h3><ul><li><b>RAM</b>: 16GB minimum (32GB recommended for full spatial analysis)</li><li><b>Storage</b>: 15GB free space for data extraction and processing</li><li><b>CPU</b>: Multi-core processor recommended for parallel processing scripts</li></ul><h2>Detailed Description of the VRE Siting and Cost-Minimization Model</h2><p><br></p><p dir="ltr">This section provides an in-depth description of the Variable Renewable Energy (VRE) siting model, including the software, the core algorithm, and the optimisation process used to determine the least-cost, spatially constrained development trajectory for VRE infrastructure in Queensland, Australia.…"