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. …”

Figure 1 from PD-1 Blockade Mitigates Surgery-Induced Immunosuppression and Increases the Efficacy of Photodynamic Therapy for Pleural Mesothelioma by Gwendolyn M. Cramer (16964052)

“…<b>D,</b> In the AB12 mouse mesothelioma TI model, IL-1Ra protein levels are higher at 4 hours after TI (<i>n</i> = 7) compared with samples of untreated TC (<i>n</i> = 6, Mann–Whitney test <i>P</i> = 0.001).…”

<b>Optimizing Task Scheduling and Containers in Cloud Data Centers</b> by Arash GhorbanniaDelavar (22563696)

“…Overall, TPMCD provides a scalable and cost-efficient framework that enhances both <b>performance and sustainability</b> in cloud data centers.</p><p dir="ltr"><code>Original article DOI: https://doi.org/10.1016/j.jnca.2025.104132</code></p>…”

Supplementary file 1_Predicting first-time anaphylaxis in the elderly using stacked machine learning and population registers.docx by Toni Mora (8145624)

“…Key predictors included healthcare utilisation patterns, age, socioeconomic proxy (copayment level), and specific diagnostic codes related to allergic conditions.…”

CSPP instance by peixiang wang (19499344)

“…</li><li>Containers are randomly assigned to different attribute groups (<code>attr_group_no</code>).</li></ul></li><li><b>Yard Location Assignment</b>:</li><li><ul><li>The script systematically assigns each container a specific location in the simulated yard, including <code>area_no</code>, <code>area_bay</code>, <code>area_row</code>, and <code>area_level</code>.…”

Supplementary Data: Biodiversity and Energy System Planning - Queensland 2025 by 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.…”

Supplementary file 1_A real-world disproportionality analysis of FDA adverse event reporting system (FAERS) events for lecanemab.docx by Linlin Yan (4480570)

“…Using the Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-item Gamma Poisson Shrinker (MGPS) algorithms, we conducted a comprehensive analysis of lecanemab-related AEs, restricting the analysis to AEs with the role code of primary suspect (PS).…”

Data Sheet 1_Forestry climate adaptation with HarvesterSeasons service—a gradient boosting model to forecast soil water index SWI from a comprehensive set of predictors in Destinat... by Mikko Strahlendorff (20458865)

“…<p>Soil wetness forecasts on a local level are needed to ensure sustainable forestry operations during summer when the soil is neither frozen nor covered with snow. …”

Machine Learning-Ready Dataset for Cytotoxicity Prediction of Metal Oxide Nanoparticles by Soham Savarkar (21811825)

“…Core Material Properties:</b></p><p dir="ltr">Four elemental-level descriptors were added to enrich prediction with periodic trends:</p><p dir="ltr">Atomic weight, group number, period number, and electronegativity difference of elements in the nanoparticle core.…”

<b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043) by Erola Fenollosa (20977421)

“…Those leaf positions corresponded to the youngest fully developed leaf, found at the ramet tip (Position 1), and the last leaf found on the ramet (Position 2). From each ramet type and individual, the two fully developed leaves from each position (corresponding to the two opposite leaves of the verticil) were collected. …”

<b>Rethinking neighbourhood boundaries for urban planning: A data-driven framework for perception-based delineation</b> by Shubham Pawar (22471285)

“…</p><p dir="ltr"><b>Reference:</b> <code>cluster_perceptions.py</code> script logic</p><p dir="ltr">Stages:</p><ul><li>(a) Data input</li><li>(b) K-nearest neighbours spatial weights matrix</li><li>(c) Initial agglomerative clustering</li><li>(d) Merging small clusters</li><li>(e-f) Iterative splitting of largest clusters</li></ul><h4>Figure 7: Predicted Urban Perception Scores</h4><p dir="ltr">ET cell-level perception scores across the study area.…”

Integrating urinary metabolomics and clinical datasets for multi-cancer detection by Dongyong Lee (18786694)

“…</p><p dir="ltr">- `group_code`: short group code </p><p dir="ltr"> - e.g., `Normal`, `HTN`, `DM`, `HTN+DM`, `CRC`, `LungCA`, `PancreasCA`.…”

archive.zip by Tasneem Fatima (21976946)

“…The dataset extracted from the archive consists of a large number of labeled images of wheat grains, organized in directories such as <code>wheat_for_cnn</code>, with filenames reflecting numerical categories (e.g., <code>10_1.jpg</code>, <code>100_5.jpg</code>, <code>200_0003.jpg</code>). …”

Performance evaluation of SpaVGN on melanoma ST dataset. by Haiyan Wang (25821)

“…Color-coded regions correspond to different tissue domains. …”

Monotone Cubic B-Splines with a Neural-Network Generator by Lijun Wang (176511)

“…We evaluate our method against several existing methods, some of which do not use the monotonicity constraint, on some monotone curves with varying noise levels. We demonstrate that our method outperforms the other methods, especially in high-noise scenarios. …”

Massive Mixed Models in Julia by Phillip M. Alday (2814652)

“…<p dir="ltr">Traditional approaches to mixed effects models using generalized least squares or expectation-maximization approaches struggle to scale to datasets with many thousands of observations and hundreds of levels of a single blocking variable. Special casing of nesting or crossing of random effects is required to achieve acceptable computational performance, but this special casing often makes it very difficult to handle less-than-idealized cases, such partial crossing or multiple levels of nesting. …”

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. …”

Supporting data for "Fracture and Non-linear Response of Biopolymer Network with Dynamic Cross-linkers" by Bingxian Tang (9151802)

“…It details the input parameters, such as line density and crosslink number, as well as the algorithms employed for filament arrangement and crosslink determination. …”

Table 1_Correlation of triglyceride-glucose index with the incidence and prognosis of hyperglycemic crises in critically ill patients with diabetes mellitus: a machine-learning-bas... by Mingchen Xie (4325692)

“…Through multivariate logistic regression, TyG was pinpointed as a separate risk element for both in-hospital (OR 1.956) and ICU death (OR 2.260), linked to extended hospital stays. …”

Climate anomalies due to Cerrado native vegetation loss by Argemiro Leite-Filho (10283801)

“…</li></ul><p dir="ltr"><b>Code/software</b></p><p dir="ltr">To analyze the CSV files in your dataset, you can use various software options, such as R and Microsoft Excel. …”