MOMA compared to MFA-derived estimates, carbon yield efficiencies and CBA co-factor profile comparison across unconstrained, manually curated and experimentally constrained solutio... by Laura de Arroyo Garcia (9226096)

“…MFA ranges were extracted from a pre-existing dataset (Long et al., 2019), using a Python algorithm to select the minimal and maximal flux ranges.…”

Map Matching on Low Sampling Rate Trajectories Through Deep Inverse Reinforcement Learning and Multi Intention Modeling by Reza Safarzadeh (18072472)

“…</p><p dir="ltr">This repository contains the following Python codes:</p><p><br></p><p dir="ltr"><br></p><ul><li>`environmnet.py`: Contains the implementation of the environment used for IRL. …”

Mechanomics Code - JVT by Carlo Vittorio Cannistraci (5854046)

“…At the beginning of the code, there is a help section that explains how to use it.<br></li><li>Python (written by Syed Shafat Ali and tested by Yan Ge): analogous functions of the MATLAB folder. …”

Landscape17 by Vlad Carare (22092515)

“…</p><h3>Density functional theory calculations</h3><p dir="ltr">The reference potential energy landscapes were computed using density functional theory with the ωB97x hybrid-energy exchange correlation functional and a 6-31G(d) basis set within Psi4. …”

Code and data for evaluating oil spill amount from text-form incident information by Yiming Liu (18823387)

“…These files include:</p><ul><li><b>"func_set_general.ipynb"</b> and <b>"func_set_ra_eval.ipynb"</b>:</li><li><ul><li>Include custom functions that are automatically called and used in the three primary notebooks.…”

Spatiotemporal Soil Erosion Dataset for the Yarlung Tsangpo River Basin (1990–2100) by peng xin (21382394)

“…The corrected bias functions were then applied to adjust the years (2020–2100) of daily rainfall data using the "ibicus" package, an open-source Python tool for bias adjustment and climate model evaluation. …”

COI reference sequences from BOLD DB by John Sundh (12853901)

“…Sorry for the inconvenience.</b></p><h4><b>Methods</b></h4><p dir="ltr">The code used to generate this dataset consists of a snakemake workflow wrapped into a python package that can be installed with <a href="https://docs.conda.io/en/latest/miniconda.html" target="_blank">conda </a>(`conda install -c bioconda coidb`). …”

Code by Baoqiang Chen (21099509)

“…</p><p><br></p><p dir="ltr"><b>RNA functional analysis</b></p><p dir="ltr">Gene Ontology (GO) analysis was performed using the Metascape website, and gene set enrichment analysis (GSEA) was conducted using the GSEABase and enrichplot packages in R. …”

Core data by Baoqiang Chen (21099509)

“…</p><p><br></p><p dir="ltr"><b>RNA functional analysis</b></p><p dir="ltr">Gene Ontology (GO) analysis was performed using the Metascape website, and gene set enrichment analysis (GSEA) was conducted using the GSEABase and enrichplot packages in R. …”

Decoding fairness motivations - repository by Sebastian Speer (6489207)

“…</div><div>To obtain neural activation patterns for multivariate analysis individual time series were modeled using a double γ hemodynamic response function in a single trial GLM design using FSL’s FEAT. …”

The software structure. by Moritz Hoffmann (6411821)

“…<p><b>(a)</b> Python user interface: Provides a Python binding to the “C++ user interface” with some additional convenience functionality. …”

CSPP instance by peixiang wang (19499344)

“…</b></p><p dir="ltr">Its primary function is to create structured datasets that simulate container terminal operations, which can then be used for developing, testing, and benchmarking optimization algorithms (e.g., for yard stacking strategies, vessel stowage planning).…”

Barro Colorado Island 50-ha plot aerial photogrammetry orthomosaics and digital surface models for 2018-2023: Globally and locally aligned time series. by Vicente Vasquez (13550731)

“…We first computed a grid of co-registration point using arosics.COREG_LOCAL function and used the highest reliability point position to globally align to the closest date orthomosaics. …”

VinaLigGen: a method to generate LigPlots and retrieval of hydrogen and hydrophobic interactions from protein-ligand complexes by Raghvendra Agrawal (17135479)

Skeletal_ Muscle_MRI_Registration by Lucia Fontana (9435020)

“…<p><b>MSKregPy</b> is a collection of algorithms and GUI for muscolo-skeletal image processing and registration.…”

A paired dataset of multi-modal MRI at 3 Tesla and 7 Tesla with manual hippocampal subfield segmentations on 7T T2-weighted images by Shuyu Li (18401358)

“…This dataset is designed to support the development and evaluation of both 3T-to-7T MR image synthesis models and automated hippocampal segmentation algorithms on 3T images. We assessed the image quality using MRIQC. …”

An Ecological Benchmark of Photo Editing Software: A Comparative Analysis of Local vs. Cloud Workflows by Pierre-Alexis DELAROCHE (22092572)

“…Performance Profiling Algorithms Energy Measurement Methodology # Pseudo-algorithmic representation of measurement protocol def capture_energy_metrics(workflow_type: WorkflowEnum, asset_vector: List[PhotoAsset]) -> EnergyProfile: baseline_power = sample_idle_power_draw(duration=30) with PowerMonitoringContext() as pmc: start_timestamp = rdtsc() # Read time-stamp counter if workflow_type == WorkflowEnum.LOCAL: result = execute_local_pipeline(asset_vector) elif workflow_type == WorkflowEnum.CLOUD: result = execute_cloud_pipeline(asset_vector) end_timestamp = rdtsc() energy_profile = EnergyProfile( duration=cycles_to_seconds(end_timestamp - start_timestamp), peak_power=pmc.get_peak_consumption(), average_power=pmc.get_mean_consumption(), total_energy=integrate_power_curve(pmc.get_power_trace()) ) return energy_profile Statistical Analysis Framework Our analytical pipeline employs advanced statistical methodologies including: Variance Decomposition: ANOVA with nested factors for hardware configuration effects Regression Analysis: Generalized Linear Models (GLM) with log-link functions for energy modeling Temporal Analysis: Fourier transform-based frequency domain analysis of power consumption patterns Cluster Analysis: K-means clustering with Euclidean distance metrics for workflow classification Data Validation and Quality Assurance Measurement Uncertainty Quantification All energy measurements incorporate systematic and random error propagation analysis: Instrument Precision: ±0.1W for CPU power, ±0.5W for GPU power Temporal Resolution: 1ms sampling with Nyquist frequency considerations Calibration Protocol: NIST-traceable power standards with periodic recalibration Environmental Controls: Temperature-compensated measurements in climate-controlled facility Outlier Detection Algorithms Statistical outliers are identified using the Interquartile Range (IQR) method with Tukey's fence criteria (Q₁ - 1.5×IQR, Q₃ + 1.5×IQR). …”