Table_5_An Intratumor Heterogeneity-Related Signature for Predicting Prognosis, Immune Landscape, and Chemotherapy Response in Colon Adenocarcinoma.csv by Cong Liu (66219)

Table_4_An Intratumor Heterogeneity-Related Signature for Predicting Prognosis, Immune Landscape, and Chemotherapy Response in Colon Adenocarcinoma.csv by Cong Liu (66219)

Table_3_An Intratumor Heterogeneity-Related Signature for Predicting Prognosis, Immune Landscape, and Chemotherapy Response in Colon Adenocarcinoma.csv by Cong Liu (66219)

Image_2_An Intratumor Heterogeneity-Related Signature for Predicting Prognosis, Immune Landscape, and Chemotherapy Response in Colon Adenocarcinoma.tif by Cong Liu (66219)

Table_1_An Intratumor Heterogeneity-Related Signature for Predicting Prognosis, Immune Landscape, and Chemotherapy Response in Colon Adenocarcinoma.csv by Cong Liu (66219)

A portfolio selection model based on the knapsack problem under uncertainty by Fereshteh Vaezi (6655028)

“…<div><p>One of the primary concerns in investment planning is to determine the number of shares for asset with relatively high net value of share such as Berkshire Hathaway on Stock market. …”

Data_Sheet_2_Computational Neural Modeling of Auditory Cortical Receptive Fields.pdf by Jordan D. Chambers (6732224)

Data_Sheet_1_Computational Neural Modeling of Auditory Cortical Receptive Fields.PDF by Jordan D. Chambers (6732224)

Data_Sheet_3_Computational Neural Modeling of Auditory Cortical Receptive Fields.PDF by Jordan D. Chambers (6732224)

Predicting the Shear Viscosity of Carbonated Aqueous Amine Solutions and Their Blends by Using an Artificial Neural Network Model by Ali Aminian (9580734)

“…A total of 1682 amine + CO₂ + water viscosity data sets for primary, secondary, and tertiary amines and 220 data points for further accuracy examinations were used. …”

The pseudocode outlines the proposed method for scoring the similarity between two protein sequences. by Belén Otero-Carrasco (21262360)

A construction method of a multidimensional and multilingual association network for earth surface system science data by Qinjun Qiu (13306416)

“…The method quantitatively computes one-dimensional and multidimensional similarities using five primary indicators of multilingual data, enabling semantic interconnection and facilitating knowledge discovery within open scientific data related to the Earth surface system. …”

Data_Sheet_1_Measuring the impact of monoclonal antibody therapies.pdf by Ka Keat Lim (8915009)

Data_Sheet_1_Measuring the impact of monoclonal antibody therapies.pdf by Ka Keat Lim (8915009)

Data_Sheet_1_Early Prediction of Sepsis in the ICU Using Machine Learning: A Systematic Review.PDF by Michael Moor (10887888)

Data_Sheet_1_A comprehensive analysis of genes associated with hypoxia and cuproptosis in pulmonary arterial hypertension using machine learning methods and immune infiltration ana... by Zuguang Chen (19743121)

Image1_Adverse events related to neuromuscular blocking agents: a disproportionality analysis of the FDA adverse event reporting system.pdf by Liangxia Li (17664248)

“…A positive signal was generated when both algorithms show an association between the target drug and the AE.…”

Table1_Adverse events related to neuromuscular blocking agents: a disproportionality analysis of the FDA adverse event reporting system.xlsx by Liangxia Li (17664248)

“…A positive signal was generated when both algorithms show an association between the target drug and the AE.…”

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

“…</p><p dir="ltr"><b>Quality Assurance</b>: Comprehensive technical validation demonstrates the dataset's integrity, sensitivity to rainfall impacts, and capability to reveal complex traffic-weather interaction patterns.</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>…”

Table_1_Early Prediction of Sepsis in the ICU Using Machine Learning: A Systematic Review.pdf by Michael Moor (10887888)