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Mathematical datasets, statistical benchmarks, probability, optimization, operations research
2,459 datasets
Experimental data details the design and testing of gemcitabine-based galactoside prodrugs for targeting senescent cells. The dataset includes results for the lead compound Gal-dMor-Gem, which achieved a senolytic index of 16.1β56.7 across six senescent cell models, representing a 2.8- to 3.7-fold improvement over a control. It was compiled by Jie Liu and published in 2026.
A 2025 working paper from the Reality Drift series introduces the concept of Filter Fatigue as a form of cognitive exhaustion from persistent choice overload in digital environments. Authored by the Reality Drift Archive, this conceptual framework synthesizes themes from cultural and media analysis to examine continuous filtering as a structural condition of modern digital life. The paper is intended for discussion and is not an empirical or diagnostic account.
Ulster University, via OpenDataNI, provides historical shoreline data for the entire Northern Ireland coastline. The dataset was created by analyzing Ordnance Survey maps and aerial imagery from the early 1800s onward, using the Digital Shoreline Analysis System (DSAS) to calculate rates of change. It includes statistics like Net Shoreline Movement and Linear Regression Rate, measured at 25-meter intervals.
Ulster University and OpenDataNI provide a historical shoreline analysis for the entire Northern Ireland coastline. The dataset was created by analyzing Ordnance Survey maps and aerial imagery from the early 1800s onward, using the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics at 25-meter intervals. The data, last updated in March 2026, includes metrics like Net Shoreline Movement and Weighted Linear Regression Rate to visualize coastal change over annual to decadal periods.
Historical shoreline positions for the Northern Ireland coastline, analyzed from Ordnance Survey maps and aerial imagery dating back to the early 1800s. Ulster University processed the data using the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics at 25-meter intervals. The dataset includes metrics like Linear Regression Rate (LRR) and Net Shoreline Movement (NSM) to visualize coastal change.
Historical shoreline analysis for the entire Northern Ireland coastline, based on Ordnance Survey maps and aerial imagery from the early 1800s onward. Ulster University processed the data using the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics at 25-meter intervals. The dataset includes metrics like End Point Rate (EPR) and Linear Regression Rate (LRR) to visualize and assess coastal change.
Historical shoreline analysis for the entire Northern Ireland coastline, with rate-of-change statistics calculated at 25-meter intervals. Ulster University produced this dataset using Ordnance Survey maps and aerial imagery, analyzing changes from the early 1800s onward. The data was processed using the Digital Shoreline Analysis System (DSAS) to calculate metrics like Net Shoreline Movement and Linear Regression Rate.
Historical shoreline analysis for the entire Northern Ireland coastline, tracking annual to decadal changes since the early 1800s. Ulster University produced this digital asset using Ordnance Survey maps and aerial imagery, processed with the Digital Shoreline Analysis System (DSAS). The data provides rate-of-change statistics at 25-meter intervals, visualizing coastal retreat and accretion.
Historical shoreline positions for the Northern Ireland coastline, derived from Ordnance Survey maps and aerial imagery. Ulster University analyzed the data using the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics at 25-meter intervals. The dataset visualizes shoreline movement and assesses historical change rates for coastal management.
Historical shoreline positions for the entire Northern Ireland coastline, analyzed at 25-meter intervals to calculate rates of change since the early 1800s. Ulster University produced this dataset using the Digital Shoreline Analysis System (DSAS) on Ordnance Survey maps and aerial imagery. The data provides five key rate-of-change statistics, including Net Shoreline Movement and Linear Regression Rate, to visualize coastal evolution.
2002β2024 annual time-series data for 3,890 global lakes, supporting research on environmental changes and extreme weather responses. The dataset includes covariates like water temperature, precipitation, GDP, and heatwave characteristics, alongside chlorophyll-a trends and methane simulation results. It was authored by Zhigang Cao and published on figshare in April 2026.
Reference measurement data from the Micro-Imaging Dust Analysis System (MIDAS) flight spare unit, collected on the ground in 2009. The data was acquired by NASA to improve the accuracy of images from the ROSETTA Orbiter's instrument and develop measurement procedures for its mission to comet 67P/Churyumov-Gerasimenko. This dataset contains 3D images and statistical parameters of pristine cometary particles.
GLM-5.1 generated this distilled reasoning dataset from 1.2 million prompts in the OpenThoughts3 collection. The dataset covers three domains, with the Science split containing 56,974 distilled responses from 100,000 original prompts. Author Kassadin88 last updated the dataset on Hugging Face in April 2026.
2013 reference measurement data from the Micro-Imaging Dust Analysis System (MIDAS) flight spare unit. The dataset was acquired on ground to improve the accuracy of images gathered by the actual flight unit on the ROSETTA Orbiter, which analyzed pristine particles from comet 67P/Churyumov-Gerasimenko. It was created by the National Aeronautics and Space Administration.
Micro-Imaging Dust Analysis System (MIDAS) ground reference data was collected by NASA to calibrate the instrument aboard the ROSETTA Orbiter. The flight spare unit was used to improve the accuracy of 3D images of pristine particles from comet 67P/Churyumov-Gerasimenko. This specific dataset contains reference measurement data from 2010.
The Micro-Imaging Dust Analysis System (MIDAS) instrument on the ROSETTA Orbiter captured 3D images of pristine cometary particles near comet 67P/Churyumov-Gerasimenko. This dataset contains reference measurement data acquired with the flight spare unit on ground in 2015, used to improve the accuracy of images from the flight unit. The data was collected by NASA.
MIDAS instrument reference data from 2014 was used to improve the accuracy of 3D images of pristine cometary particles collected by the ROSETTA Orbiter at comet 67P/Churyumov-Gerasimenko. The National Aeronautics and Space Administration gathered this test data using a flight spare unit on ground to develop measurement procedures for the actual flight mission.
AIMindTeams created a high-fidelity synthetic dataset representing a Tier-3 End Unit operating under continuous stress and operational surges. The 5,000-hour sample is engineered for zero-drift mathematical precision and models high-stakes stochastic chaos in mission-critical supply chains. This dataset was last updated on May 8, 2026.
Statistical information on the receipt of requests for public information to the Main Directorate of the State Geocadastre in Sumy region. The data originates from the States site of Ukraine and was last updated on 2026-05-04. It likely contains tabular records of requests and their handling.
A systematic review and network meta-analysis of 209 randomized controlled trials involving 3,773 participants with mild cognitive impairment or dementia. The study compares dance interventions to other exercise modalities across outcomes like global cognition, working memory, and physical performance. It was authored by Ye Zhao and published in 2026.