Find research datasets worth reusing

opencc-by-4.0Jul 2022View details →

Supplementary data - "Learning Reduced Models for Large-Scale Agent-Based Systems"

This repository contains supplementary data on my PhD thesis "Learning Reduced Models for Large-Scale Agent-Based Systems". Chapters 1-3, 7 and A do not have supplementary data. Chapter 4 <ul> <li>Large_deviation_example.zip contains the trajectory for Figure 4.8.</li> <li>mean_exit_time* contains the raw data to compute the mean exit time and standard deviation for the ABM process (JP) and SDE process (CLE). It contains additionally a precomputed mean and standard deviation as well as the corresponding numbers of agents.</li> <li>transition_matrix* contain the computed box discretizations as MATLAB and Numpy files as used for Figures 4.2-4.4, 4.6 and Tables 4.1 and 4.2.</li> </ul> Chapter 5 <ul> <li>CVM_2021-07-09-15-53_training_data.npz contains the training data for Figure 5.7 a and b.</li> <li>CVM_2021-09-29-07-13_distribution.npz contains the raw data for Figure 5.7 c.</li> <li>The remaining data for Chapter 5 can be found in the related dataset <a href="https://doi.org/10.5281/zenodo.4522119">doi.org/10.5281/zenodo.4522119</a>.</li> </ul> Chapter 6 <ul> <li>CVM_pareto_estimate contains trajectory data required for Figure 6.6 b to estimate points in the Pareto Front using the civil violence model. </li> <li>CVM_training_data contains the training data to construct the surrogate model. Each data set consists of CVM_*_cops_train.npz as training set, CVM_*_cops_trajectory.npz as sample trajectory and CVM_*_cops.pkl to compute the training data.</li> <li>CVM_covering_iterations_8.mat Pareto set covering after 8 iterations for the civil violence model. Required for Figure 6.6 a.</li> <li>CVM_pareto_set+front.npz is required for Figure 6.6 b. </li> <li>CVM_surrogate_model.mat contains the surrogate model for the civil violence model</li> <li>Expl_iterations_* contains Pareto set coverings after 8 and 12 iterations for Example 6.1.4 and Figure 6.1.</li> <li>VM_covering_iterations_12.mat contains the Pareto set covering depicted in Figure 6.4 a.</li> <li>VM_ODE_covering_iterations_12_subset_front.mat contains the Pareto set covering depicted in Figure 6.5 and 6.5 c.</li> <li>VM_ODE_covering_iterations_12_subset.mat contains the Pareto set covering depicted in Figure 6.5 and 6.5 d.</li> <li>VM_ODE_covering_iterations_12.mat contains the Pareto set covering depicted in Figure 6.4 b.</li> <li>VM_surrogate_model.mat contains the surrogate model for the extended voter model.</li> <li>VM_test_points_non_pareto.npz contains Non-Pareto points in Figure 6.5 and 6.5 d.</li> <li>VM_test_points_pareto.npz contains Pareto points in Figure 6.5 and 6.5 c.</li> </ul>

opencc-zeroJul 2022View details →

Allometric scaling of a superposition eye optimises sensitivity and acuity in large and small hawkmoths

Animals vary widely in body size within and across species. This has consequences for the function of organs and body parts in both large and small individuals. How these scale, in relation to body size, reveals evolutionary investment strategies, often resulting in trade-offs between functions. Eyes exemplify these trade-offs, as they are limited by their absolute size in two key performance features: sensitivity and spatial acuity. Due to their size polymorphism, insect compound eyes are ideal models for studying the allometric scaling of eye performance. Previous work on apposition compound eyes revealed that allometric scaling led to poorer spatial resolution and visual sensitivity in small individuals, across a range of insect species. Here, we used X-ray microtomography to investigate allometric scaling in superposition compound eyes – the second most common eye type in insects – for the first time. Our results reveal a novel strategy to cope with the trade-off between sensitivity and spatial acuity, as we show that the eyes of the hummingbird hawkmoth retain an optimal balance between these performance measures across all body sizes.

opencc-by-4.0Jul 2022View details →

Transmission and Distribution Substation Energy Management Considering Large-Scale Energy Storage, Demand Side Management and Security-Constrained Unit Commitment

Data used in "Transmission and Distribution Substation Energy Management Considering Large-Scale Energy Storage, Demand Side Management and Security-Constrained Unit Commitment".

opencc-by-4.0Jun 2022View details →

ReSPack: A Large-Scale Rectilinear Steiner Tree Packing Benchmark for Wire Routing

Combinatorial optimization (CO) has been studied as a useful tool for modeling industrial problems, but it still remains a challenge in complex domains because of the NP-hardness. With recent advances in machine learning, the field of CO is shifting to the study of neural combinatorial optimization using a large amount of data, showing promising results in some CO problems. Rectilinear Steiner Tree Packing Problem (RSTPP) is a well-known CO problem and is widely used in modeling wiring problem among components in a printed circuit board and an integrated circuit design. Despite the importance for a design automation, the lack of availab le data has restricted to fully leverage machine learning approaches. In this paper, we present ReSPack, a large-scale synthetic RSTPP dataset and a benchmark for wire routing. ReSPack includes a source code for generating RSTPP problems of various types with different sizes, data instances generated for the benchmark testing, and implementations of several baseline algorithms. We believe that ReSPack can contribute to solving circuit design problems as well as the development of CO with machine learning.

opencc-by-nc-nd-1.0Aug 2022View details →

Assessing Vaccine-Related Content for Journalistic Quality: A large-scale dataset and article repository

This dataset was produced through a collaboration with the NSF-funded <a href="https://artt.cs.washington.edu/">ARTT project</a> (led by Hacks/Hackers) and <a href="https://overtone.ai/">Overtone</a>. It consists of 1,000 vaccine-related articles, pulled from a wide variety of news media sources, with associated scores based on their journalistic quality. The scores were provided through Overtone’s algorithm, and range from one (low-quality or low informational value add) to five (high-quality or high informational value add). Articles were sourced from traditional journalism outlets (news and news-leaning websites), as well as non-journalistic sources of vaccine information, such as governmental websites, healthcare and NGO websites, and medical journals. Given the algorithm’s focus on editorial content, as opposed to other metrics such as author, outlet, or engagement, analyzing a diverse set of article types allowed the research team to examine how different styles of vaccine-related content measured against traditional journalistic quality standards. Therefore, this dataset provides a unique insight into the spectrum of vaccine reporting, and serves as a contribution to the field of automated quality assessment.  About ARTT: The Analysis and Response Toolkit for Trust (ARTT) project is focused on helping people engage in trust-building ways when discussing vaccine efficacy and other topics online.  About Overtone: Overtone has built a Natural Language Processing algorithm that finds and sorts online content by its intrinsic qualities, rather than clicks or shares. Their AI assesses texts for journalistic signals that demonstrate human effort. For any questions about this dataset, please contact artt@hackshackers.com.

opencc-zeroAug 2022View details →

Large-scale reforestation can increase water yield and reduce drought risk for water-insecure regions in the Asia-Pacific

Large-scale reforestation can potentially bring both benefits and risks to the water cycle, which needs to be better quantified under future climates to inform reforestation decisions. We identified 477 water-insecure basins worldwide accounting for 44.6% (380.2 Mha) of the global reforestation potential. As many of these basins are in the Asia-Pacific, we used regional coupled land-climate modelling for the period 2041–2070 to reveal that reforestation increases evapotranspiration and precipitation for most water-insecure regions over the Asia-Pacific. This resulted in a statistically significant increase in water yield (p < 0.05) for the Loess Plateau-North China Plain, Yangtze Plain, Southeast China and Irrawaddy regions. Precipitation feedback was influenced by the degree of initial moisture limitation affecting soil moisture response and thus evapotranspiration, as well as precipitation advection from other reforested regions and moisture transport away from the local region. Reforestation also reduces the probability of extremely dry months in most of the water-insecure regions. However, some regions experience non-significant declines in net water yield due to heightened evapotranspiration outstripping increases in precipitation, or declines in soil moisture and advected precipitation.

Weak population genetic structure in Eurasian spruce bark beetle over large regional scales in Sweden

The Eurasian spruce bark beetle, Ips typographus, is a major pest, capable of killing spruce forests during large population outbreaks. Recorded dispersal distances of individual beetles are typically within hundreds of meters or a few kilometres. However, the connectivity between populations at larger distances and longer time spans and how this is affected by the habitat is less studied, despite its importance for understanding at which distances local outbreaks may spread. Previous population genetic studies in I. typographus typically used low resolution markers. Here, we use genome-wide data to assess population structure and connectivity of I. typographus in Sweden. We used 152 individuals from 19 population samples, distributed over 830 km from Strömsund (63º 46' 8'' N) in the north to Nyteboda (56º 8' 50'' N) in the south, to capture processes at a large regional scale, and a transect sampling design adjacent to a recent outbreak to capture processes at a smaller scale (76 km). Using restriction site-associated DNA sequencing (RADseq) markers capturing 1409-1997 SNPs throughout the genome, we document a weak genetic structure over the large scale, potentially indicative of high connectivity with extensive gene flow. No differentiation was detected at the smaller scale. We find indications of isolation-by-distance both for relative (FST) and absolute divergence (Dxy). The two northernmost populations are most differentiated from the remaining populations, and diverge in parallel to the southern populations for a set of outlier loci. In conclusion, the population structure of I. typographus in Sweden is weak, suggesting a high capacity to disperse and establish outbreak populations in new territories.

opencc-by-4.0Jun 2009View details →

Large-scale grid computing for content-based image retrieval

The author presents an approach in which a large distributed processing Grid has been used to apply a range of content-based image retrieval methods to a substantial number of images. By massively distributing the required computational task across thousands of Grid nodes, we have achieved very high throughput at relatively low overheads.

Grassland bird population declines at three Breeding Bird Survey spatial scales in contrast to a large native prairie

Grassland biomes in North America are threatened by agricultural intensification with implications for grassland associated bird populations via habitat loss, alteration, pesticide use and declining landscape heterogeneity. Despite decades of conservation concern, steep declines of North American grassland bird populations continue. Key to optimizing conservation effort is understanding how land-use practices, such as agriculture, across the annual cycle affects population status. Determining the relative influence of impacts on grassland bird declines is difficult given that the most robust estimates of population trends, the North American Breeding Bird Survey (BBS), are from surveys throughout agriculturally dominated regions. Our goal was to explore whether agriculture during the breeding season is a major driver of grassland bird declines. We derived trends for 16 grassland bird species spanning 23 years (1994-2016) at a large (459 km2), native prairie site, Suffield National Wildlife Area (SNWA) in Alberta, Canada. We compared those trends to the BBS across three spatial scales, a regional monitoring scheme with higher than average native grass cover (GBM), BCR 11 - Canada (Canada) and all of BCR 11 (BCR 11). Trends measured as annual percent change and credible interval varied greatly among species and survey strata. Across all species, declines were greatest for Canada (-1.3%, CI: -2.8, 0.0) and BCR 11 (-1.9%, CI: -3.2, -0.6). This contrasts with positive mean trends for GBM routes (1.0%, CI: -0.4, 2.3) and the SNWA data (1.7%, CI: 0.3, 3.3). Six of 16 species at SNWA were increasing with one decreasing. Five species increased at GBM and four declined. Canada had 10 species declines and three increases and BCR 11 had 10 declines and no increases. None of six grassland obligate species declined at SNWA, two declined at GBM, and all six declined over the two larger BBS strata. Our results showing fewer negative population trends at a large native grassland site compared to BBS at three spatial scales across the North American prairies support the prediction that agricultural intensification on breeding grounds is a major driver of declining populations and protection of remaining native grasslands should remain a key component of grassland bird conservation efforts.

Large scale eDNA monitoring of multiple aquatic pathogens as a tool to provide risk maps for wildlife diseases

Multiple parasites and pathogens cause disease in aquatic wildlife and in aquaculture species, generating a need for monitoring and management. Conventional disease monitoring methods involve laborious, costly and invasive capture and examination of host species, and require specialised expertise for every host and pathogen of interest. These restrictions could be alleviated by using pathogen detection techniques based on environmental DNA that provide simultaneous surveys of multiple aquatic pathogens across different host taxa. This would also be valuable for approaches employing parasite diversity as bioindicators of ecosystem disturbance, which suffer from similar restrictions. Here, we tested the potential for simultaneous detection of four wildlife pathogens in water samples from 280, mainly riverine, sites across Switzerland. We targeted the crayfish pathogen Aphanomyces astaci, the amphibian pathogen Batrachochytrium dendrobatidis, and the fish pathogens Saprolegnia parasitica and Tetracapsuloides bryosalmonae. The eDNA detection showed a widespread distribution of A. astaci, S. parasitica and T. bryosalmonae, although A. astaci and T. bryosalmonae were not detected in some alpine river catchments. B. dendrobatidis was detected only rarely, which was expected since the sampling did not target amphibian breeding sites. Co-detection rates were higher in rivers than in lakes, likely reflecting the habitat preferences and distributions of the host species. We discuss the advantages and limitations of eDNA-based pathogen monitoring and list a set of recommendations for managers. Our study illustrates how eDNA-based techniques can monitor several pathogen species concurrently, thus facilitating more comprehensive disease monitoring schemes. Combined with metabarcoding approaches in the future, eDNA based sampling and detection can facilitate the incorporation of parasite and pathogen occurrence and diversity as an indicator for aquatic ecosystem health, and for revealing the hidden biodiversity and structure of parasite communities.

Do large-scale associations in birds imply biotic interactions or environmental filtering?

Aim: There has been a wide interest in the effect of biotic interactions on species' occurrences and abundances at large spatial scales, coupled with a vast development of the statistical methods to study them. Still, the evidence whether the effects of within-trophic level biotic interactions (e.g. competition and heterospecific attraction) are discernible beyond local scales remains inconsistent. Here, we present a novel hypothesis-testing framework based on joint dynamic species distribution models (JDSDMs) and functional trait similarity to dissect between environmental filtering and biotic interactions. Location: France and Finland. Taxon: Birds. Methods: We estimated species-to-species associations within a trophic level, independent of the main environmental variables (mean temperature and total precipitation) for common species at large spatial scale with joint dynamic species distribution models (VAST). We created hypotheses based on species' functionality (morphological and/or diet dissimilarity) and habitat preferences about the sign and strength of the pairwise spatio-temporal associations to estimate the extent to which they result from biotic interactions (competition, heterospecific attraction) and/or environmental filtering. Results: Spatio-temporal associations were mostly positive (80%), followed by random (15%), and only 5% were negative. Negative spatio-temporal associations in different communities were due to a few species when they existed. The relationship between spatio-temporal association and functional dissimilarity among species was negative, which fulfills the predictions of both environmental filtering and heterospecific attraction. Main conclusions: We showed that processes leading to species aggregation (mixture between environmental filtering and heterospecific attraction) seem to dominate assembly rules, and we did not find evidence for competition. Altogether, hypothesis-testing framework based on joint dynamic species distribution models and functional trait similarity is beneficial in ecological interpretation of species-to-species associations from the long-term large-scale data.

opencc-by-4.0Oct 2017View details →

Dynamics of the Young Solar Wind: Weakened Magnetization and Onset of Large Scale Turbulence (Simulation Data)

Simulation data used in "Dynamics of the Young Solar Wind: Weakened Magnetization and Onset of Large Scale Turbulence", submitted to Geophysical Research Letters.

opencc-by-4.0Feb 2024View details →

Data and code for "Large-scale remote sensing analysis reveals an increasing coupling of grassland vitality to atmospheric water demand"

Data and code for  "Large-scale remote sensing analysis reveals an increasing coupling of grassland vitality to atmospheric water demand" All R code used for the analysis is provided in the folder code.  Data and intermediate results are provided or stored in the folders data and tmp_data. All results including figures will be stored in the folder results.  R version: 4.3.1 To carry out the entire analysis the code should be run in the provided order: 1) Code to run non-metric multidimensional scaling (NMDS) for habitat groups and  produce Fig. 1b (habitat map and legend for Fig 1a: data/eunis_gl_habitat_ger_990m.tif,eunis_gl_habitat_ger_990m_legend.clr)   2) Code to generate grassland vitality maps and time series from 1985 to 2021 (Fig. 3).  Grassland vitality maps on 30m for all grasslands in Germany provided in data/glv_1985-2021.zip. 3) Code to model relation of grassland vitality to five drought indices (VPD, temperature, CWB, soil moisture, precipitation), output are Fig. 4, Fig. S1, Tab. 1. 4) Code for trend analysis of drought sensitivity based on 5-, 10-, and 15-year moving windows, output are Fig. 5, Fig. S2.  5) Code to model drought sensitivity of grassland habitat groups and habitat types, output are Fig. 6 and table with sensitivity per habitat type.

opencc-by-4.0Apr 2024View details →

Unsupervised detection of Large-scale Weather Patterns in the Northern Hemisphere via Markov State Modelling: from Blockings to Teleconnections

Data Source This dataset is derived from the NCEP-NCAR Reanalysis 1 data provided by the NOAA PSL, Boulder, Colorado, USA, from their website at <a href="https://psl.noaa.gov/">https://psl.noaa.gov</a>., a robust atmospheric dataset that includes a wide range of climatic measurements essential for comprehensive climate analysis. The original data can be accessed at the NOAA Physical Sciences Laboratory website:  https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html.

Swarm-C Neutral Density Data for Large-Scale Wave (LSW) Structures

Open the record for dataset details and reuse information.

Comprehensive large-scale datasets for 26 viral families for fine-tuning BERT-infect models

These datasets were constructed in the paper "Hidden Challenges in Evaluating Spillover Risk of Zoonotic Viruses using Machine Learning Models" (doi: https://doi.org/10.1101/2024.04.25.591033). The details were also described in the git-hub (https://github.com/Junna-Kawasaki/BERT-infect_2024). <ul> <li>The compressed files, such as ${virus}.tar.xz, contain fasta and genbank files.</li> </ul>

opencc-by-4.0Apr 2024View details →

MobileWell400+: A Large-Scale Multivariate Longitudinal Mobile Dataset for Investigating Individual and Collective Well-Being

This study engaged 409 participants over a period spanning from July 10 to August 8, 2023, ensuring representation across various demographic factors: 221 females, 186 males, 2 non-binary, year of birth between 1951 and 2005, with varied annual incomes and from 15 Spanish regions. The MobileWell400+ dataset, openly accessible, encompasses a wide array of data collected via the participants' mobile phone, including demographic, emotional, social, behavioral, and well-being data. Methodologically, the project presents a promising avenue for uncovering new social, behavioral, and emotional indicators, supplementing existing literature. Notably, artificial intelligence is considered to be instrumental in analysing these data, discerning patterns, and forecasting trends, thereby advancing our comprehension of individual and population well-being. Ethical standards were upheld, with participants providing informed consent.  The following is a non-exhaustive list of collected data: <ul> <li>Data continuously collected through the participants' smartphone sensors: physical activity (resting, walking, driving, cycling, etc.), name of detected WiFi networks, connectivity type (WiFi, mobile, none), ambient light, ambient noise, and status of the device screen (on, off, locked, unlocked).</li> <li>Data corresponding to an initial survey prompted via the smartphone, with information related to demographic data, effects and COVID vaccination, average hours of physical activity, and answers to a series of questions to measure mental health, many of them taken from internationally recognised psychological and well-being scales (PANAS, PHQ, GAD, BRS and AAQ), social isolation (TILS) and economic inequality perception.</li> <li>Data corresponding to daily surveys prompted via the smartphone, where variables related to mood (valence, activation, energy and emotional events) and social interaction (quantity and quality) are measured.</li> <li>Data corresponding to weekly surveys prompted via the smartphone, where information on overall health, hours of physical activity per week, lonileness, and questions related to well-being are asked.</li> <li>Data corresponding to an final survey prompted via the smartphone, consisting of similar questions to the ones asked in the initial survey, namely psychological and well-being items (PANAS, PHQ, GAD, BRS and AAQ), social isolation (TILS) and economic inequality perception questions.</li> </ul> For a more detailed description of the study please refer to MobileWell400+StudyDescription.pdf. For a more detailed description of the collected data, variables and data files please refer to MobileWell400+FilesDescription.pdf.

Large-Scale Multipurpose Benchmark Datasets For Assessing Data-Driven Deep Learning Approaches For Water Distribution Networks

<div> <div><a href="https://arxiv.org/search/cs?searchtype=author&query=Tello,+A">Andres Tello*</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Truong,+H">Huy Truong*</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Lazovik,+A">Alexander Lazovik</a>, <a href="https://arxiv.org/search/cs?searchtype=author&query=Degeler,+V">Victoria Degeler</a>. Large-Scale Multipurpose Benchmark Datasets For Assessing Data-Driven Deep Learning Approaches For Water Distribution Networks. Engineering Proceedings. 2024; 69(1):50. <a href="https://doi.org/10.3390/engproc2024069050">https://doi.org/10.3390/engproc2024069050</a></div> <div>(*) Both authors contributed equally. </div> <h2>Update</h2> <div>(04/09/2024): Citation is updated. We have added headers for CSVs and auxiliary data (duration time, edge list, ordered names.. ) in the configuration file (JSON format). As such, corresponding INP files can be omitted when working with this version.  The EXN network has been included in this version, so the total number of processed networks is 11. For more details, please read ZENODO_README.md.</div> <h2>Contact</h2> <div>For dataset-related questions: <a href="mailto:h.c.truong@rug.nl" target="_blank" rel="noopener">Huy Truong</a></div> <div>For data acquisition: <a href="mailto:a.tello@rug.nl" target="_blank" rel="noopener">Andres Tello</a></div> <div>If you use this dataset, please cite:</div> <blockquote>@article{tello2024largescale,     AUTHOR = {Tello, Andrés and Truong, Huy and Lazovik, Alexander and Degeler, Victoria},     TITLE = {Large-Scale Multipurpose Benchmark Datasets for Assessing Data-Driven Deep Learning Approaches for Water Distribution Networks},     JOURNAL = {Engineering Proceedings},     VOLUME = {69},     YEAR = {2024},     NUMBER = {1},     ARTICLE-NUMBER = {50},     URL = {https://www.mdpi.com/2673-4591/69/1/50},     ISSN = {2673-4591},     DOI = {10.3390/engproc2024069050} }</blockquote> </div>

opencc-zeroMay 2024View details →

Data from: Lianas associated with continued forest biomass losses following large-scale disturbances

Lianas are important to rainforest ecosystems but often impede tree growth and increase tree mortality and stem damage after disturbances that favour their growth. Understanding how lianas affect biomass recovery and rates of carbon sequestration following disturbance is therefore of crucial importance. In this study, we determine how a tropical forest recovers biomass following a large-scale disturbance and test how this varies with liana dominance and stem damage. We use remote sensing methods to develop a model, validated by field data from 40 20 m x 20 m vegetation plots, to measure change in tree above-ground biomass eight years after Tropical Cyclone Yasi damaged logged forests in the Australian Wet Tropics. We related tree biomass changes to field measures of current liana dominance over trees, expressed as liana: tree basal area ratio, and assessed how these measures related to tree stem damage. Biomass declined in 34 of the 40 plots during the eight years post-disturbance, with loss rates and proportions of damaged tree stems increasing with the liana: tree ratio. From spatial upscaling, we found a net loss in biomass across the study landscape over the same period. Our results show that, following disturbances, lianas not only limit tree biomass recovery but are also associated with further biomass declines, most likely through their contribution to stem damage and delayed mortality. Furthermore, our finding of net biomass loss across the landscape since the cyclone shows that, post-disturbance, rainforests can act as a carbon source with consequences for the global carbon sink.

Supplementary data to "Quantum-critical properties of the one- and two-dimensional random transverse-field Ising model from large-scale quantum Monte Carlo simulations"

This dataset contains the data used to generate the results in the work "Quantum-critical properties of the one- and two-dimensional random transverse-field Ising model from large-scale quantum Monte Carlo simulations" [1]. processed_data.zip contains the data used for the figures shown in [1], while raw_data.zip contains the original simulation results without further processing. To get an overview of the organization of the directories and a description of the data we recommend the README files in the top- and subdirectories. [1] C. Krämer et al., Quantum-critical properties of the one- and two-dimensional random transverse-field Ising model from large-scale quantum Monte Carlo simulations, <a href="https://doi.org/10.48550/arXiv.2403.05223">10.48550/arXiv.2403.05223</a>, 2024