Find research datasets worth reusing

Data supporting the study "The impact of molecular self-organisation on the atmospheric fate of a cooking aerosol proxy" by Milsom et al.

Model and experimental data from the study "The impact of molecular self-organisation on the atmospheric fate of a cooking aerosol proxy" to be published in Atmospheric Chemistry and Physics.

F4TCNQ and TTF on approximate supported graphene, 3D surface adsorbate search with BOSS

These datasets were employed in the manuscript: [1] J. Järvi, M. Todorović, and P. Rinke, Efficient modeling of organic adsorbates on oxygen-intercalated graphene on Ir(111), Phys. Rev. B 105, 195304 (2022). DOI: 10.1103/PhysRevB.105.195304 The two datasets feature DFT sampling of adsorption configurations for F4TCNQ and TTF on approximate supported graphene (Gr) using the Bayesian Optimization Structure Search (BOSS) method. The 3D configurational searches were conducted for each molecule over two molecular translations (x, y) and an in-plane rotation (gamma). The search range of on-surface translation (x, y) is [0, 1] in fractional coordinates of the Gr unit cell. The in-plane rotation (gamma) is done in the range [0, 180] deg. Energy (Eads) is the adsorption energy of F4TCNQ or TTF on the approximate supported Gr, computed with DFT. For additional details on search coordinates and DFT calculations please refer to [1].   The 3D models of the adsorption energy surfaces were constructed with 500 energy points for each molecule, the full lists are provided in the datasets. Each calculation is denoted with an ID number (001-500). The raw data for each calculation can be found in the NOMAD repository with the corresponding ID, DOI: 10.17172/NOMAD/2022.04.07-1

opencc-by-4.0Aug 2017View details →

Fig. 1 in Comparison Of Biting Midges Of The Early Eocene Cambay Amber (India) And Late Eocene European Ambers Supports The Independent Origin Of European Ambers

Fig. 1. Eohelea sp. with unique structure of wing organ from Rovno amber: 1 — dorsal view, 2 — ventral view.

opencc-by-4.0Dec 2015View details →

Fig. 4 in New Species Of Praepusa (Carnivora, Phocidae, Phocinae) From The Netherlands Supports East To West Neogene Dispersal Of True Seals

Fig. 4. Geographical and palaeogeographical locations of the studied area with arrows indicating dispersals of different species of the genus Praepusa from the Eastern Paratethys westward: 1 — Praepusa vindobonensis: Western Kazakhstan and Austria, Middle Miocene, early Sarmatian (16.5–11.2 Ma); 2 — Pr. vindobonensis (= tarchankutica): Ukraine and Moldova, Middle Miocene, middle Sarmatian (13.6–12.3 Ma); 3 — Pr. pannonica: Moldova and Hungary, Middle Miocene, early-middle Sarmatian (12.3–11.2 Ma). 4 — Pr. magyaricus: Vienna Basin, middle Sarmatian, Middle Miocene (13.6–12.3 Ma); 5 — Pr. boeska: The Netherlands and Belgium, Late Miocene — Early Pliocene (11.6–3.2 Ma).

opencc-by-4.0Dec 2015View details →

Fig. 1 in New Species Of Praepusa (Carnivora, Phocidae, Phocinae) From The Netherlands Supports East To West Neogene Dispersal Of True Seals

Fig. 1. Sandpit de Kuilen, location of Mill-Langenboom, in the eastern Noord-Brabant, The Netherlands(Late Miocene).

opencc-by-4.0Dec 2015View details →

Fig. 3 in New Species Of Praepusa (Carnivora, Phocidae, Phocinae) From The Netherlands Supports East To West Neogene Dispersal Of True Seals

Fig. 3. Sacrum of Praepusa boeska sp. n., RGM 629552, collection of the Naturalis Biodiversity Center in Leiden (NL). Zanclian–Piacenzian (Pliocene), Antwerp Basin, Belgium: A — ventral view; B — dorsal view; C — cranial view.

opencc-by-4.0Jun 2022View details →

Supporting information for the paper: Terrestrial Gamma-ray Flashes with Accompanying Elves Detected by ASIM

Supporting data to the paper "Terrestrial Gamma-ray Flashes with Accompanying Elves Detected by ASIM"

Research Data supporting "Pachyrhynchus weevils use 3D photonic crystals with varying degrees of order to create diverse and brilliant displays"

The research data is arranged into different folders containing the following files (.txt, .tif, .xlsx files; italics). This data and the descriptions below should be read in conjunction with the manuscript and “Supporting Info”, both of which may be found at the following DOI: 10.1002/smll.202200592.

opencc-zeroApr 2022View details →

dryad40/100

Data supporting: Success of post-fire plant recovery strategies varies with shifting fire seasonality

Wildfires are increasing in size and severity and fire seasons are lengthening, largely driven by climate and land use change. Many plant species from fire prone ecosystems are adapted to specific fire regimes corresponding to historical conditions and shifts beyond these bounds may have severe impacts on vegetation recovery and long-term species persistence. Here, we conduct a meta-analysis of field-based studies across different vegetation types and climate regions to investigate how post-fire plant recruitment, reproduction and survival are affected by fires that occur outside of the historical fire season. We find that fires outside of the historical fire season may lead to decreased post-fire recruitment for many species, particularly obligate seeding species. Conversely, we find a general increase of post-fire survival in resprouting species. Our results highlight the trade-offs that exist when considering the effects of changes in the seasonal timing of fire, an already present aspect of climate-related global fire regime change.

Codes and model output supporting Analysis of the Evolution of Parametric Drivers of High-End Sea-Level Hazards

Codes and model output supporting Analysis of the Evolution of Parametric Drivers of High-End Sea-Level Hazards (Advances in Statistical Climatology, Meteorology and Oceanography, May 2022)

Supporting dataset for: "Plasma essential amino acid concentration and profile are associated with performance of lactating dairy cows as revealed through meta-analysis and hierarchical clustering"

This dataset was used in the meta-analysis and hierarchical clustering published in "Plasma essential amino acid concentration and profile are associated with performance of lactating dairy cows as revealed through meta-analysis and hierarchical clustering" in the Journal of Dairy Science. We searched Web of Science and Google Scholar databases through March 2020 with the terms “plasma EAA,” “milk urea” or “blood urea,” and “dairy” or lactating dairy”. To be included in our study, the papers must have met the following selection criteria: (1) been published in English in a peer-reviewed journal; (2) reported dietary ingredients on a DM basis and at minimum dietary CP concentration; (3) used treatments based on diet changes (e.g., no infusion trials were included); (4) reported DMI, lactation performance, and milk components yield; (5) reported all individual [EAA]p (excluding Trp); and (6) reported blood urea-N or plasma urea-N. Infusion studies were excluded to avoid possible effects of method of EAA supply (e.g., infusion vs. feeding) and to narrow the scope of application. The final dataset included 22 studies and 96 dietary treatments. For a more complete description of the methods, please refer to the published paper.

Catalytic Dehydrogenation of Ethane over Mn Oxide Supported on Zeolite Chabazite

A new class of Mn-containing zeolites prepared by incipient wetness impregnation (IWI) have been found to catalyze the ethane dehydrogenation reaction with high selectivity (98%+). Preparation by IWI leads to the formation of Mn2O3 nanoparticles on the external surface of the zeolite crystals and herein is shown that the primary active sites for the reaction are located on the surface of these particles. Propane dehydrogenation is also successfully catalyzed by this catalyst. Other Mn-zeolites (MFI and BEA) also have high reactivity and selectivity towards light alkane dehydrogenation.

opencc-by-4.0Jan 2022View details →

Data supporting "Large-scale citizen science programs can support ecological and climate change assessments"

Text file of phenology observations pulled from the USA National Phenology Network's database (www.usanpn.org) and used in this analysis.

dryad40/100

Whole-genome analysis of multiple wood ant population pairs supports similar speciation histories, but different degrees of gene flow, across their European ranges

The application of demographic history modelling and inference to the study of divergence between species has become a cornerstone of speciation genomics. Speciation histories are usually reconstructed by analysing single populations from each species, assuming that the inferred population history represents the actual speciation history. However, this assumption may not be met when species diverge with gene flow, e.g., when secondary contact may be confined to specific geographic regions. Here, we tested whether divergence histories inferred from heterospecific populations may vary depending on their geographic locations, using the two wood ant species Formica polyctena and F. aquilonia. We performed whole-genome resequencing of 20 individuals sampled in multiple locations across the European ranges of both species. Then, we reconstructed the histories of distinct heterospecific population pairs using a coalescent-based approach. Our analyses always supported a scenario of divergence with gene flow, suggesting that divergence started in the Pleistocene (ca. 500 kya) and occurred with continuous asymmetrical gene flow from F. aquilonia to F. polyctena until a recent time, when migration became negligible (2-19 kya). However, we found support for contemporary gene flow in a sympatric pair from Finland, where the species hybridise, but no signature of recent bidirectional gene flow elsewhere. Overall, our results suggest that divergence histories reconstructed from a few individuals may be applicable at the species level. Nonetheless, the geographical context of populations chosen to represent their species should be taken into account, as it may affect estimates of migration rates between species when gene flow is spatially heterogeneous.

opencc-zeroMay 2022View details →

opencc-by-4.0Mar 2022View details →

Supporting information for "An Atlas of Convection in Main-Sequence Stars"

The contents of 'code.zip' are the plotting and analysis scripts used in generating the plots in this work. The contents of 'atlas_Z_MW_time_2022_05_06_13_40_06_sha_94d5.zip' are the history files for the MESA runs which the plotting scripts analyze. Each file is in its own directory, labelled by the mass of the star in solar units.

Dataset supporting manuscript entitled 'Partitioning of Small Hydrophobic Molecules into Polydimethylsiloxane in Microfluidic Analytical Devices'

This is the dataset supporting the manuscript 'Surface and bulk modifications of polydimethylsiloxane to reduce absorption/adsorption of small molecules in lab-on-a-chip' published in Micromachines

Supporting data for "Multipartite entangled states in dipolar quantum simulators"

Supporting data for "Multipartite entangled states in dipolar quantum simulators" (https://arxiv.org/abs/2205.03910.), by Tommaso Comparin, Fabio Mezzacapo and Tommaso Roscilde. If you use these data in a scientific work, please cite the corresponding article. This dataset includes tVMC and exact results for the two-dimensional dipolar XX model, on square or triangular (periodic) lattices. These results are directly shown in Figures 1-5 of the main text, with the following organization: - See Fig_collective_spin_dynamics for Fig. 1(b); see Fig_GHZ_fidelity for Fig. 1(d). - See Fig_spin_squeezing for Fig. 2. - See Fig_full_counting_statistics_N20 for Fig. 3. - See Fig_Fisher_information_inequality for Fig. 4. - See Fig_GHZ_fidelity for Fig. 5. We also include the exact-diagonalization results shown in Fig. 7 of the Supplementary Material -- see Fig_tower_of_states.

Supporting data for "Modeling the albedo neutron decay source of radiation belt electrons and protons"

Data sets are provided in support of the publication to appear in JGR-Space Physics. They include tabulated values of computed albedo neutron flux above the atmosphere, and of resulting radiation belt electron and proton source functions. Data format is described in the README files.

UF & UAB's Phase 2 Demonstration Study: Developing a Model to Support Transportation System Decisions considering the Experiences of Drivers of all Age Groups with Autonomous Vehicle Technology (Project A3)

Enclosed you will find the data collected during our STRIDE Phase II research project (A3) and a data dictionary.

Online Repository of the Study "I want to RIDE my e-bicycle!": Supporting Developers Categorizing User Issues of a Mobility-as-a-Service Platform

Online Repository of the Study “I want to RIDE my e-bicycle!": Supporting Developers Categorizing User Issues of a Mobility-as-a-Service Platform Introduction In the Mobility-as-a-Service (MaaS) context, e-bikes are important and environmental-friendly transportation resources providing flexibility, time and cost savings, and reducing traffic congestion. Additional to user satisfaction and marketing advantages, the resolution of user-reported issues is regulated in many cities. In order to efficiently solve the issues, it is essential to quickly identify their types (e.g., software- or hardware-related?) to assign them to the responsible team. But for popular e-mobility services, the manual analysis of the reports is inefficient because of its tediousness, high time requirements, and error-proneness.  Our empirical study, carried out in the context of a Mobility as a Service start-up company, proposes an approach for the automated identification of relevant concerns reported by users of e-bike services. The company has more than 20,000 private customers across seven different countries and dedicates considerable effort in analyzing user behavior. However, the current manual process of analyzing and triaging user-reported issues hinders MaaS-company’s ability to grow and expand its services.  To help MaaS providers identify relevant user-reported issues, In the study, we (i) manually inspect about 3,000 user-reported issues received by the MaaS company; (ii) design a taxonomy modeling the types of relevant issues reported by users; and (iii) propose MaaS-RIDE, an approach to automatically classify the user-reported issues according to the categories of the devised taxonomy.  Our results demonstrate that MaaS-RIDE is able to accurately (F-measure ≥ 93%) identify software and hardware user-reported issues. This result is critical for e-bike sharing companies to address such issues in an agile way and achieve the required user satisfaction. Dataset Overview The dataset is composed of the following different sorts of data:  <ul> <li> “Data_and_preprocessing” folder  <ul> <li>o the user-reported issues data</li> <li>o the user-reported issues data processed as Bag of Words for Machine Learning training.  <ul> <li>For this look at the sub-folder “input_data_for_ML” and the following matrices: <ul> <li>tf-idf-matrix-of-comment_finals_with_oracle_info_low_level.csv</li> <li>tf-idf-matrix-of-comment_finals_with_oracle_info.csv</li> </ul> </li> <li>Moreover, a sample of selected issues was reported in the replication package: <ul> <li>see file “randomSamples.csv” (due to a non-disclosure agreement with our industrial partner, we are unauthorized to share the whole raw user reports used in our experiments)</li> <li> “RQ1” folder: Types of E-bikes User-reported Issues</li> </ul> </li> </ul> </li> <li> the resulting taxonomy after the analysis of the issues</li> <li> “RQ2” folder: Classifying E-bikes Issue types</li> <li> the trained models </li> <li> the results of the models</li> </ul> </li> </ul> The following sections describe more in detail what each of those folders and files contain. “Data_and_preprocessing” folder <ul> <li>User-reported issues subset.</li> </ul> In an industrial setting, due to privacy reasons, we disclose only an example subset of the user-reported issues, this information is in the file randomSamples.csv. The randomSamples.csv a subset that was generated randomly adding 20 examples using a stratified sampling from the High-level categories and 20 from the Low-level categories. This subset is not exhaustive but serves the purpose of showing the reviewers the kind of issues that this particular industrial set is confronted with. The file contains: <ul> <li> <ul> <li> the Id of the user report; </li> <li> the column "comment_final" contains the issue text after the replacement of information that needed anonymization (e.g., vehicle-plates, personal names, addresses and timestamps); </li> <li> the column "High_level_category" contains the selected category from the 5 first level categories of the presented Three-level taxonomy of e-bike user reported issues; </li> <li>• the columns ‘Low_level_category" and "Fine_grained_topic" contain the assigned, if existing, respective category. </li> </ul> </li> <li>Bag of Words Term by Document matrix.</li> </ul> An important input for training the ML models is the Bag of Words representation generated after processing the  2,989 manually-labeled user issues. The result of this process is a Term-by-Document matrix. We share this matrix in the files in the sub-folder input_data_for_ML where they are labeled for High- and Low-level categories.  In the tf-idf-matrix-of-comment_finals_with_oracle_info.csv and tf-idf-matrix-of-comment_finals_with_oracle_info_low_level.csv files, the first column refers to the issue “Id”, the last column “oracle” is the labeled category, the rest of the columns represent the terms contained in the 2,989 user-reported issues and in each row the weight of the i−𝑡ℎ term contained in the j−𝑡ℎ user issue by using the tf-idf score. “RQ1” folder <ul> <li>“Three-level taxonomy of e-bike user-reported issues.pdf” file</li> </ul> The taxonomy derives from the manual analysis of the 2,989 user issues. We found that a three-level taxonomy provides significant granularity to the MaaS-company. The taxonomy encompasses 5 High-level categories, 16 Low-level categories, and 15 Low-level subcategories of e-bike user-reported issues. The file Three-level taxonomy of e-bike user-reported issues.pdf  presents the taxonomy categories and in the columns “Nr.” and “%” it shows the number of occurrences within the analyzed dataset, and the corresponding percentages. “RQ2” folder <ul> <li>“Trained Models” folder</li> </ul> We provide the trained machine and deep learning models in the sub-folder ML_DL_models. Our approach experimented with classic machine learning models based on the Bag-of-Words approach using SVM, on Word Embeddings using FastText, and Language models leveraging BERT. The SVM and BERT models were trained using the open source low-code data analytics platform KNIME and were used to classify issues corresponding to the first and second levels of the taxonomy from the “RQ1” folder. A 10-fold cross validation strategy was used to assess the classification performance.   The fastText model was trained by using default values of parameters (https://fasttext.cc/docs/en/options.html) and a 10-fold cross-validation strategy. With fastText, we classified issues corresponding only to the first level of the taxonomy from “RQ1” folder, since fastText is more effective when more data points are available in the training set (i.e., lower levels in the taxonomy have fewer well-represented issue types). <ul> <li>“Model results” folder</li> </ul> In the sub-folder model_results we provide the tables summarizing the results of using the proposed MaaS-RIDE approach, with which we automatically identify and categorize user-reported issues according to the High-level and Low-level categories of the taxonomy devised in RQ1, which are relevant for the MaaS-company.