Find research datasets worth reusing

opencc-by-4.0Feb 2022View details →

Dataset: Tensor-network study of correlation-spreading dynamics in the two-dimensional Bose-Hubbard model

Dataset Tensor-network study of correlation-spreading dynamics in the two-dimensional Bose-Hubbard model Ryui Kaneko, Ippei Danshita

opencc-by-4.0Apr 2022View details →

Combining Policies to Reduce the Spread of Viral Misinformation Online

Data were collected as part of the Election Integrity Partnership. Instances of potential misinformation were flagged as tickets. These were reviewed and categorized as misinformation if they made false claims related to election integrity. Details on the collection methods of the EIP can be found in our Report. These tickets were grouped together into qualitatively similar incidents. For example, tickets regarding false narratives about the use of Benford's law to detect fraud in Wisconsin became an incident. For each incident, search terms and appropriate data-ranges were determined to query our database.  Our full database consisted of all tweets matching an evolving set of keywords, collected in real time, using the Twitter API. To maintain user privacy, we are providing data segmented into events and aggregated into 5-minute blocks of time. This should be sufficient for replicating our findings (predicated on the aggregation and segmentation). In order to permit analysis under various user-removal conditions, we have provided multiple versions of this dataset with users removed according to the conditions evaluated in the manuscript. We encourage anyone with the need for more granular data or alternate conditions to reach out to the University of Washington Center for an Informed Public.

opencc-by-4.0Jul 2021View details →

Local chromatin context dictates the genetic determinants of the heterochromatin spreading reaction. Analysis Code, Numerical and Primary data.

Uploaded under this Zenodo DOI is the following: 1. the Analysis Code used for Flow Cytometry analysis in the paper, GO complex analysis (Figure 3) and Hit visualization (Figure 1, 2 S1, S4 Figs). 2. The primary Flow Cytometry data from both the initial screen (ScreenFlowFCS) and validation experiments (ValidationFlowFCS) are included as .zip files. 3. a .zip folder is uploaded that contains all the analysis code for the ChIP-Seq experiments.  4. Excel worksheets that contain the numerical source data for all qPCR bar plots.

opencc-by-4.0Jun 2022View details →

MRI data for "Stress-inducible phosphoprotein 1 (HOP/STI1/STIP1) regulates the spreading, aggregation, and toxicity of α-synuclein in vivo"

Repository for magnetic resonance imaging data from the project titled "Stress-inducible phosphoprotein 1 (HOP/STI1/STIP1) regulates the spreading, aggregation, and toxicity of α-synuclein in vivo" Contains the pre-processed ex vivo T1-weighted images (Bruker 7T; 70 micron isotropic voxel resolution) for WT mice, M83 homozygous, and M83 homozygous mice with one copy of the TPR transgene. Full subject list can be viewed with the prado_MRI_M83dTPR_subjectlist_final.csv file. Whole brain region segmentations are available for these mice. These labels were generated using the MAGeT-Brain segementation pipleine (https://github.com/CobraLab/MAGeTbrain) and using a modified/merged version of the Allen brain atlas. The full list of regions included can be found in the file named Allen_brain_mapping_final.csv. See readme.txt file for more information

opencc-by-4.0Jul 2022View details →

Quantifying reagent spreading by cross borehole electrical tomography to assess performance of groundwater remediation

This repository contains data related to the articleof the same name, published at Water Resources Research in 2022. inversion_inputs folder = all cross-borehole ERT/IP data formatted for the software AarhusInv inversion_results folder = output files from AarhusInv that can be used for plotting and further data analysis, for each inversion 2x32_Z.xml = spread file for the ABEM Terrameter LS2 when two boreholes with 32 electrodes each are connected hvede_2xbsb.txt = quadrupole series for a given pair of boreholes, including the two single-borehole and two types of cross-borehole configurations. The electrodes order is A-B-M-N. Electrodes 1-32 are in borehole 1, while electrodes 33-64 are in borehole 2. hvede_2xbsb.xml = protocol file for the ABEM Terrameter LS2, that can be used in combination with the spread file 2x32_Z.xml. The paper abstract is given below. In-situ remediation of contaminated groundwater often relies on the installation of a treatment zone degrading the contamination. Zero-valent-iron (ZVI) is a type of reagent used for this purpose. Adequate delivery of ZVI in the whole target volume is particularly challenging and requires monitoring with high spatial resolution. We present a monitoring tool for imaging the dynamic spreading of ZVI and its associated ionic cloud, using cross-borehole time-lapse electrical resistivity tomography (ERT). This tool works in urban areas and is particularly suitable for achieving the required spatial resolution at the scale of the target volume. Groundwater and sediment samples show a consistent spatial and temporal distribution of the remediation cloud with cross-borehole ERT. Yet, the 2D anomalies observed with cross-borehole ERT provide a more spatially complete and rapid image of the remediation cloud distribution than if based solely on monitoring screens. At the study site, ZVI injection leads to uneven spreading, clearly documented by cross-borehole ERT monitoring. The benefit of hydraulic conductivity (K) mapping by cross-borehole induced polarization (IP) to understand unexpected injection paths (upstream leakage, spreading in preferred pathways) is investigated.  A 2D, IP-based, continuous and coherent K-distribution is obtained that compares well with estimations by grain size analyses from the treatment zone. However, the IP-based K-field fails at predicting injection paths, suggesting the creation of pathways during the high-pressure injection of ZVI. Cross-borehole time-lapse ERT is the most promising geophysical tool for performance assessment of in situ remediation involving reagents with conductivity contrast.

opencc-by-4.0Oct 2022View details →

Study of the non-vector spread of the pine nematode Bursaphelenchus xylophilus through sawdust

The goal of the study was to assess the possibility of Pinus sylvestris trees to be infested with pinewood nematode B. xylophilus through PWN-infested sawdust. The trials were conducted in climatic room at a temperature of 26℃ and at humidity of 60-70% from June to October, 2020. Each trial included 4-year-old seedlings of 12 Pinus sylvestris pines. The experiment contained seven trials, including the control: 1) uninjured stem + PWN-infested sawdust, 2) injured stem + PWN-infested sawdust, 3) injured stem + PWN-infested sawdust is 2.5 cm from the stem, 4) uninjured roots + PWN-infested sawdust in soil, 5) injured roots + PWN-infested sawdust in soil, 6) injured roots without sawdust, and 7) control. At the end of the experiment, the number of pinewood nematodes in the stem and roots of infested seedlings was counted. The number of nematodes is based on 100 grams wet weight of woody substrate and 100 cm3 for soil substrate. We counted the number of wilted pine seedlings taking into account wilt classes (from 0 to 5) in different trials at the 20th week of the experiment.

opencc-by-4.0Oct 2022View details →

Composition and electrical resistance results of a Ir-Pd-Pt-Rh-Ru composition spread thin film materials library

The dataset contains the results of electrical resistance measurement and composition analysis of a thin film composition spread materials library.  342 measurement areas were evaluated for chemical composition using energy dispersive X-ray spectroscopy and electrical resistance using a 4-point probe. CSV columns: x: x-coordinate of materials library in µm y: y-coordinate of materials library in µm Ir: relative chemical composition in at.% Pd: relative chemical composition in at.% Pt: relative chemical composition in at.% Rh: relative chemical composition in at.% Ru: relative chemical composition in at.% Resistance: electrical resistance in Ohm   This dataset is supplementary information for an associated publication. A link to the publication will be provided after publishing.

dryad40/100

The spread of Aedes albopictus (Diptera: Culicidae) in the islands of São Tome and Príncipe

The mosquito Aedes albopictus (Diptera: Culicidae) is a vector species of the causal agents of Dengue, yellow fever, and Zika among other diseases pathogens. The species originated in Southeast Asia and has spread widely and rapidly in the last century. The species has been reported in localities from the Gulf of Guinea since the early 2000s, but systematic sampling has been scant. We sampled Ae. albopictus twice, in 2013 and 2023 across the altitudinal gradient in São Tomé and found that the species was present in all sampled years at altitudes up to 680 meters. We also found some evidence of increases in proportional representation compared to Ae. aegypti over time. We report the presence of the species in Príncipe for the first time, suggesting that the range of Ae. albopictus is larger than previously thought. Finally, we use bioclimatic niche modeling to infer the potential range of Ae. albopictus and infer that the species has the potential to spread across a large portion of São Tomé and Príncipe. Our results suggest that Ae. albopictus has established itself as a resident species of the islands of the Gulf of Guinea and should be incorporated into the list of potential vectors that need to be surveyed and controlled.

opencc-zeroMay 2024View details →

opencc-by-4.0May 2024View details →

Fig. 1 in Solving the 250-year-old mystery of the origin and global spread of the German cockroach, Blattella germanica

Fig. 1. Population genetic structure and global spread routes of the German cockroach, Blattella germanica. (A) Median joining haplotype network based on the COI gene (1,536 bp). (B) Principal component analysis based on 158,216 genome-wide single nucleotide polymorphisms. (C) Bar plot (Top), split into regionspecific bar plots mapped to sampling sites, derived from maximum likelihood estimation of ancestry (ADMIXTURE) at the optimal number of ancestral clusters (K = 6). The diagram on top of the bar plot indicates nucleotide diversity (π) per locus at each sampling site. The inferred timing and routes of global spread are mapped with black arrows. (D) Divergence of key populations presented in the form of an allele-frequency-based unrooted tree with residuals of drift parameters mapped as migration edges. (E) A zoomed-in view of (C) focused on Asia. The natural range of the ancestor, B. asahinai, is shown in green.

Figure 3 in Dynamics of arbuscular mycorrhizal fungi in relation to root colonization, spore density, and soil properties among different spreading stages of the exotic plant threeflower beggarweed (Desmodium triflorum) in a ZoysiO tenuifoliO lawn

Figure 3. Dynamics of the soil arbuscular mycorrhizal fungal spore density within Desmodium triflorum coverage levels and seasons.

Figure 6 in Dynamics of arbuscular mycorrhizal fungi in relation to root colonization, spore density, and soil properties among different spreading stages of the exotic plant threeflower beggarweed (Desmodium triflorum) in a ZoysiO tenuifoliO lawn

Figure 6. Conceptual framework demonstrating possible mechanisms of soil arbuscular mycorrhizal fungi (AMF) during the spreading process of Desmodium triflorum in the Zoysia tenuifolia lawn. Numbers 1, 2, 3, and 4 indicate different spreading stages of the invasive plant D. triflorum. Corresponding mycorrhizal structures were shown as the four microscopic views. Light-green and medium-yellow circles indicate AM fungal spores predominantly produced by the root mycorrhizal structures of Z. tenuifolia and D. triflorum, respectively. Medium-green and dark-yellow lines indicate the life cycle of spores in Z. tenuifolia plants and in D. triflorum plants, respectively. The AM fungi might influence the spread of D. triflorum by the following steps: (1) the early stage of the lawn's development with only Z. tenuifolia growing but without D. triflorum present. This occurs at the very beginning of the lawn establishment, and the AM fungal spores that previously existed in the lawn soil first infected the fine roots of Z. tenuifolia and completed the life cycle on their own. (2) The early spreading stage of D. triflorum (level 1). The roots of the two plants come into contact with each other, inducing the external hyphae that originally grow closely on the Z. tenuifolia roots to infect the roots of D. triflorum. The difference between the mycorrhizal infections of the two host plants contributes to higher root mycorrhizal colonizations of D. triflorum compared with Z.tenuifolia. However, at this stage,D. triflorum is not as competitive as Z. tenuifolia in the lawn, although it has advantages in terms of mycorrhizal infections. Therefore, the soil AM fungal spores are still predominantly produced by the mycorrhizal structures of the AMF-infected Z. tenuifolia roots. (3) The intermediate spreading stage of D. triflorum (levels 2 and 3). Desmodium triflorum continues to spread in the lawn. The contact of the two plants becomes more frequent and further induces a much closer relationship between the AM infections of the two plants. The increased D. triflorum plants in the lawn and the advantage of D. triflorum in root mycorrhizal infections facilitate the contribution of the mycorrhizal structures of the D. triflorum roots to sporulation. Thus, in this stage, the soil AM fungal spores were produced by the mycorrhizal structures of both plants, thereby inducing insignificant correlations between the spore densities and the root colonizations of either Z. tenuifolia or D. triflorum. (4) The late spreading stage of D. triflorum (levels 4 and 5). Desmodium triflorum is dominant in the lawn.The large numbers of D. triflorum plants and the AM infection advantage of D. triflorum facilitate AMF sporulation in the soil, thereby inducing significant correlations between the spore densities and the root colonizations of D. triflorum. At the different spreading stages of D. triflorum, the soil AM fungal communities also change as a result of the changed contributions of the AMF-infected host plants to the sporulation.

Figure 5 in Dynamics of arbuscular mycorrhizal fungi in relation to root colonization, spore density, and soil properties among different spreading stages of the exotic plant threeflower beggarweed (Desmodium triflorum) in a ZoysiO tenuifoliO lawn

Figure 5. The relative abundance and community composition at the family (A) and species levels (B) of arbuscular mycorrhizal fungi (AMF) in soils of different Desmodium triflorum coverage levels.

Figure 2 in Dynamics of arbuscular mycorrhizal fungi in relation to root colonization, spore density, and soil properties among different spreading stages of the exotic plant threeflower beggarweed (Desmodium triflorum) in a ZoysiO tenuifoliO lawn

Figure 2. Dynamics of the total, hyphal, and vesicular colonizations of Zoysia tenuifolia and Desmodium triflorum among different D. triflorum coverage levels and seasons. "Season," "Coverage," and "Species" indicate ANOVA results of each indicator among seasons and D. triflorum coverage levels and between the two plants, respectively.

Figure 4 in Dynamics of arbuscular mycorrhizal fungi in relation to root colonization, spore density, and soil properties among different spreading stages of the exotic plant threeflower beggarweed (Desmodium triflorum) in a ZoysiO tenuifoliO lawn

Figure 4. Correlations among the root mycorrhizal colonizations, arbuscular mycorrhizal fungal spore densities ("AMF spore density"), and soil properties in different coverage levels of Desmodium triflorum. ZTC, ZHC, and ZVC in light-green circles indicate the total colonization (TC), hyphal colonization (HC), and vesicular colonization (VC) of Zoysia tenuifolia, respectively. DTC, DHC, and DVC in light-red circles indicate the TC, HC, and VC of D. triflorum, respectively. Green lines and green-colored numbers indicate significant correlations between the colonization indicators of Z. tenuifolia and corresponding correlation coefficients, respectively. Red lines and red-colored numbers indicate significant correlations between the colonization indicators of Z. tenuifolia and corresponding correlation coefficients, respectively. Dark-green double arrows and dark-green numbers indicate the correlations between the colonizations of Z. tenuifolia and those of D. triflorum and corresponding correlation coefficients, respectively. Light-blue double arrows and light-blue numbers indicate the correlations between the spore densities and soil properties/root colonizations and corresponding correlation coefficients,respectively. Darkyellow double arrows and dark-yellow numbers indicate the correlations between the soil properties and root colonizations and corresponding correlation coefficients, respectively. Correlation is significant at: *P <0.05; **P <0.01; ***P <0.001. The minus sign indicates a negative correlation. Insignificant correlations are not shown.

Figure 1 in Dynamics of arbuscular mycorrhizal fungi in relation to root colonization, spore density, and soil properties among different spreading stages of the exotic plant threeflower beggarweed (Desmodium triflorum) in a ZoysiO tenuifoliO lawn

Figure 1. Dynamics of the soil physiochemical properties (average ± SE, n = 5) within different Desmodium triflorum coverage levels and seasons. "Season" and "Coverage" indicate ANOVA results of each indicator among seasons and D. triflorum coverage levels, respectively. Level 1, level 2, level 3, level 4, and level 5 indicate the coverage levels of D. triflorum in the Zoysia tenuifolia lawn, respectively, in this and all following figures.

opencc-by-4.0Nov 2020View details →

Figure 3 in The effectiveness of hot water pressurized spray in field conditions to slow the spread of invasive alien species

Figure 3. (A) Average maximum temperature, (B) Average thermal exposure (area under the curve), of hot water spray applied to Dreissena polymorpha, Dikerogammarus villosus and Crassula helmsii from three distances (10, 20, 30 cm) and for three durations (5, 10, 15 seconds). Error bars show standard error (n = 36).

Figure 6 in Better biosecurity: spread-prevention of the invasive Asian clam, Corbicula fluminea (Müller, 1774)

Figure 6. Mean mortality (± SE) of adult Corbicula fluminea specimens (SH = 15–26 mm) 24 hrs post-exposure to a direct steam application, at a distance of 2–3 cm from the source, for 10 sec, 30 sec, 1, 2, 5 and 10 minutes (n = 5, with 70 clams per n).

Figure 4 in Better biosecurity: spread-prevention of the invasive Asian clam, Corbicula fluminea (Müller, 1774)

Figure 4. Mean mortality (± SE) for groups of ten adult Corbicula fluminea specimens (SH = 15–26 mm) 24 hrs post-exposure to 35 (35 g L-1) or 70% (70 g L-1) aerated salt solutions (regular table salt) for 1, 6, 24, 48 and 72 hrs (n = 5, with 150 clams per n).

Figure 2 in Better biosecurity: spread-prevention of the invasive Asian clam, Corbicula fluminea (Müller, 1774)

Figure 2. Mean mortality (± SE) of adult Corbicula fluminea specimens (SH = 15–26 mm) 24 hrs post-exposure to warm water (30 °C) solutions of aquatic disinfectants Virasure® Aquatic and Virkon® Aquatic, at both 2% (20 g L-1) and 4% (40 g L-1) concentrations. Experimental groups, each consisting of ten adult clams, were immersed in solutions of either chemical for 10, 20, 40 and 80 minutes (n = 3, with 200 clams per n).

Figure 5 in Better biosecurity: spread-prevention of the invasive Asian clam, Corbicula fluminea (Müller, 1774)

Figure 5. Mean mortality (± SE) for groups of ten medium (A: SH = 15–20.9 mm) and ten large (B: SH = 21–36 mm) adult Corbicula fluminea specimens 24 hrs post-exposure to hot water temperatures of 35, 40 and 45 °C for 5, 10 and 20 minutes (n = 5, with 120 clams per n).