Find research datasets worth reusing

opencc-zeroSep 2021View details →

Combined pressure and flow measurements to guide treatment of coronary stenoses

Objectives: The aim of this study was to assess clinical outcomes after combined pressure and flow assessment of coronary lesions. Background: Although fractional flow reserve (FFR) remains the invasive reference standard for revascularization, approximately 40% of stenoses have discordant coronary flow reserve (CFR). Optimal treatment for these disagreements remains unclear. Methods: A total of 455 subjects with 668 lesions were enrolled from 12 sites in 6 countries. Only lesions with reduced FFR and CFR underwent revascularization; all other combinations received initial medical therapy. Results: Fourteen percent of lesions had FFR<=0.8 but CFR>=2.0 while 23% of lesions had FFR>0.8 but CFR<2.0. During 2-year follow-up, the primary endpoint of composite all-cause death, myocardial infarction, and revascularization in lesions with FFR<=0.8 but CFR>=2 (10.8% event rate) compared with lesions with FFR>0.8 and CFR>=2 (6.2% event rate) exceeded the prespecified +10% noninferiority margin (P = 0.090). Target vessel failure models using both continuous FFR and continuous CFR found that only higher FFR was associated with reduced target vessel failure (Cox P = 0.007) after initial medical treatment. Central core laboratory review accepted 69.8% of all tracings with mean differences of <0.01 for FFR and <0.02 for CFR, indicating no material impact on clinical measurements or outcomes. Conclusions: All-cause death, myocardial infarction, and revascularization after 2 years was not noninferior between lesions with FFR<=0.8 but CFR>=2 and lesions with FFR>0.8 and CFR>=2. These results do not support using invasive CFR>=2 to defer revascularization for lesions with reduced FFR if the patient would otherwise be a candidate on the basis of the entire clinical scenario and treatment preference.

opencc-by-4.0Sep 2021View details →

Variable Flow Data Sets

Easterly and Northerly Imposed Flow datasets.

opencc-zeroSep 2021View details →

Data from: A global perspective on the functional responses of stream communities to flow intermittence

The current erosion of biodiversity is a major concern that threatens the ecological integrity of ecosystems and the ecosystem services they provide. Due to global change, an increasing proportion of river networks are drying and changes from perennial to non-perennial flow regimes represent dramatic ecological shifts with potentially irreversible alterations of community and ecosystem dynamics. However, there is minimal understanding of how biological communities respond functionally to drying. Here, we highlight the taxonomic and functional responses of aquatic macroinvertebrate communities to flow intermittence across river networks from three continents, to test predictions from underlying trait-based conceptual theory. We found a significant breakpoint in the relationship between taxonomic and functional richness, indicating higher functional redundancy at sites with flow intermittence higher than 28%. Multiple strands of evidence, including patterns of alpha and beta diversity and functional group membership, indicated that functional redundancy did not compensate for biodiversity loss associated with increasing intermittence, contrary to received wisdom. A specific set of functional trait modalities, including small body size, short life span and high fecundity, were selected with increasing flow intermittence. These results demonstrate the functional responses of river communities to drying and suggest that ongoing biodiversity reduction due to global change in drying river networks is threatening their functional integrity. These results indicate that such patterns might be common in these ecosystems, even where drying is considered a predictable disturbance. This highlights the need for the conservation of natural drying regimes of intermittent rivers to secure their ecological integrity.

opencc-zeroSep 2021View details →

Targeted and passive environmental DNA approaches outperform established methods for detection of quagga mussels, Dreissena rostriformis bugensis in flowing water

<ol> <li>The early detection of invasive non-native species (INNS) is important for informing management actions. Established monitoring methods require the collection or observation of specimens, which is unlikely at the beginning of an invasion when densities are likely to be low. Environmental DNA (eDNA) analysis is a highly promising technique for the detection of INNS – particularly during the early stages of an invasion. </li> <li>Here, we compared the use of traditional kick-net sampling with two eDNA approaches (targeted detection using both conventional and quantitative PCR, and passive detection via metabarcoding with conserved primers) for detection of quagga mussel, Dreissena rostriformis bugensis; a high priority INNS, along a density gradient on the River Wraysbury, UK. </li> <li>All three molecular tools outperformed traditional sampling in terms of detection. Conventional PCR and qPCR both had 100% detection rate in all samples, and outperformed metabarcoding when the target species was at low densities. Additionally, quagga mussel DNA copy number (qPCR) and relative read count (metabarcoding) were significantly influenced by both mussel density and distance from source population, with distance being the most significant predictor. </li> <li> Synthesis and application. All three molecular approaches were more sensitive than traditional kick-net sampling for the detection of the quagga mussel in flowing water, and both qPCR and metabarcoding enabled estimates of relative abundance. Targeted approaches were more sensitive than metabarcoding, but metabarcoding has the advantage of providing information on the wider community, and consequently impacts of INNS. </li> </ol>

opencc-by-4.0Sep 2021View details →

Raw Data for Data Set of Publication on Detecting Violations of Access Control and Information Flow Policies in Data Flow Diagrams

This data set contains the build script, software and intermedia results that we used to create the result data set for the publication "<a href="https://doi.org/10.1016/j.jss.2021.111138">Detecting Violations of Access Control and Information Flow Policies in Data Flow Diagrams</a>".

opencc-by-4.0Oct 2021View details →

A nocturnal jet flows over a wind farm in complex terrain

A nocturnal jet simulated with the Weather Research and Forecasting model flows over topography where a wind farm is located. It produces downstream flow acceleration that enhances the performances of turbines in the back rows. This simulation is related to the case 3 (transect 1) of the paper Nocturnal jets over wind farms in complex terrain that will be submitted to Applied Energy.

opencc-by-4.0Oct 2021View details →

OCCA Flow Fields for examples in PlanktonIndividuals.jl

OCCA Flow Fields for examples in PlanktonIndividuals.jl

opencc-by-4.0Oct 2021View details →

Rotating shallow water flow under location uncertainty with a structure-preserving discretization -- Data set

With this data set one can reproduce the figures in the manuscript "Rotating shallow water flow under location uncertainty with a structure-preserving discretization". The figures can be created with the following MATLAB scripts: Figure 3           -  plot_contour_plane.m Figure 4 and 5 - plot_Energy_convergence.m Figure 6           - plot_sphere_snapshot.m Figure 7           - plot_contour_sphere.m Figure 8           - plot_specs.m Figure 9           - plot_spread.m Figure 10          - createhist.m Figure 11          - plot_MSB_MEV.m

opencc-zeroOct 2021View details →

Channel Islands song sparrow (Melospiza melodia) landscape genomics and adaptation to climate with gene flow dataset

Disentangling the effects of neutral and adaptive processes in maintaining phenotypic variation across environmental gradients is challenging in natural populations. Song sparrows (Melospiza melodia) on the California Channel Islands occupy a pronounced east-west climate gradient within a small spatial extent, providing a unique opportunity to examine the interaction of genetic isolation (gene flow) and the environment (selection) in driving variation. We used reduced representation genomic libraries to infer the role of neutral processes (drift and restricted gene flow) and divergent selection in driving variation in thermoregulatory traits with an emphasis on the mechanisms that maintain bill divergence among islands. Analyses of 22,029 neutral SNPs confirm distinct population structure by island with restricted gene flow and relatively large effective population sizes, suggesting bill differences are likely not a product of genetic drift. Instead, we found strong support for local adaptation using 3,294 SNPs in differentiation-based and environmental association analyses coupled with genome-wide association (GWA) tests. Specifically, we identified several putatively adaptive and candidate loci in or near genes involved in bill development pathways (e.g., BMP, CaM, Wnt), confirming the highly complex and polygenic architecture underlying bill morphology. Furthermore, we found divergence in genes associated with other thermoregulatory traits (i.e., feather structure, plumage color, and physiology). Collectively, these results suggest strong divergent selection across an island archipelago results in genomic changes in a suite of traits associated with thermal adaptation over small spatial scales. Future research should move beyond the study of univariate traits to better understand the multivariate adaptive responses to these complex climate regimes.

Figure 5 from: Aketarawong N, Isasawin S, Sojikul P, Thanaphum S (2015) Gene flow and genetic structure of Bactrocera carambolae (Diptera, Tephritidae) among geographical differences and sister species, B. dorsalis, inferred from microsatellite DNA data. In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 239-272. https://doi.org/10.3897/zookeys.540.10058

Figure 5 - Simplified network of Bactrocera carambolae and Bactrocera dorsalis groups, and the sequential disconnection of the network. The network was constructed using eight SSRs. Scanning was done for decreasing thresholds A is the fully connected network B is the percolation threshold (Dp = 0.20, with all links corresponding to distances superior to Dp excluded). DP, JK, and NT are connecting between Bactrocera carambolae and Bactrocera dorsalis groups. Red dashed lines with number are corresponded to the threshold values, revealing serial disconnection of the network C is the lowest threshold (thr = 0.15).

Figure 4 from: Aketarawong N, Isasawin S, Sojikul P, Thanaphum S (2015) Gene flow and genetic structure of Bactrocera carambolae (Diptera, Tephritidae) among geographical differences and sister species, B. dorsalis, inferred from microsatellite DNA data. In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 239-272. https://doi.org/10.3897/zookeys.540.10058

Figure 4 - Simplified network of seven Bactrocera carambolae populations, and the sequential forms of cluster. The network was constructed using eight SSRs. Scanning was done for decreasing thresholds A is the fully connected network B is the percolation threshold (Dp = 0.52, with all links corresponding to distances superior to Dp excluded). JK plays an important role connecting between native and introduced populations C–D are the lower thresholds chosen (thr = 0.40 and 0.15, respectively) to reveal sub-structured network.

Figure 3 from: Aketarawong N, Isasawin S, Sojikul P, Thanaphum S (2015) Gene flow and genetic structure of Bactrocera carambolae (Diptera, Tephritidae) among geographical differences and sister species, B. dorsalis, inferred from microsatellite DNA data. In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 239-272. https://doi.org/10.3897/zookeys.540.10058

Figure 3 - The individual admixture plot for K = 3. Each bar reveals a single individual. Each color of bars represents each genetic cluster. Samples of Bactrocera carambolae belong to clusters 2 and 3 (green and blue, respectively) while samples of Bactrocera dorsalis belong to cluster 1 (red). Potential hybrids have a proportion of genetic cluster (Q) between 0.100 to 0.900 (0.100 ≤ Q ≤ 0.900) as identified with asterisk (*).

Figure 1 from: Aketarawong N, Isasawin S, Sojikul P, Thanaphum S (2015) Gene flow and genetic structure of Bactrocera carambolae (Diptera, Tephritidae) among geographical differences and sister species, B. dorsalis, inferred from microsatellite DNA data. In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 239-272. https://doi.org/10.3897/zookeys.540.10058

Figure 1 - Sampling collections of Bactrocera carambolae and Bactrocera dorsalis in this study. Seven populations of Bactrocera carambolae (blue dots) were collected from Southeast Asia and Suriname. Three populations of Bactrocera dorsalis (red dots) were sampled from East and Southeast Asia. Two other unidentified populations (purple dots) were included. Information for each population is described in Table 1.

Figure 6 from: Aketarawong N, Isasawin S, Sojikul P, Thanaphum S (2015) Gene flow and genetic structure of Bactrocera carambolae (Diptera, Tephritidae) among geographical differences and sister species, B. dorsalis, inferred from microsatellite DNA data. In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 239-272. https://doi.org/10.3897/zookeys.540.10058

Figure 6 - Simplified network of the SY5 strain and wild populations, and the sequential disconnection of the network. The network was constructed using seven SSRs. Scanning was done for decreasing thresholds A is the fully connected network B is the percolation threshold (Dp = 0.23, with all links corresponding to distances superior to Dp excluded). DP, JK, and NT are connecting between Bactrocera carambolae and Bactrocera dorsalis groups C is the lowest threshold (thr = 0.15). Red dashed lines with number are corresponded to the threshold values, revealing serial disconnection of the network.

Figure 2 from: Aketarawong N, Isasawin S, Sojikul P, Thanaphum S (2015) Gene flow and genetic structure of Bactrocera carambolae (Diptera, Tephritidae) among geographical differences and sister species, B. dorsalis, inferred from microsatellite DNA data. In: De Meyer M, Clarke AR, Vera MT, Hendrichs J (Eds) Resolution of Cryptic Species Complexes of Tephritid Pests to Enhance SIT Application and Facilitate International Trade. ZooKeys 540: 239-272. https://doi.org/10.3897/zookeys.540.10058

Figure 2 - Three-dimensional plot of Principal Coordinate Analysis (PCoA) and STRUCTURE analysis. A the planes of the first three principal coordinates explain 43.65%, 20.13%, and 16.91% of total genetic variation, respectively, for seven Bactrocera carambolae populations using eight SSRs B the planes of the first three principal coordinates explain 33.05%, 23.17%, and 15.87%, respectively, for Bactrocera carambolae and Bactrocera dorsalis groups using eight SSRs C the planes of the first three principal coordinates explain 30.50%, 22.14%, and 18.53%, respectively, for the SY5 strain and wild populations using seven SSRs. Pie graphs, consisting of different colored sections, represent co-ancestor distribution of 185, 289, and 321 individuals in A two, B three, and C two hypothetical clusters, respectively.

opencc-by-4.0Dec 2018View details →

Reading flow without BDD

Figure of the reading flow of participants who did not use BDD scenario to answer Task 1.2

opencc-by-4.0Dec 2021View details →

Model codes and data for ``A control volume finite element model for predicting the morphology of cohesive-frictional debris flow deposits"

The code and the dataset can be read/run by using Matlab. The description is as follows: 1. Dataset (field_data) includes transect data of three field debris flow deposits from Coussot et al. (1996). The data can be read and calibrated with the analytical solution by the code field_calibration.m. 2. Dataset (data_T01-T04, T11-T15_DT) includes experimental fan topography data, calibrated parameters, and simulation outputs.  3. Two calibration codes are used for the model parameter calibrations of the two sets of experiments. 4. Function aggradation_DT.m is the CVFEM model for simulating fan morphology. Use CVFEM_exp_simulation.m code to run simulations for the experiments.

opencc-by-4.0Dec 2022View details →

Raw flow cytometry data files (fcs-files)

These FCS files are a part of the supplementary data for the following publication: Meiotic transmission patterns of additional genomic elements in Brachionus asplanchnoidis, a rotifer with intraspecific genome size variation  Julie Blommaert 1,2 & Claus-Peter Stelzer 1,* 1 Research Department for Limnology, University of Innsbruck, Mondsee, Austria 2 The New Zealand Institute for Plant & Food Research Limited Nelson, New Zealand * Corresponding author: claus-peter.stelzer@uibk.ac.at Scientific Reports (https://doi.org/10.1038/s41598-022-25566-8)

opencc-by-4.0Dec 2022View details →

Enhanced surface area carbon cathodes for the hydrogen-bromine redox flow battery

Raw data by published figure