Find research datasets worth reusing

opencc-by-4.0Feb 2021View details →

Fig. 1 in Individual Movement Of Large Carabids As A Link For Activity Density Patterns In Various Forestry Treatments

Fig. 1. Mean activity density of Carabus scheidleri (a) and C. coriaceus (b) per sampling plot in different for- estry treatments (C = control, CC = clear-cutting, P = preparation cut- ting) between 2014 and 2018. Verti- cal lines represent a 95% confidence interval and capital letters above bars indicate significant differences based on Tukey's multiple compari- sons of means

opencc-by-4.0Feb 2021View details →

Fig. 2 in Individual Movement Of Large Carabids As A Link For Activity Density Patterns In Various Forestry Treatments

Fig. 2. Movements of Carabus scheidleri (a) within and between forestry treatments (C = control, CC = clear-cutting, P = preparation cutting) based on CMR. The number next to the arrow corresponds with the number of recorded movements. Individual trajectories of radio-tracked C. coriaceus (b) in the experimental area, black dots represent the first release point for each trajectory

opencc-by-4.0Dec 2016View details →

Fig. 2 in Foraging activity of Palmistichus elaeisis (Hymenoptera: Eulophidae) at various densities on pupae of the eucalyptus defoliator Thyrinteina arnobia (Lepidoptera: Geometridae)

Fig. 2. (A) Duraton of life cycle (egg to adult) and (B) numbers of Palmistichus elaeisis progeny with a density of 1, 3, 6, 9, 12, 15, 18, or 21 ovipositng females per Thyrinteina arnobia pupa at 25 ± 2 °C, 70 ± 10% RH, and a 12:12 h L:D photoperiod.

opencc-by-4.0Dec 2016View details →

Fig. 1 in Foraging activity of Palmistichus elaeisis (Hymenoptera: Eulophidae) at various densities on pupae of the eucalyptus defoliator Thyrinteina arnobia (Lepidoptera: Geometridae)

Fig. 1. Percentage of pupae parasitzed and percentage of emergence of Palmistichus elaeisis with a density of 1, 3, 6, 9, 12, 15, 18, or 21 ovipositng females per Thyrinteina arnobia pupa at 25 ± 2 °C, 70 ± 10% RH, and a 12:12 h L:D photoperiod. Statstcal significance: parasitsm, P = 0.3770; emergence, P = 0.034.

opencc-by-4.0Jun 2012View details →

Figure2. Generation of negative feedbacks gets tuned once a TCR completes stimulation beyond the threshold l. A TCell generates activation signal to BCell once it gets stimulation of its k-TCRs.-AIDEN: A Density Conscious Artificial Immune System for Automatic Discovery of Arbitrary Shape Clusters in Spatial Patterns

A TCR at position p is stimulated if rp (x) - rn(x) > l. Figure 1 depicts this process. When a T Cell receives stimulations on more than k receptors, it generates activation signal to a B Cell, as represented in Figure2.

opencc-by-4.0Mar 2019View details →

359,569 commits with source code density; 1149 commits of which have software maintenance activity labels (adaptive, corrective, perfective)

This dataset comes as SQL-importable file and is compatible with the widely available MariaDB- and MySQL-databases. It is based on (and incorporates/extends) the dataset "1151 commits with software maintenance activity labels (corrective,perfective,adaptive)" by Levin and Yehudai (<a href="https://doi.org/10.5281/zenodo.835534">https://doi.org/10.5281/zenodo.835534</a>). The extensions to this dataset were obtained using Git-Tools, a tool that is included in the Git-Density (<a href="https://doi.org/10.5281/zenodo.2565238">https://doi.org/10.5281/zenodo.2565238</a>) suite. For each of the projects in the original dataset, Git-Tools was run in extended mode. The dataset contains these tables: <ul> <li>x1151: The original dataset from Levin and Yehudai. <ul> <li>despite its name, this dataset has only 1,149 commits, as two commits were duplicates in the original dataset.</li> <li>This dataset spanned 11 projects, each of which had between 99 and 114 commits</li> <li>This dataset has 71 features and spans the projects RxJava, hbase, elasticsearch, intellij-community, hadoop, drools, Kotlin, restlet-framework-java, orientdb, camel and spring-framework.</li> </ul> </li> <li>gtools_ex (short for Git-Tools, extended) <ul> <li>Contains 359,569 commits, analyzed using Git-Tools in extended mode</li> <li>It spans all commits and projects from the x1151 dataset as well.</li> <li>All 11 projects were analyzed, from the initial commit until the end of January 2019. For the projects Intellij and Kotlin, the first 35,000 resp. 30,000 commits were analyzed.</li> <li>This dataset introduces 35 new features (see list below), 22 of which are size- or density-related.</li> </ul> </li> </ul> The dataset contains these views: <ul> <li>geX_L (short for Git-tools, extended, with labels) <ul> <li>Joins the commits' labels from x1151 with the extended attributes from gtools_ex, using the commits' hashes.</li> </ul> </li> <li>jeX_L (short for joined, extended, with labels) <ul> <li>Joins the datasets x1151 and gtools_ex entirely, based on the commits' hashes.</li> </ul> </li> </ul>   Features of the gtools_ex dataset: <ul> <li>SHA1</li> <li>RepoPathOrUrl</li> <li>AuthorName</li> <li>CommitterName</li> <li>AuthorTime (UTC)</li> <li>CommitterTime (UTC)</li> <li>MinutesSincePreviousCommit: Double, describing the amount of minutes that passed since the previous commit. Previous refers to the parent commit, not the previous in time.</li> <li>Message: The commit's message/comment</li> <li>AuthorEmail</li> <li>CommitterEmail</li> <li>AuthorNominalLabel: All authors of a repository are analyzed and merged by Git-Density using some heuristic, even if they do not always use the same email address or name. This label is a unique string that helps identifying the same author across commits, even if the author did not always use the exact same identity.</li> <li>CommitterNominalLabel: The same as AuthorNominalLabel, but for the committer this time.</li> <li>IsInitialCommit: A boolean indicating, whether a commit is preceded by a parent or not.</li> <li>IsMergeCommit: A boolean indicating whether a commit has more than one parent.</li> <li>NumberOfParentCommits</li> <li>ParentCommitSHA1s: A comma-concatenated string of the parents' SHA1 IDs</li> <li>NumberOfFilesAdded</li> <li>NumberOfFilesAddedNet: Like the previous property, but if the net-size of all changes of an added file is zero (i.e. when adding a file that is empty/whitespace or does not contain code), then this property does not count the file.</li> <li>NumberOfLinesAddedByAddedFiles</li> <li>NumberOfLinesAddedByAddedFilesNet: Like the previous property, but counts the net-lines</li> <li>NumberOfFilesDeleted</li> <li>NumberOfFilesDeletedNet: Like the previous property, but considers only files that had net-changes</li> <li>NumberOfLinesDeletedByDeletedFiles</li> <li>NumberOfLinesDeletedByDeletedFilesNet: Like the previous property, but counts the net-lines</li> <li>NumberOfFilesModified</li> <li>NumberOfFilesModifiedNet: Like the previous property, but considers only files that had net-changes</li> <li>NumberOfFilesRenamed</li> <li>NumberOfFilesRenamedNet: Like the previous property, but considers only files that had net-changes</li> <li>NumberOfLinesAddedByModifiedFiles</li> <li>NumberOfLinesAddedByModifiedFilesNet: Like the previous property, but counts the net-lines</li> <li>NumberOfLinesDeletedByModifiedFiles</li> <li>NumberOfLinesDeletedByModifiedFilesNet: Like the previous property, but counts the net-lines</li> <li>NumberOfLinesAddedByRenamedFiles</li> <li>NumberOfLinesAddedByRenamedFilesNet: Like the previous property, but counts the net-lines</li> <li>NumberOfLinesDeletedByRenamedFiles</li> <li>NumberOfLinesDeletedByRenamedFilesNet: Like the previous property, but counts the net-lines</li> <li>Density: The ratio between the two sums of all lines added+deleted+modified+renamed and their resp. gross-version. A density of zero means that the sum of net-lines is zero (i.e. all lines changes were just whitespace, comments etc.). A density of of 1 means that all changed net-lines contribute to the gross-size of the commit (i.e. no useless lines with e.g. only comments or whitespace).</li> <li>AffectedFilesRatioNet: The ratio between the sums of NumberOfFilesXXX and NumberOfFilesXXXNet</li> </ul>   This dataset is supporting the paper "Importance and Aptitude of Source code Density for Commit Classification into Maintenance Activities", as submitted to the QRS2019 conference (The 19th IEEE International Conference on Software Quality, Reliability, and Security). Citation: Hönel, S., Ericsson, M., Löwe, W. and Wingkvist, A., 2019. Importance and Aptitude of Source code Density for Commit Classification into Maintenance Activities. In The 19th IEEE International Conference on Software Quality, Reliability, and Security.

opencc-by-4.0Dec 2022View details →

Estimated densities of activity from: Characterising diel activity patterns to design conservation measures: Case study of European bat species

Estimated densities of activity calculated in "Characterising diel activity patterns to design conservation measures: case study of European bat species" (see Materials and Methods for more information on these calculations). The files named "densitiyAllYear" correspond to the estimated densities based on our entire dataset. The files named "densitiySpring" correspond to the estimated densities based on a subset of our dataset comprising only monitoring carried out between 1 March and 21 June. The files named "densitiySummer" correspond to the estimated densities based on a subset of our dataset comprising only monitoring carried out between 22 June and 21 August. The files named "densitiyAutumn" correspond to the estimated densities based on a subset of our dataset comprising only monitoring carried out between 22 August and 31 October. The first column of each file ("PercentageNight") corresponds to the percentage of the night elapsed (0 % = sunset time, 100 % =  sunrise time), the second to the estimated activity density ("Density").

opencc-by-4.0Jun 2023View details →

Data for: Food Anticipatory Behaviour on European Seabass in Sea Cages: Activity-, Positioning- and Density-based approaches

Telemetry and sensory data data for: Food Anticipatory Behaviour on European Seabass in Sea Cages: Activity-, Positioning- and Density-based approaches Please read the README.txt file before working with the data.

opencc-by-4.0Feb 2022View details →

Data from: Evaluating predator control using two non-invasive population metrics: a camera trap activity index and density estimation from scat genotyping

Includes datasets from the Wimmera and Mallee, Victoria, Australia: - Fox camera trap data used to model activity - Fox scat SECR capture and trap files used to model density

opencc-by-4.0Feb 2020View details →

Data file for paper:Zalitis, Christopher; Kucernak, Anthony; Lin, Xiaoqian; Sharman, Jonathan, "Electrochemical Measurement of Intrinsic Oxygen Reduction Reaction Activity at High Current Densities as a Function of Particle Size for Pt4-xCox /C (x=0,1,3) Catalysts", ACS Catalysis, 2020 - https://doi.org/10.1021/acscatal.9b04750

The data in this spreadsheet was used to produce the figures in the paper             Authors:              Zalitis, Christopher; Kucernak, Anthony; Lin, Xiaoqian; Sharman, Jonathan Title:      Electrochemical Measurement of Intrinsic Oxygen Reduction Reaction Activity at High Current Densities as a Function of Particle Size for Pt4-xCox /C (x=0,1,3) Catalysts Journal: ACS Catalysis Year:      2020

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Data from: Density-dependent diel activity in stream-dwelling Arctic charr Salvelinus alpinus

Intraspecific competition plays a significant role in shaping how animals use and share habitats in space and time. However, the way individuals may modify their diel activity in response to increased competition has received limited attention. We used juvenile (age 1+) Arctic charr Salvelinus alpinus to test the prediction that individuals at high population density are more active and distribute their foraging activity over a greater portion of the 24-h cycle than individuals at low population density. Individually tagged fish were stocked in seminatural stream enclosures at low (2 fish/m2) and high (6 fish/m2) density. During each of two 2-week experimental rounds, activity of all fish within each enclosure was recorded every 3 h over seven 24-h cycles. At high density, fish were more active and distributed their activity over a greater portion of the 24-h cycle, with increased activity particularly at crepuscular times. Fluctuations in ecological conditions (e.g., water temperature and light intensity) also affected activity. Fish at high density grew as fast as fish at low density. This study demonstrates that individuals exhibit a degree of behavioral flexibility in their response to changes in ecological conditions and suggests that intraspecific competition can cause animals to modify temporal aspects of their activity to gain access to resources and maintain growth.

opencc-zeroDec 2015View details →

dryad32/100

Density-dependent effects of parasitism on the activity of a benthic engineer species: potential impact on ecosystem functioning

While parasitism is a common lifestyle on Earth, its importance for the functioning of marine ecosystems has been overlooked for a long time. In particular, parasites have significant potential to influence central ecological processes through their impacts on hosts that serve as ecosystem engineers. Using an ex-situ experimental approach, we explored the effects of trematode parasites on the engineering bioturbation activity of a common and abundant bivalve along European Atlantic soft-bottom coastlines, the peppery furrow shell Scrobicularia plana, as well as knock-on effects for nutrient exchanges at the sediment-water interface. Trematodes negatively impacted the host's ability to transport sediment particles and solutes in a density-dependent way with parasite burden explaining 22–31% of the inter-individual variability. This could be explained by parasitism impairing the bivalve physiological state and ability to burrow as we observed a decrease in the condition index and the burrowing depth of the bivalves with an increase in the number of parasites they host. In contrast, the influence of S. plana on benthic biogeochemical fluxes did not vary significantly according to parasitic burden over a short time scale. Here, we focused on the effects of trematode parasites on the sole behaviour of S. plana and thus excluded other macrofaunal organisms. We should next test whether trematodes modulate the structure and functioning of benthic communities dominated by S. plana to better understand and quantify the engineering role of parasites in soft-bottom coastal environments.

opencc-zeroJan 2024View details →

opennotspecifiedNov 2017View details →

Distribution. Now restricted to the Channel Country of SW Queensland and the Lake Eyre Basin in NE South Australia. Descriptive notes. Head-body 95-120 mm, tail 105-160 mm, ear 23-29 mm, hindfoot 32-37 mm; weight 30-50 g. The Fawn Hopping Mouse has body form typical of hopping mice, with very long hindfeet, long tail with distal brush of longer hairs, very long ears, and large protruberant eyes. Dorsal fur is of variable color, from pale pinkish fawn to gray; ventral fur white. Unlike most other hopping mice, it has no throat pouch, but males have a glandular area of naked skin on the chest. Habitat. Occurs in low shrublands and tussock grasslands on stony ("gibber") plains and claypans. Shows marked habitat segregation from the Dusky Hopping Mouse (N. fuscus), which is closely associated with sandy substrates. Food and Feeding. The Fawn Hopping Mouse is mostly granivorous, but also eats other plant material (stems, leaves) and occasionally invertebrates. It uses succulent, salt-adapted plants around edges of claypans as a source of water. Breeding. Reproduction is probably largely opportunistic and aseasonal, with high reproductive output from near-continuous breeding after periods of high rainfall; reported littersize is 1-5, most commonly three; gestation period 38-43 days for nonlactating females. Females may mature later than other hopping mice, with reproductive maturity reached at about six months. Activity patterns. Terrestrial and nocturnal. Fawn Hopping Mice shelter during day in burrow systems that are typically simpler and shallower than those of other hopping mice. Movements, Home range and Social organization. Fawn Hopping Mice generally live singly or in small groups; typically uncommon within range, but population density may increase by an order of magnitude following periods of high rainfall. Status and Conservation. Classified as Near Threatened on The IUCN Red List. The Fawn Hopping Mouse has shown marked decline in range (estimated at greater than 50%), and presumably population size, since European settlement of Australia. This is mostlikely due to predation by the introduced house cat and Red Fox (Vulpes vulpes), and to habitat degradation associated with pastoralism. Bibliography. Brazenor (1934), Burbidge et al. (2008), Finlayson (1939), Gould (1853), Jackson & Groves (2015), Murray et al. (1999), Ogilby (1892), Thomas (1921h), Van Dyck & Strahan (2008), Waite (1898), Watts & Aslin (1981), Woinarski et al. (2014), Wood Jones (1925). in Muridae

Distribution. Now restricted to the Channel Country of SW Queensland and the Lake Eyre Basin in NE South Australia. Descriptive notes. Head-body 95-120 mm, tail 105-160 mm, ear 23-29 mm, hindfoot 32-37 mm; weight 30-50 g. The Fawn Hopping Mouse has body form typical of hopping mice, with very long hindfeet, long tail with distal brush of longer hairs, very long ears, and large protruberant eyes. Dorsal fur is of variable color, from pale pinkish fawn to gray; ventral fur white. Unlike most other hopping mice, it has no throat pouch, but males have a glandular area of naked skin on the chest. Habitat. Occurs in low shrublands and tussock grasslands on stony ("gibber") plains and claypans. Shows marked habitat segregation from the Dusky Hopping Mouse (N. fuscus), which is closely associated with sandy substrates. Food and Feeding. The Fawn Hopping Mouse is mostly granivorous, but also eats other plant material (stems, leaves) and occasionally invertebrates. It uses succulent, salt-adapted plants around edges of claypans as a source of water. Breeding. Reproduction is probably largely opportunistic and aseasonal, with high reproductive output from near-continuous breeding after periods of high rainfall; reported littersize is 1-5, most commonly three; gestation period 38-43 days for nonlactating females. Females may mature later than other hopping mice, with reproductive maturity reached at about six months. Activity patterns. Terrestrial and nocturnal. Fawn Hopping Mice shelter during day in burrow systems that are typically simpler and shallower than those of other hopping mice. Movements, Home range and Social organization. Fawn Hopping Mice generally live singly or in small groups; typically uncommon within range, but population density may increase by an order of magnitude following periods of high rainfall. Status and Conservation. Classified as Near Threatened on The IUCN Red List. The Fawn Hopping Mouse has shown marked decline in range (estimated at greater than 50%), and presumably population size, since European settlement of Australia. This is mostlikely due to predation by the introduced house cat and Red Fox (Vulpes vulpes), and to habitat degradation associated with pastoralism. Bibliography. Brazenor (1934), Burbidge et al. (2008), Finlayson (1939), Gould (1853), Jackson & Groves (2015), Murray et al. (1999), Ogilby (1892), Thomas (1921h), Van Dyck & Strahan (2008), Waite (1898), Watts & Aslin (1981), Woinarski et al. (2014), Wood Jones (1925).

opencc-by-4.0Apr 2024View details →

A qualitative assessment of limits of active flight in low density atmospheres

Supplementary video files for the "A qualitative assessment of limits of active flight in low density atmospheres".  Supplementary Dataset S1 contains the following video files recorded from the stereo camera no.1:  1) flies_2_N2_gstream1.mp4 - video showing the experiment with flushing with N2 (first repetition). 2) flies_2_N2_2_gstream1_1.mp4 - video showing the experiment with flushing with N2 (second repetition). 3) flies_2_N2_3_gstream1_1.mp4 - video showing the experiment with flushing with N2 (third repetition). 4) flies_1__He_gstream1_1.mp4 - video showing the experiment with flushing with He (first repetition) 5) flies_2_He_2_gstream1_1.mp4 - video showing the experiment with flushing with He (second repetition) 6) flies_2_He_3_gstream1_1.mp4 - video showing the experiment with flushing with He (third repetition)

opencc-by-nc-4.0Apr 2018View details →

GPS data for 'Low-Latitude Ionospheric Density Irregularities and Associated Scintillations Investigated by Combining COSMIC RO and Ground-Based GPS Observations over a Solar Active Period' by Zhe Yang and Zhizhao Liu

This dataset contains the final derived GPS data reported in the paper 'Low-Latitude Ionospheric Density Irregularities and Associated Scintillations Investigated by Combining COSMIC RO and Ground-Based GPS Observations over a Solar Active Period' by Zhe Yang and Zhizhao Liu.

opencc-by-4.0Feb 2022View details →

Active Brownian particles in external force fields: field-theoretical models, generalized barometric law, and programmable density patterns

Supplementary data for the following manuscript: Jens Bickmann, Stephan Bröker, Michael te Vrugt, Raphael Wittkowski, "Active Brownian particles in external force fields: field-theoretical models, generalized barometric law, and programmable density patterns".