Find research datasets worth reusing

opencc-by-4.0Feb 2023View details →

Figure 4 in Evaluation of Meloidogyne incognita and Rotylenchulus reniformis nematode-resistant cotton cultivars with supplemental Corteva Agriscience nematicides

Figure 4: Auburn University's Tennessee Valley Research Extension Center showing the nematode susceptible PHY 340 W3FE on the left and the R. reniformis-resistant PHY 332 W3FE on the right 102 DAP.

opencc-by-4.0Dec 2023View details →

Figure 1 in Evaluation of Plastic Shipping Bags for Hypothenemus hampei (Ferrari) (Coleoptera: Curculionidae) Containment

Figure 1. Diagram of Hypothenemus hampei (Ferrari) shipping bag observation arenas used in this experiment. Arenas were constructed of lidded 3.78 L (1-gal) glass jars with drying treated coffee in one of nine bag treatments suspended from the top by a hot-glued string tether to allow escaping (left) or not escaping (right) H. hampei observation in the bottom of the jar.

Figure 5 in It's a Trap! An evaluation of different passive trap types to effectively catch and control the invasive red swamp crayfish (Procambarus clarkii) in streams of the Santa Monica Mountains

Figure 5. Mean crayfish counts by size (cm) class across twelve trap types with standard error bars.

Figure 2 in It's a Trap! An evaluation of different passive trap types to effectively catch and control the invasive red swamp crayfish (Procambarus clarkii) in streams of the Santa Monica Mountains

Figure 2. Six standard, base trap types used in this study; a = Steel silver Gee Minnow trap, b = Vinyl coated black Promar Minnow trap, c = Mountain Restoration Trust custom design pyramid trap, d = Collapsible red square mesh Promar 501 trap, e = Colapsible cylindrical black mesh Promar 503 trap, and f = Mountain Restoration Trust custom PVC tube/refuge traps. Specific modifications to these traps to create the 12 types tested are provided in Table 1.

Figure 1 in It's a Trap! An evaluation of different passive trap types to effectively catch and control the invasive red swamp crayfish (Procambarus clarkii) in streams of the Santa Monica Mountains

Figure 1. Placement of traps compared in study in Las Virgenes Creek within Malibu Creek State Park. Inset shows specific study location within a regional context. Section locations were selected based on their representativeness of habitat types occurring over the entire reach (i.e. amount of riffle, runs and pools being comparable) and presence of suitable habitat for trap placement and visual observance of crayfish, tadpoles and native chub.

Figure 7 in It's a Trap! An evaluation of different passive trap types to effectively catch and control the invasive red swamp crayfish (Procambarus clarkii) in streams of the Santa Monica Mountains

Figure 7. Mean catches by stream habitat type. Differences in mean catches between stream Pools vs. Runs was evaluated using Wilcoxon rank-sum tests. * P-value <0.05.

Figure 3 in It's a Trap! An evaluation of different passive trap types to effectively catch and control the invasive red swamp crayfish (Procambarus clarkii) in streams of the Santa Monica Mountains

Figure 3. Mean catch per trap type with standard errors. Letters indicate significantly different mean counts within groups.

Figure 6 in It's a Trap! An evaluation of different passive trap types to effectively catch and control the invasive red swamp crayfish (Procambarus clarkii) in streams of the Santa Monica Mountains

Figure 6. Mean chub counts by size class across twelve trap types with standard error bars. Size classes include small as ≤ 60mm, medium as 61–89 mm, and large as 89–150mm as described by O'Brien et al. (2011).

opencc-by-sa-4.0Jun 2024View details →

Benchmark datasets for RDF load time evaluation (RiverBench)

<div> Datasets to be used for reproducing the RDF load time benchmark, using the code here: <a href="https://github.com/Ostrzyciel/rdf4led-riverbench">https://github.com/Ostrzyciel/rdf4led-riverbench</a> The datasets were obtained from <a href="https://w3id.org/riverbench/v/2.0.1/profiles/flat-triples" rel="nofollow">RiverBench profile <code>flat-triples</code> version 2.0.1</a>. The detailed licensing and authorship information for each individual dataset is available on <a href="https://w3id.org/riverbench/v/2.0.1/datasets" rel="nofollow">RiverBench's website</a>. The most restrictive license that applies to any of the datasets is CC BY-SA. Benchmark results: <a href="https://doi.org/10.5281/zenodo.12087112">https://doi.org/10.5281/zenodo.12087112</a> </div>

openapache2.0Jan 2024View details →

Evaluation datasets and results of the paper "A Framework for Measuring the Quality of Business Process Simulation Models"

Datasets and files used in the evaluation of the publication entitled "A Framework for Measuring the Quality of Business Process Simulation Models", where: <ul> <li>BPS-models/: folder containing the BPS models used in the evaluation (the BPS models discovered by ServiceMiner are not included due to privacy reasons). <ul> <li>The BPS models discovered by SIMOD are composed of i) a BPMN file with the process model structure, and ii) a JSON file with the parameters of the simulation. These files correspond to the format of Prosimos simulation engine (<a href="https://prosimos.cloud.ut.ee/">https://prosimos.cloud.ut.ee/</a>).</li> <li>The BPS models of the Loan Application and Procure to Pay processes are composed of a BPMN file with both the process model structure and parameters, corresponding to the format of the BIMP simulator used in APROMORE (<a href="https://apromore.com/">https://apromore.com/</a>).</li> </ul> </li> <li>measures/: folder containing the distance values of each measure reported in the paper.</li> <li>original-event-logs/: folder containing the (train and test) event logs used in the evaluation.</li> <li>simulated-logs/: folder containing the simulated logs evaluated in the paper (synthetic, SIMOD, and ServiceMiner).</li> <li>ComputeLogDistance.py: script to compute the distance measures proposed in the paper.</li> </ul>   To evaluate the distance measures of a set of simulated event logs in the folder simulated_logs/ against the test log test_event_log.csv.gz, run:     python ComputeLogDistance.py -cfld test_event_log.csv.gz simulated_logs/ *The flag -cfld is optional, due to the high computational complexity of the CFLD measure. WARNING: set the column names of each log accordingly (where log_1_ids are the IDs of the test log, and log_2_ids the IDs of the simulated logs). Examples: <pre><code># Column IDs for the (train/test) real-life logs, and the SIMOD simulated logs. EventLogIDs(     case='case_id',     activity='activity',     start_time='start_time',     end_time='end_time',     resource='resource' ) # Column IDs for the Loan Application and Procure to Pay simulated logs. EventLogIDs(     case='case_id',     activity='activity',     start_time='Start_Time',     end_time='End_Time',     resource='resource' ) # Column IDs for the ServiceMiner simulated logs. EventLogIDs(     case='case_id',     activity='Activity',     start_time='start_time',     end_time='end_time',     resource='Resource' )</code></pre>

opencc-by-4.0Jan 2021View details →

Figure 2 in Evaluation of root-knot nematode resistance assays for sugarcane accession lines in Australia

Figure 2: Regressions to show the relationship between root biomass and ln(eggs per g roots+1) in eight nematode trials.

opencc-by-4.0Jan 2021View details →

Figure 1 in Evaluation of root-knot nematode resistance assays for sugarcane accession lines in Australia

Figure 1: Examples of root-knot nematode gall ratings for sugarcane based on percentage of root system with galls. 1 = ≤1 to 2%, 2 = 2 to 25%, 3 = 25 to 50%, 4 = 51 to 75%, 5 ≥ 75% (modified from Shepherd 1979).

Fig. 7 in Evaluating the utility of linear measurements to identify isolated tooth loci of extinct Hyracoidea

Fig. 7. Simulated and observed values of Borges et al.'s (Borges et al. 2019) δ values for simulated trait distributions on the tree in Fig. 1 for sets of traits (A, m1: m2 length; B, M1: M2 length; C, M2: M3 length) that show phylogenetic signal (red triangles) and phylogenetic retention (gray circles).

Fig. 2 in Evaluating the utility of linear measurements to identify isolated tooth loci of extinct Hyracoidea

Fig. 2. Illustration of measurements taken on lower (m1–m3, A–C) and upper (M1–M3, D–F) teeth in occlusal views to calculate potentially diagnostic traits. Measurements are illustrated on specimen UMZC H5101A, Procavia capensis. Abbreviations: LE, length; MW, width of the crown at metaloph; PW width of the crown at paraloph.

Fig. 6 in Evaluating the utility of linear measurements to identify isolated tooth loci of extinct Hyracoidea

Fig. 6. Overlap in potentially diagnostic trait values for upper molar loci of three example hyracoid taxa (A1, B1, Procavia capensis; A2, B2, Saghatherium bowni; A3, B3, Thyrohyrax meyeri). A. Length vs. proportional frequency, showing how a single trait, length, would be modeled in a univariate discriminant analysis using observed means and variances. Colored sections of the distributions show length values that are within 95% confidence intervals of the means of more than one tooth locus, indicating regions of ambiguous lengths. B. Length vs. relative width, showing scatter plots overlaid on 2D density diagrams showing the distribution of values for individual teeth.

Fig. 8 in Evaluating the utility of linear measurements to identify isolated tooth loci of extinct Hyracoidea

Fig. 8. Overlap in potentially diagnostic trait values for a case study of isolated molars of Meroehyrax kyongoi. In contrast to Fig. 4, molar locus identifications are based on occupation of space in this scatterplot. Question marks are overlaid over two specimens whose inferred tooth position conflicts with published diagnoses. In parentheses original identification in publication.

Fig. 1 in Evaluating the utility of linear measurements to identify isolated tooth loci of extinct Hyracoidea

Fig. 1. Phylogenetic tree and tooth size distribution in hyracoids (topology from Cooper et al. 2014). Taxa are time-scaled along the x-axis of the tree to reflect fossil occurrences based on the literature, with branches rescaled between these tip dates and a root age estimated at 70.1 million years. Taxa in bold text were included in analyses. Minimum monophyletic clade including taxa in bold indicates the range of the phylogenetic bracket applied for both length and width measures (base of clade indicated by black star). Minimum monophyletic clade for length measures from the literature is indicated by a white star at the base of the clade. Shapes to the right of tips indicate whether there is a significant fit with a model of ascending (increasing) tooth size down the molar row. Abbreviations: M, upper molars; m, lower molars.

Fig. 3 in Evaluating the utility of linear measurements to identify isolated tooth loci of extinct Hyracoidea

Fig. 3. Distribution of values for a set of univariate, potentially locus-diagnostic traits (A, length vs. m1 length; B, trigonid width vs. talonic width) described in Fig. 2 in lower molars of a range of hyracoid species.

Fig. 5 in Evaluating the utility of linear measurements to identify isolated tooth loci of extinct Hyracoidea

Fig. 5. Distribution of values for a set of univariate, potentially locus-diagnostic traits (A, length vs. M1 length; B, paraloph vs. metaloph; C, metaloph vs. length; D, paraloph vs. length) described in Fig. 2 in upper molars of a range of hyracoid species.

Fig. 4 in Evaluating the utility of linear measurements to identify isolated tooth loci of extinct Hyracoidea

Fig. 4. Overlap in potentially diagnostic trait values for lower molar loci of three example hyracoid taxa (A1, B1, Procavia capensis; A2, B2, Saghatherium bowni; A3, B3, Thyrohyrax domorictus). A. Length vs. proportional frequency, showing how a single trait, length, would be modeled in a univariate discriminant analysis using observed means and variances. Colored sections of the distributions show length values that are within 95% confidence intervals of the means of more than one tooth locus, indicating regions of ambiguous lengths. B. Length vs. relative width, showing scatter plots overlaid on 2D density diagrams showing the distribution of values for individual teeth.