Find research datasets worth reusing

opencc-by-4.0Dec 2021View details →

Replication package for: Using Bid Rotation and Incumbency to Detect Collusion: A Regression Discontinuity Approach

Replication file for Using Bid Rotation and Incumbency to Detect Collusion: A Regression Discontinuity Approach. The files create figures and tables reported in the text.

opennotspecifiedFeb 2022View details →

FIGURE. Phylogenetic tree of specimens on Poaceae and related host plants constructed by MP method based on ITS+28S regions of rDNA. Bootstrap values of MP and ML are followed by the Bayesian posterior probabilities (Bpp) on the nodes in the topology. Asterisk () represents bootstrap values or Bpp less than 50% in the topology. Sample data are shown with voucher specimen number or GenBank accession number, and host plant. Sequence data determined in this study are shown in color. Teliospore shapes are shown in each clade detected, and new species are shown by asterisk () on clades. 0, I: Spermogonial and aecial host genus. Asterisk (*) on host plants: Spermogonial and aecial host plants. in Phylogenetic approach for identification and life cycles of Puccinia (Pucciniaceae) species on Poaceae from northeastern China

FIGURE. Phylogenetic tree of specimens on Poaceae and related host plants constructed by MP method based on ITS+28S regions of rDNA. Bootstrap values of MP and ML are followed by the Bayesian posterior probabilities (Bpp) on the nodes in the topology. Asterisk (*) represents bootstrap values or Bpp less than 50% in the topology. Sample data are shown with voucher specimen number or GenBank accession number, and host plant. Sequence data determined in this study are shown in color. Teliospore shapes are shown in each clade detected, and new species are shown by asterisk (*) on clades. 0, I: Spermogonial and aecial host genus. Asterisk (*) on host plants: Spermogonial and aecial host plants.

opencc-by-4.0Jan 2022View details →

Test_S: a synthesised dataset for evaluating few-shot Bioacoustic events detection system (DCASE 2021 Task5)

<ul> <li>The database consists of : <ul> <li>DC class  and MEL class </li> <li>dense bioacoustic event like official Evaluation Set in each audio</li> </ul> </li> </ul>

opencc-zeroFeb 2022View details →

Detecting selection using extended haplotype homozygosity (EHH)-based statistics in unphased or unpolarized data

Analysis of population genetic data often includes the search for genomic regions with signs of recent positive selection. One of the approaches involves the concept of Extended Haplotype Homozygosity (EHH) and its associated statistics. These statistics typically need phased haplotypes and, some of them, polarized variants. Here, we unify and extend previously proposed modifications to loosen these requirements. We compare the modified versions with the original ones by measuring the False Discovery Rate in simulated whole-genome scans and quantifying the overlap of inferred candidate regions in empirical data. We find that phasing information is indispensable for the accurate estimation of within-population statistics for all but very large samples and of cross-population statistics for small samples. Ancestry information, in contrast, is of lesser importance for both. Our publicly available R package rehh incorporates the modified statistics presented here.

From Microorganisms to Biosignatures: Subcritical Water Extraction as a Sample Preparation Technique for Future Life Detection Missions

Data for all figures included in "From Microorganisms to Biosignatures:  Subcritical Water Extraction as a Sample Preparation Technique for Future Life Detection Missions". Amino acid concentrations, enantiomeric excesses, and relative distributions for E. coli cells and B. subtilis spores after subcritical water extraction for 30 min at 200 °C using water and dilute acid.

artificial dataset of small engine parts for object detection-segmentation

This dataset contains images and masks of parts used in engine assembly. The images were generated artificially from CAD models using gazebo simulator. The dataset consists of three classes: Large Bolt, Small Bolt and Rocker Arm. Annotations are represented as mask images with the same name as corresponding RGB images. 1080 images for each class, 3240 images total. Resolution of each image: 640x480 pixels. CAD models for each part are also included.

Pupil dilation during orienting of attention and conscious detection of visual targets in patients with left spatial neglect

Right Brain-Damaged patients (RBD) with left spatial neglect (N+), are characterised by deficits in orienting and re-orienting attention to stimuli in the contralesional left side of space. In a recent ERPs study with visual stimuli (Lasaponara et al., 2018) we have pointed out that the pathological attentional bias of N+ is matched with exaggerated novelty reaction and contextual updating of targets in the right ipsilesional space and reduced novelty reaction and contextual updating of targets in the left contralesional space. To characterise further the attentional performance of N+, here we measured Pupil Dilation (PDil), which is a reliable marker of noradrenergic-locus coeruleus activity and response to unexpected events/rewards. Compared to Neutral and Valid targets, N+ patients displayed a pathological reduction of PDil in response to infrequent Invalid targets in the left side of space, while in Healthy Controls (HC) and RBD without neglect (N-) the same targets enhanced PDil with respect to Neutral and frequent Valid targets. Invalid targets in the right side of space enhanced PDil in all experimental groups. Interestingly, both N- and N+ showed a consistent number of target omissions both in the left and right side of space. With respect to seen targets, N- showed reduced PDil in response to unseen targets both in the left and right side of space. In contrast, N+ had reduced PDil in response to unseen targets in the left side of space though not in the right side, where seen and unseen targets evoked comparable levels of PDil. These results disclose, for the first time, the PDil correlates of spatial attention in left spatial neglect and suggest that the pathological attentional bias suffered by N+ might enhance the autonomic responses reflected in PDil to unseen ipsilesional stimuli. This enhancement can contribute to biasing contextual updating and predictive coding of stimuli in the ipsilesional space, thus worsening the pathological attentional bias of N+.

Data Set of Thesis on Architectural Data Flow Analysis for Detecting Violations of Confidentiality Requirements

The data set contains the results of the validation, the docker image for conducting the validation and the source code of all developed projects to conduct the validation.

A benchmarking dataset for peak detection methods in untargeted metabolomics using LC/HRMS

Randomly selected 20,000 mz and rt pairs were manually evaluated for true positive and true negative signals in a single LC/HRMS data file (003.mzML) from the study MTBLS1684. The data file was processed using four peak detection methods - IDSL.IPA, XCMS, MZMINE and MSDIAL.

opencc-by-4.0Jul 2021View details →

Data for "An Ensemble-Based Statistical Methodology to Detect Differences in Weather and Climate Model Executables" Part 1/2

Ensemble simulations from the weather and climate model COSMO. The data has been used for model verification cases in the corresponding paper (https://doi.org/10.5194/gmd-2021-248). The data is partitioned into the following parts: <ol> <li>gpu_dycore.tar.gz 5-day ensemble (600 members) produced with COSMO 5.09 GPU version in double precision.</li> <li>cpu_nodycore.tar.gz 5-day ensemble (200 members) produced with COSMO 5.09 CPU version in double precision.</li> <li>gpu_dycore_sp.tar.gz 5-day ensemble (200 members) produced with COSMO 5.09 GPU version in single precision.</li> </ol> The second part of the dataset with the diffusion ensembles can be found here: https://doi.org/10.5281/zenodo.6355647

opencc-by-4.0Mar 2022View details →

On the Detection of Performance Regression Introducing Code Changes: Experience from the Git Project

This is the dataset and source code of the paper: On the Detection of Performance Regression Introducing Code Changes: Experience from the Git Project The STEP-1-AND-2 folder is for doig things on digitalocean The STEP-3 folder is for running lizard on each commit The STEP-4 folder is for basically everything else "messing-with-understand" is the code i used to run understand on every commit "nn" is the code i used when toying with neural nets instead of perphecy

opencc-by-4.0Mar 2022View details →

Research Artifacts - An Anomaly-based Approach for Detecting Modularity Violations on Method Placement

This record contains research artifacts of our paper. The description of each file is as follows. <ul> <li>case_study.xlsx: a spreadsheet that contains a list of our detected cases and results of our manual inspection</li> <li>java-large+.tar.gz: a preprocessed dataset used for training our detection model</li> <li>model_parameters.ckpt.gz: trained parameters and a word dictionary of our neural network model</li> <li>src.tar.gz: source code of our neural network model written in Python and a dataset preprocessor written in Java</li> </ul>

openother-ncMar 2022View details →

syslrn: Learning What to Monitor for Efficient Anomaly Detection [Dataset]

This repository includes the dataset for the paper: <a href="http://doi.org/10.1145/3517207.3526979">D. Sanvito, G. Siracusano, S. Santhanam, R. Gonzalez, R. Bifulco</a> <a href="http://doi.org/10.1145/3517207.3526979">syslrn: Learning What to Monitor for Efficient Anomaly Detection </a> <a href="http://doi.org/10.1145/3517207.3526979">ACM EuroMLSys 2022</a> The dataset contains two directories at the root level: <ul> <li>raw_dataset</li> <li>processed_dataset</li> </ul> Each folder in the raw_dataset directory contains the raw monitoring data used to generate the graph associated to a single experiment together with additional metadata files. Each folder in the processed_dataset directory contains the graph associated to a single experiment as a set of three CSV files: two for the graph edges (pid_childof_pid_df.csv and pid_speakswith_pid_df.csv) and one for the graph nodes (proc_df.csv). We provide below a code snippet to parse a graph from processed_dataset directory. In both folders the name of each sub-folder is based on the following schema: [SCENARIO]_[W]wl/test_[TEST_ID] where: <ul> <li>[SCENARIO] reports the target component for the failure injection (cinder_failure, neutron_failure, nova_failure). ff  indicates instead a failure-free execution</li> <li>[W] reports the number of concurrent workloads</li> <li>[TEST_ID] reports the ID of the specific failure scenario injected (same ID selected by the OpenStack failure injection framework [1] )</li> </ul> Each experiment includes the following data in the raw_dataset sub-folders: <ul> <li>audit_raw_logs_[TEST_ID]/: raw audit monitoring data</li> <li>bpf_tools_[TEST_ID]/: raw ebpf tools monitoring data</li> <li>instance-[INSTANCE_ID]/: workload-specific metadata files, e.g. stdout/stderr (generated by the OpenStack failure injection framework [1] )</li> <li>logs_workload_[TEST_ID]/: OpenStack application logs</li> <li>perf_tools_[TEST_ID]/: raw perf tools monitoring data</li> <li>audit_filtered_[TEST_ID].log: audit data pre-processed by ausearch (e.g. numerical entities are resolved to symbols)</li> <li>failure_[TEST_ID].info: metadata information about the specific failure scenario (generated by the OpenStack failure injection framework [1] )</li> <li>timestamps_[TEST_ID]: timing information</li> </ul> [1] D. Cotroneo, L. De Simone, P. Liguori, R. Natella, N. Bidokhti - How Bad Can a Bug Get? An Empirical Analysis of Software Failures in the OpenStack Cloud Computing Platform [ACM ESEC/FSE 2019]   Example: parsing a graph from processed_dataset directory <pre><code class="language-python">import pandas as pd import networkx as nx def parse_csv(path): processes_df = pd.read_csv('%sproc_df.csv' % path, index_col=0).reset_index(drop=True) speakswith_edges_df = pd.read_csv('%spid_speakswith_pid_df.csv' % path, index_col=0) speakswith_edges_df['type'] = 'speaksWith' childof_edges_df = pd.read_csv('%spid_childof_pid_df.csv' % path, index_col=0) childof_edges_df['type'] = 'childOf' return processes_df, pd.concat([speakswith_edges_df, childof_edges_df], ignore_index=True) def make_graph(nodes_df, edges_df): G = nx.MultiGraph() for _, node in nodes_df.iterrows(): G.add_node(node.pid, **node) for _, edge in edges_df.iterrows(): G.add_edge(edge.pid1, edge.pid2, type=edge.type) return G PATH = 'processed_dataset/ff_1wl/test_1/' nodes_df, edges_df = parse_csv(PATH) G = make_graph(nodes_df, edges_df) nx.draw_networkx(G, node_size=10, with_labels=False)</code></pre>   If you use this dataset for your research, please cite the following paper: <pre><code>@inproceedings{sanvito2022syslrn, title={syslrn: Learning What to Monitor for Efficient Anomaly Detection}, author={Sanvito, Davide and Siracusano, Giuseppe and Santhanam, Sharan and Gonzalez, Roberto and Bifulco, Roberto}, booktitle={2nd European Workshop on Machine Learning and Systems (EuroMLSys '22)}, year={2022}, address = {Rennes, France}, publisher = {ACM}, month = apr, } </code></pre>

opencc-by-4.0Jan 2022View details →

BotHunter: An Approach to Detect Software Bots in GitHub

Contains the oracle and BIMAN's output.

openodc-byMar 2022View details →

VWFP: Virtual World Fallen People Dataset for Visual Fallen People Detection

A synthetic dataset for visual fallen people detection comprising images extracted from the highly photo-realistic video game Grand Theft Auto V developed by Rockstar North. Each image is labeled by the game engine providing bounding boxes and statuses (fallen or non-fallen) of people present in the scene. The dataset comprises 6,071 synthetic images depicting 7,456 fallen and 26,125 non-fallen pedestrian instances in various looks, camera positions, background scenes, lightning, and occlusion conditions.

opencc-by-4.0Mar 2022View details →

First Detection of the Pekeris Internal Global Atmospheric Resonance: Evidence from the 2022 Tonga Eruption and from Global Reanalysis Data

The numerical model simulation data necessary to reproduce figures in our paper submitted to the Journal of the Atmospheric Sciences.

opencc-zeroApr 2022View details →

Data from: A new composite abundance metric detects stream fish declines and community homogenization during six decades of invasions

Aim: We developed a new technique, utilizing species-specific counts of individuals from historical fish community samples, to examine landscape-level, spatiotemporal trends in relative abundance distributions. Abundance-based historical distribution analyses are often plagued by data comparability issues, but provide critical information about community composition trends inaccessible to those using analyses based only on species presence-absence. We established trends in native and non-native fish abundance and community homogenization, uniqueness, and diversity to help local conservation managers prioritize targets and motivate similar studies globally to support fish conservation. Location: Upper and middle New River (UMNR) basin, Appalachian Mountains, USA. Methods: We compiled catch data from 61 years of fish community surveys (1958-2019) and tested for community homogenization by comparing data from repeatedly sampled sites (1900s versus 2000s samples) using dispersion analyses. We measured community uniqueness (site contributions to beta diversity) and species diversity (Shannon index) at sampled streams to identify potential conservation hotspots. We then used regression analyses and Wilcoxon signed-rank tests to examine species-specific basin-wide and local abundance trends and identify species of potential conservation concern. Results: Dispersion of sites in species-abundance space was significantly greater in the 1900s compared to the 2000s, indicating homogenization had occurred. Of 36 native species analyzed, 44.4% (16) showed basin-wide declines. Non-native species exhibited mixed patterns; site-level abundance increased in 2 of 15 species analyzed (13%). Main conclusions: Our results indicate basin-wide community homogenization has occurred within the UMNR, but many unique and diverse communities persist. If conserved, these could help maintain regional fish diversity. We found basin-wide declines in four endemic species, as well as spread patterns of non-native and native species that were not detected by a presence-absence analysis applied within the same study area. This finding illustrates the importance of considering both species' abundance and occurrence patterns as separate dimensions of biodiversity to inform conservation planning.

opencc-zeroApr 2022View details →

Detection of Khapra Beetle environmental DNA using portable technologies in Australian biosecurity

Khapra beetle, Trogoderma granarium Everts, 1898, is a serious pest of stored grain products globally. Environmental DNA (eDNA)-based methods offer sensitive detection tools used to inform biosecurity officers on the presence of high-risk pests. This study tested laboratory and portable molecular technologies to detect khapra beetle environmental DNA extracted from dust samples collected during biosecurity responses (Tuggeranong and Fyshwick) to khapra beetle incursions in Australia. Airborne and floor dust samples were collected opportunistically using handheld vacuum cleaners and eDNA was extracted using either field or laboratory-based extraction methods and analyzed using laboratory benchtop real time PCR machines and portable machines with two TaqMan and one LAMP-based assay. We successfully collected, extracted, and amplified khapra beetle eDNA from dust samples by qPCR, but failed to amplify T. granarium eDNA using LAMP. The Laboratory qPCR machine showed significantly higher mean Ct values (p &lt; 0.001) and significantly higher positive detections for both assays (p &lt; 0.001) compared to the portable thermocycler. DNA yield was significantly higher in samples extracted using laboratory-based kits compared to field kits (p &lt; 0.001) for both vacuumed and airborne samples (Mean DNA ± S.D. = 5.52 ± 4.45 and 4.77 ± 1.68 ng/μL, respectively), compared to field kits, (1.75 ± 1.17 and 1.36± 1.29 ng/μL for vacuumed and airborne samples, respectively). There were no significant differences in DNA yield between collection methods or differences in amplification associated to extraction or collection methods in either platform tested in this study. Portable technologies tested in this study (Franklin™ Real Time Thermocycler and Genie III) accurately amplified all tissue derived DNA during assay optimisation and field testing, highlighting the capacity of these technologies to complement biosecurity in confirming specimen ID. There was a high incidence of positive detections in field negative controls (Tuggeranong = 12.3 % and Fyshwick = 50 %), mostly attributed to the use of contaminated vacuum cleaners. We discuss suitable methods to minimize sample cross-contamination, the potential of portable molecular technologies as tools for biosecurity applications, and the suitability of eDNA-based molecular detection methods to complement global trade biosecurity for one of the most invasive and important grain pests worldwide.

opencc-zeroMay 2022View details →

Ancient geological dynamics impact neutral biodiversity accumulation and are detectable in phylogenetic reconstructions

Aim Landmasses have been continuously modified by tectonic activity, the breakup and collision of landmasses is thought to have generated or suppressed ecological opportunities, altering the rates of speciation, dispersal and extinction. However, the extent to which the signatures of past geologic events are retained in modern biodiversity patterns - or obliterated by recent ecological dynamics - remains unresolved. We aim to identify the fingerprint of different scenarios of geological activity on phylogenetic trees and geographic range size distributions. Location Global. Time period Geological time. Major taxa studied Theoretical predictions for any taxa. Methods We conducted spatially explicit simulations under a neutral model of range evolution, speciation and extinction for three different geological scenarios that differed in their geological histories. We set a limit in the number of populations that locally can coexist which along with the geographic boundaries of landmasses, influences the rate of range expansion. Results Our results demonstrate regions of similar size, age and ecological limits will differ in richness and macroevolutionary patterns based solely on the geological history of landmass breakup-collision even in the absence of species' ecological differences i.e., neutrality. When landmasses collide, regional richness is higher, lineages exhibit more similar rates of speciation and phylogenetic trees are more balanced than in the geologically static scenario. Stringent local limits to coexistence yield lower regional diversity but in general do not affect our ability to distinguish geological scenarios. Main conclusions These findings provide an alternative explanation for existence of some hotspots of diversity in areas of high geological activity. Although a limit in the number of coexisting species largely influences regional diversity, its contribution to phylogenetic patterns is lower than variation in per-capita rates of speciation and extirpation. Importantly, these findings demonstrate the potential for inferring past geological history from distributions of phylogenies and range sizes.