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478 results for “artifact”
Data from: Fine-scale landscape genetics of the American badger (Taxidea taxus): disentangling landscape effects and sampling artifacts in a poorly understood species
Landscape genetics is a powerful tool for conservation because it identifies landscape features that are important for maintaining genetic connectivity between populations within heterogeneous landscapes. However, using landscape genetics in poorly understood species presents a number of challenges, namely, limited life history information for the focal population and spatially biased sampling. Both obstacles can reduce power in statistics, particularly in individual-based studies. In this study, we genotyped 233 American badgers in Wisconsin at 12 microsatellite loci to identify alternative statistical approaches that can be applied to poorly understood species in an individual-based framework. Badgers are protected in Wisconsin owing to an overall lack in life history information, so our study utilized partial redundancy analysis (RDA) and spatially lagged regressions to quantify how three landscape factors (Wisconsin River, Ecoregions and land cover) impacted gene flow. We also performed simulations to quantify errors created by spatially biased sampling. Statistical analyses first found that geographic distance was an important influence on gene flow, mainly driven by fine-scale positive spatial autocorrelations. After controlling for geographic distance, both RDA and regressions found that Wisconsin River and Agriculture were correlated with genetic differentiation. However, only Agriculture had an acceptable type I error rate (3–5%) to be considered biologically relevant. Collectively, this study highlights the benefits of combining robust statistics and error assessment via simulations and provides a method for hypothesis testing in individual-based landscape genetics.
Artifact for "Diagnosis of Package Installation Incompatibility via Knowledge Base"
<p>This is the artifact for the paper entitled "Diagnosis of Package Installation Incompatibility via Knowledge Base"</p>
XFP-056 bone artifact, Sanak Island, Alaska.
Sea mammal bone artifact, perhaps a plug. Sanak Island, Alaska. CAT# XFP-056-26 XFP-056 is a group of large house depressions on the south shore of Pauloff Harbor, Sanak Island, Alaska. Multiple radiocarbon dates place it from 300 CE to 800 CE, although the upper most levels may date to the 13th century. These artifacts were scanned with either a Faro Edge Arm or a Minolta Vivid 9i. Processed in Geomagic or Polyworks. 4-8 photos were used for texture in ZBrush. The Sanak Island artifacts are presented as a result of the research conducted under grants NSF 0326584, NSF 0508101, NSF 1139266, NSF 1321411. H. Maschner, Principal Investigator. Original digitizing work done at the IVL at Id. St. Univ. Subsequent processing completed at Global Digital Heritage. Fieldwork and analysis done with the permission and collaboration of the Pauloff Harbor Tribe and the Sanak Corporation Source: Objaverse 1.0 / Sketchfab
77-47-T260 Ivory Artifact, Hot Springs Village
Ivory Artifact, Hot Springs Village, Port Moller, Alaska CAT# 77-47-T260 Okada excavations HHT, Level 5C. Hot Springs 1B. 1600-1300 BCE. The Hot Springs site is a massive village on the shore of Port Moller, on the Alaska Peninsula side of the southern Bering Sea. It was excavated by several different teams over the last 100 years. The main occupations are from 2000 BCE-1000 BCE, and from 100 CE to 800 CE. The Hot Springs artifacts are presented as a result of the research conducted under grants NSF 0137756, NSF 1204020, NSF 1139266, and NSF 1321411. H. Maschner, Principal Investigator. Original digitizing work done at the IVL at Id. St. Univ. Subsequent processing completed at Global Digital Heritage. Source: Objaverse 1.0 / Sketchfab
UNCW Archaeology Lab Artifact of the Week #1
UNCW Archaeology Lab Artifact of the Week #1 2021 Source: Objaverse 1.0 / Sketchfab
Archaeology artifact 1
An archaeological lintel from an unknown place in Asia. Size about 1m. Made with Reality Capture (16 pictures). Source: Objaverse 1.0 / Sketchfab
77-47-Q414 Barbed Artifact, Hot Springs Village
Barbed Bone Artifact, Harpoon Section, part of composite, Hot Springs Village, Port Moller, Alaska CAT# 77-47-Q414 Okada excavations HHQ, Level 4-15 Hot Springs 11B. 1600-1300 BCE The Hot Springs site is a massive village on the shore of Port Moller, on the Alaska Peninsula side of the southern Bering Sea. It was excavated by several different teams over the last 100 years. The main occupations are from 2000 BCE-1000 BCE, and from 100 CE to 800 CE. The Hot Springs artifacts are presented as a result of the research conducted under grants NSF 0137756, NSF 1204020, NSF 1139266, and NSF 1321411. H. Maschner, Principal Investigator. Original digitizing work done at the IVL at Id. St. Univ. Subsequent processing completed at Global Digital Heritage. Source: Objaverse 1.0 / Sketchfab
UNCW Artifact of the Week #4
Artifact of the Week #4 UNCW Archaeology Lab 2021 Source: Objaverse 1.0 / Sketchfab
XFP-056-27 Bone artifact, Sanak Island, Alaska.
Bone artifact, Sanak Island, Alaska. CAT# XFP-056-27 XFP-056 is a group of large house depressions on the south shore of Pauloff Harbor, Sanak Island, Alaska. Multiple radiocarbon dates place it from 300 CE to 800 CE, although the upper most levels may date to the 13th century. These artifacts were scanned with either a Faro Edge Arm or a Minolta Vivid 9i. Processed in Geomagic or Polyworks. 4-8 photos were used for texture in ZBrush. The Sanak Island artifacts are presented as a result of the research conducted under grants NSF 0326584, NSF 0508101, NSF 1139266, NSF 1321411. H. Maschner, Principal Investigator. Original digitizing work done at the IVL at Id. St. Univ. Subsequent processing completed at Global Digital Heritage. Fieldwork and analysis done with the permission and collaboration of the Pauloff Harbor Tribe and the Sanak Corporation Source: Objaverse 1.0 / Sketchfab
FIGURE 4. Cuticular structures and artifacts. A in Considerations on the genus Gordius (Nematomorpha, horsehair worms), with the description of seven new species
FIGURE 4. Cuticular structures and artifacts. A. Scars on the surface of G. aquaticus from Germany (SR 952). B. The mixture of smooth and otherwise structured surface may be due to erostion (undetermined Gordius specimen from Italy; SR 1367). C. Cuticular surface structure in an undetermined Gordius specimen from Germany; SR 1031). D. Smooth and rough structure of the cuticle in G. z w i c k i sp. nov. (holotype ZMH V13275). E. Cross section of the cuticle (cut) with layers of fibres. Below cuticle are epidermis (epi), longitudinal musculature (mus) and parenchyme (par) (G. helveticus sp. nov., paratype ZMH V13277). F. "Rhomboidal pattern" on the cuticle created by the underlying arrangement of cuticular fibres (G. aquaticus from Germany, SR 995).
FIGURES 15–18. Immature artifacts. 15 in Two new species of clearwing moths (Lepidoptera: Sesiidae) from Taiwan
FIGURES 15–18. Immature artifacts. 15. Galls induced by infection of Ceratocorema woodstocki Liang & Hsu sp. nov. immature on stem of Viburnum luzonicum. 16. Mature larva of Ceratocorema woodstocki Liang & Hsu sp. nov. in gallery of V. luzonicum, exposed. 17. Swelling of Trichosanthes quinquangulata stem by the presence of Melittia tao Liang & Hsu sp. nov. larva, with slit covered by frass. 18. Cocoon of Melittia tao Liang & Hsu sp. nov.. made from sand grains.
Artifact of the paper "An Empirical Investigation on the Challenges in Scientific Workflow Systems Development"
<p><strong><span>Scientific Workflow Systems (SWSs)</span></strong><span> play a critical role in the contemporary scientific landscape, significantly enriching research endeavors by augmenting productivity and fostering collaboration</span><span>, SWSs</span><span> elevate the standard of scholarly inquiry, fortifying its pillars of reproducibility and ethical adherence. Essentially, they </span><span>serve as</span><span> the bedrock upon which efficient, transparent, and impactful research </span><span>is built</span><span>, propelling knowledge and innovation across diverse fields. SWSs accomplish mundane yet essential tasks intrinsic to scientific inquiry—ranging from data acquisition to analysis and reporting. By liberating researchers from the shackles of manual labor, SWSs enable them to channel their energies toward more intellectually demanding pursuits, thereby enhancing the pace and quality of research outcomes. Moreover, SWSs wield a formidable influence in standardizing workflows across research cohorts, instilling a sense of uniformity in experimental methodologies and data-handling practices. This standardization not only cultivates a culture of rigor and coherence but also fosters cross-disciplinary dialogue and collaboration.</span></p> <p>Integral to the operation of SWSs is their capacity to integrate diverse tools, software, and data sources, effectively functioning as centralized hubs for research management. This integration expedites the research process and facilitates seamless data exchange and interoperability—a pivotal asset in an era characterized by the deluge of data and the imperative of interdisciplinary collaboration. Furthermore, SWSs afford researchers and project managers real-time insights into the progress of research endeavors, empowering them to identify bottlenecks, allocate resources judiciously, and optimize workflow execution. This granular oversight enhances project transparency and accountability and serves as a catalyst for informed decision-making.</p> <p>Crucially, SWSs are engineered to accommodate the complexities inherent in scientific inquiry, adeptly handling vast volumes of data and supporting parallel processing to meet the evolving demands of research projects. This scalability underscores their adaptability to diverse research paradigms, ensuring their relevance across a spectrum of scientific disciplines. Facilitating collaboration across geographic and temporal divides, SWSs offer a suite of collaborative features—including version control, shared workspaces, and communication tools—that transcend the constraints of physical proximity. By fostering a culture of inclusivity and knowledge exchange, SWSs catalyze innovation and synergy among distributed research teams.</p> <p>Moreover, SWSs serve as custodians of reproducibility, meticulously documenting each facet of the research workflow—from data sources to analysis methods—thus safeguarding the integrity of scientific inquiry. This commitment to transparency and methodological rigor underpins the credibility of research findings, engendering trust within the scientific community and beyond. The customizable nature of SWSs empowers research teams to tailor their workflows to suit their unique needs and preferences, further amplifying their utility and versatility. In essence, SWSs emerge not merely as tools of convenience but as indispensable allies in the relentless pursuit of scientific excellence.</p> <p>Numerous developers actively participate in the advancement of SWSs through diverse roles, including designing system architectures to ensure flexibility and performance, developing algorithms for data processing and analysis, crafting user-friendly interfaces, handling backend logic, integrating with external tools, and ensuring quality, security, and compliance. They address challenges such as optimizing performance and scalability by leveraging parallel processing and distributed computing techniques. To tackle these diverse tasks, developers encounter numerous challenges, often turning to crowd-sourced platforms like Stack Overflow and GitHub to discuss and address them. Stack Overflow serves as a vital resource for developers to seek solutions, learn new technologies, validate best practices, and engage with the programming community. Similarly, GitHub facilitates collaborative development by allowing developers to report problems, propose enhancements, and contribute to open-source projects. Our research draws insights from Stack Overflow discussions, GitHub issues, and pull request reports related to SWSs, reflecting the dynamic and collaborative nature of software development in this domain.</p>
Dataset for paper: Research Artifacts in Secondary Studies: A Systematic Mapping in Software Engineering
Open the record for dataset details and reuse information.
CiDiff Artifact
<h2>CiDiff Artifact</h2> <ul> <li>The source code of the CiDiff program and its analysis (also available at https://github.com/labri-progress/cidiff and https://github.com/labri-progress/cidiff-analysis).</li> <li>A dataset of success-failure pair of CI logs from public repositories on GitHub.</li> </ul> <p> </p> <h2>Licenses:</h2> <ul> <li> <div>Creative Commons Attribution 4.0 International, for the dataset</div> </li> <li>Apache License 2.0, for the code</li> </ul>
Artifacts for the paper "Automated and Complete Generation of Traffic Scenarios at Road Junctions Using a Multi-level Danger Definition"
<div> <div> <div>This deposit contains measurement data and additional artifacts pertaining to the "<em>Automated and Complete Generation of Traffic Scenarios at Road Junctions Using a Multi-level Danger Definition</em>" paper. The deposit is structured as follows:</div> <br> <div>Data pertaining to <strong>RQ1</strong> is found in the <em>baseline-comparison/</em> directory, which contains (1) statistics measured during scenario generation and (2) data analysis results for both our proposed approach (which we name <em>complete</em>) and the baseline <em>Scenic</em> approach, including statistical significance data.</div> <br> <div>Data pertaining to <strong>RQ2-4</strong> and to the following <strong>Discussion</strong> is found in the following three directories.</div> </div> </div> <div> </div> <ul> <li><em>0-generated-scenarios/ </em>contains (1) the generated abstract scenario specifications (i.e. maneuver instance and path region assignments) and (2) concrete scenarios represented in an `xml` format that are executable through the <a href="https://github.com/carla-simulator/scenario_runner">CARLA Scenario Runner</a> framework.</li> <li><em>1-simulation-results/ </em>contains the simulation results for our measurement runs. We include simulation traces, which show the exact position of each actor at each frame, in a human-readable, textual format. We also include result analysis (i.e. pertaining to simulation runtime, outcome, preventive maneuvers, etc.) within `measurements.json` files.</li> <li><em>2-generated-figures/ </em>contains figures derived from the contents of <em>1-simulation-results/</em> (including additional figures not included in the publication).</li> </ul> <div>All the code of the proposed scenario generation approach is implemented as extensions to the <a href="https://github.com/ArenBabikian/concretize">Concretize</a> framework (for scenario generation and analysis), and to the <a href="https://github.com/ArenBabikian/transfuser/tree/complete-gen">Transfuser</a> repository (for simulation). <a href="https://github.com/ArenBabikian/concretize">Concretize</a> is available under the <a href="https://www.eclipse.org/legal/epl-2.0/">Eclipse Public License - v 2.0</a>, while <a href="https://github.com/autonomousvision/transfuser">Transfuser</a> is available under the <a href="https://opensource.org/license/mit">MIT License</a>.</div>
Artifact: Quick Theory Exploration for Algebraic Data Types via Program Transformations
<p>This is the repeatability package, including the tool (called LemmaCalc) in the paper, the benchmark files, a TheSy binary, Z3 binaries for Linux, and scripts to repeat the experiments.</p> <p>Parts of the paper supported by this artifact: Main results in Fig 1, implementation of Algs 1--3.</p>
Artifact for "Efficient Construction of Practical Python Call Graphs with Entity Knowledge Base"
<p>This is the artifact for the paper entitled "Efficient Construction of Practical Python Call Graphs with Entity Knowledge Base"</p>
Artifact Evaluation for "CSAL: the Next-Gen Local Disks for the Cloud" (EuroSys 2024)
<p>This is for Artifact Evaluation of paper "CSAL: the Next-Gen Local Disks for the Cloud" published in EuroSys 2024.</p>
Artifact for An Extensive Empirical Study of Nondeterministic Behavior in Static Analysis Tools
<p>This repository contains data for 'An Extensive Empirical Study of Nondeterministic Behavior in Static Analysis Tools' and the source code of the tool NDDetector that is used for performing the experiments in RQ2.</p><p>There are two directories, data and tool:</p><p><data> contains the data for the conclusion made in the two research questions, RQ1 and RQ2. (rq1 is Research Question 1s data)</p><p>In rq1/ there are:</p><p>final_results.csv - Contains 43 distinct results from 4 repositories (SOOT, WALA, FlowDroid, DroidSafe) that fix or report nondeterminism.</p><p>summary.pdf - Reports the number of nondeterminism results by tool repository at each stage of the qualitative study.</p><p>categorization.pdf - Reports the number of nondeterminism results by root cause categories at each component of analysis codebase in which the nondeterminism takes place</p><p>raw_data.zip - Contains the raw commits and issues extracted from 9 repositories (SOOT, DOOP, WALA, FlowDroid, DroidSafe, AmanDroid, TAJS, Code2Flow, PyCG)</p><p>key_words_results.zip - Contains the results extracted by each keyword (concurrency, concurrent, consistent, determinism, deterministic, different, flakiness, flaky, parallel, thread) from the raw data.</p><p>In rq2/ there are:</p><p>ICSE2024_AGGREGATE_DATA.csv - Contains the result distributions of each combination of target program, configuration hash, and tool aswell as the calculated consistency score.</p><p>analyze_results.py - Script that makes this data.</p><p>node_freqs - Contains the frequency of each node in the nondeterministic results we observed,it also keeps track of whether this particular node is a callee or caller or source/sink.</p><p>edge_dists - Contains the actual edge distributions of all of our results that behaved nondeterministically. it contains, for each result (edge/flow) across repetitions, which repetitions did or did not contain this edge/flow and which did. This means if you are interested in the actual differences across results generated by tool edge_dists/ is the place to look.</p><p>figure_8 - The raw data and occurences per node sheet for generating Figure_8.</p><p><tool> contains the framework and its source code that we used for conducting the experiments as well as the scripts that are used to post-process the detected nondeterminstic behavior and generate the summarized results in Section 4.</p>
crypto-detectors-evaluation-artifacts
<p>The artifacts for the paper "Towards Precise Reporting of Cryptographic Misuses" contain all reported alarms from evaluated detectors, analysis results of labeled alarms, and refined CryptoGuard as well as false positive examples.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.