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FIGURES 9–12. Tamarixia dahlsteni. 9. Habitus, female. 10. Forewing, female. 11. Antenna, female. 12 in Two new species of Ta m a r i x i a (Hymenoptera: Eulophidae) from Chile and Australia, established as biological control agents of invasive psyllids (Hemiptera: Calophyidae, Triozidae) in California
FIGURES 9–12. Tamarixia dahlsteni. 9. Habitus, female. 10. Forewing, female. 11. Antenna, female. 12. Head and antennae, male.
When do agents outperform centralized algorithms? - A systematic empirical evaluation in logistics - datasets and results v1.1.0
<p>This directory contains the data and results that were used and obtained during the realization of the following paper:</p> <p>When do agents outperform centralized algorithms? - A systematic empirical evaluation in logistics. Rinde R.S. van Lon and Tom Holvoet. Journal of Autonomous Agents and Multi-Agent Systems (2017).</p> <p>This is version v1.1.0. At the time of writing the paper is not yet accepted, some of the details (e.g. title, date of publication) are subject to change. The code that has been used can be found in this repository: https://github.com/rinde/vanLon17-JAAMAS-code </p> <p>This directory has the following structure:</p> <p>- makefile - script that can be used to run the analyses. The most important commands are:<br> - all - runs all analyses.<br> - paper-deps - runs only the analyses that were directly used in the paper.<br> - additional-analysis - runs several additional analyses.</p> <p>- readme.txt - this file.</p> <p>- results - contains all R-scripts used to analyse the data<br> - data/main - contains the results of the main result.<br> - data/mas-tuning - contains the results of the MAS tuning experiments.<br> - data/optaplanner-tuning-gendreau - contains the results of the OptaPlanner tuning experiments.<br> - data/sensitivity - contains the results of the simulator sensitivity experiments (using OptaPlanner algorithms).</p> <p>- scenarios<br> - gendreau2006 - contains the dataset from the Gendreau et al. [1] paper, used for the OptaPlanner tuning experiments.<br> - mas-tuning-dataset - contains the dataset that was used for tuning the MAS. This was generated using the code from https://github.com/rinde/vanLon17-JAAMAS-code<br> - vanLonHolvoet15-adapted-to-4-hours - contains the dataset that was used for the main experiment. This is an adapted version of the dataset from [2]. This version has a duration of 4 hours and requires a real-time simulator. It was generated using the code from https://github.com/rinde/vanLon17-JAAMAS-code </p> <p>[1] Michel Gendreau, Francois Guertin, Jean-Yves Potvin, and René Séguin. Neighborhood search heuristics for a dynamic vehicle dispatching problem with pick- ups and deliveries. Transportation Research Part C: Emerging Technologies, 14 (3):157–174, 2006. ISSN 0968090X. doi:10.1016/j.trc.2006.03.002.</p> <p>[2] Rinde R. S. van Lon and Tom Holvoet. Towards systematic evaluation of multi-agent systems in large scale and dynamic logistics. In Qingliang Chen, Paolo Torroni, Serena Villata, Jane Hsu, and Andrea Omicini, editors, PRIMA 2015: Principles and Practice of Multi-Agent Systems: 18th International Conference, Bertinoro, Italy, October 26-30, 2015, Proceedings, pages 248–264. Springer In- ternational Publishing, Cham, 2015. ISBN 978-3-319-25524-8. doi:10.1007/978- 3-319-25524-8 16.</p>
FIGURES 24‒27 in Description of the mature larva and pupa of Anthonomus santacruzi Hustache (Coleoptera, Curculionidae), a biological control agent of Solanum mauritianum Scop. (Solanaceae), and remarks about its biology
FIGURES 24‒27. Field photos of Anthonomus santacruzi and Solanum mauritianum: 24—A. santacruzi on S. mauritianum inflorescence, 25, 26—S. mauritianum inflorescences exhibiting A. santacruzi damaged (brown) buds, 27—S. mauritianum with inflorescences in the field.
FIGURES 20‒23 in Description of the mature larva and pupa of Anthonomus santacruzi Hustache (Coleoptera, Curculionidae), a biological control agent of Solanum mauritianum Scop. (Solanaceae), and remarks about its biology
FIGURES 20‒23. Anthonomus santacruzi, pupa: 20, 21—head and pronotum (20—ventral, 21—lateral), 22—dorsal chaetotaxy, 23a, b—terminalia, ventral (a—female, b—male), ur—urogomphus, setae: as—apical, d—dorsal, ds—discal, l— lateral, os—orbital, pas—postantennal, pls—posterolateral, rs—rostral, sls—superlateral, vs—vertical.
FIGURES 14–16 in Description of the mature larva and pupa of Anthonomus santacruzi Hustache (Coleoptera, Curculionidae), a biological control agent of Solanum mauritianum Scop. (Solanaceae), and remarks about its biology
FIGURES 14–16. Anthonomus santacruzi, mature larva, mouth parts: 14—maxillolabial complex, ventral, 15a, b—left maxillia and part of praelabium (a—dorsal side, b—ventral side), 16—maxillae and prelabium, sn—sensillium, setae: dmsdorsal malar, ligs—ligular, mbs—malar basiventral, mxps—maxillary palps, pfs—palpiferal, prms—prelabial, pms—postlabial, stps—stipal, vms—ventral malar.
FIGURES 17‒19 in Description of the mature larva and pupa of Anthonomus santacruzi Hustache (Coleoptera, Curculionidae), a biological control agent of Solanum mauritianum Scop. (Solanaceae), and remarks about its biology
FIGURES 17‒19. Anthonomus santacruzi, pupa: 17—ventral, 18—dorsal view, 19—lateral, Th1–3—pro-, meso- and metathorax, Abd1–9—abdominal segments I̅IX, ur—urgomphus.
FIGURES 12, 13 in Description of the mature larva and pupa of Anthonomus santacruzi Hustache (Coleoptera, Curculionidae), a biological control agent of Solanum mauritianum Scop. (Solanaceae), and remarks about its biology
FIGURES 12, 13. Anthonomus santacruzi, mature larva, mouthparts: 12—clypeus, labrum, and epipharynx (a—dorsal side, b, c—ventral side), 13—left mandible, clss—clypeal sensorium, esc—epipharynx sensillium clusters, lr—labral rods, snpsensory pore, setae: als—anterolateral, ams—anteromedial, cls—clypeal, lms—labral, mds—mandibular, mes—median.
FIGURES 4‒9 in Description of the mature larva and pupa of Anthonomus santacruzi Hustache (Coleoptera, Curculionidae), a biological control agent of Solanum mauritianum Scop. (Solanaceae), and remarks about its biology
FIGURES 4‒9. Anthonomus santacruzi, mature larva, chaetotaxy: 4, 6, 8—thorax and abdominal segment I, 5, 7, 9— abdominal segments V̅X, 4, 5—dorsal, 6, 7—lateral, 8, 9—ventral. Th1–3—pro-, meso- and metathorax, Abd1–9— abdominal segments I̅IX, setae: as—alar, ds—dorsal, eps—epipleural, eus—eusternal, lsts—laterosternal, pda—pedal, pds— postdorsal, prns—pronotal, prs—prodorsal, ps—pleural, sps—spiracular, sts—sternal.
FIGURES 10, 11 in Description of the mature larva and pupa of Anthonomus santacruzi Hustache (Coleoptera, Curculionidae), a biological control agent of Solanum mauritianum Scop. (Solanaceae), and remarks about its biology
FIGURES 10, 11. Anthonomus santacruzi, mature larva: 10—head, 11—antenna. HH—head height, HW—head width, ststemmata, Se—sensorium, sensiliae: sa—apullacea, sb—basiconium, ss—styloconium, setae: des—dorsal epicranial, fs— frontal, les—lateral epicranial, pes—postepicranial, ves—ventral.
Figs. 10–12 in New Information About the Cypress Weevil,Eudociminus mannerheimii(Boheman, 1836) (Coleoptera: Curculionidae: Molytinae): Redescription, Range Expansion, New Host Records, and Report as a Possible Causative Agent of Tree Mortality
Figs. 10–12. Tree damage by Eudociminus mannerheimii. 10) Exit holes; 11) Larval galleries after bark was removed; 12A–B) Larva in situ.
Figs. 7–9 in New Information About the Cypress Weevil,Eudociminus mannerheimii(Boheman, 1836) (Coleoptera: Curculionidae: Molytinae): Redescription, Range Expansion, New Host Records, and Report as a Possible Causative Agent of Tree Mortality
Figs. 7–9. Eudociminus mannerheimii, immature stages and landscape damage. 7) Larva; 8) Pupa; 9) Landscape damage. "X" indicates the same tree in both photographs; A) View left showing one undamaged tree and three minimally damaged trees, B) View right showing three minimally damaged trees and two dead trees.
Figs. 1–6 in New Information About the Cypress Weevil,Eudociminus mannerheimii(Boheman, 1836) (Coleoptera: Curculionidae: Molytinae): Redescription, Range Expansion, New Host Records, and Report as a Possible Causative Agent of Tree Mortality
Figs. 1–6. Eudociminus mannerheimii, adults, dorsal (A) and lateral (B) habitus. 1) Steel Creek, Newton Co., Arkansas; 2) "Univ. of Ark. Student Coll."; 3–4) Phelps Lake, North Carolina; 5) Holly Springs, Wake Co., North Carolina; 6) Gainesville, Alachua Co., Florida. Photograph by Michael C. Thomas. Used with permission. Not to scale.
Datasets for Creative Agents
<ul><li>image_origin.zip: original images with text description for CraftAssist buildings (image-text dataset)</li><li>image_augmented.zip: augmented images for CraftAssist and ISM buildings (image-voxel dataset, image part), "cat image_augmented.zip.* > image_augmented.zip"</li><li>voxel_augmented.zip: augmented voxels in RGB format for CraftAssist and ISM buildings (image-voxel dataset, voxel part)</li><li>voxel2seq.tar.gz: voxel-sequence dataset with 6M steps for augmented CraftAssist buildings</li></ul>
Agent P
Source: Objaverse 1.0 / Sketchfab
Replication Package for ML-EUP Conversational Agent Study
<p>This is the replication package of the paper <a href="https://conf.researchr.org/details/icse-2024/icse-2024-research-track/5/How-to-Support-ML-End-User-Programmers-through-a-Conversational-Agent">How to Support ML End-User Programmers through a Conversational Agent</a>, published at ICSE 2024.</p> <p><strong>Replication Package Files</strong></p> <ul> <li><strong>Readme.pdf:</strong> document that describes the replication package and indicates how to use it. </li> <li> <p><strong>1. Forms.zip: </strong>contains the forms used to collect data for the experiment.</p> </li> <li> <p><strong>2. Experiments.zip: </strong>contains the participants’ and sandboxers’ experimental task workflow with Newton.</p> </li> <li> <p><strong>3. Responses.zip: </strong>contains the responses collected from participants during the experiments.</p> </li> <li> <p><strong>4. Analysis.zip:</strong> contains the data analysis scripts and results of the experiments.</p> </li> <li> <p><strong>5. newton.zip: </strong>contains the tool we used for the WoZ experiment.</p> </li> <li> <p><strong>Interactions.pdf: </strong>explains Figure 4 of the paper in detail by depicting the interactions of P4.</p> </li> <li> <p><strong>TutorialStudy.pdf:</strong> script used in the experiment with and without Newton to be consistent with all participants.</p> </li> <li> <p><strong>Woz_Script.pdf:</strong> script wizard used to maintain consistent Newton responses among the participants.</p> </li> <li><strong>Dockerfile</strong>: docker definition of newton-docker.tar.gz.</li> <li> <p><strong>newton-docker.tar.gz:</strong> docker image that contains both the tool and the analysis files.</p> </li> <li><strong>LICENSE: </strong>license file describing the license of data and code files.</li> </ul> <p> </p> <p><strong>1. Forms.zip</strong></p> <p>The forms zip contains the following files:</p> <ul> <li> <p><strong>Demographics.pdf: </strong>a PDF form used to collect demographic information from participants before the experiments</p> </li> <li> <p><strong>Post-Task Control (without the tool).pdf:</strong> a PDF form used to collect data from participants about challenges and interactions when performing the task without Newton </p> </li> <li> <p><strong>Post-Task Newton (with the tool).pdf:</strong> a PDF form used to collect data from participants after the task with Newton.</p> </li> <li> <p><strong>Post-Study Questionnaire.pdf:</strong> a PDF form used to collect data from the participant after the experiment.</p> </li> </ul> <p> </p> <p><strong>2. Experiments.zip</strong></p> <p>The experiments zip contains two types of folders:</p> <ul> <li> <p><strong>exp[participant’s number]-c[number of dataset used for control task]e[number of dataset used for experimental task]</strong>. Example: exp1-c2e1 (experiment participant 1 - control used dataset 2, experimental used dataset 1)</p> </li> <li> <p><strong>sandboxing[sandboxer’s number].</strong> Example: sandboxing1 (experiment with sandboxer 1)</p> </li> </ul> <p> </p> <p>Every experiment subfolder contains:</p> <ul> <li> <p><strong>warmup.json: </strong>a JSON file with the results of Newton-Participant interactions in the chat for the warmup task.</p> </li> <li> <p><strong>warmup.ipynb: </strong>a Jupyter notebook file with the participant’s results from the code provided by Newton in the warmup task.</p> </li> <li> <p><strong>sample1.csv: </strong>Death Event dataset.</p> </li> <li> <p><strong>sample2.csv: </strong>Heart Disease dataset.</p> </li> <li> <p><strong>tool.ipynb: </strong>a Jupyter notebook file with the participant’s results from the code provided by Newton in the experimental task.</p> </li> <li> <p><strong>python.ipynb: </strong>a Jupyter notebook file with the participant’s results from the code they tried during the control task.</p> </li> <li> <p><strong>results.json:</strong> a JSON file with the results of Newton-Participant interactions in the chat for the task with Newton.</p> </li> </ul> <p> </p> <p>To load an experiment chat log into Newton, add the following code to the notebook:</p> <pre><code>import anachat import json with open("result.json", "r") as f: anachat.comm.COMM.history = json.load(f) </code></pre> <p>Then, click on the notebook name inside Newton chat</p> <p>Note 1: the subfolder for P6 is exp6-e2c1-serverdied because the experiment server died before we were able to save the logs. We reconstructed them using the notebook newton_remake.ipynb based on the video recording.</p> <p>Note 2: The sandboxing occurred during the development of Newton. We did not collect all the files, and the format of JSON files is different than the one supported by the attached version of Newton.</p> <p> </p> <p><strong>3. Responses.zip</strong></p> <p>The responses zip contains the following files:</p> <ul> <li> <p><strong>demographics.csv: </strong>a CSV file containing the responses collected from participants using the demographics form</p> </li> <li> <p><strong>task_newton.csv: </strong>a CSV file containing the responses collected from participants using the post-task newton form.</p> </li> <li> <p><strong>task_control.csv:</strong> a CSV file containing the responses collected from participants using the post-task control form.</p> </li> <li> <p><strong>post_study.csv:</strong> a CSV file containing the responses collected from participants using the post-study control form.</p> </li> </ul> <p> </p> <p><strong>4. Analysis.zip</strong></p> <p>The analysis zip contains the following files:</p> <ul> <li> <p><strong>1.Challenge.ipynb:</strong> a Jupyter notebook file that performs the statistical tests and creates the perceptions of challenges figure.</p> </li> <li> <p><strong>2.Interactions.py: </strong>a Python file that creates the participants’ JSON files.</p> </li> <li> <p><strong>3.Interactions.Graph.ipynb: </strong>a Jupyter notebook file that creates the participant’s interaction figure.</p> </li> <li> <p><strong>4.Interactions.Count.ipynb:</strong> a Jupyter notebook file that counts participants’ interaction with each figure.</p> </li> <li> <p><strong>config_interactions.py:</strong> this file contains the definitions of interaction colors and grouping</p> </li> <li> <p><strong>interactions.json: </strong>a JSON file with the interactions during the Newton task of each participant based on the categorization.</p> </li> <li> <p><strong>requirements.txt: </strong>dependencies required to run the code to generate the graphs and json analysis.</p> </li> </ul> <p> </p> <p>To run the analyses, please follow the steps:</p> <p>1- Extract Analysis.zip and cd into the directory</p> <p>2- Install Python 3.10, and then the analysis dependencies with the following command:</p> <pre><code>pip install -r requirements.txt</code></pre> <p>3- Run Jupyter Notebook/Lab and execute all cells of <strong>1.Challenge.ipynb</strong>. It will generate the challenges figure.</p> <p>4- Run <strong>2.Interactions.py</strong> using the following command:</p> <pre><code>python 2.Interactions.py</code></pre> <p>This file was created manually by individually categorizing each interaction of the participants. The execution will generate the file interactions.json with the graph definitions of the interactions.</p> <p>5- Run Jupyter Notebook/Lab and execute all cells of <strong>3.Interactions.Graph.ipynb</strong>. It will create the interactions graph visualization.</p> <p>6- Run Jupyter Notebook/Lab and execute all cells of <strong>4.Interactions.Count.ipynb</strong>. It will create the interactions table.</p> <p> </p> <p><strong>5. newton.zip</strong></p> <p>The newton zip contains the <strong>source code of the Jupyter Lab extension</strong> we used in the experiments. Read the <strong>README.md</strong> file inside it for instructions on how to install and run it.</p> <p> </p> <p><strong>6. newton-docker.tar.gz</strong></p> <p>This file contains the Docker image with the replication package in a configured environment for both the tool and the dat analyses.</p> <p>To import the image, run:</p> <pre><code><span>docker load <</span> <span>newton-docker.tar.gz</span></code></pre> <p>Then, start the container by running:</p> <pre><code><span>docker run -p 8888:8888 -it newton</span></code></pre> <p>Finally, start Jupyter Lab:</p> <pre><code><span>jupyter lab --collaborative --ip="*" --port=8888 --allow-root</span></code></pre> <p> </p>
A comparison of model-based and model-free agents in solving semi-automatically generated PPDDL problems - Plots
<p>A collection of all plots generated for deriving the conclusions seen in "<span><span>A comparison of model-based and model-free agents in solving semi-automatically generated PPDDL problems</span></span>".</p>
Dataset and SPSS syntax for study 1 paper Implicit Agentic Narcissism
<p>Dataset and SPSS syntax study 1 paper on Implicit Agentic Narcissism.</p>
Conversational Agents in Software Engineering - Replication Package
<p>Replication Package for the research method conducted in the paper "Conversational Agents in Software Engineering"</p>
Data from: A maximalist approach to the systematics of a biological control agent: Gryon aetherium Talamas, sp. nov. (Hymenoptera, Scelionidae)
<p>A morphological and molecular analysis of <em>Gryon</em> Haliday (Platygastroidea, Scelionidae) was conducted to provide a taxonomic and phylogenetic context for a species under evaluation as a biological control agent of <em>Bagrada hilaris</em> (Burmeister) (Hemiptera, Pentatomidae). Our analysis revealed that <em>Gryon</em> is polyphyletic and that the biological control agent is not <em>G. gonikopalense</em>, a name that was tentatively applied to this species in 2019. We here describe this species as new, <em>Gryon aetherium</em> Talamas sp. nov., and resurrect the generic name <em>Hadronotus</em> Förster. Morphological characters that delimit our concepts of <em>Gryon</em> and <em>Hadronotus</em> are presented. Based on morphological characters and multilocus phylogenies, we determined that five presently valid scelionid genera belong within <em>Gryon</em>. In total, 15 species are transferred into <em>Gryon</em> from these genera, 215 species are transferred from <em>Gryon</em> to <em>Hadronotus</em>, and 6 species are transferred from <em>Gryon</em> to <em>Dyscritobaeus</em> Perkins. Specimens collected during field studies in California and reevaluation of specimens determined as <em>G. myrmecophilum</em> in Mexico reveal that <em>G. aetherium</em> is adventive in North America.</p>
Table A6 images from Computer-aided drug design (CADD) to de-orphanise marine molecules: Finding potential therapeutic agents for neurodegenerative and cardiovascular diseases
<p>High Reslution Images from Table A6</p>
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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.