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3,709 results for “urbanization.”
FIGURES 1–5 in A new species of Malacophagomyia (Malacophagomyia) Lopes, 1966 (Diptera: Sarcophagidae) collected from an urban zone of Southern Colombia
FIGURES 1–5. Malacophagomyia (M.) gaelana Córdoba-Suarez, Ramos-Pastrana & Mulieri, sp. nov. Holotype male. 1, Habitus, left lateral view; 2, Head, fronto-lateral view; 3, Thorax, dorsal view; 4, Wing; 5, Abdomen, dorsal view.
Dataset for: Factors associated with self-reported diagnosed asthma in urban and rural Malawi: observations from a population-based study of 3 non-communicable diseases
<p>This dataset was used in analyses reported on the in paper with the same title, published in PLOS Global Health.</p>
A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.0
<p>This dataset accompanies the GMD article 'A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.0' (https://doi.org/10.5194/egusphere-2024-96).</p> <ul> <li>The input files to run the presented cases using uDALES are contained in 'inputs'.</li> <li>The model outputs are contained in separate folders: 'XCC', 'indoor-outdoor', 'XCB', and 'SEB'. When downloaded, move into a folder called 'outputs' so that the paths defined in the scripts work as intended (see below).</li> <li>The Matlab scripts to plot the figures are contained in 'scripts'.</li> <li>The figures shown in the article are contained in 'figures'.</li> </ul>
Forensic determination of adhesive vinyl microplastics in urban soils
<p>All the pictures used for all the size measurements of microplastics in the work "Forensic determination of adhesive vinyl microplastics in urban soils"</p>
Data for "Elevated urban energy risks due to climate-driven biophysical feedbacks"
<p>This dataset contains the global multi-model urban climate and energy projections from Li et al. (2024), "Elevated urban energy risks due to climate-driven biophysical feedbacks", published in <em>Nature Climate Change</em>. It contains global monthly mean projections of urban 2-meter air temperature, and urban cooling and heating energy fluxes derived from 25 Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6). Details about how this dataset was generated are described in the article. This dataset may be useful for multiple communities interested in future energy risks, climate change impacts and vulnerability, and climate-sensitive adaptation and energy planning.</p> <p>For more details, please refer to the README.md file included in the dataset.</p>
A digital twin model of urban utility tunnels and its application:One-dimensional comparison verification
<div> <div> <div> <div> <div> </div> 重点词汇</div> <div> <div>93<em>/</em>5000</div> </div> </div> </div> </div> <div> </div> <div> <div> <div> <div> <div> <div>通用场景</div> <div> </div> </div> </div> </div> </div> <div> <div> <p><span>论文《城市综合管廊数字孪生模型及其应用》中一维综合管廊中天然气浓度分布快速预测模型结果对比</span></p> </div> </div> </div>
FIGURE 7 in Long-Term Avifaunal Survey In An Urban Ecosystem From Southeastern Brazil, With Comments On Range Extensions, New And Disappearing Species
FIGURE 7: Individual of Chalk-browed Mockingbird (Mimus saturninus) with blackish-brown throat and upper breast. Photo: D. Hoffmann.
FIGURE 4 in Long-Term Avifaunal Survey In An Urban Ecosystem From Southeastern Brazil, With Comments On Range Extensions, New And Disappearing Species
FIGURE 4: Distribution of bird species of different trophic guilds using different habitat on the campus of the Pontifícia Universidade Católica de Minas Gerais, Belo Horizonte, Minas Gerais, southeastern Brazil. Guilds: CAR = carnivorous; DET = detritivorous; FRU = frugivorous; GRA = granivorous; INS = insectivorous; NEC = nectarivorous; ONI = omnivorous; PIS = piscivorous.
Differences in the genomic potential of soil bacterial and phage communities between urban greenspaces and natural arid soils.
<p>This repository holds the final data products from metagenomics processing of bacteria and viruses from the article : "Differences in the genomic potential of soil bacterial and phage communities between urban greenspaces and natural arid soils"</p> <p>Contents: </p> <ul> <li>LU_metadata.csv: information on the samples</li> <li>soil_chemistry.txt: physicochemical information on samples</li> <li>*_len.csv: tables containing the length information for annotated genes, divided by database. These are used to calculate RPKM abundances from count tables. </li> <li>BACTERIA</li> <li>ko_table, ko_unknown, ko2level, ko_description: count table of KEGG annotations, total counts for unnanotated genes, match of ko number to level and description</li> <li>all_bracken.csv: count table of taxonomic bacterial annotations using kraken2 and bracken</li> <li>mags_tax.csv: taxonomy assignments to MAGs (metagenome assembled genomes)</li> <li>mags_count_table.csv: abundante table of MAGs in counts</li> <li>ags_result, gc_mean, gc_variance: functional traits results, average genome size, and gc content</li> <li>lu_c_count, lu_n_count, card_d0, metals_count_table: abundance tables of genes annotated with Cazy (carbon), Ncydb (nitrogen), CARD (antibiotic resistance genes), and Bacmet (heavy metal resistance genes)</li> <li>VIRUS</li> <li>amg_summary.csv: results from AMG annotation with DRAM-V, filtered to keep genes of interest</li> <li>genomad_virus_summary.tsv: viral taxonomy annotations with geNomad</li> <li>virus_len.txt: length of inferred viruses (used for calculation of RPKM from count tables)</li> <li>all_host_prediction_to_genus.csv: virus host annotation with IPhop</li> <li>final_checkv.tsv: table of final viral inferences with quality estimates</li> <li>viral_species_count_table.txt: abundance table of infered viral contigs in counts</li> </ul>
Supplementary material 1 from: Unterweger PA, Klammer J, Unger M, Betz O (2018) Insect hibernation on urban green land: a winter-adapted mowing regime as a management tool for insect conservation. BioRisk 13: 1-29. https://doi.org/10.3897/biorisk.13.22316
Table with all captured species / morphotypes sorted by order, family and species / morphotype. : Explanation note: Collection: University of Tübingen, Evolutionary Biology of Invertebrates, Auf der Morgenstelle 28, 72076 Tübingen, Germany. Individuals with scientific species name that were checked by a taxonomic expert were counted as taxonomic species (s); all the other determinations were counted as morphotypes (m). Morphotypes are defined by the lowest practical taxonomic level (e.g. Hanula et al. 2009; Kutschbach-Brohl et al. 2010). In some cases, the family or the morphometric body length (in mm, numbers in column C, Mini: smaller than 1 mm) was counted as a morphotype (Daly 1985). In cases for which the determination was not validated by a taxonomic expert, our species determination was checked for plausibility in terms of its geographical occurrence via the Entomofauna Germanica (http://www.colkat.de, 2017.11.06). Alternatively (if no taxonomic name could be found), a classification letter / number was assigned for a morphotype. The provided author name refers to the lowest practical taxonomic level (e.g. Hanula et al. 2009; Kutschbach-Brohl et al. 2010). Validation: name of scientific expert who checked the taxonomic determination. Management type of meadow in autumn: mown /unmown. Plant compartment: flower head, stem, tuft, leaves. All numbers represent total sums of all sample sites over the entire study period. Brown-labelled species names are thought to have hibernated in the soil. Green-labelled species names could only be found in flower heads and stems. Black-labelled species occurred in all plant compartments without any preference for a specific plant compartment.
Realistic urban sound mixture dataset
<p>This dataset resumes an urban sound corpus whose the realism has been proved through a perceptual test [1]. This corpus has been used in order to estimate the traffic sound level with the Non-negative Matrix Factorization formula [2].</p> <p>This dataset presents 4 folders :</p> <ul> <li><em>dictionary</em> where the traffic audio samples dedicated to the dictionary design of NMF are,</li> <li><em>recordings</em> which contains the 74 original recordings,</li> <li><em>annotation</em> which contains the annotations text files of the 74 audio files,</li> <li><em>transcribed scenes </em>which contains the 74 transcribed audio files generated with <a href="https://bitbucket.org/mlagrange/simscene"><em>SimScene</em></a> software. 4 folders composed it, according to the sound environment of the audio files (<em>park, quiet street, noisy street, very noisy street). </em> In each folder, one can find the global sound mixtures, the audio of each sound class as well as the files that include all the elements associated with the traffic and the interfering class (which contains all the other sound sources).</li> </ul> <p>[1] Gloaguen, J. R., Can, A., Lagrange, M., & Petiot, J. F. (2017, June). Creation of a corpus of realistic urban sound scenes with controlled acoustic properties. In <em>173rd Meeting of the Acoustical Society of America and the 8th Forum Acusticum (Acoustics' 17)</em>.</p> <p>[2] Gloaguen, J. R., Can, A., Lagrange, M., & Petiot, J. F. (2018), Road traffic sound level from realistic urban sound mixtures by Non-negative Matrix Factorization, submitted for publication</p>
Isolated urban sound database
<p>The Isolated urban sound database contains the audio samples used to design urban sound mixtures using <a href="https://bitbucket.org/mlagrange/simscene">SimScene</a> software. </p> <p>This database has already been used to design urban sound mixtures that can be found in <a href="https://zenodo.org/record/1145855">Estimation of the road traffic sound levels based on Non-Negative Matrix Factorization dataset</a> [1] and in <a href="https://zenodo.org/record/1184443">Realistic urban sound mixture dataset</a> [2]</p> <p>The dataset contains two folders :</p> <p>- 'event' which includes includes 231 brief sound samples considered as salient, with a 1 to 20 seconds duration and classified among 21 sound classes (ringing bell, whistling bird, car horn, passing car, hammer, barking dog, siren, footstep, metallic noise, voice...)</p> <p>- 'background' which includes 162 long duration sounds (~1mn30), whose acoustic properties do not vary in time. This category includes among others, whistling bird, crowd noise, rain, children playing in schoolyard, constant traffic noise ...</p> <p>More details on this sound database can be found in [3]</p> <p> </p> <p>[1] J.-R. Gloaguen, M. Lagrange, A. Can, J.-F. Petiot, Estimation of the road traffic sound levels in urban areas based on non-negative matrix factorization techniques, submitted for publication</p> <p>[2] J.-R. Gloaguen, A. Can, M. Lagrange, J.-F. Petiot, Road traffic sound level estimation from realistic urban sound mixtures by Non-negative Matrix Factorization, submitted for publication</p> <p>[3] J.-R. Gloaguen, A. Can, M. Lagrange, J.-F. Petiot, Creation of a corpus of realistic urban sound scenes with controlled acoustic properties, in: Acoustics ’17 Boston, Vol. 141 of The Journal of the Acoustical Society of America, Acoustical Society of America and the European Acoustics Association, Boston, United States, 2017, pp. 4044–4044.</p>
TUT Urban Acoustic Scenes 2018 Mobile, Development dataset
<p>TUT Urban Acoustic Scenes 2018 Mobile development dataset consists of 10-seconds audio segments from 10 acoustic scenes:</p> <ul> <li>Airport - <em>airport</em></li> <li>Indoor shopping mall - <em>shopping_mall</em></li> <li>Metro station - <em>metro_station</em></li> <li>Pedestrian street - <em>street_pedestrian</em></li> <li>Public square - <em>public_square</em></li> <li>Street with medium level of traffic - <em>street_traffic</em></li> <li>Travelling by a tram - <em>tram</em></li> <li>Travelling by a bus - <em>bus</em></li> <li>Travelling by an underground metro - <em>metro</em></li> <li>Urban park - <em>park</em></li> </ul> <p>Recordings were made with three devices that captured audio simultaneously. Each acoustic scene has 864 segments (144 minutes of audio) recorded with device A (main device) and 72 segments of parallel audio (12 minutes) each recorded with devices B and C. The dataset contains in total 28 hours of audio.</p>
TUT Urban Acoustic Scenes 2018, Development dataset
<p>TUT Urban Acoustic Scenes 2018 development dataset consists of 10-seconds audio segments from 10 acoustic scenes:</p> <ul> <li>Airport - <em>airport</em></li> <li>Indoor shopping mall - <em>shopping_mall</em></li> <li>Metro station - <em>metro_station</em></li> <li>Pedestrian street - <em>street_pedestrian</em></li> <li>Public square - <em>public_square</em></li> <li>Street with medium level of traffic - <em>street_traffic</em></li> <li>Travelling by a tram - <em>tram</em></li> <li>Travelling by a bus - <em>bus</em></li> <li>Travelling by an underground metro - <em>metro</em></li> <li>Urban park - <em>park</em></li> </ul> <p>Each acoustic scene has 864 segments (144 minutes of audio). The dataset contains in total 24 hours of audio.</p>
Supplementary material 1 from: Palomo-Campesino S, Palomo I, Moreno J, González J (2018) Characterising the rural-urban gradient through the participatory mapping of ecosystem services: insights for landscape planning. One Ecosystem 3: e24487. https://doi.org/10.3897/oneeco.3.e24487
List of the 19 socio-demographic and ecological parameters used for the study area clustering and their values for each municipality of the study area.
Supplementary material 2 from: Palomo-Campesino S, Palomo I, Moreno J, González J (2018) Characterising the rural-urban gradient through the participatory mapping of ecosystem services: insights for landscape planning. One Ecosystem 3: e24487. https://doi.org/10.3897/oneeco.3.e24487
Eigenvalue, percentage of explained variablity and accumulated percentage of explained variability of the five factors (with an eingenvalue higher than 1) result of the PCA analysis and used for the HCA analysis.
Supplementary material 3 from: Palomo-Campesino S, Palomo I, Moreno J, González J (2018) Characterising the rural-urban gradient through the participatory mapping of ecosystem services: insights for landscape planning. One Ecosystem 3: e24487. https://doi.org/10.3897/oneeco.3.e24487
Factors' loadings for each of the 19 socio-demographic and ecological variables analysed. Values in bold are statistically significant at P>0.05.
TUT Urban Acoustic Scenes 2018 Mobile, Leaderboard dataset
<p>TUT Urban Acoustic Scenes 2018 Mobile, Leaderboard dataset consists of 10-seconds audio segments from 10 acoustic scenes:</p> <ul> <li>Airport - <em>airport</em></li> <li>Indoor shopping mall - <em>shopping_mall</em></li> <li>Metro station - <em>metro_station</em></li> <li>Pedestrian street - <em>street_pedestrian</em></li> <li>Public square - <em>public_square</em></li> <li>Street with medium level of traffic - <em>street_traffic</em></li> <li>Travelling by a tram - <em>tram</em></li> <li>Travelling by a bus - <em>bus</em></li> <li>Travelling by an underground metro - <em>metro</em></li> <li>Urban park - <em>park</em></li> </ul>
TUT Urban Acoustic Scenes 2018, Leaderboard dataset
<p>TUT Urban Acoustic Scenes 2018, Leaderboard dataset consists of 10-seconds audio segments from 10 acoustic scenes:</p> <ul> <li>Airport - <em>airport</em></li> <li>Indoor shopping mall - <em>shopping_mall</em></li> <li>Metro station - <em>metro_station</em></li> <li>Pedestrian street - <em>street_pedestrian</em></li> <li>Public square - <em>public_square</em></li> <li>Street with medium level of traffic - <em>street_traffic</em></li> <li>Travelling by a tram - <em>tram</em></li> <li>Travelling by a bus - <em>bus</em></li> <li>Travelling by an underground metro - <em>metro</em></li> <li>Urban park - <em>park</em></li> </ul>
Simulation results of the agent-based model of urban insurgence with the effect of gathering sites and Koopman mode analysis
<p>The data set contains the simulation results of the agent-based model of urban insurgence with the effect of gathering sites and Koopman mode analysis. Some details on the agent-based model (without gathering sites) can be found in [Maria Fonoberova, Vladimir A. Fonoberov, Igor Mezic, Jadranka Mezic and P. Jeffrey Brantingham, Nonlinear Dynamics of Crime and Violence in Urban Settings, Journal of Artificial Societies and Social Simulation, 15(1), 2, http://jasss.soc.surrey.ac.uk/15/1/2.html, DOI: 10.18564/jasss.1921].</p> <p>Files in folder "0bar" are related to the case with 0 preferential gathering sites.</p> <p>Each file with name starting with Actives has one row for each time step of the simulation and has columns that are: number of active citizens, number of intimidated citizens, number of LEOs. These files are provided for lattice sizes from 100x100 to 600x600 and for different random seeds.</p> <p>Each file with name starting with Day for each non-intimidated agent has his/her x-coordinate, y-coordinate, agent's state, agent's risk aversion, agent's hardship, total number of days of being active and -1. Last two values are not used. If an agent is LEO, then last four values are -1. These files are provided for each time step of the simulation, each lattice size and the corresponding random seed used. For example, file "Day_10000_100_111.txt" provides information on the lattice situation at time step 10000 with lattice size 100 and random seed 111.</p> <p>Files in folder "1bar" are related to the case with 1 preferential gathering site.</p> <p>Each file with name starting with Actives has one row for each time step of the simulation and has columns that are: number of active citizens, number of intimidated citizens, number of LEOs. These files are provided for lattice sizes from 100x100 to 600x600 and for different random seeds.</p> <p>Each file with name starting with Day for each non-intimidated agent has his/her x-coordinate, y-coordinate, agent's state, agent's risk aversion, agent's hardship, total number of days of being active and average distance from the preferential gathering site. Last two values are not used. If an agent is LEO, then last four values are -1. These files are provided for each time step of the simulation, each lattice size and the corresponding random seed used. For example, file "Day_10000_100_111.txt" provides information on the lattice situation at time step 10000 with lattice size 100 and random seed 111.</p> <p>Files in folder "2bars" are related to the case with 2 preferential gathering sites.</p> <p>Each file with name starting with Actives has one row for each time step of the simulation and has columns that are: number of active citizens, number of intimidated citizens, number of LEOs, number of non-intimidated citizens. The last value is not used. These files are provided for lattice sizes from 100x100 to 600x600 and for different random seeds.</p> <p>Each file with name starting with Day for each non-intimidated agent has his/her x-coordinate, y-coordinate, agent's state, agent's risk aversion, agent's hardship, total number of days of being active and -1. Last two values are not used. If an agent is LEO, then last four values are -1. These files are provided for each time step of the simulation, each lattice size and the corresponding random seed used. For example, file "Day_10000_100_111_bars2.txt" provides information on the lattice situation at time step 10000 with lattice size 100 and random seed 111.</p> <p>Files in folder "3bars" are related to the case with 3 preferential gathering sites.</p> <p>Each file with name starting with Actives has one row for each time step of the simulation and has columns that are: number of active citizens, number of intimidated citizens, number of LEOs, number of non-intimidated citizens. The last value is not used. These files are provided for lattice sizes from 100x100 to 600x600 and for different random seeds.</p> <p>Each file with name starting with Day for each non-intimidated agent has his/her x-coordinate, y-coordinate, agent's state, agent's risk aversion, agent's hardship, total number of days of being active and -1. Last two values are not used. If an agent is LEO, then last four values are -1. These files are provided for each time step of the simulation, each lattice size and the corresponding random seed used. For example, file "Day_10000_100_111_bars3.txt" provides information on the lattice situation at time step 10000 with lattice size 100 and random seed 111.</p> <p>Files in folder "4bars" are related to the case with 4 preferential gathering sites.</p> <p>Each file with name starting with Actives has one row for each time step of the simulation and has columns that are: number of active citizens, number of intimidated citizens, number of LEOs, number of non-intimidated citizens. The last value is not used. These files are provided for lattice sizes from 100x100 to 600x600 and for different random seeds.</p> <p>Each file with name starting with Day for each non-intimidated agent has his/her x-coordinate, y-coordinate, agent's state, agent's risk aversion, agent's hardship, total number of days of being active and -1. Last two values are not used. If an agent is LEO, then last four values are -1. These files are provided for each time step of the simulation, each lattice size and the corresponding random seed used. For example, file "Day_10000_100_111_bars4.txt" provides information on the lattice situation at time step 10000 with lattice size 100 and random seed 111.</p> <p>Files in folder "5bars" are related to the case with 5 preferential gathering sites.</p> <p>Each file with name starting with Actives has one row for each time step of the simulation and has columns that are: number of active citizens, number of intimidated citizens, number of LEOs, number of non-intimidated citizens. The last value is not used. These files are provided for lattice sizes from 100x100 to 600x600 and for different random seeds.</p> <p>Each file with name starting with Day for each non-intimidated agent has his/her x-coordinate, y-coordinate, agent's state, agent's risk aversion, agent's hardship, total number of days of being active and -1. Last two values are not used. If an agent is LEO, then last four values are -1. These files are provided for each time step of the simulation, each lattice size and the corresponding random seed used. For example, file "Day_10000_100_111_bars5.txt" provides information on the lattice situation at time step 10000 with lattice size 100 and random seed 111.</p> <p>Files in folder "10bars" are related to the case with 10 preferential gathering sites.</p> <p>Each file with name starting with Actives has one row for each time step of the simulation and has columns that are: number of active citizens, number of intimidated citizens, number of LEOs, number of non-intimidated citizens. The last value is not used. These files are provided for lattice sizes from 100x100 to 600x600 and for different random seeds.</p> <p>Each file with name starting with Day for each non-intimidated agent has his/her x-coordinate, y-coordinate, agent's state, agent's risk aversion, agent's hardship, total number of days of being active and -1. Last two values are not used. If an agent is LEO, then last four values are -1. These files are provided for each time step of the simulation, each lattice size and the corresponding random seed used. For example, file "Day_10000_100_111_bars10.txt" provides information on the lattice situation at time step 10000 with lattice size 100 and random seed 111.</p> <p>Files in folder "20bars" are related to the case with 20 preferential gathering sites.</p> <p>Each file with name starting with Actives has one row for each time step of the simulation and has columns that are: number of active citizens, number of intimidated citizens, number of LEOs, number of non-intimidated citizens. The last value is not used. These files are provided for lattice sizes from 100x100 to 600x600 and for different random seeds.</p> <p>Each file with name starting with Day for each non-intimidated agent has his/her x-coordinate, y-coordinate, agent's state, agent's risk aversion, agent's hardship, total number of days of being active and -1. Last two values are not used. If an agent is LEO, then last four values are -1. These files are provided for each time step of the simulation, each lattice size and the corresponding random seed used. For example, file "Day_10000_100_111_bars20.txt" provides information on the lattice situation at time step 10000 with lattice size 100 and random seed 111.</p> <p>Files in folder "30bars" are related to the case with 30 preferential gathering sites.</p> <p>Each file with name starting with Actives has one row for each time step of the simulation and has columns that are: number of active citizens, number of intimidated citizens, number of LEOs, number of non-intimidated citizens. The last value is not used. These files are provided for lattice sizes from 100x100 to 600x600 and for different random seeds.</p> <p>Each file with name starting with Day for each non-intimidated agent has his/her x-coordinate, y-coordinate, agent's state, agent's risk aversion, agent's hardship, total number of days of being active and -1. Last two values are not used. If an agent is LEO, then last four values are -1. These files are provided for each time step of the simulation, each lattice size and the corresponding random seed used. For example, file "Day_10000_100_111_bars30.txt" provides information on the lattice situation at time step 10000 with lattice size 100 and random seed 111.</p> <p>Files in folder "prob25" are related to the case with 5 preferential gathering sites and 25% probability of agents moving towards them.</p> <p>Each file with name starting with Actives has one row for each time step of the simulation and has columns that are: number of active citizens, number of intimidated citizens, number of LEOs, number of non-intimidated citizens. The last value is not used. These files are provided for lattice sizes from 100x100 to 600x600 and for different random seeds.</p> <p>Each file with name starting with Day for each non-intimidated agent has his/her x-coordinate, y-coordinate, agent's state, agent's risk aversion, agent's hardship, total number of days of being active and -1. Last two values are not used. If an agent is LEO, then last four values are -1. These files are provided for each time step of the simulation, each lattice size and the corresponding random seed used. For example, file "Day_10000_100_111_bars5_prob0.25.txt" provides information on the lattice situation at time step 10000 with lattice size 100 and random seed 111.</p> <p>Files in folder "prob50" are related to the case with 5 preferential gathering sites and 50% probability of agents moving towards them.</p> <p>Each file with name starting with Actives has one row for each time step of the simulation and has columns that are: number of active citizens, number of intimidated citizens, number of LEOs, number of non-intimidated citizens. The last value is not used. These files are provided for lattice sizes from 100x100 to 600x600 and for different random seeds.</p> <p>Each file with name starting with Day for each non-intimidated agent has his/her x-coordinate, y-coordinate, agent's state, agent's risk aversion, agent's hardship, total number of days of being active and -1. Last two values are not used. If an agent is LEO, then last four values are -1. These files are provided for each time step of the simulation, each lattice size and the corresponding random seed used. For example, file "Day_10000_100_111_bars5_prob0.50.txt" provides information on the lattice situation at time step 10000 with lattice size 100 and random seed 111.</p> <p>Files in folder "prob75" are related to the case with 5 preferential gathering sites and 75% probability of agents moving towards them.</p> <p>Each file with name starting with Actives has one row for each time step of the simulation and has columns that are: number of active citizens, number of intimidated citizens, number of LEOs, number of non-intimidated citizens. The last value is not used. These files are provided for lattice sizes from 100x100 to 600x600 and for different random seeds.</p> <p>Each file with name starting with Day for each non-intimidated agent has his/her x-coordinate, y-coordinate, agent's state, agent's risk aversion, agent's hardship, total number of days of being active and -1. Last two values are not used. If an agent is LEO, then last four values are -1. These files are provided for each time step of the simulation, each lattice size and the corresponding random seed used. For example, file "Day_10000_100_111_bars5_prob0.75.txt" provides information on the lattice situation at time step 10000 with lattice size 100 and random seed 111.</p> <p>Files in folder "KMD" have detailed information for the case with 3 preferetial gathering sites and lattice size 200x200.</p> <p>File "2016_Actives_LD200_seed111_bars3.txt" has one row for each time step of the simulation and has columns that are: number of active citizens, number of intimidated citizens, number of LEOs, number of non-intimidated citizens.</p> <p>Each file with name starting with Day for each active / intimidated (jailed) / non-intimidated (notjailed) agent has his/her x-coordinate, y-coordinate, agent's state, agent's risk aversion, agent's hardship. Each file with name starting with Day for each LEO (cop) has his/her x-coordinate, y-coordinate, agent's state and -1, -1, -1. Last 3 entrees are not used. These files are provided for each time step of the simulation.</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.