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57 results for “Transport networks”
Transportation network system including trails, road construction history, and gates for the Andrews Experimental Forest, 1952-2011
Transportation network locations within the Andrews Experimental Forest. Includes locations of all the roads, trails, and gates within and around the forest. Original road layer was drawn on maps in 1992 and field validated. The road construction history (1952-1990) has been captured as an attribute. Roads were updated in 2004 to include roads that have been abandoned. Gates were field checked in 2004, as well as trail locations. The three data sets were updated after the 2008 LiDAR data was delivered. Roads were digitized on-screen from the bare-earth DEM, and gates were moved to match the new road network. Trails were updated for the 2011 Andrews map update. Many were located through GPS, and new trails were added. The original data is represented, as well as the updated datasets. The road network dataset is in an esri file geodatabase format, and the other datasets are in esri shapefile format, and all are in a zipped file format.
Least cost network data for ancient camel transportation in the Eastern desert of Egypt - Desert Networks HiSoMA CNRS
<p>This repository contains the data necessary for the realization of a least cost network for camel transport during antiquity (Ptolemaic and Roman period) in the Egyptian eastern desert. The details of the network construction and data processing can be found in the the associated paper and datapaper.</p> <p>Study paper:<br> Manière, L., Crépy, M., Redon, B. (2020) Building a Model to reconstruct the Hellenistic and Roman Road Networks of the Eastern desert of Egypt, a Semi-Empirical Approach Based on Modern Travelers’ Itineraries. DOI : <a href="http://doi.org/10.5334/jcaa.67">http://doi.org/10.5334/jcaa.67</a></p> <p>Datapaper:<br> Manière, L., Crépy, M., Redon, B. (2020) Geospatial data from the “Modelling the Hellenistic and Roman Road Networks of the Eastern desert of Egypt, a Semi-Empirical Approach Based on Modern Travelers’ Itineraries” paper. DOI : <a href="http://doi.org/10.5334/joad.71">http://doi.org/10.5334/joad.71</a></p>
Construction, validation and application of nocturnal pollen transport networks in an agro-ecosystem: datasets collected using light microscopy and DNA metabarcoding
<p>This dataset contains all data required to reproduce the analyses conducted in Macgregor <em>et al. </em>(2018), using the R Notebook archived at doi: <a href="https://dx.doi.org/10.5281/zenodo.1322712">10.5281/zenodo.1322712</a>.</p> <p>Specifically, the dataset contains details of pollen transport detected on two matched samples, each containing 311 moths of 41 species, using two methods: a traditional light microscopy approach and a novel DNA metabarcoding approach. Both raw and manually-curated versions of each dataset are archived for full clarity. The dataset additionally contains all metadata required to fully interpret these data, including the RGB tables used to prepare Fig 4 in Macgregor <em>et al. </em>(2018).</p> <p>Macgregor <em>et al. </em>(2018) Construction, validation and application of nocturnal pollen transport networks in an agro-ecosystem: a comparison using light microscopy and DNA metabarcoding. <em>Ecological Entomology</em>, doi: <a href="https://dx.doi.org/10.1111/een.12674">10.1111/een.12674</a>.</p>
Synthetic bus validation of Rennes public transportation network focus on Beaulieu campus
<p>Synthetic data based on the STAR/Keolis open data version GTFS_2021.1.0.3_20210830_20211017 for regular weeks and GTFS_2020.10.1_20210705_20210829 for holidays. This dataset contains the generation of bus validations for 3500 individuals during 14 weeks with an average of 15 travels per week. It also contains GPS information of the bus stops associated to the validation.</p>
Resilience of transportation infrastructure networks to road failures
<p>We provide the code used for the analysis that we used in the article <em>Resilience of transportation infrastructure networks to road failures</em>. As the computation for the RoadNetworks that we analysed in this manuscript is quite large, the computational load is quite high. We pre-computed the load values on the cluster and provide the results here. The code for the Figures in the notebooks will therefore not compute the loads, but just load them from files. We provide a <code>My-road-network.ipynb</code> were you can play around with a smaller RoadNetwork, computing everything locally.</p> <p>Published in<br><strong>J. Wassmer, B. Merz, N. Marwan</strong>: Resilience of transportation infrastructure networks to road failures, Chaos, <strong>34</strong>, 013124 (2024). <a href="https://dx.doi.org/10.1063/5.0165839" target="_blank" rel="noopener">DOI:10.1063/5.0165839</a></p>
Maritime entities of geographic transportation network of Acclimate
<p>maritime_entities.csv: Centroids of maritime entities and coordination of ports used by geographic transportation network of Acclimate</p> <p>XYZ_coordinates.csv: Polygon coordinates of maritime entites XYZ of the East Asian maritime trading route. Used to compute time tropical cyclone passed by based on observed trajectories from IBTrACS [http://ibtracs.unca.edu/]</p>
BRAIN Journal-About the Design of QUIC Firefox Transport Protocol-Figure 3. An example of a network switch
<p> Seamless network transition: While switching networks, QUIC can adapt to a network or a subnet switch (illustrated in Figure 3). This means that if the IP address of the device is changed, then the QUIC connection is not broken or lost. Unlike the TCP protocol where the connection is defined by the IP address and a port number, QUIC connections are defined by a connection ID. Whenever a network switch occurs, QUIC detects it and sends a piggybacked notification to the other party by indicating the new IP address and connection ID. In this way, the communication can resume normally. In contrast, TCP a new connection has to be established. </p>
Computational results data for the assoziated publication "Network Interdiction Problems in Urban Transportation: Theoretical Insights and Computational Characteristics"
<p>This repository contains two Excel tables with computational results for our paper "Network Interdiction Problems in Urban Transportation: Theoretical Insights and Computational Characteristics". Each Excel table includes multiple worksheets, each representing different scenarios and models evaluated in our study.</p> <p><strong>Worksheets Overview</strong></p> <p>Each Excel table contains the following worksheets:<br>1. <strong>ML</strong>: Results for the "ML" big M values.<br>2. <strong>MH</strong>: Results for the "MH" big M values.<br>3. <strong>MF</strong>: Results for the "MF" big M values.<br>4. <strong>Path</strong>: Results for the path model.<br>5. <strong>FMInstances</strong>: Results from applying our models on the original Fontaine and Minner (2018) instances.</p> <p><strong>Columns Description</strong></p> <p>Each worksheet contains the following columns:</p> <p>- <strong>Name of Instance</strong>: A complex string with the identifier of the used instance. The relevant part is "_RXXX_", where XXX is the random seed used to generate the instance.<br>- <strong>Number users</strong>: The number of users/commodities in the network.<br>- <strong>B:</strong> The budget (always set to infinity in our instances).<br>- <strong>GUROBI_RUNTIME</strong>: The time limit set for the computations.<br>- <strong>Modelkind</strong>: The type of model used. Possible values are:<br> - INDICATOR: Compact model.<br> - FMbenders: Benders model from Fontaine and Minner (2018).<br> - ICM: Benders-like cuts.<br> - PathModel: Path enumeration model.<br>- <strong>BigM computation</strong>: Time required to compute all the big M values used (not included in the time limit).<br>- <strong>runtime</strong>: Runtime of the selected model.<br>- <strong>BBnodes</strong>: Number of nodes in the Branch & Bound tree.<br>- <strong>gap</strong>: Gap reported by Gurobi after reaching the time limit.<br>- <strong>Cuts BLC</strong>: Number of Benders-like cuts included.<br>- <strong>Time BLC</strong>: Time required for separating Benders-like cuts.<br>- <strong>M improve BLC</strong>: Frequency of improvements to a big M when using the improved big M term in Benders-like cuts.<br>- <strong>Mcutoff_AVE</strong>: Average (non-zero) improvement of a big M when using the improved big M term in Benders-like cuts.<br>- <strong>Cuts FMBenders</strong>: Number of Benders cuts generated in the Fontaine and Minner (2018) model.<br>- <strong>Time FMBenders</strong>: Time required to generate the Benders cuts in the Fontaine and Minner (2018) model.<br>- <strong>Runtime path enum</strong>: Time required to enumerate all paths for the path-based model (not included in the time limit).<br>- <strong>Average Num Path</strong>: Average number of paths generated for a single commodity/user. Multiply this value by the number of users to obtain the absolute number of paths generated.</p> <p><strong>Note on FCP</strong></p> <p>All the results found for the instances already had integer flow solutions. Additionally, we conducted experiments where we explicitly forced the solutions to be integer for the Benders-like cuts model. We observed that the runtimes remained the same, with only some natural insignificant hardware-induced fluctuations. Therefore, we omit reporting these results again.</p> <p><br>For further information or questions, please refer to our paper "Network Interdiction Problems in Urban Transportation: Theoretical Insights and Computational Characteristics" or contact the authors.</p>
Neural-network-based molecular dynamics simulations reveal that proton transport in water is doubly gated by sequential hydrogen-bond exchange: Neural network potentials training data
<h1>Neural network potentials of an excess proton in bulk water, training data</h1> <p>This dataset contains 2188 configurations labeled at two hybrid DFT levels (revPBE0-D3 and B3LYP-D3).</p> <p>The configurations are given as a single XYZ file: configurations.xyz</p> <p>The box dimensions are written in box.txt</p> <p>The energies for all configurations at a given level of theory are written in energies_LEVEL.txt (one configuration per line)</p> <p>The atomic forces for each configuration at a given level of theory are gathered in a XYZ file: forces_LEVEL.xyz</p> <p>The relative displacements of the Wannier centroids, with respect to the closest oxygen atom, for each configuration at a given level of theory, are in the following XYZ file: wannier-centroids-displacements_LEVEL.xyz</p>
Data from: Strong and weak environmental perturbations cause contrasting restructure of ant transportation networks
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Supplementary videos for "Active flow network generates molecular transport by packets: case of the endoplasmic reticulum"
<p>Videos showing simulated motion on the active flow network for different switching timescales. In particular, compare <span class="math-tex">\(\tau_{\text{switch}} = 3 \text{ s}\)</span> to <span class="math-tex">\(\tau_{\text{switch}} = 30 \text{ ms}\)</span>. The red bubbles are proportional to the number of particles present in a node. Initially, all particles are placed in a central source node.</p>
Development of a Multi-Level Dynamic Model to Measure the Resilience Level of Transportation Infrastructure Networks
<p>The recent increase in disasters is making the largest critical infrastructure system namely the transportation infrastructure system susceptible to unexpected damage. Discontinuation of services provided by transportation infrastructures will create significant societal, economic, and collateral damages. Therefore, this study aims to identify dimensions to measure the resilience of the transportation infrastructures. This study also aims to develop a model to measure the resilience of the transportation infrastructures resilience. To fulfill the aims of this study, a questionnaire was developed which was supported by a comprehensive literature review. 92 valid responses were received and analyzed qualitatively and quantitatively. Statistically significant variables were used to develop a resilience measurement tool. The developed tool will provide relative resilience measures for multiple projects which will help in identifying the most vulnerable segment of the transportation infrastructure network. Exploratory factor analysis (EFA) was performed to identify the constructs and structural equation modeling (SEM) was used to develop the model. Without previous experience in reconstruction works, handling integrated assets becomes very critical. Also, such inexperience makes it difficult to handle emergency resources properly. However, such issues regarding integrated assets can be resolved by investing in locating integrated assets away from the roadways, so if a break in a railroad crossing or utility line occurs or emergency repairs are needed, the impact on the roadway operations can be minimized. To avoid issues related to access to previous disaster data for the roadway this study suggess investing in preparing an interactive online platform for recording and reviewing data related to disasters as well as previous resilience enhancing activities for the roadway with easy access credentials. The findings of this study will support practitioners and decision-makers in investing in the appropriate resilience enhancement activity project for funding and investment.</p>
MUSE: Multimodal Separators for Efficient Route Planning in Transportation Networks
<p>This dataset was used in the experimental evaluation of the MUSE route planning algorithm. It encompasses the Ile-de-France multimodal network. The dataset contains:</p> <p>1. The raw osm file of the Ile-de-France region from OpenStreetMap.</p> <p>2. The raw GTFS data for the public transit network.</p> <p>3. The multimodal graph based on 5 partitions: 100, 200, 300, 400, and 500 cells.</p> <p>4. The Nondeterministic Finite Automata (NFA) used during the preprocessing and query stages of MUSE.</p> <p>5. The graph overlay evaluated during the preprocessing stage of MUSE.</p> <p>To test MUSE and review the details of this dataset, please visit https://github.com/aminefalek/muse</p>
An Improved Tandem Neural Network Architecture for Inverse Modeling of Multicomponent Reactive Transport in Porous Media
<p>This data includes the training and testing dataset for DNN design and the observation data of synthetic example for validation. </p> <p>The code of TNNA-AUS inversion method.</p>
Developing a vehicle cost calculator to promote electrical vehicle adoption among transportation network company (TNC) drivers
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Data from: Non-native species spread in a complex network: the interaction of global transport and local population dynamics determines invasion success
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Microtubule networks in zebrafish hair cells facilitate presynapse transport and fusion during development
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Data from: Patterns and drivers of pollen co-transport network structure vary across pollinator functional groups
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Data from: Promiscuious pollinators - evidence from an Afromontane sunbird-plant pollen transport network
Sunbirds play a major role in the pollination of Old World nectiverous plants. However, with the exception of the Cape Floristic Region there is a major knowledge gap around African nectivore interaction networks- a stark contrast from the abundance of neotropical hummingbird-plant networks. Here we describe a sunbird pollen transfer network (PTN) which we use in conjunction with a sunbird- flower visitation network (FVN) to explore levels of sunbird specialization within an Afromontane forest habitat. Both networks were generalised compared with similar sized hummingbird networks, reflecting the wide range of flower types visited, the generalist diet and bill characteistics of sunbirds. Three sunbird species from the genus Cinnyris accounted for 85% of flower visits and 77% of all pollen transported. Of the 17 plant species across both networks, 15 are predominantly pollinated by insects while Anthonotha noldeae (Fabaceae- Caesalpinoidie) and Globimetula braunii (Loranthaceae) depend on sunbirds for seed set. Sunbird species average bill lengths varied between 14.5 mm (the variable sunbird) to 23.6 mm (the green headed sunbird) but while more pollen was carried on longer bills we found no evidence for a relationship between bill length and type of flower visited. Both networks were nested. Some specialization was observed in both networks although this does not appear to be driven much by sunbird –flower trait matching. Overall, our results suggest that in contrast to nectivores elsewhere, factors such as phenology and/or environment, rather than morphology may play important roles in limiting potential sunbird-flower interactions and need further investigation.
Data from: Wildfire alters the structure and seasonal dynamics of nocturnal pollen-transport networks
Wildfires drive global biodiversity patterns and affect plant–pollinator interactions, and are expected to become more frequent and severe under climate change. Post‐fire plant communities often have increased floral abundance and diversity, but the effects of wildfires on the ecological process of pollination are poorly understood. Nocturnal moths are globally important pollinators, but no previous study has examined the effects of wildfire on nocturnal pollination interactions. We investigated the effects of wildfire on nocturnal pollen‐transport networks. We analysed the abundance and species richness of moths and flowers, and the structure of these networks, at three burned and three unburned sites in Portugal for two years, starting eight months after a large fire. Nocturnal pollen‐transport networks had lower complexity and robustness following the fire than at nearby unburned sites. Overall, 70% of individual moths carried pollen, and moths were found to be transporting pollen from 83% of the flower species present. Burned sites had significantly more abundant flowers, but less abundant and species‐rich moths. Individual moths transported more pollen in summer at burned sites, but less in winter; however, total pollen transport by the moth assemblage at burned sites was just 20% of that at unburned sites. Interaction turnover between burned and unburned networks was high. Negative effects of fire upon moths will likely permeate to other taxa through loss of mutualisms. Therefore, if wildfires become more frequent under climate change, community resilience may be eroded. Understanding the responses of ecological networks to wildfire can inform management that promotes resilience and facilitates whole‐ecosystem conservation.
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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.