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2,721 results for “Connectivity”
Dataset: Connectivity and rigidity percolation of cytoskeletal networks.
<p>Dataset containing information for "Connectivity and rigidity percolation of cytoskeletal networks."</p> <p>File: Fig1A_MEDYAN_Unbranched_timeseries_motor_333_linker_1500_tmax_122.csv<br> Description:<br> Average MEDYAN simulations in a 1um3 box with 333 motors and 1500 linkers, no branchers.<br> Columns:<br> Last_Timestep: Last time step of the simulations<br> N_Motors: Total number of motors in the simulation<br> N_Linkers: Total number of linkers in the simulation<br> Simulation: Number of simulations<br> M_p: Number of plus ends<br> M_m: Number of minus ends<br> M_c: Number of free binding sites<br> M_M: Number of free motors<br> M_L: Number of free linkers<br> M_pm: Number of plus ends connected to minus ends (polymerized F-actin)<br> M_cMc: Number of bound motors<br> M_cLc: Number of bound linkers<br> M_G: Number of free G-actin<br> M_b: number of free branchers</p> <p>File: Fig1A_ODE_Unbranched_timeseries_motor_333_linker_1500_tmax_10000.csv<br> Description:<br> Chemical kinetics calculations for transient concentrations of motor, linker and brancher for equivalent MEDYAN simulations of a 1um3 box with 333 motors and 1500 linkers, no branchers.<br> Columns:<br> pm: Number of plus ends connected to minus ends (polymerized F-actin)<br> L: Number of free linkers<br> cMc: Number of bound motors<br> cLc: Number of bound linkers<br> c: Number of free binding sites<br> m: Number of minus ends<br> p: Number of plus ends<br> G: Number of free G-actin<br> M: Number of free motors</p> <p>File: Fig1A_Unbranched_MEDYAN.csv<br> Description:<br> Species concentrations in MEDYAN simulations in a 1um3 box with 333 motors and 1500 linkers, no branchers.<br> The simulations can be found in the Simulations_Unbranched folder<br> Columns:<br> Last_Timestep: Measured timestep<br> N_Motors: Total number of motors in the simulation<br> N_Linkers: Total number of linkers in the simulation<br> chem_path: Path of the simulation<br> AD: Number of unbound G-actins<br> MD: Number of unbound motors<br> LD: Number of unbound linkers<br> FA: Number of bound F-actin monomers<br> PA: Number of plus ends<br> MA: Number of minus ends<br> LA: Number of bound linkers<br> MOA: Number of bound motors<br> Simulation: Simulation ID</p> <p>File: Fig1B_Branched_MEDYAN.csv<br> Description:<br> Species concentrations in MEDYAN simulations in a 1um3 box with 333 motors and 1500 linkers, 300 branchers.<br> The simulations can be found in the Simulations_Branched folder<br> Columns:<br> Last_Timestep: Measured timestep<br> N_Motors: Number of motors<br> N_Linkers: Number of linkers<br> chem_path: Path of the simulation<br> AD: Number of unbound G-actins<br> BD: Number of unbound branchers<br> MD: Number of unbound motors<br> LD: Number of unbound linkers<br> FA: Number of bound F-actin monomers<br> PA: Number of plus ends<br> MA: Number of minus ends<br> LA: Number of bound linkers<br> MOA: Number of bound motors<br> BA: Number of bound branchers<br> Simulation: Simulation ID</p> <p>File: Fig1B_MEDYAN_Branched_timeseries_motor_333_linker_1500_tmax_122.csv<br> Description:<br> Average MEDYAN simulations in a 1um3 box with 333 motors and 1500 linkers, 300 branchers.<br> Columns:<br> Last_Timestep: Last time step of the simulations<br> N_Motors: Total number of motors in the simulation<br> N_Linkers: Total number of linkers in the simulation<br> Simulation: Number of simulations<br> M_p: Number of plus ends<br> M_m: Number of minus ends<br> M_c: Number of free binding sites<br> M_M: Number of free motors<br> M_L: Number of free linkers<br> M_pm: Number of plus ends connected to minus ends (polymerized F-actin)<br> M_cMc: Number of bound motors<br> M_cLc: Number of bound linkers<br> M_G: Number of free G-actin<br> M_B: total number of branchers<br> M_cBm: number of bound branchers<br> M_b: number of free branchers</p> <p>File: Fig1B_ODE_Branched_timeseries_motor_333_linker_1500_tmax_10000_v2.csv<br> Description:<br> Chemical kinetics calculations for transient concentrations of motor, linker and brancher for equivalent MEDYAN simulations of a 1um3 box with 333 motors and 1500 linkers, and 300 branchers.<br> Columns:<br> pm: Number of plus ends connected to minus ends (polymerized F-actin)<br> L: Number of free linkers<br> p: Number of plus ends<br> cMc: Number of bound motors<br> cBm: Number of bound branchers<br> cLc: Number of bound linkers<br> c: Number of free binding sites<br> m: Number of minus ends<br> M: Number of free motors<br> G: Number of free G-actin<br> B: Number of free branchers</p> <p>File: Fig1C_Ps_timeseries_unbranched.csv<br> Description:<br> Flory-Stockmayer results for unbranched chemical kinetics calculations<br> Columns:<br> pm: Number of plus ends connected to minus ends (polymerized F-actin)<br> L: Number of free linkers<br> cMc: Number of bound motors<br> cLc: Number of bound linkers<br> c: Number of free binding sites<br> m: Number of free minus ends<br> p: Number free of plus ends<br> G: Number of free G-actin<br> M: Number of free motors<br> P0: Probability that an F-actin monomer is connected to another one on its plus end<br> P1: Probability that an F-actin monomer is connected to another one on its minus end<br> P2: Probability that an F-actin monomer is connected to another one on its binding site<br> Ps: Probability that an F-actin monomer is not connected to an infinite cluster<br> Nb: Average number of bonds per F-actin monomer<br> Nn: Mean cluster size<br> Nw: Mean weighted cluster size<br> Ratio: Nw/Nn Ratio</p> <p>File: Fig1D_Ps_timeseries_branched.csv<br> Description:<br> Flory-Stockmayer results for branched chemical kinetics calculations<br> Columns:<br> pm: Number of plus ends connected to minus ends (polymerized F-actin)<br> L: Number of free linkers<br> cMc: Number of bound motors<br> cBm: Number of bound branchers<br> cLc: Number of bound linkers<br> c: Number of free binding sites<br> m: Number of free minus ends<br> p: Number free of plus ends<br> G: Number of free G-actin<br> M: Number of free motors<br> B: Number of free branchers<br> P0: Probability that an F-actin monomer is connected to another one on its plus end<br> P1: Probability that an F-actin monomer is connected to another one on its minus end<br> P2: Probability that an F-actin monomer is connected to another one on its binding site<br> Ps: Probability that an F-actin monomer is not connected to an infinite cluster<br> Nb: Average number of bonds per F-actin monomer<br> Nn: Mean cluster size<br> Nw: Mean weighted cluster size<br> Ratio: Nw/Nn Ratio<br> Qm: Probability that an F-actin monomer is not connected to an infinite cluster through the minus end<br> Qp: Probability that an F-actin monomer is not connected to an infinite cluster through the plus end<br> Qc: Probability that an F-actin monomer is not connected to an infinite cluster through the binding site</p> <p>File: Fig2_Two-step.csv<br> Description:<br> Representative steady state concentrations for a non-cooperative two-step model of linker binding.<br> Columns:<br> Fc: Concentration of free binding sites<br> FcL: Concentration of linkers bound to a single binding site<br> FcLFc: Concentration of linkers bound to a pair of binding sites<br> L: Concentration of unbound linkers<br> Fc0: Total concentration of binding sites<br> L0: Total concentration of linkers</p> <p>File: Fig3_two_step_heatmap.csv<br> Proportion of the concentration of crosslinks to the concentration of total binding sites as a function of the linker binding equilibrium constant<br> Description:<br> 2D matrix, where the columns indicate the linker binding constant multiplied by the total concentration of binding sites, the rows indicate the total concentration of linkers per binding site , and the value corresponds to the total number of linkers bound to two binding sites divided by the total concentration of binding sites.</p> <p>File: Fig5A_Ps_unbranched.csv<br> Description:<br> 2D matrix, where the columns indicate the proportion of motors to actin, the rows indicate the proportion of linkers to actin , and the value corresponds to the probability that an F-actin monomer is in a finite cluster using the chemical kinetics model without brancher.</p> <p><br> File: Fig5B Ps_branched.csv<br> Description:<br> 2D matrix, where the columns indicate the proportion of motors to actin, the rows indicate the proportion of linkers to actin , and the value corresponds to the probability that an F-actin monomer is in a finite cluster using the chemical kinetics model with brancher.<br> </p> <p>File: Fig6_Ps_Branched_var.csv<br> Description:<br> 2D matrix, where the columns indicate the proportion of branchers to actin, the rows indicate the proportion of linkers to actin , and the value corresponds to the probability that an F-actin monomer is in a finite cluster using the chemical kinetics model without brancher or motors.</p> <p><br> File: Fig7B_Ps_unbranched_linkeronly.csv</p> <p>Description:<br> 2D matrix, where the columns indicate the proportion of motors to actin, the rows indicate the proportion of linkers to actin , and the value corresponds to the probability that an F-actin monomer is in a finite cluster using the chemical kinetics model without brancher. The clusters are defined here as F-actin monomers connected by linkers, and without including motor connections.</p> <p>File: Fig7D_Ps_branched_linkeronly.csv</p> <p>Description:<br> 2D matrix, where the columns indicate the proportion of motors to actin, the rows indicate the proportion of linkers to actin , and the value corresponds to the probability that an F-actin monomer is in a finite cluster using the chemical kinetics model with brancher. The clusters are defined here as F-actin monomers connected by linkers or branchers, and without including motor connections.</p> <p>File: Fig9_data.csv<br> Description:<br> Minimum motor concentration to reach rigidity percolation as a function of the linker concentration for systems with and without brancher, considering both linker and motor connections or just motor connections and for different values of linker rigidity. The motor and linker concentrations are measured as the proportion of linkers or motors to actin.<br> Columns:<br> L: linker concentration <br> "M (unbranched, linkers and motors, bcLc=0)"<br> "M (unbranched, linkers and motors, bcLc=1)"<br> "M (unbranched, linkers and motors, bcLc=2)"<br> "M (unbranched, linkers and motors, bcLc=3)"<br> "M (unbranched, linkers and motors, bcLc=4)"<br> "M (unbranched, linkers and motors, bcLc=5)"<br> "M (unbranched, linkers and motors, bcLc=6)"<br> "M (branched, linkers and motors, bcLc=0)"<br> "M (branched, linkers and motors, bcLc=1)"<br> "M (branched, linkers and motors, bcLc=2)"<br> "M (branched, linkers and motors, bcLc=3)"<br> "M (branched, linkers and motors, bcLc=4)"<br> "M (branched, linkers and motors, bcLc=5)"<br> "M (branched, linkers and motors, bcLc=6)"<br> "M (unbranched, linkers only, bcLc=0)"<br> "M (unbranched, linkers only, bcLc=1)"<br> "M (unbranched, linkers only, bcLc=2)"<br> "M (unbranched, linkers only, bcLc=3)"<br> "M (unbranched, linkers only, bcLc=4)"<br> "M (unbranched, linkers only, bcLc=5)"<br> "M (unbranched, linkers only, bcLc=6)"<br> "M (branched, linkers only, bcLc=0)"<br> "M (branched, linkers only, bcLc=1)"<br> "M (branched, linkers only, bcLc=2)"<br> "M (branched, linkers only, bcLc=3)"<br> "M (branched, linkers only, bcLc=4)"<br> "M (branched, linkers only, bcLc=5)"<br> "M (branched, linkers only, bcLc=6)"</p> <p>File: FigS1_data.csv<br> Description:<br> Connectivity percolation as a function of the probabilities that an F-actin monomer site is bound to another F-actin.<br> Columns:<br> ppm: probability that an F-actin monomer plus end is connected to another F-actin monomer minus end<br> pcc: probability that an F-actin monomer binding site is connected to another F-actin monomer binding site<br> Pcm: probability that an F-actin monomer binding site is connected to another F-actin monomer minus end<br> Qp: Probability that an F-actin monomer is not connected to an infinite cluster through the plus end<br> Qm: Probability that an F-actin monomer is not connected to an infinite cluster through the minus end<br> Qc: Probability that an F-actin monomer is not connected to an infinite cluster through the binding site<br> Ps: Probability that an F-actin monomer is not connected to an infinite cluster<br> Percolated: Whether the system is percolated or not.</p> <p>File: simulations.tar.gz<br> Description: Contains the MEDYAN simulations used for figure 1. Each folder contains an individual simulation, with the following files:<br> systeminput.txt: Contains the input for the system conditions and settings<br> chemistryinput.txt: Contains the input for the chemical species<br> chemistry.traj: Output trajectory containing number of species in the simulations<br> snapshot.traj: Output trajectory containing the coordinates of the species.<br> For more information please reference the MEDYAN user guide and reference:<br> K Popov, JE Komianos and GA Papoian (2016) MEDYAN: Mechanochemical Simulations of Contraction and Polarity Alignment in Actomyosin Networks. PLoS Comput Biol 12(4): e1004877. doi:10.1371/journal.pcbi.1004877</p>
Functional Lake-to-Channel Connectivity Impacts Lake Ice in the Colville Delta, Alaska
<p>This data is public for a manuscript accepted in JGR Earth Surface. The article will be linked here once it is published. </p> <p>Corresponding code can be found on Github: <a href="https://github.com/whyana/colvilleConnectivity">https://github.com/whyana/colvilleConnectivity</a></p> <p>File and variable descriptions can be found in ReadMe_zenodo.docx OR on Github: <a href="https://github.com/whyana/colvilleConnectivity">https://github.com/whyana/colvilleConnectivity</a></p>
GC-PC_Cerebellar_Connectivity _Maps
<p>Here we provide the dataset (raw electrophysiological recordings + processed data) used to build synaptic maps and compute graph properties in the following article: <strong><em>Cerebellar connectivity maps embody individual adaptive behavior in mice (Spaeth, Bahuguna et al.).</em></strong> </p> <p>Just unzip the entire file to find the following elements:</p> <p><br> <strong>RawData</strong>: <br> Electrophysiological recordings were recorded with <strong>WinWCP 4.2.2</strong> freeware (<em>John Dempster</em>, SIPBS, University of Strathclyde, UK)</p> <ul> <li><strong><em>Adaptive_Dataset</em></strong>: raw electrophysiological recordings, sorted by individual maps in each adaptive conditions (<em>EC, early cuff; ES, early sham; LC, adapted cuff; LS, adapted sham; ENR, trained; WT, control</em>). Mappings were performed at high-resolution (20*20µm). <br> Experimental info as well as file sorting are noted in the corresponding spreadsheets within the following notebook: <strong><em>Spaeth_Bahuguna_et_al_GCPC_Mappings_Adaptive_High_Res_Info.xlsx</em> </strong><br> </li> <li><strong><em>Development_Dataset</em></strong>: raw electrophysiological recordings, sorted by individual maps in developmental conditions (<em>P9-P10; P12-P13; P14-P18; >P30</em>). Mappings were performed at low-resolution (40*40µm). <br> Experimental info as well as file sorting are noted in the corresponding spreadsheets within the following notebook: <strong><em>Spaeth_Bahuguna_et_al_GCPC_Mappings_Development_Low_Res_Info.xlsx</em></strong></li> </ul> <p> </p> <p><strong>Processed Data:</strong><br> Files are saved in <em>.csv</em> format.</p> <ul> <li><strong><em>Adaptive_Dataset</em></strong>: processed synaptic maps, sorted by individual maps in each adaptive conditions (<em>EC, early cuff; ES, early sham; LC, adapted cuff; LS, adapted sham; ENR, trained; WT, control</em>).<br> Measures of the Zebrin Bands are found in the following file:<br> <strong><em>Spaeth_Bahuguna_et_al_Measures_Zebrin_Adaptive_HighResDataset.xlsx</em></strong></li> <li><strong><em>Development_Dataset</em></strong>: processed synaptic maps, sorted by individual maps in each developmental condition (<em>P9-P10; P12-P13; P14-P18; >P30</em>).<br> Measures of the Zebrin Bands are found in the following file:<br> <strong><em>Spaeth_Bahuguna_et_al_Measures_Zebrins_Development_LowRes_dataset.xlsx</em></strong></li> </ul> <p>Description of the files (also included in READ_ME.pdf):</p> <ol> <li><em>XXX_Positions_cp_centered_OK.csv</em>: a vector containing the normalized, relative position along the mediolateral axis for map XXX</li> <li><em>XXX_Amp_max_OK.csv</em>: a vector containing the maximal synaptic amplitude (in pA) in each column of map XXX, sorted along the mediolateral axis</li> <li><em>XXX_Amp_Noisemap_OK.csv</em>: a matrix containing the synaptic noise (in pA) in site of map XXX</li> <li><em>XXX_Amp_Sigma_OK.csv</em>: a matrix containing the standard deviation of the synaptic noise for the entire map XXX (identical value in each cell)</li> <li><em>XXX_Amp_zscore_2D_OK.csv</em>: a matrix containing the z-score of each site in map XXX</li> <li><em>XXX_Amp_Zscore_max_OK.csv</em>: a vector containing the maximal z-score in each column of map XXX, sorted along the mediolateral axis</li> <li><em>XXX_Files_List.csv</em>: a list of the <em>.wcp</em> files used to generate map XXX</li> <li><em>XXX_Positions_OK.csv</em>: a vector containing the absolute position along the mediolateral axis for map XXX</li> <li><em>XXX_Amp_2D_OK.csv:</em> a matrix containing the average synaptic amplitude (in pA) recorded for each site of map XXX</li> <li><em>XXX_Zebrin_OK.csv</em>: a vector containing the relative position of the Zebrin bands for map XXX</li> </ol> <p> </p>
Fig. 1 in Invasive Mollusc, Crustacean, Fish And Reptile Species Along The Hungarian Stretch Of The River Danube And Some Connected Waters
Fig. 1. Increasing number of invasive species in the Hungarian Danube stretch according to the studied taxonomical groups
Query dan Perspektif Bloom untuk "Analisis Data Paradise Papers Indonesia Menggunakan Algoritma Strongly Connected Components dan Harmonic Centrality"
<p>Query dan Perspektif Bloom untuk "Analisis Data Paradise Papers Indonesia Menggunakan Algoritma Strongly Connected Components dan Harmonic Centrality"</p>
Forest cover and connectivity have pervasive effects on the maintenance of evolutionary distinct interactions in seed dispersal networks
<p>This Data set contain 29 table of weighted interaction network between plants (columns) and frugivore birds from the Brazilian Atlantic Forest used in the manuscript "Forest cover and connectivity have pervasive effects on the maintenance of evolutionary distinct interactions in seed dispersal networks" published in Oikos Journal.</p>
An estimation of the absolute number of axons indicates that human cortical areas are sparsely connected
<p>This is a collection of preprocessed data and standalone Matlab analysis code for the PLoS: Biology article of the same name, <a href="https://doi.org/10.1371/journal.pbio.3001575">https://doi.org/10.1371/journal.pbio.3001575</a>. The primary processed diffusion MRI connectivity data was reported and previous distributed in our eNeuro article <a href="http://doi.org/10.1523/ENEURO.0416-20.2020">https://doi.org/10.1523/ENEURO.0416-20.2020</a>. The replication dataset was reported and previous distributed by Arnatkeviciute et al. 2021, Nature Communications (<a href="http://doi.org/10.1038/s41467-021-24306-2">https://doi.org/10.1038/s41467-021-24306-2</a>). Please cite these publications when using relevant code or data. Files with the .mat extension are Matlab v7.3 data files. The raw imaging data from which these files were derived are available from <a href="https://db.humanconnectome.org/">https://db.humanconnectome.org</a>.</p>
Data and scripts for: Green turtles highlight connectivity across a regional marine protected area network in West Africa
<p>Data derivates and analysis scripts (in R) used for the paper on analyzing green turtle MPA coverage and connectivity in West Africa.</p>
Spatiotemporal checkins with social connections
<ul> <li><strong>Introduction</strong></li> </ul> <p>These three datasets are used in the analysis of human mobility research paper [1]. For each dataset, there are checkins info and friendshio info, </p> <ol> <li>Brightkite: "brightkite_checkins.csv" and "brightkite_friends.csv".</li> <li>Gowalla: "gowalla_checkins.csv" and "gowalla_friends.csv".</li> <li>Weeplaces: "weeplace_checkins.csv" and "weeplace_friends.csv"</li> </ol> <p> </p> <ul> <li><strong>Basic Description </strong></li> </ul> <p><em>BrightKite</em> [2] is a LBSN service provider that allowed registered users to connect with their existing social ties and also meet new people based on the places that they go. Once a user "checked in" at a place, they could post notes and photos to a location and other users could comment on those posts. The social relationship network was collected using their public API. The raw dataset is from SNAP <a href="https://snap.stanford.edu/data/loc-brightkite.html">https://snap.stanford.edu/data/loc-brightkite.html</a>.<br> </p> <p><em>Gowalla</em> [2] is a LBSN website where users share their locations by checking-in. In early versions of the service, users would occasionally receive a virtual "Item" as a bonus upon checking in, and these items could be swapped or dropped at other spots. Users became "Founders" of a spot by dropping an item there. This incentivises users to create new check-ins, not necessarily to check-in consistently at frequently visited locations. The social relationship network is undirected and was collected using their public API. The raw dataset is from SNAP <a href="https://snap.stanford.edu/data/loc-gowalla.html">https://snap.stanford.edu/data/loc-gowalla.html</a>.<br> <br> <em>Weeplaces</em> --This is collected from Weeplaces and integrated with the APIs of other LBSN services, e.g., Facebook Places, Foursquare, and Gowalla. Users can login Weeplaces using their LBSN accounts and connect with their social ties in the same LBSN who have also used this application. Weeplaces visualizes your check-ins on a map. Unlike Gowalla, there is no direct incentive in Weeplaces to alter one's visitation habits or check-ins, so there should be a more accurate representation of a regular person's mobility patterns.<br> The raw dataset is from the website <a href="https://www.yongliu.org/datasets/">https://www.yongliu.org/datasets/</a>.</p> <p> </p> <p>More details can be found in the data description of paper [1].</p> <p> </p> <ul> <li><strong>Reference</strong></li> </ul> <p>[1] Chen, Z., Kelty, S., Welles, B.F., Bagrow, J.P., Menezes, R. and Ghoshal, G., 2021. Contrasting social and non-social sources of predictability in human mobility. <em>arXiv preprint arXiv:2104.13282</em>.</p> <p>[2] Cho, Eunjoon, Seth A. Myers, and Jure Leskovec. "Friendship and mobility: user movement in location-based social networks." In <em>Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining</em>, pp. 1082-1090. 2011.</p> <p> </p> <ol> </ol> <p> </p> <p> </p>
Data from: Integrating tracking and resight data enables unbiased inferences about migratory connectivity and winter range survival from archival tags
<p>Archival geolocators have transformed the study of small, migratory organisms but analysis of data from these devices requires bias correction because tags are only recovered from individuals that survive and are re-captured at their tagging location. Data and code provided in this repository can be used to replicate the simulation and Painted Bunting case study results presented by Rushing et al. (2021) showing that integrating geolocator recovery data and mark–resight data enables unbiased estimates of both migratory connectivity between breeding and nonbreeding populations and region-specific survival probabilities for wintering locations.</p>
Fig. 2 in Absorbing Hybridization Of Cobitis Taenia And Sabanejewia Aurata (Cypriniformes, Cobitidae) In Water Reservoirs Of Northern Ukraine Connected With Diploid-Polyploid Complex Formation
Fig. 2. Electrophoretic spectra of enzymes coding by allozymic loci: aspartate amynotransferase (1 — Aat- 1100/100, 2 — Aat-1100/110-110, 3 — Aat-195/110-110, 4 — Aat-1100-100/110, 5 — Aat-195-95/110, 6 — Aat-195-100/110), lactate dehydrogenase (1 — Ldh-B90/90, 2 — Ldh-B100/100, 3 — Ldh-B90/100-100, 4 — Ldh-B90/100/110), malate dehydrogenase (1 — Mdh-1A100/100, 2 — Mdh-1A100/110-110, 3 — Mdh-1A100-100/110).
GNSS Location Verification in Connected and Autonomous Vehicles Using in-Vehicle Multimodal Sensor Data Fusion (presentation recording)
<p>Video recording of the presentation for the publication N. Souli et al., "GNSS Location Verification in Connected and Autonomous Vehicles Using in-Vehicle Multimodal Sensor Data Fusion," 2020 22nd International Conference on Transparent Optical Networks (ICTON), Bari, Italy, 2020, pp. 1-4, doi: 10.1109/ICTON51198.2020.9203087.</p>
The genetic structure and connectivity in two sympatric rodent species with different life histories are similarly affected by land use disturbances
<p><strong>Microsatellite dataset of the wood mouse (<em>Apodemus sylvaticus)</em> and the bank vole (<em>Myodes glareolus).</em></strong></p> <p>The dataset of the wood mouse is constituted of 194 samples and 7 microsatellite markers: WM_194ind_7STRs.txt</p> <p>The dataset of the bank vole is constituted of 199 samples and 8 microsatellite markers: BV_199ind_8STRs.txt</p> <p>Each locus is encoded in the three-digit format (e.g., 126126) and each column corresponds to a locus specified in the order at the beginning of the file, following the GENEPOP format.</p> <p>Pop indicates the beginning of a new location.</p> <p> </p> <p><em><strong>Locus name in WM_194ind_7STRs.txt</strong></em></p> <p>Locus_1 AS-7-FAM<br> Locus_2 AS-12-PET<br> Locus_3 AS-20-NED<br> Locus_4 AS-34-FAM<br> Locus_5 GTTD9A-PET<br> Locus_6 AS-11-VIC<br> Locus_7 MS-AF-8-NED</p> <p> </p> <p><em><strong>Locus name in BV_199ind_8STRs.txt</strong></em></p> <p>Locus_1 Cg13B8-F_FAM<br> Locus_2 Cg6A1-F_VIC<br> Locus_3 Cg3F12-F_PET<br> Locus_4 Cg13H9-F_PET<br> Locus_5 Cg2E2-F_VIC<br> Locus_6 Cg3E10-F_FAM<br> Locus_7 Cg2A4-F_FAM<br> Locus_8 Cg3A8-F_NED</p>
A Comprehensive Solution for Securing Connected and Autonomous Vehicles (presentation video)
<p>Video recording of the online presentation for the publication M. Kamal et al., "A Comprehensive Solution for Securing Connected and Autonomous Vehicles," 2022 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2022, pp. 790-795, doi: 10.23919/DATE54114.2022.9774594.</p>
Data generated from: Functional connectivity of the world's protected areas
<p>Here, we provide the two primary global connectivity datasets generated in the study titled "Functional connectivity of the world's protected areas", including the protected area isolation (PAI) metric for all included protected areas (i.e., effective resistance), provided as a csv file, and the map of global mammal movement probability (i.e., electrical current density), provided as a tif. We also include the nationally aggregated PAI values in National_PAI.csv. National PAI represents the median PAI value for each country, after excluding values equal to -1.</p> <p>Generation of these datasets relied on the following three external data sources:</p> <p>- Observed mammal movement data (0.95 quantile displacement distances over 10-days), predictor variables and the linear mixed effects model presented in: M. A. Tucker <em>et al.</em>, <em>Science</em>. <strong>359</strong>, 466–469 (2018). </p> <p>- The 2009 Global Human Footprint map presented in: O. Venter <em>et al.</em>, <em>Nat. Communications.</em> <strong>7</strong>, 1–11 (2016). </p> <p>- The May 2020 and April 2018 versions of the World Database on Protected Areas, found at: UNEP-WCMC and IUCN, Protected Planet: the World Database on Protected Areas (WDPA), Cambridge, UK, (available at www.protectedplanet.com). </p> <p>Please read the Readme.txt for file details and cite the following paper if you use these data: Brennan, A., R. Naidoo, L. Greenstreet, Z. Mehrabi, N. Ramankutty and C. Kremen. Functional connectivity of the world's protected areas. Science (2022).</p> <p> </p>
Population connectivity and genetic offset in the spawning coral Acropora digitifera in Western Australia
<p><span>Anthropogenic </span>climate change has caused widespread loss of species biodiversity and ecosystem productivity across the globe, particularly on tropical coral reefs. Predicting the future vulnerability of reef-building corals, the foundation species of coral reef ecosystems, is crucial for cost-effective conservation planning in the Anthropocene. In this study, we combine regional population genetic connectivity and seascape analyses to explore patterns of genetic offset (the mismatch of gene-environmental associations under future climate conditions) in <em>Acropora digitifera</em> across 12 degrees of latitude in Western Australia. Our data revealed a pattern of restricted gene flow and limited genetic connectivity among geographically distant reef systems. Environmental association analyses identified a suite of loci strongly associated with the regional temperature variation. These loci helped forecasting future genetic offset in random forest and generalised dissimilarity models. These analyses predicted pronounced differences in the response of different reef systems in Western Australia to rising temperatures. Under the most optimistic future warming predictions (RCP 2.6), we observed a general pattern of increasing genetic offset with latitude. Under the most extreme climate scenario (RCP 8.5 in 2090-2100), coral populations at the Ningaloo World Heritage Area were predicted to experience a higher mismatch in genetic composition, compared to populations in the inshore Kimberley region. The study suggest complex and spatially heterogeneous patterns of climate-change vulnerability in coral populations across Western Australia, reinforcing the notion that regionally tailored conservation efforts will be most effective at managing coral reef resilience into the future.</p>
Connecting the Light Curves of Type IIP Supernovae to the Properties of their Progenitors
<p>This is the dataset for the manuscript "Connecting the Light Curves of Type IIP Supernovae to the Properties of their Progenitors" (Accepted to ApJ, ADS 2021arXiv210201118B, arxiv https://arxiv.org/abs/2102.01118). </p>
Maps of ecosystem multifunctionality and ecological connectivity for identifying Green Infrastructure networks in the European Alps
<p>High resolution raster datasets (20 meters) containing the results of an ecological connectivity and an ecosystem multifunctionality assessment for identifying Green Infrastructure networks in 10 pilot regions of the European Alps, modelled as part of the LUIGI Interreg Alpine Space project. Pilot regions include: department of Isère (FR), departments of Savoie and Haute-Savoie (FR), Munich Metropolitan Region (DE), Central Area of Salzburg (AT), South Burgenland (AT), Goriška region (SI), South Tyrol (IT), canton of Grisons (CH), Metropolitan City of Milan (IT), and Metropolitan City of Turin (IT). For a preview of the data and the results available for each pilot region <a href="https://www.alpine-space.org/projects/luigi/en/project-results/d.t1.2.1-pilot-regions-policy-briefs">click here</a></p> <p>Further information on the LUIGI project is available at: <a href="https://www.alpine-space.org/projects/luigi/en/home">https://www.alpine-space.org/projects/luigi/en/home</a></p> <p><a href="https://webassets.eurac.edu/31538/1661510408-luigi-wp1-technical-annex-mapping-a-green-infrastructure-network-in-the-alpine-space.pdf">https://webassets.eurac.edu/31538/1661510408-luigi-wp1-technical-annex-mapping-a-green-infrastructure-network-in-the-alpine-space.pdf </a></p> <p>The datasets include:</p> <ul> <li>a map for ecosystem service-based multifunctionality calculated out of the average of 11 standardized ecosystem service indicators: water provision, crop potential, timber production, fodder provision, pollination potential, carbon sequestration, nitrogen retention, natural hazard mitigation, runoff retention, outdoor recreation, and landscape aesthetics.</li> <li>a map of the modelled Ecological Network composed of core areas and ecological corridors. Corridors are modelled for medium-large forest mammal species and represent least-cost pathways connecting core areas. Different classes indicate areas with different levels of current ecological connectivity starting from core areas to areas in cities or anthropized land with no connectivity. Modeled corridors are presented in two classes to mirror different levels of prioritization and management actions.</li> <li>a map of the resistance of the landscape to the movement of forest mammal species. The landscape resistance raster has been developed by reclassifying and aggregating a high resolution (5m) land use and land cover map. Resistance values have been determined in relation to the naturalness of different land use and land cover classes. In this context, land use or landscape resistance is intended as the opposite of habitat suitability.</li> </ul>
Dataset for Chicumbane Connections
<p>Supporting datafile for paper "Chicumbane Connections, Upper Limpopo Valley during the first millennium". Site data and archaeological finds. Archaeological and Anthropological Sciences in review.</p>
CEDAR Project: A Whole-Atmospheric Perspective on Connections between Intra-Seasonal Variations in the Troposphere and Thermosphere
<p>This collaborative award is aimed at studying the relationship between the variability of thermospheric winds to the variability caused by wave structures generated in the tropical troposphere. This coupling is driven by wave excitation by deep convection in the tropical troposphere that can propagate vertically into the thermosphere. Tropospheric convection associated with the Madden‐Julian Oscillation (MJO), the dominant mode of intra-seasonal variability in tropical convection and circulation, is known to modulate the intensity of upward‐propagating gravity and Kelvin waves. Previous work demonstrated that a 90-day oscillation in tropospheric convection during 2009-2010 was imprinted on both thermospheric mean winds and the eastward propagating wavenumber 3 diurnal (DE3) tidal amplitudes. This modulation was observed by the GOCE and CHAMP satellites and modeled with the TIME-GCM. The research effort would broaden participation by involving and training two undergraduate student interns through the University of Colorado BOLD internship program that focuses on promoting the recruitment, retention, and development of traditionally underrepresented engineering students.<br> <br> The new research will follow up on the results obtained in recent studies that demonstrated that strong coupling between the troposphere and the thermosphere occurs on intra-seasonal timescales. The award will address the following questions:<br> Q1: How frequent, prevalent, and persistent are correlations between 30 to 100-day variations in the three regions of troposphere, mesosphere, and thermosphere, during the past two decades?<br> Q2: What plausible roles do large-scale upward propagating waves play in dynamically coupling tropical tropospheric intra-seasonal variability into the thermosphere?<br> Q3: Is there any observational evidence suggesting a connection between this troposphere-thermosphere intra-seasonal coupling and MJO, Quasi-Biennial Oscillation (QBO) and El Niño-Southern Oscillation (ENSO)?<br> The combination of available upper atmosphere satellite data with ground-, and model-based datasets would be studied to provide insight into whether the intra-seasonal variations in the waves are caused by variability in the tropospheric sources or by wave-mean flow interactions. In the case of the latter, the study would determine at which heights these interactions are occurring. This study will determine the contribution of global-scale wave coupling between the troposphere and the thermosphere, thus addressing outstanding issues of fundamental importance to the CEDAR community.</p> <p>This research primarily involves performing correlation analyses and extracting wave information from satellite (CHAMP, GOCE, Swarm-C, TIMED, OLR), ground (Kauai, Christmas Island, and Adelaide, Maui, Urbana, and Chile), and model (MERRA-2, TIE-GCM, and WACCM-X) -based datasets and processing, plotting, data produced in standard ways to draw scientific conclusions. </p> <p>This project does not generate any new physical or observational data. The Findable, Accessible, Interoperable and Reusable (FAIR) principles are followed by making data resources (e.g. code/software and metadata) resulting from this project publicly available.</p> <p>GOCE, CHAMP, Swarm-C data (V01) are available at ftp://anonymous@thermosphere.tudelft.nl/. SABER data (V2.0, L2B) are available at http://saber.gats-inc.com/data.php. Tl DI data (V3.7) are available at http:// timed.hao.ucar.edu/tidi/. OLR data are available at https://psl.noaa.gov/data/gridded/ data.interp_OLR.html. F10.7 data are available at http://www.swpc.noaa.gov/content/data-access. kp/ap data are available at ftp:// ftp.gfz-potsdam.de/pub/home/obs/ kp-ap/.</p>
ScienceDex guides
Understand access before you commit
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.