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9,152 results for “Networking”
Back to the Past - Analysing Backporting Practices in Package Dependency Networks
<p>This is the replication package of our paper on the practice of backporting in package distributions.</p> <p>Please refer to the instructions in the README file.</p>
Data from: Performance of social network sensors during Hurricane Sandy
Information flow during catastrophic events is a critical aspect of disaster management. Modern communication platforms, in particular online social networks, provide an opportunity to study such flow and derive early-warning sensors, thus improving emergency preparedness and response. Performance of the social networks sensor method, based on topological and behavioral properties derived from the "friendship paradox", is studied here for over 50 million Twitter messages posted before, during, and after Hurricane Sandy. We find that differences in users' network centrality effectively translate into moderate awareness advantage (up to 26 hours); and that geo-location of users within or outside of the hurricane-affected area plays a significant role in determining the scale of such an advantage. Emotional response appears to be universal regardless of the position in the network topology, and displays characteristic, easily detectable patterns, opening a possibility to implement a simple "sentiment sensing" technique that can detect and locate disasters.
The joint role of coevolutionary selection and network structure in shaping trait matching in mutualisms
<p>Data used in the "The joint role of coevolutionary selection and network structure in shaping trait matching in mutualisms"</p>
Efficient parallelization of tensor network contractions for simulating quantum computation
<p> In this paper, we demonstrate a classical simulation framework for quantum computation by contracting tensor networks of sizes previously deemed out of reach. The main contribution of this work is a parallelization scheme called <em>index slicing</em> that breaks down an infeasibly large tensor network contraction task into smaller subtasks that can be executed fully in parallel, without interdependencies or intermediate communications. As a benchmarking example, we show that our algorithm can reduce the simulation of the Sycamore random circuit sampling task to less than 20 days, achieving an acceleration of over five orders of magnitude compared to the original proposal. We then showcase the capabilities of the simulation framework via investigations of near-term quantum algorithms and quantum error correction. Given the ubiquity of tensor networks in quantum information science, we believe that our simulation framework will be a valuable tool in the era of quantum information technology.</p>
Data from: Severance of arbuscular mycorrhizal networks in restoration grasslands enhances seedling biomass
<p>1. Establishment and growth of grassland plant species is generally promoted by arbuscular mycorrhizal fungi (AMF) when grown in isolation. However, in grassland communities AMF form networks that may connect individual plants of different ages within and between species. Here, we use an in-growth core approach to examine how mycorrhizal networks influences performance of seedlings in grasslands.</p> <p>2. We selected 4 grass and 4 forb species with known negative or neutral-positive plant-soil feedback and grew them individually in steel mesh cores filled with living field soil. Cores were placed in six restored grasslands, three grasslands were of relatively young and three were of older successional age.</p> <p>3. Ingrowing mycorrhizal fungal hyphae were severed twice a week in half of all cores, which resulted into reduced AMF colonisation and increased seedling biomass, irrespective of the fields' succession stage, and the plants' grass/forb group, or plant-soil feedback type. In the control cores, root colonization by AMF was negatively correlated to seedling biomass, whereas there was no such relationships in the cores that had been lifted.</p> <p>4. We conclude that connections to arbuscular mycorrhizal networks of surrounding plants had a negative impact on biomass of establishing forb and grass seedlings.</p>
First application of artificial neural networks to estimate 21st century Greenland ice sheet surface melt: scripts and models
<p>In this repository you will find the models and the scripts used to generate the journal article: "First application of artificial neural networks to estimate 21st century Greenland ice sheet surface melt."</p> <p>The model.tar contains the script for making a model, in addition to the models used in the journal artcile.</p> <p>The proc.tar contains the scripts used for processing of the CMIP6 data.</p> <p>The plots.tar contains scripts for generating the plots in the journal article, as well as the supplementary information.</p>
Figure 1. Haplotype network derived from 704 in Repeated sampling adds to the genetic diversity of Lepidochelys olivacea (Eschscholtz 1829) olive ridley sea turtle
Figure 1. Haplotype network derived from 704 bp mitochondrial D-loop fragment. Circle sizes are proportional to the frequency of each haplotype. The black circles are hypothetical haplotypes not sampled. Each colour represents the ocean basin where the sample was taken: blue is Pacific Ocean, yellow is Indian Ocean, red is Atlantic Ocean, and green is Indo-Pacific Ocean.
BIOFRUITNET - Boosting Innovation in Organic FRUIT production through knowledge NETworks - WP2 - Bibliographic search in Web of Science
<p>In the project BIOFRUITNET (Boosting Innovation in Organic FRUIT production through knowledge NETworks, HORIZON 2020 Grant Agreement No. 862850), nine search strings covering <strong>stone fruits, pome fruits and citrus fruits</strong>, within the selected main topics: <strong>pests, plant diseases and plant nutrition </strong>were developed, to target the most relevant scientific literature within the topics. The bibliographic searches were conducted on October 19, 2020 in Web of Science. The databases presented are the complete lists of references included from the WoS search. These lists will be processed to select the most relevant materials ready for practice in a following project work package. Project homepage: <a href="https://biofruitnet.eu/">https://biofruitnet.eu/</a></p>
Identifying contributors to PM2.5 simulation biases of chemical transport model using fully connected neural networks
<p>The processed data and codes in the study are included. </p> <p><strong>Source data:</strong></p> <p>The training and testing dataset is composed of observed and simulated data of pollutants and meteorology in the BTH and YRD regions in the whole year of 2015. The processed datasets used for training are named as "dataset_BTH" and "dataset_YRD" in the folder.</p> <ul> <li><em>The hourly observed pollution data</em> are from China National Urban Air Quality Real-time Release Platform of the National Environmental Monitoring Station</li> <li><em>The hourly simulated pollutants data</em> comes from the output of WRF-CMAQv5.2 (spatial resolution of 27 km).</li> <li><em>Meteorological observation data</em> is provided by China Meteorological Data Service Centre</li> <li><em>The meteorological simulation data</em> comes from the simulation results of the WRF model</li> </ul> <p><strong>Codes:</strong></p> <ul> <li>preprocessing of raw CMAQ data, observed pollution data and meteorological data</li> <li>bulid and train process of fully connected neural networks</li> <li>calculation of correlation between variables</li> <li>feature selection method</li> <li>contribution analysis</li> </ul>
Figure 5. Minimum spanning haplotype network derived from a 658 base-pair cytochrome c oxidase subunit I in Six degrees of separation in barnacles? Assessing genetic variability in the sea-turtle epibiont Stomatolepas elegans (Costa) among turtles, beaches and oceans
Figure 5. Minimum spanning haplotype network derived from a 658 base-pair cytochrome c oxidase subunit I (COI) fragment from 57 Stomatolepas elegans collected from nine different Lepidochelys olivacea nesting on Playa Teopa, Jalisco, Mexico, six S. elegans from Caretta caretta from the western Atlantic, and six S. praegustator from C. caretta from the western Atlantic. Circle sizes are proportional to the frequency of each haplotype, with haplotype 1 being most common. Coloured pie slices are also proportional, and represent the number of S. elegans from each turtle characterized by the respective haplotype. Colours represent the nine Mexican turtles randomly sampled for S. elegans populations. Open circles with numbers indicate Atlantic haplotypes. Solid black circles designate hypothetical missing haplotypes. The network includes S. elegans haplotypes 1–21, and S. praegustator haplotypes 19, 26–30. Haplotypes 1–17, shown in colour, represent Jalisco, Mexico specimens collected from nine different turtles in the Pacific, and haplotypes 18–21 and 26–30, shown as unshaded circles, represent southeastern United States Atlantic specimens collected from six different C. caretta (see Table 1).
Step-by-step simulation of the ROUTR algorithm on a road-network graph.
<p>This video simulates, step-by-step, the application of the ROUTR algorithm on a small road-network graph.</p>
Trained models for "Neural mechanisms of working memory accuracy revealed by recurrent neural networks"
<p>There are three trained models:</p> <p>1. data/6tasks_8loc_256neuron_odr3000_seed0: odr(3s delay ) task with 8 input units in a ring and 256 neurons</p> <p>2. data/6tasks_360loc_256neuron: odr(1.5s delay) task with 360 input units in a ring and 256 neurons</p> <p>3. odr_mix_uniform_00_30_01step_6tasks: odr(variable delay from 0 to 3s with 0.1s step) task with 8 input units in a ring and 256 neurons</p>
Figure 3. Ninety-five per cent maximum parsimony networks obtained for the 12 in Mitochondrial DNA genetic variation and phylogeography of the recently described vole species Proedromys liangshanensis Liu, Sun, Zeng and Zhao, 2007 (Rodentia: Arvicolinae)
Figure 3. Ninety-five per cent maximum parsimony networks obtained for the 12 haplotypes in Proedromys liangshanensis. Circle sizes are proportional to haplotype frequencies.
Figure 3. Haplotype networks for cytochrome oxidase I in Bythinella Moquin-Tandon, 1856 (Gastropoda: Rissooidea: Bythinellidae) in Romania: species richness in a glacial refugium
Figure 3. Haplotype networks for cytochrome oxidase I (COI), computed with TCS 1.21; square and ellipse size reflects haplotype frequency; connection limit excluding homoplastic changes was set to 95% (hence excluding some haplotypes from network); haplotypes in squares have biggest outgroup weights.
All raw data for the transport part of 'In-plane selective area InSb-Al nanowire quantum networks'
<p>This folder contains all the raw data gathered on the devices used in the transport part of the paper "In-plane selective area InSb–Al nanowire quantum networks" https://doi.org/10.1038/s42005-020-0324-4.</p>
FIGURE 3. Haplotype network for the 800 in Genetic evaluation of the Baja California rock squirrel Otospermophilus atricapillus (Rodentia: Sciuridae)
FIGURE 3. Haplotype network for the 800-bp Cyt b data set includes populations from California and the Baja California Peninsula. Each perpendicular hash mark across the line between adjacent haplotypes in the network represents a single-base substitution. The circle size is directly proportional to the number of specimens per haplotype; the key to the haplotype (Table 1) is adjacent to each circle; some haplotypes are present in more than one population. The clades are in boxes; Clade A (Southern Clade, lowlands across California and Baja California Peninsula); Clade B (Northern Clade, El Dorado Natural Forest); and Clade C (Central Clade, California highlands in Yosemite). Color for the haplotype circles are based on subspecies designation (see material and methods from subspecies allocation. Solid circle = O. b. atricapillus, dark gray circle O. b. beecheyi, light gray circle O. b. douglasii, open circle = O. b. fisheri, solid ellipse = O. b. nudipes, dark gray ellipse = O. b. parvulus, light gray ellipse = O. b. rupinarum, and open ellipse = O. b. sierrae.
Building pseudo proxy paleotempestology networks using synthetic North Atlantic tropical cyclones
<p>This release contains the past millennium synthetic storm datasets (MPI-ESM; CESM-LME) and scripts needed to develop pseudo paleohurricane compilations used in Wallace et al. (2021). Version 2 includes updated storm datasets that are re-calibrated to have long term mean frequency that matches the satellite era tropical cyclone frequency. The site properties (resolution, radius) are also updated. </p>
FIGURE 2. Minimum spanning haplotype networks for all S in Review of the systematic status of Sceloporus arenicolus Degenhardt and Jones, 1972 with an estimate of divergence time
FIGURE 2. Minimum spanning haplotype networks for all S. graciosus group samples sequenced at each of three nuclear loci. Size of each circle corresponds to the frequency of that haplotype. Shading corresponds to clade membership in Figure 3.
FIGURE 2. A phylogenetic network for a hypothetical data set. This network represents the relationships between four taxa, A-D in Exploring character conflict in molecular data*
FIGURE 2. A phylogenetic network for a hypothetical data set. This network represents the relationships between four taxa, A-D. The length of branch (a) is proportional to the strength of support for the relationship (A,C)(B,D). The length of branch (b) is proportional to the strength of support for the relationship (A,B)(C,D). In this example there is conflicting support for both of these arrangements, but more weight is given to (A,C)(B,D) than to (A,B)(C,D).
Figure 5. Parsimony network obtained with TCS for the 18S rRNA information from Echiniscus species. A in Congruence between molecular phylogeny and cuticular design in Echiniscoidea (Tardigrada, Heterotardigrada)
Figure 5. Parsimony network obtained with TCS for the 18S rRNA information from Echiniscus species. A photo with the cuticular design for each species is provided. E. merokensis SP, Spanish Echiniscus merokensis merokensis. E. merokensis Tar759 SUE, subspecies Echiniscus merokensis suecicus. The three supported groups found among the Echiniscus species, based on cuticle design, are identified with dotted squares, and named as I, II, and III.
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.