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695 results for “topologies”
Data from: Flow heterogeneity controls dissolution dynamics in topologically complex rocks
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Data from: Enhancement of the linear and nonlinear planar Hall effect by altermagnets on the surface of topological insulators
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Topology and kinetic pathways of colloidosome assembly and disassembly
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Data from: Mapping the topological proximity-induced gap in multiterminal Josephson junctions
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Reconfigurable non-Hermitian soliton combs using dissipative couplings and topological windings
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The topological nature of tag jumping in environmental DNA metabarcoding studies (sequencing raw data)
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Supporting information for: Accounting for the topology of road networks to better explain human-mediated dispersal in terrestrial landscapes
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Data for: Evaluating the impact of anatomical partitioning on summary topologies obtained with Bayesian phylogenetic analyses of morphological data
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Observation of topological frequency combs
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Detection of ghost introgression requires exploiting topological and branch length information
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Data from: Anomalous Landau quantization in intrinsic magnetic topological insulators
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Topological Botnet Detection
<p>Large-scale topological botnet detection datasets for graph machine learning and network security, containing 4 different types of synthetic botnet topologies and 2 different real botnet topologies overlaid onto large real-world background traffic communication networks.</p> <p>Each dataset contains a specific botnet topology, with 960 graphs in total, randomly split to train/val/test sets. There are labels on both nodes and edges indicating whether they were in the botnet (evil) community. Learning tasks could target at predicting on nodes to detect whether they are botnet nodes, or recovering the whole botnet community by also predicting on edges as whether they belong to the original botnet.</p> <p>There are no unique features on nodes or edges, as the detection is purely based on topological properties within the graph (topological discovery).</p> <p> </p>
Data from: From structure to function in mutualistic interaction networks: topologically important frugivores have greater potential as seed dispersers
1. Networks of mutualistic interactions between animals and plants are considered a pivotal part of ecological communities. However, mutualistic networks are rarely studied from the perspective of species-specific roles, and it remains to be established whether those animal species more relevant for network structure also contribute more to the ecological functions derived from interactions. 2. Here, we relate the contribution to seed dispersal of vertebrate species with their topological role in frugivore-plant interaction networks. For one year in two localities with remnant patches of Colombian tropical dry forest, we sampled abundance, morphology, behavior, and fruit consumption from fleshy-fruited plants of various frugivore species. 3. We assessed the network topological role of each frugivore species by integrating their degree of generalization in interactions with plants with their contributions to network nestedness and modularity. We estimated the potential contribution of each frugivore species to community-wide seed dispersal, on the basis of a set of frugivore ecological, morphological and behavioral characteristics important for seed dispersal, together with frugivore abundance and frugivory degree. 4. The various frugivore species showed strong differences in their network structural roles, with generalist species contributing the most to network modularity and nestedness. Frugivores also showed strong variability in terms of potential contribution to seed dispersal, depending on the specific combinations of frugivore abundance, frugivory degree and the different traits and behaviors. 5. For both localities, the seed dispersal potential of a frugivore species responded positively to its contribution to network structure, evidencing that the most important frugivore species in the network topology were also those making the strongest contribution as seed dispersers. Contribution to network structure was correlated with frugivore abundance, diet, and behavioral characteristics. This suggests that the species-level link between structure and function is due to the fact that the occurrence of frugivore-plant interactions depends largely on the characteristics of the frugivore involved, which also condition its ultimate role in seed dispersal. 22-May-2020
Learning to plan with uncertain topological maps: Dataset
<p>Dataset for training and evaluation of neural path planning algorithms, for the paper "Learning to Plan with Uncertain Topological Maps"</p> <p><a href="https://arxiv.org/abs/2007.05270">https://arxiv.org/abs/2007.05270</a></p>
Data from: Topological DNA-binding of SMC-like RecN promotes RecA-mediated DNA double-strand break repair
<p>Bacterial RecN, closely related to the structural maintenance of chromosomes (SMC) family of proteins, functions in the repair of DNA double-strand breaks (DSBs) by homologous recombination. However, the understanding of how RecN acts in concert with the RecA recombinase to promote DSB repair remains limited. Here, we demonstrated that the purified Escherichia coli RecN protein topologically loads onto both single-stranded DNA (ssDNA) and double-stranded DNA (dsDNA) that has a preference for ssDNA. RecN topologically bound to dsDNA slides off the end of linear dsDNA, but this is prevented by RecA nucleoprotein filaments on ssDNA, thereby allowing RecN to translocate to DSBs. Furthermore, we found that, once RecN is recruited onto ssDNA, it can topologically capture a second dsDNA substrate in an ATP-dependent manner, suggesting a role in synapsis. Indeed, RecN stimulates RecA-mediated D-loop formation and subsequent strand exchange activities. Our findings provide mechanistic insights into the recruitment of RecN to DSBs and sister chromatid interactions by RecN, both of which function in RecA-mediated DSB repair.</p>
Effects of Network Topology On the Performance of Consensus and Distributed Learning of SVMs Using ADMM
<p>The Alternating Direction Method Of Multipliers (ADMM) is a popular and promising distributed framework for solving large-scale machine learning problems. We consider decentralized consensus-based ADMM in which nodes may only communicate with one-hop neighbors. This may cause slow convergence. We investigate the impact of network topology on the performance of an ADMM-based learning of Support Vector Machine (SVM) using expander, and mean-degree graphs, and additionally some of the common modern network topologies. In particular, we investigate to which degree the expansion property of the network influences the convergence in terms of iterations, training and communication time. We furthermore suggest which topology is preferable. Additionally, we provide an implementation that makes these theoretical advances easily available. The results show that the performance of decentralized ADMM-based learning of SVMs in terms of convergence is improved using graphs with large spectral gaps, higher and homogeneous degrees.</p>
FIGURE 50. Preferred topology with ACCTRAN character optimisations. Strict consensus tree from 7 trees using implied weights K in The new Southeast Asian goblin spider genus Aposphragisma (Araneae, Oonopidae): diversity and phylogeny
FIGURE 50. Preferred topology with ACCTRAN character optimisations. Strict consensus tree from 7 trees using implied weights K=1–5 (L=149, CI=0.63, RI=0.77). Squares show synapomorphic (black) and homoplastic (white) character state changes. Numbers above the squares correspond to the character numbers, those below to character state changes. The ingroup Aposphragisma gen. nov. is marked in shades of grey: species showing completely ornamented sterna in light grey and those possessing sterna with a glabrous middle stripe ('stripe-clade') in dark grey.
Source dataset of Figs.3 and S10 of "Higher-order topological semimetal in acoustic crystals"
<p><strong>Fig_3.xlsx</strong> is the source data from the third figure in the main text and <strong>Fig_S10.xlsx </strong>is the source data from the tenth figure in Supplementary Information of our submitted manuscript in Nature Materials (NM20062441C ) entitled <em>Higher-order topological semimetal in acoustic crystals. </em>by Qiang Wei<span>,</span> Xuewei Zhang, Weiyin Deng, Jiuyang Lu, Xueqin Huang, Mou Yan, Gang Chen, Zhengyou Liu, Suotang Jia<span>.</span></p> <p> </p> <p> </p>
Data and Code for Inequality is rising where social network segregation interacts with urban topology
<p>This folder contains data and code to reproduce results of the paper "Inequality is rising where social network segregation interacts with urban topology". arXiv version: https://arxiv.org/abs/1909.11414.</p>
Data from: Likelihood of tree topologies with fossils and diversification rate estimation
Since the diversification process cannot be directly observed at the human scale, it has to be studied from the information available, namely the extant taxa and the fossil record. In this sense, phylogenetic trees including both extant taxa and fossils are the most complete representations of the diversification process that one can get. Such phylogenetic trees can be reconstructed from molecular and morphological data, to some extent. Among the temporal information of such phylogenetic trees, fossil ages are by far the most precisely known (divergence times are inferences calibrated mostly with fossils). We propose here a method to compute the likelihood of a phylogenetic tree with fossils in which the only considered time information is the fossil ages, and apply it to the estimation of the diversification rates from such data. Since it is required in our computation, we provide a method for determining the probability of a tree topology under the standard diversification model. Testing 21 our approach on simulated data shows that the maximum likelihood rate estimates from the phylogenetic tree topology and the fossil dates are almost as accurate as those obtained by taking into account all the data, including the divergence times. Moreover, they are substantially more accurate than the estimates obtained only from the exact divergence times (without taking into account the fossil record). We also provide an empirical example composed of 50 Permo-carboniferous eupelycosaur (early synapsid) taxa ranging in age from about 315 Ma (Late Carboniferous) to 270 Ma (shortly after the end of the Early Permian). Our analyses suggest a speciation (cladogenesis, or birth) rate of about 0.1 per lineage and per My, a marginally lower extinction rate, and a considerable hidden paleobiodiversity of early synapsids.
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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.