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317 results for “Hierarchy”
EOL Dynamic Hierarchy Erebidae Patch (ERE)
<p>Updated Erebidae classification covering subfamilies, tribes, subtribes, and genera. Compiled from multiple sources:</p> <p>Da Costa, MA, Weller, SJ (2005). Phylogeny and classification of Callimorphini (Lepidoptera: Arctiidae: Arctiinae). Zootaxa 1025:1–94.</p> <p>De Prins J. & De Prins W. 2011–2019. Afromoths, online database of Afrotropical moth species (Lepidoptera). World Wide Web electronic publication: <a href="http://www.afromoths.net/" target="_blank" rel="nofollow noopener">http://www.afromoths.net</a></p> <p>de Vos, R. 2011. Nicetosoma Gen. Nov., a New Genus for the ‘Spilosoma’ Niceta Group of Species East of the Weber Line (Lepidoptera: Erebidae, Arctiinae, Arctiini). Suara Serangga Papua 5 (4): 109-144.</p> <p>Dubatolov, VV (2010). Tiger-moths of Eurasia (Lepidoptera, Arctiidae) (Nyctemerini by Rob de Vos & Vladimir V. Dubatolov). Neue Entomologische Nachrichten 65:1–106.</p> <p>Edwards, ED (1996). Arctiidae. In: Nielsen E.S., Edwards E.D. & Rangsi T.V. (eds) Checklist of the Lepidoptera of Australia, Monographs on Australian Lepidoptera: 278–286.</p> <p>Ferguson DC, Opler PA (2006) Checklist of the Arctiidae (Lepidoptera: Insecta) of the continental United States and Canada. Zootaxa 1299:1–33.</p> <p>Fibiger, Michael (2007). Revision of the Micronoctuidae (Lepidoptera: Noctuoidea). Part 1, Taxonomy of the Pollexinae. Zootaxa 1567:1-116.</p> <p>Fibiger, Michael (2008). Revision of the Micronoctuidae (Lepidoptera: Noctuoidea). Part 2, Taxonomy of the Belluliinae, Magninae and Parachrostiinae. Zootaxa 1867:1-136.</p> <p>Fibiger, Michael (2010). Revision of the Micronoctuidae (Lepidoptera: Noctuoidea) Part 3, Taxonomy of the Tactusinae. Zootaxa 2583:1–119.</p> <p>Fibiger, Michael (2011). Revision of the Micronoctuidae (Lepidoptera: Noctuoidea). Part 4, Taxonomy of the subfamilies Tentaxinae and Micronoctuinae. Zootaxa 2842:1–188.</p> <p>Fibiger, Michael, Hacker, Hermann (2005). Systematic List of the Noctuoidea of Europe (Notodontidae, Nolidae, Arctiidae, Lymantriidae, Erebidae, Micronoctuidae, and Noctuidae). Esperlana 11:93–205.</p> <p>Fibiger, Michael, Han, Hui-Lin & Kononenko, Vladimir S. (2011). Five new species and one new subspecies of Micronoctuidae from China, with a checklist of Chinese species, including Taiwan (Lepidoptera: Noctuoidea, Micronoctuidae). Zootaxa. 2777: 1–13.</p> <p>Fibiger, Michael, Kononenko, Vladimir S. (2008). Revision of the Micronoctuidae species occurring in the Russian Far East and neighbouring countries with description of a new species (Lepidoptera, Noctuoidea). Zootaxa 1890:50-58.</p> <p>Fibiger, Michael, Lafontaine, J. Donald (2005). A review of the higher classification of the Noctuoidea (Lepidoptera) with special reference to the Holarctic fauna. Esperiana 11:7-92.</p> <p>Goodger DT, Watson A (1995) The Afrotropical Tiger-Moths. An illustrated catalogue, with generic diagnosis and species distribution, of the Afrotropical Arctiinae (Lepidoptera: Arctiidae). Apollo Books Aps.: Denmark, 55 pp.</p> <p>Han, H. L., & Kononenko, V. S. (2017). Two replacement names of the genus group of Micronoctuini and a new species of the genus Tentaxus Han & Kononenko from Sabah, East Malaysia (Lepidoptera, Erebidae, Hypenodinae). Taxonomic study of Micronoctuini. Contribution I. Zootaxa, 4362(2), 259. doi:10.11646/zootaxa.4362.2.5</p> <p>Holloway, Jeremy D. (1988). The Moths of Borneo Part 6: Family Arctiidae, subfamilies Syntomine, Euchromiinae Arciinae; Noctuidae misplaced in Arctiidae. The Moths of Borneo. Southdene Sdn. Bhd.</p> <p>Holloway, Jeremy D. (1999). The Moths of Borneo: Family Lymantriidae. Malayan Nature Journal 53:1-188.</p> <p>Holloway, Jeremy D. (2001). The Moths of Borneo Part 7: Family Arctiidae, Subfamily Lithosiinae. The Moths of Borneo. Southdene Sdn. Bhd.</p> <p>Holloway, Jeremy D. (2005) The Moths of Borneo Parts 15 & 16: Family Noctuidae, Subfamily Catocalinae" The Moths of Borneo. Southdene Sdn. Bhd.</p> <p>Holloway, Jeremy D. (2008). The Moths of Borneo: family Noctuidae, subfamilies Rivulinae, Phytometrinae, Herminiinae, Hypeninae and Hypenodinae. Malayan Nature Journal 60:1-267.</p> <p>Homziak, Nicholas T., Breinholt, Jesse W., Kawahara, Akito Y. (2016). A historical review of the classification of Erebinae (Lepidoptera: Erebidae). Zootaxa 4189(3):516–542. doi:<a href="https://doi.org/10.11646/zootaxa.4189.3.4.">10.11646/zootaxa.4189.3.4.</a></p> <p>Kaleka, AS, Rose, HS (2002). Inventory of species of Miltochrista Hübner (Lithosiinae: Arctiidae: Lepidoptera) from northwestern and northeastern India. Zoos__ Print Journal 17 (8):853-856.</p> <p>Kirti, J.S. & Singh, N. (2016) Arctiid Moths of India. Vol. 2. Nature Books India, New Delhi, 214 pp.</p> <p>Kononenko, VS, Pinratana, A (2013). Moths of Thailand Vol. 3, Part 2. Noctuoidea. An illustrated Catalogue of Erebidae, Nolidae, Euteliidae, and Noctuidae (Insecta: Lepidoptera) in Thailand. Bangkok: Brothers of St. Gabriel in Thailand.</p> <p>Lafontaine, J. Donald, Fibiger, Michael (2006). Revised higher classification of the Noctuoidea (Lepidoptera) Canadian Entomologist 138:610-635.</p> <p>Lafontaine, Donald; Walsh, J. Bruce (2010). A review of the subfamily Anobinae with the description of a new species of Baniana Walker from North and Central America (Lepidoptera, Erebidae, Anobinae). ZooKeys 39:3–11. doi:<a href="https://doi.org/10.3897/zookeys.39.428">10.3897/zookeys.39.428</a></p> <p>Lafontaine, Donald, Schmidt, Christian (2010). Annotated check list of the Noctuoidea (Insecta, Lepidoptera) of North America north of Mexico. ZooKeys 40:1-239. doi:<a href="https://doi.org/10.3897/zookeys.40.414">10.3897/zookeys.40.414</a></p> <p>Lafontaine, J. Donald; Schmidt, B. Christian (2013). Additions and corrections to the check list of the Noctuoidea (Insecta, Lepidoptera) of North America north of Mexico. ZooKeys. 264:227–236. doi:<a href="https://10.0.15.57/zookeys.264.4443">10.3897/zookeys.264.4443</a></p> <p>Savela, Markku. 2020. Lepidoptera and Some Other Life Forms. World Wide Web electronic publication: <a href="https://ftp.funet.fi/pub/sci/bio/life/intro.html" target="_blank" rel="nofollow noopener">https://ftp.funet.fi/pub/sci/bio/life/intro.html</a></p> <p>Van Nieukerken, E.J., Kaila, L., Kitching, I.J., Kristensen, N.P., Lees, D.C., Minet, J., Mitter, C., Mutanen, M., Regier, J.C., Simonsen, T.J. and Wahlberg, N., 2011. Order Lepidoptera Linnaeus, 1758. In: Zhang, Z.-Q.(Ed.) Animal biodiversity: an outline of higher-level classification and survey of taxonomic richness. Zootaxa, 3148(1):212-221.</p> <p>Volynkin, Anton V. 2016. On the generic placement and taxonomic status of some Miltochrista taxa described by Franz Daniel (Lepidoptera, Erebidae, Arctiinae) Zootaxa 4179(2):244-252.</p> <p>Volynkin, Anton V. 2017. Description of a New Species of Miltochrista Hübner from Vietnam, with Eight New Combinations (Lepidoptera, Erebidae, Arctiinae). Zootaxa 4286(1):145. <a href="https://doi.org/10.11646/zootaxa.4286.1.13" target="_blank" rel="nofollow noopener">https://doi.org/10.11646/zootaxa.4286.1.13</a>.</p> <p>Volynkin, Anton V., Singh, N., Cerný, K., Kirti, J. S., Datta, H. S. 2020. Revision of the Miltochrista obliquilinea species-group, with descriptions of four new species (Lepidoptera, Erebidae, Arctiinae, Lithosiini) Zootaxa 4780(3):448-470.</p> <p>Watson A (1971) An illustrated Catalog of the Neotropic Arctiinae type in the United States National Museum (Lepidoptera: Arctiidae) Part 1. Smithsonian Contributions to Zoology 50:1–361</p> <p>Zahiri, Reza; et al. (2011). Molecular phylogenetics of Erebidae (Lepidoptera, Noctuoidea). Systematic Entomology 37:102–124. doi:<a href="https://doi.org/10.1111/j.1365-3113.2011.00607.x">10.1111/j.1365-3113.2011.00607.x</a></p> <p>Zahiri, Reza; et al. (2011). A new molecular phylogeny offers hope for a stable family level classification of the Noctuoidea (Lepidoptera). Zoologica Scripta 40:158–173. doi:<a href="https://doi.org/10.1111/j.1463-6409.2010.00459.x">10.1111/j.1463-6409.2010.00459.x</a></p> <p>Zahiri, Reza; et al. (2012). Molecular phylogenetics of Erebidae (Lepidoptera, Noctuoidea). Systematic Entomology 37:102–124. doi:<a href="https://doi.org/10.1111/j.1365-3113.2011.00607.x]">10.1111/j.1365-3113.2011.00607.x</a></p> <p>Zahiri, Reza; et. al (2013). Relationships among the basal lineages of Noctuidae (Lepidoptera, Noctuoidea) based on eight gene regions. Zoologica Scripta 42:488–507. doi:<a href="https://doi.org/10.1111/zsc.12022">10.1111/zsc.12022</a></p> <p>Zaspel, JM, Branham, MA (2008). World Checklist of Tribe Calpini (Lepidoptera: Noctuidae: Calpinae). Insecta Mundi 0047:1-15.</p>
EOL Dynamic Hierarchy: Dynamic Hierarchy Version 2.1
Currently active Dynamic Hierarchy and archived versions. For more information, see: <p></p>https://eol.org/docs/eol-dynamic-hierarchy<p></p>The Encyclopedia of Life (EOL, eol.org) aggregates biodiversity information from more than 400 sources and provides access to the data through taxon pages, visual query and application programming interfaces. Scientific names are essential elements of the data integration infrastructure, but their shortcomings as key identifiers are well documented (Patterson et al., 2016). Complex automated workflows and continuous manual curation are required to address idiosyncrasies of source taxonomies, variation in data quality, and conflicting taxonomic opinions. To achieve a harmonized taxonomic view of EOL content, names from data sources are mapped to a dynamic reference hierarchy ([see current version here](<p></p>https://opendata.eol.org/dataset/tram-807-808-809-810-dh-v1-1/resource/00adb47b-57ed-4f6b-8f66-83bfdb5120e8)) using an algorithm that leverages canonical name strings, hierarchical information (ancestry, descendants), taxonomic ranks, synonym data, and author strings. Names that cannot be associated with a reference taxon are still accessible, but their unmapped status excludes them and any associated content from certain core EOL functions. For more information about the EOL taxonomy, see [EOL Dynamic Hierarchy](<p></p>https://eol.org/docs/eol-dynamic-hierarchy)
EOL Dynamic Hierarchy: EOL Dynamic Hierarchy Index
Currently active Dynamic Hierarchy and archived versions. For more information, see: <p></p>https://eol.org/docs/eol-dynamic-hierarchy<p></p>This is a Darwin Core Archive with an index file linking taxonomic names to EOL page IDs. Information about taxon authors, taxonomic ranks and higher classification are also provided as context. This file only includes accepted names that are mapped to the EOL reference hierarchy. Synonyms and unmapped names are not included. The Encyclopedia of Life (EOL, eol.org) aggregates biodiversity information from more than 400 sources and provides access to the data through taxon pages, visual query and application programming interfaces. Scientific names are essential elements of the data integration infrastructure, but their shortcomings as key identifiers are well documented (Patterson et al., 2016). Complex automated workflows and continuous manual curation are required to address idiosyncrasies of source taxonomies, variation in data quality, and conflicting taxonomic opinions. To achieve a harmonized taxonomic view of EOL content, names from data sources are mapped to a dynamic reference hierarchy ([see current version here](<p></p>https://opendata.eol.org/dataset/tram-807-808-809-810-dh-v1-1/resource/00adb47b-57ed-4f6b-8f66-83bfdb5120e8)) using an algorithm that leverages canonical name strings, hierarchical information (ancestry, descendants), taxonomic ranks, synonym data, and author strings. Names that cannot be associated with a reference taxon are still accessible, but their unmapped status excludes them and any associated content from certain core EOL functions. For more information about the EOL taxonomy, see [EOL Dynamic Hierarchy](<p></p>https://eol.org/docs/eol-dynamic-hierarchy)
EOL Dynamic Hierarchy: Dynamic Hierarchy Version 1.1
Currently active Dynamic Hierarchy and archived versions. For more information, see: <p></p>https://eol.org/docs/eol-dynamic-hierarchy<p></p>May 2019 The Encyclopedia of Life (EOL, eol.org) aggregates biodiversity information from more than 400 sources and provides access to the data through taxon pages, visual query and application programming interfaces. Scientific names are essential elements of the data integration infrastructure, but their shortcomings as key identifiers are well documented (Patterson et al., 2016). Complex automated workflows and continuous manual curation are required to address idiosyncrasies of source taxonomies, variation in data quality, and conflicting taxonomic opinions. To achieve a harmonized taxonomic view of EOL content, names from data sources are mapped to a dynamic reference hierarchy ([see current version here](<p></p>https://opendata.eol.org/dataset/tram-807-808-809-810-dh-v1-1/resource/00adb47b-57ed-4f6b-8f66-83bfdb5120e8)) using an algorithm that leverages canonical name strings, hierarchical information (ancestry, descendants), taxonomic ranks, synonym data, and author strings. Names that cannot be associated with a reference taxon are still accessible, but their unmapped status excludes them and any associated content from certain core EOL functions. For more information about the EOL taxonomy, see [EOL Dynamic Hierarchy](<p></p>https://eol.org/docs/eol-dynamic-hierarchy)
TRAM-804 Integrated Taxonomic Information System (ITIS) Taxonomic Hierarchy: ITIS for DH from 01-Dec-2020 downloads
Authoritative taxonomic information on plants, animals, fungi, and microbes of North America and the world. ITIS ia a partnership of U.S., Canadian, and Mexican agencies (ITIS-North America); other organizations; and taxonomic specialists. ITIS is also a partner of Species 2000 and the Global Biodiversity Information Facility (GBIF).<p></p>
TRAM-804 Integrated Taxonomic Information System (ITIS) Taxonomic Hierarchy: ITIS hierarchy March 31 2020
Authoritative taxonomic information on plants, animals, fungi, and microbes of North America and the world. ITIS ia a partnership of U.S., Canadian, and Mexican agencies (ITIS-North America); other organizations; and taxonomic specialists. ITIS is also a partner of Species 2000 and the Global Biodiversity Information Facility (GBIF).<p></p>from Aug 28 2019 downloads, with vernacular names removed
TRAM-804 Integrated Taxonomic Information System (ITIS) Taxonomic Hierarchy: ITIS hierarchy from 28-Aug-2019 downloads
Authoritative taxonomic information on plants, animals, fungi, and microbes of North America and the world. ITIS ia a partnership of U.S., Canadian, and Mexican agencies (ITIS-North America); other organizations; and taxonomic specialists. ITIS is also a partner of Species 2000 and the Global Biodiversity Information Facility (GBIF).<p></p><p></p>https://eol-jira.bibalex.org/browse/DATA-1824
TRAM-804 Integrated Taxonomic Information System (ITIS) Taxonomic Hierarchy: ITIS hierarchy temp fix
Authoritative taxonomic information on plants, animals, fungi, and microbes of North America and the world. ITIS ia a partnership of U.S., Canadian, and Mexican agencies (ITIS-North America); other organizations; and taxonomic specialists. ITIS is also a partner of Species 2000 and the Global Biodiversity Information Facility (GBIF).<p></p>ITIS hierarchy from 25-Feb-2019 downloads, with kingdom column removed.
TRAM-804 Integrated Taxonomic Information System (ITIS) Taxonomic Hierarchy: ITIS hierarchy from 25-Feb-2019 downloads
Authoritative taxonomic information on plants, animals, fungi, and microbes of North America and the world. ITIS ia a partnership of U.S., Canadian, and Mexican agencies (ITIS-North America); other organizations; and taxonomic specialists. ITIS is also a partner of Species 2000 and the Global Biodiversity Information Facility (GBIF).<p></p>
TRAM-804 Integrated Taxonomic Information System (ITIS) Taxonomic Hierarchy: ITIS hierarchy from 28-Jul-2020 downloads
Authoritative taxonomic information on plants, animals, fungi, and microbes of North America and the world. ITIS ia a partnership of U.S., Canadian, and Mexican agencies (ITIS-North America); other organizations; and taxonomic specialists. ITIS is also a partner of Species 2000 and the Global Biodiversity Information Facility (GBIF).<p></p><p></p>https://eol-jira.bibalex.org/browse/TRAM-987
TRAM-804 Integrated Taxonomic Information System (ITIS) Taxonomic Hierarchy: ITIS hierarchy from 31-Mar-2019 downloads
Authoritative taxonomic information on plants, animals, fungi, and microbes of North America and the world. ITIS ia a partnership of U.S., Canadian, and Mexican agencies (ITIS-North America); other organizations; and taxonomic specialists. ITIS is also a partner of Species 2000 and the Global Biodiversity Information Facility (GBIF).<p></p>
Data from: Parallel mechanisms signal a hierarchy of sequence structure violations in the auditory cortex
<p>The brain predicts regularities in sensory inputs at multiple complexity levels, with neuronal mechanisms that remain elusive. Here, we monitored auditory cortex activity during the local-global paradigm, a protocol nesting different regularity levels in sound sequences. We observed that mice encode local predictions based on stimulus occurrence and stimulus transition probabilities, because auditory responses are boosted upon prediction violation. This boosting was due to both short-term adaptation and an adaptation-independent surprise mechanism resisting anesthesia. In parallel, and only in wakefulness, VIP interneurons responded to the omission of the locally expected sound repeat at sequence ending, thus providing a chunking signal potentially useful for establishing global sequence structure. When this global structure was violated, by either shortening the sequence or ending it with a locally expected but globally unexpected sound transition, activity slightly increased in VIP and PV neurons respectively. Hence, distinct cellular mechanisms predict different regularity levels in sound sequences.</p>
Data from: Tropical arboreal ants form dominance hierarchies over nesting resources
Interspecific dominance hierarchies have been widely reported across animal systems. High-ranking species are expected to monopolize more resources than low-ranking species via resource monopolization. In some ant species, dominance hierarchies have been used to explain species coexistence and community structure. However, it remains unclear whether or in what contexts dominance hierarchies occur in tropical ant communities. This study seeks to examine whether arboreal twig-nesting ants competing for nesting resources in a Mexican coffee agricultural ecosystem are arranged in a linear dominance hierarchy. We described the dominance relationships among 10 species of ants and measured the uncertainty and steepness of the inferred dominance hierarchy. We also assessed the orderliness of the hierarchy by considering species interactions at the network level. Based on the randomized Elo-rating method, we found that the twig-nesting ant species Myrmelachista mexicana ranked highest in the ranking, while Pseudomyrmex ejectus was ranked as the lowest in the hierarchy. Our results show that the hierarchy was intermediate in its steepness, suggesting that the probability of higher ranked species winning contests against lower ranked species was fairly high. Motif analysis and significant excess of triads further revealed that the species networks were largely transitive. This study highlights that some tropical arboreal ant communities organize into dominance hierarchies.
Data from: Contingency rules for pathogen competition and antagonism in a genetically based, plant defense hierarchy
1. Plant defense against pathogens includes a range of mechanisms, including, but not limited to, genetic resistance, pathogen-antagonizing endophytes, and pathogen competitors. The relative importance of each mechanism can be expressed in a hierarchical view of defense. Several recent studies have shown that pathogen antagonism is inconsistently expressed within the plant defense hierarchy. Our hypothesis is that the hierarchy is governed by contingency rules that determine when and where antagonists reduce plant disease severity. 2. Here, we investigated whether pathogen competition influences pathogen antagonism using Populus as a model system. In three independent field experiments, we asked whether competition for leaf mesophyll cells between a Melampsora rust pathogen and a microscopic, eriophyid mite affects rust pathogen antagonism by fungal leaf endophytes. The rust pathogen has an annual, phenological disadvantage in competition with the mite because the rust pathogen must infect its secondary host in spring before infecting Populus. We varied mite-rust competition by utilizing Populus genotypes characterized by differential genetic resistance to the two organisms. We inoculated plants with endophtyes and allowed mites and rust to infect plants naturally. 3. Two contingency rules emerged from the three field experiments: 1) pathogen antagonism by endophytes can be preempted by host genes for resistance that suppress pathogen development, and 2) pathogen antagonism by endophtyes can secondarily be preempted by competitive exclusion of the rust by the mite. 4. Synthesis: Our results point to a Populus defense hierarchy with resistance genes on top, followed by pathogen competition, and finally pathogen antagonism by endophytes. We expect these rules will help to explain the variation in pathogen antagonism that is currently attributed to context dependency.
Dataset - An Analytical Hierarchy Process (AHP) model for mapping expectations
<p>This dataset contains detailed information about an Analytical Hierarchy Process (AHP) model developed in order to map actors' perceptions about their contributions to a gender policy. </p>
Main text figure data and scripts for "Simulating optical linear absorption for mesoscale molecular aggregates: an adaptive hierarchy of pure states approach"
<p>(as README.txt):</p> <p>Main text figure data and scripts for “Simulating optical linear absorption for mesoscale molecular aggregates: an adaptive hierarchy of pure states approach”, by Tarun Gera, Lipeng Chen, Alex Eisfeld, Jeffrey R. Reimers, Elliot J. Taffet and Doran I. G. B. Raccah.</p> <p>Each directory is dedicated to a particular figure published in the paper. In each directory there are sub-directories which contains the data plotted in each panel. Each data file is a 2-D list in the format of (x,y) for each plot. There are python scripts (Fig_X.py) in each directory to plot the data.</p> <p>Table of contents:</p> <p>Figure_2:</p> <p> - 4_site_edge_contri.npy: Calculated edge sites contribution to the total absorption spectrum for a 4-site chain system v/s energy. <br> - 4_site_inner_contri.npy: Calculated inner sites contribution to the total absorption spectrum for a 4-site chain system v/s energy. <br> - 4_site_total_spectra.npy: Calculated total absorption spectrum for a 4-site chain system v/s energy. </p> <p><br> Figure_3:</p> <p>Panel A:<br> <br> - Mean_Error_Edge.npy: Mean error for the edge case v/s number of trajectories.<br> - Mean_Error_Inner.npy: Mean error for the inner case v/s number of trajectories.<br> - Mean_Error_SS.npy: Mean error for a single site initial condition v/s number of trajectories.<br> - Mean_Error_GD.npy: Mean error for a 4-site chain system with Gaussian distributed site energies v/s number of trajectories.</p> <p>Panel B: </p> <p> - Scaled_error_SS.npy: Mean error for a single site initial condition normalized by the square-root of one v/s number of trajectories.<br> - Scaled_error_PS.npy: Mean error for a pair site initial condition normalized by the square-root of two v/s number of trajectories.<br> - Scaled_error_AS.npy: Mean error for an all site initial condition normalized by the square-root of four v/s number of trajectories.</p> <p>Figure_4: </p> <p>Panel_A:</p> <p> - List_Error.npy: Calculated mean error for a 4-site chain for a set of auxiliary error bounds.</p> <p>Panel_B:</p> <p> - Cw_4S_HOPS.npy: Absorption spectrum for a 4-site chain calculated using dyadic HOPS v/s energy.<br> - Cw_4S_DadHOPS.npy: Absorption spectrum for a 4-site chain calculated using DadHOPS v/s energy.</p> <p>Panel_C: </p> <p> - Cw_12S_DadHOPS.npy: Absorption spectrum for a 12-site chain calculated using DadHOPS without including state adaptivity v/s energy.<br> - Cw_12S_DadHOPS_SA.npy: Absorption spectrum for a 12-site chain calculated using DadHOPS with state adaptivity v/s energy.</p> <p>Panel_D:</p> <p> - Aux_states_DadHOPS.npy: Number of auxiliary states required to run a DadHOPS calculation for each N-pigment system.<br> - Aux_states_HOPS.npy: Number of auxiliary states required to run a dyadic HOPS calculation for each N-pigment system.<br> - N_states_DadHOPS.npy: Number of site states required to run a DadHOPS calculation for each N-pigment system.<br> - N_states_HOPS.npy: Number of site states required to run a dyadic HOPS calculation for each N-pigment system.<br> </p> <p>Figure_5:<br> <br> Panel_C: </p> <p> - PSI_Cw_HEOM.npy: PSI absorption spectrum calculated using HEOM v/s energy.<br> - PSI_Cw_HOPS.npy: PSI absorption spectrum calculated using dyadic HOPS v/s energy.</p> <p>Panel_D:</p> <p> - PSI_Error_Random.npy: Calculated mean error, where clusters of 4 were assigned randomly v/s number of trajectories.<br> - PSI_Error_Coupling.npy: Calculated mean error, where clusters of 4 were assigned based on electronic coupling values v/s number of trajectories.</p> <p><br> Figure_6:</p> <p>Panel_A:</p> <p> - PBI_Exp_data_dil.npy: Experimental data for a dilute solution of PBI v/s energy.<br> - PBI_Cw_DadHOPS_300.npy: Calculated spectrum for a PBI monomer with the spread in static disorder of value 300 cm^{-1} v/s energy.<br> - PBI_Cw_DadHOPS_400.npy:: Calculated spectrum for a PBI monomer with the spread in static disorder of value 400 cm^{-1} v/s energy.</p> <p>Panel_B:</p> <p> - PBI_Exp_data_conc.npy: Experimental data for a concentrated solution of PBI v/s energy.<br> - PBI_trimer_Cw_DadHOPS.npy: Calculated spectrum for a PBI trimer using DadHOPS v/s energy.</p> <p>Panel_C: </p> <p> - Cw_PBI_monomer.npy: Calculated spectrum for a PBI monomer using DadHOPS v/s energy.<br> - Cw_PBI_dimer.npy: Calculated spectrum for a PBI dimer using DadHOPS v/s energy.<br> - Cw_PBI_trimer.npy: Calculated spectrum for a PBI trimer using DadHOPS v/s energy.<br> - Cw_PBI_heptamer.npy: Calculated spectrum for a PBI heptamer using DadHOPS v/s energy.<br> - Cw_PBI_1000mer.npy: Calculated spectrum for a PBI 1000mer using DadHOPS v/s energy.</p> <p>Panel_D:</p> <p> - peak_00_position.npy: relative position of the 00 peak for different number of pigments.<br> - peak_00_position_1000.npy: relative position of the 0,0 peak for a system with 1000 pigments. (Single value file)<br> - peak_I_ratio.npy: ratio of intensities of peak 0,1 w.r.t peak 0,0 for different number of pigments.<br> - peak_I_ratio_1000.npy: ratio of intensities of peak 0,1 w.r.t peak 0,0 for a system with 1000 pigments. (Single value file)</p> <p><br> Figure_7:</p> <p> - PBI_N_states_DadHOPS.npy: Number of states required to run a DadHOPS calculation for each N-PBI molecules system. <br> - PBI_Aux_states_HOPS.npy: Number of auxiliary states required to run a dyadic HOPS calculation for each N-PBI molecules system. <br> - PBI_Aux_states_DadHOPS.npy: Number of auxiliary states required to run a DadHOPS calculation for each N-PBI molecules system. </p> <p>The packaged scripts may be run with Python 3.10 and the associated versions of the os, numpy, and matplotlib packages. <br> </p>
Reducing Uncertainty in Collective Perception using Self-organized Hierarchy
<p>This dataset accompanies an article submission and a <a href="https://github.com/BlueDiamond07/Collective_perception">code repository</a>.</p> <p><strong>Abstract:</strong><br> In collective perception, agents sample spatial data and use the samples to agree on some estimate. In this research, we identify the sources of statistical uncertainty that occur in collective perception and note that improving the accuracy of fully decentralized approaches, beyond a certain threshold, might be intractable. We propose self-organized hierarchy as an approach to improve accuracy in collective perception, by reducing or eliminating some of the sources of uncertainty. Using self-organized hierarchy, aspects of centralization and decentralization can be combined: robots can understand their relative positions system-wide and fuse their information at one point, without requiring, e.g., a fully connected or static communication network. In this way, multi-sensor fusion techniques that have been designed for fully centralized systems can be applied to a self-organized system for the first time, without losing the key practical benefits of decentralization. We implement simple proof-of-concept fusion in a self-organized hierarchy approach and test it against three fully decentralized benchmark approaches. We test the perceptual accuracy of the approaches for time-invariant and time-varying absolute conditions, and test the scalability and fault tolerance of their accuracies. We show that the self-organized hierarchy approach is substantially more accurate, more consistent, and faster than the other approaches, but also that it is comparably scalable and fault-tolerant.</p>
Data and code for "Competitive hierarchies in bryozoan assemblages mitigate network instability by keeping short and long feedback loops weak"
<p>This repository contains all scripts and data files to reproduce the analysis of the manuscript "Competitive hierarchies in bryozoan assemblages mitigate network instability by keeping short and long feedback loops weak"</p> <p><strong>Abstract</strong></p> <p>Competitive hierarchies in diverse ecological communities have long been thought to lead to instability and prevent coexistence. However, system stability has never been tested and the relation between hierarchy and instability has never been explained in complex competition networks parameterised with data from direct observation. Here we test model stability of 30 multispecies bryozoan assemblages, using estimates of energy loss from observed interference competition to parameterise both the inter- and intraspecific interactions in the competition networks. We find that all competition networks are unstable. However, instability is mitigated considerably by asymmetries in the energy loss rates brought about by hierarchies of strong and weak competitors. This asymmetric organisation results in asymmetries in the interaction strengths, which reduces instability by keeping the weight of short (positive) and longer (positive and negative) feedback loops low. Our results support the idea that interference competition leads to instability and exclusion but demonstrate that this is not because of, but despite, competitive hierarchy.</p> <p><strong>Data</strong></p> <p>Our data set contains records of overgrowth competition in 30 high-latitude bryozoan assemblages. Rocks were collected by hand from shallow subtidal coastal locations at Rothera Island, West Antarctic Peninsula, Signy Island in the maritime Antarctic and Spitsbergen in the Arctic. For each assemblage, the data set contains one .csv file with abundance per species and one .csv file containing the species-contact-matrix. All bryozoans were identified to species and counted, giving abundance data in colonies per species. Then, all pairwise contests between colonies were classified as win, draw or loss and the results were compiled in the species-contact-matrices. For details, see the methods section of the paper.</p> <p><strong>Analysis </strong></p> <p>The analysis is subdivided into the following sections:</p> <ul> <li>0 <strong>Random matrices</strong>: Stability of random matrices with symmetric and asymmetric interactions.</li> <li>1 <strong>Preparation</strong>: Define functions to calculate asymmetry measures and set plotting parameters</li> <li>2 <strong>Read and process raw data</strong>: Converts raw data to Jacobian matrices</li> <li>3 <strong>Analysis of empirical matrices</strong>: Calculates stability, asymmetry measures, loop weights of empirical matrices.</li> <li>4 <strong>Analysis of randomised matrices:</strong> Randomises empirical matrices and analyses the effect on stability, asymmetry measures and loop weights.</li> <li>5<strong> Sensitivity</strong>: Effect of model assumptions (cost-values / replacement of missing values) on the results.</li> </ul> <p>Details on how to reproduce the full analysis, including all figures and tables in the manuscript can be found in the ReadMe file.</p>
Fig. 1 in When nothing exists: The role of zero in the prosodic hierarchy
Fig. 1. Natrix natrix – the melanistic specimen from Plovdiv, Bulgaria.
Data from: A meta-analysis of plant interaction networks reveals competitive hierarchies as well as facilitation and intransitivity
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