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81 results for “morphological measurements”
Thalassia leaf morphology and productivity measurements from arbitrary plots located in a Thalassia seagrass meadow in Rabbit Key Basin, Florida Bay (FCE) from March 2000 to April 2001
Thalassia leaf morphology and productivity were measured from six arbitrary 200 cm2 plots within a Thalassia seagrass meadow in Rabbit Key Basin, Florida Bay.
Supplementary Materials for 'Measuring and assessing indeterminacy and variation in the morphology-syntax distinction'
<p><strong>Supplementary materials for the article 'Measuring and assessing indeterminacy and variation in the morphology-syntax distinction' in <em>Linguistic Typology </em>(Vol. and No. TBD).</strong></p> <p>Abstract:</p> <p>We provide a discussion of some of the challenges in using statistical methods to investigate the morphology-syntax distinction cross-linguistically. The paper is structured around three problems related to the morphology-syntax distinction; (i) the boundary strength problem; (ii) the composition problem; (iii) the architectural problem.<br> The boundary strength problem refers to the possibility that languages vary in terms of how distinct morphology and syntax are or the degree to which morphology is autonomous. The composition problem refers to the possibility that languages vary in terms of how they distinguish morphology and syntax: what types of properties distinguish the two systems. The architecture problem refers to the possibility that languages vary in terms of whether a global distinction between morphology and syntax is motivated at all and the possibility that languages might partition phenomena in different ways.<br> This paper is concerned with providing an overarching review of the methodological problems involved in addressing these three issues. We illustrate the problems using three statistical methods: correlation matrices, random forests with different choices for the dependent variable, and hierarchical clustering with validation techniques.</p> <p> </p> <p>Overview of materials:</p> <ul> <li>SM1: csv with the data</li> <li>SM2: code and pdf for generating the correlation matrices</li> <li>SM3: code and pdf for the random forest analyses</li> <li>SM4: code and pdf for the clustering and cluster validation analyses</li> </ul>
Galaxy Zoo DECaLS: Detailed Visual Morphology Measurements from Volunteers and Deep Learning for 314,000 Galaxies
<p>This repository contains the data released in the paper "Galaxy Zoo DECaLS: Detailed Visual Morphology Measurements from Volunteers and Deep Learning for 314,000 Galaxies" <em>(DOI to follow on publication).</em></p> <p>We release detailed morphology catalogues, both volunteer and automated, for Galaxy Zoo DECaLS.</p> <p>- gz_decals_volunteers_1_and_2 contains volunteer classifications for galaxies classified during the GZD-1 and GZD-2 campaigns.</p> <p>- gz_decals_volunteers_5 similarly contains classifications from the GZD-5 campaign. Note that GZD-5 used a modified schema designed to better detect mergers and weak bars, and includes many galaxies with only approx. five volunteer responses.</p> <p>- gz_decals_auto_posteriors contains the predicted posteriors for volunteer responses to all galaxies used in any campaign. The full posteriors are recorded as Dirichlet distribution concentrations. gz_decals_auto_posteriors also summarises these posteriors as the automated equivalent of previous Galaxy Zoo data releases;<strong> the expected vote fractions (mean posteriors)</strong>. Note that not all posteriors/vote fractions are relevant for every galaxy; we suggest assessing relevance using the estimated fraction of volunteers that would have been asked each question.</p> <p>We include a schema document, schema.md, to define the column names in each catalogue.</p> <p>We also release the galaxy images shown to volunteers on www.galaxyzoo.org during GZD-5. The images on which the automated classifier was trained may be derived from these volunteer-facing images. These images are split into four zip files, each of which contains images named by iauname inside a subfolder named by the first four characters in their iauname. Not all images were labelled during GZD-5 - refer to the catalog for training labels. We are working with the Zenodo team to add these large files to this repository - meanwhile, you can download them from The University of Manchester <a href="https://docs.google.com/document/d/1YgpnxiSJ7ffOW6FY8pX0pw93LTu8rLIdPL2PYhxW1fo/edit?usp=sharing">here</a>.</p> <p>The .csv and .parquet files contain identical data. Parquet is a fast column-oriented binary format which can be read with pd.read_parquet(loc, columns=[some columns]).</p> <p>You may also be interested in the <a href="https://github.com/mwalmsley/zoobot">github repository</a> which contains code to reproduce the model and to fine-tune it for new tasks (including pretrained weights).</p> <p>We will release updates if needed via Zenodo versioning. We recommend using the latest version of this repository. You can check the version you are currently viewing on the right-hand sidebar.</p> <p>Please cite the paper (DOI to follow on publication) when using the data in this repository.</p> <p>---</p> <p>History</p> <p>v0.0.1 (submission) provides the catalog files.</p> <p>v0.0.2 (first revision) renames the catalog files, adds flags for poorly sized galaxies, and includes the galaxy images via the University of Manchester</p>
Dataset Single-subject EEG measurement of interhemispheric transfer-time for the in-vivo estimation of axonal morphology
<p>This dataset is a subset of the data presented in the article Single‐subject electroencephalography measurement of interhemispheric transfer time for the in‐vivo estimation of axonal morphology Rita Oliveira, Marzia De Lucia, Antoine Lutti</p> <p><a href="https://onlinelibrary.wiley.com/doi/full/10.1002/hbm.26420">https://onlinelibrary.wiley.com/doi/full/10.1002/hbm.26420</a></p> <p><br> For a complete description of our approach for axonal morphology estimation in-vivo, see: <em>Oliveira, R., Pelentritou, A., Di Domenicantonio, G., De Lucia, M., and Lutti, A. (2022). In vivo Estimation of Axonal Morphology From Magnetic Resonance Imaging and Electroencephalography Data. Front. Neurosci. 16, 1–18. doi: 10.3389/fnins.2022.874023.</em></p> <p>This dataset contains the following Matlab files:</p> <ul> <li>CD_CondNameVisualField_LeftBrainOccipital.mat - Current source densities (pA.m) of each brain vertice, EEG trial, and time point for the left brain occipital cortex [#trials x #vertices x #timepoints]</li> <li>CD_CondNameVisualField_RightBrainOccipital.mat - Current source densities (pA.m) of each brain vertice, EEG trial, and time point for the right brain occipital cortex [#trials x #vertices x #timepoints]</li> <li>Stats_Source_CondNameVF_Occipital_LeftBrainOccipital.mat - Result of the cluster permutation for the left brain cortex for the CondNameVF, CondName being Left or Right visual stimulation (Fieldtrip stat structure)</li> <li>Stats_Source_CondNameVF_Occipital_RightBrainOccipital.mat - Result of the cluster permutation for the right brain cortex for the CondNameVF, CondName being Left or - Right visual stimulation (Fieldtrip stat structure)</li> <li>time_vec.mat - Time vector associated with the timecourses [1 x #timepoints]</li> <li>Occipital_vertices.mat - Structure containing the vertices of the brain mesh of the region of interest. Occipital_vertices.Vertices [1 x #vertices]</li> <li>G_ratio_samples.mat - MRI g-ratio sampled along the occipital transcallosal tract [#samples x 1]</li> <li>Tract_length.mat - Length of the occipital transcallosal tract (double)</li> </ul> <p>The analysis scripts that allow the users to replicate the results of the original publication can be found here: <a href="https://github.com/DNC-EEG-platform/SingleSubjectIHTTEstimation">https://github.com/DNC-EEG-platform/SingleSubjectIHTTEstimation</a><br> <br> Funding: Swiss National Science Foundation (grant no 320030 184784 and 32003B 212981), ROGER DE SPOELBERCH Foundation and Bertarelli Catalyst Foundation.</p> <p> </p> <p>Author: Rita Oliveira<br> PIs: Marzia De Lucia, Antoine Lutti</p> <p>Laboratory for Neuroimaging Research</p> <p>Lausanne University Hospital & University of Lausanne, Lausanne, Switzerland</p> <p>Copyright (C) 2022 Laboratory for Neuroimaging Research</p> <p> </p>
Appendix Morphometric parameters of Chaetonotus (Chaetonotus) antrumus Kolicka sp. nov. Abbreviations: N = number of specimens or structures analysed; Range = the smallest and the largest structure measurement found among all specimens measured; SD = standard deviation. All measurements are given in micrometers (μm); all indicators are given as a percentage (%) and italicized. in A new species of freshwater Chaetonotidae (Gastrotricha, Chaetonotida) from Obodska Cave (Montenegro) based on morphological and molecular characters
Appendix Morphometric parameters of Chaetonotus (Chaetonotus) antrumus Kolicka sp. nov. Abbreviations: N = number of specimens or structures analysed; Range = the smallest and the largest structure measurement found among all specimens measured; SD = standard deviation. All measurements are given in micrometers (μm); all indicators are given as a percentage (%) and italicized.
FIGURE 1. Linear measurements used for morphological comparison. B-L in Fossil moles from the Gray Fossil Site (Tennessee): Implications for diversification and evolution of North American Talpidae
FIGURE 1. Linear measurements used for morphological comparison. B-L - buccolingual width; upper teeth - posterior-most tip of the metastyle to the lingual margin of the protocone; lower teeth - lingual-most tip of the metaconid to the buccal margin of the talonid. A-P - anteroposterior length; upper teeth - posterior-most tip of the metastyle to the anterior-most tip of the parastyle; lower teeth - anterior tip of the trigonid (paraconid) to the posterior end of the talonid (entostylid). TRI - width of the trigonid. TAL - width of the taloned basin. HL - total humerus length; proximal-most tip of greater tuberosity to distal-most point on capitulum. PW - width of the proximal end of the humerus: lateral most extent of the lesser tuberosity to the medial most aspect of the greater tuberosity. GT - length of the greater tuberosity. LT - length of the lesser tuberosity. DW - width of the distal end of the humerus: lateral most extent (entepicondylar process) to the medial most extent (ectepicondylar process). RL - total radius length: proximal-most tip of capitular process to distal-most tip of lunar articular facet. DL - length of the diaphysis. UF - length of the lunar articular facet. TUL - total ulna length; proximal-most tip of olecranon process to distal-most tip of terminal process. UL - ulna length without the olecranon fossa. Elements not to scale.
Fig. 6. Female genital morphology. See Table 1 for localities and Table 3 for measurements. A in Cochlostoma revised: the subgenus Lovcenia Zallot et al., 2015 (Caenogastropoda, Cochlostomatidae)
Fig. 6. Female genital morphology. See Table 1 for localities and Table 3 for measurements. A. Cochlostoma (Lovcenia) erika (A.J. Wagner, 1906) (HNHM 86387). B. Cochlostoma (Lovcenia) dalmatinum (L. Pfeiffer, 1863) (NHMW 110430/MN/0162). C. Cochlostoma (Lovcenia) tropojanum sp. nov. (NHMW 111248). D1. Cochlostoma (Lovcenia) jakschae sp. nov., Bugarska Peak population (NHMW 111249). D2. Cochlostoma (Lovcenia) jakschae sp. nov., Pejë Pass population (HNHM 97221). E. Cochlostoma (Lovcenia) lanatum sp. nov. (HNHM 99861).
Fig. 9. Nine eggs from a female measuring 533 in Notes on the natural history and morphology of the Ningshan Lined Snake (Stichophanes ningshaanensis Yuen, 1983; Ophidia: Colubridae) and its distribution in the Shennongjia National Nature Reserve, China
Fig. 9. Nine eggs from a female measuring 533 mm SVL and 673 mm TL on 30 June 2006. Photo by Kevin R. Messenger.
Stickleback sensory morphology 2015 & 2017 measurements and analysis files
<p>The peripheral sensory systems, whose morphological attributes help determine the acquisition of distinct types of information, provide a means to quantitatively compare multiple modalities of a species' sensory ecology. We used morphological metrics to characterize multiple sensory modalities—the visual, olfactory, and mechanosensory lateral line sensory systems—for <em>Gasterosteus aculeatus</em>, the three‐spined stickleback, to compare how sensory systems vary in animals that evolve in different ecological conditions. We hypothesized that the dimensions of sensory organs and correlations among sensory systems vary in populations adapted to marine and freshwater environments, and have diverged further among freshwater lake-dwelling populations. Our results showed that among environments, fish differed in which senses are relatively elaborated or reduced. When controlling for body length, littoral fish had larger eyes, more neuromasts, and smaller olfactory tissue area than pelagic or marine populations. We also found differences in the direction and magnitude of correlations among sensory systems for populations even within the same habitat type. Our data suggest that populations take different trajectories in how visual, olfactory, and lateral line systems respond to their environment. For the populations we studied, sensory modalities do not conform in a predictable way to the ecological categories we assigned.</p>
Morphological measurements of coccoliths from surface samples of South China Sea
<p>The dataset compiles morphological measurements of coccoliths (<em>Gephyrocapsa</em> spp. and <em>Emiliania huxleyi</em>, >2µm) from surface samples of the South China Sea retrieved at different depths of the basin during the R/V Sonne cruises (SO-95); and of Gephyrocapsa spp. from one sample from the Western Equatorial Pacific (ODP 807A, -2H-2W, 57-59 cm) used in a dissolution experiment. The columns include station names, Longitude, Latitude, Depth (m), how much Calgon was added into sediment suspension (in the dissolution experiment), number of coccoliths measured per sample, mean ks shape factor, thickness, length, volume, mass, and standard deviation of mean ks/mean ks.</p>
Fig. 1. Morphological terms and measurement characters for wings. a in A review of the genus Enicospilus Stephens (Ichneumonidae: Ophioninae) from Vietnam, with descriptions of ten new species
Fig. 1. Morphological terms and measurement characters for wings. a. Fore wing (BC = basal cell; DS = discosubmarginal cell; FS = first subdiscal cell; MC = marginal cell; SD = second discal cell). b. Hind wing. c. Central part of fore wing (AI = cd / ab; CI = gf / fh; DI = k / fe; ICI = ab / cb; SDI = fe / ig; SI = l / j; SRI = ce / fe).
Stickleback sensory morphology 2015 & 2017 measurements and analysis files
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Measurement data for septal spacing and conch morphology in Cretaceous ammonoids
<p>We analyzed the ontogenetic trajectories of conch morphology and septal spacing between successive chambers in Cretaceous ammonoids (suborders Perisphinctina and Ancyloceratina) collected from southern India, Madagascar, and Japan. All examined species, except for the family Collignoniceratidae, exhibited similar characteristics during early ontogeny. The common ontogenetic trajectories of septal spacing show a cycle comprising an increase and a subsequent decrease in septal spacing during early ontogeny. The conch diameters at the end of the cycle were estimated to be 1–4 mm. The conch shape (aperture height and whorl expansion rate) covariably changed at this conch diameter. Such covariable changes are commonly recognized in the suborders Perisphinctina and Ancyloceratina. The similarity in the ontogenetic trajectories of conch morphology implies a closer phylogenetic relationship between these suborders compared to Lytoceratina or Phylloceratina.</p>
Morphological measurements Oryzias eversi, Oryzias nigrimas and hybrids
<p><span><span><span><span><span><span><span><span><span><span><span>The evolution of complex phenotypes like reproductive strategies is challenging to understand as they often depend on multiple adaptations, which only jointly result in a specific functionality. Sulawesi ricefishes (Adrianichthyidae) evolved a reproductive strategy termed pelvic brooding. In contrast to the more common transfer brooding, female pelvic brooders carry an egg-bundle connected to their body for weeks until the fry hatches. To examine the genetic architecture of pelvic brooding, we crossed the pelvic brooding <i>Oryzias eversi</i> and the transfer brooding <i>O. nigrimas</i> (species divergence time: ~ 3.6 my). We hypothesize, that a low number of loci and modularity have facilitated the rapid evolution of pelvic brooding. Traits associated to pelvic brooding, like rib length, pelvic fin length and morphology of the genital papilla were correlated in the parental species but correlations were reduced or lost in their F1 and F2 hybrids. Using the Castle-Wright estimator, we found that generally few loci underlie the studied traits. Further, both parental species showed modularity in their body plans. In conclusion, morphological traits related to pelvic brooding were based on a few loci and the mid-body region likely could evolve independently from the remaining body parts. Both factors presumably facilitated the rapid evolution of pelvic brooding.</span></span></span></span></span></span></span></span></span></span></span></p>
Measurement of male and female morphologies in Mercurialis annua
<p>We provide a dataset documenting the changes in male and female morphological traits after evolution at low- and high-density during three generations in the dioecious plant species <em>Mercurialis annua</em>. Our dataset corresponds to results from an experimental evolution protocol in which we have measured male and female traits after the evolution of ten experimental independent populations at the two contrasting densities. Seeds were initially collected in various populations of the species range and grown for three generations in a common garden, which aim was to build a seed bank with large genetic variance for experimental evolution. The seeds resulting from this initial generation (G0) have than been grown to build ten experimental populations (POP in the dataset) that were affected either to low or high density (TREAT in the dataset). Each population was grown separately from the other populations and its assigned density was applied during the last four weeks of growth. After three generations of evolution at their assigned density, seeds resulting from the third generation of evolution were grown in a common garden with two spatial blocks (BLOCK in the dataset) in which we recorded the spatial position of each plants (x and y in the dataset) measured vegetative and reproductive traits in male and female plants.</p>
Morphological measurements of two host specialists of the dipteran Tephritis conura, both in sympatry and allopatry
<div> <div> <div> <div> <p>Adaptation to new ecological niches is known to spur population diversification and may lead to speciation if gene flow is ceased. While adaptation to the same ecological niche is expected to be parallel, it is more difficult to predict whether selection against maladaptive hybridization in secondary sympatry results in parallel divergence also in traits that are not directly related to the ecological niches. Such parallelisms in response to selection for reproductive isolation can be identified through estimating parallelism in reproductive character displacement across different zones of secondary contact. Here, we use a host shift in the phytophagous peacock fly Tephritis conura, with both host races represented in two geographically separate areas East and West of the Baltic Sea to investigate convergence in morphological adaptations. We asked i) if there are consistent morphological adaptations to a host plant shift and ii) if the response to secondary sympatry with the alternate host race is parallel across contact zones. We found surprisingly low and variable, albeit significant, divergence between host races. Only one trait, the length of the female ovipositor, which serves an important function in the interaction with the hosts, was consistently different between host races. Instead, co-existence with the other host race significantly affected the degree of morphological divergence, but the divergence was largely driven by different traits in different contact zones. Thus, local stochastic fixation or reinforcement could generate trait divergence, and additional evidence is needed to conclude whether divergence is locally adaptive.</p> </div> </div> </div> </div>
Derived brain morphology measures from CamCAN data
<p>Derived brain morphology measures from CamCAN data.</p>
Phenotype images of Gryllus personatus and five resulting morphological measurements
<p class="MsoNormal">Sexual size dimorphism (SSD) and sexual shape dimorphism (SShD) are of interest to evolutionary ecology, but the two phenomena can very easily be conflated by not taking a multivariate approach to measuring size. In our study we draw attention to this problem by measuring four body size dimensions (maxillae span, head width, pronotum length and mean hind femur length) in lab-reared individuals of the badlands cricket (Orthoptera, Gryllinae, <em>Gryllus personatus</em>) and conducting a variety of multivariate analyses to test whether there is SSD and/or SShD.</p> <p class="MsoNormal">We found that males had wider heads and maxillae than females, and females had longer pronota and hind femora than males. This difference in the direction of sexual dimorphism indicates SShD. However, multivariate methods failed to detect SSD, instead confirming that the sexes primarily differ in body shape. We suggest that orthopterists studying sexual dimorphism minimally measure head width, pronotum length and hind femur length as a standard that will allow a more repeatable and generalizable assessment of the prevalence and direction of both SSD and SShD.</p>
Physiological and morphological growth and hydraulic measures in Asclepias syriaca and A. speciosa under drought
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Morphological measurements Oryzias eversi, Oryzias nigrimas and hybrids
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Allen Brain Atlas
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International Brain Laboratory public data
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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.