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241 results for “Structural relationships”
Figs 1—6 in Sem Study Of Hooks In The Acanthocephala With Emphasis On Structural-Functional Relationships
Figs 1—6. SEM of proboscides and hooks of Heterosentis holospinus (Arythmacanthidae) (figs 1—3) and Cavisoma magnum (Cavisomidae) (figs 4–6): 1 — proboscis of H. holospinus with very long anterior hooks and spiny anterior trunk with spine-free anterior cone; 2 — high magnification of posterior spines; 3 — a Gallium-cut longitudinal section of an anterior hook showing thin cortical layer and thick solid core with high levels of calcium and phosphorous; 4 — a partially retracted proboscis of C. magnum showing the gradual reduction in hook size posteriorly; 5 — a high magnification of a middle hook showing its shallow serrated surface; 6 — a Gallium-cut cross section of a middle hook showing its moderately thick cortical layer and core with high sulfur content.
Figs 109–114 in Sem Study Of Hooks In The Acanthocephala With Emphasis On Structural-Functional Relationships
Figs 109–114. Proboscis and hooks of Leptorhynchoides polycristatus (fig. 109), Rhadinorhynchus oligospinosus (figs
Figs 55–60 in Sem Study Of Hooks In The Acanthocephala With Emphasis On Structural-Functional Relationships
Figs 55–60. SEM of proboscis and hooks of Neoechinorhynchus ponticus (figs 55, 56) and Neoechinorhynchus personatus (figs 57–60) (Neoechinorhynchidae): 55 — proboscis of N. ponticus with a sensory pore at level of posterior hooks; 56 — anterior hook showing angle of projection and external serrations; 57 — posterior hook ofN. personatus showing serrations; 58 — a high magnification showing pattern of serrations on an anterior hook; 59 — outermost layer of a hook showing detail of longitudinal serrations in cross section; 60 — a part of a Gallium-cut section of an anterior hook showing its thin cortical layer and dense core, and its articulation vs. the root of the same core density.
FIGURE 7 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 7 | The first two axes from the distance-based redundancy analysis (dbRDA) that correlate the structure of the shallow water fish assemblage and predictors (in bold; from the fitted model) sampled from May 2000 to April 2001 in the north-south axis of the Paranaguá Bay Estuarine Complex (southern Brazilian coast). ED = early dry season (April–June), LD = Late dry season (July–September), EW = early rainy season (October–December) and LW = late rainy season (January–March). Achirus lineatus = Ac.li; Bathygobius soporator = Ba.so; Chaetodipterus faber = Ch.fa; Eucinostomus argenteus = Eu.ar; Menticirrhus americanus = Me.am; M. littoralis = Me.li; Sphoeroides greeleyi = Sp.gr; S. testudineus = Sp.te; Trachinotus carolinus = Tr.ca; T. falcatus = Tr.fa; T. goodei = Tr.go; T. marginatus = Tr.ma. Only species with Pearson correlation coefficient |r| ≥ 0.3 with the axes are shown. Percentage explained by the axis (fitted) and total variation explained by the model are provided on the axes.
FIGURE 4 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 4 | Cumulative species curve calculated with fish samples sampled from May 2000 to April 2001 at eight sites along the estuarine gradient of shallow areas of the northsouth axis of the PEC. In gray, the modeled curve based on the Coleman Estimator (Coleman et al., 1982). Boxplots were generated from mean. Crosses represent outliers.
FIGURE 2 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 2 | Salintity, tranparency (Transp) and dissolved oxygen (DO) along the estuarine gradient of shallow areas of the north-south axis of the PEC from monthly sampling of May 2000 to April 2001. For a better visualisation, the values were averaged by seasons and the error bars were omitted. ED = early dry season (April–June), LD = Late Dry season (July– September), EW = early rainy season (October–December) and LW = late rainy season (January– March).
FIGURE 1 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 1 | Maps of study area, their location in the coast of Paraná (Southestern Brazil) and, in detail, the sampling points (1–8) along the north-south axis of the Paranaguá Bay Estuarine Complex. The geographical limits of the Guaraqueçaba Area of Enviromental Protection (in Portuguese acronimous – APA) and Superagui National Park are also shown. To compute the values of distance from the mouth of the estuary and the sampling point (see methods), we used the ocean-turned face of the Island Mel as the reference of the mouth of the estuary. Distance from the estuarine mouth: Site 1 = 33.97 km, Site 2 = 34.41, Site 3 = 26.27 km, Site 4 = 29.2 km, Site 5 = 24.85 km, Site 6 = 19.30 km, Site 7 = 7.5 km, Site 8 = 5.18 km.
FIGURE 6 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 6 | Abundance (n) relationship with the environmental variables that formed the most parsimonious linear model. Line represents the modeled values, and a gray area corresponds to the standard deviation. l.n = number of individuals in logscale. Temp = temperature; Sal = salinity; Time = succession of days from beginning to end of the sampling surveys; D = distance from the mouth of the estuary (see Material and Methods section for details).
FIGURE 3 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 3 | Monthly variation in the mean historical rainfall data (monthly average between 1975 and 2015) and mean water temperature sampled from May 2000 to April 2001 at eight sites along the estuarine gradient of shallow areas of the northsouth axis of the PEC. For temperature, the values were averaged by month and bars represent standard deviation. Months were ordered according to the sequence of the sampling surveys.
FIGURE 5 in Relationship between fish assemblage structure and predictors related to estuarine productivity in shallow habitats of a Neotropical estuary
FIGURE 5 | Richness (S) relationship with the environmental variables that formed the most parsimonious GLM. Line represents the modeled values, and a gray area corresponds to the standard deviation. Temp = temperature; Transp = transparency; Sal = salinity; Time = succession of days from beginning to end of the sampling surveys (see Material and Methods section for details).
Fig. 1 in Relationship Between Grazing Intensity, Vegetation Structure And Survival Of Nests In Semi-Natural Grasslands
Fig. 1. Daily nest survival rate (±SE) for artificial ground nests according to edge vs. interior and grazing intensity in three grassland regions of Hungary
Fig. 2 in Relationship Between Grazing Intensity, Vegetation Structure And Survival Of Nests In Semi-Natural Grasslands
Fig. 2. Grass height and vegetation cover (mean±SE) around predated and not predated (intact) artificial ground nests in Hungarian grasslands. (**: P <0.01; ***: P <0.001)
BRAIN Journal-Redesigning a Flexible Material Master Data Application with Language Dependency-Figure 4. Table structure and relationships
<p>The structure of the tables, primary keys and foreign keys are shown in figure 4.The names of the fields in the database tables are relevant for their content. Only the SPRAS field in the translation-tables TABT and ARET must be explained: SPRAS is a system-field which stands for the language and is used in order to maintain the languages in which the tab/area is translated into.</p>
Figure 2 in Diet composition, guild structure and trophic relationships of wintering birds of prey in an estuarine wetland (The Evros Delta National Park, Greece)
Figure 2. Cluster analysis (dendrogram) based on the biomass proportions of the diets of the seven species of birds of prey studied in Evros Delta.
Figure 1 in Diet composition, guild structure and trophic relationships of wintering birds of prey in an estuarine wetland (The Evros Delta National Park, Greece)
Figure 1. Diet compiled for the most important prey taxa of the seven species of birds of prey studied in the Evros Delta, a) by biomass (upper graph) and b) by numbers (lower graph) (Shannon index/Evenness are shown below each species name).
The chloroplast genomes of Sanicula (Apiaceae): plastome structure, comparative analyses, and phylogenetic relationships
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Chemical-genetic interrogation of RNA polymerase mutants reveals structure-function relationships and physiological tradeoffs
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Data from: Characterizing morphological (co)variation using structural equation models: body size, allometric relationships and evolvability in a house sparrow metapopulation
Body size plays a key role in the ecology and evolution of all organisms. Therefore, quantifying the sources of morphological (co)variation, dependent and independent of body size, is of key importance when trying to understand and predict responses to selection. We combine structural equation modeling with quantitative genetics analyses to study morphological (co)variation in a meta-population of house sparrows (Passer domesticus). As expected, we found evidence of a latent variable 'body size', causing genetic and environmental covariation between morphological traits. Estimates of conditional evolvability show that allometric relationships constrain the independent evolution of house sparrow morphology. We also found spatial differences in general body size and its allometric relationships. On islands where birds are more dispersive and mobile, individuals were smaller and had proportionally longer wings for their body size. While in islands where sparrows are more sedentary and nest in dense colonies, individuals were larger and had proportionally longer tarsi for their body size. We corroborated these results using simulations and show that our analyses produce unbiased allometric slope estimates. This study highlights that in the short term allometric relationships may constrain phenotypic evolution, but that in the long term selection pressures can also shape allometric relationships.
Sequence-structure-function relationships in class I MHC: a local frustration perspective
<p>Class I Major Histocompatibility Complex (MHC) binds short antigenic peptides with the help of Peptide Loading Complex (PLC), and presents them to T-cell Receptors (TCRs) of cytotoxic T-cells and Killer-cell Immunglobulin-like Receptors (KIRs) of Natural Killer (NK) cells. With more than 10000 alleles, the Human Leukocyte Antigen (HLA) chain of MHC is the most polymorphic protein in humans. This allelic diversity provides a wide coverage of peptide sequence space, yet does not affect the three-dimensional structure of the complex. Moreover, TCRs mostly interact with pMHC in a common diagonal binding mode, and KIR-pMHC interaction is allele-dependent. With the aim of establishing a framework for understanding the relationships between polymorphism (sequence), structure (conserved fold) and function (protein interactions) of the MHC, we performed here a local frustration analysis on pMHC homology models covering 1436 HLA I alleles. An analysis of local frustration profiles indicated that (1) variations in MHC fold are unlikely due to minimally-frustrated and relatively conserved residues within the HLA peptide-binding groove, (2) high frustration patches on HLA helices are either involved in or near interaction sites of MHC with the TCR, KIR, or Tapasin of the PLC, and (3) peptide ligands mainly stabilize the F-pocket of HLA binding groove.</p>
Figs 61–66 in Sem Study Of Hooks In The Acanthocephala With Emphasis On Structural-Functional Relationships
Figs 61–66. SEM of proboscis and hooks
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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
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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.
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