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Fig. 8 in Comparative cytogenetics in Astyanax (Characiformes: Characidae) with focus on the cytotaxonomy of the group
Fig. 8. Dendogram showing the karyotypic similarity obtained by cluster analysis and Euclydean distance coefficient among the six species of Astyanax studied.
Fig. 4. CMA3 in Comparative cytogenetics in Astyanax (Characiformes: Characidae) with focus on the cytotaxonomy of the group
Fig. 4. CMA3 stained karyotypes of Astyanax argyrimarginatus (a), A. aff. bimaculatus (b), A. elachylepis (c), A. xavante (d), Astyanax sp. (e), and A. altiparanae (f). Chromosomes carrying AgNORs and 18S sites are underlined in karyotypes. Bar = 5 µm.
Fig. 7 in Comparative cytogenetics in Astyanax (Characiformes: Characidae) with focus on the cytotaxonomy of the group
Fig. 7. Idiogram for the six studied Astyanax species with data obtained with different methodologies.
Fig. 2 in Comparative cytogenetics in Astyanax (Characiformes: Characidae) with focus on the cytotaxonomy of the group
Fig. 2. Karyotypes of Astyanax argyrimarginatus (a), A. aff. bimaculatus (b), A. elachylepis (c), A. xavante (d), Astyanax sp. (e), and A. altiparanae (f), after conventional staining with Giemsa. Chromosomes carrying AgNORs and 18S sites (underlined in karyotypes) are highlighted in the box. Bar = 5 µm.
Fig. 6 in Comparative cytogenetics in Astyanax (Characiformes: Characidae) with focus on the cytotaxonomy of the group
Fig. 6. Karyotypes of Astyanax argyrimarginatus (a), A. aff. bimaculatus (b), A. elachylepis (c), A. xavante (d), Astyanax sp. (e), and A. altiparanae (f) after FISH with 5S-DNA probes. Bar = 5 µm.
Fig. 1 in Comparative Analysis Of Alien Red Oak (Quearcus Rubra L.) And Native Common Oak (Quercus Robur L.) Vegetation In Lithuania
Fig. 1. Detrented Correspondence Analysis of Quercus rubra () and Quercus robur of TilioCarpinetum stachyetosum () and Tilio-Carpinetum typicum types () plots
Fig. 4 in A comparative analysis of freshwater testate amoebae species composition between the south-eastern part of Azerbaijan and other regions of Azerbaijan
Fig. 4. Electron microphotos of new species and subspecies of testate amoebae for the fauna of Caucasus: 1 — Difflugia petricola Cash, 1909; 2 — D. microclaviformis Ogden, 1983; 3 — D. biconcava Ertl, 1964; 4 — D.corona ssp. tuberculata Vucetich, 1973; 5 — Arcella discoides ssp. scutelliformis Playfair, 1918 Рис. 4. ЭΛектронные микрофотографии новых ΑΛя фауны Кавказа виΑов и поΑвиΑов раковинных амеб: 1 — Difflugia petricola Cash, 1909; 2 — D. microclaviformis Ogden, 1983; 3 — D. biconcava Ertl, 1964; 4 — D. corona ssp. tuberculata Vucetich, 1973; 5 — Arcella discoides ssp. scutelliformis Playfair, 1918
Fig. 3 in A comparative analysis of freshwater testate amoebae species composition between the south-eastern part of Azerbaijan and other regions of Azerbaijan
Fig. 3. Cluster analysis of the faunistic similarity of testate amoebae in different parts of South-Eastern Azerbaijan Рис. 3. КΛастерный анаΛиз фаунистического схоΑства раковинных амеб в разных реги- онах юго-восточного АзербайΑжана
Fig. 2 in A comparative analysis of freshwater testate amoebae species composition between the south-eastern part of Azerbaijan and other regions of Azerbaijan
Fig. 2. Cluster analysis of faunistic similarity of testate amoebae of different regions of Azerbaijan (the results of Bray-Curtis analysis) Рис. 2. КΛастерный анаΛиз фаунистического схоΑства раковинных амеб разных регионов АзербайΑжана (резуΛьтаты анаΛиза Брея — Кертиса)
Fig. 1 in A comparative analysis of freshwater testate amoebae species composition between the south-eastern part of Azerbaijan and other regions of Azerbaijan
Fig. 1. Location of sampling points: 1 — south-eastern part of Azerbaijan (Lankaran natural area); 2 — Absheron peninsula; 3 — north-eastern part of Azerbaijan (Khachmaz district); 4 — western part of Azerbaijan (Goygol); 5 — Nakhichevan Autonomous Republic
FIGURE 4. P and S in BoneProfileR: The next step to quantify, model, and statistically compare bone section compactness profiles
FIGURE 4. P and S values ffor radial compactness analysis of (A, B) Erinaceus europaeus and (C, D) Eryops megacephalus femur using the flexit model.
FIGURE 3 in BoneProfileR: The next step to quantify, model, and statistically compare bone section compactness profiles
FIGURE 3. Posterior distribution of K1 and K2 parameters of the flexit model applied on Erinaceus europaeus femur (A, B) and on Eryops megacephalus femur (C, D). A -1000 to +1000 uniform prior distribution was used. K1 = K2 = 1 shown in interrupted line is the logistic equation.
FIGURE 2 in BoneProfileR: The next step to quantify, model, and statistically compare bone section compactness profiles
FIGURE 2. Comparison of logistic and flexit fits (A, B) of the Erinaceus europaeus femur shown in Figure 1A and (C, D) of the Eryops megacephalus femur shown in Figure 1B. Table 1 shows the AIC and Akaike weight values for these models.
FIGURE 1 in BoneProfileR: The next step to quantify, model, and statistically compare bone section compactness profiles
FIGURE 1. Example of background and foreground automatic detection in (A) Erinaceus europaeus femur, and (B) Eryops megacephalus femur. Centers were automatically detected in (A) and manually positioned in (B). Here, sections are segmented in 100 concentric circles and 60 slices for measures of global and radial compactness. Details on bone section preparation can be found in Laurin et al. (2004) and Quémeneur et al. (2013).
Fig. 3 in The correlations between certain features of the journal Neotropical Ichthyology and its impact factor: a comparative analysis at the thematic and national levels
Fig. 3. Correlation between average IF and uncitedness rate of journals on zoology in Sample 1 between 2006 and 2010. The highlighted represents the data for Neotropical Ichthyology.
Comparing first street foundation and PRIMo flood hazard data across the Los Angeles metropolitan region
<p>Extreme flooding events are becoming more frequent and costly, and impacts have been concentrated in cities where exposure and vulnerability are both heightened. To manage risks, governments, the private sector, and households now rely on flood hazard data from national-scale models that lack accuracy in urban areas due to unresolved drainage processes and infrastructure. The data in this repository supports an assessment of the uncertainties of First Street Foundation (FSF) flood hazard data, available across the U.S.. For the analysis, FSF data was compared to PRIMo-Drain, a flood hazard model that resolves drainage infrastructure and fine resolution drainage dynamics.</p> <p>In the linked journal manuscript, using the case of Los Angeles, California, we find that FSF and PRIMo-Drain estimates of population and property value exposed to 1%- and 5%-annual-chance hazards diverge at finer scales of governance, for example by 4- to 18-fold at the municipal scale. FSF and PRIMo-Drain data often predict opposite patterns of exposure inequality across social groups (e.g., Black, White, Disadvantaged). Further, at the county scale, we compute a Model Agreement Index of only 24%—a ~1 in 4 chance of models agreeing upon which properties are at risk. Collectively, these differences point to limited capacity of FSF data to confidently assess which municipalities, social groups, and individual properties are at risk of flooding within urban areas. These results caution that national-scale model data at present may misinform urban flood risk strategies and lead to maladaptation, underscoring the importance of refined and validated urban models.</p>
Data to How to best detect threatened deadwood fungi – comparing metabarcoding and fruit body surveys
<p>This data set contains occurence data of threatened (red listed) fungi on deadwood objects in the National Park Bavarian Forest and the Žofínský prales National Nature Reserve to the the publication "How to best detect threatened deadwood fungi – comparing metabarcoding and fruit body surveys" by Rieker et al. (2024). This data is mainly uploaded to recreate analyses. </p> <p>Site: Information on the sampling site</p> <p>ObjectID: ID of the sampled deadwood object</p> <p>Campaign: Sampling year</p> <p>Decaystage: Decaystage of the deadwood object at sampling time (ranging between 1 and 4)</p> <p>Kingdom: Kingdom the eadwood object tree species belongs to</p> <p>Method: sampling method</p> <p>Species: threatend species name </p> <p>Presence: only contains the value "1" for present</p>
Рис. 1. Номенклатура и условные обоЗначениЯ морфоструктур Замочной плоЩадки личиночных венерид (A, B; по Rees, 1950, с иЗменениЯми), ювенильных Turtonia minuta (С) и вЗрослых венерид Tapetinae (D): a, a0 – передний Зуб правой створки (RV); b, b0 – Задний Зуб RV; c, c0 – передний Зуб левой створки (LV); d, d0 – Задний Зуб LV; lc – лигаментнаЯ Ямка центрального расположениЯ; lp – лигаментнаЯ Ямка Заднего расположениЯ; L1 – передне-вентральный латеральный Зуб RV; L2 – передний латеральный Зуб LV; L3 – передне-дорсальный латеральный Зуб RV; n – нимфа вторичного лигамента;:a – Ямка Зуба переднего Зуба RV;:c – Ямка переднего Зуба LV; 1 – вентральный кардинальный Зуб RV; 2a – переднЯЯ часть кардинального Зуба 2 LV; 2b – ЗаднЯЯ часть кардинального Зуба 2 LV; 3а – переднЯЯ часть кардинального Зуба 3 RV; 3b – ЗаднЯЯ часть кардинального Зуба 3 RV; 4 – Задний кардинальный Зуб LV;:4 – Ямка Заднего кардинального Зуба LV. in Larval, juvenile and adult Turtonia minuta (Bivalvia: Turtoniidae) and comparative shell morphology of the veneroid and venerid taxa from Peter the Great Bay, Sea of Japan
Рис. 1. Номенклатура и условные обоЗначениЯ морфоструктур Замочной плоЩадки личиночных венерид (A, B; по Rees, 1950, с иЗменениЯми), ювенильных Turtonia minuta (С) и вЗрослых венерид Tapetinae (D): a, a0 – передний Зуб правой створки (RV); b, b0 – Задний Зуб RV; c, c0 – передний Зуб левой створки (LV); d, d0 – Задний Зуб LV; lc – лигаментнаЯ Ямка центрального расположениЯ; lp – лигаментнаЯ Ямка Заднего расположениЯ; L1 – передне-вентральный латеральный Зуб RV; L2 – передний латеральный Зуб LV; L3 – передне-дорсальный латеральный Зуб RV; n – нимфа вторичного лигамента;:a – Ямка Зуба переднего Зуба RV;:c – Ямка переднего Зуба LV; 1 – вентральный кардинальный Зуб RV; 2a – переднЯЯ часть кардинального Зуба 2 LV; 2b – ЗаднЯЯ часть кардинального Зуба 2 LV; 3а – переднЯЯ часть кардинального Зуба 3 RV; 3b – ЗаднЯЯ часть кардинального Зуба 3 RV; 4 – Задний кардинальный Зуб LV;:4 – Ямка Заднего кардинального Зуба LV.
FIGURE 3 in Comparative analysis of the reproductive activity of Leporinus piau (Characiformes: Anostomidae) in lentic and lotic environments
FIGURE 3 | Bimonthly distribution of stages of gonadal maturation of female and male Leporinus piau in sections 1 and 2 of the São Francisco River (SFR) basin from May 2015 to April 2016.
FIGURE 2 in Comparative analysis of the reproductive activity of Leporinus piau (Characiformes: Anostomidae) in lentic and lotic environments
FIGURE 2 | Histological sections of testes of Leporinus piau in different stages of gonadal maturation stained by HE. (A) At rest (M1), containing only spermatogonia (SPG) and lumen of closed seminiferous tubules. (B) Initiation of maturation with a small number of spermatozoa (SPZ) in the lumen of the seminiferous tubules. (C) Maturation/mature (M2), with seminiferous tubules filled with spermatozoa (SPZ). (D) Spent (M3), with the lumen of the seminiferous tubules open and an appreciable amount of spermatozoa. Bars: A and D = 40µm; B and C = 200µm.
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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
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.