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Figure 11 in First results of a faunistic survey on the Orthoptera of Jadovnik Mountain, southwestern Serbia, with data on the calling songs of some bush cricket species
Figure 11. SEM photographs of the stridulatory files: (A) Poecilimon pseudornatus, Sopotnica Ra; (B) Poecilimon pseudornatus, Ogoreljača–Mali Jadovnik (roadside).
Figures 5–6. 5 in New results of testing the attractant EFETOV-2 in the Far East of Russia, Siberia and South Africa
Figures 5–6. 5. Russia, Zabaykalskiy Kray, Chita Region, Mogocha District, 34 km NE of Amazar vill. Habitat of Rh. pruni pruni. 6. South Africa, KwaZulu-Natal Province, Giant's Castle Camp. Habitat of P. ochroptera. (All photos by S.A. Knyazev).
Figures 1–2. 1 in New results of testing the attractant EFETOV-2 in the Far East of Russia, Siberia and South Africa
Figures 1–2. 1. Male of Illiberis kardakoffi (Primorskiy Kray, vic. Anisimovka). 2. Male of Rhagades pruni pruni (Zabaykalskiy Kray, 34 km NE of Amazar).
Figures 3–4. 3 in New results of testing the attractant EFETOV-2 in the Far East of Russia, Siberia and South Africa
Figures 3–4. 3. Russia, Primorskiy Kray, Shkotovo District, vic. Anisimovka. Habitat of I. kardakoffi. 4. Russia, Primorskiy Kray, Khasanskiy District, vic. Vityaz. Habitat of I. kardakoffi and Rh. pruni chinensis.
Fig. 4 – Cluster analysis results for the distance from which ants mobilize from the nest. 4 in Mobilization Strategies in Ants (Hymenoptera: Formicidae)
Fig. 4 – Cluster analysis results for the distance from which ants mobilize from the nest. 4th cluster: F cin – Formica cinerea; 3rd cluster: F. fus – F. fusca; M. rub – Myrmica rubra; M. mut – Messor muticus; M. rug – Myrmica ruginodis; L. bru – Lasius brunneus; D. qua – Dolichoderus quadripunctatus; L. nig – Lasius niger; L. pla – L. platythorax; L. neg U – L. neglectus; T. cae – Tetramorium caespitum; T. err – Tapinoma erraticum; Temn – Temnothorax sp.; P. pal – Plagiolepis pallescens; L. ace – Leptothorax acervorum; S. fug – Solenopsis fugax; P. tau – Plagiolepis tauricus; T. arm – Tetramorium armatum; M. sal – Myrmica salina; M. spe – M. specioides; F. cun – Formica cunicularia; L. ema – Lasius emarginatus; F. ruf – Formica rufibarbis; F. cla – F. clara; C. aet – Camponotus aethiops; 2nd cluster: F. tru – Formica truncorum; L. ful – Lasius fuliginosus; C. vag – Camponotus vagus; F. pra – Formica pratensis; 1st cluster: F. rufa – Formica rufa; F. pol – F. polyctena; C. sub U – Crematogaster subdentata.
Fig. 4 in Double alignments of ammonoid aptychi from the Lower Cretaceous of Southeast France: Result of a post-mortem transport or bromalites?
Fig. 4. Mid−Valanginian aptychi in isolation. A. Single aptychus (one of the pair of plate), FSL 710901, Vergol section, layer 22 (Fig. 2B), Saynoceras verrucosum Zone, Subzone, and Horizon. B. Bivalved aptychi (paired structure), FSL 710902, Vergol section, layer 55 (Fig. 2B), S. verrucosum Zone, Subzone, and Horizon.
Fig. 6 in Double alignments of ammonoid aptychi from the Lower Cretaceous of Southeast France: Result of a post-mortem transport or bromalites?
Fig. 6. Mid−Valanginian aptychi in alignments. A. FSL 710907, Vergol section, layer 51 (Fig. 2B), Saynoceras verrucosum Zone, Subzone, and Horizon. B. FSL 710908, Vergol section, layer 15 (Fig. 2B), Busnardoites campylotoxus Zone, Karakaschiceras biassalense Subzone and Neocomites platycostatus Horizon. C. FSL 710909, Vergol section, layer 17 (Fig. 2B), S. verrucosum Zone, Subzone, and Horizon. D. FSL 710912, Vergol section, layer 51 (Fig. 2B), S. verrucosum Zone, Subzone, and Horizon. E. FSL 710911, Vergol section, layer 47 (Fig. 2B), S. verrucosum Zone, Subzone, and Horizon. F. FSL 710910, Vergol section, layer 17 (Fig. 2B), S. verrucosum Zone, Subzone, and Horizon (the bivalve is indicated by an arrowhead). Scale bars 10 mm.
Fig. 1. A in Double alignments of ammonoid aptychi from the Lower Cretaceous of Southeast France: Result of a post-mortem transport or bromalites?
Fig. 1. A. Location map of the Vergol (Drôme) section. B. Palaeogeographical map of the Vocontian Basin (Southeast France; Lower Cretaceous), modified from Ferry (1991).
Fig. 5 in Double alignments of ammonoid aptychi from the Lower Cretaceous of Southeast France: Result of a post-mortem transport or bromalites?
Fig. 5. Mid−Valanginian aptychi in alignments. A. FSL 710903, Vergol section, layer 17 (Fig. 2B), Saynoceras verrucosum Zone, Subzone, and Horizon. B. FSL 710904, Vergol section, layer 16 (Fig. 2B), Busnardoites campylotoxus Zone, Karakaschiceras biassalense Subzone, and Neocomites platycostatus Horizon. C. FSL 710905, Vergol section, layer 41 (Fig. 2B), S. verrucosum Zone, Subzone, and Horizon. D. FSL 710906, Vergol section, layer 43 (Fig. 2B), S. verrucosum Zone, Subzone, and Horizon. Scale bars 10 mm.
Fig. 3 in Double alignments of ammonoid aptychi from the Lower Cretaceous of Southeast France: Result of a post-mortem transport or bromalites?
Fig. 3. Morphological nomenclature of aptychi. Redrawn and partially modified from Arkell (1957) and Farinacci et al. (1976).
Fig. 4. Strict consensus cladogram resulting from a in A new plesiosauroid from the Toarcian (Lower Jurassic) of Alhadas, Portugal
Fig. 4. Strict consensus cladogram resulting from a reanalysis of the data matrix of Grossmann (2007), with Lusonectes included as an additional operational taxonomic unit. See text for interpretation. SMNS16812 is the holotype of "Plesiopterys wildii" = Seeleyosaurus according to Grossman (2007).
Fig. 1. a in Parasitological examination results of zoo animals in Germany between 2012 and 2022
Fig. 1. a) Trichodina spp. from a koi; b) Egg of Ascaridia platyceri from a Platycercus elegans; c) Egg of Oxyurida from a turtle; d) Egg of Enterobius vermicularis from a chimpanzee; e) Haematomyzus elephantis from an elephant; f) Ornithonyssus bacoti from a hamster.
Figs. 5 and 6. Results from cluster and linkage tree analyses. Fig. 5 in Myrmecofauna (Hymenoptera: Formicidae) response to habitat characteristics of tropical montane cloud forests in central Veracruz, Mexico
Figs. 5 and 6. Results from cluster and linkage tree analyses. Fig. 5. Dendrogram of hierarchical standardized clustering based on the SØrensen similarity index of the studied fragments. The cophenetic correlation coefficient of the cluster is 0.89. The dendrogram displays with continuous lines the divisions for which the SIMPROF test rejects the null hypothesis (where assemblages in that group have no further structure to explore) and with dashed lines the groups of assemblages not separated (at P <0.05) by SIMPROF. Fig. 6. Linkage tree analysis (LINKTREE) showing divisive clustering of fragments (F1–F5) from species compositions constrained by inequalities on one or more environmental variables. Only binary partitions of uncorrelated environmental variables are shown in the cluster. The dendrogram displays with continuous lines the divisions for which the SIMPROF test rejects the null hypothesis (where assemblages in that group have no further structure to explore) and with dashed lines the groups of assemblages not separated (at P <0.05) by SIMPROF.
Results and figures from "Evaluating the robustness of the ARIO model for a local disaster: 2021 Flooding in Germany"
<p>These files and notebook allow reproducing the figures from "Evaluating the robustness of the ARIO model for a local disaster: 2021 Flooding in Germany".</p> <p>The main result file is a pandas DataFrame saved in parquet format under "results/general-plot_df.parquet".</p> <p>Two notebooks allow post-processing these results and plot the figures.</p> <p>Reproduction of the raw results can be achieved with the Snakemake pipeline, available here: https://github.com/spjuhel/BoARIO-Sensitivity</p> <p> </p>
Results of Improved SMAP Soil Moisture Retrieval Using a Deep Neural Network-based Replacement of Radiative Transfer and Roughness Model
<p>This repository contains:</p> <ol> <li>A deep neural network (DNN) based soil moisture (SM) estimates (NN) based on the SMAP TB (Descending, 6 AM) and SMAP SCA-V ancillary data as the input variables. (<a href="../api/records/13309165/draft/files/SMAP_NN_36km_20150331_20220326.nc/content" target="_blank" rel="noopener noreferrer">SMAP_NN_36km_20150331_20220326.nc</a>)</li> <li>Temporally averaged roughness parameter (hNN) and scattering albedo (omegaNN) which are retrieved by inversely tracking the DNN model. (<a href="../api/records/13309165/draft/files/SMAP_hNN_omegaNN_36km_temporal_average_201503_202103.nc/content" target="_blank" rel="noopener noreferrer">SMAP_hNN_omegaNN_36km_temporal_average_201503_202103.nc</a>)</li> </ol> <p>Summary:</p> <p>The DNN model has been developed by relating SMAP TB and SMAP SCA-V ancillary data with in-situ SM data from the international soil moisture network (ISMN) using DNN. To minimize scale mismatch between gridded SMAP data and point in-situ data, the triple collocation analysis was conducted.</p> <p>The SM estimated from the DNN algorithm (NN) showed a good agreement with the ISMN data that was not used in the model training. Moreover, for a densely vegetated region located in the Amazon (Tambopata site) the NN showed less bias compared to available SM retrievals. </p> <p>Two parameters hNN and omegaNN are retrieved by ingesting NN to the modified dual channel algorithm. When the SM retrieval was conducted using the hNN and omegaNN, the result showed good agreement with the NN (DNN-based SM) with R of 0.986, ubRMSD of 0.015 m3/m3, and bias of -0.001 m3/m3.</p> <p>The paper "Improved SMAP Soil Moisture Retrieval Using a Deep Neural Network-based Replacement of Radiative Transfer and Roughness Model" published in the Transactions on Geoscience and Remote Sensing.</p> <p>For more details, please contact me (wotp12@unist.ac.kr)</p>
Results of GARPOS-MCMC v2.0.0 for GNSS-A data obtained at the SGO-A sites "TOS2", "KUM2", "FUKU", and "MYGI"
<p>Contains the results of "<a href="https://doi.org/10.5281/zenodo.13316197">GARPOS-MCMC v2.0.0</a>" for the GNSS-A data publishied by the Japan Coast Guard (<a href="https://doi.org/10.5281/zenodo.6417480">https://doi.org/10.5281/zenodo.6417480</a>). <br>Please refer Watanabe et al. (preprint will be available soon) for the details for methods and figure captions.</p> <p>Contents:</p> <p>- Results of GARPOS-MCMC v2.0.0 for the foure SGO-A sites (FUKU/KUM2/MYGI/TOS2). </p> <ul> <li>File name contains the site name and campaign code <ul> <li>*-chain.csv: Values of MCMC samples </li> <li>*-chain.pdf: Plots of MCMC samples</li> <li>*-hist.pdf: Plots of distributions and histograms for the parameters </li> <li>*-m.p.dat: Model parameters for the maximum a posteriori sample in the series (not be used as the "result")</li> <li>*-obs.csv: Acoustic data including residuals for the maximum a posteriori sample in the series (not be used as the "result")</li> <li>*-percentile.csv: Percentiles of the posterior pdfs for each parameters</li> <li>*-res.dat: Positioning result for the maximum a posteriori sample in the series (not be used as the "result")</li> <li>files in fig/ show the travel time residuals and parameters for the maximum a posteriori sample in the series</li> </ul> </li> <li>Directory "tested models" contains the MCMC series with inverse temperature of 1/(log <em>n</em>). <ul> <li>fig_searchres*png: Plots of relative WBIC values</li> <li>searchres-*csv: WBIC and relevant values for each model</li> <li>Others: same as above</li> </ul> </li> </ul>
MOM6-COBALT2 model results for asymmetrical Ocean Carbon Responses to La Niña and El Niño in the Tropical Pacific Ocean
<p>1. MOM6 COBALT2 model results</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_fco2_decomposition_1990_2021.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_fco2_decomposition_1990_2021.nc</a></p> <p>(air-sea carbon flux decomposition)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_dic_stf_gas_1980_2023_detrend_deseason_matlab_tp.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_dic_stf_gas_1980_2023_detrend_deseason_matlab_tp.nc</a></p> <p> (detrended and deseasonalized air-sea CO2 flux, positive to ocean)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_sfc_chl_1980_2023.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_sfc_chl_1980_2023.nc</a></p> <p> (sea surface chlorophyll)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_SSH_1990_2021_detrend_deseason_matlab.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_SSH_1990_2021_detrend_deseason_matlab.nc</a></p> <p> (detrended and deseasonalized sea surface height)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_sfc_no3_1980_2023.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_sfc_no3_1980_2023.nc</a></p> <p>(sea surface nitrate, NO3)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_SST_1980-2023.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_SST_1980-2023.nc</a></p> <p> (sea surface temperature)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_sfc_po4_1980_2023.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_sfc_po4_1980_2023.nc</a></p> <p> (sea surface phosphate, PO4)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_SSS_1980-2023.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_SSS_1980-2023.nc</a></p> <p> (sea surface salinity)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_SSS_1990-2023_detrend_deseason_matlab.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_SSS_1990-2023_detrend_deseason_matlab.nc</a></p> <p>(detrended and deseasonalized sea surface salinity)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_SST_1990-2023_detrend_deseason_matlab.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_SST_1990-2023_detrend_deseason_matlab.nc</a></p> <p>(detrended and deseasonalized sea surface temperature)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_u_1990-2021_detrend_deseason_matlab.nc.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_u_1990-2021_detrend_deseason_matlab.nc.nc</a></p> <p>(detrended and deseasonalized sea surface zonal velocity)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_MLD_003_1980-2023.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_MLD_003_1980-2023.nc</a></p> <p>(Mixing layer depth with a density criterial of 0.03 kg/m3)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_v_1990-2021_detrend_deseason_matlab.nc.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_v_1990-2021_detrend_deseason_matlab.nc.nc</a></p> <p>(detrended and deseasonalized sea surface meridional velocity)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_pco2surf_1980_2023_detrend_deseason_matlab_tp.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_pco2surf_1980_2023_detrend_deseason_matlab_tp.nc</a></p> <p> (detrended and deseasonalized ocean pCO2 in the ocean surface)</p> <p><a href="../api/records/13325632/draft/files/hist_gcb_simA_ocean_static.nc/content" target="_blank" rel="noopener noreferrer">hist_gcb_simA_ocean_static.nc</a></p> <p>(grid of model)</p> <p><a href="../api/records/13325632/draft/files/all_gcb_simA_monthly_budget_mld001_pco2surf_1990_2021_detrend_deseason_matlab.nc/content" target="_blank" rel="noopener noreferrer">all_gcb_simA_monthly_budget_mld001_pco2surf_1990_2021_detrend_deseason_matlab.nc</a></p> <p> (budget terms used for ocean pCO2 budget analysis, vertical mean in the mixing layer depth (criterial of 0.01 kg/m3), then do detrended and deseasonalized)<br>pco2_hadv_hdif: horizontal transport term, H_circ;<br>dpco2_vadv_vdif: vertical transport term,V_circ;<br>dpco2_bio: biological term<br>dpco2_rain: surface freshwater term<br>dpco2_sst: thermal term<br>dpco2_dt: pco2 response term<br>dpco2_flux: CO2 flux response term</p> <p>2. dataset</p> <p><a href="../api/records/13325632/draft/files/co2_products_Rodenbeck_v2022_monthly_all_detrend_deseason_by_filter.nc/content" target="_blank" rel="noopener noreferrer">co2_products_Rodenbeck_v2022_monthly_all_detrend_deseason_by_filter.nc</a></p> <p>(CO2 based MLS: detrended and deseasonalized ocean pCO2 and air-sea carbon flux in the ocean surface)</p> <p><a href="../api/records/13325632/draft/files/co2_products_Rodenbeck_v2022_monthly_area.nc/content" target="_blank" rel="noopener noreferrer">co2_products_Rodenbeck_v2022_monthly_area.nc</a></p> <div>(the grid of MLS)</div> <p><a href="../api/records/13325632/draft/files/co2_products_Landschutzer_v2022_MPI_SOM_FFN_2022_NCEI_OCADS_detrend_deseason_matlab.nc/content" target="_blank" rel="noopener noreferrer">co2_products_Landschutzer_v2022_MPI_SOM_FFN_2022_NCEI_OCADS_detrend_deseason_matlab.nc</a></p> <p>(CO2 based SOM-FFN: detrended and deseasonalized ocean pCO2 and air-sea carbon flux in the ocean surface)</p> <p><a href="../api/records/13325632/draft/files/co2_products_Landschutzer_v2022_MPI_SOM_FFN_2022_NCEI_OCADS_area.nc/content" target="_blank" rel="noopener noreferrer">co2_products_Landschutzer_v2022_MPI_SOM_FFN_2022_NCEI_OCADS_area.nc</a></p> <p>(the grid of SOM-FFN)</p> <p><a href="../api/records/13325632/draft/files/precipitation_JRA55-do-v1.5merge_res_all_monthly_prra.JRA.1.5.monthly_detrend_deseason.nc/content" target="_blank" rel="noopener noreferrer">precipitation_JRA55-do-v1.5merge_res_all_monthly_prra.JRA.1.5.monthly_detrend_deseason.nc</a></p> <p>(JRA: detrended and deseasonalized precipitation)</p> <p><a href="../api/records/13325632/draft/files/phosphate_all_woa18_all_p_monthly.nc/content" target="_blank" rel="noopener noreferrer">phosphate_all_woa18_all_p_monthly.nc</a></p> <p>(WOA: sea surface phosphate, PO4)</p> <p><a href="../api/records/13325632/draft/files/ssh_AVISO_all_sla_tp_twosat_phy_l4_vDT2018_monthly_1994_2020_03_01_detrend_deseason.nc/content" target="_blank" rel="noopener noreferrer">ssh_AVISO_all_sla_tp_twosat_phy_l4_vDT2018_monthly_1994_2020_03_01_detrend_deseason.nc</a></p> <p>(AVISO: detrended and deseasonalized sea surface height)</p> <p><a href="../api/records/13325632/draft/files/sss_satellite_all_oisss_v1_sss_201109-202203_monthly.nc/content" target="_blank" rel="noopener noreferrer">sss_satellite_all_oisss_v1_sss_201109-202203_monthly.nc</a></p> <p>(OISSS: sea surface salinity)</p> <p><a href="../api/records/13325632/draft/files/sss_satellite_all_oisss_v1_sss_201109-202203_monthly_detrend_deseason.nc/content" target="_blank" rel="noopener noreferrer">sss_satellite_all_oisss_v1_sss_201109-202203_monthly_detrend_deseason.nc</a></p> <div>(OISSS: detrended and deseasonalized sea surface salinity)</div> <p><a href="../api/records/13325632/draft/files/co2_SOCAT_SOCATv2022_tracks_gridded_monthly.nc/content" target="_blank" rel="noopener noreferrer">co2_SOCAT_SOCATv2022_tracks_gridded_monthly.nc</a></p> <p>(SOCAT: ocean pCO2)</p> <p><a href="../api/records/13325632/draft/files/mld_obs_mld_DR003_c1m_reg2.0_rewrite_nanvalue.nc/content" target="_blank" rel="noopener noreferrer">mld_obs_mld_DR003_c1m_reg2.0_rewrite_nanvalue.nc</a></p> <p>(Mixing layer depth with a density criterial of 0.03 kg/m3)</p> <p><a href="../api/records/13325632/draft/files/nitrate_all_woa18_all_n_monthly.nc/content" target="_blank" rel="noopener noreferrer">nitrate_all_woa18_all_n_monthly.nc</a></p> <p>(WOA: sea surface nitrate, NO3)</p> <p><a href="../api/records/13325632/draft/files/sst_OISST_allsst.avhrr-only-v2.1_1990_2021_monthly.nc/content" target="_blank" rel="noopener noreferrer">sst_OISST_allsst.avhrr-only-v2.1_1990_2021_monthly.nc</a></p> <p> (OISST: sea surface temperature)</p> <p><a href="../api/records/13325632/draft/files/sst_OISST_allsst.avhrr-only-v2.1_1990_2021_monthly_detrend_deseason.nc/content" target="_blank" rel="noopener noreferrer">sst_OISST_allsst.avhrr-only-v2.1_1990_2021_monthly_detrend_deseason.nc</a></p> <p>(OISST: detrended and deseasonalized sea surface temperature)</p> <p><a href="../api/records/13325632/draft/files/chl_OC_CCI_all_OC_CCI_momthly_chlor_a_4km_fv5.0_199709_202112_clim.nc/content" target="_blank" rel="noopener noreferrer">chl_OC_CCI_all_OC_CCI_momthly_chlor_a_4km_fv5.0_199709_202112_clim.nc</a></p> <p>(GlobColour: sea surface chlorophyll)</p> <p><a href="../api/records/13325632/draft/files/uwind_JRA55-do-v1.5merge_res_all_monthly_uas.JRA.1.5.monthly_detrend_deseason.nc/content" target="_blank" rel="noopener noreferrer">uwind_JRA55-do-v1.5merge_res_all_monthly_uas.JRA.1.5.monthly_detrend_deseason.nc</a></p> <p>(JAR: detrended and deseasonalized zonal wind velocity)</p> <p><a href="../api/records/13325632/draft/files/TAO_CO2_tao_pco2_13stations_monthly_deseason_1997_2017.nc/content" target="_blank" rel="noopener noreferrer">TAO_CO2_tao_pco2_13stations_monthly_deseason_1997_2017.nc</a></p> <p>(TAO: sea surface temperature, sea surface salinity, and ocean pco2)</p> <p>3. Figure</p> <p>Figure1-4, FigureS1-S11 are data analysis files used python</p> <p> </p>
FIGURE 6. 1, Talpidae phylogeny resulting from a in Condylura (Mammalia, Talpidae) reloaded: New insights about the fossil representatives of the genus
FIGURE 6. 1, Talpidae phylogeny resulting from a parsimony analysis based on 157 discrete morphological characters, modified from Sánchez-Villagra et al. (2006, figure 1). 2, Unconstrained Talpidae phylogeny based on a parsimony analysis (DELTRAN optimization) based on 176 discrete morphological characters, modified from Schwermann and Thompson (2015, figure 16A).
FIGURE 1 in Fish injuries resulting from transient operating conditions in a Brazilian hydropower plant: morphological, physiological and biochemical evaluation in Pimelodus maculatus (Siluriformes: Pimelodidae)
FIGURE 1 | Histological gill alterations in Pimelodus maculatus collected during transient operating conditions (magnification: × 400). Arrows indicate the following lesions: A. Aneurysm; B. Epithelium detachment; C. Telangiectasia; and D. Interlamellar hyperplasia.
FIGURE 2 in Fish injuries resulting from transient operating conditions in a Brazilian hydropower plant: morphological, physiological and biochemical evaluation in Pimelodus maculatus (Siluriformes: Pimelodidae)
FIGURE 2 | Histological alterations in liver and spleen of Pimelodus maculatus collected during transient operating conditions in the tailrace of Machadinho HPP (magnification: × 400). Arrows and asterisks indicate the following lesions: A. Melanomacrophage centers (asterisk) and congested vein (arrow) in the liver; B. Blood cells indicating hepatic hemorrhage (asterisk); C. Melanomacrophage centers in the spleen (asterisk); D. Mononuclear inflammatory infiltrate in the spleen (arrow).
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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.