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Fig. 1 in Chewing Lice (Order Mallophaga, Suborders Amblycera And Ichnocera) Fauna Of Domestic Chicken (Gallus Gallus Domesticus) In Ukraine
Fig. 1. Menopon gallinae: ♀: 1 — forehead; 2 — temporal lobe; 3 — antenna; 4 — eyes; 5 — abdomen (×400); ♂: 1 — forehead; 2 — temporal lobe; 3 — antenna; 4 — foot; 5 — bristles; 6 — abdomen posterior (×300).
Fig. 4 in Chewing Lice (Order Mallophaga, Suborders Amblycera And Ichnocera) Fauna Of Domestic Chicken (Gallus Gallus Domesticus) In Ukraine
Fig. 4. Morphology of Goniocotes hologaster: ♀: 1 — forehead; 2 — eyes; 3 — bristles on head; 4 — the rear of the abdomen (×300); ♂: 1 — head; 2 — temporal edges; 3 — overall oval body; 4 — the last segment of the abdomen blade-shaped (×250).
Fig. 3 in Chewing Lice (Order Mallophaga, Suborders Amblycera And Ichnocera) Fauna Of Domestic Chicken (Gallus Gallus Domesticus) In Ukraine
Fig. 3. Morphology of Menacanthus cornutus: ♀: 1 — forehead; 2 — temporal lobe; 3 — sternal plate; 4 — crop; 5 — posterior part of the abdomen with bristles; ♂: 2 — eye; 3 — prothorax with foots; 4 — mesothorax; 5 — metathorax; 6 — abdomenal bristles; 7 — oval shape of the rear of the abdomen; 8 — ejaculatory ducts (×400).
Fig. 2 in Chewing Lice (Order Mallophaga, Suborders Amblycera And Ichnocera) Fauna Of Domestic Chicken (Gallus Gallus Domesticus) In Ukraine
Fig. 2. Morphology Menacanthus stramineus: ♀: 1 — forehead; 2 — temporal lobe; 3 — prothorax; 4 — mesothorax; 5 — metathorax; 6 — tarse; 7 — crop; 8 — the egg chamber; ♂: 1 — prothorax foot; 2 — foot mesothorax; 3 — foot metathorax; 4 — testes; 5 — crop (×400).
Fig. 1 in Bird Lice (Mallophaga, Philopteridae, Menoponidae) Of Domestic Pigeons On Specialized Pigeon Breeding Farms In Poltava
Fig. 1. Fam. Philopteridae: а — Columbicola columbae — general view; b — Companulotes compare — head;
Fig. 3 in Bird Lice (Mallophaga, Philopteridae, Menoponidae) Of Domestic Pigeons On Specialized Pigeon Breeding Farms In Poltava
Fig. 3. Fam. Menoponidae: a — Bonomiella columbae — general view; b — Hohorstiella lata— general view.
Three-dimensional movement of the beak during seed processing in domestic canaries
<p>Many songbird species rely on seeds as a primary food source and the process of picking up, positioning, cracking, dehusking, and swallowing seeds is one of the most sophisticated tasks of the beak. Still, we lack understanding about how granivorous songbirds move their beak during the different phases of seed processing. In this study, we used multi-view high speed imaging to analyze the three-dimensional movement of the beak in feeding domestic canaries. Our analysis focuses on correlation of upper and lower beak, frequency of mandibulation, and direction of mandible movement in 3D space. We show that the correlation of maxilla and mandible movement differs among the phases of seed processing. Furthermore, we found that the beak moves at extremely high frequencies, up to 25 Hz, which resembles previously reported maximal syllable rates in singing canaries. Finally, we report that canaries use specific 3D mandible movements during the different phases of seed processing. Kinematic parameters do not differ between male and female canaries. Our findings provide an important biomechanical basis for better understanding the beak as a functional tool.</p>
Intermediate data files from the compilation of Economy-wide Material Flow Accounts for the Domestic Extraction of abiotic materials
<p>These files represent a selection of intermediary files from the compilation of material flow accounts on Domestic Extraction (DE) of abiotic materials. The main output of this compilation has been integrated in the UNEP IRP Global Material Flow Database (GMFD).</p> <p>These files include input files (e.g. IDs for data harmonization, or factors for data conversion), as well as output files (e.g. supplementary information, or detailed data accounts before aggregation and integration into the GMFD).</p> <p>Please note: These files are published exclusively for the purpose of making this information available to interested parties in a transparent and orderly fashion, in particular to other research projects who may have use for it. Therefore, these files are not associated with any publication and have not been adjusted or formatted with regard to any publications standards, i.e. they are uploaded exactly as they have been processed in the respective R Github repository of the underlying data compilation.</p> <p>The following description attempts to give a short overview of the respective types of files and their contents. For more detailed information on the data compilation, please refer to chapters 6, 8, and 10 in the <a href="https://resourcepanel.org/sites/default/files/irp_technical_annex_global_material_flows_database.pdf">technical report</a> of the GMFD.</p> <p> </p> <p><strong>Main data output (i.e. detailed material flow accounts)</strong></p> <p><em>DE_met_min_fos_CCC_2021-11-04.csv</em>: Data aggregated to the official categories (CCC/TCCC) used for integration into the GMFD. With IDs, without names (e.g. for materials and countries).</p> <p><em>DE_met_min_fos_CCC_with_names_2021-11-04.csv</em>: Same as above, but with names.</p> <p><em>DE_met_min_fos_Detailed_2021-11-04.csv</em>: Detailed accounts, as compiled, before final aggregation. With IDs, without names.</p> <p><em>DE_met_min_fos_Detailed_with_names_2021-11-04.csv</em>: Same as above, but with names.</p> <p> </p> <p><em>DE_met_min_fos_Detailed_2022-05-24.csv: </em>Slightly revised version from May 2022. But not included in current GMFD version.</p> <p> </p> <p><strong>ID and concordance tables</strong></p> <p><em>ccc_vs_mat_ids.csv:</em> Concordance table for allocation of detailed material accounts to aggregated CCC accounts.</p> <p><em>country_ids.csv:</em> General ID table for country IDs and names</p> <p><em>estimated_ids.csv:</em> Material IDs which are assigned during application of ore estimation factors.</p> <p><em>geo_exist.csv:</em> Table for consistent geographic adjustment of data for specific countries which have disintegrated over time (not including regions like Germany, Yemen, Ethiopia, Sudan, which all have been dealt with individually if necessary).</p> <p><em>material_ids.csv:</em> General ID table for material IDs and names.</p> <p><em>source_country_ids.csv:</em> Concordance table for country IDs (i.e. for allocation of harmonized IDs to source namings/IDs)</p> <p><em>source_material_ids.csv:</em> Concordance table for material IDs (i.e. for allocation of harmonized IDs to source namings/IDs)</p> <p><em>source_unit_ids.csv:</em> Concordance table for unit IDs (i.e. for allocation of harmonized IDs to source namings/IDs)</p> <p><em>unit_ids.csv:</em> General ID table for unit IDs and names.</p> <p> </p> <p><strong>Conversion factors</strong></p> <p><em>conversion_elements.csv:</em> Factors applied for conversion from metal compounds to elemental metals.</p> <p><em>conversion_factors_units.csv:</em> Factors applied for unit conversions.</p> <p> </p> <p><strong>Ore estimation factors</strong></p> <ul> <li>These factors represent content-to-ore ratios (i.e. "tonnes of extracted ore/mineral per ton of produced content”).</li> </ul> <p><em>all_integrated_est_fac_2021-11-04.csv:</em> Factors for estimation of metal and mineral ores (all which have been compiled/integrated)</p> <p><em>applied_est_fac_2021-11-04.csv:</em> Factors for estimation of metal and mineral ores (which have actually been applied)</p> <p><em>average_metal_prices_1990-2020.csv:</em> Metal prices applied in the compilation of estimation ratios.</p> <p><em>raw_metal_to_ore_ratios_fineprint.csv:</em> Raw metal-to-ore ratios derived from FINEPRINT mining data.</p> <p><em>raw_metal_to_ore_ratios_snl.csv:</em> Raw metal-to-ore ratios derived from SNL mining data.</p> <p> </p> <p><strong>Intermediate files from data processing</strong></p> <p><em>all_interm_conv_integr_2021-12-13.csv:</em> Harmonized, converted (units & elemental metals), integrated (i.e. without double counting). Before any estimations (ores & construction minerals) and before final cleaning/formatting.</p> <p><em>wmd_bgs_usgs_interm_harmonized_2021-12-13.csv:</em> All harmonized raw data from WMD/BGS/USGS, before any further processing (i.e. with double counting).</p> <p> </p> <p><strong>Comparison data (for mining accounts from FINEPRINT project)</strong></p> <p><em>data_for_comparison_2022-05-24.csv:</em> Data set specifically compiled for comparison with accounts on production of mines from the FINEPRINT project. Has been applied for verification of data published in <em>"Jasansky et al. (2022) An open database on global coal and metal mining"</em>.</p> <ul> <li>Includes all available types of materials which have been reported (e.g. ores and metals and metal compounds) <ul> <li>meaning: also materials which are associated with each other, for example iron ore and iron (and would therefore have been selectively integrated/excluded in the GMFD compilation).</li> </ul> </li> <li>Excludes any double counting for the exact same material from different data sources</li> <li>Harmonized IDs, converted units</li> <li>Includes metal compounds approximated/converted from reported elemental metals (where possible)</li> </ul> <p> </p> <p><strong>materialflows.net</strong></p> <p><em>data_sunburst_material_profiles_20220607.csv:</em> Full detail of data underlying the Sunburst visualization "Global Domestic Extraction in 2019, by material group" in section "Raw Material Profiles" on materialsflow.net. However, for all available years. Includes data on Domestic Extraction of biomass. Includes detail for CCC, MFA13+, MFA4+</p> <p> </p> <p><strong>Outliers</strong></p> <p><em>overview_adjusted_outliers_2021-12-22.csv:</em> Overview of outliers which were adjusted during final formatting.</p> <p> </p> <p><strong>Other</strong></p> <p><em>approximation_tailings_detailed_2021-09-26.csv:</em> Estimation of tailings based on reported amounts of ores/minerals and their respective contents.</p> <p> </p>
Fig. 4 in The threat of free-ranging domestic dog to native wildlife: implication for conservation in Southeast Asia
Fig. 4. The spatial distribution of perceived risk from domestic dog (Canis familiaris) across mainland Southeast Asia. Excluded human settlements and water bodies have been marked in white.
Fig. 3 in The threat of free-ranging domestic dog to native wildlife: implication for conservation in Southeast Asia
Fig. 3. Percentage perceived risk in Avian and Mammalian orders. Height of peaks represent number of species scaled to 2, see Supplementary Materials 4 and 5. Orders with two or less species, including Otidiformes, Dermoptera, Perissodactyla, Pholidota, and Proboscidea, were removed for visualisation.
Fig. 2 in The threat of free-ranging domestic dog to native wildlife: implication for conservation in Southeast Asia
Fig. 2. Percentage perceived risk in Red List categories. Height of peaks represent number of species scaled to 2, see Supplementary Materials 4 and 5.
Fig. 1 in The threat of free-ranging domestic dog to native wildlife: implication for conservation in Southeast Asia
Fig. 1. Bayesian networks modelling (a) perceived risk to carnivore mammalian species, (b) perceived risk to non-carnivore mammalian species, (c) perceived risk to Avian species and, (d) the spatial distribution of perceived risk from domestic dogs in mainland Southeast Asia.
Fig. 2 in Description of SarCoCYSTIS PlaTYrhYNChoSI n. sp. (Apicomplexa: Sarcocystidae) from domestic ducks ANaS PlaTYrhYNChoS (Anseriformes: Anatidae) in China
Fig. 2 Phylogenetic trees of selected members of Sarcocystis species. The trees were conducted using 18S rDNA (a), 28S rDNA (b) and mcox1 (c) sequences using maximum likelihood (ML) with the Kimura 2–parameter, Hasegawa–Kishino–Yano and Hasegawa–Kishino–Yano models, respectively. The values between the branches represent bootstrap values per 1000 replicates. Values <50% are not shown. Besnoitia besnoiti, Cystoisopora suis, Toxoplasam gondii or Hammondia heydorni were selected to root these trees.The newly obtained sequences of the 18S rDNA (OP480004), 28S rDNA (OP480005) and mtcox1 (OP485287) for Sarcocystis platyrhynchosi n. sp. are shown in bold. The phylogenetic trees inferred from the three genes had similar topologies, and Sarocystis platyrhynchosi formed a separate branch within a group encompassing Sarcocystis spp. obtained from avian or carnivorous intermediate hosts and avian marsupial, or carnivorous definitive hosts
Fig. 1 in Description of SarCoCYSTIS PlaTYrhYNChoSI n. sp. (Apicomplexa: Sarcocystidae) from domestic ducks ANaS PlaTYrhYNChoS (Anseriformes: Anatidae) in China
Fig. 1 Morphological characteristics of Sarcocystis platyrhynchosi n. sp. isolated from the skeletal muscle of domestic ducks. a Light microscopy (LM) micrograph of a sarcocyst (unstained). Note the short brush-like villar protrusions (vps). b LM micrograph of lancet-like bradyzoites (unstained). c Transmission electron microscopy (TEM) micrograph of a sarcocyst. Note the lanceolated villar protrusions (vps) and the bundles of microtubes (mt) within the vps. d TEM micrograph of a sarcocyst. Note the narrowed stalk (arrowhead) of the vps, bundled mt extending into the ground substance (gs) and the smooth electron dense layer (edl) lining the vps
Data and code for: A standardised approach to quantifying activity in domestic dogs
<p>Objective assessment of activity via accelerometry can provide valuable insights into dog health and welfare. Common activity metrics involve using acceleration cut-points to group data into intensity categories and reporting the time spent in each category. Lack of consistency and transparency in cut-point derivation makes it difficult to compare findings between studies. We present an alternative metric for use in dogs: the acceleration threshold <em>(</em>as a fraction of standard gravity<em>,1g = 9.81m/s<sup>2</sup>)</em> above which the animal's X most active minutes are accumulated (MX<sub>ACC</sub>) over a 24-hour period. We report M2<sub>ACC,</sub> M30<sub>ACC</sub> and M60<sub>ACC</sub> data from a colony of healthy beagles (n=6) aged 3-13 months. To ensure that reference values are applicable across a wider dog population, we incorporated labelled data from beagles and volunteer pet dogs (n=16) of a variety of ages and breeds. The dogs' normal activity patterns were recorded at 200 Hz for 24-hours using collar-based Axivity-AX3 accelerometers. We calculated acceleration vector magnitude and MX<sub>ACC</sub> metrics. Using labelled data from both beagles and pet dogs, we characterise the range of acceleration outputs exhibited for a variety of behaviours, enabling meaningful interpretation of MX<sub>ACC</sub>. These metrics will help standardise measurement of canine activity, inform development of exercise guidelines and adherence monitoring, and serve as outcome measures for veterinary and translational research. This repository contains two files: 1) `LMM_input_data.csv`, a spreadsheet file containing the raw data used to explore the effect of modifying epoch length and sample frequency on aggregate activity metrics using linear mixed effects models as described in the manuscript. There is one row per dog per epoch length, sample frequency and age combination, and 2) `getMostActiveMinsThresh.m`, a MATLAB function used to compute the MX ACC outcome metrics that are explored in the manuscript.</p>
Figure 2 in Genetic structure of Trypanosoma congolense "forest type" circulating in domestic animals and tsetse flies in the South-West region of Cameroon
Figure 2. NJ Tree based on Cavalli-Sforza and Edwards chord distance matrix of T. congolense "forest type" circulating in tsetse flies and domestic animals of Fontem.
Annex 1 of "Domestic fish for more versatile and safer consumption, EU-fish IV"
<p>This file is part of Annex 1 of report "Domestic fish for more versatile and safer consumption, EU-fish IV" (to be published in September 2024 in series Publications of the Government’s analysis, assessment and research activities in Finland). The data contains results of dioxins (PCDD/F + dl-PCB), PFAS compounds, total mercury and methyl mercury, fatty acids and Vitamin D in fish samples from Finland. Details on sampling and analysis are found in the report.</p>
Fig. 5 in Rumen Ciliate Biota of Domestic Cattle (Bos taurus taurus) in İstanbul, Turkey and Infraciliature of Metadinium medium (Entodiniomorphida, Ophryoscolecidae)
Fig. 5. Photomicrographs of D. dogieli. a, b – in MFS and Lugol's iodine from the right side. CV – contractile vacuole, MA – macronucleus, MI – micronucleus. Narrow longitudinal thickening of the pellicle (arrowhead).
Fig. 4 in Rumen Ciliate Biota of Domestic Cattle (Bos taurus taurus) in İstanbul, Turkey and Infraciliature of Metadinium medium (Entodiniomorphida, Ophryoscolecidae)
Fig. 4. SEM images of Diplodinium dogieli. a – from the left side, b – from the right side, c – from the right side in binary fission. AL – adoral lip, DCZ – dorsal ciliary zone, DL – dorsal lip, O – operculum. Narrow longitudinal thickening of the pellicle (arrowheads).
Fig. 3 in Rumen Ciliate Biota of Domestic Cattle (Bos taurus taurus) in İstanbul, Turkey and Infraciliature of Metadinium medium (Entodiniomorphida, Ophryoscolecidae)
Fig. 3. Photomicrographs of M. medium in binary fission from the right side, after pyridinated silver carbonate impregnation. AP – adoral polybrachykinety, DAP – dorso-adoral polybrachykinety, DP – dorsal polybrachykinety, DPR – dorsal primordium, KL – kinety loop, LP – left primordium, NP – narrow polybrachykinety between ventral and right primordia, PK – paralabial kineties, RPR – right primordium, VP – vestibular polybrachykinety, VPR – ventral primordium.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.