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667 results for “distinguishability”
MeV TOF SIMS determination of deposition order between optically distinguishable and indistinguishable inks
<p>In the forensic investigation of questioned documents, it is often very important to know the deposition order of ink traces from two different writing tools at their intersection on a paper. In the present work, intersections of inks from several writing tools were studied using optical techniques that are standardly applied for questioned documents examination in a forensic laboratory, and an accelerator-based Ion Beam Analysis (IBA) technique called Secondary Ion Mass Spectrometry using MeV ions (MeV SIMS) that is applied in an accelerator facility. MeV SIMS provides molecular information about the studied inks from writing tools, which is an added value and can be also applied for the determination of deposition order but was so far relatively rarely used in forensic studies. Aim of this paper is to compare performance of optical techniques and MeV SIMS for several combinations of intersecting lines. Cases were divided into those in which optical techniques can distinguish used inks and those which are optically completely indistinguishable. In the latter cases, we show that although mass spectra of used inks (from blue ballpoint pens) had extremely small differences, these in combination with advanced and most importantly objective multivariate algorithms could be very beneficial in resolving the deposition order at the intersection of optically indistinguishable inks. In general, MeV SIMS proved to be more efficient for oil-based inks while difficulties were encountered with water-based ones, similar to optical methods.</p>
MCR LTER: Coral Reef: Distinguishing the molecular diversity, nutrient content, and energetic potential of exometabolomes produced by macroalgae and reef-building corals; data for Kelly et al., 2022 PNAS
Metabolites exuded by primary producers comprise a significant fraction of marine dissolved organic matter, a poorly characterized, heterogenous mixture that dictates microbial metabolism and biogeochemical cycling. We present a foundational untargeted molecular analysis of exudates released by coral reef primary producers using liquid chromatography–tandem mass spectrometry to examine compounds produced by two coral species and three types of algae (macroalgae, turfing microalgae, and crustose coralline algae [CCA]) from Mo’orea, French Polynesia. Of 10,568 distinct ion features recovered from reef and mesocosm waters, 1,667 were exuded by producers; the majority (86%) were organism specific, reflecting a clear divide between coral and algal exometabolomes. These data allowed us to examine two tenets of coral reef ecology at the molecular level. First, stoichiometric analyses show a significantly reduced nominal carbon oxidation state of algal exometabolites than coral exometabolites, illustrating one ecological mechanism by which algal phase shifts engender fundamental changes in the biogeochemistry of reef biomes. Second, coral and algal exometabolomes were differentially enriched in organic macronutrients, revealing a mechanism for reef nutrient-recycling. Coral exometabolomes were enriched in diverse sources of nitrogen and phosphorus, including tyrosine derivatives, oleoyl-taurines, and acyl carnitines. Exometabolites of CCA and turf algae were significantly enriched in nitrogen with distinct signals from polyketide macrolactams and alkaloids, respectively. Macroalgal exometabolomes were dominated by nonnitrogenous compounds, including diverse prenol lipids and steroids. This study provides molecular-level insights into biogeochemical cycling on coral reefs and illustrates how changing benthic cover on reefs influences reef water chemistry with implications for microbial metabolism. This material is based upon work supported by the U.S. National Science Founda
The coupling mechanism of ligands with SERT distinguishes substrates from inhibitors (raw data)
<p>Raw data of the manuscript: Ligand coupling mechanism of the human serotonin transporter differentiates substrates from inhibitors</p> <p><strong>Abstract:</strong></p> <p>The presynaptic serotonin transporter (SERT) reuptakes the serotonin (5HT) released into the synaptic cleft, thus ensuring temporal and spatial regulation of serotonergic signalling. Clinically approved drugs used for the treatment of neurological disorders, including depression and anxiety modulate SERT by trapping the transporter in the outward-open conformation. Illicit drugs of abuse as amphetamines act as substrates but reverse the transport direction, thereby releasing intracellular accumulated 5HT. Both mechanisms increase extracellular 5HT levels. Stoichiometry of the transport cycle has been described by kinetic schemes, the structures of the main conformations within the transport cycle revealed static coordinates. By combining <em>in-silico</em> approaches with <em>in-vitro</em> experiments and making use of a homologous series of 5HT analogues, we decoded the essential coupling mechanism between the substrate and the transporter which triggers uptake. The free energy calculations showed that only scaffold-bound substrates can correctly close the extracellular gate by pulling on the bundle domain through long-range electrostatic interactions. The associated spatial and physico-chemical requirements define substrate and inhibitor properties, opening new possibilities for rational drug design approaches.</p>
Distinguishing between high entropy bit streams
<p>This dataset contains the curated files, classified by type and extension so that other researchers can compute their features and replicate outcomes. </p> <p> </p> <p>A total of 5 datasets (i.e., one according to each file size denoted as 64, 128, 256, 512, and 1024) each one consisting of exactly 50% encrypted and 50% compressed files.</p> <p>-The encryption algorithms used to generate the files were:</p> <p>AES(128 / 192 / 256) and Camelia(128 / 192 / 256</p> <p> </p> <p>-In the case of compressed files:</p> <p>ZIP RAR BZIP2 GZIP</p> <p> </p> <p>-Different source files were considered to generate the encrypted and compressed files. </p> <p>COCO Dataset (http://cocodataset.org/home) <br> Microsoft Research (https://www.microsoft.com/en-us/research/project/rgb-d-dataset-7-scenes/)<br> ArXiv (https://arxiv.org/)<br> Project Gutenberg (https://www.gutenberg.org/)<br> Several classical music symphonies in MP3 format <br> YouTube-8M dataset<br> Binaries extracted from system32 in Win10 x64 and sbin from Ubuntu 16.04</p> <p> </p> <p> </p> <p> </p> <p> </p>
Distinguishing between canonical and non-canonical tRNA genes reveals that Thermococcaceae adhere to the standard archaeal tRNA gene set
<p><strong>Abstract</strong></p> <p>Automated genome annotation is an essential tool for extracting biological information from sequence data. The identification and annotation of tRNA genes is frequently performed by the software package tRNAscan-SE, the output of which is listed – for selected genomes – in the Genomic tRNA database (GtRNAdb). Given the central role of tRNA in molecular biology, the accuracy and proper application of tRNAscan-SE is important for both interpretation of the output, and continued improvement of the software. Here, we report a manual annotation of the predicted tRNA gene sets for 20 complete genomes from the archaeal taxon Thermococcaceae. According to GtRNAdb, these 20 genomes contain a number of putative deviations from the standard set of canonical tRNA genes in Archaea. However, manual annotation reveals that only one represents a true divergence; the other instances are either (i) non-canonical tRNA genes resulting from the integration of horizontally transferred genetic elements, or CRISPR-Cas activity, or (ii) attributable to errors in the input DNA sequence. To distinguish between canonical and non-canonical archaeal tRNA genes, we recommend using a combination of automated pseudogene detection by tRNAscan-SE and the tRNAscan-SE isotype score, greatly reducing manual annotation efforts and leading to improved predictions of tRNA gene sets in Archaea.</p> <p> </p> <p><strong>Repository contents</strong></p> <p><strong>01_workflow_tRNAscanSE_predictions_210archaea.html </strong>contains the workflow and graphical output for tRNA gene set predictions in 20 Thermococcaceae genomes and 210 archaeal genomes. Files 03 to 06 below are the files quoted in this workflow.</p> <p><strong>02_workflow_tRNAscanSE_predictions_210archaea.Rmd </strong>contains the markdown file associated with 01_workflow_tRNAscanSE_predictions_210archaea.html above.</p> <p><strong>03_thermo_trnas_GtRNAdb.txt</strong><strong> </strong>contains the predicted tRNA gene sets of 20 Thermococcaceae genomes as listed on GtRNAdb (Data Release 19 (June 2021)).</p> <p><strong>04_Archaea_genome_list.txt </strong>contains the details of all 217 archaeal genomes listed on GtRNAdb (Data Release 19 (June 2021)). The seven genomes for which the NCBI genome sequences were no longer available are indicated by #### preceding the name.</p> <p><strong>05_thermo_tRNAs_genome.txt</strong><strong> </strong>contains the predicted tRNA gene sets of 20 Thermococcaceae genomes as predicted by locally run tRNAscan-SE (version 2.0.6), with standard settings for Archaea (option -A). To display the output, options -H and --detail were added. We note that pseudogene detection is active under these conditions.</p> <p><strong>06_Archaea_210_GtRNAdb_tRNAs.txt </strong>contains the predicted tRNA gene sets of the 210 archaeal genomes as listed on GtRNAdb (Data Release 19 (June 2021)).</p> <p><strong>07_Archaea_210genomes_tRNAs.txt</strong> contains the predicted tRNA gene sets of the 210 archaeal genomes as predicted by locally run tRNAscan-SE (version 2.0.6), with standard settings for Archaea (option -A). To display the output, options -H and --detail were added. We note that pseudogene detection is active under these conditions.</p> <p><strong>08_NCBI_genomes.zip</strong> contains the NCBI GenBank genome sequence files used in this study. These include the 20 Thermococcaceae genomes, the wider 210 archaeal genomes, and several others of interest. </p> <p><strong>09_phylogeny.tar.zip</strong> contains the data used to draw a phylogenetic tree for the 20 Thermococcaceae organisms. The folder includes a file listing the details of all data in the folder (Readme.md), a workflow file (workflow_UndinMarkers_v2.md), and data folders.</p> <p> </p> <p><strong>Notes</strong></p> <p>The extended TIGRFAM database referred to in the phylogenetic tree construction process can be found at <a href="https://zenodo.org/record/3839790#.YjByaVzMI3g">https://zenodo.org/record/3839790#.YjByaVzMI3g</a></p> <p>The perl script used during phylogenetic tree construction, catfasta2phyml.pl, is available in the GitHub repository <a href="https://github.com/nylander/catfasta2phyml">https://github.com/nylander/catfasta2phyml</a></p> <p>tRNAscan-SE is a freely available resource available online (<a href="http://lowelab.ucsc.edu/tRNAscan-SE/">http://lowelab.ucsc.edu/tRNAscan-SE/</a>)</p> <p>GtRNAdb is a publicly accessible resource available online (<a href="http://gtrnadb.ucsc.edu/">http://gtrnadb.ucsc.edu/</a>)</p> <p>NCBI is a publicly accessible resource available online (<a href="https://www.ncbi.nlm.nih.gov/">https://www.ncbi.nlm.nih.gov/</a>)</p> <p>rrnDB is a publicly accessible resource available online (<a href="https://rrndb.umms.med.umich.edu/">https://rrndb.umms.med.umich.edu/</a>)</p> <p>BLAST is a publicly accessible resource available online (<a href="https://blast.ncbi.nlm.nih.gov/Blast.cgi">https://blast.ncbi.nlm.nih.gov/Blast.cgi</a>)</p>
Dataset for: Owner-ascribed personality profiles distinguish domestic cats that capture and bring home wild animal prey
<p>Dataset allowing repetition of the analyses in the above paper, comprising personality scores and predation data, with details of cat characteristics. See readme.txt file.</p>
Optimising multispectral active fluorescence to distinguish the photosynthetic variability of cyanobacteria and algae
<p>Dataset underlying the following paper:</p> <p>Courtecuisse, E.; Marchetti, E.; Oxborough, K.; Hunter, P.D.; Spyrakos, E.; Tilstone, G.H.; Simis, S.G.H. Optimising Multispectral <br> Active Fluorescence to Distinguish the Photosynthetic Variability of Cyanobacteria and Algae. Sensors 2023, 23</p> <p>This study assesses the ability of a new active fluorometer, the LabSTAF, to diagnostically assess the physiology of freshwater cyanobacteria in a reservoir exhibiting annual blooms. Specifically, we analyse the correlation of relative cyanobacteria abundance with photosynthetic parameters derived from fluorescence light curves (FLCs) obtained using several combinations of excitation wavebands, photosystem II (PSII) excitation spectra and the emission ratio of 730 over 685 nm (Fo(730/685)) using obtained with excitation protocols with varying degrees of sensitivity to cyanobacteria and algae. FLCs captured obtained with blue excitation (B) and green–orange–red (GOR) excitation wavebands capture physiology parameters of algae and cyanobacteria, respectively. The green–orange (GO) protocol, expected to have the best diagnostic properties for cyanobacteria, did not guarantee PSII saturation. PSII excitation spectra showed distinct response from cyanobacteria and algae, depending on spectral optimisation of the light dose. Fo(730/685), obtained using a combination of GOR excitation wavebands, Fo(GOR, 730/685), showed a significant correlation with the relative abundance of cyanobacteria (linear regression, p-value < 0.01, adjusted R2 = 0.42). We recommend using, in parallel, Fo(GOR, 730/685), PSII excitation spectra (appropriately optimised for cyanobacteria versus algae), and physiological parameters derived from the FLCs obtained with GOR and B protocols to assess the physiology of cyanobacteria and to ultimately predict their growth. Higher intensity LEDs (G and O) should be considered to reach PSII saturation to further increase diagnostic sensitivity to the cyanobacteria component of the community.</p>
Branching patterns in phylogenies cannot distinguish diversity-dependent diversification from time-dependent diversification
One of the primary goals of macroevolutionary biology has been to explain general trends in long-term diversity patterns, including whether such patterns correspond to an up-scaling of processes occurring at lower scales. Reconstructed phylogenies often show decelerated lineage accumulation over time. This pattern has often been interpreted as the result of diversity-dependent diversification, where the accumulation of species causes diversification to decrease through niche filling. However, other processes can also produce such a slowdown, including time-dependence without diversity-dependence. To test whether phylogenetic branching patterns can be used to distinguish these two mechanisms, we formulated a time-dependent, but diversity-independent model that matches the expected diversity through time of a diversity-dependent model. We simulated phylogenies under each model and studied how well likelihood methods could recover the true diversification mode. Standard model selection criteria always recovered diversity-dependence, even when it was not present. We correct for this bias by using a bootstrap method and find that neither model is decisively supported. This implies that the branching pattern of reconstructed trees contains insufficient information to detect the presence or absence of diversity-dependence. We advocate that tests encompassing additional data, e.g., traits or range distributions, are needed to evaluate how diversity drives macroevolutionary trends.
Data from: Adaptive genetic variation distinguishes Chilean blue mussels (Mytilus chilensis) from different marine environments
Chilean mussel populations have been thought to be panmictic with limited genetic structure. Genotyping-by-sequencing approaches have enabled investigation of genome-wide variation that may better distinguish populations that have evolved in different environments. We investigated neutral and adaptive genetic variation in Mytilus from six locations in southern Chile with 1,240 SNP obtained with RAD-seq. Differentiation among locations with 891 neutral SNPs was low (FST = 0.005). Higher differentiation was obtained with a panel of 58 putative outlier SNPs (FST = 0.114) indicating the potential for local adaptation. This panel identified clusters of genetically related individuals and demonstrated that much of the differentiation (~92%) could be attributed to the three major regions and environments: extreme conditions in Patagonia, inner bay influenced by aquaculture (Reloncaví́), and outer bay (Chiloé Island). Patagonia samples were most distinct, but additional analysis carried out excluding this collection also revealed adaptive divergence between inner and outer bay samples. The four locations within Reloncaví́ area were most similar with all panels of markers, likely due to similar environments, high gene flow by aquaculture practices and low geographic distance. However, fine scale structure could be detected when analyses included only this zone. Our results and the SNP markers developed will be a powerful tool supporting management and programs of this harvested species.
Dataset to accompany publication "Distinguishing Inner and Outer-Sphere Hot Electron Transfer in Au/p-GaN Photocathodes"
<p>This dataset accompanies the publication "Distinguishing Inner and Outer-Sphere Hot Electron Transfer in Au/p-GaN Photocathodes" published in Nano Letters. The data can be used to reproduce the original plots in figures 2-4 in the main text and all original plots in figures S1-S13 in the supporting information. All files are in .xlsx and easily readable. <br>The abstract for the associated paper is as follows:<br>Exploring nonequilibrium hot carriers from plasmonic metal nanostructures is a dynamic field in optoelectronics, with applications including photochemical reactions for solar fuel generation. The hot carrier injection mechanism and the reaction rate are highly impacted by the metal/molecule interaction. However, determining the primary type of the reaction and thus the injection mechanism of hot carriers has remained elusive. In this work, we reveal an electron injection mechanism deviating from a purely outer-sphere process for the reduction of ferricyanide redox molecule in a gold/p-type gallium nitride (Au/p-GaN) photocathode system. Combining our experimental approach with ab-initio simulations, we discover that an efficient inner-sphere transfer of low-energy electrons leads to an enhancement in the photocathode device performance in the interband regime. These findings provide important mechanistic insights, showing our methodology as a powerful tool for analyzing and engineering hot-carrier-driven processes in plasmonic photocatalytic systems and optoelectronic devices.</p>
Distinguishing cophylogenetic signal from phylogenetic congruence clarifies the interplay between evolutionary history and species interactions
<p>Interspecific interactions, including host-symbiont associations, can profoundly affect the evolution of the interacting species. Given the phylogenies of host and symbiont clades and knowledge of which host species interact with which symbiont, two questions are often asked: "Do closely related hosts interact with closely related symbionts?" and "Do host and symbiont phylogenies mirror one another?". These questions are intertwined and can even collapse under specific situations, such that they are often confused one with the other. However, in most situations, a positive answer to the first question, hereafter referred to as "cophylogenetic signal", does not imply a close match between the host and symbiont phylogenies. It suggests only that past evolutionary history has contributed to shaping present-day interactions, which can arise, for example, through present-day trait matching, or from a single ancient vicariance event that increases the probability that closely related species overlap geographically. A positive answer to the second, referred to as "phylogenetic congruence", is more restrictive as it suggests a close match between the two phylogenies, which may happen, for example, if symbiont diversification tracks host diversification or if the diversifications of the two clades were subject to the same succession of vicariance events. Here we apply a set of methods (ParaFit, PACo, and eMPRess), which significance is often interpreted as evidence for phylogenetic congruence, to simulations under three biologically realistic scenarios of trait matching, a single ancient vicariance event, and phylogenetic tracking. The latter is the only scenario that generates phylogenetic congruence, whereas the first two generate a cophylogenetic signal in the absence of phylogenetic congruence. We find that tests of global-fit methods (ParaFit and PACo) are significant under the three scenarios, whereas tests of event-based methods (eMPRess) are only significant under the scenario of phylogenetic tracking. Therefore, significant results from global-fit methods should be interpreted in terms of cophylogenetic signal and not phylogenetic congruence; such significant results can arise under scenarios when hosts and symbionts had independent evolutionary histories. Conversely, significant results from event-based methods suggest a strong form of dependency between hosts and symbionts evolutionary histories. Clarifying the patterns detected by different cophylogenetic methods is key to understanding how interspecific interactions shape and are shaped by evolution.</p>
A multilabel dataset for distinguishing Bosnian, Croatian, Montenegrin, and Serbian
<p>This dataset contains files used in the VarDial 2024 Shared Task on Distinguishing Between Similar Languages - Multiple Labels for the Bosnian - Croatian - Montenegrin - Serbian (BCMS) subtask.</p> <p>The starting point for this dataset is the one published by Rupnik et al. (2023). It contains geolocated data from the BCMS linguistic area collected from Twitter (rebranded as X).<br>Each instance contains the full tweet production of a single user, which was manually annotated for the user's country.<br>The original annotation was single-label, and it was produced by a single annotator. In the version of the data produced here, the test and dev sets were reannotated by multiple annotators, in a multi-label setting. For the details on the reannotation process, please see Miletić and Miletić (2024). We have also excluded retweets from the original data, as these represent reproduced content from a different user account and may not be representative of the language use of the user themselves.</p> <p>For details on the shared task, we refer you to Chifu et al. (2024).</p>
Distinguishing GUI Component States for Blind Users using Large Language Models
<p><strong># Data Code Repository</strong></p><p> </p><p>This repository contains open-source data code that provides utilities for the paper named "Here comes trouble! Distinguishing GUI Component States for Blind Users using Large Language Models". The code is designed to facilitate data-related tasks and promote reproducibility in research and data analysis projects.</p><p> </p><p><strong>## Features</strong></p><p> </p><p>- Attribute identification and extraction: Including real-time recognition and extraction of GUI components in the view type, resource-id, color, action of four attributes</p><p>- Components State Distinction: Provides the prompt needed for large language models, covering their specific design schemes and chain of thought reasoning processes as well as contextual learning content.</p><p>- Implementation: Offers specific methods to realize the process, including the setting of relevant parameters and the use of functions.</p><p> </p><p><strong>## Installation</strong></p><p> </p><p>To use the data code, you can down or clone the required code.</p><p>Notably, before using the code, make sure the necessary environment configuration is done.</p><p> </p><p><strong>## Dependencies</strong></p><p>The data code has the following dependencies:</p><p> </p><p>Python (version 3.6 or higher)</p><p>NumPy</p><p>Pandas</p><p>Seaborn</p><p>Scikit-learn</p><p>Openai</p><p>Android Studio (version 4.0)</p><p> </p><p>Install the required dependencies using pip:</p><p>pip install numpy..</p><p> </p><p><strong>##License</strong></p><p>This data code is distributed under the MIT License. See LICENSE for more information.</p><p> </p><p><strong>##Copyright</strong></p><p>All copyright of the tool is owned by the author of the paper.</p>
Figs 9–20. Characters distinguishing Nemesia arboricola Pocock, 1903 from N. macrocephala Ausserer, 1871. 9–14. N in The Nemesia trapdoor spider fauna of the Maltese archipelago, with the description of two new species (Araneae, Mygalomorphae, Nemesiidae)
Figs 9–20. Characters distinguishing Nemesia arboricola Pocock, 1903 from N. macrocephala Ausserer, 1871. 9–14. N. arboricola; represented by two specimens (TC.016, NHMR, Figs 9, 11, 13, specimen collected from an arboreal-nest; TC.017, NHMR, Figs 10, 12, 14, specimen collected from a terrestrial nest). 15–20. N. macrocephala; represented by two specimens (Isaia.046; Figs 15, 17, 19 and Isaia.047; Figs 16, 18, 20), both collected from terrestrial nests near the type locality, Palermo, Sicily. 9–10, 15–16. Presence or absence of labial cuspules. Note presence of labial cuspules (cu) in N. arboricola (Figs 9–10) versus absence of labial cuspules in N. macrocephala (Figs 15–16). 11–12, 17–18. Colour pattern opisthosoma. Note dark coloured and speckled opisthosoma in N. arboricola (Figs 11–12) versus light coloured ophistosoma with chevron lines (Figs 17–18) in N. macrocephala. 13–14, 19– 20. Differences in structure of PMS. Note thickened and slightly swollen PMS (is) in N. arboricola (Figs 13–14) versus slender, conical PMS (cs) in N. macrocephala (Figs 19–20). Scale bars = 1 mm.
Text-fig. 2. CT slices on Block 2. Details of other skeletal parts (a). The familiar shape of an ammonite (a, c). Holes, cracks and empty cavities in both the limestone matrix and within the vertebrate fossil (b, c). Heterogeneity of the 'tuffeau' limestone, the more porous areas of the matrix clearly distinguishable from the more compact ones (c). Ferric nodules (c). in Hidden Treasures Uncovered: Successful Detection Of Fossils Below The Surface In Large Limestone Blocks Using A Standard Medical X-Ray Ct Scanner
Text-fig. 2. CT slices on Block 2. Details of other skeletal parts (a). The familiar shape of an ammonite (a, c). Holes, cracks and empty cavities in both the limestone matrix and within the vertebrate fossil (b, c). Heterogeneity of the 'tuffeau' limestone, the more porous areas of the matrix clearly distinguishable from the more compact ones (c). Ferric nodules (c).
FIGURE 6. A in Distinguishing between three modern Ellobius species (Rodentia, Mammalia) and identification of fossil Ellobius from Kaldar Cave (Iran) using geometric morphometric analyses of the first lower molar
FIGURE 6. A) First two PCs from the Principal component analysis performed on the size and shape including the reference collection and Kaldar Cave material. B) Boxplot of the total length of Ellobius from the extant reference collections and Kaldar Cave.
FIGURE 4. Ellobius right lower m1. A in Distinguishing between three modern Ellobius species (Rodentia, Mammalia) and identification of fossil Ellobius from Kaldar Cave (Iran) using geometric morphometric analyses of the first lower molar
FIGURE 4. Ellobius right lower m1. A) 14 landmarks: Landmarks on the outermost turning point of buccal (2, 4, 6) and lingual (8, 10, 12, 14) salient angles, and on the innermost turning point of buccal (3, 5) and lingual (9, 11, 13) reentrant angle. B) 60 semi-landmarks on the anterior cap.
FIGURE 2. Ellobius lower m1s in Distinguishing between three modern Ellobius species (Rodentia, Mammalia) and identification of fossil Ellobius from Kaldar Cave (Iran) using geometric morphometric analyses of the first lower molar
FIGURE 2. Ellobius lower m1s (all figured as right ones) from the extant reference collections and Kaldar Cave. A) Ellobius fuscocapillus: A.1-Kaldar Cave, 2014/4/SL5II/E6/125-130, right lower m1, number 157. A.2-Kaldar Cave, 2014/4/SL5/E5/109-111, right lower m1, number 520. A.3-Kaldar Cave, 2014/5/SL7II/E7/170-180, right lower m1, number 104. A.4- Kaldar Cave, 2014/5/SL7II/F6/135-145, right lower m1, number 547.A.5-modern, NHM86101513, Afghanistan, right lower m1. A.6-modern, FM111846, Iran, right lower m1. A.7-modern, NHM86101512, Afghanistan, right lower m1; B) Ellobius lutescens: B.1-Kaldar Cave, 2014/5/SL7II/F6/130-140, right lower m1, number 319. B.2- Kaldar Cave, 2014/4/SL5II/F7/115-118, right lower m1, number 90. B.3- Kaldar Cave, 2014/4/SL5II/F7/115-118, right lower m1, number 91. B.4- Kaldar Cave, 2014/5/SL7II/E7/145-150, right lower m1, number 436. B.5-modern, NMH916416, Turkey, right lower m1. B.6-modern, NMH916414, Turkey, right lower m1. B.7-modern, NMH916412, Turkey, right lower m1; C) Ellobius talpinus: C.1-modern, NHM3421126, Russia, right lower m1. C.2-modern, FM103163, Afghanistan, right lower m1. C.3-modern, AMNH59797, Mongolia, right lower m1. Scale 1 mm.
FIGURE 1. A in Distinguishing between three modern Ellobius species (Rodentia, Mammalia) and identification of fossil Ellobius from Kaldar Cave (Iran) using geometric morphometric analyses of the first lower molar
FIGURE 1. A) Occlusal surface of Ellobius right lower m1: triangle (T); buccal re-entrant angle (BRA); lingual reentrant angle (LRA); anterior cap (AC); posterior lobe (PL); B) Lingual view of left lower m1.
FIGURE 5 in Distinguishing between three modern Ellobius species (Rodentia, Mammalia) and identification of fossil Ellobius from Kaldar Cave (Iran) using geometric morphometric analyses of the first lower molar
FIGURE 5. Principal component analysis on the normalized landmarks and sliding semilandmarks and shape configuration at the extreme ends of the two first PCs.
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.