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3,225 results for “Case studies”
Fig. 4 in Altai Mountains - cradle of hybrids and introgressants: A case study in Veronica subg. Pseudolysimachium (Plantaginaceae)
Fig. 4. STRUCTURE results showing the probability of ancestry of each individual (horizontal axis) to each of K = 2 populations (vertical axis) in all the five scenarios. A, Veronica spicata × V. pinnata; B, V. incana and V. longifolia; C, V. longifolia and V. porphyriana; D & E, V. pinnata and V. porphyriana involving putative hybrids of V. ×schmakovii and V. ×sessiliflora. Details of the exact posterior probabilities of each putative hybrid individual and their corresponding parents are given in suppl. Table S3.
Fate and detectability of rare gas hydride ions in nova ejecta: A case study with nova templates
<p>The electron-impact HeH+ rovibrational data at temperatures up to 20,000 K used in the paper: "Fate and detectability of rare gas hydride ions in Novae ejecta: A case study with Nova templates".</p>
Interim Data and Results for Case Study: Funding rules that promote equity in climate adaptation outcomes
<p>Interim exposure data and results for the published case study. External raw data is available <a href="https://zenodo.org/records/14260630">here</a> and the remaining raw data is generated via code. This is too large to share on Zenodo. There are stochastic aspects in going from raw exposure to interim exposure data and interim exposure data to results, which is why we make the specific interim exposure data and results of the published study available here. Other interim data is not stochastic and can be reproduced following the code reproduction instructions (see https://github.com/abpoll/j40_gc). Please see the underlying study for more details about the methods. The data here can be generally reproduced (not bit-wise) following the code and instructions at this repository: https://zenodo.org/records/14261361.</p> <p> </p> <p>The interim exposure data is named "exp" and the results data is named "results."</p>
Model output from 'Modelling the circular economy potential of micromobility: A Finnish case study for e-scooters and e-bikes'
<p>These two files include the results for e-scooters and e-bikes. The dynamics of the BAU scenario is shown in the first few columns, then follow the sensitivity analyses. The column names should be self-explanatory, subject to reading the paper.</p>
How to render species comparable taxonomic units through deep time: A case study on intraspecific osteological variability in extant and extinct lacertid lizards
<p>Generally, the species is considered to be the only naturally occurring taxon. However, species recognized and defined using different species delimitation criteria cannot readily be compared, impacting studies of biodiversity through Deep Time. This comparability issue is particularly marked when comparing extant with extinct species because the only available data for species delimitation in fossils are derived from their preserved morphology, which is generally restricted to osteology in vertebrates. Here, we quantify intraspecific, intrageneric, and intergeneric osteological variability in extant species of lacertid lizards using pairwise dissimilarity scores based on a data set of 253 discrete osteological characters for 99 specimens referred to 24 species. Variability is always significantly lower intraspecifically than between individuals belonging to distinct species of a single genus, which is in turn significantly lower than intergeneric variability. Average values of intraspecific variability and associated standard deviations are consistent (with few exceptions), with an overall average within a species of 0.208 changes per character scored. Application of the same methods to six extinct lacertid species (represented by 40 fossil specimens) revealed that intraspecific osteological variability is inconsistent, which can at least in part be attributed to different researchers having unequal expectations of the skeletal dissimilarity within species units. Such a divergent interpretation of intraspecific and interspecific variability among extant and extinct species reinforces the incomparability of the species unit. Lacertidae is an example where extant species recognized and defined based on a number of delimitation criteria show comparable and consistent intraspecific osteological variability. Here, as well as in equivalent cases, application of those skeletal dissimilarity values to paleontological species delimitation potentially provides a way to ameliorate inconsistencies created by the use of morphology to define species.</p>
Supplementary datasets, data analysis code, and R tutorials for: Phylogenetic analysis of adaptation in comparative physiology and biomechanics: overview and a case study of thermal physiology in treefrogs
<p>Comparative phylogenetic studies of adaptation are uncommon in biomechanics and physiology. Such studies require collecting data from many species, a challenge when data collection is experimentally intensive. Moreover, researchers struggle to employ the most biologically appropriate phylogenetic tools for identifying adaptive evolution. Here, we detail an established but greatly underutilized phylogenetic comparative framework—the Ornstein-Uhlenbeck process—that explicitly models long-term adaptation. We discuss challenges in implementing and interpreting the model, and we outline potential solutions. We demonstrate use of the model through studying the evolution of thermal physiology in treefrogs. Frogs of the family Hylidae have twice colonized the temperate zone from the tropics, and such colonization likely involved a fundamental change in physiology due to colder and more seasonal temperatures. However, which traits changed to allow colonization is unclear. We measured cold-temperature tolerance and characterized thermal performance curves in jumping for twelve species of treefrogs distributed from the Neotropics to temperate North America. We then conducted phylogenetic comparative analyses to examine how tolerances and performance curves evolved and to test whether that evolution was adaptive. We found that tolerance to low temperatures increased with the transition to the temperate zone. In contrast, jumping well at colder temperatures was unrelated to biogeography and thus did not adapt during dispersal. Overall, our paper shows how comparative phylogenetic methods can be leveraged in biomechanics and physiology to test the evolutionary drivers of variation among species.</p>
DATA SET OF EXISTING AND ONGOING CASE STUDIES IN THE ARTS 2008-2020
<p>PURPOSE: D2.1, Data Set of Case Studies in the Arts 2008-2020 fulfils the following purposes:<br> 1. Build a research database for past and ongoing good practices in the field of arts-based social interventions in AMASS partner countries.<br> 2. Construct a solid foundation for the development of new interventions with similar objectives.<br> 3. To avoid obstacles that made many previous efforts in this field unsustainable and unadaptable.<br> 4. To offer a valid and authentic knowledge repository for policy makers, developers of future projects and researchers to identify motivations, philosophies, modes of engagement and impact of arts-based social interventions.</p>
In-depth analysis of 18 case studies on state-of-the-art of cultural tourism interventions
<p>The aim of Work Package 3 of the SmartCulTour project (<a href="http://www.smartcultour.eu">www.smartcultour.eu</a>) is to provide a state-of-the-art overview of cultural tourism interventions implemented in European cities and regions, thereby identifying best practices and the impacts and success conditions of cultural tourism interventions. Based on the previous, desk-researched 107 interesting cultural tourism interventions see "Desk research of 107 case studies on state-of-the-art of cultural tourism interventions", DOI: 10.5281/zenodo.5213017 ), a further 18 interventions were selected for in-depth analysis.</p> <p>These 18 cultural tourism interventions were analyzed via a series of expert interviews, combined with document and literature analysis, performed in the period January 2021-March 2021. Description of the case studies follows a standardized <strong>case study data collection form</strong>. This form is included here as "Case study data collection form". The form collect data on:</p> <ul> <li>Context and background information;</li> <li>The 'reason why' of the intervention;</li> <li>The intervention;</li> <li>Resources and tools necessary to design and implement the interventions;</li> <li>Impacts (expected, perceived and measured);</li> <li>(Perceived) success conditions and limiting factors.</li> </ul> <p>The semi-structured interviews left some room for adaptability depending on the case studies. A <strong>general guide on potential interview questions</strong> is included here as "Potential questions list for case study interviews".</p> <p>All case studies are included as individual odt-files, starting with "detailed case study + name of the intervention".</p>
Classification of blood cells dynamics with convolutional and recurrent neural networks: a sickle cell disease case study
<p>The fraction of red blood cells (RBC) adopting a specific motion under low shear flow is a promising inexpensive marker for monitoring the clinical status of patients with sickle cell disease (SCD). Its high-throughput measurement relies on the video analysis of thousands of cell motions for each blood sample to eliminate a large majority of unreliable samples(out of focus or overlapping cells) and discriminate between tank-treading and flipping motion, characterizing highly and poorly deformable cells respectively. These videos are of different durations (from 6 to more than 100 frames).</p> <p>This dataset contains four adult patients with SCD. They were enrolled in the study Drepaforme (approved by the institutional review board CPP Ouest 6 under the reference n°2018A00679-46) and were sampled weekly for several months. The movies were processed using in-house routines in Matlab (Matlab, R2016a) and RBC were detected individually and tracked over time. The database provided in this repository are already pre-processed sequences of tracked and centered RBC over time, each time step image being normalized to 31x31 pixels. Within the 32 experiments, the total number of sequences (or samples) is nearly 150 000. All sequences were semi-automatically labelled into 3 classes, depending on the dynamic of the cell: tank-treading, flipping and unreliable (140 000 are unreliable). The percentage of tank-treading cells with respect to all reliable cells (tank-treading+flipping) in every experiment is the final goal of this study.</p> <p>This dataset is very interesting to the community as it is a large database for cell dynamics classification: the class depends on the movement of the cell.</p> <p>An automatic processing of the database using a 2-stage deep learning model is available here https://github.com/icannos/redbloodcells_disease_classification</p> <p>For opening the data in python:</p> <p> from scipy.io import loadmat<br> x=loadmat('BG20191003shear10s01_Export.mat')</p> <p> * x['Norm_Tab'] is of size nb_samples x max_len_sequences x 31 x 31, where max_len_sequences is the length of the longest sequence of the series, typically ~150 to 180. The other sequences are padded with 31x31 zero matrices at the end in order to fill this maximal length.</p> <p> * x['Labels_Num'] is the corresponding label of each sequence, of size nb_samples. Label can be:<br> - 0 : "tank-treading" (or healthy)<br> - 1 : "flipping" (or tumbling, i.e. related to a SCD)<br> - 2 : "unreliable"</p>
FIG. 11. — A-C in Bryozoan faunas at the Tortonian-Messinian transition. A palaeoenvironmental case study from Crete Island, eastern Mediterranean
FIG. 11. — A-C, Bryocryptella torquata (Jullien, 1903); A, colony fragment, frontal view, POTB13: AMPG(IV) 2815a; B, colony fragment, dorsal view, POTB13: AMPG(IV) 2815b; C, detail view of zooids, FAN31: AMPG(IV) 3500a; D, Tessaradoma boreale (Busk, 1860), colony fragment, FAN28: AMPG(IV) 3613. E-F, Kionidella excelsa Koschinsky, 1885; E, colony fragment, basal view, FAN7: AMPG(IV)3570a; F, frontal view of a few zooids, FAN16: AMPG(IV) 3572. Scale bars: A, 500 µm; B, E, 200 µm; C, F, 100 µm; D, 1 mm.
FIG. 9. — A, B in Bryozoan faunas at the Tortonian-Messinian transition. A palaeoenvironmental case study from Crete Island, eastern Mediterranean
FIG. 9. — A, B, Cupuladria cf. canariensis (Busk, 1859); A, frontal view of a whole colony, KER39: AMPG(IV) 3078a; B, dorsal view of a whole colony, KER39: AMPG(IV) 3078b; C, D, Discoporella reussiana (Manzoni, 1869); C, frontal view of a whole colony, KER30: AMPG(IV) 3102; D, dorsal view of a whole colony, KER30: AMPG(IV) 3101; E, Nellia tenella (Lamarck, 1816), detail of an internode showing two zooids in frontal view, KER17: AMPG(IV) 3150a; F-H, Canda rectangulata Udin, 1964; F, dorsal view of an internode fragment, FAN35: AMPG(IV) 3506a; G, frontal view of an internode fragment, FAN35: AMPG(IV) 3506b; H, Detail of the same fragment, FAN35: AMPG(IV) 3506b. Scale bars: A-D, 1 mm; E, H, 100 µm; F-G, 200 µm.
FIG. 8. — A-C in Bryozoan faunas at the Tortonian-Messinian transition. A palaeoenvironmental case study from Crete Island, eastern Mediterranean
FIG. 8. — A-C, Crisia aculeata Hassall, 1841; A, internode, frontal view, POTB13: AMPG(IV) 2828a; B, internode, dorsal view, POTB13 2828b: AMPG(IV); C, internode with gonozooid, KAP22: AMPG(IV) 3339. D-F, Crisia denticulata (Lamarck, 1816); D, internode, frontal view, POTB13: AMPG(IV) 2829a; E, internode dorsal view, POTB13: AMPG(IV) 2829b; F, gonozooid, POTB13: AMPG(IV) 2829c. Scale bars: A, 500 µm; B-F, 200 µm.
FIG. 6 in Bryozoan faunas at the Tortonian-Messinian transition. A palaeoenvironmental case study from Crete Island, eastern Mediterranean
FIG. 6. — Theoretical zonation in a transect from coastal to upper bathyal palaeoenvironments following Pérès & Picard (1964). This bionomic depth zonation illustrates the situation on flat muddy bottoms in areas with very clear waters, like in the oligotrophic (eastern) Mediterranean Sea. The distribution of bryozoan growth-form assemblages (in average number of fragments per sample) and the average number of species in each assemblage is indicated in a grey circle (partly inspired from Moissette 2000).
FIG. 1. — A in Bryozoan faunas at the Tortonian-Messinian transition. A palaeoenvironmental case study from Crete Island, eastern Mediterranean
FIG. 1. — A, Situation map of Crete within the eastern Mediterranean; B, geological sketch map of the island of Crete (after Krijgsman et al. 1994), with location of the studied sections.
FIG. 7. — A, B in Bryozoan faunas at the Tortonian-Messinian transition. A palaeoenvironmental case study from Crete Island, eastern Mediterranean
FIG. 7. — A, B, Anguisia verrucosa Jullien, 1882; A, bifurcating branch, FAN36: AMPG(IV) 3471; B, encrusting base (left) and erect peristome of the encrusting proximal zooid of a running branch (right), FAN35: AMPG(IV) 3470; C, D, Exidmonea atlantica (Forbes in Johnston, 1847); C, fragment of a branch, frontal view (with a gonozooid on the left upper part), POTB13: AMPG(IV) 2853a; D, fragment of a branch, dorsal view, POTB13: AMPG(IV) 2853b; E-G, Ybselosoecia typica (Manzoni, 1878); E, fragment of a branch (with a large gonozooid), frontal view, POTB13: AMPG(IV) 2881a; F, detail of the ooeciostome of another gonozooid, POTB13: AMPG(IV) 2881b; G, fragment of a branch, dorsal view, POTB13: AMPG(IV) 2881c. Scale bars: A, D, 200 µm; B, G, 100 µm; C-E, 500 µm.
FIG. 2 in Bryozoan faunas at the Tortonian-Messinian transition. A palaeoenvironmental case study from Crete Island, eastern Mediterranean
FIG. 2. — Schematic sedimentary log of Potamida composite section with sample location and semi-quantitative abundances of bryozoan species.
FIG. 10. — A-C in Bryozoan faunas at the Tortonian-Messinian transition. A palaeoenvironmental case study from Crete Island, eastern Mediterranean
FIG. 10. — A-C, Scrupocellaria cf. elliptica (Reuss, 1847); A, view of some zooids showing opesia with 4 spine bases on the outer distal part and 3 spine bases + 1 scutal spine on the inner distal rim, FAN36: AMPG(IV) 3587; B, zooids with 7 spine bases and the scutum, FAN35: AMPG(IV) 3586a; C, dorsal surface of a colony fragment with small vibracularia and radicular pores, FAN35: AMPG(IV) 3586b; D, E, Scrupocellaria scrupea Busk, 1852; D, ovicellate colony fragment, FAN35: AMPG(IV) 3590a; E, detail frontal view showing opesia with five spine bases, FAN35: AMPG(IV) 3590b; F-H, Cellaria salicornioides Lamouroux, 1816; F, part of a slender internode, FAN18: AMPG(IV) 3513a; G, detail view showing denticles and endotoichal ovicells, POTB13: AMPG(IV) 2821a; H, avicularia in frontal and lateral view (arrow), POTB13: AMPG(IV) 2821b; I, Gemellipora eburnea Smitt, 1873, broken internode showing two zooids with two oval scars separated by a thin interzooidal groove, CAP032: AMPG(IV) 3426. Scale bars: A-E, G, I, 100 µm; F, H, 200 µm.
FIG. 12. — A-G in Bryozoan faunas at the Tortonian-Messinian transition. A palaeoenvironmental case study from Crete Island, eastern Mediterranean
FIG. 12. — A-G, Batopora rosula (Reuss, 1847); A, colony, basal-lateral view (arrow indicates the scar of an ovicellate zooid), FAN7: AMPG(IV) 3475a; B, colony, apical view, FAN7: AMPG(IV) 3475b; C, colony, lateral-apical view, FAN7: AMPG(IV) 3475c; D-G, juvenile forms (G, basal view), FAN18: AMPG(IV)a-d; H-I, Orbitulipora excentrica Seguenza, 1880; H, whole colony, FAN22: AMPG(IV) 3580a; I, detail view of the left part of the same colony (arrows indicate ovicellate zooids), FAN22: AMPG(IV) 3580a. Scale bars: H, 500 µm; A-C, I, 200 µm; D-G, 100 µm.
FIG. 5 in Bryozoan faunas at the Tortonian-Messinian transition. A palaeoenvironmental case study from Crete Island, eastern Mediterranean
FIG. 5. — Schematic sedimentary log of Faneromeni section with sample location and semi-quantitative abundances of bryozoan species.
FIG. 3 in Bryozoan faunas at the Tortonian-Messinian transition. A palaeoenvironmental case study from Crete Island, eastern Mediterranean
FIG. 3. — Schematic sedimentary log of Keramoutsi section with sample location and semi-quantitative abundances of bryozoan species.
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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.