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Data and R-code on a cross-sectional study of factors associated with lameness in dairy cows housed in freestall and compost-bedded pack dairy farms in southern Brazil
<p>The data correspond to a cross-sectional study designed to investigate factors associated with lameness in dairy cows on intensive farms in southern Brazil.<br> Farms: 38 freestall and 12 compost-bedded pack visited once in 2016. All lactating cows (n = 13,716) were examined and body condition score (BCS) and gait score were assessed. Additionally, some variables were collected through inspection of facilities and using data from an interview with farmers on routine herd management practices.<br> Additional information is provided in the published paper ("Factors associated with lameness prevalence in lactating cows housed in freestall and compost-bedded pack dairy farms in southern Brazil" https://doi.org/10.1016/j.prevetmed.2019.104773)</p>
Figure 2. Cross-sections from A. danfordi phalanges. A in Age and growth in two populations of Danford's lizard, Anatololacerta danfordi (Günther, 1876), from the eastern Mediterranean
Figure 2. Cross-sections from A. danfordi phalanges. A) Female lizard with 3 hibernations and B) male lizard with 7 hibernations. e.b.: Endosteal bone, e.r.: endosteal resorption, m.c.: medullary cavity, p.: peripheral, white arrows: LAGs.
Data from: Cross-sectional personal network analysis of adult smoking in rural areas
<p>This data package, titled <em>Data from: Cross-sectional personal network analysis of adult smoking in rural areas,</em> includes several files. First, there are annonymized raw data files in .rds file format (ego_data.rds & alter_data.rds). Second, there is the R code that allow the replication of various statistical analyses. Interested parts may consult the R code as .pdf file format (Supplementary_Material_R_Code.pdf), .Rmd file format (that can be run to create the .pdf file format) and the .R file format (that can be accesed with R and RStudio). Moreover, the labels files are useful for recreating the Supplementary Material pdf file. </p> <p>Readers should know that this dataset corresponds to the study (paper) <em>Cross-sectional personal network analysis of adult smoking in rural areas. </em></p> <p>The ego_data.rds file includes 20 variables by 76 observations (respondents) while the alter_data.rds file includes 46 variables by 1681 observations (social contacts). We collected this information by deploying a personal network analysis research design. Initially, we interviewed 83 respondents (dubbed <em>egos</em>). Due to missing data, we kept in the analysis 76 egos and dropped seven respondents. We recruited the respondents using a link-tracining sampling framework. We started from a number of six seeds. We interviewed the seeds then we asked them to recommend other people in the study. We continued in a referee-referral fashion until 83 interviews were completed. The study was performed in a small rural Romanian community (4124 residents): Lerești (Argeș county). </p> <p>Our study was carried out in accordance with the recommendations, relevant guidelines, and regulations (specifically, those provided by the Romanian Sociologists Society, i.e., the professional association of Romanian sociologists). The research was performed in accordance with the Declaration of Helsinki. The research protocol was approved by a named institutional/licensing committee. Specifically, the Ethics Committee of the Center for Innovation in Medicine (InoMed) reviewed and approved all these study procedures (EC-INOMED Decision No. D001/09-06-2023 and No. D001/19-01-2024). All participants gave written informed consent. The privacy rights of the study participants were observed. The authors did not have access to information that could identify participants. Face-to-face interviews were collected between September 13 – 23, 2023, in Lerești, Romania. After each interview, information that could identity the participants were anonymized. Before conducting the interview, we provided each participant with a dossier containing informative materials about the project's objectives, how the data would be analyzed and reported, and their participation rights (e.g., the right to withdraw from the project at any time, even after the interview was completed). All study participants gave their written informed consent prior to enrolment in the study.</p> <p>The variables in the ego_data.rds file are as follows:</p> <p>(1) "networkCanvasEgoUUID" (unique alpha numeric code for each observation); </p> <p>(2) "ego_age" (the age of each study participant); </p> <p>(3) "ego_age.cen" (the age of each study participant, centered); </p> <p>(4) "ego_educ_b" (the education of each ego, binary); </p> <p>(5) "ego_educ_f" (the education of each ego, educational achievement); </p> <p>(6) "ego_marital.s_f" (the marital status of each ego);</p> <p>(7) "ego_occupation.cat2_f" (the occupation of each ego); </p> <p>(8) "ego_occupation_b" (the occupation of each ego, unemployed vs employed); </p> <p>(9) "ego_relstatus_b" (whether the ego is in a relationship or not); </p> <p>(10) "ego_sex_f" (the sex of the ego assigned at birth; male & female); </p> <p>(11) "ego_sex_n" (the sex of the ego assigned at birth; 0 = male & 1 = female); </p> <p>(12) "ego_smk_status_b1" (smoking status: 1 smoking, 0 others);</p> <p>(13) "ego_smk_status_b2" (smoking status: 1 former smoker, 0 others); </p> <p>(14) "ego_smk_status_b3" (smoking status: 1 not a smoker, 0 others); </p> <p>(15) "ego_smkstatus_f" (smoking status: former smoker, never-smoker, non-smoker (smoked too little), occasional smoker, smoker); </p> <p>(16) "ego_smoking_3cat" (smoking status: non-smoker, former smoker, smoker);</p> <p>(17) "net.size" (number of social contacts, alters, that were elicited by an ego);</p> <p>(18) "net.components" (number of strong components in the personal network);</p> <p>(19) "net.deg.centralization" (personal network degree centralization);</p> <p>(20) "net.density" (personal network density). </p> <p>The variables in the alter_data.rds file are as follows:</p> <p>(1) "alter_age" (the age of the alter); </p> <p>(2) "alter_age.cen" (the age of the alter - centered); </p> <p>(3) "alter_btw" (alter's betweenness score); </p> <p>(4) "alter_btw.cen" (alter's betweenness score - centered); </p> <p>(5) "alter_deg" (alter's degree score); </p> <p>(6) "alter_deg.cen" (alter's degree score - centered); </p> <p>(7) "alter_educ_b" (alter's education); </p> <p>(8) "alter_educ_f" (alter's education); </p> <p>(9) "alter_marital.s_f" (alter's marital status); </p> <p>(10) "alter_relstatus_b" (alter's marital status - binary variable);</p> <p>(11) "alter_sex_f" (alter's sex assigned at birth);</p> <p>(12) "alter_sex_n" (alter's sex assigned at birth; 1 - female; 0 - male); </p> <p>(13) "alter_smk_status_b1" (alter's smoking status; 1 smoker, 0 others);</p> <p>(14) "alter_smk_status_b2" (alter's smoking status; 1 former smoker, 0 others);</p> <p>(15) "alter_smk_status_b3" (alter's smoking status; 1 non-smoker, 0 others);</p> <p>(16) "alter_smoking_3cat" (alter's smoking status: three categories - smoker, non-smoker, former smoker);</p> <p>(17) "assortativity_score_fsmoker" (assortativity score for alter, former smoker);</p> <p>(18) "assortativity_score_nsmoker" (assortativity score for alter, non-smoker);</p> <p>(19) "assortativity_score_smoker" (assortativity score for alter, smoker);</p> <p>(20) "ego.alter_meet_f" (ego's meeting frequency with alter); </p> <p>(21) "ego_alter_meet_b" (ego's meeting frequency with alter, binary variable);</p> <p>(22) "ego.alter_meet_n" (ego's meeting frequency with alter, numerical codes);</p> <p>(23) "alter_rel.w.ego_f" (type of alters in an ego's network);</p> <p>(24) "networkCanvasUUID" (alpha numeric code for alter);</p> <p>(25) "networkCanvasEgoUUID" (alpha numeric code for ego); </p> <p>(26) "ego_smkstatus_f" (smoking status: former smoker, never-smoker, non-smoker (smoked too little), occasional smoker, smoker); </p> <p>(27) "ego_smoking_3cat" (three categories, smoking status: former smoker, non-smoker, smoker);</p> <p>(28) "ego_type_fsmk" (former smoking egos by type of ego-alter relationship);</p> <p>(29) "ego_type_nsmk" (non smoking egos by type of ego-alter relationship);</p> <p>(30) "ego_type_smk" (smoking egos by type of ego-alter relationship);</p> <p>(31) "ego_sex_f" (ego's sex, binary);</p> <p>(32) "ego_sex_n" (ego's sex, numerical code, 1 female, 0 male); </p> <p>(33) "ego_educ_b" (ego's education, binary variable)</p> <p>(34) "ego_age" (ego's age)</p> <p>(35) "ego_age.cen" (ego's age, centered)</p> <p>(36) "ego_relstatus_b" (ego's marital status, binary variable)</p> <p>(37) "ego_occupation_b" (ego's employment status, binary variable)</p> <p>(38) "net.components" (number of strong components in the personal network)</p> <p>(39) "net.deg.centralization" (degree centralization score in the personal networ)</p> <p>(40) "net.density" (density score in the personal network)</p> <p>(41) "prop_fsmokers" (proportion of former smokers in the personal network - alters)</p> <p>(42) "prop_fsmokers.cen" (proportion of former smokers in the personal network, centered- alters)</p> <p>(43) "prop_nsmokers" (proportion of non-smokers in the personal network- alters)</p> <p>(44) "prop_nsmokers.cen" (proportion of non-smokers in the personal network, centered- alters)</p> <p>(45) "prop_smokers" (proportion of smokers in the personal network- alters)</p> <p>(46) "prop_smokers.cen" (proportion of smokers in the personal network, centered- alters)</p>
Data from: Variations in regional white matter volumetry and microstructure during the post-adolescence period: a cross-sectional study of a cohort of 1,713 university students
<p>Human brain white matter undergoes a protracted maturation that continues well into adulthood. Recent advances in diffusion-weighted imaging (DWI) methods allow detailed characterisations of the microstructural architecture of white matter, and they are increasingly utilised to study white matter changes during development and ageing. However, relatively little is known about the late maturational changes in the microstructural architecture of white matter during post-adolescence. Here we report on regional changes in white matter volume and microstructure in young adults undergoing university-level education. As part of the MRi-Share multi-modal brain MRI database, multi-shell, high angular resolution DWI data were acquired in a unique sample of 1,713 university students aged 18 to 26. We assessed the age and sex dependence of diffusion metrics derived from diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) in the white matter regions as defined itein the John Hopkins University (JHU) white matter labels atlas. We demonstrate that while regional white matter volume is relatively stable over the age range of our sample, the white matter microstructural properties show clear age-related variations. Globally, it is characterised by a robust increase in neurite density index (NDI), and to a lesser extent, orientation dispersion index (ODI). These changes are accompanied by a decrease in diffusivity. In contrast, there is minimal age-related variation in fractional anisotropy. There are regional variations in these microstructural changes: some tracts, most notably cingulum bundles, show a strong age-related increase in NDI coupled with decreases in radial and mean diffusivity, while others, mainly cortico-spinal projection tracts, primarily show an ODI increase and axial diffusivity decrease. These age-related variations are not different between males and females, but males show higher NDI and ODI and lower diffusivity than females across many tracts. These findings emphasize the complexity of changes in white matter structure occurring in this critical period of late maturation in early adulthood.</p>
Seroprevalence of IgG antibodies against SARS coronavirus 2 in Belgium – a serial prospective cross-sectional nationwide study of residual samples (March – October 2020)
<p>This dataset contains information on seven prospective cross-sectional nationwide residual sera collection rounds. The samples were analyzed for IgG antibodies against S1 proteins of SARS-CoV-2 with a semi-quantitative commercial ELISA (EuroImmun, Luebeck, Germany).</p> <p>We provide a CSV file containing the following variables:</p> <ul> <li><strong>code</strong>: unique sample code</li> <li><strong>age_cat</strong>: age categories by 10-year age bands (0-10, 10-20, ..., 80-90, 90-Inf), the lower limit is included, e.g. 0-10 = [0,10)</li> <li><strong>sex</strong>: sex (f = female, m = male)</li> <li><strong>province</strong>: province of residence (11 categories)</li> <li><strong>region</strong>: region of residence (3 categories: Brussels, Flanders, Walloon)</li> <li><strong>collection_round</strong>: collection round (values 1 to 7)</li> <li><strong>collection_start</strong>: start date of the collection round</li> <li><strong>collection_end</strong>: end date of the collection round</li> <li><strong>igg_orig</strong>: measured IgG OD value as character (note, a semi-quantitative ELISA was used, i.e. this should not be interpreted continiously)</li> <li><strong>igg_cat</strong>: categorized IgG OD values <ul> <li><em>LoD</em>: IgG OD < 0.15</li> <li><em>negative</em>: 0.15 ≤ IgG OD < 0.8</li> <li><em>borderline</em>: 0.8 ≤ IgG OD < 1.1</li> <li><em>positive</em>: 1.1 ≤ IgG OD</li> </ul> </li> </ul> <p>Please see publication mentioned underneath for more details (<a href="https://doi.org/10.1101/2020.06.08.20125179">https://doi.org/10.1101/2020.06.08.20125179</a>).</p> <p><strong>Funding:</strong> This work received funding from the European Union's Horizon 2020 research and innovation program - project EpiPose (No 101003688), the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement 682540 TransMID), the Flemish Research Fund (FWO 1150017N) and from The Antwerp University Fund; which is a community of donors who contribute to research and education with their personal commitment through a donation, gift, bequest or through academic chairs. The funders had no role in study design, data collection, data analysis, data interpretation, writing or submitting of the report. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.</p>
Text-fig. 4. Allosorex stenodus FEJFAR, 1966 – upper and lower incisors, Ivanovce, fissure 6523. a–g: upper left incisor (Z 28193 – OF 652360; a, f – buccal view, b, g – lingual view, c – anterior view, d – dorsal view, e – ventral view), h–i: upper right incisor (Z 28192 – OF 6523; h – buccal view, i – lingual view), j–m: lower right incisor (Z 28197 – OF 652363; j, m – buccal view, k – lingual view, l – dorsal view), n–o: lower right incisor (Z 28196 – OF 652362; n – lingual view, o – crown cross-section), p–q: lower right incisor (Z 28195 – OF 652361; p – lingual view, l – crown cross-section), r: lower left incisor (Z 28199 – OF 6523; lingual view). in Allosorex Stenodus Fejfar, 1966 (Eulipotyphla, Soricidae): Re-Description Of Type Material And Re-Interpretation Of Its Fossil Record
Text-fig. 4. Allosorex stenodus FEJFAR, 1966 – upper and lower incisors, Ivanovce, fissure 6523. a–g: upper left incisor (Z 28193 – OF 652360; a, f – buccal view, b, g – lingual view, c – anterior view, d – dorsal view, e – ventral view), h–i: upper right incisor (Z 28192 – OF 6523; h – buccal view, i – lingual view), j–m: lower right incisor (Z 28197 – OF 652363; j, m – buccal view, k – lingual view, l – dorsal view), n–o: lower right incisor (Z 28196 – OF 652362; n – lingual view, o – crown cross-section), p–q: lower right incisor (Z 28195 – OF 652361; p – lingual view, l – crown cross-section), r: lower left incisor (Z 28199 – OF 6523; lingual view).
Text-fig. 6. Comparative analysis of the three genera (Prynadaeopteris RADCZ., Geperapteris S.V.MEYEN, Tumidopteris NAUGOLNYKH) with possible affinity to Gleicheniaceae from the Permian deposits of Angaraland. a–c: Tumidopteris NAUGOLNYKH; d–f: Prynadaeopteris RADCZ. (based on Radczenko 1955, 1956, Naugolnykh 2013); g–i: Geperapteris S.V.MEYEN (based on Meyen 1982, Naugolnykh 2013). Left column – sori in plan (frontal view); central column – leaves; right column – sori in cross-section; FL – flattened sori; HS – hemispherical sori. Scale 1 cm (b, h), 5 mm (e), 1 mm (a, d), 0.5 mm (g); c, f, i – figures schematically drawn without scale. in A New Species Of The Genus Tumidopteris Naugolnykh From The Permian Of The Pechora Cis-Urals, Russia
Text-fig. 6. Comparative analysis of the three genera (Prynadaeopteris RADCZ., Geperapteris S.V.MEYEN, Tumidopteris NAUGOLNYKH) with possible affinity to Gleicheniaceae from the Permian deposits of Angaraland. a–c: Tumidopteris NAUGOLNYKH; d–f: Prynadaeopteris RADCZ. (based on Radczenko 1955, 1956, Naugolnykh 2013); g–i: Geperapteris S.V.MEYEN (based on Meyen 1982, Naugolnykh 2013). Left column – sori in plan (frontal view); central column – leaves; right column – sori in cross-section; FL – flattened sori; HS – hemispherical sori. Scale 1 cm (b, h), 5 mm (e), 1 mm (a, d), 0.5 mm (g); c, f, i – figures schematically drawn without scale.
Text-fig. 20. Scanning electron microscope (SEM) images of fruits of Hedyflora (a–d), stamen with in situ Asteropollis sp. pollen (e–g), and Hedyosmum-like staminate inflorescence (h); Torres Vedras locality, Portugal. a, b) Hedyflora sp. 1, lateral and apical views of fruits showing the triangular cross-section, remains of three tepals, apical style and the three lateral "windows" in the hypanthium; c, d) Hedyflora sp. 2, lateral views of fruits showing three well-preserved tepals, apical style and the lateral "windows" in the hypanthium; note the papillae on the lateral wall and around the base of the style; e, f, g) Stamen (f) with in situ pollen of Asteropollis sp. showing the poorly defined star-shaped apertural area (e) and reticulate tectum, with the muri ornamented by small verrucae (g); h) Hedyosmum-like staminate inflorescence with five whorls of tetrasporangiate stamens. Specimens, TV43-S101749 (a, b), TV43-S101307 (c, d), TV44-S137917 (e–g), TV39-S101220 (h). Scale bars 300 Μm (a–d, f, h), 6 Μm (e), 1.5 Μm (g). in The Early Cretaceous Mesofossil Flora Of Torres Vedras (Ne Of Forte Da Forca), Portugal: A Palaeofloristic Analysis Of An Early Angiosperm Community
Text-fig. 20. Scanning electron microscope (SEM) images of fruits of Hedyflora (a–d), stamen with in situ Asteropollis sp. pollen (e–g), and Hedyosmum-like staminate inflorescence (h); Torres Vedras locality, Portugal. a, b) Hedyflora sp. 1, lateral and apical views of fruits showing the triangular cross-section, remains of three tepals, apical style and the three lateral "windows" in the hypanthium; c, d) Hedyflora sp. 2, lateral views of fruits showing three well-preserved tepals, apical style and the lateral "windows" in the hypanthium; note the papillae on the lateral wall and around the base of the style; e, f, g) Stamen (f) with in situ pollen of Asteropollis sp. showing the poorly defined star-shaped apertural area (e) and reticulate tectum, with the muri ornamented by small verrucae (g); h) Hedyosmum-like staminate inflorescence with five whorls of tetrasporangiate stamens. Specimens, TV43-S101749 (a, b), TV43-S101307 (c, d), TV44-S137917 (e–g), TV39-S101220 (h). Scale bars 300 Μm (a–d, f, h), 6 Μm (e), 1.5 Μm (g).
Data of: Cross-sectional survey on Germans' awareness for refugees' information barriers
<p>The present dataset is the result of a cross-sectional online survey, which had been conducted to examine selected predictors of Germans' problem awareness in the form of perceived information barriers that refugees face, placing an emphasis on the role of positive intercultural contact experiences. The survey content is based on an extended version of the Empathy-Attitude-Action model and was carried out with a sample of Germans. </p> <p>The dataset is in xlsx-format and the variable-descriptions can be found in the headings of the spreadsheet. </p>
Tholin optical constants and cross-sections from Corrales & Gavilan et al., 2023 (accepted ApJL)
<p>Data release for Corrales, L., Gavilan, L., Teal, D. J., Kempton, E. M.-R., 2023, ApJL, in press</p> <p>Provides the optical constants from tholins grown in the laboratory (Gavilan et al. 2017, 2018) and computed cross-sections (Mie) for a wide range of particle sizes, for wavelengths of 0.13-10 micron. Python libraries and code for reproducing this work are provided. A static, refactored version of Exo_Transmit (Kempton et al. 2017, Teal et al. 2022, Corrales et al. 2023) is also provided for computing exoplanet transmission spectra with the new tholin species. </p> <p>See README file for a full list of contents and instructions for use.</p>
Dataset for the paper "The relationship between medical students' empathy, mental health, and burnout: A cross-sectional study" published in Medical Teacher (2022)
<p><strong>Full reference of the paper: </strong></p> <p>Valerie Carrard, Céline Bourquin, Sylvie Berney, Katja Schlegel, Jacques Gaume, Pierre-Alexandre Bart, Martin Preisig, Marianne Schmid Mast & Alexandre Berney (2022): The relationship between medical students’ empathy, mental health, and burnout: A cross-sectional study, Medical Teacher, DOI: <a href="https://doi.org/10.1080/0142159X.2022.2098708">10.1080/0142159X.2022.2098708</a></p>
Development Gateway shisha study quantitative data: a cross-sectional survey investigating factors associated with shisha use in Nigeria
<p>This data is from a cross-sectional telephone survey among 1278 respondents (611 current shisha smokers and 667 shisha non-smokers) exploring the following questions:</p> <ol> <li>What factors (demographic, social, cultural, behavioural, etc.) are associated with the use of shisha in Nigeria?</li> <li>What are the shisha use patterns and behaviours among those who use shisha in Nigeria?</li> </ol> <p>The study was conducted across the six geo-political zones in Nigeria (North-East, North-West, North-Central, South-East, South-South and South-West) in the following states: Lagos, Oyo, FCT, Plateau, Gombe, Adamawa, Kaduna, Kano, Rivers, Edo, Anambra and Ebonyi.</p> <p>The data was collected between 28th July and 11th September 2022.</p> <p>Also included is the codebook and the study questionnaire.</p>
Delving into the relationship between regular physical exercise and cardiac interoception in two cross-sectional studies.
<p>This repository contains raw data from two studies corresponding to the article "No evidence of a relationship between regular physical exercise and cardiac interoception" by Yoris et al. In Study I, 45 resting EEG files are included for the Active (N = 24) and Inactive (N = 21) groups, both for the eyes closed and eyes open conditions. For Study II, there are 60 resting EEG files (30 Active/30 Inactive). Data are in EEGLAB format .set/fdt. The project is publicly available for free use and can be accessed at <a href="https://osf.io/xrsgn/">https://osf.io/xrsgn/</a>.</p>
Cotton root cross-sections under water deficit
<p>This experiment is describing the analysis of the root cross-sections. The roots were collected in the lab of Prof. Avat Shekoofa (Uni. of Tennessee), and the root samples were sent to Julkowska lab (BTI). Magda did hand cross-sections and stained them with toluidine blue to visualize the xylem vessels. The individual images were stitched into an ortho-mosaic using Photoshop.</p>
Sociodemographic predictors of bureaucratic violence in the residency application process: findings from a mixed methods cross-sectional survey of migrant women in Spain.
<p>Dataset contains the data used for the quantitative analyses presented in the paper titled "Sociodemographic predictors of bureaucratic violence in the residency application process: findings from a mixed methods cross-sectional survey of migrant women in Spain.".</p> <p>Data were collected from a cross-sectional online survey of migrant women living in the Valencian Community of Spain between January and March 2023. The dataset contains demographic information about participants, as well as the barriers that the reported facing in the process of applying for residency within Spain.</p>
Architecture, morphology and strength of the quadriceps muscle in male and female soccer players at the national level: a cross-sectional study
<p>This is the dataset for the corresponding publication. The dataset includes the "raw" data as well as the analysis script used for the calculation of the group differences and correlations.</p>
Dataset for the paper "Exposure of medical students to sexism and sexual harassment and their association with mental health: a cross-sectional study at a Swiss medical school" published in BMJ Open (2023)
<p><strong>Full reference of the paper: </strong></p> <p>Barbier JM, Carrard V, Schwarz J, et al. Exposure of medical students to sexism and sexual harassment and their association with mental health: a cross-sectional study at a Swiss medical school. BMJ Open 2023;13:e069001. doi:10.1136/bmjopen-2022-069001</p>
Dataset SeBluCo study: SARS-CoV-2-antibodies among German blood donors 2020 – 2022, a repetitive cross-sectional study
<p>The dataset is the result of a repetitive cross-sectional study in 28 regions in Germany on SARS-CoV-2 antibodies in residual samples of blood donors from April 2020 to April 2021, September 2021 and April/May 2022. These data were used to aide in monitoring the pandemic in Germany. Data were completely anonymised at the site of sample collection. Serological test results are accompanied by demographic data including sex, age and area of residence (assigned a level two Nomenclature des Unités Territoriales Statistiques (NUTS2)). </p><p>The file contains data (sheet "data") as well as the description of variable content and coding (sheet "variables").</p>
Data from: Variations in regional white matter volumetry and microstructure during the post-adolescence period: a cross-sectional study of a cohort of 1,713 university students
Open the record for dataset details and reuse information.
Predictors of medical staff’s knowledge, attitudes, and behavior of dysphagia assessment: A cross-sectional study
Open the record for dataset details and reuse information.
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.