cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.28237655
title: #natural, #vegan, #healing: A Content Analysis of Health Content Among Instagram Posts Focused on Cannabis Edibles

description: Despite limited scientific evidence, public perceptions of cannabis as health enhancing are significant. As food products, cannabis edibles (edibles), may also leverage food-related associations that convey health. Social media is a prominent and influential source of largely unregulated cannabis information and a potential place to correct misinformation. Given its potential to shape product appeal and perceptions of health benefits and risks, understanding the social media landscape around edibles and health is a priority. We conducted a quantitative content analysis of a random sample of #edibles Instagram posts (N = 702) published in January 2020. A structured coding instrument analyzed posts for: (1) non-food related health, medicine, and wellness content (2) food-related characteristics/associations suggesting edibles are healthy foods or appropriate for particular diets. The majority of posts (61%) featured non-food related health, medicine, or wellness content. 35% of posts noted a general health or wellness issue or benefit, while 9% highlighted a medical condition, clinical diagnosis or attendant benefit; a wide range of wellness, health, and clinical issues were cited. Nearly half of all posts (45%) alluded to medicine or being medicated, while 22% referenced medical marijuana specifically. Connections to health were also made through food-related associations, with 13% of posts citing a dietary need or nutrient claim and 10% highlighting food-related characteristics that imply product healthfulness. Health-related content is widespread among #edibles Instagram posts. Communication approaches to counter unsubstantiated health claims and regulatory strategies limiting commercial promotion should be considered. Explicit connections between edibles and health and more implicit associations via hashtags and images warrant particular attention.
DOI: 10.6084/m9.figshare.28237655.v1
title: #natural, #vegan, #healing: A Content Analysis of Health Content Among Instagram Posts Focused on Cannabis Edibles

description: Despite limited scientific evidence, public perceptions of cannabis as health enhancing are significant. As food products, cannabis edibles (edibles), may also leverage food-related associations that convey health. Social media is a prominent and influential source of largely unregulated cannabis information and a potential place to correct misinformation. Given its potential to shape product appeal and perceptions of health benefits and risks, understanding the social media landscape around edibles and health is a priority. We conducted a quantitative content analysis of a random sample of #edibles Instagram posts (N = 702) published in January 2020. A structured coding instrument analyzed posts for: (1) non-food related health, medicine, and wellness content (2) food-related characteristics/associations suggesting edibles are healthy foods or appropriate for particular diets. The majority of posts (61%) featured non-food related health, medicine, or wellness content. 35% of posts noted a general health or wellness issue or benefit, while 9% highlighted a medical condition, clinical diagnosis or attendant benefit; a wide range of wellness, health, and clinical issues were cited. Nearly half of all posts (45%) alluded to medicine or being medicated, while 22% referenced medical marijuana specifically. Connections to health were also made through food-related associations, with 13% of posts citing a dietary need or nutrient claim and 10% highlighting food-related characteristics that imply product healthfulness. Health-related content is widespread among #edibles Instagram posts. Communication approaches to counter unsubstantiated health claims and regulatory strategies limiting commercial promotion should be considered. Explicit connections between edibles and health and more implicit associations via hashtags and images warrant particular attention.
DOI: 10.15468/dl.9tthfj
title: Occurrence Download

description: A dataset containing 91 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Erythranthe guttata",
 "Country is Czechia",
 "HasCoordinate is true"
 ]
}

 The dataset includes 91 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0085058-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3886/e243969
title: NNDSS - Table II. Invasive Pneumococcal Diseases, All Ages

description: NNDSS - Table II. Invasive Pneumococcal Diseases, All Ages - 2017. In this Table, provisional cases of selected notifiable diseases (≥1,000 cases reported during the preceding year), and selected low frequency diseases are displayed. The Table includes total number of cases reported in the United States, by region and by states, in accordance with the current method of displaying MMWR data. Data on United States exclude counts from US territories.

Note:
These are provisional cases of selected national notifiable diseases, from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data reported by the 50 states, New York City, the District of Columbia, and the U.S. territories are collated and published weekly as numbered tables printed in the back of the Morbidity and Mortality Weekly Report (MMWR). Cases reported by state health departments to CDC for weekly publication are provisional because of ongoing revision of information and delayed reporting.

Case counts in this table are presented as they were published in the MMWR issues. Therefore, numbers listed in later MMWR weeks may reflect changes made to these counts as additional information becomes available.

Footnotes:
C.N.M.I.: Commonwealth of Northern Mariana Islands.

U: Unavailable. —: No reported cases. N: Not reportable. NN: Not Nationally Notifiable. NP: Nationally notifiable but not published. Cum: Cumulative year-to-date counts. Med: Median. Max: Maximum.

*Three low incidence conditions, rubella, rubella congenital, and tetanus, are in Table II to facilitate case count verification with reporting jurisdictions.

† Case counts for reporting year 2017 are provisional and subject to change. For further information on interpretation of these data, see http://wwwn.cdc.gov/nndss/document/ ProvisionalNationaNotifiableDiseasesSurveillanceData20100927.pdf. Data for tuberculosis are displayed in Table IV, which appears quarterly.

§ Includes drug resistant and susceptible cases of Invasive Pneumococcal Disease. This condition was previously named Streptococcus pneumoniae invasive disease and cases were reported to CDC using different event codes to specify whether the cases were drug resistant or in a defined age group, such as &lt;5 years.
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description: (Downloaded 1/12/2026)
DOI: 10.3886/e243969v1
title: NNDSS - Table II. Invasive Pneumococcal Diseases, All Ages

description: NNDSS - Table II. Invasive Pneumococcal Diseases, All Ages - 2017. In this Table, provisional cases of selected notifiable diseases (≥1,000 cases reported during the preceding year), and selected low frequency diseases are displayed. The Table includes total number of cases reported in the United States, by region and by states, in accordance with the current method of displaying MMWR data. Data on United States exclude counts from US territories.

Note:
These are provisional cases of selected national notifiable diseases, from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data reported by the 50 states, New York City, the District of Columbia, and the U.S. territories are collated and published weekly as numbered tables printed in the back of the Morbidity and Mortality Weekly Report (MMWR). Cases reported by state health departments to CDC for weekly publication are provisional because of ongoing revision of information and delayed reporting.

Case counts in this table are presented as they were published in the MMWR issues. Therefore, numbers listed in later MMWR weeks may reflect changes made to these counts as additional information becomes available.

Footnotes:
C.N.M.I.: Commonwealth of Northern Mariana Islands.

U: Unavailable. —: No reported cases. N: Not reportable. NN: Not Nationally Notifiable. NP: Nationally notifiable but not published. Cum: Cumulative year-to-date counts. Med: Median. Max: Maximum.

*Three low incidence conditions, rubella, rubella congenital, and tetanus, are in Table II to facilitate case count verification with reporting jurisdictions.

† Case counts for reporting year 2017 are provisional and subject to change. For further information on interpretation of these data, see http://wwwn.cdc.gov/nndss/document/ ProvisionalNationaNotifiableDiseasesSurveillanceData20100927.pdf. Data for tuberculosis are displayed in Table IV, which appears quarterly.

§ Includes drug resistant and susceptible cases of Invasive Pneumococcal Disease. This condition was previously named Streptococcus pneumoniae invasive disease and cases were reported to CDC using different event codes to specify whether the cases were drug resistant or in a defined age group, such as &lt;5 years.
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description: (Downloaded 1/12/2026)
DOI: 10.13130/rd_unimi/jmksaw/wn53cr
title: 5.0_0.0_neigh.html

description: :unav
DOI: 10.13130/rd_unimi/jmksaw/1bv60b
title: Distance.Clustering_div.tab

description: :unav
DOI: 10.6073/pasta/855fde3a55756b3ae6a19808a366227b
title: Sea ice thickness, snow depth, and sea ice freeboard in lagoon sites along the Alaska Beaufort Sea coast, 2019-ongoing

description: Physical parameters related to snow and sea ice have implications for lagoon circulation, sea-air heat exchange, and underwater light regimes. To understand these relationships and their greater effect on ecosystem function, the Beaufort Lagoon Ecosystem LTER (BLE LTER) uses in situ methods to assess snow depth, ice freeboard, and ice thickness in select water bodies across the Beaufort Sea coast (Elson Lagoon, Simpson Lagoon, Kaktovik Lagoon, Jago Lagoon, and Stefansson Sound). Sea ice thickness is the distance from sea ice bottom to top, not including snow. Freeboard, determined in the same drilled hole, is the distance from the surface of the water to the top of the ice, not including snow cover. These measurements are made annually, close to maximum ice thickness (typically April).
DOI: 10.13130/rd_unimi/jmksaw/isbbe3
title: Group.Auto+Neigh.kDistance_l2_k10_max.tab

description: :unav
DOI: 10.13130/rd_unimi/jmksaw/mglweh
title: 3.0_0.0_neigh.html

description: :unav
DOI: 10.13130/rd_unimi/jmksaw/ill7ou
title: 6.0_0.0_neigh.html

description: :unav
DOI: 10.15468/dl.ew55q2
title: Occurrence Download

description: A dataset containing 106 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lilium carniolicum Bernh. ex W.D.J.Koch",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 106 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0300668-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ew7ygx
title: Occurrence Download

description: A dataset containing 11741 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Epipactis muelleri Godfery",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 11741 records from 85 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0296448-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ew9jvv
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Alchemilla argentidens Buser",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0286293-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ewaeap
title: Occurrence Download

description: A dataset containing 660 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Acer tegmentosum Maxim.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 660 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0150669-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ewbwvz
title: Occurrence Download

description: A dataset containing 4122 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Heliotropium supinum L.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 4122 records from 112 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0298907-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wbpnjp
title: Occurrence Download

description: A dataset containing 144 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Phalaenopsis aphrodite Rchb.f., Phalaenopsis aphrodite subsp. formosana Christenson, Phalaenopsis aphrodite subsp. aphrodite, Phalaenopsis aphrodite var. amabilis (Warner & B.S.Williams) A.H.Kent, Phalaenopsis amabilis subsp. aphrodite (Rchb.f.) Ames)"
 ]
}

 The dataset includes 144 records from 28 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078294-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ewfq2j
title: Occurrence Download

description: A dataset containing 4225 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Carex glareosa Schkuhr ex Wahlenb.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 4225 records from 93 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0415450-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ewmfmn
title: Occurrence Download

description: A dataset containing 342325 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lotus pedunculatus Cav.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 342325 records from 616 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0263791-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ewnk4t
title: Occurrence Download

description: A dataset containing 1002 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Silene sclerocarpa Dufour",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1002 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0288469-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ewp34m
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Stipa daghestanica Grossh.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 8 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0416426-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eww6q3
title: Occurrence Download

description: A dataset containing 55 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Arabis vochinensis Spreng.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 55 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0287922-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ewwrd5
title: Occurrence Download

description: A dataset containing 3 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Heracleum carpaticum Porcius",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 3 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0298960-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ewyqb7
title: Occurrence Download

description: A dataset containing 389 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Biarum tenuifolium (L.) Schott",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 389 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0289438-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.exhyfg
title: Occurrence Download

description: A dataset containing 56 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Macrochloa tenacissima Linnaeus, 1755",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 56 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0299764-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.exsk8f
title: Occurrence Download

description: A dataset containing 2739 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Astragalus stella L.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 2739 records from 68 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0288810-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ext7s6
title: Occurrence Download

description: A dataset containing 330868 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Chelidonium majus L.",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 330868 records from 832 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0258586-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.f3wxmt
title: Occurrence Download

description: A dataset containing 200 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Angola",
 "OccurrenceStatus is Present",
 "TaxonKey is Giraffa Brisson, 1762"
 ]
}

 The dataset includes 200 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026587-250426092105405/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/kbl4yo
title: Replication Data for: Following a Middle Way: How Rising Powers Navigate Sovereignty Debates in Peacebuilding

description: The role of rising powers in world politics has been growing. However, their influence on the international peace and security architecture is still to be evaluated. This article assesses their potential impact by analyzing how they reconceptualize “sovereignty” in peacebuilding debates. We investigate the extent to which they engage in norm entrepreneurship by analyzing the conceptualizations of sovereignty of three rising powers (Brazil, South Africa, and Turkey) and comparing them to those of the permanent members (P5) of the United Nations Security Council (UNSC). Our analysis focuses on the conceptualizations of sovereignty presented in speeches in peace-related meetings at the UNSC and in peace-related resolutions between 1991 and 2020. We show that sovereignty conceptualizations at the UNSC are situated along a spectrum, with the rising powers occupying a middle ground. By disaggregating different dimensions of sovereignty, we demonstrate that the rising powers neither align with post-Westphalian views of France, the United Kingdom, and the United States (P3), where peacebuilding priorities override sovereignty, nor with Westphalian views of China and Russia, which limit international peacebuilding activities to a strict respect of sovereignty. Instead, our results indicate that rising powers distinguish themselves from both extremes by embracing a view on sovereignty that prioritizes national ownership.
DOI: 10.21233/vjyg-f434
title: Shinkai Pond ostracode surface sample dataset

description: Raw data for the Shinkai Pond ostracode surface sample dataset submitted to the Neotoma Paleoecology Database. Data is available through the landing page in JSON format. The landing page referenced by the DOI also contains links to publications and a map-based viewer for the dataset. The Neotoma Paleoecology Database maintains a homepage at https://www.neotomadb.org.
DOI: 10.17172/nomad/2025.05.12-1
title: NOMAD dataset: Ab Initio Study of Self Interstitial Diffusion in hcp-Beryllium
DOI: 10.6084/m9.figshare.28000305
title: Deep-reinforcement-learning-based optimization for intra-urban epidemic control considering spatiotemporal orderliness

description: When planning intra-urban control measures for epidemics with significant societal impact, it is essential to consider the spatiotemporal orderliness of interventions, thus mitigating the disruption to daily life. For instance, improving intervention consistency among highly interacted sub-regions and avoid frequent and significant changes of interventions over time can be effective. However, existing studies on optimizing epidemic control overlooked the need for spatiotemporal consistency and stability of the interventions, potentially impacting their practicality and public compliance. To fill this gap, this study systematically conceptualized and quantified spatiotemporal orderliness for intra-urban epidemic control. A deep-reinforcement-learning (DRL) framework integrating the spatiotemporal orderliness was proposed to optimize the interventions across sub-regions over time. Taking Shenzhen, China as a study area, we solve a joint control plan for 74 sub-regions based on a meta-population SEIR epidemic model with a real-world intra-urban mobility network. The results demonstrate that the proposed model can effectively generate tailored dynamic interventions for sub-regions, significantly improving spatiotemporal orderliness. Furthermore, the effectiveness and generalizability of proposed model are demonstrated under different urban structures and transmissibility of respiratory viruses. Overall, this study provides a DRL-based tool for planning intra-urban epidemic control measures with enhanced spatiotemporal orderliness, potentially aiding future epidemic preparedness.