cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/dwc9mvjcbr
title: Comparative analysis of the lipidome, fatty acids, and fat globule particle size in camel and bovine milk across different regions

description: SUPPORTING INFORMATION DESCRIPTION
Table S1: The location information of the camel and bovine pastures in Northern Xinjiang, Southern Xinjiang, and Inner Mongolia.
Table S2: Dietary formulation information for camel milk from Northern Xinjiang (Altay City, Xinjiang), Southern Xinjiang (Aksu City, Xinjiang), and Inner Mongolia (Alxa League, Inner Mongolia).
Notes: XJNC: camel milk from northern Xinjiang; XJSC: camel milk from southern Xinjiang; IMC: camel milk from Inner Mongolia.
Table S3: Dietary formulation information for bovine milk from Northern Xinjiang (Altay City, Xinjiang), Southern Xinjiang (Aksu City, Xinjiang), and Inner Mongolia (Alxa League, Inner Mongolia).
Notes: XJNB: bovine milk from northern Xinjiang; XJSB: bovine milk from southern Xinjiang; IMB: bovine milk from Inner Mongolia.
Table S4: Surface area-weighted (D[3,2]) and volume-weighted (D[4,3]) particle sizes of milk fat globules in camel and bovine milk from different regions.
Table S5: Zeta potential (ZP) of milk fat globules in camel and bovine milk from different regions.
Table S6: Fatty acid composition of camel milk and bovine milk from southern Xinjiang, northern Xinjiang, and Inner Mongolia.
Table S7: Lipidome of camel milk and bovine milk from southern Xinjiang, northern Xinjiang, and Inner Mongolia.
Supplementary Figure 1: The geographical information of the camel and bovine pastures in Northern Xinjiang, Southern Xinjiang, and Inner Mongolia.
Supplementary Figure 2: PCA (Principal Component Analysis) of the lipidome of camel milk and bovine milk from different regions, including QC (quality control). 
Notes: XJNC: camel milk from northern Xinjiang; XJSC: camel milk from southern Xinjiang; IMC: camel milk from Inner Mongolia; XJNB: bovine milk from northern Xinjiang; XJSB: bovine milk from southern Xinjiang; IMB: bovine milk from Inner Mongolia.
Supplementary Figure 3: Permutation test (200 permutations) of OPLS-DA analysis for the lipidome in camel milk and bovine milk from the same region, and the lipidome in camel milk and bovine milk from different regions. 
Notes: XJNC: camel milk from northern Xinjiang; XJSC: camel milk from southern Xinjiang; IMC: camel milk from Inner Mongolia; XJNB: bovine milk from northern Xinjiang; XJSB: bovine milk from southern Xinjiang; IMB: bovine milk from Inner Mongolia.
Supplementary Figure 4: Correlation analysis of differential lipids in camel milk and bovine milk from the same region (a), correlation analysis of differential lipids in camel milk (b) from different regions and bovine milk (c) from different regions; Bubble plot of KEGG metabolic pathways involved in differential lipids and metabolic pathway network diagram (d).
Notes: XJNC: camel milk from northern Xinjiang; XJSC: camel milk from southern Xinjiang; IMC: camel milk from Inner Mongolia; XJNB: bovine milk from northern Xinjiang; XJSB: bovine milk from southern Xinjiang; IMB: bovine milk from Inner Mongolia.
DOI: 10.17632/dwc9mvjcbr.1
title: Comparative analysis of the lipidome, fatty acids, and fat globule particle size in camel and bovine milk across different regions

description: SUPPORTING INFORMATION DESCRIPTION
Table S1: The location information of the camel and bovine pastures in Northern Xinjiang, Southern Xinjiang, and Inner Mongolia.
Table S2: Dietary formulation information for camel milk from Northern Xinjiang (Altay City, Xinjiang), Southern Xinjiang (Aksu City, Xinjiang), and Inner Mongolia (Alxa League, Inner Mongolia).
Notes: XJNC: camel milk from northern Xinjiang; XJSC: camel milk from southern Xinjiang; IMC: camel milk from Inner Mongolia.
Table S3: Dietary formulation information for bovine milk from Northern Xinjiang (Altay City, Xinjiang), Southern Xinjiang (Aksu City, Xinjiang), and Inner Mongolia (Alxa League, Inner Mongolia).
Notes: XJNB: bovine milk from northern Xinjiang; XJSB: bovine milk from southern Xinjiang; IMB: bovine milk from Inner Mongolia.
Table S4: Surface area-weighted (D[3,2]) and volume-weighted (D[4,3]) particle sizes of milk fat globules in camel and bovine milk from different regions.
Table S5: Zeta potential (ZP) of milk fat globules in camel and bovine milk from different regions.
Table S6: Fatty acid composition of camel milk and bovine milk from southern Xinjiang, northern Xinjiang, and Inner Mongolia.
Table S7: Lipidome of camel milk and bovine milk from southern Xinjiang, northern Xinjiang, and Inner Mongolia.
Supplementary Figure 1: The geographical information of the camel and bovine pastures in Northern Xinjiang, Southern Xinjiang, and Inner Mongolia.
Supplementary Figure 2: PCA (Principal Component Analysis) of the lipidome of camel milk and bovine milk from different regions, including QC (quality control). 
Notes: XJNC: camel milk from northern Xinjiang; XJSC: camel milk from southern Xinjiang; IMC: camel milk from Inner Mongolia; XJNB: bovine milk from northern Xinjiang; XJSB: bovine milk from southern Xinjiang; IMB: bovine milk from Inner Mongolia.
Supplementary Figure 3: Permutation test (200 permutations) of OPLS-DA analysis for the lipidome in camel milk and bovine milk from the same region, and the lipidome in camel milk and bovine milk from different regions. 
Notes: XJNC: camel milk from northern Xinjiang; XJSC: camel milk from southern Xinjiang; IMC: camel milk from Inner Mongolia; XJNB: bovine milk from northern Xinjiang; XJSB: bovine milk from southern Xinjiang; IMB: bovine milk from Inner Mongolia.
Supplementary Figure 4: Correlation analysis of differential lipids in camel milk and bovine milk from the same region (a), correlation analysis of differential lipids in camel milk (b) from different regions and bovine milk (c) from different regions; Bubble plot of KEGG metabolic pathways involved in differential lipids and metabolic pathway network diagram (d).
Notes: XJNC: camel milk from northern Xinjiang; XJSC: camel milk from southern Xinjiang; IMC: camel milk from Inner Mongolia; XJNB: bovine milk from northern Xinjiang; XJSB: bovine milk from southern Xinjiang; IMB: bovine milk from Inner Mongolia.
DOI: 10.17632/7xf995f56v
title: Feed Type Modulates Metabolic Responses and Thermal Tolerance of Mandarin Fish (Siniperca chuatsi) Under Acute Warming

description: Metabolomic files records the relative concentrations of metabolites in both positive and negative modes. The group information is shown in the file group.
DOI: 10.17632/7xf995f56v.1
title: Feed Type Modulates Metabolic Responses and Thermal Tolerance of Mandarin Fish (Siniperca chuatsi) Under Acute Warming

description: Metabolomic files records the relative concentrations of metabolites in both positive and negative modes. The group information is shown in the file group.
DOI: 10.17632/yxb72xktww
title: Caucasian bee varroa selection 2026

description: This data concerns varroa, the number of brood, and the total number of frames with bees in honey bee colonies. Data were collected at the beginning of the study to select groups of resistant and non-resistant to Varroa. Then, bee colonies were equalized and started from the same point. At the end, the same data were collected again to see the differences.
DOI: 10.17632/yxb72xktww.1
title: Caucasian bee varroa selection 2026

description: This data concerns varroa, the number of brood, and the total number of frames with bees in honey bee colonies. Data were collected at the beginning of the study to select groups of resistant and non-resistant to Varroa. Then, bee colonies were equalized and started from the same point. At the end, the same data were collected again to see the differences.
DOI: 10.5281/zenodo.18301401
title: Pseudechinolaena polystachya (Kunth) Stapf. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:53
DOI: 10.5281/zenodo.18301400
title: Pseudechinolaena polystachya (Kunth) Stapf. In: Marchesi E., Mailhos A. & Bonifacino J.M. (Eds.). Flora Uruguaya: Flora Vascular del Uruguay. ISSN 3121-2050, V. 1.0.

description: Citable snapshot. Includes PDF and CSV of collections. Date: January 13th, 2026 at 16:53
DOI: 10.17632/8msty2md8j
title: Data and Scripts for "Mismatches between satellite-based vegetation greenness and primary productivity in response to the 2022/23 megadrought in Southwest China"

description: The “.bin” files represent the original data employed in this analysis. The data can be accessed by Python or NCL. The files of "gogpp.bin", "gosif.bin", "inter.FluxMGPP.toGOGPP.bin", "inter.modis.NIRv.toGOGPP.bin", "inter.modisevi.toGOGPP.bin", "inter.modislai.toGOGPP.bin", "inter.modisndvi.toGOGPP.bin" are vegetation metrics data. And "mask.ERAland_climtogogpp.bin", "ssrd.ssr.era5.bin", "vpd.tcc.ssrd.era5.bin" are hydrothermal variables.
DOI: 10.17632/8msty2md8j.1
title: Data and Scripts for "Mismatches between satellite-based vegetation greenness and primary productivity in response to the 2022/23 megadrought in Southwest China"

description: The “.bin” files represent the original data employed in this analysis. The data can be accessed by Python or NCL. The files of "gogpp.bin", "gosif.bin", "inter.FluxMGPP.toGOGPP.bin", "inter.modis.NIRv.toGOGPP.bin", "inter.modisevi.toGOGPP.bin", "inter.modislai.toGOGPP.bin", "inter.modisndvi.toGOGPP.bin" are vegetation metrics data. And "mask.ERAland_climtogogpp.bin", "ssrd.ssr.era5.bin", "vpd.tcc.ssrd.era5.bin" are hydrothermal variables.
DOI: 10.17632/5pvx727rp4
title: ships and offshore structures

description: for the publication
DOI: 10.15468/dl.xkadgn
title: Occurrence Download

description: A dataset listing the 111 species recorded in GBIF matching the query:
{
 "DatasetKey" : [
 "is Swiss National Fish Databank"
 ]
}

 The dataset's 111 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020694-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/5pvx727rp4.2
title: ships and offshore structures

description: for the publication
DOI: 10.15468/dl.tjj3as
title: Occurrence Download

description: A dataset containing 731 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((98.432 8.744085, 98.360917 8.738512999999999, 98.291591 8.721933999999999, 98.22573300000001 8.694756999999999, 98.16497099999999 8.657655, 98.11080200000001 8.611542999999999, 98.064561 8.557558999999999, 98.02738600000001 8.497037000000001, 98.00019 8.431468000000001, 97.983637 8.36247, 97.978129 8.291741999999999, 97.983797 8.221026, 98.000495 8.152063999999999, 98.027806 8.086551, 98.065054 8.026099, 98.11132000000001 7.972194, 98.165464 7.92616, 98.226153 7.889128, 98.29189599999999 7.862008, 98.36107800000001 7.845465, 98.432 7.839905, 98.502922 7.845465, 98.572104 7.862008, 98.63784699999999 7.889128, 98.698536 7.92616, 98.75268 7.972194, 98.798946 8.026099, 98.83619400000001 8.086551, 98.863505 8.152063999999999, 98.88020299999999 8.221026, 98.88587099999999 8.291741999999999, 98.880363 8.36247, 98.86381 8.431468000000001, 98.836614 8.497037000000001, 98.79943900000001 8.557558999999999, 98.753198 8.611542999999999, 98.699029 8.657655, 98.638267 8.694756999999999, 98.57240899999999 8.721933999999999, 98.503083 8.738512999999999, 98.432 8.744085))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 731 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020716-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/86whtxkfk2
title: MAOC along elevation gradient

description: MAOC along elevation gradient
DOI: 10.17632/86whtxkfk2.1
title: MAOC along elevation gradient

description: MAOC along elevation gradient
DOI: 10.15468/dl.4uvxnk
title: Occurrence Download

description: A dataset containing 360 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Nemoura tau",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 360 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020717-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wz2a69
title: Occurrence Download

description: A dataset containing 451 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((0.44457 44.80895,0.46242 44.80895,0.46242 44.82438,0.44457 44.82438,0.44457 44.80895))",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 451 records from 24 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020718-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a3x9b8
title: Occurrence Download

description: A dataset listing the 122 species recorded in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is Argentina",
 "DatasetKey is iNaturalist Research-grade Observations",
 "GadmGid is ARG.5_1",
 "Geometry POLYGON((-58.40403 -34.56369,-58.41027 -34.55786,-58.40954 -34.55631,-58.41118 -34.55691,-58.41994 -34.55331,-58.4291 -34.55101,-58.43514 -34.55289,-58.434 -34.55383,-58.4412 -34.55779,-58.43903 -34.56153,-58.43505 -34.56181,-58.43643 -34.56355,-58.44127 -34.56248,-58.44814 -34.5684,-58.42941 -34.57769,-58.43811 -34.58765,-58.42956 -34.59324,-58.43461 -34.59708,-58.42113 -34.60318,-58.41033 -34.60417,-58.40469 -34.58075,-58.39864 -34.5831,-58.3973 -34.57335,-58.40414 -34.56948,-58.40356 -34.5676,-58.40086 -34.56737,-58.40403 -34.56369))",
 "TaxonKey is Aves",
 "Year 2024-2026"
 ]
}

 The dataset's 122 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0020696-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/gj3x6r263d
title: Raw, uncropped supporting Western blot files for: Kito Y. ...Rona G. and Pagano M. “GMCL1 controls 53BP1 stability and modulates taxane sensitivity”

description: Raw, uncropped supporting Western blot files for: Yuki Kito, Tania J. González-Robles, Sharon Kaisari, Juhee Pae, Sheena Faye Garcia, Juliana Ortiz-Pacheco, Beatrix Ueberheide, Antonio Marzio, Gergely Rona, and Michele Pagano; GMCL1 controls 53BP1 stability and modulates taxane sensitivity
DOI: 10.17632/gj3x6r263d.1
title: Raw, uncropped supporting Western blot files for: Kito Y. ...Rona G. and Pagano M. “GMCL1 controls 53BP1 stability and modulates taxane sensitivity”

description: Raw, uncropped supporting Western blot files for: Yuki Kito, Tania J. González-Robles, Sharon Kaisari, Juhee Pae, Sheena Faye Garcia, Juliana Ortiz-Pacheco, Beatrix Ueberheide, Antonio Marzio, Gergely Rona, and Michele Pagano; GMCL1 controls 53BP1 stability and modulates taxane sensitivity
DOI: 10.17632/fpgsn3j373
title: Toxic Metals and PFAS in Svalbard Reindeer (Rangifer tarandus platyrhynchus) Liver and Muscle

description: Svalbard reindeer (Rangifer tarandus platyrhynchus) liver and muscle samples from August (2022) and October (2023) were analysed for toxic metals (Hg, Cd, and Pb) and PFAS (PFUnDA, PFTriDA, PFTDA, PFHxDA, PFPeS, PFHxS, PFOS, PFNS, PFDS, PFECHS, FOSAA, MeFOSAA, EtFOSAA, and NaDONA) concentrations to determine seasonal fluctuations in contaminant accumulation. We found a significant increase in both toxic metals and PFAS from August to October, which is when the Svalbard reindeer peak in weight. This may be explained by an extended foraging period (in October compared to August) following the annual winter fasting. The increased concentrations in October may also be explained by a dietary shift in vegetation with plant senescence at the end of summer. Overall, the PFAS profile indicated a predominant exposure to long-range transported PFAS (e.g., PFCAs). However, high concentrations of PFSAs indicate local pollution contributions too (e.g., firefighting foam). 

Hg was determined using DMA-80, PFAS were determined using an Xevo TQ-XS Triple Quadrupole Mass Spectrometer coupled with an ACQUITY UPLC system, and Cd and Pb were determined using an 8800 Triple Quadrupole inductively coupled plasma mass spectrometry (ICP-MS) system. A total of 41 PFAS were included in the analysis: PFBA, PFPeA, PFHxA, PFHpA, PFOA, PFNA, PFDA, PFUnDA, PFDoDA, PFTriDA, PFTDA, PFHxDA, PFOcDA PFBS, PFPeS, PFHxS, PFHpS, PFOS, PFNS, PFDS, PFDoDS, PFECHS, 4:2 FTS, 6:2 FTS, 8:2 FTS, and 10:2 FTS, FOSAA, MeFOSAA, EtFOSAA, PFOSA, MeFOSA, EtFOSA, MeFOSE, EtFOSE, GenX, NaDONA, 9Cl-PF3ONS, P37DMOA, SaMPAP and diSAMPAP. Only contaminants detected above the LOD in at least 25 % of the samples are reported. 

All samples were freeze-dried and homogenised prior to analysis. The water content of the samples was 70.1% in the liver and 72.0% in the muscle. The water content was used to calculate the wet weight concentrations of the samples. The concentrations are provided in both dry weight and wet weight. 

The provided data are as follows: age (years), weight (kg), contaminants (Hg, Se, Cd, Pb, PFUnDA, PFTriDA, PFTDA, PFHxDA, PFPeS, PFHxS, PFOS, PFNS, PFDS, PFECHS, FOSAA, MeFOSAA, EtFOSAA, and NaDONA) in ng/g. Values missing as a result of analytical errors are named "na", while values below the LOD were left blank.
DOI: 10.17632/fpgsn3j373.1
title: Toxic Metals and PFAS in Svalbard Reindeer (Rangifer tarandus platyrhynchus) Liver and Muscle

description: Svalbard reindeer (Rangifer tarandus platyrhynchus) liver and muscle samples from August (2022) and October (2023) were analysed for toxic metals (Hg, Cd, and Pb) and PFAS (PFUnDA, PFTriDA, PFTDA, PFHxDA, PFPeS, PFHxS, PFOS, PFNS, PFDS, PFECHS, FOSAA, MeFOSAA, EtFOSAA, and NaDONA) concentrations to determine seasonal fluctuations in contaminant accumulation. We found a significant increase in both toxic metals and PFAS from August to October, which is when the Svalbard reindeer peak in weight. This may be explained by an extended foraging period (in October compared to August) following the annual winter fasting. The increased concentrations in October may also be explained by a dietary shift in vegetation with plant senescence at the end of summer. Overall, the PFAS profile indicated a predominant exposure to long-range transported PFAS (e.g., PFCAs). However, high concentrations of PFSAs indicate local pollution contributions too (e.g., firefighting foam). 

Hg was determined using DMA-80, PFAS were determined using an Xevo TQ-XS Triple Quadrupole Mass Spectrometer coupled with an ACQUITY UPLC system, and Cd and Pb were determined using an 8800 Triple Quadrupole inductively coupled plasma mass spectrometry (ICP-MS) system. A total of 41 PFAS were included in the analysis: PFBA, PFPeA, PFHxA, PFHpA, PFOA, PFNA, PFDA, PFUnDA, PFDoDA, PFTriDA, PFTDA, PFHxDA, PFOcDA PFBS, PFPeS, PFHxS, PFHpS, PFOS, PFNS, PFDS, PFDoDS, PFECHS, 4:2 FTS, 6:2 FTS, 8:2 FTS, and 10:2 FTS, FOSAA, MeFOSAA, EtFOSAA, PFOSA, MeFOSA, EtFOSA, MeFOSE, EtFOSE, GenX, NaDONA, 9Cl-PF3ONS, P37DMOA, SaMPAP and diSAMPAP. Only contaminants detected above the LOD in at least 25 % of the samples are reported. 

All samples were freeze-dried and homogenised prior to analysis. The water content of the samples was 70.1% in the liver and 72.0% in the muscle. The water content was used to calculate the wet weight concentrations of the samples. The concentrations are provided in both dry weight and wet weight. 

The provided data are as follows: age (years), weight (kg), contaminants (Hg, Se, Cd, Pb, PFUnDA, PFTriDA, PFTDA, PFHxDA, PFPeS, PFHxS, PFOS, PFNS, PFDS, PFECHS, FOSAA, MeFOSAA, EtFOSAA, and NaDONA) in ng/g. Values missing as a result of analytical errors are named "na", while values below the LOD were left blank.
DOI: 10.17632/y3nzn8pdmj
title: Disruption of chrna5 blunts aversion and adaptive transcriptomic responses to nicotine and alcohol

description: Data used to generate all main and supplementary figures in the publication ' Disruption of chrna5 blunts aversion and adaptive transcriptomic responses to nicotine and alcohol', iScience. Please see publication for full details on data collection and reproduction.

V.2. Update 16_1_25
- Updated heading names from dispensed concentration to mean chamber concentration so as to match corresponding figure legends for self-administration for zebrafish assay (SAZA) data. (e.g. 500uM -&gt; x̄25uM, 20% -&gt; x̄0.5%).
- Removed 'Mean normalized intensity (% of control region)' column from figure S6 data.
Data used to generate all main and supplementary figures in the publication ' Disruption of chrna5 blunts aversion and adaptive transcriptomic responses to nicotine and alcohol', iScience.
- Added references to figure sub-panels where applicable (e.g. Figure S4A)
DOI: 10.17632/y3nzn8pdmj.2
title: Disruption of chrna5 blunts aversion and adaptive transcriptomic responses to nicotine and alcohol

description: Data used to generate all main and supplementary figures in the publication ' Disruption of chrna5 blunts aversion and adaptive transcriptomic responses to nicotine and alcohol', iScience. Please see publication for full details on data collection and reproduction.

V.2. Update 16_1_25
- Updated heading names from dispensed concentration to mean chamber concentration so as to match corresponding figure legends for self-administration for zebrafish assay (SAZA) data. (e.g. 500uM -&gt; x̄25uM, 20% -&gt; x̄0.5%).
- Removed 'Mean normalized intensity (% of control region)' column from figure S6 data.
Data used to generate all main and supplementary figures in the publication ' Disruption of chrna5 blunts aversion and adaptive transcriptomic responses to nicotine and alcohol', iScience.
- Added references to figure sub-panels where applicable (e.g. Figure S4A)
DOI: 10.17632/gshzc6rd7j
title: Directions and Trends in Citizenship Literacy Research in Education: A Systematic Literature Review

description: Directions and Trends in Citizenship Literacy Research in Education: A Systematic Literature Review
DOI: 10.17632/gshzc6rd7j.1
title: Directions and Trends in Citizenship Literacy Research in Education: A Systematic Literature Review

description: Directions and Trends in Citizenship Literacy Research in Education: A Systematic Literature Review