cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.2ewhtm
title: Occurrence Download

description: A dataset listing the 29 species recorded in GBIF matching the query:
{
 "and" : [
 "GadmGid is USA.14_1",
 "OccurrenceStatus is Present",
 "TaxonKey is Turdidae"
 ]
}

 The dataset's 29 records were derived from 50 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030455-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25810/e48e-fs57
title: FIRED Armenia Nov 2000 - July 2024

description: This is event-level polygons for the fire event delineation (FIRED) product for ARMENIA from November 2000  to July 2024. It is derived from the MODIS MCD64A1 burned area product (see https://lpdaac.usgs.gov/products/mcd64a1v061/ for more details). The MCD64A1 is a monthly raster grid of estimated burned dates. Firedpy (https://github.com/earthlab/firedpy) is an algorithm that converts these rasters into events by stacking the entire time series into a spatial-temporal data cube, then uses an algorithm to assign event identification numbers to pixels that fit into the same 3-dimensional spatial temporal window. This particular dataset was created using a spatial parameter of 1 pixels and 5 days. Daily polygons are included and the event identification numbers are the same for both files, but the event-level product has only single polygons for each entire event, while the daily product has separate polygons for each date per event. See the associated paper for more details on the methods and more:

Balch, J.K.; St. Denis, L.A.; Mahood, A.L.; Mietkiewicz, N.P.; Williams, T.M.; McGlinchy, J.; Cook, M.C. FIRED (Fire Events Delineation): An Open, Flexible Algorithm and Database of US Fire Events Derived from the MODIS Burned Area Product (2001–2019). Remote Sens. 2020, 12, 3498. https://doi.org/10.3390/rs12213498
DOI: 10.15468/dl.pweyqq
title: Occurrence Download

description: A dataset containing 50 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((95.90392 64.23851,87.88885 64.84239,83.46137 63.19304,81.37712 61.1701,79.3797 56.33324,81.46581 51.72183,84.6261 50.25844,89.1515 48.64755,95.79412 49.74551,97.82534 50.84346,98.9233 52.21591,102.21716 54.02753,104.08368 56.38814,102.16227 60.99955,101.2839 62.53668,95.90392 64.23851))",
 "TaxonKey is Neckera Hedw."
 ]
}

 The dataset includes 50 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030485-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7488/401fb629-2271-4a95-b3c1-365129b39751
title: Exploring understandings of publics and practices of public involvement for digital health governance in different local UK settings.

description: ## Access ##
This dataset is held in the Edinburgh DataVault, directly accessible only to authorised University of Edinburgh staff. External users may request access to a copy of the data by contacting the Principal Investigator, Contact Person or Data Manager named on this page. Requests for access will not necessarily be granted. University of Edinburgh users who wish to have direct access should consult the information about retrieving data from the DataVault at: https://www.ed.ac.uk/is/research-support/datavault.
description: Data in support of doctoral thesis titled "The construction of publics: an examination of how visions of digital health technologies shape publics' potential roles in governance practices of such technologies". This study constitutes the third approach of the wider doctoral research and aims at exploring how current policy discourses around DH technologies may influence how publics participate in DH governance processes. 
To achieve such aims, the research objectives are:
• to develop an in-depth understanding of how PI activities are design and implemented in a small number of case studies.
• to acquire in-depth knowledge about discourses, visions and other factors that may influence PI practitioners and DH governance experts' conceptualisation and practice of PI.
• to examine how local discourses and policy implementations of DH technologies present and use publics and engagement activities within governance processes.
• to understand the tensions that may exists between high-level conceptualisations of publics and PI driven by dominant discourses and visions of DH technologies.

Examining visions and imaginaries of DH technologies is important because it may provide rich insights into how these discourses influence how publics participate in governance processes of DH technologies. Existing literature has highlighted how perceptions of publics underpinned by knowledge deficit rationales can lead to the design and implementation of PI exercises as means to gain public trust and support. The analysis of how visions and imaginaries of DH technologies shape perceptions of publics can help to better understand how PI activities are taking place in the field of DH governance. Hence, it may help suggests basis for transformation and improvement of DH governance policies in a way that are more capable of incorporating the perspectives of publics
DOI: 10.15468/dl.e6s279
title: Occurrence Download

description: A dataset containing 205391 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is EOD – eBird Observation Dataset",
 "Geometry POLYGON((-8.77004 37.30185,-7.39193 37.35753,-7.28749 41.24841,-8.84202 41.07903,-8.77004 37.30185))",
 "HasGeospatialIssue is false",
 "Year 2000-2010"
 ]
}

 The dataset includes 205391 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030467-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25318/3710013601-fra
title: Diplomation des étudiants inscrits dans un programme menant à un certificat de formation technique ou professionnelle, au Canada, selon les caractéristiques de l’étudiant

description: Taux de diplomation, nombre moyen d'années prises pour compléter le programme et nombre d'étudiants dans la cohorte de nouveaux inscrits pour les étudiants inscrits dans un programme menant à un certificat de niveau collégial, au Canada, selon les caractéristiques démographiques.
DOI: 10.15468/dl.cwyew5
title: Occurrence Download

description: A dataset containing 9607 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "OccurrenceStatus is Present",
 "TaxonKey is Vultur gryphus Linnaeus, 1758"
 ]
}

 The dataset includes 9607 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030488-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.1136081_d5
title: Ex1R07 C from Synaptic molecular imaging in spared and deprived columns of mouse barrel cortex with array tomography.

description: This data represents 3 repeated staining and stripping (elution) cycles of an array tomography tissue ribbon from mouse barrel cortex with antibodies against synaptic molecules gephyrin and parvalbumin as well as a DAPI nuclear stain. Included are images from 16 consecutive serial sections aligned to produce a high-resolution volumetric reconstruction of each stain.
DOI: 10.6084/m9.figshare.1136081_d4
title: Ex1R02 A from Synaptic molecular imaging in spared and deprived columns of mouse barrel cortex with array tomography.

description: This data represents 3 repeated staining and stripping (elution) cycles of an array tomography tissue ribbon from mouse barrel cortex with antibodies against synaptic molecules Synapsin1, vGluT2, and NR2B (GluN2B) as well as a DAPI nuclear stain. Included are four discontinuous but approximately aligned sections from the ribbon imaged in three sequential imaging sessions.
DOI: 10.6084/m9.figshare.1136081_d3
title: Ex1R07 B from Synaptic molecular imaging in spared and deprived columns of mouse barrel cortex with array tomography.

description: This data represents 3 repeated staining and stripping (elution) cycles of an array tomography tissue ribbon from mouse barrel cortex with antibodies against synaptic molecules GAD2, vGAT as well as a DAPI nuclear stain. Included are images from 6 consecutive serial sections aligned to produce a high-resolution volumetric reconstruction of each stain.
DOI: 10.6084/m9.figshare.1019859_d6
title: Achilles_QC_v2.4.3.shRNA.table.txt

description: Per shRNA quality file from the ATARiS gene summarization of the shRNA data.
DOI: 10.6084/m9.figshare.1015506_d12
title: Clodia database Categories 1997-2013

description: Detailed information on the categories included in the time series of landing data from 1997-2013.
Clodia database. Database of Fishery Data from Chioggia, Northern Adriatic Sea.
DOI: 10.6084/m9.figshare.1015506_d9
title: Clodia database landing data 1945-2013

description: Landing data from 1945-2013, in kilograms, for each category included in the file Clodia database Categories 1945-2013.
Clodia database. Database of Fishery Data from Chioggia, Northern Adriatic Sea.
DOI: 10.6084/m9.figshare.1015506_d11
title: Clodia database Categories 1945-2013

description: Detailed information on the categories included in the time series of landing data from 1945-2013
Clodia database. Database of Fishery Data from Chioggia, Northern Adriatic Sea.
DOI: 10.6084/m9.figshare.853801_d10
title: SSI_NLDAS.zip

description: The Global Integrated Drought Monitoring and Prediction System (GIDMaPS) provides near real-time drought information based on multiple drought indicators and input data sets (http://drought.eng.uci.edu/). In this package, the folder names indicate the drought index and the source of data (INDEX_SOURCE). Index options are: 1-PSI: Multivariate Standardized Drought Index (MSDI) based on Precipitation (P) and Soil Moisture (S). 2-SSI: Standardized Soil Moisture Index 3-SPI: Standardized Precipitation Index. In each folder the files are named as INDEXYYYYMM.asc, where YYYY= year; MM= month, and INDEX = PSI, SSI, SPI.
<br>
GIDMaPS is presented in [Hao et al, 2014]. The deatails of MSDI, SSI and SPI are discussed in [Hao and AghaKouchak 2013a, 2013b]. GIDMaPS data has been used in [Damberg and AghaKouchak, 2013].
 
<strong>References</strong>
[1] Hao Z., AghaKouchak A., Nakhjiri N., Farahmand A., 2014, Global Integrated Drought Monitoring and Prediction System, Scientific Data, 1: 140001, doi: 10.1038/sdata.2014.1.
<br>
[2]  Hao Z., AghaKouchak A., 2013a, A Nonparametric Multivariate Multi-Index Drought Monitoring Framework,Journal of Hydrometeorology, doi:10.1175/JHM-D-12-0160.1.
<br>
[3]  Hao Z., AghaKouchak A., 2013b, Multivariate Standardized Drought Index: A Parametric Multi-Index Model,Advances in Water Resources, 57, 12-18, doi: 10.1016/j.advwatres.2013.03.009.
<br>
[4]  Damberg L., AghaKouchak A., 2013, Global Trends and Patterns of Droughts from Space, Theoretical and Applied Climatology, doi: 10.1007/s00704-013-1019-5. 
<br>
DOI: 10.6084/m9.figshare.853801_d3
title: PSI_NLDAS.zip

description: The Global Integrated Drought Monitoring and Prediction System (GIDMaPS) provides near real-time drought information based on multiple drought indicators and input data sets (http://drought.eng.uci.edu/). In this package, the folder names indicate the drought index and the source of data (INDEX_SOURCE). Index options are: 1-PSI: Multivariate Standardized Drought Index (MSDI) based on Precipitation (P) and Soil Moisture (S). 2-SSI: Standardized Soil Moisture Index 3-SPI: Standardized Precipitation Index. In each folder the files are named as INDEXYYYYMM.asc, where YYYY= year; MM= month, and INDEX = PSI, SSI, SPI.
<br>
GIDMaPS is presented in [Hao et al, 2014]. The deatails of MSDI, SSI and SPI are discussed in [Hao and AghaKouchak 2013a, 2013b]. GIDMaPS data has been used in [Damberg and AghaKouchak, 2013].
 
<strong>References</strong>
[1] Hao Z., AghaKouchak A., Nakhjiri N., Farahmand A., 2014, Global Integrated Drought Monitoring and Prediction System, Scientific Data, 1: 140001, doi: 10.1038/sdata.2014.1.
<br>
[2]  Hao Z., AghaKouchak A., 2013a, A Nonparametric Multivariate Multi-Index Drought Monitoring Framework,Journal of Hydrometeorology, doi:10.1175/JHM-D-12-0160.1.
<br>
[3]  Hao Z., AghaKouchak A., 2013b, Multivariate Standardized Drought Index: A Parametric Multi-Index Model,Advances in Water Resources, 57, 12-18, doi: 10.1016/j.advwatres.2013.03.009.
<br>
[4]  Damberg L., AghaKouchak A., 2013, Global Trends and Patterns of Droughts from Space, Theoretical and Applied Climatology, doi: 10.1007/s00704-013-1019-5. 
<br>
DOI: 10.6084/m9.figshare.853801_d4
title: SPI_GDCDR.zip

description: The Global Integrated Drought Monitoring and Prediction System (GIDMaPS) provides near real-time drought information based on multiple drought indicators and input data sets (http://drought.eng.uci.edu/). In this package, the folder names indicate the drought index and the source of data (INDEX_SOURCE). Index options are: 1-PSI: Multivariate Standardized Drought Index (MSDI) based on Precipitation (P) and Soil Moisture (S). 2-SSI: Standardized Soil Moisture Index 3-SPI: Standardized Precipitation Index. In each folder the files are named as INDEXYYYYMM.asc, where YYYY= year; MM= month, and INDEX = PSI, SSI, SPI.
<br>
GIDMaPS is presented in [Hao et al, 2014]. The deatails of MSDI, SSI and SPI are discussed in [Hao and AghaKouchak 2013a, 2013b]. GIDMaPS data has been used in [Damberg and AghaKouchak, 2013].
 
<strong>References</strong>
[1] Hao Z., AghaKouchak A., Nakhjiri N., Farahmand A., 2014, Global Integrated Drought Monitoring and Prediction System, Scientific Data, 1: 140001, doi: 10.1038/sdata.2014.1.
<br>
[2]  Hao Z., AghaKouchak A., 2013a, A Nonparametric Multivariate Multi-Index Drought Monitoring Framework,Journal of Hydrometeorology, doi:10.1175/JHM-D-12-0160.1.
<br>
[3]  Hao Z., AghaKouchak A., 2013b, Multivariate Standardized Drought Index: A Parametric Multi-Index Model,Advances in Water Resources, 57, 12-18, doi: 10.1016/j.advwatres.2013.03.009.
<br>
[4]  Damberg L., AghaKouchak A., 2013, Global Trends and Patterns of Droughts from Space, Theoretical and Applied Climatology, doi: 10.1007/s00704-013-1019-5. 
<br>
DOI: 10.6084/m9.figshare.853801_d5
title: SPI_GLDAS.zip

description: The Global Integrated Drought Monitoring and Prediction System (GIDMaPS) provides near real-time drought information based on multiple drought indicators and input data sets (http://drought.eng.uci.edu/). In this package, the folder names indicate the drought index and the source of data (INDEX_SOURCE). Index options are: 1-PSI: Multivariate Standardized Drought Index (MSDI) based on Precipitation (P) and Soil Moisture (S). 2-SSI: Standardized Soil Moisture Index 3-SPI: Standardized Precipitation Index. In each folder the files are named as INDEXYYYYMM.asc, where YYYY= year; MM= month, and INDEX = PSI, SSI, SPI.
<br>
GIDMaPS is presented in [Hao et al, 2014]. The deatails of MSDI, SSI and SPI are discussed in [Hao and AghaKouchak 2013a, 2013b]. GIDMaPS data has been used in [Damberg and AghaKouchak, 2013].
 
<strong>References</strong>
[1] Hao Z., AghaKouchak A., Nakhjiri N., Farahmand A., 2014, Global Integrated Drought Monitoring and Prediction System, Scientific Data, 1: 140001, doi: 10.1038/sdata.2014.1.
<br>
[2]  Hao Z., AghaKouchak A., 2013a, A Nonparametric Multivariate Multi-Index Drought Monitoring Framework,Journal of Hydrometeorology, doi:10.1175/JHM-D-12-0160.1.
<br>
[3]  Hao Z., AghaKouchak A., 2013b, Multivariate Standardized Drought Index: A Parametric Multi-Index Model,Advances in Water Resources, 57, 12-18, doi: 10.1016/j.advwatres.2013.03.009.
<br>
[4]  Damberg L., AghaKouchak A., 2013, Global Trends and Patterns of Droughts from Space, Theoretical and Applied Climatology, doi: 10.1007/s00704-013-1019-5. 
<br>
DOI: 10.6084/m9.figshare.853801_d6
title: SPI_MERRA.zip

description: The Global Integrated Drought Monitoring and Prediction System (GIDMaPS) provides near real-time drought information based on multiple drought indicators and input data sets (http://drought.eng.uci.edu/). In this package, the folder names indicate the drought index and the source of data (INDEX_SOURCE). Index options are: 1-PSI: Multivariate Standardized Drought Index (MSDI) based on Precipitation (P) and Soil Moisture (S). 2-SSI: Standardized Soil Moisture Index 3-SPI: Standardized Precipitation Index. In each folder the files are named as INDEXYYYYMM.asc, where YYYY= year; MM= month, and INDEX = PSI, SSI, SPI.
<br>
GIDMaPS is presented in [Hao et al, 2014]. The deatails of MSDI, SSI and SPI are discussed in [Hao and AghaKouchak 2013a, 2013b]. GIDMaPS data has been used in [Damberg and AghaKouchak, 2013].
 
<strong>References</strong>
[1] Hao Z., AghaKouchak A., Nakhjiri N., Farahmand A., 2014, Global Integrated Drought Monitoring and Prediction System, Scientific Data, 1: 140001, doi: 10.1038/sdata.2014.1.
<br>
[2]  Hao Z., AghaKouchak A., 2013a, A Nonparametric Multivariate Multi-Index Drought Monitoring Framework,Journal of Hydrometeorology, doi:10.1175/JHM-D-12-0160.1.
<br>
[3]  Hao Z., AghaKouchak A., 2013b, Multivariate Standardized Drought Index: A Parametric Multi-Index Model,Advances in Water Resources, 57, 12-18, doi: 10.1016/j.advwatres.2013.03.009.
<br>
[4]  Damberg L., AghaKouchak A., 2013, Global Trends and Patterns of Droughts from Space, Theoretical and Applied Climatology, doi: 10.1007/s00704-013-1019-5. 
<br>
DOI: 10.6084/m9.figshare.1019859_d4
title: cBOTv8_sbsv3_allreps_log.gct

description: cBOTv8_sbsv3_allreps_log.gct is the raw normalized and logged read counts for the second group of cancer cell lines undergoing pooled shRNA screening.
DOI: 10.5281/zenodo.14393874
title: Prueba AA
DOI: 10.5281/zenodo.14393875
title: Prueba AA
DOI: 10.6084/m9.figshare.878253_d1
title: zenith_angle.zip

description: Zenith angle of the sun (degrees). Each netCDF file contains 24 layers of global extent, one for each hour of the day (starting at 0:00 hrs) for a given month of the year, at ~15km resolution.
 
 
Fileset Description:
The microclim dataset provides microclimate estimates of conditions above and below ground for each hour of the day for the middle day of each month based on a long-term average climatology. Details of this dataset are presented in [Kearney et al. 2014].
The dataset comprises a set of NetCDF files with one file per variable per month, each file comprising 24 layers (one for each hour of the day from 0:00 hrs to 23:00 hrs, so layer 13 is 12:00 midday) for the globe (852 rows, 2159 columns, latitudinal extents -58.57 to 83.43 degrees, longitudinal extents -180.00 to 180.00 degrees). For the naming convention, mon is month of the year (1 to 12, where 1 = Jan, 12 = Dec), shd is shade level in % (0, 25, 50, 75, 90, 100), and sub is substrate (soil, rock, sand).
To facilitate downloading the data, the NetCDF files are grouped into compressed (zipped) files, one per variable per shade and substrate type, each comprising all monthly values and, for the substrate temperatures, all depths. Note that not all variables are shade or substrate specific, specifically zenith angle, wind speeds, solar radiation, and 120 cm air temperature and relative humidity.
DOI: 10.6084/m9.figshare.878253_d2
title: wind_speed_ms_1cm.zip

description: Wind speed (m/s) at 1cm above ground. Each netCDF file contains 24 layers of global extent, one for each hour of the day (starting at 0:00 hrs) for a given month of the year, at ~15km resolution.
 
 
Fileset Description:
The microclim dataset provides microclimate estimates of conditions above and below ground for each hour of the day for the middle day of each month based on a long-term average climatology. Details of this dataset are presented in [Kearney et al. 2014].
The dataset comprises a set of NetCDF files with one file per variable per month, each file comprising 24 layers (one for each hour of the day from 0:00 hrs to 23:00 hrs, so layer 13 is 12:00 midday) for the globe (852 rows, 2159 columns, latitudinal extents -58.57 to 83.43 degrees, longitudinal extents -180.00 to 180.00 degrees). For the naming convention, mon is month of the year (1 to 12, where 1 = Jan, 12 = Dec), shd is shade level in % (0, 25, 50, 75, 90, 100), and sub is substrate (soil, rock, sand).
To facilitate downloading the data, the NetCDF files are grouped into compressed (zipped) files, one per variable per shade and substrate type, each comprising all monthly values and, for the substrate temperatures, all depths. Note that not all variables are shade or substrate specific, specifically zenith angle, wind speeds, solar radiation, and 120 cm air temperature and relative humidity.
DOI: 10.6084/m9.figshare.988749
title: Austrian Science Fund (FWF) Publication Cost Data 2013
DOI: 10.6084/m9.figshare.1029129
title: test
DOI: 10.6084/m9.figshare.1056323
title: Remote sensing, a tool for erosion study; A case study of Nekede (Imo State, Nigeria) and its environs
DOI: 10.6084/m9.figshare.1059263
title: The Saga of Babafats v1.0
DOI: 10.6084/m9.figshare.1112792
title: O universo da testagem psicolgica
DOI: 10.6084/m9.figshare.1233987
title: testing
DOI: 10.5281/zenodo.14388052
title: Genome Sequencing of Peanut from Pakistan
DOI: 10.5281/zenodo.14388053
title: Genome Sequencing of Peanut from Pakistan
DOI: 10.6084/m9.figshare.1047265
title: KEGGscape: a Cytoscape app for pathway data integration
DOI: 10.6084/m9.figshare.1084348
title: Test Article
DOI: 10.6084/m9990139
title: Science Communication & Social Media (Pt 2)
DOI: 10.6084/m9.figshare.947751
title: Mathematical Modelling of the Kidney - an update on ABI activities
DOI: 10.6084/m9.figshare.956289
title: #scholarAfrica: Enhancing the Visibility of Research. Tools and Strategies
DOI: 10.6084/m9.figshare.944611
title: Social Media for Research:  Making Twitter Work For You   - Language Of Access Worskhop
DOI: 10.6084/m9.figshare.942302
title: An interactive tool for exploring physiome models: introducing a python prototype
DOI: 10.6084/m9.figshare.1280880
title: Legal Study On The Protection Of Children In Social Network: Special Reference To Indian Law
DOI: 10.6084/m9.figshare.1280899
title: Managing Performance through Reward System
DOI: 10.6084/m9.figshare.1280887
title: Mate selection preferences among college Students in Bagalkot, Karnataka
DOI: 10.6084/m9.figshare.1280885
title: De-Constructing Decentralization and Devolution of Powers: Rethinking the Functionality of Local Government System in Nigeria.
DOI: 10.6084/m9.figshare.1280888
title: Assessment Maturity Model for Competency Mapping - A Talent Management Enabler
DOI: 10.6084/m9.figshare.1280883
title: The Politics of Issue-Based Political Campaign in Nigeria
DOI: 10.6084/m9.figshare.1280884
title: Effect to Analyze the Arab Spring for Political Change in the Middle East
DOI: 10.6084/m9.figshare.1280890
title: Postmodernist Genre in Science Fiction
DOI: 10.6084/m9.figshare.1280886
title: A study of Street Children in Kaduna Metropolis, Nigeria
DOI: 10.6084/m9.figshare.1280873
title: Effect of privatization on economy and its adverse effects on economy
DOI: 10.6084/m9.figshare.1280889
title: Translation of Present-Day Egyptian Slang into English
DOI: 10.6084/m9.figshare.1280870
title: Information Literacy Skills of Arts Subject Teachers in Lagos State Senior Secondary Schools Nigeria
DOI: 10.6084/m9.figshare.1280868
title: Millennium Development Goals (MDGs) in Africa: The Role of an Ethno-botanist (Part 1)
DOI: 10.6084/m9.figshare.1280872
title: The Influence of Counselling on Population and Economic Growth in Nigeria
DOI: 10.6084/m9.figshare.1280867
title: Effects of Yoga Training Aerobic Training and Detraining On Muscular Strength among College Boys
DOI: 10.6084/m9.figshare.1280871
title: Effect of privatization on fertilizer sector: (real world case study) (disinvestment in PAK Saudi fertilizer and its effect on FAUJI FERTILIZER COMPANY)
DOI: 10.6084/m9.figshare.1280869
title: Promotion of Unopposed Elections in Haryana Panchayats: A Visionary Approach