cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.7784976
title: Plasticity of neuronal dynamics in the lateral habenula for cue-punishment associative learning.

description: The brain’s ability to associate threats with external stimuli is vital to execute essential behaviours including avoidance. Disruption of this process contributes instead to the emergence of pathological traits which are common in addiction and depression. However, the mechanisms and neural dynamics at the single-cell resolution underlying the encoding of associative learning remain elusive. Here, employing a Pavlovian discrimination task in mice we investigate how neuronal populations in the lateral habenula (LHb), a subcortical nucleus whose excitation underlies negative affect, encode the association between conditioned stimuli and a punishment (unconditioned stimulus).
DOI: 10.14473/csda/ionqlg/dpllqk
title: K01_V2109_jihocesky.pdf

description: :unav
DOI: 10.14473/csda/ionqlg/gjk8xr
title: K08_V2109_pardubický.pdf

description: :unav
DOI: 10.14473/csda/ionqlg/besph2
title: PR01_V2109_Důvěra ústavním institucím v září říjnu 2021.pdf

description: :unav
DOI: 10.14473/csda/ionqlg/julu6k
title: K11_V2109_stredocesky.pdf

description: :unav
DOI: 10.14473/csda/ionqlg/ebiko1
title: TI02_V2109.pdf

description: :unav
DOI: 10.14473/csda/ionqlg/gfyoy9
title: TI_V2109.pdf

description: :unav
DOI: 10.14473/csda/ionqlg/gisi63
title: K03_V2109_karlovarský.pdf

description: :unav
DOI: 10.14473/csda/ionqlg/s69prt
title: K14_V2109_zlinsky.pdf

description: :unav
DOI: 10.14473/csda/ionqlg/lgnhqc
title: D_V2109.pdf

description: :unav
DOI: 10.14473/csda/ionqlg/xobfrw
title: K06_V2109_moravskoslezský.pdf

description: :unav
DOI: 10.14473/csda/ionqlg/ywyahb
title: K12_V2109_ustecky.pdf

description: :unav
DOI: 10.14473/csda/ionqlg/pfjszz
title: NS_2109_DataFile_FINAL.tab

description: :unav
DOI: 10.14473/csda/ionqlg/4j5ib9
title: K05_V2109_liberecky.pdf

description: :unav
DOI: 10.14473/csda/ionqlg/81vuka
title: PR02_V2109_Občané o vývoji situace v Afghánistánu – září říjen 2021.pdf

description: :unav
DOI: 10.14473/csda/ionqlg/hjz3gn
title: K04_V2109_královéhradecký.pdf

description: :unav
DOI: 10.14473/csda/ionqlg/jprdoz
title: K13_V2109_vysocina.pdf

description: :unav
DOI: 10.14473/csda/ionqlg/gnuoxu
title: K02_V2109_jihomoravsky.pdf

description: :unav
DOI: 10.14473/csda/ionqlg/jk78k8
title: K09_V2109_plzeňský.pdf

description: :unav
DOI: 10.14473/csda/ionqlg/ykoauq
title: OM_V2109.pdf

description: :unav
DOI: 10.14473/csda/ionqlg/gskziw
title: K07_V2109_olomoucký.pdf

description: :unav
DOI: 10.14473/csda/ionqlg/i78jx9
title: K10_V2109_praha.pdf

description: :unav
DOI: 10.34740/kaggle/dsv/6071981
title: Global Genomic Neurofibromatosis Neoplasia
DOI: 10.5281/zenodo.8108659
title: cGAN model data

description: cGAN MODEL DATA.
DOI: 10.5281/zenodo.8108658
title: cGAN model data

description: cGAN MODEL DATA.
DOI: 10.4121/07711969-6e9a-4944-9132-8cdc005ee6a4.v1
title: Data underlying the publication: "Optical observations find high brightness of the BlueWalker 3 satellite"

description: This dataset contains the original observational video files (AAV format) as well as the resulting astrometrical and photometric data from observations over Sept 2022-Apr 2023 of the experimental Bluewalker 3 satellite (2022-111AL), observational data that are included in the paper "Optical observations find high brightness of the BlueWalker 3 satellite". They were obtained from Leiden, NL, with a WATEC 902H2 camera and 1.2/50 mm lens. They are part of a larger multi-institute dataset used to study the brightness characteristics and behaviour of the Bluewalker satellite and the general accuracy of orbital elements for this satellite, with an eye on characterizing the interference of this satellite (and future satellites in this class) with astronomical observations, and how to mitigate this.
DOI: 10.14473/csda/x70frh/6ckdef
title: PR05_V2108 Důvěra k vybraným institucím veřejného života – srpen_září 2021.pdf

description: :unav
DOI: 10.14473/csda/x70frh/xbfhmg
title: PR01_V2108 Názor na zadlužení obyvatel a státu – srpen_září 2021.pdf

description: :unav
DOI: 10.14473/csda/x70frh/jyfyti
title: K13_V2108_vysočina.pdf

description: :unav
DOI: 10.14473/csda/x70frh/4arwj3
title: TI_V2108.pdf

description: :unav
DOI: 10.14473/csda/x70frh/nmmnpa
title: K07_V2108_olomoucký.pdf

description: :unav
DOI: 10.14473/csda/x70frh/mtss5m
title: K09_V2108_plzensky.pdf

description: :unav
DOI: 10.14473/csda/x70frh/y4w5ka
title: PR04_V2108 Hodnocení vlády Andreje Babiše – srpen_září 2021.pdf

description: :unav
DOI: 10.14473/csda/x70frh/0lfb7n
title: K01_V2108_jihocesky.pdf

description: :unav
DOI: 10.14473/csda/x70frh/bevj5x
title: PR03_V2108 Česká veřejnost o fungování demokracie a nedemokratických alternativách politického systému – srpen_září 2021.pdf

description: :unav
DOI: 10.14473/csda/x70frh/5hi7vm
title: K10_V2108_praha.pdf

description: :unav
DOI: 10.14473/csda/x70frh/qdpip8
title: K05_V2108_liberecký.pdf

description: :unav
DOI: 10.14473/csda/x70frh/jxpdov
title: K06_V2108_moravskoslezský.pdf

description: :unav
DOI: 10.14473/csda/x70frh/v7oxh5
title: D_V2108.pdf

description: :unav
DOI: 10.14473/csda/x70frh/ay8yji
title: K04_V2108_královéhradecký.pdf

description: :unav
DOI: 10.14473/csda/x70frh/wbftqu
title: K03_V2108_karlovarský.pdf

description: :unav
DOI: 10.14473/csda/x70frh/ajxbfq
title: PR02_V2108 Jak jsou domácnosti zatíženy půjčkami – srpen_září 2021.pdf

description: :unav
DOI: 10.14473/csda/x70frh/kzfgq9
title: TI02_V2108.pdf

description: :unav
DOI: 10.14473/csda/x70frh/p1lntq
title: K08_V2108_pardubický.pdf

description: :unav
DOI: 10.14473/csda/x70frh/vuxwz0
title: K02_V2108_jihomoravsky.pdf

description: :unav
DOI: 10.14473/csda/x70frh/ba1ca5
title: K11_V2108_středočeský.pdf

description: :unav
DOI: 10.14473/csda/x70frh/jcgaff
title: OM_V2108.pdf

description: :unav
DOI: 10.14473/csda/x70frh/l4y8fm
title: PR06_V2108 Image politických stran – srpen_září 2021.pdf

description: :unav
DOI: 10.14473/csda/x70frh/swrggr
title: NS_2108_DataFile-FINAL_spss_7.0._width_corrected.tab

description: :unav
DOI: 10.14473/csda/x70frh/j2gnkz
title: K14_V2108_zlínský.pdf

description: :unav
DOI: 10.14473/csda/x70frh/t2pevm
title: K12_V2108_ústecký.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/9xmfn8
title: PR10__V2106.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/gqqcvf
title: PR15_V2106.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/4k8kdx
title: K_V2106.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/ocyprx
title: TI_V2106.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/mhobqn
title: PR13__V2106.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/d1adxz
title: OM_V2106.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/8ipplm
title: PR03_V2106.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/u5vyap
title: TI02_V2106.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/vcn0hd
title: PR06_V2106.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/cckuya
title: PR02_V2106.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/noszpx
title: PR07_V2106.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/cdhle3
title: D_V2106.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/f5tnep
title: PR11_V2106.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/nxzyqm
title: PR08_V2106.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/nu1vmg
title: PR09_V2106.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/mqgkmy
title: PR04_V2106.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/1drbqj
title: PR12_V2106.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/uywimu
title: PR05_V2106.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/zz8s6q
title: PR01_V2106.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/vt2syb
title: PR14_V2106.pdf

description: :unav
DOI: 10.14473/csda/bfhzrw/f1poci
title: NS_2106_DataFile-Final-2_FINALNI.tab

description: :unav
DOI: 10.14473/csda/bfhzrw/hzdago
title: PR16_V2106.pdf

description: :unav
DOI: 10.5281/zenodo.8108701
title: VICTRE Simulated Tomosynthesis Projections

description: The dataset was simulated using the VICTRE<sup>1</sup> pipeline and contains two sets of 259 raw-projections, each from a different phantom. The first set of projections has an equal dose for all projections. The dose of the second set follows data from the Malmö Breast Tomosynthesis Trial<sup>2</sup>. 1, Evaluation of Digital Breast Tomosynthesis as Replacement of Full-Field Digital Mammography Using an In Silico Imaging Trial.” Aldo Badano, Ph. D., Christian G. Graff, Ph. D., Andreu Badal, Ph. D., Diksha Sharma, M. Sc., Rongping Zeng, Ph. D., Frank W. Samuelson, Ph. D., Stephen Glick, Ph. D., and Kyle J. Myers, Ph. D. <em>JAMA Network Open. 2018;1(7):e185474;</em> doi:10.1001/jamanetworkopen.2018.5474. 2, Victor Dahlblom, Magnus Dustler, and Sophia Zackrisson (2019) Mammograms from cancer screening doi:10.23698/aida/mbtst-dm
DOI: 10.5281/zenodo.8108700
title: VICTRE Simulated Tomosynthesis Projections

description: The dataset was simulated using the VICTRE<sup>1</sup> pipeline and contains two sets of 259 raw-projections, each from a different phantom. The first set of projections has an equal dose for all projections. The dose of the second set follows data from the Malmö Breast Tomosynthesis Trial<sup>2</sup>. 1, Evaluation of Digital Breast Tomosynthesis as Replacement of Full-Field Digital Mammography Using an In Silico Imaging Trial.” Aldo Badano, Ph. D., Christian G. Graff, Ph. D., Andreu Badal, Ph. D., Diksha Sharma, M. Sc., Rongping Zeng, Ph. D., Frank W. Samuelson, Ph. D., Stephen Glick, Ph. D., and Kyle J. Myers, Ph. D. <em>JAMA Network Open. 2018;1(7):e185474;</em> doi:10.1001/jamanetworkopen.2018.5474. 2, Victor Dahlblom, Magnus Dustler, and Sophia Zackrisson (2019) Mammograms from cancer screening doi:10.23698/aida/mbtst-dm
DOI: 10.5281/zenodo.8108745
title: Dataset Forest@Risk

description: This report documents the collection of forest disturbance datasets for the Forest@Risk project. Here a brief description of the project: <em>European forests provide a set of fundamental services that contribute to climate mitigation and human well-being. On the other hand, forests are vulnerable systems because the long life-span of trees limits the possibility of a rapid adaptation to drastic environmental changes. Climate-driven hazards on forests, such as drought, wildfire and insect outbreaks, are expected to rise drastically in view of global warming. As a result, key forest services, such as carbon sequestration and supply of wood products, could be seriously affected in the near future. Despite the relevance and urgency of the issue, little is known about the upcoming risks of multiple climate-related hazards on European forests. To fill this knowledge gap we aim to investigate the evolution of forest disturbances under various climate scenarios. For this scope we will model the long-term changes in species composition, whereas forest vulnerability will be assessed with satellite observations and records of disturbances. The integration of these elements will produce a range of plausible risk estimates to support the definition of effective adaptation strategies, with the goal of increasing the resilience and long-term stability of these fundamental elements of the European landscape. </em> In order to investigate the vulnerability of forest to climate change, we have collected data of forest disturbances that occurred in Europe and US over the 2000-2017 period. The areas of interests are: 1) US, and 2) Europe. The US are included in the study because the abundance of data of forest disturbance due to insect outbreaks compared to EU. The number of EU records is abysmal compared to the US. The period of study is 2000 – 2017. In this way we can merge forest disturbance information with remote sensing imagery. From 2000 onwards there are systematic satellite acquisitions over Europe and US, whereas before the data availability (in terms of both spatial and temporal resolution) does not allow an accurate study of forest disturbance dynamics. The forest disturbance dataset consists <strong>in 3 different archives</strong>: 1) USDA (forest disturbance across US) 2) EFFIS (European forest fires) 3) WIND (European windthrown dataset) and <strong>ancillary information</strong> from: 1) ESA Globcover (land cover) 2) Vegetation Optical Depth (VOD, a proxy for biomass) 3) Hansen maps of deforestation 4) Koppen Geiger Climate Classification 5) Biomass data 6) Leaf Area Index (LAI) from satellite Other relevant documents are in the annex folder. <br>
DOI: 10.5281/zenodo.8108744
title: Dataset Forest@Risk

description: This report documents the collection of forest disturbance datasets for the Forest@Risk project. Here a brief description of the project: <em>European forests provide a set of fundamental services that contribute to climate mitigation and human well-being. On the other hand, forests are vulnerable systems because the long life-span of trees limits the possibility of a rapid adaptation to drastic environmental changes. Climate-driven hazards on forests, such as drought, wildfire and insect outbreaks, are expected to rise drastically in view of global warming. As a result, key forest services, such as carbon sequestration and supply of wood products, could be seriously affected in the near future. Despite the relevance and urgency of the issue, little is known about the upcoming risks of multiple climate-related hazards on European forests. To fill this knowledge gap we aim to investigate the evolution of forest disturbances under various climate scenarios. For this scope we will model the long-term changes in species composition, whereas forest vulnerability will be assessed with satellite observations and records of disturbances. The integration of these elements will produce a range of plausible risk estimates to support the definition of effective adaptation strategies, with the goal of increasing the resilience and long-term stability of these fundamental elements of the European landscape. </em> In order to investigate the vulnerability of forest to climate change, we have collected data of forest disturbances that occurred in Europe and US over the 2000-2017 period. The areas of interests are: 1) US, and 2) Europe. The US are included in the study because the abundance of data of forest disturbance due to insect outbreaks compared to EU. The number of EU records is abysmal compared to the US. The period of study is 2000 – 2017. In this way we can merge forest disturbance information with remote sensing imagery. From 2000 onwards there are systematic satellite acquisitions over Europe and US, whereas before the data availability (in terms of both spatial and temporal resolution) does not allow an accurate study of forest disturbance dynamics. The forest disturbance dataset consists <strong>in 3 different archives</strong>: 1) USDA (forest disturbance across US) 2) EFFIS (European forest fires) 3) WIND (European windthrown dataset) and <strong>ancillary information</strong> from: 1) ESA Globcover (land cover) 2) Vegetation Optical Depth (VOD, a proxy for biomass) 3) Hansen maps of deforestation 4) Koppen Geiger Climate Classification 5) Biomass data 6) Leaf Area Index (LAI) from satellite Other relevant documents are in the annex folder. <br>
DOI: 10.5281/zenodo.8108184
title: Intelligent approach for the rational use of a shared resource using blockchain.

description: This dataset was created in the <em>Intelligent approach for the rational use of a shared resource using blockchain</em> dissertation of Federal University of Technology - Paraná (UTFPR), campus Curitiba, by Evandro Sestrem supervised by Prof. Marco Aurélio Wehrmeister and cosupervised by Prof. Alécio Binotto.
DOI: 10.5281/zenodo.8108185
title: Intelligent approach for the rational use of a shared resource using blockchain.

description: This dataset was created in the <em>Intelligent approach for the rational use of a shared resource using blockchain</em> dissertation of Federal University of Technology - Paraná (UTFPR), campus Curitiba, by Evandro Sestrem supervised by Prof. Marco Aurélio Wehrmeister and cosupervised by Prof. Alécio Binotto.
DOI: 10.5281/zenodo.7585219
title: RTI simulated imagery - Coin-like object with and without surface markings

description: A set of simulated reflectance transformation imaging (RTI) acquisitions using the 3D model of a coin-like object. One set is simulated with the base model and the other is with some markings created on the surface. The images were simulated using Blender. Each acquisitions contained the simulated RGB images as well as depth maps and normal maps computed by Blender using the 3D model. Also included are the .blend files used for the simulations which include the 3D models. There is also a .lp file which describes the light positions used.
DOI: 10.5281/zenodo.7585220
title: RTI simulated imagery - Coin-like object with and without surface markings

description: A set of simulated reflectance transformation imaging (RTI) acquisitions using the 3D model of a coin-like object. One set is simulated with the base model and the other is with some markings created on the surface. The images were simulated using Blender. Each acquisitions contained the simulated RGB images as well as depth maps and normal maps computed by Blender using the 3D model. Also included are the .blend files used for the simulations which include the 3D models. There is also a .lp file which describes the light positions used.
DOI: 10.5281/zenodo.7584854
title: SFF-RTI simulated imagery - Statue du parc d'Austerlitz

description: A set of simulated image acquisitions using the 3D model of a statue hosted on Sketchfab by `Archeomatique` (Link: https://skfb.ly/o6uVZ). As such, the 3D model itself cannot be made open-access. The images were simulated using Blender version 3.3.1. Each acquisition contains the simulated RGB images as well as depth maps and normal maps computed by Blender using the 3D model. There also exists a folder with output processed using shape from focus (SFF) and SFF-RTI, a method proposed in a to-be-published journal paper. A CSV is also included with computed statistics for each acquisition. The acquisitions contained within this zip file are organized into: <strong>Ground truth</strong> - Ground truth images without any variation in light position. Also simulated without an aperture so that there is no simulated optical blurring. <strong>SFF </strong>- Acquisitions to be used with the shape from focus method. <strong>SFF-RTI</strong> - Acquisitions that combine the focus variation from shape from focus with the varying light position using in multi-light imaging methods such as photometric stereo and reflectance transformation imaging.
DOI: 10.5281/zenodo.7584855
title: SFF-RTI simulated imagery - Statue du parc d'Austerlitz

description: A set of simulated image acquisitions using the 3D model of a statue hosted on Sketchfab by `Archeomatique` (Link: https://skfb.ly/o6uVZ). As such, the 3D model itself cannot be made open-access. The images were simulated using Blender version 3.3.1. Each acquisition contains the simulated RGB images as well as depth maps and normal maps computed by Blender using the 3D model. There also exists a folder with output processed using shape from focus (SFF) and SFF-RTI, a method proposed in a to-be-published journal paper. A CSV is also included with computed statistics for each acquisition. The acquisitions contained within this zip file are organized into: <strong>Ground truth</strong> - Ground truth images without any variation in light position. Also simulated without an aperture so that there is no simulated optical blurring. <strong>SFF </strong>- Acquisitions to be used with the shape from focus method. <strong>SFF-RTI</strong> - Acquisitions that combine the focus variation from shape from focus with the varying light position using in multi-light imaging methods such as photometric stereo and reflectance transformation imaging.
DOI: 10.6084/m9.figshare.23617806
title: <strong>Isolated and Accompanied Lacrimal Gland Involvement with Idiopathic Orbital Inflammation Patients Excel</strong>

description: <strong>Isolated and Accompanied Lacrimal Gland Involvement with Idiopathic Orbital Inflammation Patients Excel</strong>
DOI: 10.6084/m9.figshare.23617806.v1
title: <strong>Isolated and Accompanied Lacrimal Gland Involvement with Idiopathic Orbital Inflammation Patients Excel</strong>

description: <strong>Isolated and Accompanied Lacrimal Gland Involvement with Idiopathic Orbital Inflammation Patients Excel</strong>
DOI: 10.18430/m3cp4r
title: X-ray diffraction data for the crystal structure of a RNA binding domain of a U2 small nuclear ribonucleoprotein auxiliary factor 2 (U2AF) from mouse at 2.15 A resolution (4Z2X)
DOI: 10.18430/m3dk5d
title: X-ray diffraction data for the crystal structure of a duf4847 family protein (BVU_2626) from Bacteroides vulgatus ATCC 8482 at 1.00 A resolution (4ZGF)
DOI: 10.18430/m3hc71
title: X-ray diffraction data for the crystal structure of a DUF1329 family protein (DESPIG_00262) from Desulfovibrio piger ATCC 29098 at 1.75 A resolution (4Z48)
DOI: 10.18430/m3p305
title: X-ray diffraction data for the crystal structure of an exotoxin 6 (SAV0422) from Staphylococcus aureus subsp. aureus Mu50 at 2.25 A resolution (4ZYS)
DOI: 10.18430/m3vp43
title: X-ray diffraction data for the crystal structure of a Putative Acyl-CoA ligase (BT_0428) from Bacteroides thetaiotaomicron VPI-5482 at 2.41 A resolution (4RVO)
DOI: 10.18430/m3wk5r
title: X-ray diffraction data for the crystal structure of a thioredoxin-like protein (BACCAC_02376) from Bacteroides caccae ATCC 43185 at 1.90 A resolution (4YOD)
DOI: 10.18430/m34599
title: X-ray diffraction data for the crystal structure of a putative adhesin (BACEGG_01763) from Bacteroides eggerthii DSM 20697 at 2.20 A resolution (4YGU)
DOI: 10.18430/m3530h
title: X-ray diffraction data for the crystal structure of a nuclear receptor binding factor 2 MIT domain (NRBF2) from Homo sapiens at 1.50 A resolution (4ZEY)
DOI: 10.18430/m3jc7b
title: X-ray diffraction data for the crystal structure of a putative alpha-L-fucosidase (BACOVA_04357) from Bacteroides ovatus ATCC 8483 at 1.59 A resolution (4ZRX)
DOI: 10.18430/m3n30v
title: X-ray diffraction data for the crystal structure of a DUF3829 family protein (BVU_3067) from Bacteroides vulgatus ATCC 8482 at 1.80 A resolution (4YJW)
DOI: 10.18430/m3rw2g
title: X-ray diffraction data for the crystal structure of a sensory box/GGDEF family protein (CC_0091) from Caulobacter crescentus CB15 at 1.40 A resolution (PSI Community Target, Shapiro) (4YME)
DOI: 10.18430/m3sw2s
title: X-ray diffraction data for the crystal structure of an uncharacterized protein (PARMER_03598) from Parabacteroides merdae ATCC 43184 at 1.50 A resolution (5BMT)
DOI: 10.6073/pasta/97df2ab6fbee416efbcaf59017a73a9b
title: Mass and Chemistry of Organic Horizons and Surface Mineral Soils 
			on Watershed 6 at the Hubbard Brook Experimental Forest, 1976 - present
DOI: 10.6073/pasta/20c2eaf1b1c70304b5e427f6abc746cc
title: Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra nitrogen and phosphorus fertilization simulation
DOI: 10.6073/pasta/581c62bd6b4c91b16116ccfe5fc35b3e
title: Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra nitrogen fertilized simulation
DOI: 10.6073/pasta/826a10115a88d854a58d62d5a5597780
title: Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra control simulation
DOI: 10.6073/pasta/826cc94199a28a8f8926b88dc00f5dab
title: Marsh vegetation cover data from quadrats along transects through two hayed and two reference sites near Stackyard Rd, Rowley, MA
DOI: 10.6073/pasta/8458d97cbd3ad85ffda70e757aa49a9e
title: Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra fertilized greenhouse simulation
DOI: 10.6073/pasta/fc6970640ea2d604f1a7f922db84d674
title: Long term response of arctic tussock tundra to thermal erosion features: A modeling analysis. Tussock tundra greenhouse simulation